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学者姓名：程强
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Abstract ：
Utilizing fake data (simulated based on mechanism models or generated through data-driven models) for data enhancement is a popular approach to solve the problem of fault diagnosis with small samples. Consequently, the quality of such fake data impacts fault diagnosis accuracy. This article proposes a data model fusion (DMF)-driven framework for small sample fault diagnosis. This framework integrates the digital twin model (DTM) and the conditional deep convolutional generative adversarial network (C-DCGAN). Digital twin data (DTD) under various fault conditions is first obtained in the data generation stage based on DTM simulation. Then, a data generation method based on DTM-C-DCGAN is proposed. The method adopts DTD as the soft-physics constraint input to the generator of C-DCGAN. Hence, the generator is induced to generate data that is more consistent with the failure mechanism and closer to the real data. During the fault diagnosis stage, the generated data (GD) are used to enhance the training process of the fault diagnosis model, improving its generalization ability. Finally, the effectiveness of the proposed method is comprehensively verified via two publicly rolling bearing datasets. Compared with the existing single data-driven and physics-based methods, the experimental results demonstrate that the proposed DMF method can significantly enhance the quality of the GD and improve the accuracy of fault identification, achieving an average accuracy of 97.31%.
Keyword ：
Accuracy Accuracy digital twin model (DTM) digital twin model (DTM) generated data (GD) generated data (GD) Generators Generators small sample fault diagnosis small sample fault diagnosis Data collection Data collection Data models Data models Conditional deep convolutional generative adversarial network (C-DCGAN) Conditional deep convolutional generative adversarial network (C-DCGAN) data model fusion (DMF) data model fusion (DMF) Rolling bearings Rolling bearings Digital twins Digital twins Generative adversarial networks Generative adversarial networks Fault diagnosis Fault diagnosis Feature extraction Feature extraction Training Training
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| GB/T 7714 | Zhu, Yonghuai , Cheng, Jiangfeng , Liu, Zhifeng et al. Data Generation Approach Based on Data Model Fusion: An Application for Rolling Bearings Fault Diagnosis With Small Samples [J]. | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT , 2025 , 74 . |
| MLA | Zhu, Yonghuai et al. "Data Generation Approach Based on Data Model Fusion: An Application for Rolling Bearings Fault Diagnosis With Small Samples" . | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 74 (2025) . |
| APA | Zhu, Yonghuai , Cheng, Jiangfeng , Liu, Zhifeng , Zou, Xiaofu , Cheng, Qiang , Xu, Hui et al. Data Generation Approach Based on Data Model Fusion: An Application for Rolling Bearings Fault Diagnosis With Small Samples . | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT , 2025 , 74 . |
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Abstract ：
Various remaining useful life (RUL) prediction methods, encompassing model-based, data-driven, and hybrid methods, have been developed and successfully applied to prognostics and health management for diverse rolling bearing. Hybrid methods that integrate the merits of model-based and data-driven methods have garnered significant attention. However, the effective integration of the two methods to address the randomness in rolling bearing full life cycle processes remains a significant challenge. To overcome the challenge, this paper proposes a data and model synergy-driven RUL prediction framework that includes two data and model synergy strategies. First, a convolutional stacked bidirectional long short-term memory network with temporal attention mechanism is established to construct Health Index (HI). The RUL prediction is achieved based on HI and polynomial model. Second, a three-phase degradation model based on the Wiener process is developed by considering the evolutionary pattern of different degradation phases. Then, two synergy strategies are designed. Strategy 1: HI is adopted as the observation value for online updating of physics degradation model parameters under Bayesian framework, and the RUL prediction results are obtained from the physics degradation model. Strategy 2: The RUL prediction results from the data-driven and physics-based model are weighted linearly combined to improve the overall prediction accuracy. The effectiveness of the proposed model is verified using two bearing full life cycle datasets. The results indicate that the proposed approach can accommodate both short-term and long-term RUL predictions, outperforming state-of-the-art single models.
