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Design and intelligent optimization of Z-Shaped MEMS Accelerometer Structure for Heart Sound Detection

IEEE SENSORS JOURNAL 2025年第7期25卷 10685-10693页

作者： An, Qi An, Daren Zang, Junbin Zhang, Zhidong Xue, Chenyang Shanxi Coll Technol Shuozhou 036000 Peoples R China North Univ China Sch Instrument & Elect Taiyuan 030051 Peoples R China North Univ China Key Lab Instrumentat Sci & Dynam Measurement Taiyuan 030051 Peoples R China

Digital heart sound auscultation technology is crucial for the early diagnosis of coronary heart disease, and the optimal structural design and parameter optimization of high-performance heart sound sensor devices can significantly enhance the quality of heart sound signal acquisition. The determination of conventional sensor structural parameters primarily relies on empirical selection based on simulation analysis results and repeated experimental validation, which is time-consuming and inefficient, making it difficult to reduce research and development cycles and costs. Based on this, this study proposes a novel Z-shaped cantilever beam accelerometer-based heart sound sensor structure and designs a PSO-back-propagation neural network (BPNN) optimization model that combines particle swarm optimization (PSO) and back propagation (BP) neural networks to achieve intelligent analysis and optimization selection of the parameters for the Z-shaped cantilever beam acceleration heart sound sensing structure. The results indicate that the PSO-BPNN demonstrates extremely high accuracy in predicting the maximum stress (S) and natural frequency (F) of the sensor, with relative errors as low as 1.3% and 0.1%, respectively. Furthermore, transient simulation tests using COMSOL with heart sound interpolation signals show that the optimized Z-shaped sensor performs excellently, with an output voltage amplitude reaching 0.025 V, significantly improving its response sensitivity compared to the empirical parameter structure. Therefore, this study not only enhances the efficiency of design and development while reducing empirical errors but also theoretically validates the effectiveness of intelligent analysis and design methods, laying a solid foundation for technological advancements in sensor design and the widespread application of intelligent analysis and design methods.

关键词： Heart sound sensor intelligent optimization MEMS Z-shaped accelerometer Heart sound sensor intelligent optimization MEMS Z-shaped accelerometer

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An intelligent optimization probability imaging method based on ultrasonic guided waves for rim-driven thruster protective layer damage detection

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SMART MATERIALS AND STRUCTURES 2025年第4期34卷 045009-045009页

作者： Yue, Jikang Hong, Xiaobin Xu, Guochen Chen, Weiguo Zhang, Bin South China Univ Technol Sch Mech & Automot Engn Guangzhou 510641 Peoples R China

The propagation characteristics of ultrasonic guided waves within the rim-driven thruster protective layer are more complex due to its anisotropic nature, resulting in low accuracy in damage detection using traditional imaging methods. Therefore, an intelligent optimization probability damage imaging method based on guided waves is proposed. First, a different probability of an individual is given by comparing the differences in the travel time of the individual with the travel time of the scattered signal. The total probability for the individual is derived by superimposing all paths, which serves as the fitness function. Subsequently, the individual with the highest fitness value is iteratively searched by the intelligent optimization algorithm. Finally, the optimized population distribution is considered as the damage location. The experimental results indicate that this method achieves a higher signal-to-noise ratio and detection accuracy compared to other approaches.

关键词： rim-driven thruster ultrasonic guided waves intelligent optimization damage detection

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intelligent optimization and seismic fragility evaluation of large-span spatial steel structures

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JOURNAL OF CONSTRUCTIONAL STEEL RESEARCH 2025年 232卷

作者： Yang, Xiangbing Shan, Wenchen Liu, Jiepeng Tang, Yuxin Chongqing Univ Sch Civil Engn Chongqing 400045 Peoples R China Southwest Jiaotong Univ Inst Smart City & Intelligent Transportat Chengdu 610000 Peoples R China

