Papers by Keyword: Hydraulic Pump

Abstract: As the failure of a hydraulic pump is always instantaneous, the failure data are difficult to obtain. High-efficiency fault diagnosis under small-sample conditions for hydraulic pumps is urgently required in engineering applications. A fault diagnosis approach based on wavelet packet transform (WPT), singular value decomposition (SVD), and support vector machine (SVM) is proposed in this study. First, the nonlinear, non-stationary vibration signal of the hydraulic pump is decomposed into components by WPT. Second, singular value vectors are acquired as feature vectors by applying SVD to the components. Third, the health states of the hydraulic pumps are determined and classified with a SVM classifier. Furthermore, the SVM and Elman neural network classifiers are compared in terms of fault classification to demonstrate the superiority of SVM in dealing with small-sample problems. The results of the plunger pump rig test show that the proposed method can diagnose the faults of the hydraulic pump accurately even when the number of samples is small.

Abstract: The principle of neural network’s PNN algorithm was introduced, Combining with the structure feature and work principle of the hydraulic pump, a fault diagnosis system based on PNN neural network was established. The feasibility of the system was proved through the identification, emulation and experimentation of hydraulic system’s fault patterns. The PNN control model was simulated using Matlab/Simulink toolbox. This model analyzed and studied the PNN network predictive diagnostic rate. Under different sample size and SPREAD, the simulation’s results show that this method has favorable identified capability of fault mode and favorable applicability to the hydraulic pump.

Abstract: A novel method which is based on ensemble empirical mode decomposition (EEMD) and symbolic time series analysis (STSA) was proposed in this paper. Firstly, the vibration signal of hydraulic pump was decomposed into a number of stationary intrinsic mode functions (IMFs). Secondly, the sensitive component was extracted. Finally, the relative entropy (RE) was extracted from the sensitive components and they were used as the indicator to distinguish the faults of hydraulic pump. The research results of actual testing vibration signal demonstrated the rationality and effectiveness of the proposed method in this paper.

Abstract: In this paper, an approach of fuzzy Petri nets (FPN) is proposed to simulate the fault spreading and diagnosis of hydraulic pump. First, the fuzzy production rules and the definition of FPN were briefly introduced. Then, its knowledge reasoning process and the matrix operations based on an algorithm were conducted, which makes full use of its parallel reasoning ability and makes it simpler and easier to implement. Finally, a case of hydraulic pump fault diagnosis with FPN was presented in detail, for illustrating the interest of the proposed modeling and analysis algorithm.

Abstract: The failure of hydraulic pump as a power unit in hydraulic systems affects directly the proper performance of the systems. Therefore, the monitoring of the pump performance and diagnosis of pump faults are urgent problems in want of solution. The principle of RBF algorithm is described. Study on fault diagnosis based on RBF for hydraulic pump. The test and analysis results indicate that the method is simple and efficient.

Abstract: This paper presents a new method to solve the problem of speed and pressure constant value adjustment in the high-power hydraulic pumps and hydraulic motors performance test system which is based on energy recycling technology. The constant value control method is designed based on characteristic parameters of the process, including control resolution, overshoot and adjustment time. Experiments were implemented to verify the effectiveness of the proposed method. Experimental result shows that the proposed method reduced the test time by about 52.4% than before. The convergence rate of the constant value adjusting process and the test efficiency are significantly improved by the proposed method.

Abstract: The application of Bondsim library for the stochastic vibrations modelling andsimulation is given in this paper. For that purpose the stochastic Bondsim elementsare used. The efficiency of the proposed approach for modeling and simulation ofstochastic dynamic systems vibrations is illustrated using an example ofhydraulic ram pump.

Abstract: For the problems of not enough fault information for the complicated equipment and difficult to predict the fault, we apply Support Vector Machine (SVM) to build the fault prediction model. On the basis of analyzing regression algorithm of SVM, we use Least Square Support Vector Machine (LS-SVM) to build the fault prediction model.LS-SVM can effectively debase the complication of the model. Finally, we take the fault data of a hydraulic pump to validate this model. By selecting appropriate parameters, this model can make better prediction for the fault data, and it has higher prediction precision. It is proved that the fault prediction model which based on LS-SVM can make better prediction for fault trend of complicated equipment.

Abstract: In the testing of the oil temperature controlling of hydraulic pump performance test-system, the changing of oil temperature bring the testing accuracy decrease, so it can influence nicety and contrast of test-bed. A computer device of oil temperature real time control are designed. The result of control achieve B level accuracy of international and guild. The software of computer is minimum variance correcting by oneself.

Abstract: The performance of hydraulic pump will directly affect the normal work of the entire hydraulic system, so it is essential for its condition monitoring and fault prediction. It collects vibration signal and pressure signal for hydraulic pump which degenerates from the normal state to loose slipper state. It uses wavelet packet to decompose energy of frequency area in order to get fault feature vectors and builds support vector machine prediction model for feature vectors, then predicts possible fault by D-S evidence theory. The experiment results show that the method can effectively predict fault for hydraulic pump.