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Journal articles on the topic 'Mechanical diagnosis'

Author: Grafiati

Published: 6 June 2023

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1

Remmerbach, Torsten W., Falk Wottawah, Julia Dietrich, Bryan Lincoln, Christian Wittekind, and Jochen Guck. "Oral Cancer Diagnosis by Mechanical Phenotyping." Cancer Research 69, no. 5 (2009): 1728–32. http://dx.doi.org/10.1158/0008-5472.can-08-4073.

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2

Donelson, Ronald. "Mechanical Diagnosis and Therapy for Radiculopathy." Physical Medicine and Rehabilitation Clinics of North America 22, no. 1 (2011): 75–89. http://dx.doi.org/10.1016/j.pmr.2010.11.001.

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3

Zhu, Hong. "Machine-Learning-Based Mechanical Fault Diagnosis Method." Advanced Materials Research 1044-1045 (October 2014): 798–800. http://dx.doi.org/10.4028/www.scientific.net/amr.1044-1045.798.

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With the development of science and technology, the theoretical content of mechanical fault diagnosis technology has been initially improved and established a scientific research system. Combining the mechanical diagnostic techniques with the current advanced science and technology, a variety of mechanical fault diagnosis methods have been researched and developed. Mechanical fault diagnosis evolved from empirical diagnosis to mechanical diagnosis and then to the current intelligent learning diagnosis. Now mechanical fault diagnosis collects mechanical failure data precisely mainly by a variet

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4

Jing, Hong Lei, Jing Nie, and Nian Zhang. "Augmented-Reality-Based Mechanical Fault Diagnosis Method." Advanced Materials Research 1044-1045 (October 2014): 720–22. http://dx.doi.org/10.4028/www.scientific.net/amr.1044-1045.720.

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With the rapid development of modern society, the industrial mechanized production reached unprecedented climax in this era. Science and technology advance increasingly, modern equipment from structure to function tends to be complex and improved, and gradually achieve a high degree of automation. However, due to the inevitable factors such as wear and tear, abrasion and chemicals infection, machinery equipment will inevitably appear unforeseen fault, causing the machine to detract from the performance, or even causing serious economic losses. Therefore, mechanical fault diagnosis can reduce e

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5

Yu, Guangwei, Xianzhi Wang, and Chunlin Da. "Compound mechanical fault diagnosis based on CMDE." Advances in Mechanical Engineering 14, no. 2 (2022): 168781322210805. http://dx.doi.org/10.1177/16878132221080560.

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The fault diagnosis technique is of important for the safety operation of the rotating machinery. In the fault diagnosis framework, the entropy-based method is a promising tool for the feature extraction and signal processing. Among the entropy-based methods, the diversity entropy has arisen increasing attention due to its merits of high consistency, strong robustness, and high calculation efficiency. However, it suffers the defect that the multiscale procedure leads to unstable complexity estimation at higher scales. This induces a poor cluster performance in analyzing the compound mechanical

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6

Xu, Gang. "MECHANICAL FAILURE DIAGNOSIS IN UNSTEADY OPERATING CONDITIONS." Chinese Journal of Mechanical Engineering 37, no. 12 (2001): 104. http://dx.doi.org/10.3901/jme.2001.12.104.

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7

Wu, Wen Bing, Shu Qun Yang, and Yi Jian Huang. "Application of Bipectrum in Mechanical Fault Diagnosis." Advanced Materials Research 538-541 (June 2012): 2645–48. http://dx.doi.org/10.4028/www.scientific.net/amr.538-541.2645.

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Bispectrum produced by third order cumulant contains the asymmetric and nonlinear information of signal, which can be used to describe the nonlinear phase coupling, especially the quadratic phase coupling, has been widely applied in fault diagnosis. The features of fault signals and normal signals are fetched by 2-D wavelet in different directions, then these features are used to diagnose fault. The experiment shows that the method can achieve satisfactory result.

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8

CHEN, Yushu. "Nonlinear dynamical principle of mechanical fault diagnosis." Chinese Journal of Mechanical Engineering 43, no. 01 (2007): 25. http://dx.doi.org/10.3901/jme.2007.01.025.

