Journal articles: 'Sewer blockage detection system'

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S, Aakash Thalavaisamy, Keerthi Sree K, Padmanabhan S, Dr Manikandan R P S, Mr B. Varun Kumar, and Dr S. Prakash. "IOT BASED-Sewage Blockage Detection System." International Journal for Research in Applied Science and Engineering Technology 10, no. 2 (February 28, 2022): 671–75. http://dx.doi.org/10.22214/ijraset.2022.40320.

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Abstract: Sewer system monitoring is important to keep the city clean. Irregular monitoring of the sewage system leads to obstruction of drainage. Sewer blockages are the main causes of sewer flooding and pollution. Sometimes, out of ignorance, workers may encounter an accident as they may not be aware of the conditions inside the manhole. This document represents an experimentation of the smart sanitation system using IoT. In this model, a water pump motor, transformer, microcontroller and IoT module is used to obtain the desired output from the module.

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Rupali S. Kokate, Saniya Ansari, S. M. Khairnar, Ravindra R. Patil,. "AN ASSESSMENT - WATER QUALITY MONITORING PRACTICES AND SEWER ROBOTIC SYSTEMS." INFORMATION TECHNOLOGY IN INDUSTRY 9, no. 1 (February 28, 2021): 140–48. http://dx.doi.org/10.17762/itii.v9i1.113.

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Water pollution has become a global issue and creating a severe problems due to contamination of various water sources such as agricultural waste, industrial waste, and sewage waste etc. So, the available sensory systems, nodes, and techniques plays a crucial role in identification of harmful pollutants in distinct water resources. The water pollutants monitoring techniques with prospered tools and sensors have been unfolded to find gap for future research maneuver. The need of real-time newer sensory system has been put forwarded for identification of mostly occurring harmful pollutants such as BOD, COD, TSS, and Hydrogen sulfide in examination of water quality. In this modern advancement, robotic systems have taken an intrinsic stand in diverse fields of humankind. An underground infrastructure is a base of modern society. In this paper, the existing methodologies and developed sewer robotic systems have been discussed and concluded on their applications, limitations and impact on realistic scenarios. Also, the cardinal point is revealed that previous art work focused only on sewer defect identification but not standardized work on sewer blockages detection and removal. So, the sewer robotic system with features of cost effectiveness and standardized accuracy matrix should be developed to resolve sewer blockage issues and followed by human scavenging. The survey outcomes extend a province of sewer robotics to resolve blockages issues of buried sewers of distinct diameters in real-time with substantial methodology.

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Et al., Pratim Bhosale. "IOT BASED SYSTEM FOR DETECTION OF SEWAGE BLOCKAGES." INFORMATION TECHNOLOGY IN INDUSTRY 9, no. 1 (March 15, 2021): 961–70. http://dx.doi.org/10.17762/itii.v9i1.224.

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In smart cities, the Internet of Things(IoT) is a key aspect providing seamless and unique access to public resources, with the aim of achieving better utilization and optimization of power, water and transportation facilities. Today urban India is faced with a water crisis, about 80% of sewage enters lakes, rivers and groundwater untreated, due to the lack of effective wastewater infrastructure management. This research focuses mainly on monitoring of sewage infrastructure, to predict blockages, preventing them from turning into Sanitary Sewer Overflows (SSO). This paper proposes an IoT based full-fledged system to tackle this issue. The system monitors the working of access manholes in a network, collecting multiple data parameters, generated in and around these manholes, and sends alerts when the development of a blockage is detected. This geospatial data along with the alerts are observed via a centralized visual dashboard. Through this system, the objectives that the paper proposes to achieve, are generation of dynamic geo-spatial map of manhole networks, enabling the stakeholders to perform proactive maintenance of this infrastructure. Another goal of this work is to generate a data set for developing machine learning models for advanced maintenance methods.

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Wang, Shiyao, Jesus Leonardo Corredor Garcia, Jonathan Davidson, and Andrew Nichols. "Conductance-Based Interface Detection for Multi-Phase Pipe Flow." Sensors 20, no. 20 (October 16, 2020): 5854. http://dx.doi.org/10.3390/s20205854.

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Sediment and flow depth monitoring in sewers is important for informing flow models and for predicting and mitigating against sewer blockage formation and surcharge. In this study, a novel sensor based on conductance measurement has been developed and tested under a laboratory environment and validated by a finite-element model. The relative conductance is measured between pairs of adjacent electrodes to provide a conductance profile along the sensor length. A piecewise linear relationship between conductance and electrode length was derived and the interface positions between sediment, water, and air can be determined from the profile. The results demonstrated that the root mean square error of the model and the measured interface level are within 1.4% and 2.6% of sensor’s measurement range. An error distribution of interface height shows that all anticipated errors are within the resolution of the electrode length increments. Furthermore, it was found that the conductivity of the measured medium is proportional to the gradient of the linear relationship of conductance and electrode length. It could therefore prove a valuable new tool for the accurate quantification of sediment and flow levels in sewer conduits, coastal environments, drainage systems for transport networks, and other industrial or academic applications.

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Himanshu, S. "IOT based Manhole Detection and Monitoring System." International Journal for Research in Applied Science and Engineering Technology 10, no. 6 (June 30, 2022): 1608–13. http://dx.doi.org/10.22214/ijraset.2022.43862.

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Abstract: The sewage system must be monitored in order to maintain the city clean. Uneven sewage system monitoring causes drainage to become clogged. Blockages in the sewer system are a major source of sewer flooding and pollution. Workers may be involved in an accident as a result of their ignorance of the situation inside the manhole. To get the necessary output from the module, this model uses a regulator circuit, sensor driver circuit, microcontroller, serial communication devices, and IoT module. Overflowing drains in the sewage system are one of the most prevalent difficulties identified, which become more severe during the monsoon seasons when the authorities are ignorant of the overflowing drains. It is unsanitary for the adjacent residents and creates waterlogging, which leads to bug breeding. Our answer to this problem is an IoT system that warns municipal officials about overflowing drains immediately by email or notification at the city control centre, as well as citizens via social media or a mobile app. The essential component of this system is a low-power IoT-based portable gadget that is mounted below the manhole cover. [2][7]

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Dirckx, G., T. Wambecq, A. Qvick, and M. Weemaes. "EPIGONE: the argus on the daily operation of throttle structures." Water Practice and Technology 8, no. 3-4 (September 1, 2013): 382–89. http://dx.doi.org/10.2166/wpt.2013.038.

