Table of Content

10 February 2022, Volume 33 Issue 03

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Electromechanical Coupling Modeling and Dynamic Characteristic Analysis of Wind Power Transmission Systems under Operation Conditions

QIN Datong, LYU Xuehui, CHEN Ruibo, YANG Zhanbin

2022, 33(03):  253-260.  DOI: 10.3969/j.issn.1004-132X.2022.03.001

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To reveal the electromechanical coupling dynamic characteristics of the wind power transmission systems under the variable speeds and variable load operation conditions， the electromechanical coupling model of the wind power transmission systems including the gear system dynamics model， the finite element model of permanent magnet synchronous generator and the operation control model of wind turbine was established， taking into consideration of the nonlinear factors such as gears time-varying meshing stiffness， cogging effect and magnetic saturation of generators. The dynamic responses of the systems under the starting and power generation operation conditions and the electromechanical coupling dynamic characteristics of the system were analyzed. The results show that the dynamic responses of the wind power transmission systems are stable under the starting condition； under the power generation operation condition， the wind power transmission systems are under a variable speed and variable load state， and low-frequency torsional vibrations are vulnerable to be excited and dynamic responses are complicated. Under the effects of generator cogging， magnetic saturation and other factors， the currents and electromagnetic torques may produce main harmonic frequency fluctuations caused by time harmonics and space harmonics. Because of the electromechanical coupling effects， the gear vibration characteristics and the electromagnetic characteristics may affect each other. The currents and electromagnetic torques contain more mechanical vibration frequency components related to gear meshing. At the same time， the electromagnetic torques react to the gear systems， which excites rich structural frequency components of the gear systems. 

Scale Thorn Formation Regularity and Inhibitory Measures in Cryogenic Cutting Processes of Aluminum Alloy 7075

LIU Xiao, DENG Wenjun, CHEN Haitao, ZHANG Baoyu

2022, 33(03):  261-269.  DOI: 10.3969/j.issn.1004-132X.2022.03.002

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 Aiming at the problems of dry cutting aluminum alloys that were prone to scale thorns and poor surface integrity under low and medium cutting speeds, the orthogonal cutting experiments of aluminum alloy 7075 were carried out at different machining parameters using liquid nitrogen. The surface topography of workpieces and distribution of scale thorns were analyzed through scanning electron microscope, and the dimensions of scale thorns were measured by 3D surface profiler accurately. The effects of cutting speeds, feed rates, rake angles and cooling strategies (dry cutting, liquid nitrogen cooling, cutting fluid) on the distributions and sizes of scale thorns were analyzed. Based on the formation theory of scale thorns, the effects of machining parameters and liquid nitrogen cooling on the formation processes of scale thorns were discussed. Accumulated metals were a necessary and sufficient condition of the formation of scale thorns, and might be inhibited by improving tribological properties between chip and rake face. The results show that high cutting speed, low feed rate and large tool rake angle may reduce the thickness of accumulated metals, and inhibit the formation of scale thorns. Under cryogenic cutting conditions, the distribution density and size of the scale thorns are less than that of dry cutting, and a finishing surface topography of workpieces may be obtained.

Body Design of a Storage Tank Wall-climbing Robot Based on Magnetic Adsorption

QIU Shicheng, WU Jianbo, ZHAO Hengzhong, WANG Shen, HU Qifan, YAN Rong

2022, 33(03):  270-278.  DOI: 10.3969/j.issn.1004-132X.2022.03.003

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 For the automatic detection of weld defects in large storage tanks, a wall-climbing robot needed to complete automatic omni-directional scanning. Firstly, according to the force state of the wall-climbing robot under different operating conditions, a mechanics model of the wall-climbing robot was established to analyze and obtain the four unstable hazards of non-sliding, non-longitudinal rollover, non-lateral rollover and compound motion state. The force state of the permanent magnet adsorption wheel was simulated and optimized by Maxwell software to meet the adsorption requirements. At the same time, the coding wheel with auxiliary adsorption function was designed to supplement the margin of safe adsorption force while feeding back the position information to increase the obstacle crossing and anti-instability abilities. Finally, according to the design model, the wall-climbing robot body was manufactured and tested. The test results prove that the robot designed herein may realize the omnidirectional driving operations with load stability at various ustable hazards.