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9

Gelman, L., S. Gorpinich, and C. Thompson. "Adaptive diagnosis of the bilinear mechanical systems." Mechanical Systems and Signal Processing 23, no. 5 (2009): 1548–53. http://dx.doi.org/10.1016/j.ymssp.2009.01.007.

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10

Remmerbach, T. W., J. Guck, and J. Käs. "O33. Oral cancer diagnosis by mechanical phenotyping." Oral Oncology 47 (July 2011): S39. http://dx.doi.org/10.1016/j.oraloncology.2011.06.144.

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11

Holenstein, Anton P. "Diagnosis of mechanical seals in large pumps." Sealing Technology 1996, no. 33 (1996): 9–12. http://dx.doi.org/10.1016/1350-4789(96)84413-8.

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12

Fillmore, Maggie. "The Upper Limb: Mechanical Diagnosis and Therapy." Physical Therapy 77, no. 11 (1997): 1667–68. http://dx.doi.org/10.1093/ptj/77.11.1667a.

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13

IRIE, TAKASUKE. "Ultrasonic diagnosis." Journal of the Japan Society for Precision Engineering 53, no. 4 (1987): 522–25. http://dx.doi.org/10.2493/jjspe.53.522.

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14

MATSUYAMA, Hisayoshi. "Diagnosis algorithm." Journal of the Japan Society for Precision Engineering 57, no. 3 (1991): 433–35. http://dx.doi.org/10.2493/jjspe.57.433.

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15

R.S, Kiran, Sarmukh S, and Azmi H. "Gallstone ileus: Rare Entity for Mechanical Small Bowel Obstruction." Journal of Surgical Case Reports and Images 4, no. 8 (2021): 01–04. http://dx.doi.org/10.31579/2690-1897/088.

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Gallstone ileus is common in elderly female population. To obtain a diagnosis of gallstone ileus is a challenge requiring clinical and radiological assistance. It’s a rare cause of intestinal obstruction, accounts approximately 1-4%. Here we report a case of 56 years old lady presented with intestinal obstruction sign and symptoms. Per abdomen examination revealed generalised tenderness with sluggish bowel sound. Abdominal X-ray revealed prominent small bowel with presence of gas till rectum. CT abdomen noted intraluminal mass over distal small bowel loops mimickering intusseption. Exploratory

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16

See, Isaac, Julia Chang, Nicole Gualandi, et al. "Clinical Correlates of Surveillance Events Detected by National Healthcare Safety Network Pneumonia and Lower Respiratory Infection Definitions—Pennsylvania, 2011–2012." Infection Control & Hospital Epidemiology 37, no. 7 (2016): 818–24. http://dx.doi.org/10.1017/ice.2016.74.

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OBJECTIVETo determine the clinical diagnoses associated with the National Healthcare Safety Network (NHSN) pneumonia (PNEU) or lower respiratory infection (LRI) surveillance eventsDESIGNRetrospective chart reviewSETTINGA convenience sample of 8 acute-care hospitals in PennsylvaniaPATIENTSAll patients hospitalized during 2011–2012METHODSMedical records were reviewed from a random sample of patients reported to the NHSN to have PNEU or LRI, excluding adults with ventilator-associated PNEU. Documented clinical diagnoses corresponding temporally to the PNEU and LRI events were recorded.RESULTSWe r

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17

Shen, Wei Hua. "Mechanical Fault Diagnosis Based on Data Mining Technology." Advanced Materials Research 320 (August 2011): 663–68. http://dx.doi.org/10.4028/www.scientific.net/amr.320.663.

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Data mining is a variety of analysis tools using the data found in the mass relationship between model and data technology, and relationships of these models can be used to predict. Organically with the combination of expert system, can solve the problem of automatic acquisition of knowledge. It from a large number, incomplete, noisy, fuzzy, random data mining the hidden decision-making has important reference value to generate the information. Data mining technology used in machinery fault diagnosis system, the scene of large quantities of raw data into valuable knowledge for specialists to e

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18

Huang, S. N., K. K. Tan, and T. H. Lee. "Automated Fault Detection and Diagnosis in Mechanical Systems." IEEE Transactions on Systems, Man and Cybernetics, Part C (Applications and Reviews) 37, no. 6 (2007): 1360–64. http://dx.doi.org/10.1109/tsmcc.2007.900623.