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This study presents the development of an Early Warning System (EWS) called EPIGONE focusing on the detection of dry weather overflows in the vicinity of throttle structures in sewer systems. Throttle structures are considered as vital parts of a sewer system as they are control sections limiting flow rates to a designed operational value. Because these structures are by definition prone to potential clogging or blockages, a close follow-up of the daily operation by an EWS facilitates increased vigilance or even alarm. Primary goal of EPIGONE is to alert operators and thus allow fast intervention in case of suspected failures of these structures within a settled timeframe. EPIGONE combines overflow water level measurements with rainfall radar information to determine Combined Sewer Overflow (CSO) activity during dry weather as this dual condition will indicate malfunctioning. This combination of measurements was found to be the most cost effective set-up to deploy on a large scale. Water level data are recorded and logged on-site and sent to a central controller via GSM/GPRS, where an algorithm determines dry weather overflow conditions. Rainfall radar data are used as criterion to decide on dry weather conditions. From there on alarms are sent out to multiple recipients via e-mail and/or text messages (SMS). Next to this, it is obvious that this system can also be used for ‘regular’ wet weather CSO monitoring.

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Bin Ali, M. T., K. V. Horoshenkov, and S. J. Tait. "Rapid detection of sewer defects and blockages using acoustic-based instrumentation." Water Science and Technology 64, no. 8 (October 1, 2011): 1700–1707. http://dx.doi.org/10.2166/wst.2011.183.

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Sewer flooding incidents in the UK are being increasingly associated with the presence of blockages. Blockages are difficult to deal with as although there are locations where they are more likely to occur, they do occur intermittently. In order to manage sewer blockage pro-actively sewer managers need to be able to identify the location of blockages promptly. Traditional closed-circuit television (CCTV) inspection technologies are slow and relatively expensive so are not well suited to the rapid inspection of a network. This is needed if managers are to be able to address sewer blockages pro-actively. This paper reports on the development of an acoustic-based sensor. The sensor was tested in a full scale sewer pipe in the laboratory and it was shown that it is able to find blockages and identify structural aspects of a sewer pipe such as a manhole and lateral connection. Analysis of the received signal will locate a blockage and also provide information on its character. The measurement is very rapid and objective and so inspections can be carried out at much faster rates than using existing CCTV technologies.

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Melville-Shreeve, Peter, Sarah Cotterill, Alex Newman, and David Butler. "Campus Study of the Impact of Ultra-Low Flush Toilets on Sewerage Networks and Water Usage." Water 13, no. 4 (February 5, 2021): 419. http://dx.doi.org/10.3390/w13040419.

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Water demand management often focuses on quantifying the benefits of water efficiency rather than the potential impact of reduced flows on the sewer network. This study assessed the impact of a high-density deployment of ultra-low flush toilets (ULFT). A pre-installation washroom survey was carried out in July 2018. Water demand and sewer network condition were assessed ahead of the installation of 119 ULFTs and a real-time monitoring system across seven buildings on the University of Exeter campus. ULFTs were flushed 257,925 times in 177 days saving an estimated 2287 m3 per annum (compared to traditional 6 litre WCs). The annual cost saving of this reduction is approximately £12,580/annum, assuming a volumetric cost of £5.50/m3 of water. Mean discharge to the sewer network reduced by 6 m3/day. In the six-month period, 95 maintenance issues were reported, equating to 1 in 2700 flushes (0.037%). However, the frequency of incidents decreased after an initial commissioning period. There is no evidence, from blockage reports or photographs of manhole flow conditions, that the risk of blockage in the sewer network increased as a result of the ULFT installation programme.

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Jamaludin, J., R. A. Rahim, M. H. F. Rahiman, W. Z. W. Ismail, I. Ismail, M. Sahrim, S. R. Balakrishnan, S. N. Raisin, F. M. Rahalim, and B. Naeem. "A study on early detection of sewer pipeline blockage using CCD tomography approach." IOP Conference Series: Earth and Environmental Science 646, no. 1 (January 1, 2021): 012049. http://dx.doi.org/10.1088/1755-1315/646/1/012049.

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Marquez, Andres, C. Jagroop, and C. Maharaj. "Wastewater collection system failures in a capital city: analysis and sustainable prevention." Water Science and Technology 83, no. 8 (March 19, 2021): 1958–72. http://dx.doi.org/10.2166/wst.2021.105.

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Abstract An analysis of failures in a capital city's wastewater collection system was carried out and recommendations were made for sustainable preventive measures based on a risk of failure assessment. Most failures in sewer lines were associated with blockage caused by sediment accumulation and clogging from fats, oils and/or grease dumped by restaurants along several streets, combined with poor or nonexistent maintenance of the lines. Sewer lines in streets with higher risk levels due to multiple food establishments along those streets experienced most of the failures. Sustainability of the proposed maintenance was evidenced since it reduces costs and exposure to harmful substances and hazardous conditions as well as minimizing environmental impacts.

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Okwori, E., M. Viklander, and A. Hedström. "Performance assessment of Swedish sewer pipe networks using pipe blockage and other associated performance indicators." H2Open Journal 3, no. 1 (January 1, 2020): 46–57. http://dx.doi.org/10.2166/h2oj.2020.027.

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Abstract Sewer pipe networks are expected to operate with minimal or no interruptions. The complex nature of randomly occurring failures in sewer networks arising from blockages significantly adds to the cost of operation and maintenance. Blockages are significant due to sewage backup or basements flooding, resulting from their occurrence. Therefore, continuous performance assessment of sewer pipe networks is necessary to ensure required levels of service at an acceptable cost. This study provides insight into the performance of the sewer pipe networks by assessing the proneness of the network to blockages. Furthermore it draws inferences at a holistic strategic level of influential explanatory factors of blockage proneness, using data available in the Swedish Water and Wastewater Association's benchmarking system. Results indicate that medium sized municipalities are prone to at least 30% more blockages per km per year compared to other municipalities. A hypothesis of explanatory factors includes reduced flow volumes and flow depth. Flow velocities below self-cleaning velocity in sewer pipe networks, encouraged by sluggishness of flow are responsible for increased possibility for sediment deposition and accumulation in sewers leading to blockages. This is also exacerbated by the deposition of non-disposables (wet wipes, baby diapers, hard paper, etc.), accumulation of fats, oils and grease in sewers and increased water conservation measures.

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Draude, Sabrina, Edward Keedwell, Rebecca Hiscock, and Zoran Kapelan. "A statistical analysis on the effect of preceding dry weather on sewer blockages in South Wales." Water Science and Technology 80, no. 12 (December 15, 2019): 2381–91. http://dx.doi.org/10.2166/wst.2020.063.

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Abstract Water and sewerage companies (WaSC) in the UK are under increasing pressures to improve customer satisfaction. The biggest cause for customer dissatisfaction in the wastewater sector is a service failure caused by a blockage. There is therefore a need to understand the factors which influence blockage processes in order to prevent them. This work demonstrates how preceding rainfall impacts the sewer system of two highly populated regions within South Wales that have differing gradients. The total rainfall, number of dry days and consecutive number of dry days prior to a blockage were investigated using statistical analysis in order to determine the impact that rainfall has on blockages. The results obtained demonstrate the importance that dry weather has on blockage rates in both steep and flat catchments. Future work will incorporate predicted rainfall impact into a proactive maintenance scheduling model.