Simulations and Experiments on Abrasive Water Jet Machining Based on Fluid Self-excitation

DENG Qianfa, WANG Yangxiao, YUAN Julong, LYU Binghai, ZHAO Tianchen, WANG Xu,

2022, 33(03):  279-289.  DOI: 10.3969/j.issn.1004-132X.2022.03.004

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To precisely machine advanced ceramics with enhanced machining efficiency, a new type of water jet machining method was proposed based on fluid self-excitation, termed self-excited oscillating abrasive water jet machining(SEO-AWJM). ANSYS Fluents large eddy simulation model was used for fluid simulation. Simulation results show that with the inlet velocity of 135 m/s and the cavity length of 4 mm, the downstream nozzle outlet pulse rate reaches a maximum of 28.47%. The pulse characteristics of the jet beam cause periodically changes of stagnant layer of workpiece surfaces. Thereby a higher peak wall shear force was obtained and the force reciprocated on workpiece surfaces. SEO-AWJM experiments were conducted, the length of the chamber was adjusted to obtain the best fluid self-excited effectiveness, and silicon nitride substrate was processed. Experimental results show that after 10min fixed-point machining, the maximum removed depth is as 7.5 μm with abrasive water jet machining(AWJM)，while it is as 9.4 μm with SEO-AWJM. The initial surface roughness value Ra was 108.9 nm. After 6 times of AWJM, Ra reaches a stable value of 47.9 nm, after 4 times of SEO-AWJM, Ra reaches a stable value of 51.3 nm.

Design Optimization for Hydraulic Systems of Forklift Boom Based on Deep Surrogate Model

LIN Jingliang, HUANG Yunbao, LI Haiyan, ZHOU Sheng, HUANG Zeying

2022, 33(03):  290-298.  DOI: 10.3969/j.issn.1004-132X.2022.03.005

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To improve the performance of using fine-tune to construct deep neural network surrogate models(named also by DSMs), an active closed-loop Monte Carlo method for design of experiments was presented. The design point was associated with the model gradient through Fisher information matrix, and solved by multiplication algorithm. A random-discretization based Monte Carlo algorithm was then given for closed-loop sampling, so that the design points had the statistical characteristics covering the entire design space. Based on this method, a DSM of action characteristics of a telescopic forklift was constructed with multilayer perception, and combined with minimizing the predictor and expected improvement to realize the design optimization of the hydraulic control systems. Experimental results show that compared with the benchmarks, the simulation data required by the proposed method is reduced by 64.3%. The pressure fluctuation of luffing cylinders for the optimized forklift booms is more stable, and the maximal value is decreased by 46%.

Design of Dimensional Parameters of Chip Breaker Groove for PCD Cutting Tools

CHI Jianying, YU Aibing, WU Maochao, YUAN Jiandong, CHEN Qiujie, SUN Lei

2022, 33(03):  299-309.  DOI: 10.3969/j.issn.1004-132X.2022.03.006

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In order to solve the chip winding problems during aluminum alloy cutting by PCD cutting tool, a chip breaker groove was designed on rake surface of PCD cutting tools. Through the analysis of forces on chip and chip breaking mechanism of chip breaker grooves, the derivation of the cutting geometry relationships and the finite element cutting simulation experiments, five parameters of chip breaker groove of PCD cutting tools were proposed, including rib width, dip angle, anti-chip angle, groove width and rotation angle of anti-chip surface. The calculation formula of rib width and anti-chip angle of chip breaker grooves for PCD cutting tools were established, and the calculation formula of groove width was improved. The ranges both of dip angle and rotation angle of anti-chip surface were determined. Combined with the solving processes of five parameters of chip breaker grooves, a design method of dimension parameters of chip breaker groove for PCD cutting tools was proposed. Chip breaker groove was fabricated on rake surface of PCD cutting tools with laser. Chip breaking effectiveness of the designed chip breaker groove of PCD cutting tools was proved through cutting experiments of aluminum alloy materials. Experimental results show that the designed chip breaker groove of PCD cutting tools may expand the ranges of cutting parameters with good chip breaking effectiveness.

