During a fire, an alarm is triggered before visible smoke is generated, and it is determined whether particles are generated by the heat of the insulator, thus achieving extremely early monitoring of electrical fires and preventing them from happening.

The above is the whole process of electrical line fire. Since we cannot prevent it through residual current in many places, can we reduce the risk of electrical fire by analyzing the process from heating - temperature rise - high temperature - high temperature coking? By collecting data such as cable temperature, conductor temperature, air humidity, current load, high-sensitivity pyrolysis particle detection, and then through big data analysis, we can finally achieve accurate early warning of electrical fire. This system fundamentally solves the problem that the residual current electrical fire monitoring system cannot filter massive false alarm information, and it is difficult to make timely warnings under low load conditions, making accurate early warning and protection of electrical line fires possible.

Detection: The detector obtains gas particles in the air by sampling. The sampling method can be active, which is to obtain gas particles by blowing air flow into the air, and passive, which is to obtain gas particles through the natural flow of air. The detector is usually equipped with a filter to remove dust and other water mist impurities in the air to ensure the accuracy of detection.

Pyrolysis: The pyrolysis device inside the detector heats the collected gas to a high temperature, causing it to undergo a pyrolysis reaction, further decomposing the gas into smaller molecules or atoms. The purpose of this step is to better identify and detect pyrolysis gas particles in the gas.

Multi-dimensional AI algorithm analysis: The internal component analyzer performs component analysis on the pyrolyzed gas. Through laser spectral analysis, chromatographic analysis or mass spectrometry, temperature, humidity, gas and other sensors, determine whether there are flammable or toxic gases in the gas, as well as their concentration.

Warning and alarm: Based on the results of the component analysis, the detector determines whether the preset warning or alarm conditions have been met. If the early warning conditions are met, the detector will send out an audible and visual early warning signal to indicate that there may be a fire hazard; if the alarm conditions are met, the detector will send out a fire alarm signal and link the fire protection system to carry out emergency measures such as fire extinguishing.

Comprehensive analysis: Due to the current prefabricated cabin structure protection and improved exhaust performance, traditional temperature and smoke detectors can only send out alarm information after a fire occurs. BMS and gas detection are limited in sensitivity and false alarm rate, and are unable to monitor fires in external electrical equipment. Therefore, traditional status monitoring and alarm equipment in energy storage power stations cannot achieve effective online monitoring and early warning of the energy storage system as a whole.