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Pulido, Eliana Soriano, Carlos Valencia Arboleda, and Juan Pablo Rodríguez Sánchez. "Study of the spatiotemporal correlation between sediment-related blockage events in the sewer system in Bogotá (Colombia)." Water Science and Technology 79, no. 9 (May 1, 2019): 1727–38. http://dx.doi.org/10.2166/wst.2019.172.

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Abstract The planning and scheduling of maintenance operations of large conventional sewer systems generate a complex decision-making environment due to the difficulty in the collection and analysis of the spatiotemporal information about the operational and structural condition of their components (e.g. pipes, gully pots and manholes). As such, water utilities generally carry out these operations following a corrective approach. This paper studies the impact of the spatiotemporal correlation between these failure events using Log-Gaussian Cox Process (LGCP) models. In addition, the association of failure events to physical and environmental covariates was assessed. The proposed methods were applied to analyze sediment-related blockages in the sewer system of an operative zone in Bogotá (Colombia). The results of this research allowed the identification of significant covariates that were further used to model spatiotemporal clusters with high sediment-related failure risk in sewer systems. The LGCP model proved to be more accurate in comparison to those models that build upon a fundamental assumption that a failure is equally likely to occur at any time regardless of the state of the system and the system's history of failures (i.e. a homogeneous Poisson process model).

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Rosin, T. R., Z. Kapelan, E. Keedwell, and M. Romano. "Near real-time detection of blockages in the proximity of combined sewer overflows using evolutionary ANNs and statistical process control." Journal of Hydroinformatics 24, no. 2 (March 1, 2022): 259–73. http://dx.doi.org/10.2166/hydro.2022.036.

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Abstract Blockages are a major issue for wastewater utilities around the world, causing loss of service, environmental pollution, and significant clean-up costs. Increasing telemetry in combined sewer overflows (CSOs) provides the opportunity for near real-time data-driven modelling of wastewater networks. This paper presents a novel methodology, designed to detect blockages and other unusual events in the proximity of CSO chambers in near real-time. The methodology utilises an evolutionary artificial neural network (EANN) model for short-term CSO level predictions and statistical process control (SPC) techniques to analyse unusual level behaviour. The methodology was evaluated on historic blockage events from several CSOs in the UK and was demonstrated to detect blockage events quickly and reliably, with a low number of false alarms.

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Bhutada, Sudit, Suparn More, Tarush Shrivastav, Chaitanya Suryawanshi, and Pranav Suryawanshi. "IoT Based Smart Sewage Monitoring System for Smart City." International Journal for Research in Applied Science and Engineering Technology 10, no. 11 (November 30, 2022): 1702–7. http://dx.doi.org/10.22214/ijraset.2022.47704.

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Abstract: Sewer monitoring is an important aspect of maintaining cleanliness around us. Lack of sewage monitoring systems may lead to blockage of the drainage. These blockages in sewers may lead to sewer flooding and pollution. Sometimes, workers may meet with accidents as they might not be aware of the condition inside the manhole. This paper aims to measure and analyze the real time levels of sewage. In order to ensure safety of the workers working under some severe conditions. This project attempts to devise an IOT technology that shall detect the level of sewage in the tunnel while keeping track of flow rate of it. If the level exceeds beyond threshold, it shall send an alert through the blynk web app. Additionally provide the information about the flow through the blynk web app itself. To obtain the desired output ultrasonic sensor, flow sensor, nodemcu esp8266, Arduino Uno and blynk web app are used in the proposed model.

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Alshami, Ahmad, Moustafa Elsayed, Saeed Reza Mohandes, Ahmed Farouk Kineber, Tarek Zayed, Ashraf Alyanbaawi, and Mohammed Magdy Hamed. "Performance Assessment of Sewer Networks under Different Blockage Situations Using Internet-of-Things-Based Technologies." Sustainability 14, no. 21 (October 28, 2022): 14036. http://dx.doi.org/10.3390/su142114036.

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This study aims to model the performance of sewage networks under diverse blockage situations in terms of overflow occurrence using internet-of-things-based technologies in Hong Kong. To this end, a multi-stage methodological approach is employed, starting from collecting required data using smart sensors, utilizing novel data mining techniques, and using a case study simulation. From the results obtained, the following conclusions are drawn: (1) several sites under investigation are imbued with partial blockages, (2) the overall performance of the sewer network has a nonlinear relationship with the blockages in terms of the remaining time to overflow, (3) in cases of complete blockages, the sewer only takes few minutes to reach the manhole cover level that causes the system to experience overflow, and (4) cleaning work significantly improve the performance of the sewage network by 86%. The outcomes of this study provide a solid foundation for the concerned environmental engineers and decision-makers towards reducing the magnitude of sewer overflow and improving different aspects of our environment.

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Marleni, N., S. Gray, A. Sharma, S. Burn, and N. Muttil. "Impact of water source management practices in residential areas on sewer networks – a review." Water Science and Technology 65, no. 4 (February 1, 2012): 624–42. http://dx.doi.org/10.2166/wst.2012.902.

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Prolonged drought which has occurred everywhere around the world has caused water shortages, leading many countries to consider more sustainable practices, which are called source management practices (SMPs) to ensure water availability for the future. SMPs include the practices of water use reduction, potable water substitution and wastewater volume reduction such as water demand management, rainwater harvesting, greywater recycling and sewer mining. Besides the well known advantages from SMPs, they also contribute to the alteration of wastewater characteristics which finally affect the process in downstream infrastructure such as sewerage networks. Several studies have shown that the implementation of SMPs decreases the wastewater flow, whilst increasing its strength. High-strength wastewater can cause sewer problems such as sewer blockage, odour and corrosion. Yet, not all SMPs and their impact on existing sewer networks have been investigated. Therefore, this study reviews some examples of four common SMPs, the wastewater characteristics and the physical and biochemical transformation processes in sewers and the problems that might caused by them, and finally the potential impacts of those SMPs on wastewater characteristics and sewer networks are discussed. This paper provides sewer system managers with an overview of potential impacts on the sewer network due to the implementation of some SMPs. Potential research opportunities for the impact of SMPs on existing sewers are also identified.

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Arthur, S., H. Crow, L. Pedezert, and N. Karikas. "The holistic prioritisation of proactive sewer maintenance." Water Science and Technology 59, no. 7 (April 1, 2009): 1385–96. http://dx.doi.org/10.2166/wst.2009.134.

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In sewerage asset management, there has been a concerted move away from primarily assessing system capacity or physical performance, to focus on “serviceability” as a key performance indicator. After identifying flooding due to blockages as a key failure mode, this paper documents the development of a tool which can contribute towards efficient sewerage asset management within the context of maintaining “serviceability” to customers, the public and the environment. Against the background of poor availability of reliable data, the reported project provides a process based on FMECA which can be implemented with limited information and without the need for additional data gathering. Land use and network characteristics data have been used alongside a hydrodynamic model to determine critical points in a network. Based on this, a methodology for identifying where blockage likelihood lies is outlined alongside an approach which allows failure consequence to be quantified. The text then outlines a framework which allows failure likelihood and consequence to be combined to prioritise sewerage asset maintenance.