Analysis of Low Frequency Vibration Characteristics of Locally-resonant Vibration Isolation Systems

GAO Shengyao, GUO Peng, ZHOU Qizheng

2022, 33(03):  310-317,347.  DOI: 10.3969/j.issn.1004-132X.2022.03.007

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To effectively reduce the impact of low-frequency vibration of the base on measurement accuracy of precision instruments， a vibration attenuation method of periodically arranged absorbers was proposed. The dynamics model of substrate-vibration isolation equipment-vibration absorber system was established， the analytical solution of coupled vibration equation of the systems was derived by modal superposition method and verified by finite element method. The influence laws of number and parameters of vibration absorbers on low frequency vibration performance of the systems were obtained， when the total number of vibration absorbers was fixed， which was divided into several periodic cells with different number of resonators. Taking 0.7 times of the maximum amplitude and 0.3 times of the average amplitude as objective function， the parameters of resonator in cell were optimized by PSO algorithm. Results show that within the target frequency range， the relative errors between the analytical solution and the finite element one are as 4.39% and 2.98% respectively. Within the target frequency range， for the single-resonator cell， the vibration attenuation performance with 5 resonators is the best and the vibration attenuation efficiency is as 11.34%. When the mass ratio， natural frequency ratio and damping ratio of the absorber are around 0.16， 0.8 and 0.18 respectively， the vibration attenuation performance is the best， and the damping efficiencies are as 10.46%， 8.69% and 12.20% respectively. The vibration attenuation efficiency of optimized single-resonator， double-resonator， and triple-resonator cells may achieve 12.45%， 18% and 18.3% respectively. 

Surface Roughness Prediction Method of CNC Milling Based on Multi-source Heterogeneous Data

LI Congbo, LONG Yun, CUI Jiabin, ZHAO Xikun, ZHAO De

2022, 33(03):  318-328.  DOI: 10.3969/j.issn.1004-132X.2022.03.008

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To overcome the poor generalization and low accuracy of the traditional surface roughness prediction model of CNC milling, a novel surface roughness prediction method of CNC milling was proposed based on multi-source heterogeneous data. Firstly, the static data such as processing parameters, tool diameter and workpiece material and dynamic data such as vibration signals, force signals and power signals were collected in CNC milling with variable technologies. Then, particle swarm optimization(PSO) algorithm was used to optimize the network structure parameters of CNN for obtaining PSO-CNN, which might adaptively extract the features of dynamic data. Features of static data were manually extracted. A shallow neural network was carried out to fuse the features of multi-source heterogeneous data such as dynamic data and static data, which might be used to build surface roughness prediction model of CNC milling with variable technologies. Finally, the superiority of the proposed method was demonstrated according to the performance comparison tests with different surface roughness prediction models. And, the validity of the proposed method was verified by the example of two workpiece machining.

Related Parallel Machine Online Scheduling Method Based on LSTM-PPO Reinforcement Learning

HE Junjie, ZHANG Jie, ZHANG Peng, WANG Junliang, ZHENG Peng, WANG Ming

2022, 33(03):  329-338.  DOI: 10.3969/j.issn.1004-132X.2022.03.009

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To solve the related parallel machine online scheduling problems, the total weighted completion time was taken into account, and an online scheduling method was proposed based on LSTM-PPO reinforcement learning. A LSTM-integrated agent was designed to record the historical variations of workshop states and the corresponding scheduling policy adjustment, and then online scheduling decision was made according to the state information. Meanwhile, the workshop state matrix was designed to describe the problem constraints and optimization goals, additional machine waiting was introduced in scheduling action space to expand solution space, and the reward function was designed to decompose the optimization goal into step-by-step rewards to achieve scheduling decision evaluation. Finally, the model updating and global optimization of parameters was achieved by PPO algorithm. Experimental results show that the proposed method has competitive solutions than the existing heuristic rules, and the proposed algorithm is applied to the production scheduling of the actual workshops, which effectively reduces the total weighted completion time.

