Health status assessment is an indispensable part of the high-quality development of mechanical products. Starting from the motion level, it proposes a health state assessment method based on approximate ideal solution and fuzzy comprehensive evaluation method based on the meta-action unit in mechanical products as the research object. Firstly, the M-FMMECA method was used to determine the key degradation indicators of meta-action performance, and then the quantitative index of meta-action unit health index was given. Next, the approximate ideal solution was applied to the evaluation of meta-action health state, and a quantitative model of meta-action unit health state was established. Then, after completing the classification of health status, the fuzzy comprehensive evaluation method was used to determine the health status membership function of the meta-action unit, and the health status assessment was completed. Finally, taking the bevel gear rotation element action unit of a reliability test bench as an example, a case analysis of the health state assessment method was carried out. The results show that combining the approximation ideal solution with fuzzy comprehensive evaluation can quantitatively and comprehensively evaluate the health status of the meta-action unit.

In order to lapping the structured fish scale surface with traveling wave structure on the surface of the cylindrical workpiece,firstly,based on the characteristic analysis of the surface morphology of fish scales in nature,the mathematical model of the structured fish scale surface of cylindrical workpieces arranged along axial direction was established. Secondly,according to the principle of lapping and topological theory,a structured topological whetstone for lapping fish scales on cylindrical surfaces was designed. Then,according to the abrasive grain movement trajectory for the cylindrical lapping,the boundary conditions for realizing the lapping processing of structured fish scale surface on the cylindrical workpiece were discussed. And the cylindrical lapping process was simulated to obtain the structured fish scale surfaces with traveling wave structure. The results show that cylindrical lapping for the structured fish scale surface can be realized by using the designed structured topological whetstone; by changing the amplitude and frequency of lapping,the shape parameters of the structured fish scale surface also change,but its surface topological properties do not change.

Automatic fibex laying quality inspection is both time consuming and inadequate,with low defect contrast.In this regard,according to the thermal characteristics of the fibex tow laying process,a platform for fibex tow placement accuracy detection is constructed,and the morphological algorithm is combined with infrared image features of defects for fibex tow placement accuracy detection.Firstly,the top-hat transform of structural elements with the same shape and different scales is carried out,and then the multi-scale bright and dark regions under each group of scales and multi-scale bright and dark details between adjacent groups of scales are extracted to enhance the image;secondly,the multi-directional and multi-scale structural elements and the morphological edge detection algorithm with coefficients self-adjustment are used to obtain the location of filament bundle edges.The experimental results show that the method balances the coordination problem between edge detection accuracy and antinoise performance on top of image noise reduction and image contrast enhancement,and effectively detects the fibex tow placement accuracy with a maximum placement error of no more than 4.53 %.

Aiming at the influence of transportation time on green production scheduling of mixed flow workshop,the maximum completion time,production energy consumption and production cost were taken as optimization objectives. An Improved Multi-Objective Sparrow Search Algorithm (IMOSSA) was proposed to solve the problem. The fitness values of the population were divided by reference to non-dominated ordering,the quality of the solution set was improved by introducing sine-cosine strategy,and the convergence speed and global search ability of the solution set were improved by adding polynomial mutation operators and Levy flight,so as to avoid falling into local optimality. Then 16 test examples were designed to compare IMOSSA with other multi-objective optimization algorithms to verify the superiority of IMOSSA solution. Finally,taking an actual production workshop as an example,the production scheduling was divided into four modes to prove the practicability of the algorithm.

At present, the intelligent production line of household appliances has many problems, such as multi-task operation conflict, long response time of scheduling control and low utilization rate of manufacturing resources. In order to realize the rational resource scheduling of household appliance intelligent production line, based on multi-objective optimization and distributed resource scheduling theory, a distributed resource scheduling model of household appliance intelligent production line was established, and a distributed resource scheduling algorithm based on genetic algorithm was proposed. The simulation results show that compared with the traditional production line scheduling method, the maximum completion time of the proposed distributed resource scheduling algorithm is reduced by 5.76 %, and the fitness of the solution is increased by 8 %, which verifies the feasibility and efficiency of the algorithm.

Pneumatic soft robots are suitable for performing tasks in unstructured and complex environments due to good flexibility and safety.As it is difficult to mount sensors on the soft robot to directly measure shape and posture,making it difficult to achieve accurate position control, its motion accuracy is generally much lower than that of conventional rigid robots. A vision-based method of shape reconstruction,posture measurement and inverse kinematic control of soft robot was proposed to address these issues.The experimental results show that the root-mean-square error of the end-effector position of the soft robot using the method is less than 6 mm,the position error of the key point measured by this method is less than 2.80 mm,the position deviation of the overall shape is 1.67 mm,the average errors of the bending angle and the deflection angle are 3.6° and 3.4° respectively,the maximum position error and angle error of the control reaching the desire are 3.47mm and 0.24° respectively.The experimental results show that the proposed posture measurement and control method is useful for improving the motion accuracy and working ability of the soft robot.

