长期以来，采空区、煤堆、煤仓等空间的煤自燃火灾时有发生，受限于工作区域的复杂环境和火源探测技术瓶颈等因素，较难实现煤自燃灾害高温点的快速量化识别。而声学测温技术具有测量精度高、测温范围宽、测量空间大等特点，可实现采空区等隐蔽火源位置精准探测且极具发展前景。目前该技术在松散煤体温度测量领域尚处于基础研究和实验室研究阶段，仍需开展大量研究。基于伪随机序列的优越性能，将其引入作为声源信号，并根据声学测温原理和伪随机序列声源信号产生原理，搭建了松散煤体声波测温试验系统。系统主体部分包括声学测试系统、程序升温系统、隔音系统和煤样箱体，结合试验测试和仿真模拟方法，验证了系统的准确性。利用理论分析、Matlab仿真和试验测试相结合的方法，开展伪随机序列声源信号的失真特性研究，确定了该信号的最佳处理方法，成功将其应用于松散煤体测温中。结果表明：伪随机序列可以作为采空区、煤堆、煤仓等空间的松散煤体声学测温的声源信号，但需运用二次相关PHAT–β算法对伪随机序列声源信号发生频率区间(1 000～3 000 Hz)进行处理，使频带变窄，能量集中；运用伪随机序列声源信号测量声波在松散煤体中飞渡时间，发现不同距离下声波飞渡时间测量结果误差小于5%，并通过了对比验证；伪随机序列作为松散煤体的测温声源信号时，所反演温度与不同粒径的煤样温度之间的平均绝对误差为2.051 ℃，平均误差率5.293%，能够较为精准、可靠地反演煤温。

For a long time, spontaneous coal combustion fires in the air mining area, coal pile, coal silo and other spaces occur from time to time, and it is more difficult to realize the rapid quantitative identification of the high temperature point of the spontaneous coal combustion disaster due to factors such as the complex environment of the working area and the bottleneck of the fire source detection technology. The acoustic temperature measurement technology has the characteristics of high measurement accuracy, wide temperature measurement range, large measurement space, etc., which can realize the accurate detection of the hidden fire source location in the air mining area and other hidden fire sources and is very promising for development. At present, this technology is still in the stage of basic and laboratory research in the field of temperature measurement of loose coals, and a lot of research still needs to be carried out. Based on the superior performance of pseudo-random sequences, they were introduced as acoustic source signals, and an experimental system for acoustic temperature measurement of loose coals was constructed according to the principle of acoustic temperature measurement and the principle of pseudo-random sequence acoustic source signal generation. The main part of the system includes an acoustic test system, a programmed warming system, a soundproofing system and a coal sample box, and the accuracy of the system was verified by combining experimental tests and simulation and modelling methods. Using a combination of theoretical analysis, Matlab simulation and experimental testing, we carried out a study on the distortion characteristics of the pseudo-random sequence acoustic source signal, determined the optimal processing method for this signal, and successfully applied it to the temperature measurement of loose coals. The results show that pseudo-random sequences can be used as sound source signals for the acoustic temperature measurement of loose coal bodies in the space of air-mining areas, coal piles, and coal silos, etc. However, it is necessary to apply the quadratic correlation PHAT–β algorithm to the frequency interval (1 000−3 000 Hz) of the pseudo-random sequences sound source signals to process them, so as to make the bandwidth narrower and to concentrate the energy. The pseudo-random sequence of sound source signals is used to measure the flying time of acoustic waves in a loose coal body, and it is found that the error of the acoustic flying time measurement results is less than 5% at different distances, and it is verified by comparison. When the pseudo-random sequence is used as the acoustic source signal for temperature measurement of loose coals, the average absolute error between the inverted temperature and the temperature of coal samples with different grain sizes is 2.051 °C, with an average error rate of 5.293%, which is capable of inverting the coal temperature in a more accurate and reliable way.