China Mechanical Engineering

Research Progresses of Mechanical Dressing for Arc Diamond Grinding Wheels

CHEN Bing1, QING Guangye1, GUO Ye1, DENG Zhaohui2

2024, 35(08): 1331-1347. DOI: 10.3969/j.issn.1004-132X.2024.08.001

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The arc diamond grinding wheels had unique arc profile and commonly used for precision and ultra-precision grinding of optical components made from difficult-to-cut materials such as ceramics, optical glass, and cemented carbide. However, during the grinding process of optical elements, the interaction between the grinding wheel and the workpiece surface caused the abrasive grains on the grinding wheel to be squeezed and damaged. Then, this led to issues such as grinding wheel blockage, wear, reduction in size and shape accuracy, ultimately affecting the surface roughness, shape accuracy, and damage thickness of the optical elements after grinding. To address these problems, dressing the arc-shaped diamond grinding wheel was an effective solution. Among the various dressing methods, mechanical dressing remained the primary approach in production due to the high dressing efficiency and ease of implementation. This paper provided a comprehensive review of the mechanical dressing methods for arc diamond grinding wheels. The truing mechanism and characteristics of different methods were explored, the evaluation method for truing effectiveness was analyzed, and a future outlook for the mechanical truing of arc diamond grinding wheels was presented.

Design and Analyses of a Novel Two-axis Flexure Hinge with Elliptical Transverse Cross-sections

WEI Huaxian1, 2, ZHAO Yongjie2, YANG Nan2, WANG Fengtao2, NIU Xiaodong2

2024, 35(08): 1348-1357. DOI: 10.3969/j.issn.1004-132X.2024.08.002

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Two-axis flexure hinges with orthogonally-collocated notches comprised rectangular transverse cross-sections which increased the stress concentration on the sharp edges. In addition, such effects could not be avoided through notch optimization. Consequently, a novel kind of two-axis flexure hinge with elliptical transverse cross-sections was developed herein. Firstly, the parametric model of the flexure hinges with circular notches was established. Then, the compliance and stress models of the flexure hinges were developed based on the Castiglianos second theorem. The analytical models were verified through finite element analyses and the parametric simulations were performed to evaluate the characteristics of compliances and stress concentration. Finally, the compliances of a flexure specimen were tested through experiments. The results show that the ETC flexure hinges have two-dimensional anisotropic compliances. The sharp-edge structures are avoided. Therefore, the stress concentration effects are reduced and the motion capability is increased. Compared to exiting two-axis flexure hinges with identical notch profiles but rectangular transverse cross-sections, the motion capability of the ETC type flexures hinges is increased by 47.9%. The ETC type two-axis flexure hinges expand the design spaces of the primary flexure structures.

Study on Dynamic Mechanics Characteristics and Fatigue Life Prediction of Single PCPs

ZU Haiying, SUN Jinshan, YE Weidong, LI Daqi

2024, 35(08): 1358-1365. DOI: 10.3969/j.issn.1004-132X.2024.08.003

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Aiming at the rubber fatigue failures of the stator of conventional production PCPs, the fatigue test of stator rubber material under 50 ℃ oil immersion condition was carried out with GLB120-27 type single PCP as the research object, the fatigue performance parameters of rubber material were obtained, and the fatigue life prediction model was established. The dynamic mechanics characteristics of PCPs were analyzed by finite element method with ABAQUS software. Based on the stress-strain response results obtained by numerical simulation and the stress-strain fitting expression of stator rubber materials in uniaxial tensile tests, the range of strain energy release rate at fatigue danger points was calculated. The fatigue life prediction of PCPs under different interference conditions was studied by using the established fatigue life prediction model. The results show that the fatigue life decreases exponentially with the increase of interference. Compared with the average working life of a single PCP in recent 5 years, based on crack propagation method the fatigue life of the stator rubber may meet the requirements of engineering prediction accuracy.