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19

Pandey, Arvind K., and Lisa Mendes. "MECHANICAL MITRAL VALVE DYSFUNCTION: STUCK ON A DIAGNOSIS." Journal of the American College of Cardiology 67, no. 13 (2016): 1127. http://dx.doi.org/10.1016/s0735-1097(16)31128-7.

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20

Li, Yong, Jing Lin, Xiufeng Wang, and Yaguo Lei. "Biphase randomization wavelet bicoherence for mechanical fault diagnosis." Measurement 49 (March 2014): 407–20. http://dx.doi.org/10.1016/j.measurement.2013.12.012.

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21

Remmerbach, T., J. Liese, J. Dietrich, F. Wottawah, and J. Guck. "O.499 Oral cancer diagnosis by mechanical phenotyping." Journal of Cranio-Maxillofacial Surgery 36 (September 2008): S125. http://dx.doi.org/10.1016/s1010-5182(08)71623-8.

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22

Wong, Pak Kin, James Lam, Dingli Yu, Xiangyang Ji, and Chi Man Vong. "Intelligent monitoring, diagnosis and control in mechanical engineering." Advances in Mechanical Engineering 10, no. 11 (2018): 168781401881211. http://dx.doi.org/10.1177/1687814018812112.

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23

Qiu, Zhibin, Jiangjun Ruan, and Daochun Huang. "Mechanical fault diagnosis of outdoor high-voltage disconnector." IEEJ Transactions on Electrical and Electronic Engineering 11, no. 5 (2016): 556–63. http://dx.doi.org/10.1002/tee.22273.

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24

Cao, Huiteng. "Big Data Technology Application in Mechanical Intelligent Fault Diagnosis." Journal of Physics: Conference Series 2066, no. 1 (2021): 012064. http://dx.doi.org/10.1088/1742-6596/2066/1/012064.

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Abstract With the rapid implementation of made in China 2025 plan and the rapid development and application of information technology such as artificial intelligence, big data technology, industrial Internet of things and 5G, information technology has been integrated into every link of the whole life management cycle of mechanical products, such as tool condition detection and mechanical fault diagnosis in machining process. Based on this, the purpose of this study is to study the application of big data technology in mechanical intelligent fault diagnosis. In the process of this study, the d

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25

Menon, A., and S. May. "Shoulder pain: Differential diagnosis with mechanical diagnosis and therapy extremity assessment – A case report." Manual Therapy 18, no. 4 (2013): 354–57. http://dx.doi.org/10.1016/j.math.2012.06.011.

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26

Shi, Lian, and Lei Liu. "Vibration Test Measures for Pump Fault Diagnosis." Journal of Electronic Research and Application 5, no. 6 (2021): 6–10. http://dx.doi.org/10.26689/jera.v5i6.2683.

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The vibration measuring standard for compound machinery utilized in modern industrial production will be employed for the application of detecting technologies. The vibration intensity can be obtained by selecting the detecting method to obtain the speed of mechanical vibration, and technicians can examine whether the vibrating machinery is in a proper functioning state based on the value of vibration intensity, allowing for thorough fault diagnosis. In order to provide useful diagnosis ideas for technicians, this study examines the measurement of mechanical vibration and investigates the calc

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27

Xu, Yun Jie. "Research on Internet-Based Reconfigurable Distance Mechanical System Fault Diagnosis." Applied Mechanics and Materials 52-54 (March 2011): 109–14. http://dx.doi.org/10.4028/www.scientific.net/amm.52-54.109.

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In order to meet requirements of increasingly high-speed, large and intelligent mechanical equipments on fault diagnosis, the Internet-based reconfigurable mechanical system fault diagnosis program was presented. The overall structure and networking schema of distance mechanical fault diagnosis system were analyzed, and the distance fault diagnosis network model based on J2EE framework was also described. The structural model and reconfigurable manner of the reconfigurable distance diagnosis system was provided, which used CORBA component technology to achieve reconfiguration. The detail steps

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28

Cai, Yuqi, and Liang Jin. "Reviews of Research on Mechanical Fault Diagnosis in GIS." E3S Web of Conferences 155 (2020): 01015. http://dx.doi.org/10.1051/e3sconf/202015501015.

