In an actual control system, it is often difficult to find out where the faults are if only based on the outside fault phenomena, acquired frequently from a fault system. So the fault diagnosis by outside fault phenom...In an actual control system, it is often difficult to find out where the faults are if only based on the outside fault phenomena, acquired frequently from a fault system. So the fault diagnosis by outside fault phenomena is considered. Based on the theory of fuzzy recognition and fault diagnosis, this method only depends on experience and statistical data to set up fuzzy query relationship between the outside phenomena (fault characters) and the fault sources (fault patterns). From this relationship the most probable fault sources can be obtained, to attain the goal of quick diagnosis. Based on the above approach, the standard fuzzy relationship matrix is stored in the computer as a system database. And experiment data are given to show the fault diagnosis results. The important parameters can be on line sampled and analyzed, and when faults occur, faults can be found, the alarm is given and the controller output is regulated.展开更多
Damping faults in a helicopter rotor hub are diagnosed by using vibration signals from the fuselage. Faults include the defective lag damper and raspings in its flap and feathering hinges. Experiments on the diagnosis...Damping faults in a helicopter rotor hub are diagnosed by using vibration signals from the fuselage. Faults include the defective lag damper and raspings in its flap and feathering hinges. Experiments on the diagnosis of three faults are carried out on a rotor test rig with the chosen fault each time. Fuselage vibration signals from specified locations are measured and analyzed by the fast Fourier transform in the frequency domain. It is demonstrated that fuselage vibration frequency spectra induced by three faults are different from each other. The probabilistic neural network （PNN） is adopted to detect three faults. Results show that it is feasible to diagnose three faults only using fuselage vibration data.展开更多
A relevance vector machine (RVM) based fault diagnosis method was presented for non-linear circuits. In order to simplify RVM classifier, parameters selection based on particle swarm optimization (PSO) and preprocessi...A relevance vector machine (RVM) based fault diagnosis method was presented for non-linear circuits. In order to simplify RVM classifier, parameters selection based on particle swarm optimization (PSO) and preprocessing technique based on the kurtosis and entropy of signals were used. Firstly, sinusoidal inputs with different frequencies were applied to the circuit under test (CUT). Then, the resulting frequency responses were sampled to generate features. The frequency response was sampled to compute its kurtosis and entropy, which can show the information capacity of signal. By analyzing the output signals, the proposed method can detect and identify faulty components in circuits. The results indicate that the fault classes can be classified correctly for at least 99% of the test data in example circuit. And the proposed method can diagnose hard and soft faults.展开更多
The stochastic resonance behavior of coupled stochastic resonance(SR)system with time-delay under mass and frequency fluctuations was studied.Firstly,the approximate system model of the time-delay system was obtained ...The stochastic resonance behavior of coupled stochastic resonance(SR)system with time-delay under mass and frequency fluctuations was studied.Firstly,the approximate system model of the time-delay system was obtained by the theory of small time-delay approximation.Then,the random average method and Shapiro-Loginov algorithm were used to calculate the output amplitude ratio of the two subsystems.The simulation analysis shows that increasing the time-delay and the input signal amplitude appropriately can improve the output response of the system.Finally,the system is applied to bearing fault diagnosis and compared with the stochastic resonance system with random mass and random frequency.The experimental results show that the coupled SR system taking into account the actual effect of time-delay and couple can more effectively extract the frequency of the fault signal,and thus realizing the diagnosis of the fault signal,which has important engineering application value.展开更多
Simultaneous faults often occur in running equipments, in order to solve the problems of the simultaneous faults, a new approach based on random sets and Dezert-Smarandache Theory (DSmT) is proposed in this paper. Fir...Simultaneous faults often occur in running equipments, in order to solve the problems of the simultaneous faults, a new approach based on random sets and Dezert-Smarandache Theory (DSmT) is proposed in this paper. Firstly, the simultaneous faults' model is built based on the generalized frame of discernment in DSmT. Secondly, according to the unified description of combination rules in evidence reasoning based on random sets, a new combination rule for simultaneous faults diagnosis is proposed. Thirdly, according to the working characteristics and environment of the sensors used to acquire fault characteristic information, a new method to construct basic probability assignment function is pro- posed based on membership. Finally, diagnosis result is obtained by use of the new combination rule combined with decision rules. A case pertaining to the fault diagnosis for a multi-function rotor test-bed is given, and the result shows that the proposed diagnosis approach is feasible and efficient.展开更多
