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| 1 | Adaptive decision-level fusion strategy for the fault diagnosis of axial piston pumps using multiple channels of vibration signals显示文摘An axial piston pump is a key component that plays the role of the 'heart' in hydraulic systems. The pump failure will lead to an unexpected breakdown of the entire hydraulic system or even economic loss and catastrophic safety consequences. Several vibration-based machine learning methods have been developed to detect and diagnose faults of axial piston pumps. However,most of these intelligent diagnosis methods use single-sensor vibration data to monitor the pump health states. Additionally, the diagnostic accuracy is unacceptable in most situations due to the complex pump structure and limited sensor information.Therefore, this study proposes a multi-sensor fusion method to improve the fault diagnosis performance of axial piston pumps.The convolutional neural network receives three channels of vibration data and makes the final diagnosis through information fusion at the decision level. The proposed decision fusion method is evaluated on the classification task of leakage levels of an actual axial piston pump. The experimental results show that the proposed method improves the classification accuracy by adjusting the probability distribution of classification according to the learned weight matrix. | CHAO Qun GAO HaoHan TAO JianFeng WANG YuanHang ZHOU Jian LIU ChengLiang | 2022 | Science China(Technological Sciences)2022，65，2： | 2 |
| 2 | Fault diagnosis of axial piston pumps with multi-sensor data and convolutional neural network显示文摘Axial piston pumps have wide applications in hydraulic systems for power transmission.Their condition monitoring and fault diagnosis are essential in ensuring the safety and reliability of the entire hydraulic system.Vibration and discharge pressure signals are two common signals used for the fault diagnosis of axial piston pumps because of their sensitivity to pump health conditions.However,most of the previous fault diagnosis methods only used vibration or pressure signal,and literatures related to multi-sensor data fusion for the pump fault diagnosis are limited.This paper presents an end-to-end multi-sensor data fusion method for the fault diagnosis of axial piston pumps.The vibration and pressure signals under different pump health conditions are fused into RGB images and then recognized by a convolutional neural network.Experiments were performed on an axial piston pump to confirm the effectiveness of the proposed method.Results show that the proposed multi-sensor data fusion method greatly improves the fault diagnosis of axial piston pumps in terms of accuracy and robustness and has better diagnostic performance than other existing diagnosis methods. | Qun CHAO Haohan GAO Jianfeng TAO Chengliang LIU Yuanhang WANG Jian ZHOU | 2022 | Frontiers of Mechanical Engineering2022，17，3： | 2 |
| 3 | SVR Recommendation Algorithm of Civil Aviation Auxiliary Service Based on Context-Awareness显示文摘Analysis of the particularity of the civil aviation passenger auxiliary service recommendation scenario.As application of the traditional recommendation algorithm has certain limitation in civil aviation auxiliary services recommendation,a SVR recommendation algorithm of auxiliary service of civil aviation based on context-awareness was proposed.Analysis of the civil aviation passenger travel data,construct the civil aviation passenger preference model,then recommend auxiliary service for passengers.Based on the traditional two-dimensional user-item recommendation,considering the user characteristics,item attributes and user contextual information in the process of recommendation,which can effectively reduce the data sparseness in some degree.In addition,when there is a new user or a new item,whose similar users or items can be found according to the user or item attributes,to some extent,which can solve the problem of cold start.The experimental results show that the algorithm can recommend auxiliary service for passengers more accurately,which can provide convenience for passengers as well as increase the quality of airlines’services. | Haohan Liu Hongli Zhang Kanghua Hui Huaiqing He | 2015 | 国际计算机前沿大会会议论文集2015，，B12： | 0 |
| 4 | Preparation of Quaternary FeCoMoCu Metal Oxides for Oxygen Evolution Reaction显示文摘Molybdenum doping is an effective way to improve the oxygen evolution reaction(OER)properties of catalysts,which can efficiently improve the electronic conductivity,mass transport process,and intrinsic activity of transition metal oxides or hydroxides,especially for those multi-component oxides with more abundant active sites.Herein,we have prepared a quaternary FeCoMoCu metal oxide on Cu foam(FeCoMoCuO_(x)@Cu)as an efficient OER catalyst.As expected,FeCoMoCuO_(x)@Cu could exhibit a low overpotential(252 mV at the current density of 10 mA/cm^(2))and exceptional stability(10000 cycles of CV scans or constant electrolysis for 48 h). | HAO Zhimin LIU Dapeng GE Huaiyun ZUO Xintao FENG Xilan SHAO Mingzhe YU Haohan YUAN Guobao ZHANG Yu | 2022 | Chemical Research in Chinese Universities2022，38，3： | 0 |
