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    25 September 2023, Volume 51 Issue 9
    2023, 51(9):  0. 
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    Mechanical Engineering
    WANG Shiyong, QIAN Guokang, LI Di, et al.
    2023, 51(9):  1-10.  doi:10.12141/j.issn.1000-565X.220745
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    Template matching is a common key technology in the field of machine vision. Currently, edge feature-based template matching methods are facing challenges such as time-consuming searching and low matching accuracy in a complex environment. In order to ensure the robustness while improving the real-time performance, this paper proposed a real-time edge feature-based template matching method. Firstly, in the stage of template creation, a new edge sparse method was proposed, and it can screen out the strong invariant edge points from the template image. It reduces the redundancy of template information while retaining the key template features to ensure the stability and improve the computing efficiency. Secondly, in the stage of pyramid search-based image-matching, a top-level pre-screening method was proposed. Normalized Manhattan distance was used as a constraint to exclude incorrect target poses from the top search results to speed up the search in subsequent layers. Five datasets with different working conditions were constructed, and the proposed template matching method was compared and applied to the fast visual dispensing process for free plane pose. The experimental results show that the proposed matching method can significantly improve the matching speed while ensuring high accuracy. And it can overcome interference factors such as illumination change, rotation, defects, multiple targets, and occlusion, enabling practical applications that require both high robustness and real-time performance.

    ZENG Min, XIE Jianxing, LI Zhitao, et al.
    2023, 51(9):  11-18.  doi:10.12141/j.issn.1000-565X.220826
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    Hot bar soldering is a method used to connect electronic components. The stability of soldering horn temperature is the decisive factor of soldering quality. Due to the short time of hot bar soldering, the thermal inertia and random noise of thermocouple measurement have a great influence on the temperature control of the process. This paper developed a hot bar soldering power supply with STM32F407 microprocessor as the core, and designed the main circuit and control system of the power supply. By analyzing the delay response and time constant error of the thermocouple, this paper designed a new control method of hot bar soldering based on an Extended Kalman Filter (EKF) state observer, which realizes pulse width modulation and stable control of soldering temperature. It also analyzed the heating and thermal radiation effects of the heater tip, established a temperature model of the heater tip, and developed a simulation model of the hot bar soldering system based on the above main circuit and control scheme to verify the effectiveness of the control methods. A testing platform for the hot bar soldering system was built, and experiments were conducted according to the process parameters set by the simulation model. The simulated temperature waveform was compared and analyzed with the measured waveform. The results show that the trend of the simulated and tested temperature waveforms follows the same pattern. Compared to only using PID control, the control method based on EKF achieves a shorter adjustment time, reduces the impact of effective noise on the hot bar soldering system, and improves temperature control stability. The simulation model of the hot bar soldering system provides a reference model for the design of the hot bar soldering power supply. Finally, the hot bar soldering tests of FPC and PCB board, coaxial cable and LED circuit board were carried out to achieve the reliable connection of the components.

    YU Mingquan, ZHAO Jiyun, MAN Jiaxiang, et al.
    2023, 51(9):  19-29.  doi:10.12141/j.issn.1000-565X.220693
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    High water-based hydraulic motors can be used in fields such as coal mining, food, and underwater operation due to their medium-friendly nature. However, currently high water-based motors still use hydraulic oil motor structure, only replacing the medium with high-water-based emulsion. Traditional shaft and disk flow structures will suffer severe leakage and rusting phenomena under low-speed, high-pressure, and high water-based conditions. Additionally, the current valve flow structure problem is that one plunger needs to be equipped with two check valves, which causes the motor to have a larger volume, and the flow valves must be accurately matched. Otherwise, there will be channeling and fluid entrapment phenomena. In view of the above problems, a shuttle valve flow structure was proposed to control the motor flow distribution, which consists of a shuttle valve and a cam. The cam drives the plunger’s liquid intaking and discharging process. Firstly, the flow valve was structurally designed and theoretically analyzed, revealing its flow distribution principle. Secondly, the dynamic response characteristics of its parameters were analyzed in AMESim. The cam driven by the sine acceleration function curve was selected to control the valve core, and the flow-through hole with a diameter of 0.6 mm, with small pressure and flow fluctuations, was used. Additionally, the motor’s torque fluctuation was 7.39%, verifying the shuttle valve’s good flow distribution performance. Fluent simulation was used to optimize the valve’s internal flow field and select the notch structure with small pressure drop and uniform velocity distribution. Based on this, prototype preparation and experimental analysis were carried out. Under 16 MPa working condition, the plunger chamber can quickly build pressure, the pressure fluctuation at the inlet of the flow valve is 12.5%, and the leakage is 2 drops/min. It can be seen that after the shuttle valve is applied to the high water-based hydraulic motor, stable flow distribution can be achieved.