Large-span spatial structures are considered a significant indicator of advanced architectural and engineering capabilities, characterized by complex connections and mechanical mechanisms. The main challenge in structural optimization lies in balancing the need to optimize dimensions, weight, and cost, while maintaining the structure's performance and safety. Conventional methods often fail to effectively manage the intricate optimization demands of large-scale spatial structures, particularly given their complex geometries and constraints. To address these challenges, an intelligent algorithm is proposed for the optimization of complex large-span spatial structures, conducting the Brazzaville Stadium in Congo as a typical case to validate the rationality of the proposed approach. The results demonstrate that the material cost is reduced by approximately 12.84 %, while structural stiffness and component strength are in full compliance with design codes. The optimization efficiency of complex large-span spatial steel structures is significantly improved. Additionally, a quantitative seismic fragility assessment of the original and optimized structures was conducted to clarify the optimized structures' safety under severe earthquakes. The results demonstrate that Collapse Margin Ratio of the optimized structure decreased slightly from 6.264 to 5.960, with a reduction of 4.85 %. Under rare earthquakes, collapse risks of original and optimized structures are 0.110 % and 0.436 %, respectively, both well below the quantitative threshold of 'No collapse under rare earthquake' recommended by FEMA P695. Specifically, when the peak ground acceleration exceeds severer earthquakes, the optimized structure exhibits superior seismic performance over the original structure. The proposed optimization algorithm can provide a reference for the optimization of complex steel structures.

关键词： Large-span spatial structure intelligent optimization Full stress design Grey wolf optimization Seismic fragility analysis

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intelligent optimization methods of phase-modulation waveform

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Journal of Systems Engineering and Electronics 2022年第4期33卷 916-923页

作者： SUN Jianwei WANG Chao SHI Qingzhan REN Wenbo YAO Zekun YUAN Naichang College of Electronic Science and Technology National University of Defense TechnologyChangsha 410073China State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System National University of Defense TechnologyChangsha 410073China

With the continuous improvement of radar intelligence, it is difficult for traditional countermeasures to achieve ideal results. In order to deal with complex, changeable, and unknown threat signals in the complex electromagnetic environment, a waveform intelligent optimization model based on intelligent optimization algorithm is proposed. By virtue of the universality and fast running speed of the intelligent optimization algorithm, the model can optimize the parameters used to synthesize the countermeasure waveform according to different external signals, so as to improve the countermeasure *** algorithm(GA) and particle swarm optimization(PSO)are used to simulate the intelligent optimization of interruptedsampling and phase-modulation repeater waveform. The experimental results under different radar signal conditions show that the scheme is feasible. The performance comparison between the algorithms and some problems in the experimental results also provide a certain reference for the follow-up work.

关键词： waveform optimization intelligent optimization phase-modulation genetic algorithm(GA) particle swarm optimization(PSO)

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intelligent optimization of Availability and Communication Cost in Satellite-UAV Mobile Edge Caching System With Fault-Tolerant Codes

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IEEE TRANSACTIONS ON COGNITIVE COMMUNICATIONS AND NETWORKING 2020年第4期6卷 1230-1241页

作者： Gu, Shushi Wang, Ye Wang, Niannian Wu, Wen Harbin Inst Technol Shenzhen Sch Elect & Informat Engn Shenzhen 518055 Peoples R China Network Commun Res Ctr Peng Cheng Lab Shenzhen 518052 Peoples R China Univ Waterloo Dept Elect & Comp Engn Waterloo ON N2L 3G1 Canada

Mobile computing provides storage and computation resources of proximal devices to satisfy the real-time and low-energy communication demands of the Internet of Things (IoT). However, in the areas without terrestrial base station infrastructures, the IoT sensors have trouble implementing reliable and stable connections, which results in the difficulties of data gathering and data caching. In this paper, we consider a space-air-ground integrated mobile edge caching IoT system composed of satellite and unmanned aerial vehicles (UAVs), where LEO satellite broadcasts data, and UAVs collect the data from decentralized ground sensors. Since the sensors' low-power property leads data loss, fault-tolerant codes are employed for availability protection. We first derive the exact expressions of system availability and communication cost for data repair and collection. Then, to address the problems of the lower availability, we exploit an intelligent optimization to determine the erasure coding parameters. Lastly, we further optimize the system parameters, i.e., communication ranges and unit power costs of UAV and decentralized sensors, to minimize the total communication cost. Simulation results show that, compared to MDS codes and regenerating codes, adaptive minimum storage regenerating (AMSR) codes with optimized parameters can significantly reduce total communication cost and maintain availability of the system.