Probabilistic Fatigue Life Prediction Model for Filled Natural Rubber under Constant Amplitude Loading

LIU Xiangnan1, 2, XU Jingwei1

2024, 35(08): 1366-1372. DOI: 10.3969/j.issn.1004-132X.2024.08.004

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A conditional probability distribution model was proposed to quantify the distribution law of rubber fatigue life under arbitrary strain levels. The uniaxial tensile fatigue tests of rubber under different strain levels were carried out. The distribution law of rubber fatigue life was analyzed, and the parameter values of the probability distribution model were determined by a great likelihood estimation method. The least squares method was used to fit the functional relationship between strain level and parameter values of the probability distribution model, and then the conditional probability distribution model was established. The rubber fatigue reliability assessment was carried out, and the rubber P-ε-N model was established. The validity of the rubber P-ε-N model was verified by comparison with the measured lifetimes.

Feature Extraction Method for Seawater Pump Excitation Sources Based on SOA-VMD-ICA

TENG Jiapeng, WU Guoqi

2024, 35(08): 1373-1380. DOI: 10.3969/j.issn.1004-132X.2024.08.005

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Aiming at the complex multi-source excitation feature extraction problems of the seawater pumps， a feature extraction method was proposed based on the combination of SOA，VMD and ICA for the excitation sources of the seawater pumps. Based on the single-channel measurement signals， the VMD algorithm and SOA optimization algorithm were used to calculate the signal square envelope spectral kurtosis statistic as the fitness function to optimize the modal decomposition number K，the penalty coefficient α，and the eigenmodal function components（IMF). The signal alignment entropy was used as the noise test function. After choosing a reasonable threshold value， the IMF components for noise were screened then the non-noise IMF component signals were obtained. Fast-ICA algorithm was used to obtain the excitation source signal vector，thus realizing the excitation source feature signal extraction. The effectiveness of the feature extraction method was verified through the experimental and comparative analysis of the excitation source feature extraction of the real ships seawater pumps. The results show that SOA-VMD-ICA algorithm meet the requirements of extracting the excitation source features of seawater pumps accurately under single-channel measurement conditions.

Analytical Solution of Permanent Deformations and Sliding Lengths during the Elasto-plastic Oblique Contact-impacts

WANG Yao1, GUAN Enguang1, ZHANG Qinglei1, 2

2024, 35(08): 1381-1389，1396. DOI: 10.3969/j.issn.1004-132X.2024.08.006

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For the design and applications of mechanical systems, the elasto-plastic contact impact phenomenon among the multi-body surfaces was one of the key mechanics problems, which contained complex physical and mechanics properties. There still were many controversies and mysteries regarding the analysis and characterization of key parameters such as contact force. For the elasto-plastic oblique contact-impact events, the calculated formulas of instantaneous contact forces and contact deformations were established based on the Brake indentation model, and the elasto-plastic contact impact process from the contact deformations was described systematically in detail. The internal relationship among impact duration, permanent deformation and sliding length was analyzed analytically based on the generalized momentum theorem, and the permanent deformations and sliding lengths expressed in the integral form were obtained respectively, and then, combined with testing data for the motions of the impact objects before and after contact impact reported in literatures, the analytical solution was obtained. The deformation region of the impacted object after the contact impact was measured, and the comparative analysis was also performed. The experimental and numerical results show that the calculated results of the permanent deformations and sliding lengths solved by using the approach developed by the generalized momentum theorem are found to be in good agreement with the experimental data. And this approach yields more accurate results compared to the direct integration of mathematical equations using the Brake indentation model.

Modeling and Reliability Analysis of Wheel Two-stage Degradation of High-speed Trains

