An Improved Vibration Analysis Algorithm as a Diagnostic Tool for Detecting Mechanical Anomalies on Power Circuit Breakers

Landry, M.; Léonard, François; Landry, Christian R.; Beauchemin, R.; Turcotte, O.; Brikci, F.

doi:10.1109/tpwrd.2008.2002846

Cited by 73 publications

(48 citation statements)

References 13 publications

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“…Three types of mechanical fault signals were collected in a field experiment on a real HVCB: (1) jam fault of the iron core (fault type I); (2) lack of mechanical lubrication (fault type II); (3) base screw looseness (fault type III). As shown in Figure 1, the starting time of fault type I and fault type II lags behind the normal signal in different degrees.…”

Section: Analysis Of the Results Obtained By The Lmd Methodsmentioning

confidence: 99%

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Mechanical Fault Diagnosis of High Voltage Circuit Breakers with Unknown Fault Type Using Hybrid Classifier Based on LMD and Time Segmentation Energy Entropy

Huang

Fang

Cai

et al. 2016

Entropy

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Abstract:In order to improve the identification accuracy of the high voltage circuit breakers' (HVCBs) mechanical fault types without training samples, a novel mechanical fault diagnosis method of HVCBs using a hybrid classifier constructed with Support Vector Data Description (SVDD) and fuzzy c-means (FCM) clustering method based on Local Mean Decomposition (LMD) and time segmentation energy entropy (TSEE) is proposed. Firstly, LMD is used to decompose nonlinear and non-stationary vibration signals of HVCBs into a series of product functions (PFs). Secondly, TSEE is chosen as feature vectors with the superiority of energy entropy and characteristics of time-delay faults of HVCBs. Then, SVDD trained with normal samples is applied to judge mechanical faults of HVCBs. If the mechanical fault is confirmed, the new fault sample and all known fault samples are clustered by FCM with the cluster number of known fault types. Finally, another SVDD trained by the specific fault samples is used to judge whether the fault sample belongs to an unknown type or not. The results of experiments carried on a real SF 6 HVCB validate that the proposed fault-detection method is effective for the known faults with training samples and unknown faults without training samples.

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Section: Analysis Of the Results Obtained By The Lmd Methodsmentioning

confidence: 99%

“…Mechanical faults are the main reasons that affect the reliability of HVCBs [1][2][3][4][5]. It is therefore necessary to carry out the research on the diagnosis method of HVCB mechanical faults in order to ensure the safe and stable running of the power system.…”

Section: Introductionmentioning

confidence: 99%

Mechanical Fault Diagnosis of High Voltage Circuit Breakers with Unknown Fault Type Using Hybrid Classifier Based on LMD and Time Segmentation Energy Entropy

Huang

Fang

Cai

et al. 2016

Entropy

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“…(3). Because ADAMS is good for the parasolid file format identification, after importing file will correctly identify each component and related information, therefore, the complete assembly in the UG after should be saved as the parasolid file name extension, research on Simulation of the motion characteristic of contactor to easily import in ADAMS environment [12].…”

