Table of Content

10 August 2023, Volume 34 Issue 15

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Patent Data Driven Product Innovation Design Based on SAO

LIN Wenguang, LIU Xiaodong, XIAO Renbin

2023, 34(15):  1765-1777.  DOI: 10.3969/j.issn.1004-132X.2023.15.001

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The patent data-driven product innovation design method was proposed based on SAO using big data mining technology. Firstly， semantic dependency parsing was used to mine the SAO structure and interaction relationships among product components from patent text databases. Subsequently， a complex network knowledge model was constructed for product systems， and the constraint coefficients of components in the complex network were calculated by using structural hole theory to identify the innovative target components. Then， the semantic similarity coefficients of components were calculated using Word2Vec， and the functional similarity coefficients were calculated using SAO similarity algorithm. And the recommendation algorithm and combination matrix were integrated to achieve structural innovation， functional innovation， and functional optimization. Finally， a typical bathroom shower product was taken as an example to demonstrate the method in detail， which fully verifies the effectiveness and progressiveness of the method. 

Correction Model and Experimental Study of Removal Rate in Tangential Cylindrical Grinding Based on Grinding Thermal Deformation Analysis

CHI Yulun, WU Zixuan

2023, 34(15):  1778-1788.  DOI: 10.3969/j.issn.1004-132X.2023.15.002

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In order to solve the problem in plunge type cylinder grinding caused by the traditional grinding removal efficiency model of grinding thermal deformation is different from the actual grinding， the traditional grinding removal efficiency model was modified based on the analysis of grinding thermal deformation mechanism. By analyzing the grinding thermal deformation and thermal deformation rate of grinding wheel and workpiece， the correction function was determined， the material removal efficiency correction model based on the thermal deformation was established. The model was verified by grinding experiment， and the results show that the model has higher accuracy. 

Focusing Characteristics of High Voltage Electron Guns under Variable Electromagnetic and Beam Source Parameters

LI Shengbo, SONG Ye, QIU Yufan, FU Shengping, SHUTIN Denis, CHANG Jiawei, BAI Fengmin

2023, 34(15):  1789-1796.  DOI: 10.3969/j.issn.1004-132X.2023.15.003

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 The domestic ZD-VEBW series high-voltage electron gun was taken as the research object， and the mapping relationship among the potential on the electron gun axis and the beam waist and beam spot diameter， as well as the movement trajectory of the charged particles when passing through the focusing coil， was analyzed theoretically. The CST simulation platform was used to build the electron gun simulation model. The variation law of electron beam spot diameters under different electrostatic focusing structure parameters was obtained by simulation. According to the rule， bias cups and anodes with different apertures were designed， and an experimental platform for electron beam welding was constructed. The distance between cathode and anode and beam source parameters were dynamically adjusted， and the single-parameter and orthogonal experiments of electron beam welding were studied. The results show that the increase of the distance between the cathode and the anode leads to the increase of the beam spot diameter， and the increase of the bias cup aperture leads to the decrease of the beam spot diameter. When the distance between the cathode and anode is as 28.4 mm， the diameter of the bias cup is as 6.00 mm， and the diameter of the anode is as 10.00 mm， the aspect ratio of the electron beam weld under the same power of the test model equipment may be significantly improved. The performance of the tested homemade ZD-VEBW series high voltage electron guns is effectively improved， which verifies the correctness of the theoretical and simulation analysis. 

SOC Estimation of Lithium-ion Batterys Based on Second-order Approximation Extended Kalman Filter

