The condition monitoring and fault diagnosis of rolling element bearings are particularly crucial in rotating mechanical applications in industry. A bearing fault signal contains information not only about fault condi...The condition monitoring and fault diagnosis of rolling element bearings are particularly crucial in rotating mechanical applications in industry. A bearing fault signal contains information not only about fault condition and fault type but also the severity of the fault. This means fault severity quantitative analysis is one of most active and valid ways to realize proper maintenance decision. Aiming at the deficiency of the research in bearing single point pitting fault quantitative diagnosis, a new back-propagation neural network method based on wavelet packet decomposition coefficient entropy is proposed. The three levels of wavelet packet coefficient entropy（WPCE） is introduced as a characteristic input vector to the BPNN. Compared with the wavelet packet decomposition energy ratio input vector, WPCE shows more sensitive in distinguishing from the different fault severity degree of the measured signal. The engineering application results show that the quantitative trend fault diagnosis is realized in the different fault degree of the single point bearing pitting fault. The breakthrough attempt from quantitative to qualitative on the pattern recognition of rolling element bearings fault diagnosis is realized.展开更多
Based on the internet technology,it has become possible to complete remote monitoring and fault diagnosis for the numerical control machine.In order to capture the micro-shock signal induced by the incipient fault on ...Based on the internet technology,it has become possible to complete remote monitoring and fault diagnosis for the numerical control machine.In order to capture the micro-shock signal induced by the incipient fault on the rotating parts,the reso-nance demodulation technology is utilized in the system.As a subsystem of the remote monitoring system,the embedded data acquisi-tion instrument not only integrates the demodulation board but also complete the collection and preprocess of monitoring data from different machines.Furthermore,through connecting to the internet,the data can be transferred to the remote diagnosis center and data reading and writing function can be finished in the database.At the same time,the problem of the IP address floating in the dial-up of web server is solved by the dynamic DNS technology.Finally,the remote diagnosis software developed on the Lab VIEW platform can analyze the monitoring data from manufacturing field.The research results have indicated that the equipment status can be monitored by the system effectively.展开更多
The early impulse fault diagnosis of the gearbox in rolling mills is often difficult and labour intensive because the gearbox of that high speed machine is multi-shafting transmission system,in which many gearsets and...The early impulse fault diagnosis of the gearbox in rolling mills is often difficult and labour intensive because the gearbox of that high speed machine is multi-shafting transmission system,in which many gearsets and rolling bears work together at the same time and there are much complex frequency structure and various disturb.A new time-frequency method based on the wavelet packets technique was developed and used to extract the impact feature from signals collected from faulty data of one rolling mills gearbox.The method improves the signal to noise ration so that results obtained using this method represents features with fine resolution in both low-frequency and the high frequency bands.The results of analysis indicate the validity and the practicability of the method proposed here.展开更多
The component of gear vibration signal is very complex,when a localized tooth defect such as a tooth crack is pre-sent,the engagement of the cracked tooth will induce an impulsive change with comparatively low energy ...The component of gear vibration signal is very complex,when a localized tooth defect such as a tooth crack is pre-sent,the engagement of the cracked tooth will induce an impulsive change with comparatively low energy to the gear mesh signal and the background noise.This paper presents a new comprehensive demodulation method which combined with amplitude envelop demodulation and phase demodulation to extract gear crack early fault.A mathematical model of gear vibration signal contain crack fault is put forward.Simulation results based on this model show that the new comprehensive demodulation method is more effective in finding fault and judging fault level then conventional single amplitude demodulation at present.展开更多
