Relevant bibliographies by topics / Tool Condition Monitoring

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Tool Condition Monitoring'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 April 2022

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Journal articles on the topic "Tool Condition Monitoring"

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KUMAKURA, R., Y. KAKINUMA, T. ARAI, E. UCHISHIBA, M. MURAKAMI, T. SAGARA, and T. AOYAMA. "D004 Sensorless tool condition monitoring in buffing processes." Proceedings of International Conference on Leading Edge Manufacturing in 21st century : LEM21 2013.7 (2013): 463–68. http://dx.doi.org/10.1299/jsmelem.2013.7.463.

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Horváth, L., and B. Szabó. "Tool Condition Monitoring System." IFAC Proceedings Volumes 19, no. 13 (November 1986): 291–95. http://dx.doi.org/10.1016/s1474-6670(17)59556-7.

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GOLOVIN, V. I., and S. Yu RADCHENKO. "TOOL CONDITION MONITORING SYSTEM IN SERIAL PRODUCTION CONDITIONS." Fundamental and Applied Problems of Engineering and Technology 4, no. 2 (2020): 161–68. http://dx.doi.org/10.33979/2073-7408-2020-342-4-2-161-168.

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One of the most important tasks of serial and mass production is to maintain the continuity of the technological process in order to reduce equipment downtime and, as a result, the cost of production. One of the systems is the tool condition monitoring system. However, the solutions used today are complex software and hardware systems that are not available for most medium and small productions. The article proposes a system based on a comparative analysis of the applied tool with reference instances. The results of the analysis are sent to the decision-making system, which determines the feasibility of further use of the cutting tool for subsequent machining. An example of an experimental study of milling processing is given. The results obtained show the possibility and rationality of using this model to predict the state of the instrument.
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Axinte, Dragoş A., and Nabil Gindy. "Tool condition monitoring in broaching." Wear 254, no. 3-4 (February 2003): 370–82. http://dx.doi.org/10.1016/s0043-1648(03)00003-6.

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Jemielniak, Krzysztof. "Tool and process condition monitoring." Mechanik 90, no. 7 (July 10, 2017): 504–10. http://dx.doi.org/10.17814/mechanik.2017.7.64.

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Automatic tool condition monitoring is based on the measurements of physical phenomena which are correlated with this condition. There are numerous signal features (SFs) that can be extracted from the signal. As it is really not possible to predict which signal features will be useful in a particular case they should be automatically selected and combined into one tool condition estimation. This can be achieved by various artificial intelligence methods.
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Jemielniak, K. "Commercial Tool Condition Monitoring Systems." International Journal of Advanced Manufacturing Technology 15, no. 10 (September 1999): 711–21. http://dx.doi.org/10.1007/s001700050123.

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Visariya, Ramesh, Ronak Ruparel, and Rahul Yadav. "Review of Tool Condition Monitoring Methods." International Journal of Computer Applications 179, no. 37 (April 18, 2018): 29–32. http://dx.doi.org/10.5120/ijca2018916853.

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Ambhore, Nitin, Dinesh Kamble, Satish Chinchanikar, and Vishal Wayal. "Tool Condition Monitoring System: A Review." Materials Today: Proceedings 2, no. 4-5 (2015): 3419–28. http://dx.doi.org/10.1016/j.matpr.2015.07.317.

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Du, R. "Signal understanding and tool condition monitoring." Engineering Applications of Artificial Intelligence 12, no. 5 (October 1999): 585–97. http://dx.doi.org/10.1016/s0952-1976(99)00026-3.

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Holroyd, Trevor J. "Acoustic Emission — The Condition Monitoring Tool." Measurement and Control 34, no. 4 (May 2001): 115–16. http://dx.doi.org/10.1177/002029400103400409.

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Dissertations / Theses on the topic "Tool Condition Monitoring"

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Aitchison, David Robert. "Laser based cutting tool condition monitoring." Thesis, University of Hull, 1995. http://hydra.hull.ac.uk/resources/hull:3693.

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El, Siblani Ali. "Tool condition analysis and monitoring in cold rolling process." Thesis, KTH, Industriell produktion, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-41318.

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This research is about a costly problem in the automotive industry due to tool fracture during the splines cold rolling of steel shafts. The objective is to study the cause of this failure and propose solutions that can be implemented in the workshop.The writing starts with a brief introduction of the companies involved in shafts production and problem solving. It introduces the cold rolling process and its advantages on splines manufacturing, and it goes through relevant material and process characteristics that help to determine the cause of tool fracture.In order to understand the process failure and production flow, it has been necessary to build up an Ishikawa diagram with possible tool fracture causes. After collecting and analysing the data about the machine tool, cold rolling process and work-piece and rolling tool materials, tests and experiments have been done.It has been considered that there is a rolling tool fatigue that causes tool fracture. Beside tool fracture, two more problems with production flow instability and the right side rolling tool have been detected. Testing the material hardness of the work-piece has shown continuous hardness fluctuations from the supplier. Rolling tool misalignment has been measured by using a vernier caliper measurement device. Rolling tools material hardness analysis shows that tool is very hard and it is possible to use a tougher material which responds better to cyclic loads.Leax has tried to solve the problem by testing another lubrication and tool coatings. A modal analysis test has been performed in order to find the natural frequency of the work-piece which possibly may lead to vibration and over loading one of the rolling tools.The conclusion that has been reached is that main cause of fracture is rolling tool fatigue due to cyclic loads and it is important to use other rolling tool material. The other two detected problems, production flow instability and rigth side rolling tool fracture, should be considered as a part of the problem in order to significantly increase tools life and stabilize production flow rate.
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Seemuang, Nopparat. "Non-destructive evaluation and condition monitoring of tool wear." Thesis, University of Sheffield, 2016. http://etheses.whiterose.ac.uk/13392/.

