Transformer substation environment anomaly detection system, method and device

An anomaly detection and substation technology, applied in closed-circuit television systems, neural learning methods, instruments, etc., can solve the problems of heavy workload of workers, inability to save alarm conditions, and untimely alarms, to facilitate transmission and reduce manual monitoring and missed detection. and the probability of untimely discovery, the effect of good robustness and adaptability

Pending Publication Date: 2019-10-18
SHENZHEN JIANGXING INTELLIGENCE INC
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  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] However, in the actual operation process, this method of manual patrol or video monitoring is inefficient and places a heavy workload on the staff, and there are cases where abnormalities are not discovered in time or missed due to the negligence of the staff. The alarm status cannot be saved in the form of pictures for later inspection

Method used

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  • Transformer substation environment anomaly detection system, method and device
  • Transformer substation environment anomaly detection system, method and device
  • Transformer substation environment anomaly detection system, method and device

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Embodiment 1

[0038] A substation environment anomaly detection system is used to detect the environment anomaly information of a substation, including a front-end video acquisition module, a network transmission module, a monitoring management center, an abnormality alarm module, and a data storage module.

[0039] The front-end video acquisition module includes a network camera with intelligent detection function. The network camera is integrated with an intelligent algorithm module. The intelligent algorithm module adopts an unsupervised anomaly detection algorithm based on generative confrontation learning. detection.

[0040] The front-end video acquisition module is used for real-time monitoring of the surrounding environment of the substation. When an abnormality is detected, the acquired monitoring information is transmitted to the monitoring management center through the network transmission module.

[0041] The network camera is placed near the substation equipment to realize the ...

Embodiment 2

[0061] A method for detecting an abnormality in a substation environment, comprising the following method steps:

[0062] Data acquisition and processing: Real-time monitoring of the surrounding environment of the substation to collect video data of the surrounding environment of the substation, and real-time detection of the environmental video data to detect abnormal pictures in the environmental video data;

[0063] Data upload: Upload the detected picture information that may be abnormal to the monitoring management terminal;

[0064] Abnormal analysis and processing: conduct a comprehensive analysis of the pictures that may have abnormalities uploaded to the monitoring management terminal, remove the pictures without abnormalities, and send an alarm when the pictures with abnormalities are determined;

[0065] Abnormal data storage: save the pictures that are confirmed to be abnormal, so as to facilitate subsequent inspection.

Embodiment 3

[0067] A substation environmental anomaly detection device, comprising:

[0068] memory for storing computer programs;

[0069] The processor is configured to load a computer program to execute the substation environment anomaly detection method of the above embodiment.

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Abstract

The invention discloses a transformer substation environment anomaly detection system, method and device. The transformer substation environment anomaly detection system comprises a front-end video acquisition module, a network transmission module, a monitoring management center, an anomaly alarm module and a data storage module, wherein the front-end video acquisition module comprises a network camera with an intelligent detection function, an intelligent algorithm module is integrated in the network camera, the intelligent algorithm module adopts an unsupervised anomaly detection algorithm based on generative adversarial learning, and the intelligent algorithm module is used for quickly detecting the anomaly of the surrounding environment of the equipment. According to the invention, thenetwork camera with an intelligent detection function is adopted to carry out anomaly detection on the collected environment information, and only picture information which may have anomaly is output, so that data transmission is facilitated. Compared with a traditional abnormal target detection algorithm, the method has better robustness and adaptability, has the advantages of being uninterrupted and timely, reduces the probability of missed detection and untimely discovery of manual monitoring, and reduces the potential safety hazard of a transformer substation.

Description

technical field [0001] The invention relates to the technical field of power equipment monitoring, in particular to a substation environment anomaly detection system, method and device. Background technique [0002] For substations in remote areas or unattended substations, in order to ensure the safety of substations, it is necessary to monitor and send alarm information for abnormal conditions such as transformer explosions, smoke and fire from substation equipment, non-staff or animal intrusion in substations, and existing In the technology, manual inspection and remote camera monitoring are usually used to obtain changes in the internal and surrounding conditions of the substation. In this way, inspectors are relied on to conduct on-site inspections every day to observe the conditions of the equipment and the surrounding conditions of the power station, or to continuously observe the monitor screen to find abnormal conditions. And issue a warning in time to perform a ser...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04N7/18G06K9/00G06N3/04G06N3/08G08B19/00
CPCH04N7/18G06N3/08G08B19/00G06V20/40G06N3/045
Inventor 樊小毅刘江川张聪庞海天杨洋邵俊松
Owner SHENZHEN JIANGXING INTELLIGENCE INC
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