Coal mines require various kinds of machinery. The fault diagnosis of this equipment has a great impact on mine production. The problem of incorrect classification of noisy data by traditional support vector machines ...Coal mines require various kinds of machinery. The fault diagnosis of this equipment has a great impact on mine production. The problem of incorrect classification of noisy data by traditional support vector machines is addressed by a proposed Probability Least Squares Support Vector Classification Machine (PLSSVCM). Samples that cannot be definitely determined as belonging to one class will be assigned to a class by the PLSSVCM based on a probability value. This gives the classification results both a qualitative explanation and a quantitative evaluation. Simulation results of a fault diagnosis show that the correct rate of the PLSSVCM is 100%. Even though samples are noisy, the PLSSVCM still can effectively realize multi-class fault diagnosis of a roller bearing. The generalization property of the PLSSVCM is better than that of a neural network and a LSSVCM.展开更多
A 5-level PFC （power factor correction） topology with fault-diagnostic and fault-tolerant capability is proposed and compared to known structures. It is derived from a 3-level non differential double-boost PFC inclu...A 5-level PFC （power factor correction） topology with fault-diagnostic and fault-tolerant capability is proposed and compared to known structures. It is derived from a 3-level non differential double-boost PFC including fly-cap cells. The series-connection of the two low-voltage switching-cells is decoupled by a single flying capacitor that provides a direct fault-tolerant capability and a post-failure operation increasing the availability of converter. The monitoring of the voltages across flying capacitors allows a rapid detection and localization either for open circuit failure or short-circuits failure. A PWM （pulse width modulation） phase-disposition type reconfiguration is also used and presented in order to optimize both normal operation and post-fault continuation. The design and the most important features are highlighted thanks to a digital control frame and a mock-up rated to： AC voltage network 115 V-load 400 V-nominal power 4 kW-switching frequency 62 kHz.展开更多
文摘In an actual control system, it is often difficult to find out where the faults are if only based on the outside fault phenomena, acquired frequently from a fault system. So the fault diagnosis by outside fault phenomena is considered. Based on the theory of fuzzy recognition and fault diagnosis, this method only depends on experience and statistical data to set up fuzzy query relationship between the outside phenomena (fault characters) and the fault sources (fault patterns). From this relationship the most probable fault sources can be obtained, to attain the goal of quick diagnosis. Based on the above approach, the standard fuzzy relationship matrix is stored in the computer as a system database. And experiment data are given to show the fault diagnosis results. The important parameters can be on line sampled and analyzed, and when faults occur, faults can be found, the alarm is given and the controller output is regulated.
文摘Damping faults in a helicopter rotor hub are diagnosed by using vibration signals from the fuselage. Faults include the defective lag damper and raspings in its flap and feathering hinges. Experiments on the diagnosis of three faults are carried out on a rotor test rig with the chosen fault each time. Fuselage vibration signals from specified locations are measured and analyzed by the fast Fourier transform in the frequency domain. It is demonstrated that fuselage vibration frequency spectra induced by three faults are different from each other. The probabilistic neural network （PNN） is adopted to detect three faults. Results show that it is feasible to diagnose three faults only using fuselage vibration data.
基金Project(Z132012)supported by the Second Five Technology-based in Science and Industry Bureau of ChinaProject(YWF1103Q062)supported by the Fundemental Research Funds for the Central Universities in China
文摘A relevance vector machine (RVM) based fault diagnosis method was presented for non-linear circuits. In order to simplify RVM classifier, parameters selection based on particle swarm optimization (PSO) and preprocessing technique based on the kurtosis and entropy of signals were used. Firstly, sinusoidal inputs with different frequencies were applied to the circuit under test (CUT). Then, the resulting frequency responses were sampled to generate features. The frequency response was sampled to compute its kurtosis and entropy, which can show the information capacity of signal. By analyzing the output signals, the proposed method can detect and identify faulty components in circuits. The results indicate that the fault classes can be classified correctly for at least 99% of the test data in example circuit. And the proposed method can diagnose hard and soft faults.