Keyword ：
health indicator health indicator remaining useful life prediction remaining useful life prediction Wiener process Wiener process and diagnostics and diagnostics sensing sensing monitoring monitoring plant engineering and maintenance plant engineering and maintenance data and model synergy data and model synergy
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| GB/T 7714 | Zhu, Yonghuai , Zhou, Xiaoya , Cheng, Jiangfeng et al. Data and Model Synergy-Driven Rolling Bearings Remaining Useful Life Prediction Approach Based on Deep Neural Network and Wiener Process [J]. | JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME , 2025 , 147 (4) . |
| MLA | Zhu, Yonghuai et al. "Data and Model Synergy-Driven Rolling Bearings Remaining Useful Life Prediction Approach Based on Deep Neural Network and Wiener Process" . | JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME 147 . 4 (2025) . |
| APA | Zhu, Yonghuai , Zhou, Xiaoya , Cheng, Jiangfeng , Liu, Zhifeng , Zou, Xiaofu , Cheng, Qiang et al. Data and Model Synergy-Driven Rolling Bearings Remaining Useful Life Prediction Approach Based on Deep Neural Network and Wiener Process . | JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME , 2025 , 147 (4) . |
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Abstract ：
Tolerance allocation optimization (TAO) is a crucial step in the manufacturing process of the portal milling machine (PMM). Traditional design approaches often consider only the machining errors arising from geometric errors. However, the thermal characteristics of the bi-rotary milling head (BRMH), which significantly machine tool accuracy, are frequently overlooked. Hence, a novel TAO model of PMM is proposed, considering the thermal characteristics of BRMH across multiple operating conditions. Firstly, based on the multi-body system (MBS) theory and homogeneous transform matrix (HTM), a mapping function relating geometric errors to tolerance and volume errors is developed. Secondly, the heat generation and dissipation mechanisms of the BRMH are analyzed, and precise boundary conditions for thermal simulations are determined. Notably, the spin friction torque of the rolling body on the bearing, which contributes to heat generation, must be considered. Finally, the established accuracy design optimization model, which balances total cost and machining accuracy, is solved using the NSGA-II algorithm. The Pareto optimal solution set reveals an 11.74% reduction in total cost and improved machining accuracy for the PMM. Besides, the proposed framework for accuracy design optimization with thermal characteristics is applicable to the manufacturing processes of other machine tools.
Keyword ：
thermal characteristics analysis thermal characteristics analysis bi-rotary milling head bi-rotary milling head Portal milling machine Portal milling machine NSGA-II algorithm NSGA-II algorithm tolerance allocation optimization tolerance allocation optimization
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| GB/T 7714 | Niu, Peng , Cheng, Qiang , Liu, Zhifeng et al. Multi-objective optimal tolerance allocation design of machine tool based on NSGA-II algorithm and thermal characteristic analysis [J]. | PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE , 2025 . |
| MLA | Niu, Peng et al. "Multi-objective optimal tolerance allocation design of machine tool based on NSGA-II algorithm and thermal characteristic analysis" . | PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE (2025) . |
| APA | Niu, Peng , Cheng, Qiang , Liu, Zhifeng , Chen, Chuanhai , Zhao, Yongsheng , Li, Ying et al. Multi-objective optimal tolerance allocation design of machine tool based on NSGA-II algorithm and thermal characteristic analysis . | PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE , 2025 . |
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Abstract ：
Ionic liquids (ILs) are molten organic salts consisting of organic cations and weakly coordinating organic/inorganic anions at room temperature. ILs have excellent physical and chemical properties such as high thermal stability, high combustible temperature, high miscibility with organic compounds and so on, making them good candidates for high performance lubricants and lubricant additives. The functional designability of ILs makes them novel lubrication materials that can break through the bottleneck of the active control of friction and lubrication. This paper firstly briefly introduces how to design the physical and chemical properties of the ILs required for different friction conditions by bonding specific cations with anions. Then, the lubrication mechanisms of ILs as base lubricants and additives for oils and water are focused on. The correlation between the structure of ILs and the lubrication results are established, which can guide the structural design of ILs in different applications. The response behaviors of friction characteristics under external electric fields are analyzed, which can provide a theoretical basis for the intelligent control of friction based on ILs.