A digital twin-based modeling approach was innovatively introduced in robotic systems to promote the improvement of real-time simulation and monitoring of robots.On the Unity3D platform,the synchronized update of data and state was achieved by constructing a virtual twin model of a physical entity and establishing a communication connection,thus accurately realizing the virtual-reality mapping of the digital twin.After that,virtual scenes and motion simulation models were constructed and experimentally verified to demonstrate the efficiency and accuracy of the system. A digital twin system that implements robot motion simulation and state virtual-reality synchronization techniques,demonstrating the prospect and application value of digital twins in the field of robotics was presented by studies. The system is expected to optimize robot operations,improve machining quality,and increase the safety level of staff operations.

In order to improve the accuracy of braking intent recognition of brake-by-wire system and make it have stronger braking scene adaptability,a braking intent recognition strategy based on fuzzy reasoning algorithm was designed,which uses vehicle gear,tire angle,brake pedal opening and brake pedal speed as characteristic parameters to reason the driver′s braking intention and the vehicle driving scene in real time,and matches the expected pressure value and dynamic characteristics of the brake-by-wire system pipeline based on the actual braking demand of the vehicle in each scenario.This strategy adopts the PID closed-loop pressure control strategy based on the FOC control algorithm of permanent magnet synchronous motor to track the expected pressure assigned by the fuzzy inference model in different braking intentions and braking scenarios in real time,and realizes the accurate conversion from the expected pressure to the actual pressure of the system pipeline,and successfully assigns the dynamic characteristics of pressure changes matched to the expected pressure in different scenarios to the actual pressure of the pipeline,and realizes the differentiated control of the actual pressure dynamic characteristics of the offline control system in different scenarios.Finally,based on the overall control strategy,a mechanical hydraulic model and a control algorithm model were built in AMEsim and Simulink,and braking intent recognition and brake pressure tracking were co-simulated,which verified the effectiveness and practicability of the strategy.

In the frontal collision, the acceleration curve of the vehicle body is the most important factor on occupants protection,due to the characteristic of high frequency oscillation of crash curve, it is very difficult to be directly used to research on the relationships between crash pulse and occupants injury. According to the characteristics of the vehicle frontal collision, the transmission path of the vehicle was divided into different stages and the acceleration curves were parametric modeled due to the different stages. The effects of two kinds of vehicle acceleration curves on the dummy injury were discussed by using the finite element model. The results show that the similarity between the simplified curve and the original curve was high, and the responses of dummies in the two curves were basically the same. The simplified curve can be used to replace the original curve for vehicle crash and dummy injury and provide assistance in studying the relationship between the vehicle acceleration characteristic points and their occurrence time on the damage of passengers.

Powerpack system is an important part of the internal-combustion railcar,and its vibration isolation performance is directly related to the running safety and riding comfort of the train.A Frequency Response Function (FRF) based substructuring synthesis method was proposed for the rigid-flexible coupled Powerpack Two-stage Vibration Isolation System (PTVIS). The method divides the PTVIS into for substructures,i.e.,diesel generating set,radiator units,public frame and train floor. Thus, the combined frequency response function of flexible public frame B, flexible base D and rigid units A can be established by synthesizing the substructures through FRF-based substructuring synthesis method twice. The reduced model can greatly improve the modeling efficiency and calculation speed,which has more important value for engineering calculation and design.The correctness and accuracy of the proposed method were verified by comparing it with the results of finite element frequency response in ABAQUS software. Taking the powerpack system of an exported philippine internal combustion railcar as the research object,the FRF-based substructuring synthesis modeling method was used to study the influence of substructure mass ratio,substructure stiffness,substructure damping,stiffness and damping of isolators,and other parameters on the vibration isolation performance of the PTVIS,which provides theoretical support for the design and optimization of powerpack vibration isolation system.

Nano-grinding has been gradually applied to wafer thinning as one of the techniques to achieve low-damage processing of single crystal silicon,but the force-thermal behavior and its effect mechanism on subsurface damage formation are still unclear in the grinding process.Therefore,the connection between force-thermal behavior and subsurface damage during nano-grinding of single crystal silicon was investigated by molecular dynamics simulations. The results showed that the tangential grinding force plays a major role in material removal during nano-grinding of single crystal silicon,and the phenomenon on heat accumulation and stress concentration is obvious in the area below the front of the grit.Amorphization and phase transition are the main mechanisms of subsurface damage formation during nano-grinding of single crystal silicon under force-thermal loading.The increase in grinding force leads to a larger subsurface damage layer during removal,while a certain high temperature inhibits the formation of subsurface damage layer by enhancing the toughness of single crystal silicon.

