Neural network and fuzzy control fused electrical fire intelligent alarm method

Abstract

The invention discloses a neural network and fuzzy control fused electrical fire intelligent alarm method. The method comprises the following steps of: 1, acquiring a leakage current signal, current and voltage signals, an arc light signal, a temperature signal and a field electromagnetic environment parameter signal by using a sensor on site, and pre-processing signals acquired by the sensor by using a velocity detection algorithm; 2, transmitting processed data to a three-layer feedforward error counterpropagation neural network and processing, wherein the neural network is subjected to supervised learning and establishes a weight matrix in advance; and 3, transmitting electrical circuit undamage probability, electrical circuit damage probability, and electrical circuit fire probability output by the neural network to a fuzzy inference module and performing fuzzy inference to acquire a forecast result of electrical fire. In the method, the probability of the electrical fire is accurately forecast by using the advantages of advanced theories, such as neural network, fuzzy control and the like, and without depending on deep knowledge of an object, the electrical fire forecasting accuracy is obviously improved and the damage of the electrical fire can be effectively prevented and reduced.

Description

technical field [0001] The invention relates to a fire intelligent alarm method, in particular to an electrical fire intelligent alarm method fused with neural network and fuzzy control. Background technique [0002] With the development of social economy and technology, power electronic equipment and electricity load have increased significantly, and the fire accidents caused by electricity have increased sharply, causing huge property losses and threatening personal safety. In order to use electricity safely, people have successively invented and manufactured devices such as pull switches, fuses, leakage switches, circuit breakers, and air switches. At present, the end-user electricity protection is mainly based on leakage protection switches, but the use of leakage switches to achieve electricity safety exists as follows Disadvantages: [0003] 1) The protection parameters of ordinary leakage switch are set by the manufacturer when leaving the factory. When the protectio...

AI Technical Summary

Problems solved by technology

[0015] In order to solve the above-mentioned technical problems existing in the existing electrical fire alarm system, the present invention provides an intelligent electrical fire alarm method that integrates neural network and fuzzy control. Through the data analysis and processing technology based on the fusion of neural network and fuzzy reasoning, the fire forecast signal can be given quickly and accurately, and the loss of life and property caused by electrical fire can be effectively reduced.

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