    热压焊是一种应用于电子元器件的焊接方法,热压焊头温度的稳定性是焊接质量的决定性因素。热压焊接时间短,热电偶测温热惯性及随机噪声对热压焊过程温度控制有较大影响。文中研制了一种以STM32F407微处理器为核心的热压焊电源,设计了电源的主电路与控制系统;通过对热电偶的延迟响应和时间常数误差的分析,设计了一种基于扩展卡尔曼滤波器(EKF)的热压焊控制方法,实现了脉宽调制以及输出温度的稳定控制;分析了热压焊头的加热和热辐射效应,建立了热压焊头的温度模型,并以上述的主电路和控制方案为基础,建立了热压焊系统仿真模型,验证控制方法的有效性。搭建热压焊系统试验平台,按照仿真模型设定的工艺参数进行试验,将仿真温度波形与试验测量波形进行对比分析。结果表明:仿真与试验温度波形趋势呈现相同变化规律,相较于仅PID控制,基于EKF的控制方法具有更短的调节时间,减少了有效噪声对热压焊系统的影响,提高了温度控制的稳定性;该热压焊系统仿真模型为热压焊电源设计提供了一种参考模型;最后进行了FPC与PCB板、同轴线与LED电路板热压焊试验,实现了元器件的可靠连接。
    DING Jiang, LU Mengen, ZENG Ziyang, et al.
    2023, 51(9):  30-43.  doi:10.12141/j.issn.1000-565X.220767
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    To broaden the effective frequency band of piezoelectric energy harvesters, this paper designed a nonlinear magnetic piezoelectric energy harvester with adjustable frequency and fast switching between monostable and bi-stable mode. This harvester is composed by adding a pair of movable magnets on a piezoelectric cantilever beam with an end magnet. Firstly, the distributed parameter dynamics of the harvester was analyzed. The dynamics equation of the system was derived based on Euler-Bernoulli theory, and the expressions of kinetic energy, potential energy and electric energy of the system were analyzed according to Lagrange function. The magnetic force expression of the system was obtained according to the magnetic dipole model. The first-order reduced model of the system was obtained by Galerkin discrete method and Taylor expansion, and the analytical expression of the equations was derived via the harmonic balance method. Then, the monostable and bi-stable characteristics of the harvester were studied by simulation software, and the effects of magnet spacing, damping, load resistance and other parameters on the output voltage and output power of the system were analyzed and verified by the subsequent experiment. According to the experimental result, the nonlinear magnetic force brought by the movable magnet can significantly increase the output voltage and output power of the harvester; the resonant frequency of the energy harvester can be changed by adjusting the magnet spacing, which better widens the working frequency band; the energy harvesting system can rapidly switch between monostable mode and bi-stable mode by adjusting the magnet spacing, and use the monostable mode and and the bi-stable mode to harvest vibration energy in high-frequency environment and the low-frequency environment, respectively.

