Thermal power plant violation behavior warning method and system based on neural network

Abstract

The invention relates to a thermal power plant violation behavior warning method based on a neural network. The method comprises the following steps: S1, a video acquisition unit acquires monitoring video data; s2, a data processing unit extracts behavior characteristics in the monitoring video data and sends the behavior characteristics to a data analysis unit; s3, the data analysis unit acquiresbehavior characteristics and judges whether the behavior belongs to a violation behavior or not through the neural network, and if yes, the step S4 is executed; and S4, judging the violation behaviortype, and controlling a warning unit to correspondingly send out warning information according to the violation behavior type. Compared with the prior art, the method has the advantages of high detection efficiency, low error rate and the like.

Description

technical field [0001] The invention relates to the field of thermal power plant safety monitoring, in particular to a neural network-based warning method and system for thermal power plant violations. Background technique [0002] The security system is the physical basis for real-time monitoring of key departments or important places in various industries. Management departments can obtain effective data, images or sound information through it, and timely monitor and record the process of sudden abnormal events for efficient, Timely command and deploy police forces, handle cases, etc. [0003] In the thermal power plant construction site, 24-hour monitoring of the construction site can be realized through the security system, and the use of video monitoring means can effectively overcome the problem of fewer personnel and comprehensively improve management efficiency and supervision level. Through the security system, the management department can not only keep abreast of...

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to provide a neural network-based thermal power plant violation warning method and system with high detection efficiency and low error rate in order to overcome the defects in the above-mentioned prior art, and change the original manual identification of violations. After collecting, processing, and analyzing the monitoring video data of construction personnel, the supervisory personnel will remind the construction personnel through the intercom system or punish violations through the assessment system according to the analysis results, which solves the problem of heavy workload and low work efficiency of the supervisory personnel

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