Section: The Design Processmentioning

confidence: 99%

Dynamic Simulation of AC Contactor Operating Mechanism

Zhang¹,

Li²

2014

TOMEJ

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Unigraphics NX (UG NX) software is mechanical engineering aided design system development America UGS a set of CAD / CAM / CAE in one. UG originated in USA McDonnell Douglas Aircraft Company, later merged in 1991 into the world's largest software company --EDS. Widely used in electronics, aviation, automobile, household appliances, toys and other industries. By modeling the characteristics of UG based entity, has the dimension driven editing and unified database. The core of parasolid provides powerful modeling software and seamless data conversion ability, digital model of UG established capable of data conversion in a variety of software, and provides convenience for data exchange.Keywords: CAD/CAE/CAM software, CJX2-40 type AC contactor, dynamic simulation ESTABLISHING THE VIRTUAL PROTOTYPING OF CONTACTOR MECHANICAL SYSTEMThe modeling features of UG: UG provides a very flexible composite modeling methods, it realizes the association and shared between all relevant and digital entity modeling data for users to edit graphics is very convenient. Such as solid modeling (Solid), surface modeling (Surface), the wire frame modeling (Wireframe), feature modeling and realistic photographic powerful rendering [1], animation and rapid prototyping tool based on. The user can mix various modeling method according to actual needs, fully display its superiority modeling, UG users can quickly and accurately the tolerance feature will feature information of tolerance and geometric objects associated, so that you can on the assembly model analysis.UG software in the design of software has a great advantage in the aspect of modeling, management and development. Through the software understanding, general characteristics are: desktop style is very simple; the main model can conveniently inquire into the parameter expression; tree management style history, can easily query to the entire modeling step; a strong hint function for modeling process, every step has clear indication; software has development, provides two times the development of means, provides convenience to meet different needs of enterprises [2].Unigraphics works in the product development the most competitive victory in the MACD industry, compared the characters and functions of UG, has many unique features, such as: Unigraphics provides a powerful programming framework, so that customers and suppliers of software applications can be developed with UG very good integration and complete relevant, personalized the program can continue to add users. In the machinery industry, the most closely to CAD/CAM/CAE integrated with PDM, the formation of the whole design, analysis, processing, management integration of a high level of software. In the extended enterprise customers the meaning of the data can be converted to each other, even including those input data is the problem of the high rate of success of intelligent conversion etc.. UG software into China for more than 20 years, has been widely recognized by Chinese enterprises, has become one of the main use...

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“…Vibration analysis is an effective signal-based approach of fault diagnosis [6]. Over the past decade, the vibration signatures generated during the operation of mechanical structure have been used for condition monitoring and fault diagnosis with good effects [7][8][9][10][11][12]. A HVCB's vibration signal is a typical non-stationary signal with strong transients.…”

Section: Introductionmentioning

confidence: 99%

“…A HVCB's vibration signal is a typical non-stationary signal with strong transients. The existing vibration signal processing methods such as short-time energy [7], dynamic time warping (DTW) [8], wavelet packet transform (WPT) [9] and empirical mode decomposition (EMD) [10,11] have all achieved good results in this area. However, these methods also have some disadvantages.…”

Section: Introductionmentioning

confidence: 99%

Mechanical Fault Diagnosis of High Voltage Circuit Breakers Based on Wavelet Time-Frequency Entropy and One-Class Support Vector Machine

Huang

Chen

Zhang

et al. 2015

Entropy

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Mechanical faults of high voltage circuit breakers (HVCBs) are one of the most important factors that affect the reliability of power system operation. Because of the limitation of a lack of samples of each fault type; some fault conditions can be recognized as a normal condition. The fault diagnosis results of HVCBs seriously affect the operation reliability of the entire power system. In order to improve the fault diagnosis accuracy of HVCBs; a method for mechanical fault diagnosis of HVCBs based on wavelet time-frequency entropy (WTFE) and one-class support vector machine (OCSVM) is proposed. In this method; the S-transform (ST) is proposed to analyze the energy time-frequency distribution of HVCBs' vibration signals. Then; WTFE is selected as the feature vector that reflects the information characteristics of vibration signals in the time and frequency domains. OCSVM is used for judging whether a mechanical fault of HVCBs has occurred or not. In order to improve the fault detection accuracy; a particle swarm optimization (PSO) algorithm is employed to optimize the parameters of OCSVM; including the window width of the kernel function and error limit. If the mechanical fault is confirmed; a support vector machine (SVM)-based classifier will be used to recognize the fault type. The experiments carried on a real SF 6 HVCB demonstrated the improved effectiveness of the new approach.

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An Improved Vibration Analysis Algorithm as a Diagnostic Tool for Detecting Mechanical Anomalies on Power Circuit Breakers

Cited by 73 publications

References 13 publications

Mechanical Fault Diagnosis of High Voltage Circuit Breakers with Unknown Fault Type Using Hybrid Classifier Based on LMD and Time Segmentation Energy Entropy

Mechanical Fault Diagnosis of High Voltage Circuit Breakers with Unknown Fault Type Using Hybrid Classifier Based on LMD and Time Segmentation Energy Entropy

Dynamic Simulation of AC Contactor Operating Mechanism

Mechanical Fault Diagnosis of High Voltage Circuit Breakers Based on Wavelet Time-Frequency Entropy and One-Class Support Vector Machine

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