    XIA Yimin, LI Zhenghui, TAN Shunhui, et al.
    2023, 51(9):  44-55.  doi:10.12141/j.issn.1000-565X.220651
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    In the working process of large-scale construction machinery such as excavators and shield machines, due to the complex working conditions and changeable environment, the hydraulic system power component axial piston pump of large displacement has greater hydraulic impact than the conventional piston pump, and it causes greater flow pulsation and pressure pulsation. In order to reduce the flow and pressure pulsation of axial piston pump of large displacement under excavation, shield and other working conditions, reduce the impact damage of oil medium on downstream components, and provide theoretical guidance for selecting oil medium methods, this paper built a mathematical model of oil dynamic viscosity, density and bulk elastic modulus based on the influence of temperature field. On this basis, a mathematical model of piston pump with solid-liquid-temperature coupling was established. ADAMS and AMESim software were used to complete the joint simulation of 750 mL/r piston pump under the coupling of solid-liquid-temperature, and the variation law of flow pulsation and pressure pulsation of piston pump under different temperature was obtained. The influence of oil temperature on the pressure pulsation of the piston pump was investigated by the whole pump test, and the correctness of the solid-liquid-temperature coupling simulation model of the 750 mL/r piston pump was verified. According to the three characteristics of oil, the orthogonal test method and the single factor analysis method were used to consider their influence degree and influence law on the flow pulsation rate of the piston pump, respectively. The results show that the outlet flow pulsation and pressure pulsation of the piston pump increase with the increase of temperature. Under the set condition, the influence of oil bulk modulus on flow pulsation rate is 97.19%, the density is 2.03%, and the dynamic viscosity is 0.78%. In order to reduce the influence of oil characteristics on the pulsation rate of piston pump outlet, hydraulic oil with larger bulk modulus and smaller density should be selected.

    JI Xiang, WANG Haihong, ZHAI Tiansong, et al.
    2023, 51(9):  56-68.  doi:10.12141/j.issn.1000-565X.220415
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    The position control of robot manipulators has been recognized as the most fundamental and simplest objective in the robotic control field. For the high-precision position control problem of the multi-axis robot system, this study proposed a simple output feedback nonlinear PD plus gravity compensation (PD+) synchronization position controller combining with the cross-coupling techniques. The global finite-time stability of closed-loop systems was strictly demonstrated by applying Lyapunov stability theory and geometric homogeneity techniques. Compared with the asymptotic stable full-states feedback control schemes, the presented controller ensures the finite-time stability of the robot manipulators with position measurements only; compared with the output feedback asymptotic stable controllers, the proposed controller ensures the finite-time convergence of robot’s states; compared with the output feedback controllers without synchronization term, the proper introduction of nonlinear synchronization control items enables the proposed controller to take into account the synchronous and coordinated motion between the axes on the premise of ensuring the high-precision position control of the multi-axis robot system. The proposed controller has the advantages of simple structure, easy implementation, faster response speed and better overall system performance, which meets the high precision requirements of actual production for the robot system. Numerical simulation results demonstrate the effectiveness of the proposed control algorithm and the expected performance of the system. The proposed control method not only ensures the global output feedback finite-time stable synchronization control of multi-axes robot systems, but also provides an effective alternative approach for the output feedback synchronization position stabilization of a large class of nonlinear second-order systems.

