基于时频联合小波法的采煤机关键部件故障诊断研究
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摘要
煤炭资源在我国能源体系结构中具有非常重要的地位和作用，采煤机作为煤矿生产过程的关键设备，是集机械、电子、电气、传动、液压等为一体的复杂机械。采煤机设备的安全、稳定运行对于保证煤炭生产的安全、促进企业生产效率具有重要意义。由于采煤机常处于潮湿、粉尘颗粒多、电磁干扰严重等复杂井下运行环境，时常出现机械磨损、齿轮断裂、轴承破损等采煤机关键部件故障。一旦出现此类故障，将导致整个煤矿生产过程停滞，乃至瘫痪。
针对采煤机关键部件故障，本文在深入研究与分析采煤机运行环境、工作特点、影响因素等导致采煤机机械故障的基础上，将时域－频域方法与正交小波法相结合，利用现有的采煤机监控系统和检测装置的基础，提出了基于时频联合小波法的采煤机关键部件故障诊断方法，取得了如下的研究成果：首次将时频联合分析引入到采煤机关键部件特征分析中；针对采煤机关键部件故障信号进行特征提取并建立模型；提出了基于正交小波的采煤机关键部件故障诊断的新方法。根据某煤炭企业生产实际，设计开发了基于时频联合小波法的采煤机关键部件故障诊断专家系统。本文的主要研究内容主要包括以下几个方面：
(1)针对采煤机故障类型进行了采煤机故障特性分析。详细研究了采煤机关键部件故障信号的时域、频域、时域－频域分析方法。
(2)在分析采煤机关键部件故障信号的基础上，研究了基于主元分析法、谱熵和小波分析法的采煤机关键部件故障信号特征提取方法，研究了每种方法下采煤机关键部件故障特征的影响因素、提取过程、实验分析。
(3)在分析正交小波分析方法的基础上，针对采煤机关键部件故障信号，提出了基于正交小波分析的采煤机关键部件故障诊断方法。研究了该方法的理论基础、实现流程以及采煤机常见的电动机轴承外环、内环、滚动体等部件的故障类型及诊断方法。
(4)设计开发了基于时频联合小波法的采煤机关键部件故障诊断专家系统。研究了该系统的系统结构、系统功能、工作流程、以及相应的软硬件平台。
现场实际应用结果表明本文所设计的基于时频联合小波法的采煤机关键部件故障诊断专家系统能够实现采煤机机械故障的准确判断，对于提高采煤机机械运行的安全性与稳定性、促进企业安全生产具有重要意义。
The coal resources has a very important position and role in our country's energysystem structure, coal mining machine as a key equipment of coal mine productionprocess is a complex machinery that is a collection of machinery, electronics, electricand hydraulic transmission. Safety and stable operation of coal mining machinesequipment is important to guarantee safety in coal production and promote productionefficiency. Because of coal winning machine is often in a moist、 dust grain much、electromagnetic interference and other complex underground operation environment,coal winning machine faults appear such as mechanical wear、gear fault and bearingdamage. Once coal minning machine fault appears, it will cause the entire coal mineproduction process stagnation and even paralysis.
In view of mechanical faults of coal mining machine, based on thorough study andanalysis of coal winning machine operation environment、the working characteristicsand influence factors which lead to coal winning machine mechanical faults, with thecombination of time-frequency domain method and orthogonal wavelet method, usingthe existing coal mining machine monitoring system and detecting device for foundation,coal winning machine mechanical fault diagnosis based on the combination method ofwavelet and time-frequency are put forward. The research results are obtained asfollows: Analyze the coal winning machine mechanical fault type and faultcharacteristics analysis; Study on feature extraction and feature analysis of coal winningmachine fault signal; According to a coal production, coal winning machine mechanicalfault diagnosis expert system based on combination method of wavelet andtime-frequency is designed. The main content of this paper mainly includes thefollowing aspects:
(1) According to the types of coal winning machine fault, coal mining machineryfault characteristic analysis is preceded. A detailed study of analysis method of the coalmining machine fault signal in the time domain, frequency domain and time domain andfrequency domain.
(2) On the basis of analysis of coal winning machine mechanical fault signal, weresearch mechanical fault signal feature extraction method based on the principalcomponent analysis, spectral entropy and wavelet analysis method and study of the influence factors, extracting process, experimental analysis of machine mechanical faultsignal in each method.
(3) On the basis of analysis of orthogonal Wavelet analysis method, for coalwinning machine mechanical fault signal, coal winning machine mechanical faultdiagnosis method was put forward based on the orthogonal wavelet analysis. Study ofthe theoretical foundation of the method, implementation process and the coal miningmachine asynchronous motor’s fault type and diagnosis method of bearing outer ring,the inner ring, a rolling body and other parts.
(4) Coal winning machine mechanical fault diagnosis expert system based oncombination method of wavelet and time-frequency is designed. Study on the systemstructure of the system, system function, workflow, as well as the correspondinghardware and software platforms.
