Infrared beam type fire disaster smoke detector and detecting method thereof

Abstract

The invention discloses an infrared light beam type fire smoke detector and a detection method thereof. The detector comprises a MCU core circuit, a power supply circuit, a clock circuit, a keyboard, a display interface, a local communication circuit, a remote communication circuit, a switching value input circuit, a switching value output circuit, an acousto-optical alarm circuit, an analog signal acquisition module and an infrared transmitting and receiving circuit. The detection method is a fuzzy neural network fire detection algorithm, and a fuzzy neural network model adopts a four-layer structure which respectively represents an input layer, division of a fuzzy subspace of the input variable, division of a fuzzy subspace of the fire occurrence probability U, and an output layer; and the generalization ability of the network is improved through the learning and training of the fuzzy neural network, and the trained fuzzy neural network can accuracy judge the current input. The invention can reduce the failure rate when improving the flexibility of the detector simultaneously, has strong anti-interference ability, and greatly improves the reliability of the fire detection system.

Description

technical field [0001] The invention belongs to the technical field of fire smoke detection of building structures. Background technique [0002] Traditional fire smoke detectors mainly include ion smoke detectors and photoelectric smoke detectors. The ionization smoke detector is a micro-current change device that detects smoke particles through the voltage change caused by the smoke in the ionization chamber. It has a relatively balanced detection performance for gray smoke, black smoke and smoke of various particle sizes. Radioactive elements are used in the design of the chamber, and the process of production, storage, transportation and scrapping has the risk of polluting the environment, and the detector itself is extremely susceptible to environmental interference such as humidity and wind speed. There are two types of photoelectric smoke detectors: point type and linear type. The point-type photoelectric smoke detector uses the scattering principle of infrared ligh...

AI Technical Summary

Problems solved by technology

However, due to the thickness of the laser image smoke detection technology, the spot superposition phenomenon in the collected image is serious due to the thickness of the beam, which affects the feasibility and accuracy of image processing; in addition, the detector software and hardware are relatively complex and the cost is high

At present, the laser image smoke sensing technology is still far from being widely used

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