    Computer Science & Technology
    LI Fang, GUO Weisen, ZHANG Ping, et al.
    2023, 51(9):  69-81.  doi:10.12141/j.issn.1000-565X.220809
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    Bearing is one of the important components in many production equipment, and the study of its remaining useful life is of great value. A prediction method for remaining useful life of bearings based on spatial-temporal dual-cell state self-adaptive network (ST-DCSN) was proposed for the prediction error caused by the degradation state change and timing correlation that are not fully considered in the traditional bearing remaining life prediction in different environments. This paper adopted an embedded convolution of coexisting temporal and spatial states to operate the dual-state recurrent network and introduced spatio-temporal dual-cell state and sub-cell state differential mechanism to realize adaptive perception of bearing attenuation states. This method effectively captures the feature state of the bearing monitoring data in both temporal and spatial dimensions, so as to solve the influence of environmental and timing problems on the prediction performance of bearing remaining life prediction. To investigate the effectiveness of the proposed method and compare it with other state-of-the-art approaches, two real bearing life accelerated degradation datasets, namely FEMTO-ST and XJTU-SY, were used for validation. Both ablation experiments and comparative experiments were conducted, and four evaluation metrics were employed to assess the prediction performance. The ablation results demonstrate that the complete version of ST-DCSN outperforms the experiment groups with removed spatial cell and dynamic and static sub-cell in terms of stability and performance metrics. Compared to other methods, the proposed method achieves superior prediction performance with higher fitness and better stability in the prediction results at the end of life of bearing. This demonstrates that the ST-DCSN method can effectively improve the accuracy of bearing’s remaining useful life prediction.

    LI Jiachun, LI Bowen, LIN Weiwei
    2023, 51(9):  82-89.  doi:10.12141/j.issn.1000-565X.220825
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    The harm caused by video tampering has been endangering people’s lives, which makes deep forgery detection technology gradually obtain widespread attention and development. However, current detection methods could not effectively capture noisy residuals due to the use of inflexible constraints. In addition, they ignore the correlation between texture and semantic features and the impact of temporal features on detection performance improvement. To solve these problems, this paper proposed an adaptive network (AdfNet) with diverse features for deep forgery detection. It helps the classifier to judge authenticity by extracting semantic features, texture features and temporal features. The paper explored the adaptive texture noise extraction (ATNEM) mechanism, and flexibly captured the noise residuals in non-fixed frequency bands through unpooled feature mapping and frequency-based channel attention mechanism. The deep semantic analysis guidance strategy (DSAGS) was designed to highlight the tampering traces through spatial attention mechanism, and guide the feature extractor to focus on the deep features of the focus region. The paper studied multi-scale temporal feature processing (MTFPM), and used temporal attention mechanism to assign weights to different video frames and capture the difference of time series in tampered videos. The experimental results show that the ACC score of the proposed network in the HQ mode of FaceForensics++(FF++) dataset is 97.41%, which is significantly better than that of the existing mainstream algorithms. Moreover, while maintaining the AUC value of 99.80% on the FF++ dataset, the AUC value can reach 76.41% on Celeb-DF, reflecting strong generalization.

    SU Jindian, YU Shanshan, HONG Xiaobin
    2023, 51(9):  90-98.  doi:10.12141/j.issn.1000-565X.230031
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    Although the pre-trained language models like BERT/RoBERTa/MacBERT can learn the grammatical, semantic and contextual features of characters and words well through the language mask model MLM pre-training task, they lack the ability to detect and correct spelling errors. What’s more, they faces the problem of inconsistency between the pre-training and downstream fine-tuning stages in Chinese spelling correction CSC task. In order to further improve BERT/RoBERTa/MacBERT’s ability of spelling error detection and correction, this paper proposed a self-supervised pre-training method MASC for CSC, which converts the prediction of masked words into recognition and correction of misspelled words on the basis of MLM. First of all, MASC expands the normal word-masking in MLM to whole word masking, aiming to improve BERT’s ability of learning semantic representation at word-level. Then, the masked words are replaced with candidate words from the aspects of the same tone, similar tone and similar shape with the help of external confusion set, and the training target is changed to recognize the correct words, thus enhancing BERT’s ability of detecting and correcting spelling errors. Finally, the experimental results on three open CSC corpora, sighan13, sighan14 and sighan15, show that MASC can further improve the effect of the pre-training language model, i.e. BERT/RoBERTA/MacBERT, in downstream CSC tasks without changing their structures. Ablation experiments also confirm the importance of whole word masking, phonetic and glyph information.