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As tool wear is unavoidable, a tool condition monitoring system is an essential system to prevent machine tool downtime due to unnecessary tool replacement, tool breakage caused by using worn tools, and to reduce part rejections. Currently, multiple indirect sensing signals are commonly fused and used to detect tool wear to enhance the system reliability and generalisation. Many of the recently developed systems uses expensive sensing methods which are seemingly not suitable for real machining. Almost all of these monitoring systems were also developed in a laboratory control environment, resulting in lower performance if they are utilised in real machining operations. This thesis takes these discrepancies as motivation to investigate and develop low-cost based tool condition monitoring systems. The cost effective tool monitoring systems were developed from a non-destructive evaluation (NDE) method and a multiple sensor fusion approach in order to monitor tool wear of common machining processes (turning, drilling, and gear hobbing). First, Barkhausen noise technique, an off-line NDT method commonly used in the hardened case-depth evaluation, was used to evaluate the coating thickness of TiN and CrN layers on HSS cutting tools. The results confirm that this proposed measurement system can be successfully used to indicate between different coating thicknesses. Secondly, an on-line tool condition monitoring system based on multiple sensor fusion using a combination of inexpensive sensors (AE, microphone, and power monitoring system) was developed. Sensory features extracted from those sensors were trained by neural networks to obtain the tool wear prediction and tool wear state classification models. The system was successfully used to predict flank wear width and classify the tool wear states during a turning operation. Furthermore, a novel sensing feature extracted from cutting sound, named 'spindle noise', was first introduced in this study as this feature can successfully detect the excessive tool wear in turning and drilling or any other machining process which has a rotary spindle. The cost-effective systems proposed in this study can be utilised in small and medium sized manufacturing companies and will improve productivity and add more value to the manufacturing processes.
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Cooper, Clayton Alan. "Milling Tool Condition Monitoring Using Acoustic Signals and Machine Learning." Case Western Reserve University School of Graduate Studies / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=case1575539872711423.

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Wilcox, Anthony John. "The condition monitoring of press-working systems using ultrasonic Lamb waves." Thesis, Birmingham City University, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.386941.

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Zheng, Kougen. "Application of the Wigner distribution to monitoring cutting tool condition." Thesis, University of Warwick, 1992. http://wrap.warwick.ac.uk/56557/.

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This thesis is about the application of the Wigner distribution to cutting tool monitoring and control. After reviewing traditional methods, a new method is proposed. This is to regard the surface texture and geometric error of form of a machined workpiece as the fingerprint of a cutting process, to analyse it, and to extract cutting tool vibration information from it, which can then be used for cutting tool monitoring. In order to analyse the surface texture effectively, three analysing tools, i.e. the Fourier transform, the ambiguity function, the Wigner distribution (WD), are examined and compared with each other, and it is concluded that the WD is best able to analyse both stationary and nonstationary signals. Furthermore, computer simulation of both chirp signals and frequency modulated signals is then carried out, and it is shown that the WD can be used to extract useful parameters successively. In order to demonstrate the suitability of the WD for machine tool condi- tion monitoring, first cutting tool vibration are measured directly by two linear variable differential transformers mounted on the cutting tool, and then these measured data about vibration are used to verify those parameters extracted from the surface of the machined workpiece by the WD. It is found that • the extracted frequencies in both horizontal and vertical direction are within 10% of those measured, • the extracted amplitudes in both horizontal and vertical direction are highly correlated with those measured. This result confirms the feasibility of this technique. In spite of being an off-line process, this technique is simple, reliable, and can reveal the direct effect of cutting processes.
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Fu, Pan. "An intelligent cutting tool condition monitoring system for milling operation." Thesis, Southampton Solent University, 2000. http://ssudl.solent.ac.uk/1237/.

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A very important requirement of modern machining systems in an 'unmanned' factory is to change tools that have been subjected to wear or damage in time. The old tool change strategies are based on conservative estimates from the past tool wear data, hence tools can be replaced too early or too late. This can increase the production cost or endanger the quality of the products. An integrated tool condition monitoring system composed of multi-sensors, signal processing methodology and decision-making plans is a crucial requirement for automtic manufacturing processes. An intelligent tool condition monitoring system for milling operations will be introduced in this report. The system is composed of four kinks of sensors, signal transforming and sampling apparatus and a microcomputer. By using intelligent pattern recognition techniques, different sensor signals are combined and the tool wear states can be recognised reliably. The efficient and effective orthogonal experimental design procedure is applied to comprehensively verify the monitoring system in a limited number of test runs. 50 signal features are extracted from time and frequency domain and they are found to be related to the development of tool wear values. A fuzzy clustering feature filter has been developed to remove less tool wear relevant features under different cutting conditions. multi-sensor signals reflect tool condition comprehensively and the sensor fusion strategy is used to provide reliable recognition results. Combining fuzzy approaching degree and fuzzy closeness provides a unique and overall fuzzy similarity index, the two-dimensional fuzzy approaching degree. A new type of fuzzy system, the fuzzy driven neural network has been established. The network can assign signal features suitable weights to make the tool wear state recognition process more accurate and robust. The advanced B-spline neurofuzzy networds are also successfully applied in the tool condiiton monitoring process. This powerful modelling system is established by combining the qualitative fuzzy rule representation with the quantitative adaptive numeric processing process. The fuzzy driven neural network and the B-spline neurofuzzy network can then be combined to build a neurofuzzy hybrid pattern recognition system, which is more reliable and accurate. Armed with the well- developed pattern recognition methodology, the established intelligent tool condition monitoring system has the advantages of being suitable for a wide range of machining conditions, robust to noise and tolerant to faults. As can be seen in the thesis, several innovations have been made in the research process of this project. The fuzzy clustering feature filter can significantly improve the efficiency and reliability of the tool wear state recognition process. The two-dimensional fuzzy approaching degree comprehensively characterises the similarity between two fuzzy sets. The fuzzy driven neural network indirectly solves the weight assignment problem of the conventional fuzzy system. The established neurofuzzy hybrid pattern recognition system obviously improves the system's recognition resolution and reliabilty
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Ajilo, Deborah (Deborah M. ). "eyeDNA : Tool Condition Monitoring for a desktop CNC milling machine." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/115670.

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Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2018.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 81-84).
Tool wear is a major obstacle to realizing full automation in metal cutting operations. In this thesis, we designed and implemented a low cost Tool Condition Monitoring (TCM) system using off-the-shelf sensors and data acquisition methods . Peripheral end milling tests were done on a low carbon steel workpiece and the spindle vibration, cutting zone temperature and spindle motor current were recorded. Features from these data sources were used to train decision tree models in MATLAB with the aim of classifying the stages of tool wear. Results showed that the feature sets fusing information from all data sources performed the best, classifying the tool wear stage with up to 93% average accuracy.
by Deborah Ajilo.
S.M.
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Harris, C. G. "Fault diagnosis and condition monitoring for NC/CNC machine tools." Thesis, Cardiff University, 1987. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.381227.

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Dominguez, Caballero Javier Alejandro. "Live tool condition monitoring of SiAlON inserted tools whilst milling nickel-based super alloys." Thesis, University of Sheffield, 2017. http://etheses.whiterose.ac.uk/20763/.

