Self-learning fire-source simulating system and method

Abstract

The invention relates to a self-learning fire-source simulating system and method. The system comprises an infrared flame detecting module, a main control circuit, a constant-power driving circuit and an MEMS light source. The main control circuit comprises a microprocessor and a peripheral circuit of the microprocessor. The output of the infrared flame detecting module is connected to the microprocessor of the main control circuit through a serial port. The main control circuit is connected with the constant-power driving circuit, and the constant-power driving circuit is connected with the MEMS light source. A product based on the self-learning fire-source simulating system and method can serve as an instrument for regularly checking and calibrating some important site fire alarm systems and can also serve as a research and development tool of a fire detector manufacturer and a quality testing tool of a manufacturing shop; meanwhile, multiple interference sources in a site can be learnt in a close-range mode, and the effect of accumulating interference signal mode identification data can be achieved. By means of the self-learning fire-source simulating system and method, the reliability of a fire detector can be improved, the maintenance workloads can be reduced, the quality testing efficiency can be improved, and the research, development and production cost can be reduced.

Description

technical field [0001] The invention provides a system and method for simulating a fire source, in particular a system and method capable of self-learning and simulating a fire source, which can be used to accurately simulate the flame spectrum characteristics of fuel combustion of different materials. Background technique [0002] In the research and development of fire detection instruments and other related products, to obtain experimental data to determine the empirical thresholds of different flame types and detection distances, and to select flame recognition algorithms based on this, it is often necessary to light open flames for experiments; in nuclear submarines, aircraft carriers, oil refineries and Fire detectors in arsenals and other places must be regularly inspected and maintained. Lighting fires to test fire alarm systems has huge potential risks. In the production process of fire detectors, fire detectors also need to light fires to obtain experimental data fo...

AI Technical Summary

Problems solved by technology

[0004] These three types of devices have their own advantages and disadvantages, but the first type requires the use of electric motors, which generate relatively large noise, are relatively large in size, heavy and consume a large amount of energy

The shape of the second type of flame is mainly determined by the hardware. Once you want to change the shape of the flame, you need to change the hardware, and the change of the flame is discontinuous and uncontrollable

The third type of intelligent flame can imitate a flame with a certain frequency, but its imitation frequency is relatively fixed, but the flame flickering frequency is different when different materials burn

The type of fire source simulated by the device is relatively single, and cannot be popularized and used; in addition, the internal resistance of the spectrum lamp used in the device will increase significantly with the increase of use time. Since the power supply voltage of the bulb remains unchanged, the power of the spectrum lamp Will be significantly reduced, that is, the luminous intensity will be significantly reduced

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