Volume 47,Issue 9,2024 Table of Contents

1 Multi-objective flexible job shop scheduling considering group preventive maintenance

LI Liwei , DENG Lei , LIAO Wenzhu , TANG Baoping , WANG Yi

2024, 47(9):1-13. DOI: 10.11835/j.issn.1000-582X.2023.106

[Abstract](211) [HTML](37) [PDF 2.26 M](221)

Abstract:
The demand for individualized, small batch, and customized products in society can be satisfied by the flexible job shop system, which features numerous equipment, complex process paths, and varying failure frequencies. However, the single machine preventive maintenance approach currently employed to avoid equipment breakdowns increases the number of maintenance activities, maintenance costs, and negatively impacts production operations. To address the problems caused by traditional single machine preventive maintenance, this study proposes the application of a group preventive maintenance approach in the flexible job shop system. A joint mathematical model of group preventive maintenance and multi-objective flexible job shop scheduling is established. To overcome the local search limitations of traditional algorithms, a new multi-objective evolutionary algorithm is designed to solve the multi-objective flexible job shop scheduling problem, and demonstrate the application of the group preventive maintenance strategy in the flexible job shop system. Experimental results show that the designed multi-objective evolutionary algorithm can obtain more optimal solutions, has a faster convergence speed, and achieves better optimal solutions. Compared with the single preventive maintenance method, the group preventive maintenance approach results in fewer maintenance activities, lower maintenance costs, and less impact on production activities. The example results show that the group preventive maintenance time and maintenance cost are reduced by 150% compared with the single preventive maintenance method. The study proposes that the group preventive maintenance approach can be effectively used for the maintenance of production equipment in the semiconductor foundries in the future.

2 Design and development of a large-amplitude ultrasonic vibration-assisted high-speed dry cutting device and its performance tests

HUANG Xuefeng , CAO Huajun , ZHANG Jin , SONG Yang , KANG Xinzhen

2024, 47(9):14-29. DOI: 10.11835/j.issn.1000-582X.2023.105

[Abstract](142) [HTML](38) [PDF 8.32 M](257)

Abstract:
The ultrasonic transducer is the core component of an ultrasonic vibration-assisted cutting device. To develop a large-amplitude ultrasonic vibration-assisted cutting device suitable for high-speed dry cutting, the first step is to design and develop the ultrasonic transducer. Based on the design method of the second-stage amplified ultrasonic transducer considering the tool, following the integrated design concept of amplifier-ultrasonic transducer, and combined with the results of modal analysis and harmonious response analysis using ANSYS finite element software, a two-stage amplified ultrasonic transducer was designed and developed. According to the characteristics of the developed two-stage amplified ultrasonic transducer, its matching ultrasonic generator, anti-rotation ring, power transmission system, and tool holder shell structure were systematically designed and developed. Performance tests including impedance analysis and amplitude measurement were carried out for the developed two-stage amplified ultrasonic transducer. Experimental test and analysis of the designed and developed large-amplitude ultrasonic vibration-assisted high-speed dry cutting device were conducted to explore the improvement of surface quality in the difficult-to-machining material 30CrMnSiNi2A. The results show that the longitudinal ultrasonic vibration simulation results of the two-stage amplified ultrasonic transducer are consistent with the theoretical design, and the longitudinal vibration amplitude output is stable. The longitudinal vibration amplitude is 15.4 μm at 50 % output power and can reach a maximum of 25.1 μm, with the output amplitude positively correlated with the power percentage, indicating good performance test results. The developed large-amplitude ultrasonic vibration-assisted cutting device greatly reduces the cutting force and surface roughness in the feeding direction, significantly improves the surface quality of difficult-to-machine materials, and is suitable for high-speed dry cutting of such materials.

