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煤体结构类型的超声波判识理论与方法研究
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摘要
我国是煤与瓦斯突出灾害现象严重的国家,特别是近年来煤与瓦斯突出灾害出现的频率越来越高,严重影响了我国的煤炭生产秩序以及国家能源安全战略的稳定。因此如何有效地预测煤与瓦斯突出灾害的发生就显得尤为迫切。实践证明,发生煤与瓦斯突出灾害的一个必要条件是存在构造煤(Ⅲ类煤、Ⅳ类煤),所以,可以通过探测煤层中构造煤的存在与否,对煤与瓦斯突出灾害的预测进行指导。本文正是从这一角度出发,提出了利用超声波对煤体结构类型进行探测和判识的新方法。通过对其探测理论的深入研究,确定了超声反射法作为多层煤体介质条件下的探测方式,以及以超声波波速及超声波衰减系数作为主要的探测参数,并通过实验明确了煤体结构类型与超声波波速及超声波衰减系数之间的量化关系;建立了煤体中超声波波速的计算模型和煤体超声波衰减系数计算模型;在此基础上进一步构建了基于超声波和BP神经网络的煤体结构类型判识模型。该模型为典型的三层结构,以煤体的超声波波速、衰减系数及所采用的超声波工作频率作为输入的评判指标,以煤体结构类型作为输出,通过对评判指标的综合分析和处理,实现探测煤体结构类型的准确判断。本文的理论模型得到了实验证明,BP神经网络通过了校验数据的检验,说明理论和模型是合理的和正确的。总之,本文在煤体的超声波性质、煤体类型的探测方式及判识模型等方面进行了较深入的研究,为今后进一步开发煤体类型探测系统提供了较完善的理论基础。
The disaster of coal and gas outburst is serous in China. In these years with the increasing of coal production and exploitation depth, the frequency of the disaster is higher and it has badly affected the order of coal production. So how to effectively forecast the disaster is imminent. Practice has been proved that the necessary condition of coal and gas outburst is the existence of coal structure (coal ofⅢ&Ⅳ),so the disaster can be forecasted by exploring coal structure in coal bed or not. This paper brings forward a new method of exploring and differentiating coal structure types. By studying the exploring theory, models of calculating ultrasonic speed and ultrasonic attenuation coefficient in coal have been set up. Models have achieved the measure of ultrasonic speed and ultrasonic attenuation under the condition of multilayer and the relation between coal structure types and ultrasonic attenuation coefficient has been proved by experiments. Then the differentiating model of ultrasonic and BP neural network has been set up .The model is typical three-layer structure and in the model the input judging indexes are ultrasonic speed, ultrasonic attenuation coefficient and ultrasonic work frequency, the output indexes are coal structure types. By analyzing these indexes, coal structure types can be made exact estimation. These theories and models are proved to be reasonable and correct through experiments, BP neural network have been verified by the checkout data. In a word, this paper has made in-depth studies at ultrasonic quality, exploring project of coal structure types and theory modeling. And these studies have offered theory basis to exploring system of exploiting coal structure types for the future.
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