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Gas Insulated Switchgear (GIS) has been widely used in recent years due to their advantages of small floor area, high reliability and good safety. It has arised a series of problems. At present, researchers at home and abroad have done more in-depth research on insulation fault, but research on mechanical fault is insufficient. Firstly, this paper reviews the research status of mechanical fault detection technology in GIS at home and abroad. Secondly, the aspect of the principles of mechanical fault in GIS, fault judgment and location technology, and early fault prediction and status evaluatio

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29

Pang, Tian Yang, Tian Xiang Yu, and Bi Feng Song. "Fault diagnosis for mechanical system using dynamic Bayesian network." IOP Conference Series: Materials Science and Engineering 1043, no. 3 (2021): 032062. http://dx.doi.org/10.1088/1757-899x/1043/3/032062.

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30

Jinde, ZHENG, PAN Haiyang, CHENG Junsheng, BAO Jiahan, LIU Qingyun, and DING Keqin. "Adaptive Empirical Fourier Decomposition Based Mechanical Fault Diagnosis Method." Journal of Mechanical Engineering 56, no. 9 (2020): 125. http://dx.doi.org/10.3901/jme.2020.09.125.

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31

ANDOU, MASASHI. "Mechanical Diagnosis of Low Back Pain by McKenzie Approach." Rigakuryoho Kagaku 16, no. 4 (2001): 239–48. http://dx.doi.org/10.1589/rika.16.239.

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32

Uller, L., S. M. Bastos, O. F. Ferreira, Marize Varella de Oliveira, I. C. Abud, and R. O. Centeno. "Diagnosis of Mechanical and Corrosion Wear in Sugar Industry." Key Engineering Materials 20-28 (January 1991): 2509–17. http://dx.doi.org/10.4028/www.scientific.net/kem.20-28.2509.

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33

Hong, Geonkyo, and Dongjun Suh. "Supervised-Learning-Based Intelligent Fault Diagnosis for Mechanical Equipment." IEEE Access 9 (2021): 116147–62. http://dx.doi.org/10.1109/access.2021.3104189.

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34

Wei, Yadong, Tuzhi Long, Xiaoman Cai, Shaohui Zhang, Dejan Gjorgjevikj, and Chuan Li. "Mechanical fault diagnosis by using dynamic transfer adversarial learning." Measurement Science and Technology 32, no. 10 (2021): 104005. http://dx.doi.org/10.1088/1361-6501/ac0184.

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35

S. Kapitonov, Sergei, Sergei Y. Grigorovich, Sergei A. Medvedev, and Ivan I. Kurbakov. "Diagnosis of internal combustion engine based on mechanical noise." International Journal of Engineering & Technology 7, no. 2.2 (2018): 9. http://dx.doi.org/10.14419/ijet.v7i2.2.9889.

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The work of sensors is investigated in the article when they are used to detect malfunctions of automobile engines by the method of analyzing noise spectrum. The method of diagnostics of internal combustion engines for noise and vibration has been developed. This method allows to determine the fault at an early stage in a short period of time (the diagnostic process takes 5-10 minutes). The proposed solution allows to reduce the degree of influence of the human factor. Such an approach to diagnostics makes it possible to determine a huge number of faults due to the use of modern computer techn

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36

Jung, Hoon, and Ju-Won Kim. "A Machine Learning Approach for Mechanical Motor Fault Diagnosis." Journal of Society of Korea Industrial and Systems Engineering 40, no. 1 (2017): 57–64. http://dx.doi.org/10.11627/jkise.2017.40.1.057.

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37

Rus, Guillermo, Juan M. Melchor, Inas Faris, et al. "Mechanical biomarkers by torsional shear ultrasound for medical diagnosis." Journal of the Acoustical Society of America 144, no. 3 (2018): 1747. http://dx.doi.org/10.1121/1.5067744.

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38

Cai, HongJuan, and Hengqiang Gao. "Mechanical fault diagnosis based on digital image processing technology." International Journal of Information and Communication Technology 15, no. 1 (2019): 68. http://dx.doi.org/10.1504/ijict.2019.10023623.

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39

Gao, Hengqiang, and HongJuan Cai. "Mechanical fault diagnosis based on digital image processing technology." International Journal of Information and Communication Technology 15, no. 1 (2019): 68. http://dx.doi.org/10.1504/ijict.2019.102055.