Keyword ：
ionic liquids ionic liquids additive additive external electric field external electric field lubricant lubricant lubrication mechanism lubrication mechanism
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| GB/T 7714 | Liu, Mengmeng , Ni, Jing , Zhang, Caixia et al. The Application of Ionic Liquids in the Lubrication Field: Their Design, Mechanisms, and Behaviors [J]. | LUBRICANTS , 2024 , 12 (1) . |
| MLA | Liu, Mengmeng et al. "The Application of Ionic Liquids in the Lubrication Field: Their Design, Mechanisms, and Behaviors" . | LUBRICANTS 12 . 1 (2024) . |
| APA | Liu, Mengmeng , Ni, Jing , Zhang, Caixia , Wang, Ruishen , Cheng, Qiang , Liang, Weihao et al. The Application of Ionic Liquids in the Lubrication Field: Their Design, Mechanisms, and Behaviors . | LUBRICANTS , 2024 , 12 (1) . |
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Abstract ：
As increasingly extensive applications of flexible manufacturing systems (FMSs) arise, their reliability allocation has been a research hot spot. But, since FMSs are always composed of transfer and buffer devices, production machines, and complex control systems, the large number of basic elements makes the number of variables and constraints of reliability-allocation optimization increase greatly, which leads to the difficulty and inefficiency of optimization. To solve the above problem, two dimension-reduction strategies are proposed for the FMS reliability optimization with low cost and a high level of reliability as the objectives, and they are the reliability-weight double-threshold qualification strategy (RWTS) and the bi-level optimization strategy (BLOS), respectively. Based on these two strategies, an overall reliability-allocation optimization model and a bi-level reliability-allocation optimization model are established based on the FMS reliability evaluation presented in our previous work, and their algorithms based on particle swarm optimization (PSO) are presented. In terms of their contributions, for the RWTS, thresholds of reliability and the weight index of each basic element are set to dynamically reduce the number of variables in each iteration of the optimization; for the BLOS, the overall reliability-allocation optimization problem for transitioning from the FMS to basic elements can be transformed into simpler allocation optimizations from the FMS to subsystems and from subsystems to basic elements, which have fewer variables, and this can largely improve the optimization convergence performance. Through applying this to a box-parts finishing FMS, compared with the traditional optimization method, the high efficiency and the good allocation effect of the optimization based on these two strategies for improving convergence speed are verified by the simulation results. The proposed method has great significance for FMS design due to its limited cost but high-reliability requirement.
Keyword ：
reliability evaluation reliability evaluation reliability allocation reliability allocation reliability index system reliability index system dimension-reduction strategy dimension-reduction strategy flexible manufacturing system (FMS) flexible manufacturing system (FMS)
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| GB/T 7714 | Xu, Jingjing , Tao, Long , Pei, Yanhu et al. An Optimization Method of Flexible Manufacturing System Reliability Allocation Based on Two Dimension-Reduction Strategies [J]. | MACHINES , 2024 , 12 (1) . |
| MLA | Xu, Jingjing et al. "An Optimization Method of Flexible Manufacturing System Reliability Allocation Based on Two Dimension-Reduction Strategies" . | MACHINES 12 . 1 (2024) . |
| APA | Xu, Jingjing , Tao, Long , Pei, Yanhu , Liu, Zhifeng , Yan, Qiaobin , Cheng, Qiang . An Optimization Method of Flexible Manufacturing System Reliability Allocation Based on Two Dimension-Reduction Strategies . | MACHINES , 2024 , 12 (1) . |
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Abstract ：
As a kind of space robot, the two-arm cascade combination system (TACCS) has been applied to perform auxiliary operations at different locations outside space cabins. The motion coupling relation of two arms and complex surrounding obstacles make the collision-free trajectory planning optimization of TACCS more difficult, which has become an urgent problem to be solved. For the above problem, this paper proposed collision-free and time-energy-minimum trajectory planning optimization algorithms, considering the motion coupling of two arms. In this method, the screw-based inverse kinematics (IK) model of TACCS is established to provide the basis for the motion planning in joint space by decoupling the whole IK problem into two IK sub-problems of two arms; the minimum distance calculation model is established based on the hybrid geometric enveloping way and basic distance functions, which can provide the efficient and accurate data basis for the obstacle-avoidance constraint condition of the trajectory optimization. Moreover, the single and bi-layer optimization algorithms are presented by taking motion time and energy consumption as objectives and considering obstacle-avoidance and kinematics constraints. Finally, through example cases, the results indicate that the bi-layer optimization has higher convergence efficiency under the premise of ensuring the optimization effect by separating variables and constraint terms. This work can provide theoretical and methodological support for the efficient and intelligent applications of TACCS in the space arena.
