By building mathematical model for HAGC （hydraulic automation gauge control） system of strip rolling mill, treating faults as unknown inputs induced by model uncertainty, and analyzing fault direction, an unknown in...By building mathematical model for HAGC （hydraulic automation gauge control） system of strip rolling mill, treating faults as unknown inputs induced by model uncertainty, and analyzing fault direction, an unknown input fault diagnosis observer group was designed. Fault detection and isolation were realized through making ob- server residuals robust to specific faults but sensitive to other faults. Sufficient existence conditions and design of the observers were given in detail. Diagnosis observer parameters for servo-valve, cylinder, roller and body rolling mill were obtained resoectively. The effectiveness of this diagnosis method was oroved bv actual data simulations.展开更多
Including servo valve, hydraulic cylinder, mill and sensor and ignoring nonlinear factors, the linear dynamic model of hydraulic automatic gage control(HAGC) system of a temper rolling mill was theoretically derived. ...Including servo valve, hydraulic cylinder, mill and sensor and ignoring nonlinear factors, the linear dynamic model of hydraulic automatic gage control(HAGC) system of a temper rolling mill was theoretically derived. The order of the model is 4/4, and can be reduced to 2/2. Based on modulating functions method, utilizing numerical integration, we constructed the equivalent identification model of HAGC, and the least square estimation algorithm was established. The input and output data were acquired on line at temper rolling mill in Shangshai Baosteel Group Corporation, and the continuous time model of HAGC system was estimated with the proposed method. At different modulating window intervals, the estimated parameters changed remarkably. When the frequency bandwidth of modulating filter matches that of estimated system, the parameters can be estimated accurately. Finally, the dynamic model of the HAGC was obtained and validated based on the spectral analysis result.展开更多
The fault diagnosis of HAGC （Hydraulic Gauge Control） system of strip rolling mill is researched. Taking the advantage of the accompanying characteristics of the closed loop control system, rolling force forecasting...The fault diagnosis of HAGC （Hydraulic Gauge Control） system of strip rolling mill is researched. Taking the advantage of the accompanying characteristics of the closed loop control system, rolling force forecasting model is built based on neural networks. The comparison results of the prediction and the actual signal are taken as residual signals. Wavelet transform is used to obtain the components of high and low frequency of the residual signal. Wave let decomposition results make fault feature clear and time-domain positioning accurately. Fault numerical criterion is established through Lipschitz exponent. By analyzing the varied fault features which correspond to varied fault rea sons, the fault diagnosis of HAGC system is implemented successfully.展开更多
文摘By building mathematical model for HAGC （hydraulic automation gauge control） system of strip rolling mill, treating faults as unknown inputs induced by model uncertainty, and analyzing fault direction, an unknown input fault diagnosis observer group was designed. Fault detection and isolation were realized through making ob- server residuals robust to specific faults but sensitive to other faults. Sufficient existence conditions and design of the observers were given in detail. Diagnosis observer parameters for servo-valve, cylinder, roller and body rolling mill were obtained resoectively. The effectiveness of this diagnosis method was oroved bv actual data simulations.
文摘Including servo valve, hydraulic cylinder, mill and sensor and ignoring nonlinear factors, the linear dynamic model of hydraulic automatic gage control(HAGC) system of a temper rolling mill was theoretically derived. The order of the model is 4/4, and can be reduced to 2/2. Based on modulating functions method, utilizing numerical integration, we constructed the equivalent identification model of HAGC, and the least square estimation algorithm was established. The input and output data were acquired on line at temper rolling mill in Shangshai Baosteel Group Corporation, and the continuous time model of HAGC system was estimated with the proposed method. At different modulating window intervals, the estimated parameters changed remarkably. When the frequency bandwidth of modulating filter matches that of estimated system, the parameters can be estimated accurately. Finally, the dynamic model of the HAGC was obtained and validated based on the spectral analysis result.
基金Item Sponsored by National Natural Science Foundation of China(50375135)Provincial Natural Science Foundation of Hebei Province of China(E2005000323)
文摘The fault diagnosis of HAGC （Hydraulic Gauge Control） system of strip rolling mill is researched. Taking the advantage of the accompanying characteristics of the closed loop control system, rolling force forecasting model is built based on neural networks. The comparison results of the prediction and the actual signal are taken as residual signals. Wavelet transform is used to obtain the components of high and low frequency of the residual signal. Wave let decomposition results make fault feature clear and time-domain positioning accurately. Fault numerical criterion is established through Lipschitz exponent. By analyzing the varied fault features which correspond to varied fault rea sons, the fault diagnosis of HAGC system is implemented successfully.
