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采煤機傳動裝置檢測與故障診斷系統(tǒng)的研究

發(fā)布時間:2018-08-04 12:56
【摘要】:采煤機是煤礦生產(chǎn)機械化與現(xiàn)代化的重要設(shè)備之一,是集機械、液壓、電氣于一體的大型復(fù)雜系統(tǒng)。采煤機傳動裝置是采煤機的重要組成部分,它與采煤效率有著密切的關(guān)系。采煤機傳動裝置是采煤機故障頻發(fā)區(qū),尤其是傳動裝置的齒輪和軸承。對采煤機傳動裝置進行檢測與故障診斷對煤礦安全生產(chǎn)具有重要意義。本文依據(jù)《滾筒采煤機型式檢驗規(guī)范》,總結(jié)分析采煤機傳動裝置的試驗要求,確定了截割部減速箱齒輪和軸承的振動,截割部齒輪箱油溫,牽引部減速箱齒輪和軸承的振動,齒輪傳動系統(tǒng)油池溫度,截割電機電壓和電流,牽引電機電壓和電流,滾筒轉(zhuǎn)速為主要檢測參數(shù),并研究確定了各參數(shù)的檢測方法及傳感器的安裝位置。針對采煤機傳動裝置齒輪和軸承故障,確定了用于故障診斷的改進型BP神經(jīng)網(wǎng)絡(luò)結(jié)構(gòu),并選取了神經(jīng)網(wǎng)絡(luò)輸入的時域和頻域特征參數(shù)。論文設(shè)計了采煤機傳動裝置檢測與故障診斷系統(tǒng)。系統(tǒng)硬件主要由傳感器、調(diào)理電路、數(shù)據(jù)采集裝置組成。以圖形化編程語言LabVIEW2011為開發(fā)平臺,結(jié)合改進型BP神經(jīng)網(wǎng)絡(luò)研發(fā)了檢測與診斷軟件,實現(xiàn)了采煤機截割部和牽引部傳動裝置的狀態(tài)檢測與故障診斷。通過實驗對系統(tǒng)的靜態(tài)特性進行分析,結(jié)果表明,系統(tǒng)各通道靜態(tài)特性良好,能夠達到采煤機截割部檢測要求。并對系統(tǒng)的各模塊功能進行了實驗驗證,結(jié)果表明,檢測模塊能夠?qū)崿F(xiàn)對采煤機傳動裝置各被測參數(shù)的數(shù)據(jù)分析、存儲、顯示等功能,故障診斷模塊能夠?qū)Σ擅簷C傳動裝置的齒輪和軸承進行故障診斷。
[Abstract]:Shearer is one of the important equipment of mechanization and modernization of coal mine production. It is a large complex system which integrates machinery, hydraulic pressure and electricity. Shearer drive is an important part of shearer, which is closely related to coal mining efficiency. Shearer transmission is the fault area of shearer, especially the gear and bearing of transmission device. The detection and fault diagnosis of shearer drive is of great significance to the safety of coal mine production. According to the Standard for Type Inspection of Drum Shearer, this paper summarizes and analyzes the test requirements of shearer transmission, and determines the vibration of gear and bearing in the cutting part, the oil temperature of the gear box in the cutting part, the vibration of the gear and bearing of the reducer in the traction part. The oil pool temperature, the voltage and current of cutting motor, the voltage and current of traction motor and the rotational speed of drum are the main detection parameters of gear transmission system. The detection method of each parameter and the installation position of sensor are studied and determined. In view of the gear and bearing faults of shearer drive, the improved BP neural network structure for fault diagnosis is determined, and the time domain and frequency domain characteristic parameters of neural network input are selected. The paper designs the system of detecting and fault diagnosis of shearer transmission device. The hardware of the system is mainly composed of sensor, conditioning circuit and data acquisition device. Based on the graphical programming language LabVIEW2011 and the improved BP neural network, the detection and diagnosis software is developed. The condition detection and fault diagnosis of the driving device of the cutting part and the traction part of the shearer are realized. The static characteristics of the system are analyzed through experiments. The results show that the static characteristics of each channel of the system are good and can meet the requirements of the shearer cutting part detection. The experimental results show that the testing module can realize the functions of data analysis, storage, display and so on. The fault diagnosis module can diagnose the gear and bearing of shearer.
【學位授予單位】:西安科技大學
【學位級別】:碩士
【學位授予年份】:2017
【分類號】:TD421.6

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