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Cutting tools with ceramic inserts are often used in the process of machining many types of super alloys, mainly due to their high strength and thermal resistance. Nevertheless, during the cutting process, the plastic flow wear generated in these inserts enhances and propagates cracks due to high temperature and high mechanical stress. This leads to a very variable failure of the cutting tool. Furthermore, in high-speed rough machining of nickel-based super alloys, such as Inconel 718 and Waspalloy, it is recommended to avoid the use of any type of coolant. This in turn, enables the clear visualization of cutting sparks, which in these machining tasks are quite distinctive. The present doctoral thesis attempts to set the basis of a potential Tool Condition Monitoring (TCM) system that could use vison-based sensing to calculate the amount of tool wear. This TCM system would work around the research hypothesis that states that a relationship exists between the continuous wear that ceramic SiAlON (solid solutions based on the Si3N4 structure) inserts experience during a high-speed machining process, and the evolution of sparks created during the same process. A successful TCM system such as this could be implemented at an industrial level to aid in providing a live status of the cutting tool’s condition, potentially improving the effectiveness of these machining tasks, whilst preventing tool failure and workpiece damage. During this research, sparks were analyzed through various visual methods in three main experiments. Four studies were developed using the mentioned experiments to support and create a final predictive approach to the TCM system. These studies are described in each thesis chapter and they include a wear assessment of SiAlON ceramics, an analysis of the optimal image acquisition systems and parameters appropriate for this research, a study of the research hypothesis, and finally, an approach to tool wear prediction using Neural Networks (NN). To carry out some of these studies, an overall methodology was structured to perform experiments and to process spark evolution data, as image processing algorithms were built to extract spark area and intensity. Towards the end of this thesis, these spark features were used, along with measured values of tool wear, namely notch, flank and crater wear, to build a Neural Network for tool wear prediction.
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Books on the topic "Tool Condition Monitoring"

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Crushell, James M. Condition monitoring support tools for CNC machines. Dublin: University College Dublin, 1995.

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Zheng, Kougen. Application of the Wigner distribution to monitoring cutting tool condition. [s.l.]: typescript, 1992.

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Dimla, Dimla E. Snr. Multivariate tool condition monitoring in a metal cutting operation using neural networks. Wolverhampton: University of Wolverhampton, 1998.

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Andrews, Gail Glick. Stream*A*Syst: A tool to help you examine stream conditions on your property. [Corvallis, Or.]: Oregon State University Extension Service, 2000.

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Boškoski, Pavle, Andrej Debenjak, and Biljana Mileva Boshkoska. Fast Electrochemical Impedance Spectroscopy: As a Statistical Condition Monitoring Tool. Springer, 2017.

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Silva, R. G. Cutting tool condition monitoring of the turning process using artificial intelligence. 1997.

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Artificial Intelligence Tools: Decision Support Systems in Condition Monitoring and DIagnosis. Taylor & Francis Group, 2015.

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Tejerina, Eva, and Andrés Esteban. Post-mortem examination in the ICU. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780199600830.003.0391.

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Autopsy has long been regarded as a valuable and reliable tool to improve quality of medical care by monitoring diagnostic accuracy and treatment of the critically-ill patients. However, post-mortem examination rates have fallen worldwide during the past decades. Unexpected findings at autopsy contribute to the increasing pool of medical knowledge and may allow the development of strategies for the early detection of diagnoses, leading to better patient care. Several studies have shown that major discrepancies are frequent, and in 5–40% of all hospitalized patients, and in 7–32% of adult intensive care patients a treatable condition that might have altered outcome, had it been recognized, is identified at post-mortem examination. Despite technological improvements in medicine, the percentage of missed diagnoses had not changed over time. Autopsy provides a ‘gold standard’ to assess the accuracy of diagnostic tests and also offers relevant information for the advance of medical knowledge and the description of new disease entities. The health care system as a whole can benefit enormously from autopsy data, the autopsy providing information unavailable by any other method, and should be considered in every patient who dies in the intensive care unit.
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Martins, Marielza R. Ismael. Transtornos de Aprendizagem: A abordagem multidisciplinar. Brazil Publishing, 2021. http://dx.doi.org/10.31012/978-65-5861-557-6.

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The themes included in this book, involving active collaborators, confirm the need to fill the gap for health and education professionals. By presenting information from reliable sources and step-by-step activities to implement interventions with visual and phonological, dysgraphic, dyscalculic and ADHD dyslexics, it aims to provide effective procedures for screening, evaluation, intervention selection and monitoring. Issues examined such as visual dyslexia analyze developmental dyslexia as a condition that has been associated with motor difficulties, but little is known about what is shared or differentiated between its subtypes. The assessment of dyscalculia, which is often neglected, is clearly presented providing a tool for assessment and addressing family or support networks of students with Learning Disorders deepens our understanding Understanding the development of the school allows us to recognize specific situations that are often ignored. All activities have multisensory instruction, that is, students use more than one sense at a time, and multisensory instruction offers students more than one way to make connections and learn concepts The contributors to this book are active researchers in the teachinglearning process and the objective was to expand information on Learning Disorders with content chosen in a selective manner, giving relevance to the multidisciplinary team.
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Gaddam, Samson Sujit Kumar, and Claudia S. Robertson. Cerebral blood flow and perfusion monitoring in the critically ill. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780199600830.003.0222.

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Prevention of secondary cerebral ischaemic insults is an important management strategy in acute neurological conditions. Monitoring of cerebral perfusion may aid in early identification of ischaemic insults and help with management. A number of tools are available for this purpose. Cerebral perfusion pressure (CPP) is the simplest assessment of cerebral perfusion, but in some cases ischaemia can be present even with a normal CPP. Cerebral blood flow (CBF) imaging, either with computed tomography or magnetic resonance imaging techniques, can provide quantitative regional CBF measurement, but only at a single instance in time. Such studies are valuable in the diagnosis of ischaemia, but are difficult for the management of critically-ill patients. CBF can also be measured within the intensive care unit (ICU), either directly or indirectly through the measurement of cerebral oxygenation. These monitors provide a more continuous measure of CBF, and are more useful in assessing response to treatment. Some of the ICU tools monitor global perfusion and some assess perfusion only in a local area of brain surrounding the monitor. With local monitors, the location of the probe is important for interpretation of the findings.
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Book chapters on the topic "Tool Condition Monitoring"

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Boškoski, Pavle, Andrej Debenjak, and Biljana Mileva Boshkoska. "Statistical Condition Monitoring Tool." In Fast Electrochemical Impedance Spectroscopy, 43–55. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-53390-2_5.

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Lister, P. M., and G. Barrow. "Tool Condition Monitoring Systems." In Proceedings of the Twenty-Sixth International Machine Tool Design and Research Conference, 271–88. London: Macmillan Education UK, 1986. http://dx.doi.org/10.1007/978-1-349-08114-1_36.