3 Intelligent identification method of spring energy storage state of circuit breaker operating mechanism based on GAF and CNN

SHI Yizhu , MAN Tianxue , ZHOU Yuqing , REN Yan , SHEN Zhihuang , SUN Weifang

2024, 47(9):30-38. DOI: 10.11835/j.issn.1000-582X.2023.224

[Abstract](129) [HTML](28) [PDF 3.04 M](135)

Abstract:
Robust identification of the spring energy state in circuit breaker operating mechanism is of great significance for maintaining service performance. However, establishing a mapping relationship between the sampled signal and the spring energy storage state remains a key challenge limiting its widespread application. To solve this problem, this study proposes an intelligent identification method that combines Gramian angular field(GAF) and convolutional neural network(CNN) and successfully applies it to the operating mechanism of a circuit breaker. In the proposed method, GAF is used to transform the collected time-domain signal into a two-dimensional representation, which helps track the evolution process of the dynamic characteristics of the operating mechanism. The state identification experiment of the circuit breaker operating mechanism verifies the effectiveness of the proposed intelligent diagnosis method, achieving a recognition success rate close to 100.00%. This method offers a promising approach for the robust identification of the in-service state of circuit breakers.

4 Modal analysis and structural parameter optimization of aviation elastic parallel casing

WU Anyang , SONG Chaosheng , ZHAO Shuaitao , DENG Zili

2024, 47(9):39-50. DOI: 10.11835/j.issn.1000-582X.2023.108

[Abstract](112) [HTML](17) [PDF 4.31 M](138)

Abstract:
To solve the resonance problem of an aviation parallel casing, the finite element method is used to analyze the constrained modal frequencies, considering typical working conditions and the elastic support stiffness of the aircraft frame. This study investigates the influence of casing structural parameters on the constrained modal frequencies. The results show that optimizing the constraint position is the most effective way to significantly change the natural frequencies. When the natural frequency is at the edge of the resonance intervals, it can be adjusted slightly by optimizing the wall thickness and stiffener parameters. When the two constraint positions are located on the symmetry axis of the casing plane, the natural frequencies reach their minimum and decrease obviously with a reduction in the constraint distance. With an increase of the thin-wall thickness, the 1^st, 3^rd, 5^th and 6^th modal frequencies decrease, while the 2^nd and 4^th modal frequencies increase. The 1^st and 3^rd modal frequencies are almost unaffected by the stiffener parameters. The 2^nd and 4^th modal frequencies increase with the increasing width and height of the stiffener and decreasing stiffener aspect ratio. In addition, the 4^thmodal frequency increases with the increasing angle of the stiffener. The 5^th and 6^thmodal frequencies increase with an increasing stiffener angle and decreasing stiffener width. Based on these findings, the aviation elastic parallel casing was optimized to ensure the natural frequencies avoid the resonance intervals, thus improving the vibration resistance of the casing.

5 Auto disturbance rejection control of joints driven by pneumatic muscles

HUANG Guoqin , MI Juncheng , ZUO Sihong

2024, 47(9):51-60. DOI: 10.11835/j.issn.1000-582X.2023.205

[Abstract](106) [HTML](23) [PDF 2.12 M](158)

Abstract:
To solve the problems of external interference and system parameter uncertainty in the trajectory tracking of a lower limb rehabilitation robot driven by pneumatic artificial muscles, an active disturbance rejection algorithm for joint control is proposed. Based on the mathematical model of the servo control system of the pneumatic artificial muscle joint, the method firstly estimates the system state and disturbance using a third-order state expansion observer. It then compensates for the disturbance in real time and adjusts the parameters based on the separation principle. Subsequently, with using a pneumatic artificial muscle test platform, the step signal tracking control, square wave tracking control, and sine tracking control of the control system are compared and verified under fixed angle conditions. Experimental results show that the designed active disturbance rejection control (ADRC) has a faster response time and lower control error than the proportional integral differential (PID)controller, meeting the application control requirements of the lower limb rehabilitation robot.

6 Digital minimum quantity lubrication device with oil-water-air mixing

TAO Guibao , WANG Lidan , ZHU Yicheng

2024, 47(9):61-69. DOI: 10.11835/j.issn.1000-582X.2024.09.006

[Abstract](102) [HTML](21) [PDF 3.22 M](133)

Abstract:
The accurate control of oil-water-air volume and its atomization effect by the minimum quantity lubrication (MQL) device directly affect the cooling and cutting performance, thereby influencing the machining quality of parts. To improve the auxiliary cutting effect of the MQL device, a digital MQL device with oil-water-air mixing has been designed and developed to improve the continuity and uniformity of lubricant mist spray. Based on MQL atomization technology, an experimental platform for the milling process has been constructed to test its auxiliary cutting effect. The results show that the developed oil-water-air mixing digital MQL device significantly improves the quality of oil mist and the auxiliary cutting effect.