基金Project(61771085)supported by the National Natural Science Foundation of ChinaProject(KJQN 201900601)supported by the Research Project of Chongqing Educational Commission,China。
文摘The stochastic resonance behavior of coupled stochastic resonance(SR)system with time-delay under mass and frequency fluctuations was studied.Firstly,the approximate system model of the time-delay system was obtained by the theory of small time-delay approximation.Then,the random average method and Shapiro-Loginov algorithm were used to calculate the output amplitude ratio of the two subsystems.The simulation analysis shows that increasing the time-delay and the input signal amplitude appropriately can improve the output response of the system.Finally,the system is applied to bearing fault diagnosis and compared with the stochastic resonance system with random mass and random frequency.The experimental results show that the coupled SR system taking into account the actual effect of time-delay and couple can more effectively extract the frequency of the fault signal,and thus realizing the diagnosis of the fault signal,which has important engineering application value.
基金Supported by the National Natural Science Foundation of China (No.60434020, No.60772006)the Zhejiang Natural Science Foundation (R106745, Y1080422)
文摘Simultaneous faults often occur in running equipments, in order to solve the problems of the simultaneous faults, a new approach based on random sets and Dezert-Smarandache Theory (DSmT) is proposed in this paper. Firstly, the simultaneous faults' model is built based on the generalized frame of discernment in DSmT. Secondly, according to the unified description of combination rules in evidence reasoning based on random sets, a new combination rule for simultaneous faults diagnosis is proposed. Thirdly, according to the working characteristics and environment of the sensors used to acquire fault characteristic information, a new method to construct basic probability assignment function is pro- posed based on membership. Finally, diagnosis result is obtained by use of the new combination rule combined with decision rules. A case pertaining to the fault diagnosis for a multi-function rotor test-bed is given, and the result shows that the proposed diagnosis approach is feasible and efficient.
基金supported by the Program for New Century Excellent Talents in University (NoNCET- 08-0836)the National Natural Science Foundation of China (Nos60804022, 60974050 and 61072094)+1 种基金the Fok Ying-Tung Education Foundation for Young Teachers (No121066)by the Natural Science Foundation of Jiangsu Province (No.BK2008126)
文摘Coal mines require various kinds of machinery. The fault diagnosis of this equipment has a great impact on mine production. The problem of incorrect classification of noisy data by traditional support vector machines is addressed by a proposed Probability Least Squares Support Vector Classification Machine (PLSSVCM). Samples that cannot be definitely determined as belonging to one class will be assigned to a class by the PLSSVCM based on a probability value. This gives the classification results both a qualitative explanation and a quantitative evaluation. Simulation results of a fault diagnosis show that the correct rate of the PLSSVCM is 100%. Even though samples are noisy, the PLSSVCM still can effectively realize multi-class fault diagnosis of a roller bearing. The generalization property of the PLSSVCM is better than that of a neural network and a LSSVCM.
文摘A 5-level PFC （power factor correction） topology with fault-diagnostic and fault-tolerant capability is proposed and compared to known structures. It is derived from a 3-level non differential double-boost PFC including fly-cap cells. The series-connection of the two low-voltage switching-cells is decoupled by a single flying capacitor that provides a direct fault-tolerant capability and a post-failure operation increasing the availability of converter. The monitoring of the voltages across flying capacitors allows a rapid detection and localization either for open circuit failure or short-circuits failure. A PWM （pulse width modulation） phase-disposition type reconfiguration is also used and presented in order to optimize both normal operation and post-fault continuation. The design and the most important features are highlighted thanks to a digital control frame and a mock-up rated to： AC voltage network 115 V-load 400 V-nominal power 4 kW-switching frequency 62 kHz.
