Under different degradation conditions, the complexity of natural oscillation of the piston pump will change. Given the difference of the characteristic values of the vibration signal under different degradation states, this paper presents a degradation state recognition method based on improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) and eXtreme gradient boosting (XGBoost) to improve the accuracy of state recognition. Firstly, ICEEMDAN is proposed to alleviate the mode mixing phenomenon, which decomposes the vibration signal and obtain the intrinsic mode functions (IMFs) with less noise and more physical meaning, and subsequently the optimal IMF is found by using the correlation coefficient method. Then, the time domain, frequency domain, and entropy of the effective IMF are calculated, and the new characteristic values which can represent the degradation state are selected by principal component analysis (PCA) that it realizes dimension reduction. Finally, the above-mentioned characteristic indexes are used as the input of the XGBoost algorithm to achieve the recognition of the degradation state. In this paper, the vibration signals of four different degradation states are generated and analyzed through the piston pump slipper degradation experiment. By comparing the proposed method with different state recognition algorithms, it can be seen that the method based on ICEEMDAN and XGBoost is accurate and efficient, the average accuracy rate can reach more than 99%. Therefore, this method can more accurately describe the degradation state of the piston pump and has a highly practical application value.

The double flapper-nozzle servo valve is widely used to launch and guide the equipment. Due to the large instantaneous flow rate of servo valve working under specific operating conditions, the tempera

A remaining useful life (RUL) prediction method for an external gear pump is proposed by Bayesian regularized radial basis function neural network (Trainbr-RBFNN). The variational mode decomposition (VMD) algorithm has been used to denoise the vibration data of accelerated degradation test, followed by which, using the Hilbert modulation the reconstructed signal has been demodulated. After which, compared with the ensemble empirical mode decomposition (EEMD) algorithm and the modified ensemble empirical mode decomposition (MEEMD) algorithm. Subsequently, factor analysis (FA) has been selected to realize the fusion of various characteristic parameters, after which, the external gear pump's degradation evaluation index established and analyzed. Finally, the degradation evaluation index has been used to train the Trainbr-RBFNN model, and achieve gear pump degradation evaluation model for RUL prediction. Experiment results evidence that the RUL of the external gear pump can be accurately evaluated with the method used.

A water hydraulic axial piston pump has become the preferred power component of environmentally friendly water hydraulic transmission systems, due to its advantages of a compact structure, high power density, and so on. The poor friction and wear performance in the water medium, especially under extreme conditions of high speed and high pressure, limit the engineering application of the water hydraulic axial piston pump. In this review, the research progress for key friction pair materials (such as special corrosion-resistant alloys, engineering plastics, and engineering ceramics) for water hydraulic axial piston pumps is, firstly, summarized. Secondly, inspired by nature, the processing methods, lubrication drag-reduction mechanism, and tribological properties of the biomimetic surface textures are discussed. The effects of the surface texture shape, equivalent diameter, depth, and arrangement on the pump’s tribological properties are reviewed in detail. Finally, the application status of, and problems with, surface texture technology in water hydraulic axial piston pumps are summarized. It is suggested that future studies should focus on the multi-field coupling lubrication anti-friction mechanism of the multi-type composite texture under extreme conditions and mixed lubrication; and the anti-wear performance of the texture coupled with a coating modification, to further promote the surface texture in the field of lubrication antifriction engineering applications.

As a kind of hydraulic power component, the external gear pump determines the performance of the entire hydraulic system. The degradation state of gear pumps can be monitored by sensors. Based on the accelerated life test (ALT), this paper proposes a method to identify the wear degradation state of external gear pumps based on flow field analysis. Firstly, the external gear pump is theoretically analyzed. Secondly, dynamic grid technology is used to simulate the internal flow field of the gear pump in detail. Finally, the theoretical and simulation results are verified by the ALT. The results show that this method can effectively identify the wear degradation status of four sample pumps. The results of the work not only provide a solution to the research on the wear degradation of external gear pumps, but also provide strong technical support for the predictive maintenance of hydraulic pumps.

The slipper pair is the crucial friction pair of the seawater axial piston pump. Taking seawater as the working medium will inevitably affect the bearing performance of the slipper pair. In this paper, a seawater axial piston pump slipper pair model with a composite bionic micro-texture of the first-stage circular pit and the second-stage circular ball is established. Using the CFD simulation method, 18 groups of orthogonal tests are designed to explore the effects of seven test factors, such as rotational speed, first-stage diameter, first-stage aspect ratio, second-stage diameter, second-stage aspect ratio, area ratio, and distribution angle, on the bearing characteristics of the water film of the slipper pair. Study whether cavitation can further improve the bearing characteristics of the water film. The research shows that there is a vortex behind the circular pit, and there is a pressure difference in the calculation domain of the water film. The existence of the pressure difference causes the bearing force of the water film surface to increase. The cavitation phenomenon mainly occurs at the divergent wedge behind the circular pit. Among them, the total pressure bearing force of the 5th test group increased by 90% after introducing cavitation effect, and the total pressure bearing force of the 17th test group increased by about 86% compared with other test groups at the same speed. The order of the test factors affecting the water film bearing features is: A (rotational speed) > C (first-stage aspect ratio) > B (first-stage diameter) > E (second-stage aspect ratio) > F (area ratio) > D (second-stage diameter) > G (distribution angle). The optimal model is A₆B₂C₁D₃E₃F₂G₃.