DUAN Linchao, ZHANG Xugang, ZHANG Hua, SONG Huawei, AO Xiuyi

2023, 34(15):  1797-1804.  DOI: 10.3969/j.issn.1004-132X.2023.15.004

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To improve the accuracy of battery SOC estimation， a higher order EKF algorithm was used to estimate SOC. Firstly， the first-order Thevenin equivalent circuit model（ECM） of lithium-ion battery was established， and the function relationship between open circuit voltage（OCV） and SOC was expressed by spline function. In order to more accurately identify the ECM parameters， a new kind of with VFFRLS algorithm was proposed for on-line identification of model parameters. Since the accuracy of the VFFRLS solution depended on the setting of the initial values of the algorithm， the improved particle swarm optimization algorithm was used to obtain the initial parameters of ECM， which helped to obtain more accurate initial values of VFFRLS. Finally， the second-order EKF was employed to estimate the SOC of the batterys to improve the estimation accuracy. Two different datasets were used to demonstrate the universality of second-order EKF estimation SOC. The experimental results indicate that the mean absolute error（MAE） of second-order EKF is within 1% when estimating SOC under different working conditions， which proves the effectiveness of the proposed method. 

Early Weak Fault Detection Method of Gear Rotating Machinery by Combining SPCA and OCHD

LI Xin, CHENG Junsheng, WU Xiaowei, WANG Jian, YANG Yu,

2023, 34(15):  1805-1812.  DOI: 10.3969/j.issn.1004-132X.2023.15.005

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Aiming at the problems that early weak faults of rotating machinery were difficult to detect in time and accurately, an intelligent detection method was proposed based on SPCA and OCHD. Firstly, SPCA was used to map vibration signals to a symplectic space, and the symplectic eigenvalues which might best characterize the main energy and effective information of the signals were extracted as the fault features of rotating machinery. Then, the hyperdisk model was introduced into the one-class classification domain to propose the OCHD model. OCHD used the hyperdisk model to evaluate the class distribution of known samples, and the optimal one-class hyperplane was constructed by finding the closest points on the geometric model to the origin, so as to realize the intelligent detection of early weak faults. Finally, the effectiveness of the proposed method was verified by the bearing life cycle data from the university of Cincinnati. The experimental results show that SPCA may effectively extract the sensitive fault information of bearings, and the fault detection performance of OCHD is significantly better than that of other one-class models.

A Method for Constructing Bearing HIs with IGI Weighting

QIAN Mengui, CHEN Tao, YU Yaoxiang, GUO Liang, GAO Hongli, LI Weilin,

2023, 34(15):  1813-1819，1855.  DOI: 10.3969/j.issn.1004-132X.2023.15.006

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In the bearings condition monitoring, it was important to construct a HI that might accurately describe bearings degradation trends and identify EDP. At present, most of HIs proposed might describe the degradation trends of bearings well, but could not accurately identify the EDP. A method for constructing bearing HIs was proposed with IGI weighting. The original signals were decomposed by using EEMD, and the reconstructed signals were weighted according to the FCER of each components. The IGI of the reconstructed signals was calculated.The IGI was weighted as the FCER of the reconstructed signals to obtain the final IGI-FCER-HI. The effectiveness of the method was verified by two experiments. The results show that the IGI-FCER-HI has well monotonicity and trend, may identify EDPs of bearings accurately.

Carbon Consumption Prediction Method of Gear Hobbing Based on Data Migration in Shared Manufacturing

YI Qian, LUO Yusong, HU Chunhui, ZHUO Junkang, LI Congbo, YI Shuping

2023, 34(15):  1820-1831.  DOI: 10.3969/j.issn.1004-132X.2023.15.007

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Aiming at the problems that general manufacturing enterprises were not intelligent enough and it was difficult for a single enterprise to collect enough processing data， a prediction method of carbon consumption in gear hobbing processes was proposed based on data transfer between enterprises under shared manufacturing. The data characteristics of gear hobbing processes were analyzed， and the data migration method of improved TrAdaBoost algorithm was proposed to integrate the carbon consumption data of gear hobbing processes among enterprises under the data sharing manufacturing to form a cross-enterprise joint data set. The Dragonfly algorithm was used to optimize the support vector regression to construct a cross-enterprise carbon prediction model for gear hobbing processes. The effectiveness of the proposed method was verified by case analysis. Predictive performance has advantages when the data volume is small and the data correlation is low. Compared with the traditional algorithm， mean absolute percentage errors and coefficient of determination are improved by 59.23% and 16.56% respectively. 