7 Multi-attribute balance design of vehicle cowl

BU Kunquan , ZHOU Lei , MAO Jie , ZHANG Yanan , ZHANG Ben , ZHOU Changshui , YAO Zaiqi

2024, 47(9):70-80. DOI: 10.11835/j.issn.1000-582X.2023.206

[Abstract](85) [HTML](22) [PDF 2.90 M](108)

Abstract:
This paper proposes a composite body solution (CBS) bracket method to balance the interior rumbling noise caused by the cowl with the adult head score for pedestrian protection. This method not only improves the interior noise level but also enhances the head score for pedestrian protection. Firstly, a comparison of the basic parameters and mechanical properties of CBS scaffold material and common metal materials reveals that CBS scaffold material has the advantages of low Young’s modulus and low yield strength. The sensitivity of adult head score for pedestrian protection to linear and nonlinear segments was distinguished according to the material’s mechanical property curve, indicating that the yield section has a higher impact on head injury. Secondly, the topology optimization method is used to obtain the initial CBS contour structure based on the main noise transfer function (NTF) contribution path of the vehicle roar noise, and the specific structure of the contour is refined. Finally, noise and pedestrian protection are verified for specific CBS structures. The results show that compared to the basic state, the roar noise from the Z-direction excitation of the right suspension to the driver’s external ear in the car is improved by 2 dB in 70 Hz to 80 Hz frequency band and about 3 dB in 150 Hz to 170 Hz frequency band, and the score for pedestrian protection is 1 points higher than the basic state. This method achieves a balance between noise reduction and pedestrian protection, verifying the feasibility of this method to resolve the conflict between noise and pedestrian safety.

8 Froth flotation purity prediction based on Wasserstein GAN data augmentation

WU Haosheng , JIANG Pei , WANG Zuoxue , YANG Bodong

2024, 47(9):81-90. DOI: 10.11835/j.issn.1000-582X.2023.107

[Abstract](95) [HTML](24) [PDF 2.07 M](115)

Abstract:
In the mineral processing industry, accurately predicting concentrate grade can help engineers adjust process parameters in advance and improve flotation performance. However, the prediction accuracy of concentrate grade has been restricted by small sample sizes, high-dimensional data, and complex temporal correlations in actual mineral processing. To address the predication challenges associated with small sample data, a time-series data generation model called LS-WGAN is proposed, which combines the Wasserstein generative adversarial network (Wasserstein GAN) and long short-term memory (LSTM) neural network. The LSTM network is mainly used to capture the time correlation in mineral processing data, while the Wasserstein GAN generates samples similar to the original data distribution for data augmentation. To improve the prediction accuracy of the concentrate grade, a mineral processing prediction model called C-LSTM is established. The prediction accuracy of the proposed method is verified through experiments based on real froth flotation process data.

9 Apparent disease detection of bridges using improved YOLOv5s

DONG Shaojiang , TAN Hao , LIU Chao , HU Xiaolin

2024, 47(9):91-100. DOI: 10.11835/j.issn.1000-582X.2023.101

[Abstract](119) [HTML](26) [PDF 2.64 M](203)

Abstract:
To solve the problems of low accuracy, high false detection rate, and high missed detection rate in current target detection methods for apparent diseases in concrete bridges, an improved YOLOv5s method is proposed. To achieve more effective fusion of features at different scales and increase receptive fields, an improved spatial pyramid pooling module is added to the YOLOv5s network to enhance feature extraction capabilities and reduce computational cost; a light-weight attention module is incorporated into the YOLOv5s network to tackle the high false detection and missed detection rates caused by the cross-distribution of different defect features in disease images; and a loss function considering vector angles is adopted to solve the problems related to varying defect sizes, classification difficulties and small dataset-induced boundary box regression mismatches. Experimental results show that the improved YOLOv5s detector significantly improves accuracy while reducing false detection and missed detection rates in the task of detecting apparent diseases in bridges.