    LI Haiyan, YIN Haolin, LI Peng, et al.
    2023, 51(9):  99-109.  doi:10.12141/j.issn.1000-565X.220420
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    To effectively solve the problems of low feature utilization and poor image structure coherence occurred when existing algorithms are used to repair large irregularly missing images, this study proposed an image repair algorithm based on dense feature inference (DFR) and hybrid loss function. The repair network consists of multiple inference modules (FRs) densely connected. Firstly, after the image to be restored was fed into the first inference module for feature inference, the output feature map channels were merged and sent to the next inference module. The input of each subsequent inference module was the inferred features from all the previous inference modules and so on, so as to make full use of the feature information captured by each reasoning module. Subsequently, a propagation consistent attention (PCA) mechanism was proposed to improve the overall consistency of the patched regions with the known regions. Finally, a hybrid loss function (ML) was proposed to optimize the structural coherence of the repair results. The whole DFR network adopted group normalization (GN), and excellent repair results can be achieved even using small training batches. The performance of the proposed algorithm was verified on Paris StreetView and CelebA face datasets, which are internationally recognized datasets. The objective and subjective experimental results show that the proposed algorithm can effectively repair large irregular missing images, improve feature utilization and structural coherence. Its average peak signal-to-noise ratio (PSNR), average structural similarity ( SSIM), mean square error (MSE), Fréchet distance (FID) and learning perceptual image block similarity (LPIPS) metrics all outperform the comparison algorithms.

    LIU Yijun, WANG Jiada, ZHONG Shijie, et al.
    2023, 51(9):  110-119.  doi:10.12141/j.issn.1000-565X.220751
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    In the field of multi-view clustering, many methods learn the similarity matrix directly from the original data, but this ignores the effect of noise in the original data. In addition, some methods must perform a feature decomposition on the graph Laplacian matrix, which leads to reduced interpretability and requires post-processing such as k-means. To address these issues, this paper proposed a fast multi-view clustering based on a unified label matrix. Firstly, a non-negative constraint was added to the objective function from the unified viewpoint of the normalized cut of the relaxation and the ratio cut. Then, a structured graph reconstruction was performed on the similarity matrix by the indicator matrix to ensure that the obtained graph has strong intra-cluster connections and weak inter-cluster connections. In addition, the number of iterations was reduced by setting a unified label matrix, thus further improving the speed of the method. Finally, the problem was solved optimally based on an alternating direction multiplication strategy. The algorithm aligns the multi-view dataset by randomly selecting the anchor addresses, and aligning the views can significantly improve the accuracy of clustering. The problem of the high computational complexity of traditional spectral clustering algorithms was effectively solved by using singular value decomposition instead of feature decomposition in the iterative process. Labels were obtained directly by indicating the column labels of the largest element of the matrix by row index. Experimental results on four real datasets demonstrate the effectiveness of the algorithm, and show that its clustering performance outperformed the nine existing benchmark algorithms.

    Architecture & Civil Engineering
    WU Bo, DING Jinpeng
    2023, 51(9):  120-128.  doi:10.12141/j.issn.1000-565X.230008
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    Large amount of hole slag will be produced in the construction of punched cast-in-place piles for highway bridges. It is an effective countermeasure to apply the hole slag to concrete components of highway bridges nearby. Based on the recycling use of recycled coarse aggregates (RCAs) and considering that concrete structures in coastal areas are greatly affected by chloride corrosion, this paper prepared the recycled aggregate concrete mixed with the hole slag by replacing natural sand and natural coarse aggregates with the hole slag and RCAs, respectively. To investigate the effects of the hole slag replacement ratio (0, 50%, 70%, 100%) and RCAs replacement ratio (0, 50%, 70%, 100%) on the compressive and chloride resistance properties of such concrete, this paper carried out compression and chloride resistance tests of 96 specimens (48 cylinders with Φ 150×300 mm for compression test, and 48 cylinders with Φ 100×50 mm for chloride resistance test) made of such concrete, and mercury intrusion tests of the hole slag, river sand, and corresponding mortar. The test results show that: the compressive strength of such concrete decreases gradually with the increase of the replacement ratios of the hole slag and RCAs, and the reductions caused by the two are roughly the same; compared with RCAs, the influence of the hole slag on the elastic modulus and peak strain of such concrete is relatively limited; the chloride ion migration coefficient of such concrete increases gradually with the increase of the replacement ratios of the hole slag and RCAs on the whole, but the influence of the hole slag is obviously lower than that of RCAs; with the increase of the replacement ratio of the hole slag, the porosity of such concrete generally shows a trend of increasing gradually from fast to slow. When the hole slag and RCAs are used simultaneously in practical projects, it is suggested that the maximum replacement ratios of both should be limited to 50%.