关键词： Satellite-UAV mobile edge caching intelligent optimization availability communication cost fault-tolerant codes

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intelligent optimization system of burden structure in sintering and blast furnace ironmaking process based on improved genetic algorithm

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IRONMAKING & STEELMAKING 2022年第10期49卷 1005-1010页

作者： Bo, Cui Wei, Chen Wang Bao-xiang Ying, Chen Wu Peng-fei Yan, Tong North China Univ Sci & Technol Coll Artificial Intelligence Tangshan Peoples R China North China Univ Sci & Technol Coll Met & Energy Tangshan 063210 Peoples R China High Qual Steel Continuous Casting Engn Technol R Tangshan 063000 Peoples R China New Tianjin Iron & Steel Grp Co Ltd Tianjin Peoples R China

Under the premise of ensuring the smooth production of the blast furnace, the quality and output of molten iron, minimizing the cost of hot metal and reducing the impact of harmful elements are the most difficult problems faced by iron and steel enterprises at present. The intelligent optimization system of burden structure in the whole process of sintering and blast furnace ironmaking is developed based on the principle of blast furnace ironmaking and material balance, improved genetic algorithm and penalty function. It includes four parts: raw fuel database, intelligent sintering optimization, blast furnace burden structure intelligent optimization and company cost accounting. The industrial application shows that the system can not only guarantee the output and quality of molten iron, but also effectively reduce the cost of molten iron in the process of optimizing the sintering and blast furnace production of the steel company.

关键词： Blast furnace sinter improved genetic algorithm penalty function intelligent optimization molten iron cos optimization of sintering burden furnace burden optimizationt

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intelligent optimization METHOD OF SCREW DRILL ASSEMBLY BASED ON BOREHOLE TRAJECTORY PREDICTION

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THERMAL SCIENCE 2024年第2A期28卷 1073-1078页

作者： Chen, Mingzhu Liu, Zihao Gao, Peng Palihati, Cordelia Song, Xianzhi Li, Zhen Zhu, Zhaopeng Xinjiang Oilfield Co Engn Technol Res Inst Xinjiang Peoples R China China Univ Petr Beijing Peoples R China

This study constructs an intelligent wellbore trajectory prediction and BHA optimization process, which ensures efficient optimization of the BHA on the premise of high wellbore trajectory prediction accuracy, the MAE of deviation and azimuth angles of the borehole trajectory model was 0.35 degrees and 0.55 degrees. The optimized BHA can effectively improve the deflection effect. It also has obvious advantages in calculation efficiency and can provide effective guidance and theoretical support for on-site BHA optimization.

关键词： Wellbore trajectory prediction BHA screw drill assembly intelligent optimization sensitivity analysis

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intelligent optimization of Matching Layers for Piezoelectric Ultrasonic Transducer

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IEEE SENSORS JOURNAL 2021年第12期21卷 13107-13115页

作者： Sun, Xinhao Man, Jiujing Chen, Dongdong Fei, Chunlong Li, Di Zhu, Yuanbo Zhao, Tianlong Feng, Wei Yang, Yintang Xidian Univ Sch Microelect Xian 710071 Peoples R China Xidian Univ Sch Microelect Xian 710071 Peoples R China Chinese Acad Sci Shenzhen Inst Adv Technol Shenzhen 518055 Peoples R China