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Tonomura, Osamu, Satoshi Taniguchi, Kazuki Nishi, Aiichiro Nagaki, Jun-ichi Yoshida, Katsuyuki Hirose, Norio Ishizuka, and Shinji Hasebe. "Blockage Detection and Diagnosis of Externally Parallelized Monolithic Microreactors." Catalysts 9, no. 4 (March 28, 2019): 308. http://dx.doi.org/10.3390/catal9040308.

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To realize stable operation of a microchemical system, it is necessary to develop a process monitoring method that can detect and diagnose blocked microreactors. In this study, a system composed of five monolithic microreactors and a split-and-recombine-type flow distributor (SRFD) was developed for Suzuki–Miyaura coupling. Firstly, the effects of operating conditions on the yield was examined by using a single microreactor. After that, an optimal design problem was formulated to maximize the blockage detection performance by adjusting the channel resistances of the SRFD and the sensor locations in the SRFD under the design constraints. To efficiently solve the problem, a pressure drop compartment model, which is analogous to electrical resistance networks, was used. The optimally designed system was experimentally evaluated from the viewpoint of the capability of continuous operation and the blockage detection and diagnosis performance. The evaluation results show that continuous operation was successfully carried out for one hour, and that the artificially generated blockage of each microreactor was accurately identified. The developed system minimized the process performance degradation due to blockage.

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Mohapatra, Pranab K., M. Hanif Chaudhry, Ahmed Kassem, and Jamaluddin Moloo. "Detection of Partial Blockages in a Branched Piping System by the Frequency Response Method." Journal of Fluids Engineering 128, no. 5 (January 15, 2006): 1106–14. http://dx.doi.org/10.1115/1.2238880.

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Steady oscillatory flow in a branched piping system with partial blockages is studied by using the frequency response method. The peak pressure frequency diagrams at the downstream end are developed with the partial blockage at different locations in the system by using the transfer matrix method. A systematic procedure is presented to estimate the size and the location of a single partial blockage in the system. For more than one partial blockage, it is observed that there is a definite relationship between the frequency responses of the individual and combined partial blockages.

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See, Chan H., Kirill V. Horoshenkov, M. Tareq Bin Ali, and Simon J. Tait. "An Acoustic Sensor for Combined Sewer Overflow (CSO) Screen Condition Monitoring in a Drainage Infrastructure." Sensors 21, no. 2 (January 8, 2021): 404. http://dx.doi.org/10.3390/s21020404.

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Combined sewer overflow structures (CSO) play an important role in sewer networks. When the local capacity of a sewer system is exceeded during intense rainfall events, they act as a “safety valve” and discharge excess rainfall run-off and wastewater directly to a natural receiving water body, thus preventing widespread urban flooding. There is a regulatory requirement that solids in CSO spills must be small and their amount strictly controlled. Therefore, a vast majority of CSOs in the UK contain screens. This paper presents the results of a feasibility study of using low-cost, low-energy acoustic sensors to remotely assess the condition of CSO screens to move to cost-effective reactive maintenance visits. In situ trials were carried out in several CSOs to evaluate the performance of the acoustic sensor under realistic screen and flow conditions. The results demonstrate that the system is robust within ±2.5% to work successfully in a live CSO environment. The observed changes in the screen condition resulted in 8–39% changes in the values of the coefficient in the proposed acoustic model. These changes are detectable and consistent with observed screen and hydraulic data. This study suggested that acoustic-based sensing can effectively monitor the CSO screen blockage conditions and hence reduce the risk of non-compliant CSO spills.

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See, Chan H., Kirill V. Horoshenkov, M. Tareq Bin Ali, and Simon J. Tait. "An Acoustic Sensor for Combined Sewer Overflow (CSO) Screen Condition Monitoring in a Drainage Infrastructure." Sensors 21, no. 2 (January 8, 2021): 404. http://dx.doi.org/10.3390/s21020404.

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Combined sewer overflow structures (CSO) play an important role in sewer networks. When the local capacity of a sewer system is exceeded during intense rainfall events, they act as a “safety valve” and discharge excess rainfall run-off and wastewater directly to a natural receiving water body, thus preventing widespread urban flooding. There is a regulatory requirement that solids in CSO spills must be small and their amount strictly controlled. Therefore, a vast majority of CSOs in the UK contain screens. This paper presents the results of a feasibility study of using low-cost, low-energy acoustic sensors to remotely assess the condition of CSO screens to move to cost-effective reactive maintenance visits. In situ trials were carried out in several CSOs to evaluate the performance of the acoustic sensor under realistic screen and flow conditions. The results demonstrate that the system is robust within ±2.5% to work successfully in a live CSO environment. The observed changes in the screen condition resulted in 8–39% changes in the values of the coefficient in the proposed acoustic model. These changes are detectable and consistent with observed screen and hydraulic data. This study suggested that acoustic-based sensing can effectively monitor the CSO screen blockage conditions and hence reduce the risk of non-compliant CSO spills.

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AHRARY, ALIREZA, LI TIAN, SEI-ICHIRO KAMATA, and MASUMI ISHIKAWA. "NAVIGATION OF AN AUTONOMOUS SEWER INSPECTION ROBOT BASED ON STEREO CAMERA IMAGES AND LASER SCANNER DATA." International Journal on Artificial Intelligence Tools 16, no. 04 (August 2007): 611–25. http://dx.doi.org/10.1142/s0218213007003461.

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Sewer environment is composed of cylindrical pipes, in which only a few landmarks such as manholes, inlets and pipe joints are available for localization. This paper presents a method for navigation of an autonomous sewer inspection robot in a sewer pipe system based on detection of landmarks. In this method, location of an autonomous sewer inspection robot in the sewer pipe system is estimated from stereo camera images. The laser scanner data are also used to ensure accurate localization of the landmarks and reduce the error in distance estimation by image processing. The method is implemented and evaluated in a sewer pipe test field using a prototype robot, demonstrating its effectiveness.

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Zhou, Qianqian, Zuxiang Situ, Shuai Teng, Weifeng Chen, Gongfa Chen, and Jiongheng Su. "Comparison of classic object-detection techniques for automated sewer defect detection." Journal of Hydroinformatics 24, no. 2 (March 1, 2022): 406–19. http://dx.doi.org/10.2166/hydro.2022.132.

