System and method for oil field united station fire disaster pre-warning system based on video images

Abstract

The invention discloses a system and a method for oil field united station fire disaster pre-warning system based on video images. The system comprises a fire disaster pre-warning management computer and a fire disaster pre-warning controller connected with the fire disaster pre-warning management computer; the input end of the fire disaster pre-warning management computer is connected with a plurality of image type fire disaster detectors arranged in the monitored oil field united station. The method comprises the following steps: 1, acquiring and transmitting video images, 2, pre-processing the video images, 3, extracting characteristics, 4, acquiring a training sample, 5, constructing BP neural network model, 6, training BP neural network model, and 7, recognizing fire disaster and pre-warning. The system and the method have reasonable design, good real-time property, high sensitivity, high accuracy, high effectiveness and reliability, strong anti-jamming capability, strong practicability, good use effect, and high popularization and application values.

Description

technical field [0001] The invention relates to the field of intelligent security technology, in particular to a video image-based fire warning system and method for an oil field joint station. Background technique [0002] The oil field joint station is an important place for the collection, storage, preliminary processing and treatment, storage and export of crude oil and natural gas produced in the oil field. As a place for oil and gas transfer and distribution, the oil and gas in the station area are concentrated, with vertical and horizontal equipment, and these equipment are mostly operated under a certain pressure and temperature, and the materials handled are flammable and explosive, so the risk of fire and explosion is extremely high. [0003] Fire is one of the major disasters that endanger human beings, and it is a burning phenomenon that is out of control in time and space. It directly endangers human life and property, causes environmental pollution, and even e...

AI Technical Summary

Problems solved by technology

Due to the single criterion of this detector, it is easy to generate false alarms for high-power heat sources or strong lights (such as arcs, etc.)

[0008] (4) The composite fire detector does not completely eliminate the above shortcomings, but only increases the number of criteria to improve the overall performance of the probe, but in the case of relatively bad environmental conditions and many interferences (dust, electromagnetic interference , water vapor, air conditioning, light interference, vibration, etc.), still cannot be applied to the detection and alarm of large space fires

[0009] (5) Traditional detectors are mostly used in small spaces. For example, the installation distance of heat detectors should not exceed 10 meters, and the installation distance of smoke detectors should not exceed 15 meters. Obscuring, not suitable for use in large spaces

[0010] To sum up, due to the uncertainty and variability of fire occurrences, ordinary temperature-, smoke-, light-, and composite fire detectors are inevitably subject to monitoring of the area, height, humidity, dust, airflow, etc. of the environment. These effects are more obvious in large-space fire detection. The fire detectors in the prior art still have small detection range, weak anti-interference ability, high false alarm rate, and it is difficult to meet the requirements of early detection and complex prediction of joint stations. Flaws and deficiencies in the fire requirements in the environment, it is impossible to realize early warning in real time and accurately

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