Keyword ：
obstacle avoidance obstacle avoidance bi-layer optimization bi-layer optimization space robot space robot two-arm cascade combination system two-arm cascade combination system trajectory planning trajectory planning
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| GB/T 7714 | Xu, Jingjing , Tao, Long , Pei, Yanhu et al. Collision-Free Trajectory Planning Optimization Algorithms for Two-Arm Cascade Combination System [J]. | MATHEMATICS , 2024 , 12 (14) . |
| MLA | Xu, Jingjing et al. "Collision-Free Trajectory Planning Optimization Algorithms for Two-Arm Cascade Combination System" . | MATHEMATICS 12 . 14 (2024) . |
| APA | Xu, Jingjing , Tao, Long , Pei, Yanhu , Cheng, Qiang , Chu, Hongyan , Zhang, Tao . Collision-Free Trajectory Planning Optimization Algorithms for Two-Arm Cascade Combination System . | MATHEMATICS , 2024 , 12 (14) . |
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Abstract ：
Small-modulus gears, which are essential for motion transmission in precision instruments, present a measurement challenge due to their minuscule gear gaps. A high-precision measurement method under the influence of positioning errors is proposed, enabling precise evaluation of the machining quality of small-modulus gears. Firstly, a compound measurement platform for small-modulus gears is developed. Using a 3D model of the measurement system, the mathematical relationships governing motion transmission between various components are analyzed. Secondly, the formation mechanism of gear positioning error is revealed and its important influence on measurement accuracy is discussed. An optimization method for spatial coordinate transformation matrices under positioning errors of gears is proposed. Thirdly, the study focuses on small-sized gears with a modulus of 0.1 mm and a six-level accuracy. Based on the aforementioned measurement system, the tooth profile measurement points are collected in the actual workpiece coordinate system. Then, gear error parameters are extracted based on the established models for tooth profile deviation and pitch deviation. Finally, the accuracy and effectiveness of the proposed measurement method are verified by comparing the measurement results of the P26 gear measuring center.