Traditional fault diagnosis systems of rolling mills mostly use single machine monitoring net,which leads the re-al-time data running only in the enterprise locally and can not monitor and manage the high-speed wire r...Traditional fault diagnosis systems of rolling mills mostly use single machine monitoring net,which leads the re-al-time data running only in the enterprise locally and can not monitor and manage the high-speed wire rolling mills between units,workshops and factories concentratedly.A new-type structure of remote diagnosis system for high-speed wire rolling mills is pre-sented in this paper.The signal processing,computer network and remote diagnosis etc techniques are used to predictive maintenance manage the rolling mills units in this system.The new structure reinforced the remote feedback function,made up the existing fault diagnosis systems’insufficiency in the extension and the function,promoted resource sharing and avoided the repeat develop-ment.The remote diagnosis example shows that the system can monitor and diagnose the fault information of remote machine timely and effectively.展开更多
In order to solve the low efficiency and poor precision problems of traditional ink control methods on domestic offset printers,developing modern ink automatic control system has become more and more urgent.As an impo...In order to solve the low efficiency and poor precision problems of traditional ink control methods on domestic offset printers,developing modern ink automatic control system has become more and more urgent.As an important subsystem,the hu-man computer interface(HCI)is a key function for the wholly automatic control.Once this goal is obtained,all the printing pro-cedures especially the automatic control of ink volume should be finished with human computer interface in different areas.consid-ering the HCI design theory and structure characteristics of domestic printers comprehensively,the HCI prototype for automatic ink control system has been developed based on Visual Basic platform.As the individual ink key is instead of the integrated key,the di-vision result of ink fountain can be displayed on the interface.Through the interface,the dynamic adjusting functions such as mod-ifying ink volume,locking or unlocking each ink key and real-time displaying the adjusting results etc.can be completed.The sim-ulation test has shown that the opening and practical feature of the prototype is satisfactory.展开更多
针对强背景噪声及谐波干扰的滚动轴承早期微弱故障特征提取,提出一种改进奇异值分解(Improved singular value decomposition,ISVD)的故障诊断新方法。首先,针对正弦信号、复合正弦信号和周期性冲击信号各自特征,根据奇异值子对(Singula...针对强背景噪声及谐波干扰的滚动轴承早期微弱故障特征提取,提出一种改进奇异值分解(Improved singular value decomposition,ISVD)的故障诊断新方法。首先,针对正弦信号、复合正弦信号和周期性冲击信号各自特征,根据奇异值子对(Singular value pairs,SVP)的形成原理,分别提出改进的Hankel矩阵嵌入维数优化选取原则,明确了该参数的量化范围,进而确定奇异值分解(Singular value decomposition,SVD)的最佳嵌入维数。该算法可自适应匹配SVD的Hankel矩阵最佳嵌入维数,进而获得形成SVP分布的信号分解策略。随后,结合谐波干扰的能量及SVP分布,实现对包含轴承微弱故障成分的子信号进行定位。最后,采用反对角线平均法重构目标子信号,对其进行包络谱分析获得诊断结果。仿真的滚动轴承故障信号和多组试验信号分析验证了所提方法的可行性和有效性。展开更多
基金Supported by National Natural Science Foundation of China(Grant Nos.51175007,51075023)
文摘The condition monitoring and fault diagnosis of rolling element bearings are particularly crucial in rotating mechanical applications in industry. A bearing fault signal contains information not only about fault condition and fault type but also the severity of the fault. This means fault severity quantitative analysis is one of most active and valid ways to realize proper maintenance decision. Aiming at the deficiency of the research in bearing single point pitting fault quantitative diagnosis, a new back-propagation neural network method based on wavelet packet decomposition coefficient entropy is proposed. The three levels of wavelet packet coefficient entropy（WPCE） is introduced as a characteristic input vector to the BPNN. Compared with the wavelet packet decomposition energy ratio input vector, WPCE shows more sensitive in distinguishing from the different fault severity degree of the measured signal. The engineering application results show that the quantitative trend fault diagnosis is realized in the different fault degree of the single point bearing pitting fault. The breakthrough attempt from quantitative to qualitative on the pattern recognition of rolling element bearings fault diagnosis is realized.
文摘Based on the internet technology,it has become possible to complete remote monitoring and fault diagnosis for the numerical control machine.In order to capture the micro-shock signal induced by the incipient fault on the rotating parts,the reso-nance demodulation technology is utilized in the system.As a subsystem of the remote monitoring system,the embedded data acquisi-tion instrument not only integrates the demodulation board but also complete the collection and preprocess of monitoring data from different machines.Furthermore,through connecting to the internet,the data can be transferred to the remote diagnosis center and data reading and writing function can be finished in the database.At the same time,the problem of the IP address floating in the dial-up of web server is solved by the dynamic DNS technology.Finally,the remote diagnosis software developed on the Lab VIEW platform can analyze the monitoring data from manufacturing field.The research results have indicated that the equipment status can be monitored by the system effectively.