Green Scheduling Optimization Method of Special Vehicle Body-in-White Prototype Shops Considering Equipment Preventive Maintenance

LI Xixing, ZHOU Wenlong, TANG Hongtao, WU Rui,

2023, 34(15):  1832-1847.  DOI: 10.3969/j.issn.1004-132X.2023.15.008

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A typical multi-objective flexible job-shop green scheduling model was established， and the makespan， total energy consumption of equipment and total smoke emission were taken into consideration. And an improved artificial bee colony algorithm was designed to solve this model. Firstly， according to the characteristics of periodic power attenuation of laser equipment， a preventive maintenance strategy that could distinguish laser equipment from ordinary mechanical equipment was proposed to reduce the makespan and the frequency of equipment failure. Then， a mutation method was designed based on equipment allocation and power selection， which could improve the local search ability of the algorithm. A selection method was introduced based on crowded distance in the follow bee search stage for population regeneration to obtain high-quality individuals. Finally， the comparison experiments were carried out based on the expanded common benchmark. Meanwhile， the effectiveness and feasibility of the model and algorithm were verified through the production case of a special vehicle body-in-white prototype workshop in an automotive equipment manufacturing enterprise. 

Research on Availability Analysis Method of CNC Machine Tools Based on Meta-action

LI Jian, MU Zongyi, DU Yanbin, HUANG Guangquan, RAN Yan

2023, 34(15):  1848-1855.  DOI: 10.3969/j.issn.1004-132X.2023.15.009

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In order to accurately analyze the availability of CNC machine tools， a analyzing method for the availability of CNC machine tools was proposed based on meta-action theory. Firstly， the “function-motion-action” structural decomposition tree was used to decompose the mechanical system， and the basic meta-action and meta-action chain were obtained. And a steady-state availability model was established based on the faults and maintenance data of the constituent components of the meta-action unit. Then， a steady-state availability analysis model for the meta-action chain was established based on Markov process. Finally， a steady-state availability model of the whole machine system was established based on the formation processes of the whole machine system function. Taking the availability analysis of CNC grinding machines as an example， and the proposed method was explained. 

Cross-domain Fault Diagnosis of Bearings Based on Discriminant Feature Extraction and Dual-domain Alignment

DONG Shaojiang, ZHOU Cunfang, CHEN Lili, XU Xiangyang

2023, 34(15):  1856-1863.  DOI: 10.3969/j.issn.1004-132X.2023.15.010

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 A deep transfer learning method was proposed to address the challenge of inconsistent feature distributions and difficulties in removing noise components in vibration data collected under different operating conditions for rolling bearings. The method utilized a combination of discriminative feature extraction and dual-domain alignment. Firstly， the labeled vibration signals and unlabeled vibration signals were segmented into fixed-length data sets using a data segmentation method. To mitigate the interference of noise signals in practical operating conditions， a channel attention mechanism known as SENet was employed. Additionally， a discriminative loss term was incorporated to assist the feature extractor in extracting features that exhibit discriminative properties. To handle the issue of inconsistent data feature distributions， the MMD was utilized to align the global domain distributions between the source and target domains. Furthermore， conditional adversarial learning techniques were employed to align the sub-domain distributions， resulting in dual-domain alignment. Experimental validation was conducted on two publicly available rolling bearing fault datasets collected under different operating conditions. The results show that the proposed method achieves an average recognition accuracy of over 98%. Comparative analyses with different diagnostic methods further demonstrate the effectiveness and superiority of the proposed method. 