Keyword ：
small-modulus gears small-modulus gears workpiece coordinate system workpiece coordinate system gear measurement gear measurement 3D point cloud data 3D point cloud data error model error model
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| GB/T 7714 | Niu, Peng , Cheng, Qiang , Zhang, Xinlei et al. Research on High-Precision Measurement Method for Small-Size Gears with Small-Modulus [J]. | SENSORS , 2024 , 24 (16) . |
| MLA | Niu, Peng et al. "Research on High-Precision Measurement Method for Small-Size Gears with Small-Modulus" . | SENSORS 24 . 16 (2024) . |
| APA | Niu, Peng , Cheng, Qiang , Zhang, Xinlei , Liu, Zhifeng , Zhao, Yongsheng , Yang, Congbin . Research on High-Precision Measurement Method for Small-Size Gears with Small-Modulus . | SENSORS , 2024 , 24 (16) . |
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Abstract ：
The computer numerically controlled (CNC) system is the key functional component of CNC machine tool control systems, and the servo drive system is an important part of CNC systems. The complex working environment will lead to frequent failure of servo drive systems. Taking effective health management measures is the key to ensure the normal operation of CNC machine tools. In this paper, the comprehensive effect of fault prediction and fault diagnosis is considered for the first time, and a health management system for machine tool servo drive systems is proposed and applied to operation and maintenance management. According to the data collected by the system and related indicators, the technology can predict the state trend of equipment operation, identify the hidden fault characteristics in the data, and further diagnose the fault types. A health management system mainly includes fault prediction and fault diagnosis. The core of fault prediction is the gated recurrent unit (GRU). The attention mechanism is introduced into a GRU neural network, which can solve the long-term dependence problem and improve the model performance. At the same time, the Nadam optimizer is used to update the model parameters, which improves the convergence speed and generalization ability of the model and makes it suitable for solving the prediction problem of large-scale data. The core of fault diagnosis is the self-organizing mapping (SOM) neural network, which performs cluster analysis on data with different characteristics, to realize fault diagnosis. In addition, feature standardization and principal component analysis (PCA) are introduced to balance the influence of different feature scales, enhance the feature of fault data, and achieve data dimensionality reduction. Compared with the other two algorithms and their improved versions, the superiority of the health management system with high-dimensional data and the enhancement effect of fault identification are verified. The relative relationship between fault prediction and diagnosis is further revealed, and the adjustment idea of the production plan is provided for decision makers. The rationality and effectiveness of the system in practical application are verified by a series of tests of fault data sets.
Keyword ：
machine tool servo drive system machine tool servo drive system fault diagnosis fault diagnosis failure prediction failure prediction GRU GRU health management health management PHM PHM SOM SOM
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| GB/T 7714 | Cheng, Qiang , Cao, Yong , Liu, Zhifeng et al. A Health Management Technology Based on PHM for Diagnosis, Prediction of Machine Tool Servo System Failures [J]. | APPLIED SCIENCES-BASEL , 2024 , 14 (6) . |
| MLA | Cheng, Qiang et al. "A Health Management Technology Based on PHM for Diagnosis, Prediction of Machine Tool Servo System Failures" . | APPLIED SCIENCES-BASEL 14 . 6 (2024) . |
| APA | Cheng, Qiang , Cao, Yong , Liu, Zhifeng , Cui, Lingli , Zhang, Tao , Xu, Lei . A Health Management Technology Based on PHM for Diagnosis, Prediction of Machine Tool Servo System Failures . | APPLIED SCIENCES-BASEL , 2024 , 14 (6) . |
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Abstract ：
Forging is an important sector in China's machinery manufacturing industry. To complete the processing of forgings, it is often necessary to go through multiple processes, which are commonly performed by different workshops. Due to the complexity of cross-workshop production, there are few studies on cross-workshop scheduling in the forging industry. Therefore, in order to realize resource sharing and collaborative production between multiple workshops, and improve the overall production efficiency and resource utilization rate, it is very important to optimize the scheduling of linked cross-workshop production. In this paper, a new crossworkshop partial flexible hammer forging scheduling model (CSPFH-FSM) is established to solve the scheduling problem of linked cross-workshop production with production time and energy consumption serving as the overall optimization goals in the whole partially flexible free forging production line (P3FPL). A single-machine forward-prediction variable genetic operator NGSA-II algorithm (SPVGO-NGSA II) is proposed to solve the multiobjective optimization problem of partially flexible production, in which the variable genetic operator is added to the effective coding, and the search strategy is dynamically adjusted to avoid reaching locally optimal solutions. Due to the interference of maintenance and the insufficient utilization of energy after forging, a fixed maintenance disturbance and a residual temperature utilization strategy are added to the scheduling process. Finally, the optimization obtained using the proposed variable and traditional fixed genetic operators are compared for different orders, and the algorithm proposed in this paper is compared with the typical multiobjective optimization algorithms. The results validate the effectiveness of the proposed algorithm, and provide a basic scheme for the linked scheduling of the whole production line in practical applications.