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Abstract Sewer systems play a key role in cities to ensure public assets and safety. Timely detection of defects can effectively alleviate system deterioration. Conventional manual inspection is labor-intensive, error-prone and expensive. Object detection is a powerful deep learning technique that can complement and/or replace conventional inspection, especially in complex environments. This study compares two classic object-detection methods, namely faster region-based convolutional neural network (R-CNN) and You Only Look Once (YOLO), for the detection and localization of five types of sewer defects. Model performances are evaluated based on their detection accuracy and processing speed under parameterization impacts of dataset size and training parameters. Results show that faster R-CNN achieved higher prediction accuracy. Training dataset size and maximum number of epochs (MaxE) had dominant impacts on model performances of faster R-CNN and YOLO, respectively. The processing speed increased along with the increasing training data for faster R-CNN, but did not vary significantly for YOLO. The models' abilities to detect disjoint and residential wall were highest, whereas crack and tree root were more difficult to detect. The results help to better understand the strengths and weaknesses of the classic methods and provide a useful user guidance for practical applications in automated sewer defect detection.

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Moradi, Saeed, Tarek Zayed, and Farzaneh Golkhoo. "Review on Computer Aided Sewer Pipeline Defect Detection and Condition Assessment." Infrastructures 4, no. 1 (March 1, 2019): 10. http://dx.doi.org/10.3390/infrastructures4010010.

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Physical and operational inspection of sewer pipelines is critical to sustaining an acceptable level of system serviceability. Emerging inspection tools in addition to developments in sensor and lens technologies have facilitated sewer condition assessment and increased the quality and consistency of provided data. Meanwhile, sewer networks are too vast to be adequately investigated manually so the development of innovative computer vision techniques for automation applications has become an interest point of recent studies. This review paper presents the current state of inspection technology practices in sewer pipelines. An overall inspection tool comparison was conducted and the advantages and disadvantages of each method were discussed. This was followed by a comprehensive review of recent studies on visual inspection automation using computer vision and machine learning techniques. Finally, current achievements and limitations of existing automation methods were debated to outline open challenges and future research for both infrastructure management and computer science researchers.

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CHOWDHURY, MAINUL ISLAM, MD Rakib Hasan, Maruf Chowdhury, Saad Mohammad Bhuiya, and Md Saniat Rahman Zishan. "Design And Development Of Air Conditioner (AC) Monitoring And Management System." AIUB Journal of Science and Engineering (AJSE) 21, no. 3 (December 31, 2022): 132–38. http://dx.doi.org/10.53799/ajse.v21i3.260.

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Nowadays Air Conditioner (AC) has become a more important appliance in our life. Gas leakage, blockage in the evaporator and compressor coil, pipelines as well as dust in the air filters, are the major reasons behind AC explosion. Many people have been injured over the years due to AC blasts. In this paper a system is developed that uses sensor technology and smart devices to reduce AC blast. As a result, pipeline leaks or blockage fault detection system is planned and constructed using MQ-02, TTC 103, optical dust sensors for gas detection, temperature detection and for detecting dust density respectively. Also bacteria can be detected through MQ-3 gas sensor as it combines with AC refrigerant and produces ethanol. This system is also digitally connected to smart devices (cellphones) and a control device (RM MINI 3) so that user can receive a detection notification at any time and operate AC from any location. By implementing these sensors, the initial target was achieved. The work is low cost and environment friendly. Index Terms— Explosions, blockage, leakage, RM MINI 3, cellphone, refrigeration cycle, sensor, safety

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Ahrary, Alireza, Yoshinori Kawamura, and Masumi Ishikawa. "An Automated Intelligent Fault Detection System for Inspection of Sewer Pipes." IEEJ Transactions on Electronics, Information and Systems 127, no. 6 (2007): 943–50. http://dx.doi.org/10.1541/ieejeiss.127.943.

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Lv, Jianbing, Weijun Wu, Xiaoyu Kang, Juan Huang, Gongfa Chen, Shuai Teng, and Hejie Gao. "Automatic Classification System of Drainage Hole Blockage Based on Convolution Neural Network Transfer Learning." Advances in Civil Engineering 2022 (July 15, 2022): 1–16. http://dx.doi.org/10.1155/2022/4928018.

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The blockage or failure of the drainage holes will endanger the stability of the slopes and traffic safety of a highway tunnel. This paper studies an algorithm for the automatic classification of drainage hole blockage degree based on convolutional neural network transfer learning to explore the intelligent detection method of drainage hole blockage. The model transfer method is adopted to input drainage hole image samples to retrain the pretrained network to classify new images. Experiments are performed on the collected samples of drainage hole images, and the accuracy of different network models is compared, ResNet-18 being the best. The ResNet-18 performance is compared using different transfer strategies and parameters. The results show that when the SGDM gradient optimisation algorithm is used and the learning rate is 0.0001, the identification effect of these samples is the best. The validation accuracy can reach 91.7%, test accuracy is 90.0%, and the effective classification of drainage hole blockage to different degrees is realised under the transfer learning strategy of ResNet-18 model 1–34 frozen layers. Furthermore, with an expansion of the samples in the future, the identification accuracy will be further improved. The automatic classification system of the blockage degree of drainage hole greatly reduces the cost of manual detection, plays a guiding role in the maintenance of drainage pipes, and effectively improves the safety of highway tunnels and slopes.

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Henderson, Zach, and Justin deMello. "A Happy Marriage? Leveraging Sewer System Evaluation Surveys and Illicit Discharge Detection and Elimination for Sewer and Drain Collection System Best Management." Proceedings of the Water Environment Federation 2016, no. 10 (January 1, 2016): 2322–33. http://dx.doi.org/10.2175/193864716819707698.

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Kim, Sanghyun. "Multiple Discrete Blockage Detection Function for Single Pipelines." Proceedings 2, no. 11 (August 3, 2018): 582. http://dx.doi.org/10.3390/proceedings2110582.

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This work presents a platform for efficient representation in the frequency domain of multiple partial blockages in a single pipeline. Blockage detection studies were explored to calibrate the location and size of partial blockages using pressure variation induced by each blockage. To obtain feasible expressions for complicated analytical formulas of multiple partial blockages, an alternative formula is proposed for use in a reservoir pipeline valve system. The validity of the alternative formula was checked by comparing impedance distributions produced by it, with those of existing approaches. The new formula was validated and tested in terms of model parsimony.

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Yao, Jiang, Zhiqiang Wang, Chunhui Liu, Guichen Huang, Qingbo Yuan, Kai Xu, and Wenhui Zhang. "Detection Method of Crushing Mouth Loose Material Blockage Based on SSD Algorithm." Sustainability 14, no. 21 (November 3, 2022): 14386. http://dx.doi.org/10.3390/su142114386.