The performance of piezoelectric ultrasonic transducer (PUT) is obviously affected by its matching layer. An intelligent optimization method for matching layer of PUT is proposed to fabricate PUT with high performance. The original data, including matching layer and performance parameters of PUT, is obtained by PiezoCAD software. Then the neural network models are established to mathematically characterize the effect of matching layer on the performance of PUT. The optimization criteria for PUT is constructed according to its performance requirements, such as center frequency (CF), bandwidth (BW) and pulse width (PW). In order to decrease the material cost, the thicknesses of matching layers are also considered in the optimization criteria. The modified particle swarm optimization algorithm is used to optimize the thicknesses of matching layers (Ag-epoxy and Parylene C). According to the designed performance, the optimized thicknesses of Ag-epoxy and Parylene C are about 54 mu m and 21 mu m, respectively. Based on the optimized thicknesses of matching layers, the simulated and experimental performances of PUT well agree with the designed ones. In addition, compared to the traditional quarter-wavelength theory, the proposed method can effectively decrease the materials cost. The -6dB BW and PW of PUT fabricated according to the optimized parameters are about 68.5% and 0.123 mu s, which are better than that fabricated according to the quarter-wavelength theory (about 50% and 0.147 mu s).

关键词： Piezoelectric ultrasonic transducer intelligent optimization matching layer particle swarm optimization algorithm

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intelligent optimization of stiffener unit cell via variational autoencoder-based feature extraction

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STRUCTURAL AND MULTIDISCIPLINARY optimization 2023年第1期66卷 1-24页

作者： Liu, Dachuan Hao, Peng Xu, Tengfei Zhu, Yingjie Liu, Xuanxiu Wang, Bo Li, Gang Dalian Univ Technol Dept Engn Mech State Key Lab Struct Anal Ind Equipment Key Lab Digital Twin Ind Equipment Dalian 116023 Liaoning Peoples R China China Acad Launch Vehicle Technol Beijing 100076 Peoples R China

Grid-stiffened structures are widely used in industrial equipment, where the layout of stiffener unit cells is critical in the structural performance. However, owing to the lack of design techniques, existing stiffener unit cell designs are often achieved only by comparative selection among several common cell configurations. In this study, a deep learning-based intelligent optimization framework for the stiffener unit cell of grid-stiffened panels was proposed. First, a database containing nearly 10,000 stiffener unit cells was generated by traversal while considering the manufacturability. Feature extraction was then performed on the generated database using a variational autoencoder and mapped to a 16-dimensional continuous latent design space according to geometric features. Subsequently, in this latent space, a Gaussian process model was established, and the maximum expected improvement criterion was utilized to drive the model update and optimization search, thus realizing data-driven optimization for the stiffener unit cell of grid-stiffened panels. In three typical numerical examples, compared with the best of the traditional stiffener unit cells, the obtained optimal designs were improved by 25.61%, 25.88%, and 10.66%, respectively, demonstrating the effectiveness of this method as an alternative stiffener unit cell design method. Furthermore, this study also indicates the significant potential of geometric feature extraction and further structural layout optimization via deep learning.

关键词： Grid-stiffened panel Stiffener unit cell Variational autoencoder intelligent optimization

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intelligent optimization METHOD FOR LARGE-SCALE SYSTEMS WITH FUZZY PARAMETERS

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COMPUTERS & INDUSTRIAL ENGINEERING 1994年第1-4期27卷 461-464页

作者： LI, LZ QIN, SY WAN, BW XIAN JIAOTONG UNIV INST SYST ENGNXIAN 710049PEOPLES R CHINA

In this paper, a proper description for large-scale steady-state systems with fuzzy parameters (LSSFP) is given and a novel intelligent optimization method(IOMFP) for LSSFP and several theorems about non-inferior solution and the convergence of IOMFP are proposed. The simulation results for some typical problems illustrate the effectiveness of IOMFP.

关键词： intelligent optimization LARGE-SCALE SYSTEMS FUZZY PARAMETERS

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