10 Investment method of cooling electric load demand response equipment embedded with operation strategy optimization

YANG Gaofeng , LIU Sixu , MU Jie , YANG Zhifang , WANG Yi

2024, 47(9):101-111. DOI: 10.11835/j.issn.1000-582X.2022.212

[Abstract](95) [HTML](20) [PDF 1.91 M](98)

Abstract:
With the further advancement of electricity market reform, the introduction of time-of-use price and other policies has provided a favorable market environment for the application and development of demand response technology. The cooling electric load demand response technology represented by the cold storage air conditioning system can effectively alleviate the problem of power supply and demand balance. The demand response capability and potential benefits of cooling electric load are closely related to the investment planning and operation methods of demand response equipment. The-existing-cooling-technology-based demand response equipment investment planning methods mostly consider a single equipment type, and based on fixed or simplified system operation strategy for operation simulation, it is difficult to achieve the optimal matching of different types of equipment and user cold demand characteristics, resulting in the limited optimization space of the system demand response capacity and economic value. Therefore, this paper investigates the unified investment planning modeling method for cooling electric load demand response equipment considering the optimization of operation strategy. Firstly, this paper proposes a demand response model considering multiple types of chillers and operation strategy optimization in the electricity market. It realizes flexible response of cooling electric load to price signals and fully saves electricity cost. Then, this paper constructs a demand response equipment investment planning model with embedded unified operation strategy optimization to minimize the total cost of investment and operation. This model considers the price policy, cold demand characteristics, investment cost and operating characteristics of related equipment, and adopts linearization techniques to build a mixed-integer linear programming model. It can be efficiently solved by a commercial solver. The analysis shows that the proposed method can fully adapt to the current electricity market environment, effectively improve the investment efficiency of customer, optimize the electricity load curve, and leverage the value of demand response technology.

11 Day-ahead optimal scheduling of buildings considering continuous double auction trading mechanism

LIU Hui , XIONG Zhenyu , HUANG Lidong

2024, 47(9):112-128. DOI: 10.11835/j.issn.1000-582X.2023.202

[Abstract](92) [HTML](22) [PDF 4.22 M](120)

Abstract:
As the main consumers of urban energy, the low carbon and efficient operation of intelligent buildings is crucial for achieving the goals of “peak carbon dioxide emissions and carbon neutrality”. To enhance building economics while improving energy sharing and the consumption of distributed energy resources, a distributed optimal scheduling model for buildings taking into account building characteristics and energy trading was proposed. At the building optimization level, a multi-objective building operation optimization model considering economic and temperature comfort requirements was established. At the energy sharing level, a peer-to-peer buildings trading market was set up, and a new continuous double auction trading mechanism combining building optimization results and market risks was proposed. This mechanism feeds back the results of market transactions to the optimization level of each building, achieving iterative optimization and energy sharing within buildings. Robust optimization was used to test the effectiveness of the model in various uncertainty scenarios. Simulation results show that the distributed optimal scheduling model can optimize building economics while enhancing energy complementarity and the consumption of distributed energy resources in various scenarios.

12 Multi-featured short-term load forecasting based on TabNet-LSTNet

WU Wenhui , HE Jiafeng , CAI Gaoyan , LUO Dehan

2024, 47(9):129-140. DOI: 10.11835/j.issn.1000-582X.2023.201

[Abstract](83) [HTML](24) [PDF 2.71 M](133)

Abstract:
To explore the importance of different input features in load forecasting, effectively handle the linear and nonlinear components in load data, and improve the accuracy of load prediction, a combined load prediction model based on TabNet and LSTNet (long and short-term temporal networks) is proposed in this paper. First, the prediction accuracy of TabNet is improved by introducing self-supervised pre-training, and then the global importance of the input features and the prediction results are obtained by training. Next, the features with high importance are input to LSTNet, which is trained to obtain the prediction results. Finally, the prediction results of the combined model are derived using the variance-covariance combination method. Simulation analysis shows that the proposed combined model has higher accuracy compared with traditional LSTM (long and short-term memeory), Xgboost (extreme gradient boost), Lightgbm (lignt gradient boosting machine) and other combined models.

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