scholarly journals Two-Level Fault Diagnosis of SF6 Electrical Equipment Based on Big Data Analysis

2019 ◽  
Vol 3 (1) ◽  
pp. 4
Author(s):  
Hongxia Miao ◽  
Heng Zhang ◽  
Minghua Chen ◽  
Bensheng Qi ◽  
Jiyong Li
Keyword(s):  
Fault Diagnosis ◽  
Operating Time ◽  
Electrical Equipment ◽  
Monitoring Data ◽  
Practical Significance ◽  
Massive Data ◽  
Sulphur Hexafluoride ◽  
Mapreduce Framework ◽  
Hadoop Platform ◽  
Insulation Performance

With the increase of the operating time of sulphur hexafluoride (SF6) electrical equipment, the different degrees of discharge may occur inside the equipment. It makes the insulation performance of the equipment decline and will cause serious damage to the equipment. Therefore, it is of practical significance to diagnose fault and assess state for SF6 electrical equipment. In recent years, the frequency of monitoring data acquisition for SF6 electrical equipment has been continuously improved and the scope of collection has been continuously expanded, which makes massive data accumulated in the substation database. In order to quickly process massive SF6 electrical equipment condition monitoring data, we built a two-level fault diagnosis model for SF6 electrical equipment on the Hadoop platform. And we use the MapReduce framework to achieve the parallelization of the fault diagnosis algorithm, which further improves the speed of fault diagnosis for SF6 electrical equipment.

scholarly journals Fault Diagnosis of Brake Train Based on Multi-Sensor Data Fusion

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4370
Author(s):  
Yongze Jin ◽  
Guo Xie ◽  
Yankai Li ◽  
Xiaohui Zhang ◽  
Ning Han ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Expectation Maximization ◽  
Monitoring Data ◽  
Sensor Data ◽  
Operating Environment ◽  
Mass Model ◽  
Multi Sensor Data Fusion ◽  
Diagnosis Method ◽  
Single Mass ◽  
Parameter Identifications

In this paper, a fault diagnosis method is proposed based on multi-sensor fusion information for a single fault and composite fault of train braking systems. Firstly, the single mass model of the train brake is established based on operating environment. Then, the pre-allocation and linear-weighted summation criterion are proposed to fuse the monitoring data. Finally, based on the improved expectation maximization, the braking modes and braking parameters are identified, and the braking faults are diagnosed in real time. The simulation results show that the braking parameters of systems can be effectively identified, and the braking faults can be diagnosed accurately based on the identification results. Even if the monitoring data are missing or abnormal, compared with the maximum fusion, the accuracies of parameter identifications and fault diagnoses can still meet the needs of the actual systems, and the effectiveness and robustness of the method can be verified.

Fault Diagnosis Method for a Network Control System with Long-Time Delay and Data Packet Loss Based on H∞ Filtering

2013 ◽  
Vol 846-847 ◽  
pp. 795-798
Author(s):  
Jiao Meng ◽  
Qi Hua Xu ◽  
Xiao Xiao
Keyword(s):  
Control System ◽  
Fault Diagnosis ◽  
Time Delay ◽  
Packet Loss ◽  
Estimation Error ◽  
Network Control ◽  
Data Packet ◽  
Practical Significance ◽  
Network Control System ◽  
Long Time

Improving network control system---NCS reliability and safety has important practical significance because NCS is a hot research subject in these years. Fault diagnosis methods are researched in this paper according to NCS with long-time delay and data packet loss. Firstly, given a NCS with long-time delay, a state observer is structured. Secondly, make the state estimation error equation equivalent to an asynchronous dynamical system having event incidence constraint according to whether the system having data packets loss. The problem of fault diagnosis is converted to filtering problem through structuring filtering residual system based on the observer, then giving a corresponding filter designing algorithm. The designed fault diagnosis filter system not only make sure the stability of the closed loop system but also make the residual systems norm less than given reduction level. Finally, the simulation results prove that the algorithm can diagnose faults effectively.

Diagnosis Rule Discovery Based on Causality in the Context of Fault Diagnosis in Rotating Machinery

2014 ◽  
Vol 532 ◽  
pp. 113-117
Author(s):  
Zhou Jin ◽  
Ru Jing Wang ◽  
Jie Zhang
Keyword(s):  
Fault Diagnosis ◽  
General Framework ◽  
Complex Structure ◽  
Rotating Machinery ◽  
Massive Data ◽  
Formal Definition ◽  
Rule Discovery ◽  
Rule Based ◽  
Simple Implementation ◽  
Definition Of

The rotating machineries in a factory usually have the characteristics of complex structure and highly automated logic, which generated a large amounts of monitoring data. It is an infeasible task for uses to deal with the massive data and locate fault timely. In this paper, we explore the causality between symptom and fault in the context of fault diagnosis in rotating machinery. We introduce data mining into fault diagnosis and provide a formal definition of causal diagnosis rule based on statistic test. A general framework for diagnosis rule discovery based on causality is provided and a simple implementation is explored with the purpose of providing some enlightenment to the application of causality discovery in fault diagnosis of rotating machinery.

A Design Method of Rain Test Device Based on Water Drop Motion Simulation

2013 ◽  
Vol 871 ◽  
pp. 363-368
Author(s):  
Hong Tao Zeng ◽  
Lin Lin Lin ◽  
Cong Feng ◽  
Zhi Huai Xiao
Keyword(s):  
Design Method ◽  
Water Drop ◽  
Electrical Equipment ◽  
Simulation Software ◽  
Test Device ◽  
Rainy Weather ◽  
Drop Motion ◽  
Water Drops ◽  
Motion Characteristics ◽  
Insulation Performance

In order to measure the electric insulation performance of the electrical equipment in rainy weather, its essential to design a rain device to simulate different conditions of rainfall. In this paper, a motion model of raindrop sprayed by the rain device and differential equations describing its motion characteristics are built. Basing on the analysis of water drop motion, a set of simulation software is developed for the selection of rain test device and the analysis of test results. The software can simulate the water drops motion process from nozzle to test equipment, and the simulation results is almost the same with field test, so the simulation software provides the basis for the design of rain test device.

Maintenance of Power Equipment System Based on the Methods of Diagnosis and Control of Technical Condition

2018 ◽  
pp. 421-448 ◽  
Author(s):  
Dmitry Strebkov ◽  
Alexey Nekrasov ◽  
Anton Nekrasov
Keyword(s):  
Operating Time ◽  
Electrical Equipment ◽  
Technical Condition ◽  
Spare Parts ◽  
Actual Condition ◽  
Power Equipment ◽  
Service Strategy ◽  
Electrical Systems ◽  
Preventive Actions ◽  
Equipment System

Maintenance of the power equipment system is based on the industry standard of averaged volumes of standard maintenance and repair of power equipment, frequency and duration of the preventive measures, the nomenclature and consumption of materials and spare parts to perform operations. One of the more efficient uses of electrical equipment is to improve its maintenance system through the development and implementation of service strategies for the actual condition. The work proved the necessary conditions for the realization of electric service strategy on defining the main diagnostic parameter. The general mathematical model is proposed to implement the service strategy. The model is based on a study of basic parameters using random monotone normal type of process and diagnostic controlled parameter with three discrete product states (working, the state of preventive actions, and failure) and continuous operating time. The results of studies of the new techniques development for improving the operation of electrical systems are presented.

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