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40

Johanson, W. G., John J. Seidenfeld, Paula Gomez, Ruben De Los Santos, and Jacqueline J. Coalson. "Bacteriologic Diagnosis of Nosocomial Pneumonia Following Prolonged Mechanical Ventilation." American Review of Respiratory Disease 137, no. 2 (1988): 259–64. http://dx.doi.org/10.1164/ajrccm/137.2.259.

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41

Lv, Chun Jie, and Yong Yu Yao. "Mechanical Diagnosis Based on Similarity Extraction of Time Series." Advanced Materials Research 753-755 (August 2013): 2159–63. http://dx.doi.org/10.4028/www.scientific.net/amr.753-755.2159.

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The intelligent diagnosis emphasizes the processing method of knowledge of the historical data. The capability of an intelligent diagnosis system depends on the knowledge possessed by the system, especially by the specific knowledge in application. Currently, most of the important equipment have their own the inspection systems. With the help of these systems, plenty of historical data can be collected in real time. This paper discusses the possibility of the application of similarity extraction and pattern discovery of time series in fault diagnosis by using these historical data, presents th

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42

Brown, Amy, and Lynn Snyder-Mackler. "Diagnosis of Mechanical Low Back Pain in a Laborer." Journal of Orthopaedic & Sports Physical Therapy 29, no. 9 (1999): 534–39. http://dx.doi.org/10.2519/jospt.1999.29.9.534.

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43

Huang, Sunan, Kok Kiong Tan, and Mingbo Xiao. "Automated Fault Diagnosis and Accommodation Control for Mechanical Systems." IEEE/ASME Transactions on Mechatronics 20, no. 1 (2015): 155–65. http://dx.doi.org/10.1109/tmech.2014.2322652.

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44

Weeks, Susan M. "The Cervical and Thoracic Spine – Mechanical diagnosis and therapy." Physiotherapy 77, no. 9 (1991): 654. http://dx.doi.org/10.1016/s0031-9406(10)60403-8.

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45

Sheng, Chenxing, Zhixiong Li, Li Qin, Zhiwei Guo, and Yuelei Zhang. "Recent Progress on Mechanical Condition Monitoring and Fault Diagnosis." Procedia Engineering 15 (2011): 142–46. http://dx.doi.org/10.1016/j.proeng.2011.08.029.

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46

Zhang, Zhongwei, Huaihai Chen, Shunming Li, and Zenghui An. "Sparse filtering based domain adaptation for mechanical fault diagnosis." Neurocomputing 393 (June 2020): 101–11. http://dx.doi.org/10.1016/j.neucom.2020.02.049.

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47

HONG, Wei, Wenjian CAI, Shaoping WANG, and Mileta M. TOMOVIC. "Mechanical wear debris feature, detection, and diagnosis: A review." Chinese Journal of Aeronautics 31, no. 5 (2018): 867–82. http://dx.doi.org/10.1016/j.cja.2017.11.016.

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48

Buckley, D. E., W. G. MacKinnon, R. E. Cranston, and H. A. Christian. "Problems with piston core sampling: Mechanical and geochemical diagnosis." Marine Geology 117, no. 1-4 (1994): 95–106. http://dx.doi.org/10.1016/0025-3227(94)90008-6.

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49

Wang, W. J. "Wavelet Transform in Vibration Analysis for Mechanical Fault Diagnosis." Shock and Vibration 3, no. 1 (1996): 17–26. http://dx.doi.org/10.1155/1996/375635.

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The wavelet transform is introduced to indicate short-time fault effects in associated vibration signals. The time-frequency and time-scale representations are unified in a general form of a three-dimensional wavelet transform, from which two-dimensional transforms with different advantages are treated as special cases derived by fixing either the scale or frequency variable. The Gaussian enveloped oscillating wavelet is recommended to extract different sizes of features from the signal. It is shown that the time-frequency and time-scale distributions generated by the wavelet transform are eff

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50

Zagrai, Andrei N., and Hakan Çakan. "Magneto-mechanical impedance identification and diagnosis of metallic structures." International Journal of Engineering Science 48, no. 10 (2010): 888–908. http://dx.doi.org/10.1016/j.ijengsci.2010.05.010.

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