QI Jinping1, 2, 3, LIU Xiaoyu1, FENG Hong1, LI Hongwei1, YAN Daqiang4

2024, 35(08): 1390-1396. DOI: 10.3969/j.issn.1004-132X.2024.08.007

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Aiming at the problems that high-speed train wheels showed phased characteristics in the degradation processes, a modeling and reliability analysis method of high-speed train wheel degradation was proposed based on two-stage Wiener process. On the basis of the Markov chain Monte-Carlo（MCMC） method to estimate the unknown parameters of the model, the reliability function curve and reliability life of the wheel were obtained by Monte-Carlo simulation method for the problems that the two-stage degradation processes of the wheel were complex and the reliability analysis form was difficult to solve. Finally, the effectiveness of the model was verified by taking the measured data of a locomotive and bogie wheel in a single repair cycle as an example. The results show that due to the operating environment, the change point position of the wheel degradation processes on different sides of the bogie is different. Compared with the reliability evaluation results of the degradation model without considering the phased characteristics, the proposed model is more in line with the actual field situation. According to the reliable life prediction results, affected by the operating environment, the wheel degradation processes on different sides of the bogie has different changing point positions. By continuously obtaining the wheel degradation data, the reliable life value of the wheels may be calculated and updated by using the model proposed herein, which provides theoretical guidance for the further optimization of the wheel repair cycle.

Growth Design of Stiffeners for Shell/Plate Structures Based on MADQN Interaction

ZHONG Yi, YANG Yong, JIANG Xuetao, PAN Shunyang, ZHU Qixin, WANG Lei

2024, 35(08): 1397-1404. DOI: 10.3969/j.issn.1004-132X.2024.08.008

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Based on the Markov property of the growth steps of shell/plate stiffeners, a reinforcement learning driving strategy of the growth design of shell/plate stiffeners was proposed. Aiming at minimizing the overall strain energy of the structures, Markov decision process was used to model the growth processes of the stiffeners. By introducing a multi-agent system to share the states and the rewards of the stiffeners growth processes, and memorizing specific actions, the learning complexity was reduced. Meanwhile, the convergence of the reward value of the stiffeners growth processes was realized. Therefore, the growth design strategy of shell/plate stiffeners was achieved. Finally, a numerical example was given and the results of the smoothed stiffeners layout were compared with those of the classical algorithm, which verifies the validity of the growth design of stiffeners for shell / plate structures based on MADQN interaction.

Bearing Fault Diagnosis of Mining Drilling Rig with Time-frequency-fused Deep Network

ZOU Xiaoyu1, 3, SUN Guoqing1, WANG Zhongbin1, 3, PAN Jie2, LIU Xinhua1, 3, LI Xin1, 3

2024, 35(08): 1405-1413，1448. DOI: 10.3969/j.issn.1004-132X.2024.08.009

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To solve the problems of weak and noisy bearing fault features caused by the low-speed and heavy-load operating characteristics of mining drilling rigs, a fault diagnosis method was proposed for mining rig bearings, named time-frequency-fused deep network. It considered the limitations of fault diagnosis with single modality, and then jointly characterizes two modal features of the time domain and time-frequency domain. The designed diagnostic network differentially embeded specific attention mechanism in different modules to extract multi-dimensional key fault features. Finally, the proposed method was validated on the experimental equipment and the Case Western Reserve University bearing dataset. The results show that the proposed method may automatically extract sufficient fault features combining two domains. It has higher accuracy and noise immunity than those with a single domain.

Neural Network Sliding Mode Control of Bellows-type Pneumatic Soft Actuators Based on Improved Ternary Model

LYU Boyang1, 2, 3, MENG Qingxin1, 2, 3, XIAO Huai1, 2, 3, LAI Xuzhi1, 2, 3, WANG Yawu1, 2, 3, WU Min1, 2, 3

2024, 35(08): 1414-1425. DOI: 10.3969/j.issn.1004-132X.2024.08.010

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A sliding mode control method was proposed based on an improved ternary model for a bellows-type pneumatic soft actuator, and an RBF neural network was used to compensate the aggregate set disturbance to achieve tracking control of the desired trajectory in the vertical direction of this type of actuators. Firstly, an experimental platform was constructed to test and analyse the dynamic characteristics of the bellows-type pneumatic soft actuators. Based on the above dynamic characteristics, an improved ternary model of the bellows-type pneumatic soft actuators was proposed. Meanwhile, the parameters of the proposed model were obtained by using the collected experimental data for parameter identification based on the least squares algorithm. Then, the sliding mode controller was designed in conjunction with the improved ternary model, and the RBF neural network was used to compensate for the aggregate set disturbance. The stability of the system was analysed by using the Lyapunov method. Finally, the effectiveness of the proposed method was verified through a series of experiments.