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With the advancement of smart mines technology, unmanned and Shojinka have received widespread attention, among which unattended crushing station is one of the research directions. To realize unattended crushing station, first of all, it is necessary to detect loose material blockage at the crushing mouth. Based on deep learning (DL) and machine vision (MV) technology, an on-line detection method is studied to trace the blockage in a swift and accurate manner, so that the corresponding detection system can be designed accordingly. The charge coupled device (CCD) industrial camera set above the crushing mouth is used to collect images and input them to the edge computing equipment. The original Single Shot MultiBox Detector (SSD) preprocessing model is trained and optimized before it is combined with the MV technology to detect and then the MV technology is combined to detect whether the crushing mouth is covered. In Ansteel Group GUANBAOSHAN mine, the accuracy of recognition and detection system with human observation was examined for one month, and the tested accuracy is 95%. The experimental results show that the proposed method can detect the crushing mouth blockage in real time, which would solve the problem that the blockage can only be identified by human eyes in traditional method, and provides basic support for the unattended crushing station.

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Beheshti, M., and S. Sægrov. "Detection of extraneous water ingress into the sewer system using tandem methods – a case study in Trondheim city." Water Science and Technology 79, no. 2 (January 15, 2019): 231–39. http://dx.doi.org/10.2166/wst.2019.057.

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Abstract Infiltration and inflow (I/I) of extraneous water in separate sewer systems are serious concerns in urban water management for their environmental, social and economic consequences. Effective reduction of I/I requires knowing where excess water ingress and illicit connections are located. The present study focuses on I/I detection in the foul sewer network of a catchment in Trondheim, Norway, during a period without snowmelt or groundwater infiltration. Fiber-optic distributed temperature sensing (DTS) was used for the first time in Norway to detect I/I sources in tandem with closed-circuit television inspection (CCTV) and smoke testing. DTS was an accurate and feasible method for I/I detection, though it cannot identify exact types of failure and sources of I/I. Therefore, other complementary methods must be used, e.g. CCTV or smoke testing. However, CCTV was not completely useful in confirming the DTS results. This study provides practical insights for the rehabilitation and repair of sewer networks that suffer from the undesirable I/I of extraneous water.

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Vorkamp, Katrin, Bettina S. Haas, and Reimer Herrmann. "Development of passive samplers for the detection of chlorinated hydrocarbons in sewers." Water Science and Technology 37, no. 1 (January 1, 1998): 311–18. http://dx.doi.org/10.2166/wst.1998.0073.

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In this work a system of passive samplers was developed to examine volatile chlorinated hydrocarbons in the gas phase of sewer systems. The adsorption kinetics of chloroform, trichloroethylene and perchlor-ethylene on the adsorption materials Tenax TA, Amberlite XAD-2, Activated Charcoal, Carbosieve S-III and Carboxen-553 were surveyed in laboratory experiments. The highest values of recovery were found for Tenax TA. Further experiments were conducted, regarding the influence of different temperatures. The only significant deviation from the reference kinetics was observed at a temperature as low as 4°C. In order to examine sewer gases a stainless steel sampling system was designed which contained six glass cartridges filled with Tenax TA, and which could be fixed to th steps in the manholes. Using this system, samples were taken at seven locations within the sewer network of Bayreuth, a medium-sized town with little industry, in order to optimise the period of sampling. At least one of the three compounds could be detected at six locations within one week of sampling. An amount of perchloroethylene which exceeded all other results by two orders of magnitude indicated the large adsorption capacity of the chosen material Tenax TA. A linear decrease with increasing height above the waste water table was found; furthermore the sampling device was proved suitable for the localisation of sources of discharge.

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Kadam, Mr Suraj Nivas. "Design of Automatic Barrier Detection and Blockage Removing System in Sowing Machine." International Journal for Research in Applied Science and Engineering Technology 9, no. VI (June 30, 2021): 4863–67. http://dx.doi.org/10.22214/ijraset.2021.36018.

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This paper presents the idea of the automatic system which detects and removes the blockages automatically in the pipes of seeder machine or sowing machine. This automatic system is very useful for many farmers. As increase in the technology, all the sector needs automation in every system. In current generation most of countries do not have sufficient manpower specially in agriculture sector. So there is need to develop equipment which will reduce the efforts of farmers. This system introduces a control mechanism which aims to detect blockages in the pipes of sowing machine and automatic removal of it by developing mechanism. Objective of this system is to develop a totally automated system for seed sowing process. Hence by replacing a manual system, develop a secure, reliable and efficient system.

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Duan, Huan-Feng, Pedro J. Lee, Mohamed S. Ghidaoui, and Yeou-Koung Tung. "Extended Blockage Detection in Pipelines by Using the System Frequency Response Analysis." Journal of Water Resources Planning and Management 138, no. 1 (January 2012): 55–62. http://dx.doi.org/10.1061/(asce)wr.1943-5452.0000145.

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Zhang, Xiang Lin. "Design of a Preventive Clearing Blocked System Using PLC Control." Applied Mechanics and Materials 556-562 (May 2014): 1290–93. http://dx.doi.org/10.4028/www.scientific.net/amm.556-562.1290.

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Film coating machine by way of spraying the coating solution onto the drug is in a continuous rolling surface. The tablet tends to produce tape smaller even if the spray flow blockage. Then the tablet will crack due to high temperature. Therefore, pharmaceutical tablet coating spray flow rate is a key factor affecting the quality. This article first proposes preventive clearing blocked in the pipeline but not blocking the upcoming clogged. Air purge starts immediately. PLC real-time acquisition is carried out by the pressure at both ends of the pipeline, the pipeline flow liquid contents, when the pressure is detected. The flow reaches a critical point obtained by BP network training, immediately starting the high-pressure air purge. The value of real-time detection uses PLC gun pipeline pressure, flow, etc. It combined weights of the neural element BP neural network model that was trained by the PLC programming. Gun pipe blockage and promptly started high pressure alarm air purge, preventive clearing blocked. Experiments show that preventive clearing blocked pipe blockage can promptly remove the gun.

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Lund, N. S. V., J. K. Kirstein, H. Madsen, O. Mark, P. S. Mikkelsen, and M. Borup. "Feasibility of using smart meter water consumption data and in-sewer flow observations for sewer system analysis: a case study." Journal of Hydroinformatics 23, no. 4 (May 3, 2021): 795–812. http://dx.doi.org/10.2166/hydro.2021.166.

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Abstract Globally, smart meters measuring the water consumption with a high temporal resolution at consumers' households are deployed at an increasing rate. In addition to their use for billing or leak detection purposes, smart meters may provide detailed knowledge of the wastewater inflow to the sewer systems in space and time and open up new types of system analyses aimed at closing the urban water balance. In this study, we first validate the smart meter data against other, independent water distribution data. Subsequently, we use a detailed hydrodynamic sewer system model to link the smart meter data from almost 2,000 consumers with in-sewer flow observations in order to simulate the wastewater component of the dry weather flow (DWF) and to identify potential anomalies. Results show that it is feasible to use smart meter data as input to a distributed urban drainage model, as the temporal dynamics of the model results and in-sewer flow observations match well. Furthermore, the study suggests that in-sewer flow observations may be subject to unrecognised uncertainties, which make them unsuitable for advanced investigations of the DWF composition, and this underlines the necessity of collecting data from independent sources. The study also exemplifies that digital system integration in the water sector may be complicated. However, overcoming these obstacles may improve both offline and real-time urban drainage management.

