Research on transformer vibration monitoring and diagnosis based on Internet of things

2021 ◽  
Vol 30 (1) ◽  
pp. 677-688
Author(s):  
Zhenzhuo Wang ◽  
Amit Sharma
Keyword(s):  
Internet Of Things ◽  
Power Distribution ◽  
Vibration Analysis ◽  
Vibration Monitoring ◽  
Power Transformers ◽  
Normal Operation ◽  
Analysis Method ◽  
Power Distribution Network ◽  
Monitoring And Diagnosis ◽  
Distribution Transformers

Abstract A recent advent has been seen in the usage of Internet of things (IoT) for autonomous devices for exchange of data. A large number of transformers are required to distribute the power over a wide area. To ensure the normal operation of transformer, live detection and fault diagnosis methods of power transformers are studied. This article presents an IoT-based approach for condition monitoring and controlling a large number of distribution transformers utilized in a power distribution network. In this article, the vibration analysis method is used to carry out the research. The results show that the accuracy of the improved diagnosis algorithm is 99.01, 100, and 100% for normal, aging, and fault transformers. The system designed in this article can effectively monitor the healthy operation of power transformers in remote and real-time. The safety, stability, and reliability of transformer operation are improved.

Research on mechanism configuration and coordinated control for power distribution network live working robot

2020 ◽  
Vol 47 (3) ◽  
pp. 453-462 ◽  
Author(s):  
Yu Yan ◽  
Wei Jiang ◽  
Dehua Zou ◽  
Wusheng Quan ◽  
Hong Jun Li ◽  
...  
Keyword(s):  
Power Distribution ◽  
Control Method ◽  
Distribution Network ◽  
Coordinated Control ◽  
Internal Force ◽  
Normal Operation ◽  
Power Distribution Network ◽  
Content Type ◽  
Field Operation ◽  
Closed Chain

Purpose In the long-term network operation, the power distribution network will be subjected to the effects of ultra-high voltage, strong electromagnetic interference and harsh natural environment on the power system, which will lead to the occurrence of different faults in the distribution network and directly affect the normal operation of the power grid. Design/methodology/approach The purpose of this study is to solve the problems of labor intensity, high risk and low efficiency of distribution network manual maintenance operation, this paper proposed a new configuration of the live working robot for distribution network maintenance, the robot is equipped with dual working arms through the mobile platform, which can realize the coordination movement, the autonomous reorganization and replacement of the end tools, respectively, so as the robot power distribution maintenance function such as stripping, trimming, wiring and the operation control problem of the distribution network-robot with small arms and in small operation space can be realized. Findings To effective elimination or reduce the adverse effects of the internal forces in the closed chain between the working object and manipulator under the typical task of the 10 kV distribution network, this paper has established the robot coordinated control dynamics model in the closed-chain between the dual-working object and proposed the dynamic distribution method of closed-chain internal force and the effectiveness has been proved by simulation experiments and 10 kV field operation. Originality/value The force-position hybrid control can realize the mutual compensation of force and position so as to effectively reduce the internal force in the closed chain. Finally, the engineering practicality of the method is verified by field operation experiment, the effective implementation of this control method greatly improves the robot working efficiency and the operation reliability, the promotion and application of the control method have great theoretical and practical value and maintenance management system, so as to achieve automation of electric.

scholarly journals Survey on the Advancements of Dielectric Fluids and Experiment Studies for Distribution Power Transformers

2021 ◽  
Vol 19 ◽  
pp. 97-102
Author(s):  
S. Carvalhosa ◽  
◽  
H. Leite ◽  
F. Branco ◽  
Carlos A. Sá ◽  
...  
Keyword(s):  
Power Distribution ◽  
Power Transformers ◽  
Health Index ◽  
Dielectric Fluids ◽  
Distribution Transformers

The main objective of this work is to summarize the most commonly used dielectric fluids in the power distribution transformers, as well as to discuss what are the latest and the rationale behind those trends. The favorable and unfavorable reasons for any choice behind each of those dielectric fluids will be discussed. Additionally, this work also advances the power distribution transformers health index most commonly used to assess the condition of the transformer.

scholarly journals Vibration Analysis for Machine Monitoring and Diagnosis: A Systematic Review

2021 ◽  
Vol 2021 ◽  
pp. 1-25
Author(s):  
Mohamad Hazwan Mohd Ghazali ◽  
Wan Rahiman
Keyword(s):  
Systematic Review ◽  
Vibration Analysis ◽  
Vibration Monitoring ◽  
Learning Approaches ◽  
Vibration Data ◽  
Advantages And Disadvantages ◽  
Monitoring And Diagnosis ◽  
Machine Monitoring ◽  
Communication Devices ◽  
And Performance

Untimely machinery breakdown will incur significant losses, especially to the manufacturing company as it affects the production rates. During operation, machines generate vibrations and there are unwanted vibrations that will disrupt the machine system, which results in faults such as imbalance, wear, and misalignment. Thus, vibration analysis has become an effective method to monitor the health and performance of the machine. The vibration signatures of the machines contain important information regarding the machine condition such as the source of failure and its severity. Operators are also provided with an early warning for scheduled maintenance. Numerous approaches for analyzing the vibration data of machinery have been proposed over the years, and each approach has its characteristics, advantages, and disadvantages. This manuscript presents a systematic review of up-to-date vibration analysis for machine monitoring and diagnosis. It involves data acquisition (instrument applied such as analyzer and sensors), feature extraction, and fault recognition techniques using artificial intelligence (AI). Several research questions (RQs) are aimed to be answered in this manuscript. A combination of time domain statistical features and deep learning approaches is expected to be widely applied in the future, where fault features can be automatically extracted from the raw vibration signals. The presence of various sensors and communication devices in the emerging smart machines will present a new and huge challenge in vibration monitoring and diagnosing.

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