Simultaneous Measurement and Modeling of MDOF Static/Thermal Errors of CNC Machine Tool Rotational Axes

LI Guolong1, XIAO Yang1, LI Zheyu1, XU Kai2, ZHANG Wei1

2024, 35(08): 1426-1434. DOI: 10.3969/j.issn.1004-132X.2024.08.011

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Existing measurement and modeling methods for CNC machine tool rotational axis errors only considered the influences of multiple degrees of freedom(MDOF) static geometric errors or single degree of freedom thermal errors acting in isolation without accounting for the coupled effects, a simultaneous measurement and modeling for MDOF static/thermal errors in CNC machine tool rotational axes was proposed based on a double ball bar. Firstly, a model was developed to describe the variation in length of the double ball bar using homogeneous coordinate transformation. A static/thermal error identification model was constructed by solving a system of nonhomogeneous linear equations based on this model. Subsequently, to minimize the influences of thermal dissipation on the measurement results, a specific installation mode adapted to the simultaneous measurement of MDOF static/thermal errors was designed to reduce the installation time of the double ball bar. Additionally, a prediction model for MDOF static/thermal errors in rotational axis was established using a CNN-LSTM. Finally, experiments were conducted on the C-axis of a gear grinding machine to rapidly identify the rotational axis errors at various speeds. The accuracy of the prediction model was verified by utilizing the static/thermal error model to predict the errors of C-axis and the variation in length of the double ball bar.

Residual Life Prediction Method of Belt Conveyors Based on MDT Learning

GAO Xinqin, YANG Xueqi, ZHENG Haiyang

2024, 35(08): 1435-1448. DOI: 10.3969/j.issn.1004-132X.2024.08.012

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In the coal mining processes, the operating environments of the belt conveyors were harsh and the working conditions were complex. These resulted in a limited amount of sensor monitoring data and a large amount of noise interference, which seriously limited the accuracy of the residual life prediction. Aiming at this problem, a MDT learning residual life prediction method was proposed. To predict the residual life of key component roller bearings accurately, multiple working condition data of belt conveyors accumulated in coal flow transportation could be fully used. Firstly, integrating a multi-scale convolutional neural network and bidirectional gated recurrent unit(MCNN-BiGRU), a degradation feature extraction model was constructed. The particle swarm optimization(PSO) was used to determine the model hyperparameters. Then, using MDT learning and multiple working condition data, the residual life prediction was carried out. Combining loss of maximum mean discrepancy(MMD) with correlation alignment(CORAL) the data distribution difference of each source domain was narrowed. This might solve the problem of low training accuracy of the model due to the small amount of data. Finally, the actual production data sets of a coal mine were used for verification. The results show that the prediction effectiveness of the MDT-MCNN-BiGRU model is better, and the model performance is further improved after the Savitzky-Golay filter denoising. Using the IMS dataset and comparing with the existing methods, the proposed method has high prediction accuracy and is of some significance in guiding the health management of coal mine transportation equipment.

Prediction of Stiffness Degradation Degree of Spindle-tool Holder Interfaces Based on Two-signal Fusion

WU Shi, ZHANG Yong, WANG Yupeng, WANG Chunfeng

2024, 35(08): 1449-1461. DOI: 10.3969/j.issn.1004-132X.2024.08.013

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In order to predict the stiffness degradation degree of spindle/tool holder interfaces, a method was proposed based on excitation and response signal fusion. Firstly, side milling experiments of rectangular titanium alloy workpiece were carried out, instantaneous milling force signals and response vibration signals near the spindle-tool holder interfaces were collected, and a database reflecting the stiffness degradation of the spindle-tool holder interfaces was constructed. Then, according to the time-domain, frequency-domain and time-frequency domain features of the instantaneous milling forces and vibration signals in each direction in the database, three features, namely the time-domain mean value, frequency-domain center frequency and time-frequency first-order wavelet packet energy of the instantaneous milling force signals in the X direction and the vibration signals in the Z direction, were optimized based on correlation analysis. The low frequency filter convolution kernel and the high frequency filter convolution check after the preferred eigenmatrix were used for the dual channel convolution pooling processing respectively. The eigenvector of stiffness degradation degree of the deeply fused spindle-tool holder interfaces was obtained. Finally, the probabilistic mode of support vector machine(SVM) model was transformed into the conditional probability of naive Bayes model（NBC）, and the mixed classifier model NBC-SVM was constructed to improve the classification performance of the classifier. On the basis of the stiffness degradation database of the spindle-tool holder interfaces, the two-channel convolution pooled feature fusion method (CP-FF) and NBC-SVM model were used to predict the stiffness degradation degree of the spindle-tool holder interfaces, and the prediction accuracy is as 96%.