Relocalization-based Hand-eye Calibration Algorithm for Blade Robotic Grinding Systems

LYU Rui, PENG Zhen, LYU Yuanjian, TIAN Linli, ZHU Dahu

2022, 33(03):  339-347.  DOI: 10.3969/j.issn.1004-132X.2022.03.010

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Relocalization-based eye-hand calibration algorithm was proposed to solve the problems of manual errors and quadratic errors in hand-eye calibration in robotic grinding systems. Taking the photographic 3D scanner as the calibration object, the hand-eye calibration mathematical model of the robot was analyzed, and then the calibration scheme was constructed by using the criterion sphere that moved around tool center point in robot end-effector coordinate frame. By virtue of the least square method, the relocalization center coordinate in the scanner coordinate frame was calculated, both translation vector and rotation matrix were calibrated by using the quaternion-based multi-space points coupling, and then the conversion matrix from scanner coordinate frame to robot base coordinate frame was obtained. Both of the hand-eye calibration and blade grinding experiments shows that the sphere fitting radius deviation of the proposed algorithm reduces to 0.068 mm, which is reduced by at least 38% compared with the existing algorithms. Meanwhile, the average blade surface roughness value Ra after grinding is reduced to 0.273 μm from the value of 2.5 μm after milling operation, and the profile errors reach within ±0.08 mm, which meet the technical requirements, thereby the proposed method is verified to be effective and accurate. 

Information Extraction Method of Part Machining Features Based on Image Deep Learning

ZHANG Shengwen, ZHOU Xi, LI Bincheng, CHENG Dejun, CHEN Wendi

2022, 33(03):  348-355.  DOI: 10.3969/j.issn.1004-132X.2022.03.011

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Aiming at the information integration problems for machining features of various part models based on model definition（MBD）， a holographic information extraction method of machining features was proposed based on multi-level extraction architecture. Through the analysis of structural characteristics of parts， the machining features were classified with the simplest features that had manufacturing semantics and could not be split. Based on elaborating the extraction strategy， a machining feature classifier was built by deep learning image recognition technology. Based on the characteristics of MBD model information annotation， the machining feature topology structure was quickly located and extracted. A multi-view capture dimensionality reduction method was used to make the machining feature color image. And then a comprehensive analysis method for multi-angle image recognition of machining features was designed. Based on the query views， the annotation information of the MBD models was filtered， and a double-layer filtering extraction method for machining feature geometric information was constructed. Finally， a holographic information extraction software for machining features was established， and experimental results of key parts of marine diesel engines show the effectiveness of the method. 

Data Modeling，Integration and Storage Technology for Production Process Management and Control

SUN Yun, JIANG Haifan, DING Guofu

2022, 33(03):  356-365.  DOI: 10.3969/j.issn.1004-132X.2022.03.012

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Aiming at the problems of non-universal data description model， high interface maintenance cost and inefficient storage architecture during the implementation of production process management and control systems， after analyzing the production data characteristics， a unified data model was firstly constructed using the EXPRESS-G diagram. Then， various communication protocols were integrated and maintained via communication adaptation layer， and large-scale production data was stored efficiently based on Redis-MongoDB-HDFS architecture. Finally， a case study for production process management and control systems of a flexible manufacturing cell demonstrates the effectiveness and feasibility of the proposed method. 

Optimization of Complex Product Design Change Decision Based on Process Correlation Considering Agent Psychological Perception

XING Qingsong, LIANG Chuang, LIANG Xuedong

2022, 33(03):  366-377.  DOI: 10.3969/j.issn.1004-132X.2022.03.013

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 Based on design structure matrix， the process coupling analyses were difficult to effectively solve the multi-agent decision optimization problems in the change of complex product designs， such as the coupling of process correlation， the readjust of designs， and the reallocation of design resources. Moreover， the theory of decision optimization with the agent as a completely rational agent deviated greatly from the specific practices. An optimization method of complex product design change decision was proposed considering the psychological perception of the agent under process correlation. The prospect theory was used to construct the complex product design change decision optimization model with the objective function of minimizing the psychological disturbance of the design agent repeated execution and the delay period of design change. A thing and season-based adaptive multi-objective dynamic scheduling algorithm  was proposed by using two-layer coding method combining process and design agent. At last， the rationality and validity of the above decision model and method were verified by the comparison experiments and result analyses of the example simulation.