Automatic Layout Method of Aircraft Tank Pipelines Based on SHO-NSGA Hybrid Algorithm

QU Ligang, SU Yan, XIN Yufei

2023, 34(15):  1864-1872.  DOI: 10.3969/j.issn.1004-132X.2023.15.011

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 An automatic aircraft tank pipeline layout method was proposed based on the improved spotted hyena algorithm to address the problem of internal aircraft tank pipeline path planning. To improve the global search ability and convergence rate of the spotted hyena algorithm， the diffusion search mechanism was introduced to spread the optimal solution in the iteration processes， and then it was introduced to randomly search in the optimal solution to improve the algorithms convergence rate. The grid method was used to build the laying space mathematical model and the pipeline layout optimization mathematical model was established with the shortest pipeline path， the pipeline bending angle and the pipeline bending radius were as constraints. Furthermore， considering the pipeline arms layout problem， with arm length and arm posture as the arm layout double target optimization function， using a genetic algorithm（NSGA-Ⅱ）to code the initial individual， design cross， variation rules， to solve the Pareto solution of the pipeline arm layout sets， and to obtain the pipeline arm layout scheme. Finally， numerical examples and pipeline laying simulation were used to validate the effectiveness of the proposed method. 

Flexible Skin-shaped Optical Fiber Reconstruction Method for Allomorphic Aircrafts

WANG Yuanfeng, ZHU Lianqing, HE Yanlin, ZHOU Kangpeng,

2023, 34(15):  1873-1880.  DOI: 10.3969/j.issn.1004-132X.2023.15.012

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 Large-scale deformation monitoring of allomorphic aircrafts in the flight processes was a research difficulty and hot spot in the aerospace field， and the existing methods were difficult to achieve high-precision three-dimensional deformation monitoring during the flight of the aircrafts. Aiming at this problem， a flexible skin-shaped fiber reconstruction method for a variant aircraft was proposed based on optical fiber sensing to achieve deformation monitoring during flight of the aircrafts. Based on the principle of fiber grating strain sensing， the relationship between fiber strain and curvature was derived， the conversion matrix between the local coordinate system and the global coordinate system of optical fiber sensing was established， the conversion of fiber measurement point coordinates to the global coordinate system was realized， and the three-dimensional deformation reconstruction algorithm was studied based on curve fitting according to the spatial curve fitting method. At the same time， in order to reduce the measurement errors of the fiber optic sensors， the calibration tests of the fiber optic sensors were carried out to obtain the strain sensitivity of the sensors. In order to verify the effectiveness of the proposed method， the three-dimensional deformation reconstruction of flexible skin samples under different curvatures was tested experimentally. Experimental results show that the average error of the shape reconstruction method is as 3.5% and the minimum error is less than 2.1% in the deformation ranges of 0～15.38 m-1 curvature of flexible skin samples. The proposed method has a good application prospect in aerospace and other fields. 

Reliability-based Analysis for Two-phase Flow of Locomotive Side Wall Filtration Systems with Non-random Load Uncertainty

QU Xiaozhang, ZHANG Jiabei, ZHAI Fangzhi

2023, 34(15):  1881-1889.  DOI: 10.3969/j.issn.1004-132X.2023.15.013

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 A two-phase flow reliability analysis method was proposed for locomotive side wall filtration systems with interval non-random load uncertainty， considering the difficulty of modeling the cognitive uncertainty of load parameters and combining the randomness of manufacturing and installation， aiming at the reliability problems of the locomotive side wall filtration systems with the changes of operating environments. Firstly， the CFD model of two-phase flow in the filter system of the locomotive side walls was established through experimental comparison. Secondly， the reliability analysis of the two-phase flow mechanics problem of the locomotive side wall filtration systems was carried out by using the probabilistic and interval mixed uncertainty model and the corresponding effective reliability analysis method. The structural parameters with sufficient samples and load parameters with insufficient samples were measured by probability and interval method respectively. The difficulty of modeling cognitive uncertainty caused by insufficient samples could be quickly solved， which extended the applicability of reliability analysis technique of interval mixed uncertainty in the study of two-phase flow mechanics problems. Through the study of load reliability problems such as resistance and filtration efficiency of two-phase flow problem of electric locomotive side wall filtration systems， reasonable improvement of the uncertainty level of key parameters may take into account the cost， and improve the reliability of the filtration systems， Which meets the requirements of high reliability applications in complex operating environments of electric locomotives， and provides reference for engineering applications.