Improved Jaya Algorithm for Solving HFSPs

ZHOU Hao1, ZHANG Chaoyong1, 2, LIU Hui1, 3, LUO Min2

2024, 35(08): 1462-1471,1508. DOI: 10.3969/j.issn.1004-132X.2024.08.014

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HFSP was an NP-hard problem widely presented in process manufacturing systems. For HFSP aimed at minimizing makespan, an improved Jaya algorithm was proposed by combining the advantages of Jaya algorithm and Tabu search. During the iterative update phase of the algorithm, a path reconnection-based method was proposed for the discrete update of the algorithm according to the designed coding, which ensured the diversity of the population and enhanced the global search capability. To improve local search capability, a Tabu search algorithm integrating two types of neighborhood structures was proposed to further enhance the quality of solutions, and the neighborhood structures were adjusted adaptively according to the characteristics of the problem. The proposed algorithm was used to solve three types of HFSP benchmark sets. New optimal solutions are found in large-scale classic benchmark sets, which are superior to other algorithms in the current literatures in terms of solution quality, verifying the effectiveness and superiority of the proposed algorithm.

Research on Influences of Surface Roughness and Hardening Rate on Fatigue Property in DD5 Creep Feed Grinding

JIN Qichao1, 2, BAO Huzi1, LI Liangwan3, WANG Wenhu3, ZHANG Jinqi1, YE Ziyin1, GUO Lei1

2024, 35(08): 1472-1479. DOI: 10.3969/j.issn.1004-132X.2024.08.015

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In order to study the influence laws and mechanism of surface roughness and hardening rate on fatigue property of DD5 nickel-based single crystal superalloy during creep feed grinding, the experiments were designed and tested. The results show that the increase of surface roughness leads to the aggravation of stress concentration and decrease of fatigue property. Under different grinding processes, when the value of surface roughness increases from 0.347 μm to 0.687 μm, the fatigue life decreases from 5.51×105 to 3.38×105, and the reduction rate is about 38.66%. When the value of surface roughness is less than 0.4 μm, the surface hardening may improve the fatigue life of the specimen. When the value of surface roughness is more than 0.4 μm, the surface hardening has no significant effect on the fatigue property. The morphological tests show that with the increase of surface roughness, the number and depth of gullies generated by ploughing on the grinding surface increase, the number of crack sources on the grinding surface increases and the stress concentration intensifies under fatigue load, which leads to the decrease of fatigue life. Lower surface roughness and larger surface hardening rate may improve the creep feed grinding fatigue property of DD5.

Performance Comparison of High-speed Laser Cladding Martensitic Stainless-steel Coatings and Electroplating Coatings

WANG Jing1, 2, AI Chao1, YUAN Xiao2, ZHU Xun2, GUO Fei2

2024, 35(08): 1480-1488. DOI: 10.3969/j.issn.1004-132X.2024.08.016

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In order to compare the feasibility of high-speed laser cladding coatings replacing electroplated hard chrome coatings under different service conditions of hydraulic cylinders, martensite stainless steel cladding layers XG-1, XG-2 and electroplated hard chrome coatings were prepared respectively. The microstructure, hardness, corrosion performance and wear performance under simulated different conditions(scratch wear, dry sand grinding wear, sliding friction wear) of the three coatings were tested, and the coating failure behavior and application conditions were discussed. The results show that the microstructures of XG-1 and XG-2 coatings are dense and uniform, with an average microhardness of 720.5 HV and 653 HV, respectively. The electroplated hard chrome coatings contain defects such as pores and cracks, and the self-corrosion current density is about 10.45 μA/cm2, indicating the worst corrosion resistance. Under the three wear modes, the electroplated hard chrome coatings have cracked and peeled off, while the high-speed laser cladding coatings exhibit better wear resistance, which are suitable for the service conditions of hydraulic cylinders such as piston rod easily to be scratched, surrounding environment being rich in hard particle pollutants, and large lateral loads.

