Papers by Keyword: Fault Diagnosis

Abstract: Micro-satellite has long-term in-orbit work in the harsh environment of space, the components such as actuators and sensors in the attitude control system continue to perform in-orbit control operations, therefore are prone to faults. In practical mission, such as formation flying, orbital transfer, de-tumbing and attitude control need to use thruster to control. As the thrust control is fail, the entire mission fails. In the paper, the two-stage unscented kalman filter is used to obtain the effectiveness factor value and system estimated states are obtained. Meanwhile, a robust thruster controller is designed with the estimated results to accomplish the joint design of Fault Detection and Diagnosis and Fault-Tolerant Control.

Abstract: Hydraulic system is widely used in the ship, when the diameter of tiny particles in hydraulic oil exceeds 20μm it indicates that the abnormal wear occurred and the malfunction may cause. This paper uses the light blockage method, the microfluidic detection chip for hydraulic oil detection has been designed and fabricated, a simple and effective optical detection system is developed with the signal amplification and data collection to achieve the detection of tiny particles, and finally through the JAVA programming to count the number of particles in which the diameter is more than 20μm. The results of rapid detections on iron particles with diameter between 25μm and 38μm show the good performance of the detection system and prove that the method is feasible.

Abstract: Compare and analysis the transient identification in Nuclear Power Plant fault diagnosis method. According to how does these methods for nuclear power plant systems HTR effect, Further proposed to a problem that towards existing transient recognition of methods to verification effectiveness. Preliminary analysis of the three kinds of validation strategy, after a comparative demonstration, it is formed the preliminary research on the utility analysis framework. Utility to verify the framework for the Nuclear Power Plant fault diagnosis methods carry out intensive research provides a theoretical basis.

Abstract: This research presents a time series analysis and artificial neural network (ANN)-based scheme for fault diagnosis of power transformers, which extracts the characteristic parameters of the faults of the transformer from the results of time series analysis and bases on this basis establishes the corresponding back propagation (BP) neural network to detect the transformer operating faults. The simulation experimental results show that as compared to the related works, the proposed approach effectively integrates the superiority of time series analysis and BP neural network and thus can greatly improve the diagnosis accuracy and reliability.

Abstract: High frequency vibration signal, cylinder-inside pressure and ultrasonic wave are monitored under working condition of a reciprocating compressor. High frequency vibration signal and ultrasonic wave are processed using high frequency band-pass filtering, and then enveloped. The pressure signal is filtered with a low-pass digital filter. The fault causes of the machine can be determined by the enveloped waveform of vibration signal and ultrasonic wave, as well as the pressure curve comprehensively. We can confirm the truth that this fault diagnosis method is accurate and reliable for reciprocating compressors through a number of the results of fault diagnosis.

Abstract: High Voltage Direct Current (HVDC) system was often the link between major power grids. In order to ensure the safe operation of HVDC, fault diagnosis method was studied. The system structure of HVDC Light system was analyzed, and the normal and fault conditions of the transmission system were simulated in the Matlab platform. This method was very convenient and simple, and it could restore the real situation. The use of simulated waveform could effectively identify the fault types of actual situation, and then it was a flexible, efficient and practical method of fault diagnosis in HVDC Light system.

Abstract: In view of the appearance of instability and malfunction problem for level control system in the steam drum of boiler, a new method to use statistical process control (SPC) was proposed, which analyzed the level data by the SPC. It can extract the main features of the level variable, and set up the upper and lower monitoring limits for the level control system in the steam drum of boiler. The decision-making basis for the operator can be provided by monitoring control accuracy of the level control system. With this method, it can improve the control accuracy of the level variable and provide the information quickly and efficiently for the fault diagnosis of the level control system, prevent the malfunction occurs, ensure safety and stable operation for the boiler control system.

Abstract: For sets of measurements does not follow a Gaussian distribution, the conventional principal component analysis (PCA) method has the disadvantage of low diagnostic yield. An integrated fault diagnosing method based on the independent component analysis (ICA) and support vector machine (SVM) was proposed. The observed data is preprocessed and feature extracted by ICA and a monitoring model was developed. When the fault is detected, SVM is adopted to classifying and diagnosing the type of faults. It is applied for fault diagnosing in the Three-Tank water level control system. The simulation results show that the fault diagnosis rates of this method is 99.8%, which can effectively detect and diagnose the fault.

Abstract: An autonomous underwater vehicle (AUV) should have the ability of adapting the complexity and unpredictability of the marine environment, which means that the technology of AUV’s fault diagnosis is very significant, especially the part of thrusters. In order to make it possible, one fault diagnosis strategy of AUV’s thrusters is proposed, which is based on the support vector machine (SVM). SVM has many unique advantages in solving small-sample, nonlinear and high dimensional problems. In this paper, different character signal is inputted SVM to train and test it. The simulation results show that the fault diagnosis of AUV’s thrusters based on offline SVM can classify the fault styles successfully, which proves its feasibility and effectiveness. This method offers a new way to solve the fault diagnosis of AUVs.

Abstract: Aiming at the study of key technology of the integrated test platform of wireless communication equipment, this paper consists of several technology contents, mainly including criterion of detection, fault diagnosis evaluation, equipment type matching, optimization of circuit detection point, signal acquisition and so on. Combined with the intelligent circuit detection techniques and the development of software and hardware, the specific testing and repairing techniques of the wireless communication equipment are given to realize the steps, methods and processes, and the testing platform united with technology verification and software and hardware is developed and achieved.