The actual application result shows that this design in this paper based oncombination method of wavelet and time-frequency coal winning machine mechanicalfault diagnosis expert system can realize the accurate judgment of coal mining machinemechanical fault. It has important meaning in Improving the mechanical operationsecurity and stability and promoting the enterprise safety production.
针对采煤机关键部件故障，本文在深入研究与分析采煤机运行环境、工作特点、影响因素等导致采煤机机械故障的基础上，将时域－频域方法与正交小波法相结合，利用现有的采煤机监控系统和检测装置的基础，提出了基于时频联合小波法的采煤机关键部件故障诊断方法，取得了如下的研究成果：首次将时频联合分析引入到采煤机关键部件特征分析中；针对采煤机关键部件故障信号进行特征提取并建立模型；提出了基于正交小波的采煤机关键部件故障诊断的新方法。根据某煤炭企业生产实际，设计开发了基于时频联合小波法的采煤机关键部件故障诊断专家系统。本文的主要研究内容主要包括以下几个方面：
(1)针对采煤机故障类型进行了采煤机故障特性分析。详细研究了采煤机关键部件故障信号的时域、频域、时域－频域分析方法。
(2)在分析采煤机关键部件故障信号的基础上，研究了基于主元分析法、谱熵和小波分析法的采煤机关键部件故障信号特征提取方法，研究了每种方法下采煤机关键部件故障特征的影响因素、提取过程、实验分析。
(3)在分析正交小波分析方法的基础上，针对采煤机关键部件故障信号，提出了基于正交小波分析的采煤机关键部件故障诊断方法。研究了该方法的理论基础、实现流程以及采煤机常见的电动机轴承外环、内环、滚动体等部件的故障类型及诊断方法。
(4)设计开发了基于时频联合小波法的采煤机关键部件故障诊断专家系统。研究了该系统的系统结构、系统功能、工作流程、以及相应的软硬件平台。
现场实际应用结果表明本文所设计的基于时频联合小波法的采煤机关键部件故障诊断专家系统能够实现采煤机机械故障的准确判断，对于提高采煤机机械运行的安全性与稳定性、促进企业安全生产具有重要意义。
The coal resources has a very important position and role in our country's energysystem structure, coal mining machine as a key equipment of coal mine productionprocess is a complex machinery that is a collection of machinery, electronics, electricand hydraulic transmission. Safety and stable operation of coal mining machinesequipment is important to guarantee safety in coal production and promote productionefficiency. Because of coal winning machine is often in a moist、 dust grain much、electromagnetic interference and other complex underground operation environment,coal winning machine faults appear such as mechanical wear、gear fault and bearingdamage. Once coal minning machine fault appears, it will cause the entire coal mineproduction process stagnation and even paralysis.
In view of mechanical faults of coal mining machine, based on thorough study andanalysis of coal winning machine operation environment、the working characteristicsand influence factors which lead to coal winning machine mechanical faults, with thecombination of time-frequency domain method and orthogonal wavelet method, usingthe existing coal mining machine monitoring system and detecting device for foundation,coal winning machine mechanical fault diagnosis based on the combination method ofwavelet and time-frequency are put forward. The research results are obtained asfollows: Analyze the coal winning machine mechanical fault type and faultcharacteristics analysis; Study on feature extraction and feature analysis of coal winningmachine fault signal; According to a coal production, coal winning machine mechanicalfault diagnosis expert system based on combination method of wavelet andtime-frequency is designed. The main content of this paper mainly includes thefollowing aspects:
(1) According to the types of coal winning machine fault, coal mining machineryfault characteristic analysis is preceded. A detailed study of analysis method of the coalmining machine fault signal in the time domain, frequency domain and time domain andfrequency domain.
(2) On the basis of analysis of coal winning machine mechanical fault signal, weresearch mechanical fault signal feature extraction method based on the principalcomponent analysis, spectral entropy and wavelet analysis method and study of the influence factors, extracting process, experimental analysis of machine mechanical faultsignal in each method.
(3) On the basis of analysis of orthogonal Wavelet analysis method, for coalwinning machine mechanical fault signal, coal winning machine mechanical faultdiagnosis method was put forward based on the orthogonal wavelet analysis. Study ofthe theoretical foundation of the method, implementation process and the coal miningmachine asynchronous motor’s fault type and diagnosis method of bearing outer ring,the inner ring, a rolling body and other parts.
(4) Coal winning machine mechanical fault diagnosis expert system based oncombination method of wavelet and time-frequency is designed. Study on the systemstructure of the system, system function, workflow, as well as the correspondinghardware and software platforms.
The actual application result shows that this design in this paper based oncombination method of wavelet and time-frequency coal winning machine mechanicalfault diagnosis expert system can realize the accurate judgment of coal mining machinemechanical fault. It has important meaning in Improving the mechanical operationsecurity and stability and promoting the enterprise safety production.
引文
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