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Martin, K. F. "Condition Monitoring and Fault Diagnosis with Applications to Machine Tool Subsystems." In Profitable Condition Monitoring, 99–111. Dordrecht: Springer Netherlands, 1993. http://dx.doi.org/10.1007/978-94-011-1616-9_9.

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Hale, K. H., and B. E. Jones. "Tool wear monitoring sensors." In Condition Monitoring and Diagnostic Engineering Management, 343–48. Dordrecht: Springer Netherlands, 1990. http://dx.doi.org/10.1007/978-94-009-0431-6_51.

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Dybała, Jacek, and Jakub Komoda. "Empirical Signal Decomposition Methods as a Tool of Early Detection of Bearing Fault." In Applied Condition Monitoring, 147–56. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-61927-9_14.

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Błażej, Ryszard, Leszek Jurdziak, and Witold Kawalec. "Condition Monitoring of Conveyor Belts as a Tool for Proper Selection of Their Replacement Time." In Applied Condition Monitoring, 483–94. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-20463-5_37.

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Meddour, Ikhlas, Mohamed Athmane Yallese, and Hamdi Aouici. "Investigation and Modeling of Surface Roughness of Hard Turned AISI 52100 Steel: Tool Vibration Consideration." In Applied Condition Monitoring, 419–31. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-14532-7_43.

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Gomez, Jose L., Ilyes Khelf, Adeline Bourdon, Hugo André, and Didier Rémond. "Simplified Dynamic Model of a Wind Turbine Shaft Line Operating in Non-stationary Conditions Applied to the Analysis of IAS as a Machinery Surveillance Tool." In Applied Condition Monitoring, 33–43. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-61927-9_4.

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Jemielniak, Krzysztof. "Tool Condition Monitoring in Metal Cutting." In Studies in Systems, Decision and Control, 45–74. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-03201-2_4.

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Zhu, Kunpeng. "Tool Condition Monitoring with Sparse Decomposition." In Springer Series in Advanced Manufacturing, 235–66. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-87878-8_7.

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Conference papers on the topic "Tool Condition Monitoring"

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Ebrahimi, Morteza, and J. L. Victory. "Web-based machine tool condition monitoring." In Information Technologies 2000, edited by Nina M. Berry. SPIE, 2000. http://dx.doi.org/10.1117/12.411776.

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Khan, Qasim, Asfar A. Khan, and Furkan Ahmad. "Condition monitoring tool for electrical equipment — Thermography." In 2016 International Conference on Electrical, Electronics and Optimization Techniques (ICEEOT). IEEE, 2016. http://dx.doi.org/10.1109/iceeot.2016.7755208.

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Karacal, Cem, Sohyung Cho, and William Yu. "Sensor stream mining for tool condition monitoring." In Industrial Engineering (CIE39). IEEE, 2009. http://dx.doi.org/10.1109/iccie.2009.5223555.

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Denny, Chelladurai E., Kumar A. Santosh, Manish Yadav, and A. Venkatasami. "Design review as a diagnostic tool for power transformers — A case study." In 2008 International Conference on Condition Monitoring and Diagnosis. IEEE, 2008. http://dx.doi.org/10.1109/cmd.2008.4580448.

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Wu Yue, Y. S. Wong, and G. S. Hong. "Adaptive-VDHMM for prognostics in tool condition monitoring." In 2015 6th International Conference on Automation, Robotics and Applications (ICARA 2015). IEEE, 2015. http://dx.doi.org/10.1109/icara.2015.7081136.

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Liang, Shuang, Jinsong Yu, Diyin Tang, and Hao Liu. "A Bayesian nonparametric approach for tool condition monitoring." In 2016 UKACC 11th International Conference on Control (CONTROL). IEEE, 2016. http://dx.doi.org/10.1109/control.2016.7737616.

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Chockalingam, P., E. M. N. Ervina, and C. M. R. Prabhu. "Tool condition monitoring in turning using acoustic emission." In GREEN DESIGN AND MANUFACTURE: ADVANCED AND EMERGING APPLICATIONS: Proceedings of the 4th International Conference on Green Design and Manufacture 2018. Author(s), 2018. http://dx.doi.org/10.1063/1.5066951.

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Hayes, A. P. "MAPS-SFT, a new tool in the infrastructure manager's toolbox." In 4th IET International Conference on Railway Condition Monitoring (RCM 2008). IEE, 2008. http://dx.doi.org/10.1049/ic:20080341.

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Gockenbach, E., and H. Borsi. "Transfer function as tool for noise suppression and localization of partial discharges in transformers during on-site measurements." In 2008 International Conference on Condition Monitoring and Diagnosis. IEEE, 2008. http://dx.doi.org/10.1109/cmd.2008.4580478.

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Stuhr, Ben, and Rui Liu. "A Flexible Similarity Based Algorithm for Tool Condition Monitoring." In ASME 2021 16th International Manufacturing Science and Engineering Conference. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/msec2021-62021.

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Abstract To realize smart manufacturing in various machining processes, tool condition monitoring (TCM) systems are employed to detect the state of the tool in optimizing tool conditions and preventing catastrophic failures. Common types of TCM systems include part-specific methods and generic methods. However, many developed TCM systems lack flexibility and require extensive set-up. To address these issues, the proposed algorithm takes advantage of repetitive machining operations in manufacturing settings and adopts similarity analysis to realize tool condition monitoring by comparing the signals collected from the tool with known conditions against the signals generated by the tool to be monitored. To validate the effectiveness of the proposed TCM system, a case study was performed in which the power signal was collected and used in the similarity analysis. According to this case study, it has been proven that the proposed TCM algorithm is able to accurately predict the state of the tool, i.e. tool wear, with a very simple and flexible solution. Furthermore, several tool condition induced machining parameters have been evaluated to satisfy various monitoring requirements. Nearly all evaluated machining parameters validated the performance and flexibility of the TCM algorithm.
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Reports on the topic "Tool Condition Monitoring"

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Bowles, David, Michael Williams, Hope Dodd, Lloyd Morrison, Janice Hinsey, Tyler Cribbs, Gareth Rowell, Michael DeBacker, Jennifer Haack-Gaynor, and Jeffrey Williams. Protocol for monitoring aquatic invertebrates of small streams in the Heartland Inventory & Monitoring Network: Version 2.1. National Park Service, April 2021. http://dx.doi.org/10.36967/nrr-2284622.