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Kessili, Abdelhak, Jes Vollertsen, and Asbjørn Haaning Nielsen. "Automated monitoring system for events detection in sewer network by distribution temperature sensing data measurement." Water Science and Technology 78, no. 7 (October 1, 2018): 1499–508. http://dx.doi.org/10.2166/wst.2018.425.

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Abstract This study is related to distribution temperature sensing (DTS) in sewers for tracing illicit or unintended inflows to foul sewers. A DTS measurement is performed with a fiber optic cable that is installed at the invert of a sewer pipe in combination with a standalone laser/computer instrument. This set-up generates in-sewer temperature measurements with high resolutions in time (every minute) and space (every metre) along the cable over long periods of time (weeks on end). The prolonged monitoring period in combination with the high level of detail in the dataset allows the study of anomalies (i.e., unexpected temperatures and/or temperature variations at certain locations), even if these only occur very infrequently. The objective of this paper is to develop an automated tool to analyze the large data masses and identify anomalies caused by illicit or unintended inflows. In this study, an algorithm for detecting the temperature changes that are caused by both wastewater discharge and inflow of stormwater are developed. A comparison of the results of the automated procedure to the results of a manual assessment of the datasets (Elmehaven, Denmark) shows that the automated procedure performs very well.

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Xu, Yunzhi, Shuai Chen, Jingyi Qiao, and Jinhao Xu. "Defect Defection for Intelligent Sewer Inspection with Multi-Label Classification." Applied and Computational Engineering 1, no. 1 (May 5, 2022): 31–36. http://dx.doi.org/10.54254/ace.2022004.

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The sewerage system is held as an important part of city infrastructure, while the pipeline inspection technology based on closed-circuit television system (CCTV) is still offline and by human. This paper focus on the research topic of defect detection for intelligent sewer inspection with multi-label classification. We first use the image preprocessing methods to get the unified datasets, then deploy the framework of deep learning, and propose a multi-label classification method for defect detection. The experimental results show that our approach is a scalable and efficient method, and it will be used in the application systems.

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KaziTani, Nabil. "A Combined Probabilistic Approach for Natural Hazards Assessment of Soil-Sewer Pipes (S-SP) Systems." E3S Web of Conferences 150 (2020): 03019. http://dx.doi.org/10.1051/e3sconf/202015003019.

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The structural failure prediction of underground sewer pipes systems seems very complicated due to the natural hazards of soils in which these elements are buried. The apparition of first cracks and notches in sewer pipes parts is governed by the interaction model of soil-sewer pipes system (S-SP)parameters mainly, the constitutive material laws of soil and sewer pipe materials. The detection of critical sections where the structural damages are highly probable is the focus point of this present study. Based on probabilistic analysis of stochastic modelling results (Monte Carlo Method) of random soil properties, the mechanical behaviour of a part of sewer pipe is analysed in terms of settlements and flexural stress distribution fluctuations. A parametric study is performed to quantify the effect of correlation length (Lc) and soils types on the structural reliability of underground sewer pipes. This current structural analysis offers to engineers and researchers a useful numerical tool in order to allow them the well understanding of the structural behaviour of buried sewer pipes by considering the spatial variability of soil geo-mechanical characteristics which reflects the soil natural process of formation, its aggregation and heterogeneity. The obtained numerical results show that the probabilistic analysis of the spatial variability of soil properties into structure numerical modelling of sewer pipes presents an accurate approach for the prediction of structural responses of waste water transportation infrastructures particularly, if the sewer pipe lengths are relatively significant and buried into several classes of soils along sewer pipe networks.

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Tsai, Hao-Hung, Chiun-Li Chin, and Yung-Chih Cheng. "INTELLIGENT PULMONARY EMBOLISM DETECTION SYSTEM." Biomedical Engineering: Applications, Basis and Communications 24, no. 06 (December 2012): 471–83. http://dx.doi.org/10.4015/s1016237212500433.

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Pulmonary embolism (PE) is a blockage of the main artery of the lung or one of its branches by a substance that has travelled from elsewhere in the body through the bloodstream. Most of the traditional PE detection methods depend on the professional physician's judgment. Serious PE will lead to death. Therefore, diagnosis of PE is very important. In this paper, we develop an automatic PE detection system for relieving doctor's load. It is divided into five parts — preprocessing, finding pulmonary, vessel searching, vessel tracking and evaluation. In the finding pulmonary part, we use active contour model (ACM) to extract pulmonary area. Next, we use cubic curve contrast enhancement method to enhance the contrast of branch vessel image. Its objective is to highlight the embolism area in the branch vessel. And, in the main vessel searching, we employ k-means algorithm and Gaussian mixture model (GMM) to find the main vessel part. Moreover, we propose an effective vessel tracking method to achieve vessel tracking. Finally, we invite three radiologists to help us evaluate the performance of our proposed system and to obtain the ground truth image of our system. We can calculate the precision rate of our system according to these ground truth images. The experimental results show that a total of 62 false positives were obtained for the 16 cases. It means that the ratio of FP/DS is 3.875. At 3.875 FP/DS, the classification successful rate of our system is about 83% in main vessel detection and 82.6% precision rate in branch vessel detection. Finally, our system can relieve doctor's load according to the result of questionnaire analysis.

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Yin, Xianfei, Yuan Chen, Ahmed Bouferguene, Hamid Zaman, Mohamed Al-Hussein, and Luke Kurach. "A deep learning-based framework for an automated defect detection system for sewer pipes." Automation in Construction 109 (January 2020): 102967. http://dx.doi.org/10.1016/j.autcon.2019.102967.

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Zhu, Xuefeng, Zao Feng, Jiande Wu, and Weiquan Deng. "A Novel Feature Selection Based on VMD and Information Gain for Pipe Blockages." Applied Sciences 11, no. 22 (November 16, 2021): 10824. http://dx.doi.org/10.3390/app112210824.

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Targeting the challenge of determining the degree of blockage in buried pipelines and the difficulty of effectively extracting blockage features, a blockage detection method integrating variational mode decomposition (VMD) and information gain is proposed. Acoustic impulse response signals were obtained by deconvolving the output signals of the system, which were then subjected to VMD to obtain 12 components in different frequency ranges. Next, information gain (IG) was introduced to characterize the 12 components quantitatively, through which the components containing rich information about the pipe conditions were selected out. Meanwhile, sound pressure level conversion was performed on the selected components to amplify any changes in the sound field. Finally, the root mean square entropy (RMSE) was calculated to constitute the feature eigenvectors, which were input into Random Forests (RF) classifier for defect identification of pipeline. As the experimental results demonstrate, the proposed method is capable of determining the degree of blockage effectively in the running state. Meanwhile, it can also eliminate the interference of functional parts such as lateral connections during the identification process, thereby improving the identification accuracy. The present study has shown both theoretical significance and application value in the field of defect detection and recognition.