A nonlinear pure torsional dynamic model of a planetary gear transmission system in a specific gear position of a heavy-duty hydraulic automatic transmission was developed. This gear mode demonstrates a fully compound relationship between the plantary rows. The dynamic model synthetically considers the internal excitation factors of the system, such as the time-varying meshing stiffness, the tooth side clearance and the meshing error amplitude. On the basis of which the dimensional-dynamic equation of the system in generalized coordinates was derived. The fourth-order Runge-Kutta method was used to solve the nonlinear differential equation system, and the nonlinear dynamic response of the system was obtained. A combination of time-domain response, frequency-domain response, phase-space trajectory, system bifurcation, and Poincare cross-section was used to investigate the relationship between the specific input speed and the system response, resulting in a reasonable speed for the gear. The response differences between the planetary rows at different levels caused by the composite structure were studied. It is found that a single planetary row can affect or even determine the response of the whole transmission system, which can be used to guide the production and reduce the production cost.

The impeller is one of the important core parts of the aircraft engine,and the nickel-base high temperature alloy GH4169D closed integral impeller is the most difficult one to process.The traditional EDM closed integral impeller is mainly limited by low processing efficiency and low yield.Therefore,a multi-electrode and multi-variable adaptive control system for EDM was innovated and developed.According to the discharge state and processing environment during the machining process,the gap voltage,tool lifting period and pulse closing time can be adjusted adaptively,which not only ensures the conditions for simultaneous machining of multi-electrodes,but also maintains an efficient inter-electrode processing environment.Under the condition of high energy discharge,multi-electrodes were used to process multiple flow paths of closed integral impeller at the same time.Under the condition of small energy discharge,the flow path profile after rough machining was trimmed by step machining method,which can not only improve the processing efficiency but also meet the requirements of machining surface quality.The experimental results show that in multi-electrode rough machining,the average processing time of single flow path profile is only 17 minutes,which is about 10 times higher than that of single electrode machining.In the multi-electrode finishing process,the surface roughness of the blade basin and the blade back is only 1.246 and 1.487 μm,respectively.The results show that the EDM multi-electrode and multi-variable adaptive control system can be widely used in the machining and manufacturing of closed integral impeller,which is of far-reaching significance.

The kinematic modeling of the special structure compound machine tool is carried out by D-H and H-M methods,so that the machine tool volumetric positioning error measured by the laser tracker is convenient for model parameter identification,and the forward solution of the machine theoretical model and the identification parameters of the machine kinematic error model are listed.In the kinematic error model of the machine tool,taking the theoretical volumetric position and orientation of the verification points as the basis,according to the Jacobi matrix of the volumetric position and orientation of the tool point relative to the coordinate axis of the machine tool,the block matrix combined with the L-M algorithm is used to calculate the coordinate axis compensation of the verification points,the algorithm converges quickly,and the calculation efficiency is improved compared to the Jacobi matrix iterative method,and the average value of the volumetric position and orientation error of the machine tool after the coordinate axis compensation is 0.004 22 mm and 9.99×10^-4 rad. Compared with the error before compensation,the error is reduced by 82.5 % and 16.1 %,respectively,indicating that the volumetric position and orientation accuracy of the compound machine tool has been greatly improved.

In industrial settings, detecting surface defects on copper threaded parts often faces challenges of low efficiency and poor accuracy. To address this, it proposes a copper threaded part surface defect detection algorithm based on MFA-UNet (Multi-Scale Features and Attention Fused UNet). Firstly, a dual down sampling module is designed, utilizing both ordinary convolution and dilated convolution to enhance the model′s feature extraction capabilities. Secondly, a compound spatial attention module is integrated into the skip-connection part to improve the model′s ability to extract spatial and edge information. Subsequently, a squeeze and excitation module is incorporated during the upsampling process to enhance the model′s expressive power and feature selection ability. Lastly, it proposes a similarity comparison algorithm that measures the similarity between segmented images and mask images to obtain the defect detection results. Experimental results demonstrate that the proposed segmentation model achieves a PA of 94.81 % and an MIoU of 93.78 % on the copper threaded part defect detection dataset. The defect detection accuracy of the proposed algorithm reaches 98.9 %, meeting the requirements for industrial field applications.