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The Heartland Inventory and Monitoring Network (HTLN) is a component of the National Park Service’s (NPS) strategy to improve park management through greater reliance on scientific information. The purposes of this program are to design and implement long-term ecological monitoring and provide information for park managers to evaluate the integrity of park ecosystems and better understand ecosystem processes. Concerns over declining surface water quality have led to the development of various monitoring approaches to assess stream water quality. Freshwater streams in network parks are threatened by numerous stressors, most of which originate outside park boundaries. Stream condition and ecosystem health are dependent on processes occurring in the entire watershed as well as riparian and floodplain areas; therefore, they cannot be manipulated independently of this interrelationship. Land use activities—such as timber management, landfills, grazing, confined animal feeding operations, urbanization, stream channelization, removal of riparian vegetation and gravel, and mineral and metals mining—threaten stream quality. Accordingly, the framework for this aquatic monitoring is directed towards maintaining the ecological integrity of the streams in those parks. Invertebrates are an important tool for understanding and detecting changes in ecosystem integrity, and they can be used to reflect cumulative impacts that cannot otherwise be detected through traditional water quality monitoring. The broad diversity of invertebrate species occurring in aquatic systems similarly demonstrates a broad range of responses to different environmental stressors. Benthic invertebrates are sensitive to the wide variety of impacts that influence Ozark streams. Benthic invertebrate community structure can be quantified to reflect stream integrity in several ways, including the absence of pollution sensitive taxa, dominance by a particular taxon combined with low overall taxa richness, or appreciable shifts in community composition relative to reference condition. Furthermore, changes in the diversity and community structure of benthic invertebrates are relatively simple to communicate to resource managers and the public. To assess the natural and anthropo-genic processes influencing invertebrate communities, this protocol has been designed to incorporate the spatial relationship of benthic invertebrates with their local habitat including substrate size and embeddedness, and water quality parameters (temperature, dissolved oxygen, pH, specific conductance, and turbidity). Rigid quality control and quality assurance are used to ensure maximum data integrity. Detailed standard operating procedures (SOPs) and supporting information are associated with this protocol.
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Berkowitz, Jacob, and Christine VanZomeren. Approaches to identify and monitor for potential acid sulfate soils in an ecological restoration context. Engineer Research and Development Center (U.S.), February 2022. http://dx.doi.org/10.21079/11681/43349.

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Potential acid sulfate soils include materials with the capacity to generate acidity under certain environmental conditions. As such, these soils can pose challenges to ecological restoration projects occurring in wetlands and nearshore environments. To provide guidance for ecosystem restoration practitioners, the following technical note describes acid sulfate soil formation and distribution and then describes techniques for identifying and monitoring acid sulfate soil conditions prior to and following implementation of restoration activities. Finally, this technical note outlines a number of tools and recently published resources to help avoid unintended consequences of acid sulfate soil disturbance and achieve ecological restoration objectives.
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Furman, Alex, Jan Hopmans, Shmuel Assouline, Jirka Simunek, and Jim Richards. Soil Environmental Effects on Root Growth and Uptake Dynamics for Irrigated Systems. United States Department of Agriculture, February 2011. http://dx.doi.org/10.32747/2011.7592118.bard.

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Root water uptake is perhaps the most important unknown in the mass balance of hydrological and agricultural systems. The understanding and the ability to predict root uptake and the way it is influence by environmental conditions has great potential in increasing water and fertilizer use efficiency and allowing better control of water and contaminant leach towards groundwater. This BARD supported research is composed of several components, including a) intensive laboratory work for the quantification of root uptake and the way it is controlled by environmental conditions; b) development of tools for laboratory and field use that can help in sensing very low water fluxes and water content, which is a necessity for studying root uptake; c) development of capabilities to model compensated root uptake; and d) development of a database that will allow calibration of such a model. In addition some auxiliary research was performed as reported later. Some of the components, and especially the modeling and the HPP development, were completed in the framework of the project and even published in the international literature. The completed components provide a modeling environment that allows testing root compensated uptake modeling, a tool that is extremely important for true mechanistic understanding of root uptake and irrigation design that is based on mechanistic and not partially based myth. The new button HPP provides extended level of utilization of this important tool. As discussed below, other components did not get to maturity stage during the period of the project, but comprehensive datasets were collected and will be analyzed in the near future. A comprehensive dataset of high temporal and spatial resolution water contents for two different setups was recorded and should allow us understanding f the uptake at these fine resolutions. Additional important information about root growth dynamics and its dependence in environmental conditions was achieved in both Israel and the US. Overall, this BARD supported project provided insight on many important phenomena related to root uptake and to high resolution monitoring in the vadose zone. Although perhaps not to the level that we initially hoped for, we achieved better understanding of the related processes, better modeling capabilities, and better datasets that will allow continuation of this effort in the near future.
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Hansen, Peter J., and Amir Arav. Embryo transfer as a tool for improving fertility of heat-stressed dairy cattle. United States Department of Agriculture, September 2007. http://dx.doi.org/10.32747/2007.7587730.bard.

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The overall objective of the current proposal is to develop procedures to improve the pregnancy rate achieved following transfer of fresh or cryopreserved embryos produced in the laboratory into heat-stress recipients. The overall hypothesis is that pregnancy rate in heat-stressed lactating cows can be improved by use of embryo transfer and that additional gains in pregnancy rate can be achieved through development of procedures to cryopreserve embryos, select embryos most likely to establish and maintain pregnancy after transfer, and to enhance embryo competence for post-transfer survival through manipulation of culture conditions. The original specific objectives were to 1) optimize procedures for cryopreservation (Israel/US), 2) develop procedures for identifying embryos with the greatest potential for development and survival using the remote monitoring system called EmbryoGuard (Israel), 3) perform field trials to test the efficacy of cryopreservation and the EmbryoGuard selection system for improving pregnancy rates in heat-stressed, lactating cows (US/Israel), 4) test whether selection of fresh or frozen-thawed blastocysts based on measurement of group II caspase activity is an effective means of increasing survival after cryopreservation and post-transfer pregnancy rate (US), and 5) identify genes in blastocysts induced by insulin-like growth factor-1 (IGF-1) (US). In addition to these objectives, additional work was carried out to determine additional cellular determinants of embryonic resistance to heat shock. There were several major achievements. Results of one experiment indicated that survival of embryos to freezing could be improved by treating embryos with cytochalasin B to disrupt the cytoskeleton. An additional improvement in the efficacy of embryo transfer for achieving pregnancy in heat-stressed cows follows from the finding that IGF-1 can improve post-transfer survival of in vitro produced embryos in the summer but not winter. Expression of several genes in the blastocyst was regulated by IGF-1 including IGF binding protein-3, desmocollin II, Na/K ATPase, Bax, heat shock protein 70 and IGF-1 receptor. These genes are likely candidates 1) for developing assays for selection of embryos for transfer and 2) as marker genes for improving culture conditions for embryo production. The fact that IGF-1 improved survival of embryos in heat-stressed recipients only is consistent with the hypothesis that IGF-1 confers cellular thermotolerance to bovine embryos. Other experiments confirmed this action of IGF-1. One action of IGF-1, the ability to block heat-shock induced apoptosis, was shown to be mediated through activation of the phosphatidylinositol 3-kinase pathway. Other cellular determinants of resistance of embryos to elevated temperature were identified including redox status of the embryo and the ceramide signaling pathway. Developmental changes in embryonic apoptosis responses in response to heat shock were described and found to include alterations in the capacity of the embryo to undergo caspase-9 and caspase-3 activation as well as events downstream from caspase-3 activation. With the exception of IGF-1, other possible treatments to improve pregnancy rate to embryo transfer were not effective including selection of embryos for caspase activity, treatment of recipients with GnRH.and bilateral transfer of twin embryos. In conclusion, accomplishments achieved during the grant period have resulted in methods for improving post-transfer survival of in vitro produced embryos transferred into heat-stressed cows and have lead to additional avenues for research to increase embryo resistance to elevated temperature and improve survival to cryopreservation. In addition, embryo transfer of vitrified IVF embryos increased significantly the pregnancy rate in repeated breeder cows.
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Russo, David, Daniel M. Tartakovsky, and Shlomo P. Neuman. Development of Predictive Tools for Contaminant Transport through Variably-Saturated Heterogeneous Composite Porous Formations. United States Department of Agriculture, December 2012. http://dx.doi.org/10.32747/2012.7592658.bard.

