Low-Cost Condition Monitoring System of Rotating Machinery Based on LabVIEW

2011 ◽  
Vol 474-476 ◽  
pp. 735-738
Author(s):  
Ya Jun Fan ◽  
Yu Guo ◽  
Chuan Hui Wu

In order to change the current status that machine condition monitoring system is only generally applied to key equipments of large-scaled and high-end business, a low-cost mini condition monitoring system of rotating machinery based on LabVIEW is proposed and designed in this paper. The system is not only of advantages of lower cost, stronger expandability and higher applicability, but also changes the condition that current systems emphasize too much on the comprehensiveness, universality and complexity. It is capable of meeting the wide range of condition monitoring of common rotating machinery, for faults diagnosis and predictive maintenance needs better, then, its potential application can be foreseen.

Author(s):  
Andrew P. Strong ◽  
Norman Sanderson ◽  
Gareth Lees ◽  
Arthur Hartog ◽  
Richard Twohig ◽  
...  

In this paper we describe a unique and innovative pipeline and flowline monitoring system which has been developed by Schlumberger in collaboration with BP. Applications of the system include pipeline/flowline integrity monitoring and overall optimization of the operation of the pipeline/flowline. Details of the pipeline condition monitoring system (PCMS) components are provided along with the results from comprehensive field trials. The system uses novel optical fibre distributed sensors to provide simultaneous distributed measurements of temperature, strain and vibration for the detection, monitoring, and location of events including: • Third Party Interference (TPI), including multiple simultaneous disturbances; • Geo-hazards and landslides; • Gas and oil leaks; • Permafrost protection. The system performs analysis of the combination of measurands to provide the operator with an event recognition and location capability allowing the most appropriate early response to be initiated. Through the use of newly developed remote, optically powered amplification, an unprecedented detection range of 100km is achieved without the need for any electronics and therefore remote power in the field. A system can thus monitor 200km when configured to monitor 100km in two directions from a single location. As well as detecting the external conditions leading to leaks, this fully integrated system provides a means of detecting and locating small leaks in gas pipelines below the threshold of present online leak detection systems based on monitoring flow parameters. Other benefits include the enhancement of the operator’s existing integrity management program and the potential for reductions in surveillance costs and HSE risks. In addition to onshore pipeline systems this combination of functionality and range is available for practicable monitoring in a wide range of other applications such as: • Long subsea flowlines; • Umbilicals; • Power cables; • Offshore riser systems; • Settlement in tank farms; • Facilities perimeter security. An important deliverable from this work includes the design and field testing of a bespoke optical sensor cable, designed to be sensitive to ground movement to allow distributed strain measurement whilst withstanding the rigors of the pipeline environment. In this paper, we describe the new optical sensing methods developed, and the results of the extensive field trials performed during 2007 and 2008 to fully evaluate and prove the system for use on long hydrocarbon transmission pipelines. Specifically, we demonstrate the detection of small gas releases, simulated earth movement and a number of different types of third party interventions at the full 100km target range.


Author(s):  
Wai Kit Wong ◽  
Chu Kiong Loo ◽  
Way Soong Lim

In this chapter, a new and effective quaternion based machine condition monitoring system using log-polar mapper, quaternion based thermal image correlator and max-product fuzzy neural network classifier is discussed. Two classification characteristics namely: peak to sidelobe ratio (PSR) and real to complex ratio of the discrete quaternion correlation output (?-value) are applied in the quaternion based machine condition monitoring system. Large PSR and ?-value are observed in case of a good match among correlation of the input thermal image with a particular reference image, while small PSR and ?-value are observed in case of a bad/not match among correlation of the input thermal image with a particular reference image. Some simulation results show that log-polar mapping actually help solving rotation and scaling invariant problems in quaternion based thermal image correlation. Log-polar mapping can help in smoothing the output correlation plane, and hence it provides a better way for measuring PSR and ?-values. Results also show that quaternion based machine condition monitoring system is an efficient machine condition monitoring system with accuracy more than 98%.


2021 ◽  
Author(s):  
Hidekazu Fukai ◽  
Frederico Soares Cabral ◽  
Fernao A. L. Nobre Mouzinho ◽  
Vosco Pereira ◽  
Satoshi Tamura

In developing countries like Timor-Leste, regular road condition monitoring is a significant subject not only for maintaining road quality but also for a national plan of road network construction. The sophisticated equipment for road surface inspection is so expensive that it is difficult to introduce them in developing countries, and the monitoring is usually achieved by manual operation. On the other hand, the utilization of ICT devices such as smartphones has gained much attention in recent years, especially in developing countries because the penetration rate of the smartphone is remarkably increasing even in developing countries. The smartphones equip various high precision sensors, i.e., accelerometers, gyroscopes, GPS, and so on, in the small body in low price. In this project, we are developing an integrated road condition monitoring system that consists of smartphones, dashcams, and a server. There are similar trials in advanced countries but not so many in developing countries. This system assumes to be used in developing countries. The system is very low cost and does not require trained specialists in the field side. The items that are automatically inspected in this system were carefully selected with the local ministry of public works and include paved and unpaved classification, road roughness, road width, detection and size estimation of potholes, bumps, etc., at present. All the inspected items are visualized in Google Maps, Open Street Map, or QGIS with GPS information. The survey results are collected on a server and updated to more accurate values by the repeated surveys. On the analysis, we use several state-of-the-art machine learning and deep learning techniques. In this paper, we summarize related works and introduce this project’s target and framework, which especially focused on the developing countries, and achievements of each of our tasks.


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