Mode Transition Control of Parallel Gas-electric Hybrid Ships Based on Clutch Slipping Torque Estimation

PENG Cheng, CHEN Li, FU Shenglai

2024, 35(08): 1489-1497. DOI: 10.3969/j.issn.1004-132X.2024.08.017

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During the mode transition from motor-only propelling mode to compound propelling mode of parallel gas-electric hybrid ships, the torque coupling was conducted via the slipping clutch. However, the clutch slipping torque was uncertain, making the nominal values deviated from the actual ones. The mode transition control was degraded based on the nominal values, leading to the jerk of the propulsion shafting. To address this problem, a mode transition control strategy was proposed based on the clutch slipping torque estimation. The clutch slipping torque was estimated by combining the disturbance observer and unknown input observer. The control law of the traction motor and natural gas engine was developed based on the estimated value, respectively. Simulation and experimental results validate the accuracy of the estimator and the effectiveness of the proposed mode transition control strategy.

Research on Obstacle Avoidance Control of Booms of Aerial Work Platforms Based on Adaptive Closed-loop Feedback

2024, 35(08): 1498-1508. DOI: 10.3969/j.issn.1004-132X.2024.08.018

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In order to solve the problems of discontinuity of velocity and trajectory in the applications of the improved gradient projection method in hybrid aerial work platforms and the problems of abrupt change in velocity of ends during obstacle avoidance, an obstacle avoidance motion control algorithm was proposed based on adaptive closed-loop feedback. The improved gradient projection method was optimized to realize the continuous motion control of the speed and trajectory of the booms and the ends of aerial work platforms with telescopic arms. The pseudo distance was used to describe the proximity between the boom and the obstacle, and the traditional obstacle avoidance speed algorithm was optimized. An adaptive closed-loop feedback method was proposed, which correlated the feedback weight with the pseudo-distance, and made the feedback weight change adaptively. The algorithm guaranteed the precision of the end trajectory, and greatly improved the sudden changes in the boom joint velocity in the course of obstacle avoidance. Simulation and semi-physical experimental results verify that the speed amplitude of the proposed method is greatly reduced and the trajectory is smoother than that of the traditional method, and multi-obstacle avoidance and multiple obstacle avoidance may be realized.

Misalignment Monitoring System Based on Position Sensitive Detector

GUO Fengze, YANG Bo, RONG Zhixiang, YANG Junman, FENG Yishuo

2024, 35(08): 1509-1519. DOI: 10.3969/j.issn.1004-132X.2024.08.019

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In order to grasp the alignment status of diesel power plants in real time, a monitoring system was designed based on position sensitive detectors. Firstly, a measurement method for position and posture was proposed based on position sensitive detectors, and a nonlinear equation group incorporating position and posture was formed. By means of position and posture transformation, the alignment deviation and opening angle changes were obtained. Secondly, high-precision measurement of the constants in the equation group was achieved through the sensor bracket components. Through hardware and software design, a measurement system was formed. A composite iterative algorithm was designed to ensure fast and accurate solution of the equations based on simple Newtons method. Finally, the accuracy of the measurement system was analyzed and validated using a four-dimensional platform. The experimental results show that the monitoring system has low noise, with a deviation noise of less than 0.005 mm and an angle noise of less than 0.01°. The accuracy is greatly affected by the incident direction of the laser, with a maximum deviation measurement errors isless than 0.02 mm and a maximum opening angle measurement errors is less than of 0.019° under the best incident direction. This system will be used for monitoring the alignment status of domestic diesel power plants.

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