基金supported by national 863 project(2002AA424033)Beijing Municipal Sciencc&Tcchnology Commission project(H030330050110)Doctor’s Science and Research Start-Up Pro-ject of Beijing University of Technology(00138).
文摘The early impulse fault diagnosis of the gearbox in rolling mills is often difficult and labour intensive because the gearbox of that high speed machine is multi-shafting transmission system,in which many gearsets and rolling bears work together at the same time and there are much complex frequency structure and various disturb.A new time-frequency method based on the wavelet packets technique was developed and used to extract the impact feature from signals collected from faulty data of one rolling mills gearbox.The method improves the signal to noise ration so that results obtained using this method represents features with fine resolution in both low-frequency and the high frequency bands.The results of analysis indicate the validity and the practicability of the method proposed here.
基金This work is supported by national 863 project(2002AA424033)Beijing Municipal Science&Tech-nology Commission project(H030330050110)Doctor's Science and Research Start-Up Project of Beijing U-niversity of Technology(00138).
文摘The component of gear vibration signal is very complex,when a localized tooth defect such as a tooth crack is pre-sent,the engagement of the cracked tooth will induce an impulsive change with comparatively low energy to the gear mesh signal and the background noise.This paper presents a new comprehensive demodulation method which combined with amplitude envelop demodulation and phase demodulation to extract gear crack early fault.A mathematical model of gear vibration signal contain crack fault is put forward.Simulation results based on this model show that the new comprehensive demodulation method is more effective in finding fault and judging fault level then conventional single amplitude demodulation at present.
基金supported by national 863 project(2002AA424033)Beijing MunicipalScience&Technology Commission project(H030330050110)Doctor's Science and Research Start-Up Pro-ject of Beijing University of Technology(00138).
文摘Traditional fault diagnosis systems of rolling mills mostly use single machine monitoring net,which leads the re-al-time data running only in the enterprise locally and can not monitor and manage the high-speed wire rolling mills between units,workshops and factories concentratedly.A new-type structure of remote diagnosis system for high-speed wire rolling mills is pre-sented in this paper.The signal processing,computer network and remote diagnosis etc techniques are used to predictive maintenance manage the rolling mills units in this system.The new structure reinforced the remote feedback function,made up the existing fault diagnosis systems’insufficiency in the extension and the function,promoted resource sharing and avoided the repeat develop-ment.The remote diagnosis example shows that the system can monitor and diagnose the fault information of remote machine timely and effectively.
文摘In order to solve the low efficiency and poor precision problems of traditional ink control methods on domestic offset printers,developing modern ink automatic control system has become more and more urgent.As an important subsystem,the hu-man computer interface(HCI)is a key function for the wholly automatic control.Once this goal is obtained,all the printing pro-cedures especially the automatic control of ink volume should be finished with human computer interface in different areas.consid-ering the HCI design theory and structure characteristics of domestic printers comprehensively,the HCI prototype for automatic ink control system has been developed based on Visual Basic platform.As the individual ink key is instead of the integrated key,the di-vision result of ink fountain can be displayed on the interface.Through the interface,the dynamic adjusting functions such as mod-ifying ink volume,locking or unlocking each ink key and real-time displaying the adjusting results etc.can be completed.The sim-ulation test has shown that the opening and practical feature of the prototype is satisfactory.
文摘针对强背景噪声及谐波干扰的滚动轴承早期微弱故障特征提取,提出一种改进奇异值分解(Improved singular value decomposition,ISVD)的故障诊断新方法。首先,针对正弦信号、复合正弦信号和周期性冲击信号各自特征,根据奇异值子对(Singular value pairs,SVP)的形成原理,分别提出改进的Hankel矩阵嵌入维数优化选取原则,明确了该参数的量化范围,进而确定奇异值分解(Singular value decomposition,SVD)的最佳嵌入维数。该算法可自适应匹配SVD的Hankel矩阵最佳嵌入维数,进而获得形成SVP分布的信号分解策略。随后,结合谐波干扰的能量及SVP分布,实现对包含轴承微弱故障成分的子信号进行定位。最后,采用反对角线平均法重构目标子信号,对其进行包络谱分析获得诊断结果。仿真的滚动轴承故障信号和多组试验信号分析验证了所提方法的可行性和有效性。