| 5 | Prediction of atomization characteristics of pressure swirl nozzle with different structures显示文摘The structure of the pressure swirl nozzle is an important factor affecting its spray performance.This work aims to study pressure swirl nozzles with different structures by experiment and simulation.In the experiment,10 nozzles with different structures are designed to comprehensively cover various geometric factors.In terms of simulation,steady-state simulation with less computational complexity is used to study the flow inside the nozzle.The results show that the diameter of the inlet and outlet,the direction of the inlet,the diameter of the swirl chamber,and the height of the swirl chamber all affect the atomization performance,and the diameter of the inlet and outlet has a greater impact.It is found that under the same flow rate and pressure,the geometric differences do have a significant impact on the atomization characteristics,such as spray angle and SMD(Sauter mean diameter).Specific nozzle structures can be customized according to the actual needs.Data analysis shows that the spray angle is related to the swirl number,and the SMD is related to turbulent kinetic energy.Through data fitting,the equations for predicting the spray angle and the SMD are obtained.The error range of the fitting equation for the prediction of spray angle and SMD is within 15% and 10% respectively.The prediction is expected to be used in engineering to estimate the spray performance at the beginning of a real project. | Jinfan Liu Xin Feng Hu Liang Weipeng Zhang Yuanyuan Hui Haohan Xu Chao Yang | 2023 | Chinese Journal of Chemical Engineering2023，63，11： | 0 |
| 6 | Saline Lacustrine Source Rocks and their Generated Gas Composition显示文摘Based on salinity,organic geochemical tests and gas generation simulations of mudstones,this paper has studied the effects of salinity on organic matter richness,types and thermal maturities and generated | LIU Chenglin ZHENG Shijing LI Haohan LIU Jun ZHANG Xuan | 2014 | Acta Geologica Sinica(English Edition)2014，88，S1： | 0 |
| 7 | Measuring spatio-temporal autocorrelation in time series data of collective human mobility显示文摘Massive spatio-temporal big data about human mobility have become increasingly available.Revealing underlying dynamic patterns from these data is essential for understanding people’s behavior and urban deployment.Spatio-temporal autocorrelation analysis is an exploratory approach to recognizing data distribution in space and time.The most widely used spatial autocorrelation measurements,such as Moran’s I and local indicators of spatial association(LISA),only apply to static data,so are powerless to spatio-temporal big data about human mobility.Thus,we proposed a new method by extending Moran’s I to measure the spatial autocorrelation of time series data.Then the method was applied to taxi ride data in Beijing,China to reveal the spatial pattern of collective human mobility.The result shows that there is strong positive spatio-temporal autocorrelation within the 5th Ring Road,weak negative spatio-temporal autocorrelation nearby the Sixth Ring Road,and almost no spatiotemporal autocorrelation between the roads.Local spatial patterns of taxi travel were also recognized.This method is useful for discovering underlying patterns from spatio-temporal big data to understand human mobility. | Yong Gao Jing Cheng Haohan Meng Yu Liu | 2019 | Geo-Spatial Information Science2019，22，3： | 0 |
| 8 | Visual Analysis for Civil Aviation Passenger Reservation Data Characteristics Based on Uncertainty Measurement显示文摘Aviation data analysis can help airlines to understand passenger needs,so as to provide passengers with more sophisticated and better services.How to explore the implicit message and analyze contained features from large amounts of data has become an important issue in the civil aviation passenger data analysis process.The uncertainty analysis and visualization methods of data record and property measurement are offered in this paper,based on the visual analysis and uncertainty measure theory combined with parallel coordinates,radar chart,histogram,pixel chart and good interaction.At the same time,the data source expression clearly shows the uncertainty and hidden information as an information base for passengers’service | HuaiqingHe Hongrui Du Haohan Liu | 2015 | 国际计算机前沿大会会议论文集2015，，B12： | 0 |
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