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The vadose (unsaturated) zone forms a major hydrologic link between the ground surface and underlying aquifers. To understand properly its role in protecting groundwater from near surface sources of contamination, one must be able to analyze quantitatively water flow and contaminant transport in variably saturated subsurface environments that are highly heterogeneous, often consisting of multiple geologic units and/or high and/or low permeability inclusions. The specific objectives of this research were: (i) to develop efficient and accurate tools for probabilistic delineation of dominant geologic features comprising the vadose zone; (ii) to develop a complementary set of data analysis tools for discerning the fractal properties of hydraulic and transport parameters of highly heterogeneous vadose zone; (iii) to develop and test the associated computational methods for probabilistic analysis of flow and transport in highly heterogeneous subsurface environments; and (iv) to apply the computational framework to design an “optimal” observation network for monitoring and forecasting the fate and migration of contaminant plumes originating from agricultural activities. During the course of the project, we modified the third objective to include additional computational method, based on the notion that the heterogeneous formation can be considered as a mixture of populations of differing spatial structures. Regarding uncertainly analysis, going beyond approaches based on mean and variance of system states, we succeeded to develop probability density function (PDF) solutions enabling one to evaluate probabilities of rare events, required for probabilistic risk assessment. In addition, we developed reduced complexity models for the probabilistic forecasting of infiltration rates in heterogeneous soils during surface runoff and/or flooding events Regarding flow and transport in variably saturated, spatially heterogeneous formations associated with fine- and coarse-textured embedded soils (FTES- and CTES-formations, respectively).We succeeded to develop first-order and numerical frameworks for flow and transport in three-dimensional (3-D), variably saturated, bimodal, heterogeneous formations, with single and dual porosity, respectively. Regarding the sampling problem defined as, how many sampling points are needed, and where to locate them spatially in the horizontal x₂x₃ plane of the field. Based on our computational framework, we succeeded to develop and demonstrate a methdology that might improve considerably our ability to describe quntitaively the response of complicated 3-D flow systems. The results of the project are of theoretical and practical importance; they provided a rigorous framework to modeling water flow and solute transport in a realistic, highly heterogeneous, composite flow system with uncertain properties under-specified by data. Specifically, they: (i) enhanced fundamental understanding of the basic mechanisms of field-scale flow and transport in near-surface geological formations under realistic flow scenarios, (ii) provided a means to assess the ability of existing flow and transport models to handle realistic flow conditions, and (iii) provided a means to assess quantitatively the threats posed to groundwater by contamination from agricultural sources.
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Kulhandjian, Hovannes. Detecting Driver Drowsiness with Multi-Sensor Data Fusion Combined with Machine Learning. Mineta Transportation Institute, September 2021. http://dx.doi.org/10.31979/mti.2021.2015.

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In this research work, we develop a drowsy driver detection system through the application of visual and radar sensors combined with machine learning. The system concept was derived from the desire to achieve a high level of driver safety through the prevention of potentially fatal accidents involving drowsy drivers. According to the National Highway Traffic Safety Administration, drowsy driving resulted in 50,000 injuries across 91,000 police-reported accidents, and a death toll of nearly 800 in 2017. The objective of this research work is to provide a working prototype of Advanced Driver Assistance Systems that can be installed in present-day vehicles. By integrating two modes of visual surveillance to examine a biometric expression of drowsiness, a camera and a micro-Doppler radar sensor, our system offers high reliability over 95% in the accuracy of its drowsy driver detection capabilities. The camera is used to monitor the driver’s eyes, mouth and head movement and recognize when a discrepancy occurs in the driver's blinking pattern, yawning incidence, and/or head drop, thereby signaling that the driver may be experiencing fatigue or drowsiness. The micro-Doppler sensor allows the driver's head movement to be captured both during the day and at night. Through data fusion and deep learning, the ability to quickly analyze and classify a driver's behavior under various conditions such as lighting, pose-variation, and facial expression in a real-time monitoring system is achieved.
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Tanny, Josef, Gabriel Katul, Shabtai Cohen, and Meir Teitel. Micrometeorological methods for inferring whole canopy evapotranspiration in large agricultural structures: measurements and modeling. United States Department of Agriculture, October 2015. http://dx.doi.org/10.32747/2015.7594402.bard.