    LEI Yu, HUANG Yifan, LUO Xuedong, et al.
    2023, 51(9):  129-138.  doi:10.12141/j.issn.1000-565X.220746
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    The thermal conductivity of soil is an important soil property, which affects the soil temperature distribution underground. It has significant practical importance in geotechnical and civil engineering design and construction. Using reasonable means to predict it can effectively solve the problems such as time-consuming and complex process. According to the characteristics of nonlinearity and timing of soil thermal conductivity data, this paper proposed a firefly algorithm (FA) optimization limit learning machine (DELM) prediction model (NMI-FA-DELM) under NMI for soil thermal conductivity prediction. The model first screened the key parameters affecting the soil thermal conductivity by NMI, and took the filtered parameters as the data set. Then the soil thermal conductivity was predicted with the FA-DELM optimized by the firefly algorithm, and the predictive results were compared with those of statistical prediction equations, random forest methods, BP neural network models, DELM models, and SVR (support vector regression) models. The results show that the NMI-FA-DELM model can effectively predict soil thermal conductivity, with corresponding root mean square error, average absolute percentage error, a10 index, and determination coefficient of 0.363, 9.667%, 0.961 and 0.92, respectively. The prediction accuracy of the NMI-FA-DELM model is better than that of other prediction models, and the content of viscous soil and sand has greater influence on the prediction results of soil thermal conductivity. This model can significantly improve the prediction accuracy of soil thermal conductivity and provides important guidance for predicting soil thermal conductivity in practical engineering applications.

    LI Peizhen, XIAO Jiaqu, YANG Jinping, et al.
    2023, 51(9):  139-148.  doi:10.12141/j.issn.1000-565X.220347
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    A 1∶6 ratio frame structure model was designed for shaking table test, in order to study the influence mechanism of soil-structure interaction on the dynamic displacement response of high-rise structures on soft soil foundation. Shaking table tests were performed on a high-rise frame structure considering soil-pile-structure dynamic interaction system and on a frame structure model on fixed-base condition. By comparing the structural dynamic response of the frame models considering the soil-structure interaction (SSI) and the fixed-base condition, the influence of the SSI effect on the high-level frame structure in this experiment was summarized: after considering the SSI effect, pile-soil interaction has an obvious filtering effect on seismic waves; in a large earthquake, the peak is generally weakened, and the vibration frequency of the overall structure is reduced, and the damping ratio is increased. From the perspective of structural internal forces, the SSI effect reduces the floor shear force and bending moment, and effectively reduces the impact of ground vibration on the structure. From the perspective of structural displacement, when the magnitude is small, the SSI effect reduces the elastic displacement and interlayer displacement angle of the structure, and reduces the effect of the earthquake on the structure; when the magnitude is larger, the upper floor increases the structural displacement response due to model differences and damage accumulation under some working conditions. From the perspective of structural acceleration, the SSI effect reduces the absolute acceleration and relative acceleration of the floor, and also reduces the effect of earthquakes on the structure. This is due to the radiation damping and hysteresis damping generated by soil-pile-structure interaction under the SSI effect dissipate the energy of the entire structure-pile-soil system, while the radiation waves transmitted by the soft soil foundation to the superstructure change the dynamic characteristics of the structure.

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