Keyword ：
Multi-objective optimization Multi-objective optimization Energy-efficient scheduling Energy-efficient scheduling Linkage production Linkage production Partial flexibility Partial flexibility Temperature and disturbance constraints Temperature and disturbance constraints
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| GB/T 7714 | Cheng, Qiang , Kan, Hongmei , Ren, Jiaxiang et al. Multi-objective optimization method for cross-workshop linkage production of partially flexible free-forging with forward single-machine scheduling [J]. | COMPUTERS & INDUSTRIAL ENGINEERING , 2024 , 196 . |
| MLA | Cheng, Qiang et al. "Multi-objective optimization method for cross-workshop linkage production of partially flexible free-forging with forward single-machine scheduling" . | COMPUTERS & INDUSTRIAL ENGINEERING 196 (2024) . |
| APA | Cheng, Qiang , Kan, Hongmei , Ren, Jiaxiang , Liu, Zhifeng , Zhang, Yueze , Cheng, Chenyang . Multi-objective optimization method for cross-workshop linkage production of partially flexible free-forging with forward single-machine scheduling . | COMPUTERS & INDUSTRIAL ENGINEERING , 2024 , 196 . |
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Abstract ：
Background and Objectives: The existing medical clinical treatment institutions mostly use rigid structures to come into contact with flexible skin. The rigid flexible coupled contact biomechanical model for the skin is the first step that urgently needs to be considered in the process of medical clinical operations. However, there has been currently no effective biomechanical contact model available. Methods: Based on the principle of elastic interface deformation, the basic biomechanical characteristics of oral and maxillofacial skin and soft tissues were analyzed to address the unknown mechanism of rigid body and maxillofacial contact in oral imaging operations. A nonlinear characterization method for the mechanical properties of oral and maxillofacial skin soft tissues was proposed by deriving a general contact force model that takes into account energy dissipation. However, the problem of the inability to obtain analytical solutions for the parameters of the dynamic model exists. It is necessary to perform particle swarm parameter identification on different nonlinear contact models and verify the accuracy of the algorithm through numerical simulation. A maxillofacial contact experiment was conducted to verify the operation process of an oral imaging robot. Results: After experimental analysis, it was found that the comprehensive average error between the model and the actual contact force was 0.13325 N. The absolute error of the maximum deformation displacement was below 0.18 N, which verified the effectiveness and safety of the contact model in the contact process of the oral imaging robot system. Conclusions: The results indicate that the output force of the model has been in good agreement with the actual contact force.
Keyword ：
Oral imaging robot Oral imaging robot identification identification Particle swarm optimization parameter Particle swarm optimization parameter Biomechanics Biomechanics Oral and maxillofacial skin Oral and maxillofacial skin
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| GB/T 7714 | Hao, Xiaolong , Cheng, Qiang , Xu, Jingjing et al. Rigid flexible coupling contact mechanism for oral and maxillofacial skin and soft tissues [J]. | JOURNAL OF THE MECHANICAL BEHAVIOR OF BIOMEDICAL MATERIALS , 2023 , 150 . |
| MLA | Hao, Xiaolong et al. "Rigid flexible coupling contact mechanism for oral and maxillofacial skin and soft tissues" . | JOURNAL OF THE MECHANICAL BEHAVIOR OF BIOMEDICAL MATERIALS 150 (2023) . |
| APA | Hao, Xiaolong , Cheng, Qiang , Xu, Jingjing , Sun, Ting , Wang, Yi , Liu, Zhifeng . Rigid flexible coupling contact mechanism for oral and maxillofacial skin and soft tissues . | JOURNAL OF THE MECHANICAL BEHAVIOR OF BIOMEDICAL MATERIALS , 2023 , 150 . |
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