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Original objectives and revisions The original objectives as stated in the approved proposal were: (1) To establish guidelines for the use of micrometeorological techniques as accurate, reliable and low-cost tools for continuous monitoring of whole canopy ET of common crops grown in large agricultural structures. (2) To adapt existing methods for protected cultivation environments. (3) To combine previously derived theoretical models of air flow and scalar fluxes in large agricultural structures (an outcome of our previous BARD project) with ET data derived from application of turbulent transport techniques for different crops and structure types. All the objectives have been successfully addressed. The study was focused on both screenhouses and naturally ventilated greenhouses, and all proposed methods were examined. Background to the topic Our previous BARD project established that the eddy covariance (EC) technique is suitable for whole canopy evapotranspiration measurements in large agricultural screenhouses. Nevertheless, the eddy covariance technique remains difficult to apply in the farm due to costs, operational complexity, and post-processing of data – thereby inviting alternative techniques to be developed. The subject of this project was: 1) the evaluation of four turbulent transport (TT) techniques, namely, Surface Renewal (SR), Flux-Variance (FV), Half-order Time Derivative (HTD) and Bowen Ratio (BR), whose instrumentation needs and operational demands are not as elaborate as the EC, to estimate evapotranspiration within large agricultural structures; and 2) the development of mathematical models able to predict water savings and account for the external environmental conditions, physiological properties of the plant, and structure properties as well as to evaluate the necessary micrometeorological conditions for utilizing the above turbulent transfer methods in such protected environments. Major conclusions and achievements The major conclusions are: (i) the SR and FV techniques were suitable for reliable estimates of ET in shading and insect-proof screenhouses; (ii) The BR technique was reliable in shading screenhouses; (iii) HTD provided reasonable results in the shading and insect proof screenhouses; (iv) Quality control analysis of the EC method showed that conditions in the shading and insect proof screenhouses were reasonable for flux measurements. However, in the plastic covered greenhouse energy balance closure was poor. Therefore, the alternative methods could not be analyzed in the greenhouse; (v) A multi-layered flux footprint model was developed for a ‘generic’ crop canopy situated within a protected environment such as a large screenhouse. The new model accounts for the vertically distributed sources and sinks within the canopy volume as well as for modifications introduced by the screen on the flow field and microenvironment. The effect of the screen on fetch as a function of its relative height above the canopy is then studied for the first time and compared to the case where the screen is absent. The model calculations agreed with field experiments based on EC measurements from two screenhouse experiments. Implications, both scientific and agricultural The study established for the first time, both experimentally and theoretically, the use of four simple TT techniques for ET estimates within large agricultural screenhouses. Such measurements, along with reliable theoretical models, will enable the future development of lowcost ET monitoring system which will be attainable for day-to-day use by growers in improving irrigation management.
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Brosh, Arieh, David Robertshaw, Yoav Aharoni, Zvi Holzer, Mario Gutman, and Amichai Arieli. Estimation of Energy Expenditure of Free Living and Growing Domesticated Ruminants by Heart Rate Measurement. United States Department of Agriculture, April 2002. http://dx.doi.org/10.32747/2002.7580685.bard.

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Research objectives were: 1) To study the effect of diet energy density, level of exercise, thermal conditions and reproductive state on cardiovascular function as it relates to oxygen (O2) mobilization. 2) To validate the use of heart rate (HR) to predict energy expenditure (EE) of ruminants, by measuring and calculating the energy balance components at different productive and reproductive states. 3) To validate the use of HR to identify changes in the metabolizable energy (ME) and ME intake (MEI) of grazing ruminants. Background: The development of an effective method for the measurement of EE is essential for understanding the management of both grazing and confined feedlot animals. The use of HR as a method of estimating EE in free-ranging large ruminants has been limited by the availability of suitable field monitoring equipment and by the absence of empirical understanding of the relationship between cardiac function and metabolic rate. Recent developments in microelectronics provide a good opportunity to use small HR devices to monitor free-range animals. The estimation of O2 uptake (VO2) of animals from their HR has to be based upon a consistent relationship between HR and VO2. The question as to whether, or to what extent, feeding level, environmental conditions and reproductive state affect such a relationship is still unanswered. Studies on the basic physiology of O2 mobilization (in USA) and field and feedlot-based investigations (in Israel) covered a , variety of conditions in order to investigate the possibilities of using HR to estimate EE. In USA the physiological studies conducted using animals with implanted flow probes, show that: I) although stroke volume decreases during intense exercise, VO2 per one heart beat per kgBW0.75 (O2 Pulse, O2P) actually increases and measurement of EE by HR and constant O2P may underestimate VO2unless the slope of the regression relating to heart rate and VO2 is also determined, 2) alterations in VO2 associated with the level of feeding and the effects of feeding itself have no effect on O2P, 3) both pregnancy and lactation may increase blood volume, especially lactation; but they have no effect on O2P, 4) ambient temperature in the range of 15 to 25°C in the resting animal has no effect on O2P, and 5) severe heat stress, induced by exercise, elevates body temperature to a sufficient extent that 14% of cardiac output may be required to dissipate the heat generated by exercise rather than for O2 transport. However, this is an unusual situation and its affect on EE estimation in a freely grazing animal, especially when heart rate is monitored over several days, is minor. In Israel three experiments were carried out in the hot summer to define changes in O2P attributable to changes in the time of day or In the heat load. The animals used were lambs and young calves in the growing phase and highly yielding dairy cows. In the growing animals the time of day, or the heat load, affected HR and VO2, but had no effect on O2P. On the other hand, the O2P measured in lactating cows was affected by the heat load; this is similar to the finding in the USA study of sheep. Energy balance trials were conducted to compare MEI recovery by the retained energy (RE) and by EE as measured by HR and O2P. The trial hypothesis was that if HR reliably estimated EE, the MEI proportion to (EE+RE) would not be significantly different from 1.0. Beef cows along a year of their reproductive cycle and growing lambs were used. The MEI recoveries of both trials were not significantly different from 1.0, 1.062+0.026 and 0.957+0.024 respectively. The cows' reproductive state did not affect the O2P, which is similar to the finding in the USA study. Pasture ME content and animal variables such as HR, VO2, O2P and EE of cows on grazing and in confinement were measured throughout three years under twenty-nine combinations of herbage quality and cows' reproductive state. In twelve grazing states, individual faecal output (FO) was measured and MEI was calculated. Regression analyses of the EE and RE dependent on MEI were highly significant (P<0.001). The predicted values of EE at zero intake (78 kcal/kgBW0.75), were similar to those estimated by NRC (1984). The EE at maintenance condition of the grazing cows (EE=MEI, 125 kcal/kgBW0.75) which are in the range of 96.1 to 125.5 as presented by NRC (1996 pp 6-7) for beef cows. Average daily HR and EE were significantly increased by lactation, P<0.001 and P<0.02 respectively. Grazing ME significantly increased HR and EE, P<0.001 and P<0.00l respectively. In contradiction to the finding in confined ewes and cows, the O2P of the grazing cows was significantly affected by the combined treatments (P<0.00l ); this effect was significantly related to the diet ME (P<0.00l ) and consequently to the MEI (P<0.03). Grazing significantly increased O2P compared to confinement. So, when EE of grazing animals during a certain season of the year is estimated using the HR method, the O2P must be re measured whenever grazing ME changes. A high correlation (R2>0.96) of group average EE and of HR dependency on MEI was also found in confined cows, which were fed six different diets and in growing lambs on three diets. In conclusion, the studies conducted in USA and in Israel investigated in depth the physiological mechanisms of cardiovascular and O2 mobilization, and went on to investigate a wide variety of ruminant species, ages, reproductive states, diets ME, time of intake and time of day, and compared these variables under grazing and confinement conditions. From these combined studies we can conclude that EE can be determined from HR measurements during several days, multiplied by O2P measured over a short period of time (10-15 min). The study showed that RE could be determined during the growing phase without slaughtering. In the near future the development microelectronic devices will enable wide use of the HR method to determine EE and energy balance. It will open new scopes of physiological and agricultural research with minimizes strain on animals. The method also has a high potential as a tool for herd management.
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Seginer, Ido, Louis D. Albright, and Robert W. Langhans. On-line Fault Detection and Diagnosis for Greenhouse Environmental Control. United States Department of Agriculture, February 2001. http://dx.doi.org/10.32747/2001.7575271.bard.