Aimed at the impact of various factors such as arc light,welding wire,and arc occlusion during pipeline welding,which made it difficult to accurately extract the edge of the molten pool contour,an improved traditional Canny operator-based molten pool edge detection algorithm was proposed. Firstly,guided filtering was used to replace Gaussian filtering for edge preservation and denoising of the molten pool image. Secondly,gradient templates in the 45° and 135° diagonal directions were added to the horizontal and vertical directions for detection,and gradient components were calculated. Finally,local adaptive thresholds were used to replace the global fixed method of dual thresholds in non-maximum suppression techniques to complete the edge detection of the molten pool.At the same time,morphological processing techniques were combined to improve the noise resistance and adaptability of edge extraction. The experimental results show that through different swing width tests,the extracted molten pool width through the improved algorithm is being verified with the weld seam width after welding. The accuracy of the extracted molten pool width is greater than 95.56 %,and the error does not exceed 0.3 mm,which meets the accuracy requirements of GMAW molten pool width measurement.

It is difficult to extract the stator current fault features of induction motor,and the selection of Support Vector Machine (SVM) penalty coefficient c and kernel function parameter g has great influence on the diagnosis results.An induction motor fault diagnosis method based on Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (ICEEMDAN) and Support Vector Machine (POA-SVM) optimized by Pelican Optimization Algorithm (POA) was proposed.Firstly,ICEEMDAN was used to decompose the stator current filtered by notch filter to obtain a series of Intrinsic Mode Function (IMF).Then,the first 7 order IMF components of each state signal were selected and the energy entropy was calculated as the fault feature vector.Finally,the fault feature vector was input into the POA-SVM model to obtain the diagnosis result. Through the simulation software Ansoft/Maxwell,the motor model was established to obtain the current data,the diagnosis accuracy reaches 100 %, and the fault diagnosis of induction motor was realized. In order to further verify the superiority of the diagnosis method,a motor fault simulation test bed was built to collect current signals.The results show that the diagnosis accuracy of the proposed method can reach more than 97.5 % under three load conditions: no-load,half-load and full-load.Compared with other fault diagnosis methods,the proposed method has better recognition ability for induction motor electrical faults.

In laser powder bed fusion additive manufacturing systems, the airflow circulation system serves not only as an oxygen barrier but also plays a crucial role in creating an airflow field within the build area. This airflow field primarily removes process by-products such as smoke and spatter, which are generated during the forming process and significantly impact the quality of the fabricated parts. Based on the issues of excessive spatter and residual smoke in the RS450 laser selective melting and forming equipment manufactured by Nanjing Zhongke Yuchen, simulation and modeling of the flow channels in the air duct and the overall build chamber were conducted using software tools such as SolidWorks and AnsysFluent. Subsequently, a novel waveform air inlet duct structure was proposed and optimized, taking into account practical requirements and simulation results. The simulation data indicated that the uneven distribution of the airflow field in the forming area was responsible for the excessive accumulation of smoke and spatter during the forming process. Through simulation-based optimization, significant improvements were achieved in the distribution of the airflow field, which were further validated through experimental verification. The use of the optimized structure in density experiments on test specimens also resulted in substantial enhancements.

A new Failure Mode and Effects Analysis (FMEA) model is proposed for risk assessment of the intelligent manufacturing system. Firstly, based on the literature method, expert interviews and fishbone diagram analysis method, the potential failure modes of intelligent manufacturing system are identified from Human-Machine-Material-Method-Environment (4M1E). Secondly, the triangular fuzzy number is used to obtain the risk assessment results of each failure mode and the weights of risk factors are determined by the structural entropy weight method. Finally, the Fuzzy C-Means (FCM) algorithm is used to divide the risk levels of the identified failure modes. Besides, the effectiveness and reliability of the results are verified through comparative analysis and Monte Carlo simulation experiment.

Aiming at the difficulty of power supply in real-time monitoring of pipeline flow based on industrial internet of things, a conical rotor vane pipeline flowmeter with energy collection and wireless communication capability was proposed. Firstly, the key component of the proposed flowmeter was a four-blade rotor, and the potential energy of water flow was converted into electric energy by the rotation of the rotor with permanent magnets embedded in the periphery, and the working principle analysis and power generation efficiency calculation method were given. Then, in order to further improve the power generation performance, a cone(conical rotor) was installed at the front end of the rotor to generate high-speed water flow and guide it to the nearby blades, and the influence of the cone was analyzed by fluid simulation. Secondly, the corresponding control unit of internet of things was designed, which used the electric energy generated by the rotor rotation to detect the rotor speed and communicate wirelessly with the internet server. Finally, the power generation performance and measurement accuracy were evaluated through experi-ments. The results show that the pressure difference before and after the rotor blade with cone is obviously greater than that without cone. With the increase of cone diameter, the power and pressure difference generated by the rotor will increase, and the highest power generation efficiency is 0.074. The flow rate can be obtained by measuring the rotational speed, and the full-scale accuracy is 1.2 %. When the flow rate is greater than 0.6×10^-3 m³/s, the output power of the flowmeter is greater than 10 mW, which is enough to realize long-term wireless flow monitoring.