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Lin, Junran, Cuimei Yang, Yi Lu, Yuxing Cai, Hanjie Zhan, and Zhen Zhang. "An Improved Soft-YOLOX for Garbage Quantity Identification." Mathematics 10, no. 15 (July 28, 2022): 2650. http://dx.doi.org/10.3390/math10152650.

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Urban waterlogging is mainly caused by garbage clogging the sewer manhole covers. If the amount of garbage at a sewer manhole cover can be detected, together with an early warning signal when the amount is large enough, it will be of great significance in preventing urban waterlogging from occurring. Based on the YOLOX algorithm, this paper accomplishes identifying manhole covers and garbage and building a flood control system that can automatically recognize and monitor the accumulation of garbage. This system can also display the statistical results and send early warning information. During garbage identification, it can lead to inaccurate counting and a missed detection if the garbage is occluded. To reduce the occurrence of missed detections as much as possible and improve the performance of detection models, Soft-YOLOX, a method using a new detection model for counting, was used as it can prevent the occurrence of missed detections by reducing the scores of adjacent detection frames reasonably. The Soft-YOLOX improves the accuracy of garbage counting. Compared with the traditional YOLOX, the mAP value of Soft-YOLOX for garbage identification increased from 89.72% to 91.89%.

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Jafari, Raheleh, Sina Razvarz, Cristóbal Vargas-Jarillo, and Alexander Gegov. "Blockage Detection in Pipeline Based on the Extended Kalman Filter Observer." Electronics 9, no. 1 (January 1, 2020): 91. http://dx.doi.org/10.3390/electronics9010091.

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Currently numerous approaches with various applicability have been generated in order to detect damage in pipe networks. Pipeline faults such as leaks and partial or complete blockages usually create serious problems for engineers. The model-based leak, as well as block detection methods for the pipeline systems gets more and more attention. Among these model-based methods, the state observer and state feedback based methods are usually used. While the observability, as well as controllability, are taken to be the prerequisites for utilizing these techniques. In this work, a new technique based on the extended Kalman filter observer is proposed in order to detect and locate the blockage in the pipeline. Furthermore, the analysis of observability and controllability in the pipe networks is investigated. Important theorems are given for testing the observability as well as controllability of the pipeline system.

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Pernía, Alberto M., Héctor Andrés Mayor, Miguel J. Prieto, Pedro J. Villegas, Fernando Nuño, and Juan A. Martín-Ramos. "Magnetostrictive Sensor for Blockage Detection in Pipes Subjected to High Temperatures." Sensors 19, no. 10 (May 24, 2019): 2382. http://dx.doi.org/10.3390/s19102382.

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The use of solar thermal power plants is considered a cost-effective alternative to produce renewable energy. Unlike other energy installations, in this type of plants the transfer and storage of energy has been solved by using molten salts. These salts run between two tanks through the steam generation system that feeds the turbine. Although the use of salts as a heat transfer fluid is considered an adequate solution, they are not without problems. One of them is the formation of blockages in the pipes due to a partial solidification of the salt, which leads to the shutdown of the installation, with the consequent economic losses. Fast location of these blockages in a minimally intrusive way is the objective pursued in this work. The method to achieve this is based on the use of a new magnetostrictive sensor that simplifies previous designs.

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Ma, Duo, Jianhua Liu, Hongyuan Fang, Niannian Wang, Chao Zhang, Zhaonan Li, and Jiaxiu Dong. "A Multi-defect detection system for sewer pipelines based on StyleGAN-SDM and fusion CNN." Construction and Building Materials 312 (December 2021): 125385. http://dx.doi.org/10.1016/j.conbuildmat.2021.125385.

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Halfawy, Mahmoud R., and Jantira Hengmeechai. "Integrated Vision-Based System for Automated Defect Detection in Sewer Closed Circuit Television Inspection Videos." Journal of Computing in Civil Engineering 29, no. 1 (January 2015): 04014024. http://dx.doi.org/10.1061/(asce)cp.1943-5487.0000312.

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Sun, Jilong, Ronghe Wang, and Huan-Feng Duan. "Multiple-fault detection in water pipelines using transient-based time-frequency analysis." Journal of Hydroinformatics 18, no. 6 (July 28, 2016): 975–89. http://dx.doi.org/10.2166/hydro.2016.232.

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Pipe faults, such as leakage and blockage, commonly exist in water pipeline systems. It is essential to identify and fix these failures appropriately in order to reduce the risk of water pollution and enhance the security of water supply. Recently, transient-based detection methods have been developed for their advantages of non-intrusion, efficiency and economics compared to traditional methods. However, this method is so far limited mainly to simple pipelines with a single known type of pipe fault in the system. This paper aims to extend the transient-based method to multiple-fault detection in water pipelines. For this purpose, this study introduced an efficient and robust method for transient pressure signal analysis – a combination of the empirical mode decomposition and Hilbert transform – in order to better identify and detect different anomalies (leakage, blockage and junction) in pipelines. To validate the proposed transient-based time-frequency analysis method, laboratory experimental tests were conducted in this study for a simple pipeline system with multiple unknown types of pipe faults including leakages, blockages and junctions. The preliminary test results and analysis indicate that multiple pipe faults in simple pipelines can be efficiently identified and accurately located by the proposed method.

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Feng, Chaofan, Marilena Giglio, Biao Li, Angelo Sampaolo, Pietro Patimisco, Vincenzo Spagnolo, Lei Dong, and Hongpeng Wu. "Detection of Hydrogen Sulfide in Sewer Using an Erbium-Doped Fiber Amplified Diode Laser and a Gold-Plated Photoacoustic Cell." Molecules 27, no. 19 (October 1, 2022): 6505. http://dx.doi.org/10.3390/molecules27196505.

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A photoacoustic detection module based on a gold-plated photoacoustic cell was reported in this manuscript to measure hydrogen sulfide (H2S) gas in sewers. A 1582 nm distributed feedback (DFB) diode laser was employed as the excitation light source of the photoacoustic sensor. Operating pressure within the photoacoustic cell and laser modulation depth were optimized at room temperature, and the long-term stability of the photoacoustic sensor system was analyzed by an Allan-Werle deviation analysis. Experimental results showed that under atmospheric pressure and room temperature conditions, the photoacoustic detection module exhibits a sensitivity of 11.39 μV/ppm of H2S and can reach a minimum detection limit (1σ) of 140 ppb of H2S with an integration time of 1 s. The sensor was tested for in-field measurements by sampling gas in the sewer near the Shanxi University canteen: levels of H2S of 81.5 ppm were measured, below the 100 ppm limit reported by the Chinese sewer bidding document.

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Journal articles on the topic 'Sewer blockage detection system'

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