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Background Early detection and identification of faulty greenhouse operation is essential, if losses are to be minimized by taking immediate corrective actions. Automatic detection and identification would also free the greenhouse manager to tend to his other business. Original objectives The general objective was to develop a method, or methods, for the detection, identification and accommodation of faults in the greenhouse. More specific objectives were as follows: 1. Develop accurate systems models, which will enable the detection of small deviations from normal behavior (of sensors, control, structure and crop). 2. Using these models, develop algorithms for an early detection of deviations from the normal. 3. Develop identifying procedures for the most important faults. 4. Develop accommodation procedures while awaiting a repair. The Technion team focused on the shoot environment and the Cornell University team focused on the root environment. Achievements Models: Accurate models were developed for both shoot and root environment in the greenhouse, utilizing neural networks, sometimes combined with robust physical models (hybrid models). Suitable adaptation methods were also successfully developed. The accuracy was sufficient to allow detection of frequently occurring sensor and equipment faults from common measurements. A large data base, covering a wide range of weather conditions, is required for best results. This data base can be created from in-situ routine measurements. Detection and isolation: A robust detection and isolation (formerly referred to as 'identification') method has been developed, which is capable of separating the effect of faults from model inaccuracies and disturbance effects. Sensor and equipment faults: Good detection capabilities have been demonstrated for sensor and equipment failures in both the shoot and root environment. Water stress detection: An excitation method of the shoot environment has been developed, which successfully detected water stress, as soon as the transpiration rate dropped from its normal level. Due to unavailability of suitable monitoring equipment for the root environment, crop faults could not be detected from measurements in the root zone. Dust: The effect of screen clogging by dust has been quantified. Implications Sensor and equipment fault detection and isolation is at a stage where it could be introduced into well equipped and maintained commercial greenhouses on a trial basis. Detection of crop problems requires further work. Dr. Peleg was primarily responsible for developing and implementing the innovative data analysis tools. The cooperation was particularly enhanced by Dr. Peleg's three summer sabbaticals at the ARS, Northem Plains Agricultural Research Laboratory, in Sidney, Montana. Switching from multi-band to hyperspectral remote sensing technology during the last 2 years of the project was advantageous by expanding the scope of detected plant growth attributes e.g. Yield, Leaf Nitrate, Biomass and Sugar Content of sugar beets. However, it disrupted the continuity of the project which was originally planned on a 2 year crop rotation cycle of sugar beets and multiple crops (com and wheat), as commonly planted in eastern Montana. Consequently, at the end of the second year we submitted a continuation BARD proposal which was turned down for funding. This severely hampered our ability to validate our findings as originally planned in a 4-year crop rotation cycle. Thankfully, BARD consented to our request for a one year extension of the project without additional funding. This enabled us to develop most of the methodology for implementing and running the hyperspectral remote sensing system and develop the new analytical tools for solving the non-repeatability problem and analyzing the huge hyperspectral image cube datasets. However, without validation of these tools over a ful14-year crop rotation cycle this project shall remain essentially unfinished. Should the findings of this report prompt the BARD management to encourage us to resubmit our continuation research proposal, we shall be happy to do so.
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Aalto, Juha, and Ari Venäläinen, eds. Climate change and forest management affect forest fire risk in Fennoscandia. Finnish Meteorological Institute, June 2021. http://dx.doi.org/10.35614/isbn.9789523361355.

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Forest and wildland fires are a natural part of ecosystems worldwide, but large fires in particular can cause societal, economic and ecological disruption. Fires are an important source of greenhouse gases and black carbon that can further amplify and accelerate climate change. In recent years, large forest fires in Sweden demonstrate that the issue should also be considered in other parts of Fennoscandia. This final report of the project “Forest fires in Fennoscandia under changing climate and forest cover (IBA ForestFires)” funded by the Ministry for Foreign Affairs of Finland, synthesises current knowledge of the occurrence, monitoring, modelling and suppression of forest fires in Fennoscandia. The report also focuses on elaborating the role of forest fires as a source of black carbon (BC) emissions over the Arctic and discussing the importance of international collaboration in tackling forest fires. The report explains the factors regulating fire ignition, spread and intensity in Fennoscandian conditions. It highlights that the climate in Fennoscandia is characterised by large inter-annual variability, which is reflected in forest fire risk. Here, the majority of forest fires are caused by human activities such as careless handling of fire and ignitions related to forest harvesting. In addition to weather and climate, fuel characteristics in forests influence fire ignition, intensity and spread. In the report, long-term fire statistics are presented for Finland, Sweden and the Republic of Karelia. The statistics indicate that the amount of annually burnt forest has decreased in Fennoscandia. However, with the exception of recent large fires in Sweden, during the past 25 years the annually burnt area and number of fires have been fairly stable, which is mainly due to effective fire mitigation. Land surface models were used to investigate how climate change and forest management can influence forest fires in the future. The simulations were conducted using different regional climate models and greenhouse gas emission scenarios. Simulations, extending to 2100, indicate that forest fire risk is likely to increase over the coming decades. The report also highlights that globally, forest fires are a significant source of BC in the Arctic, having adverse health effects and further amplifying climate warming. However, simulations made using an atmospheric dispersion model indicate that the impact of forest fires in Fennoscandia on the environment and air quality is relatively minor and highly seasonal. Efficient forest fire mitigation requires the development of forest fire detection tools including satellites and drones, high spatial resolution modelling of fire risk and fire spreading that account for detailed terrain and weather information. Moreover, increasing the general preparedness and operational efficiency of firefighting is highly important. Forest fires are a large challenge requiring multidisciplinary research and close cooperation between the various administrative operators, e.g. rescue services, weather services, forest organisations and forest owners is required at both the national and international level.
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