IEEE Transactions on Instrumentation and Measurement最新文献_第5页

Dual-Level Polynomial Resampling Extracting Transform and Its Application to Bearing Fault Diagnosis at Variable Speeds 双级多项式重采样提取变换及其在变速轴承故障诊断中的应用

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2025-06-18 DOI: 10.1109/TIM.2025.3580825

Yubo Ma;Samson S. Yu;Rui Yuan;Hongyu Zhong;Huawei Wu;Hongan Wu

引用次数: 0

A Novel Underwater SINS/USBL Dual-Responder Integrated Navigation Algorithm Considering Motion Effects 一种考虑运动效应的水下SINS/USBL双响应器组合导航算法

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2025-06-18 DOI: 10.1109/TIM.2025.3580832

Shuaishuai Zhang;Tao Zhang;Shengxin Li;Liang Zhang;Yang Shi

{"title":"A Novel Underwater SINS/USBL Dual-Responder Integrated Navigation Algorithm Considering Motion Effects","authors":"Shuaishuai Zhang;Tao Zhang;Shengxin Li;Liang Zhang;Yang Shi","doi":"10.1109/TIM.2025.3580832","DOIUrl":"https://doi.org/10.1109/TIM.2025.3580832","url":null,"abstract":"In order to address the impact of underwater vehicle motion effects and common errors in ultrashort baseline (USBL) acoustic signals on positioning accuracy, this article proposes a USBL range correction (RC) model based on the strapdown inertial navigation system (SINS). The model retains high-precision characteristics for a short period. By utilizing the high-precision navigation information provided by the SINS during the USBL transmission and reception processes, this model corrects the distance errors caused by underwater vehicle motion effects. Based on this, a novel USBL tightly integrated navigation model (DT) is proposed, which uses the differential distance method with two transponders to compensate for common errors in USBL acoustic signals. In addition, to effectively reduce the impact of underwater outliers on the positioning accuracy of integrated navigation, a chi-square detection-assisted adaptive robust cubature Kalman filtering (ARCKF) algorithm is adopted to suppress outliers. Simulations and tests in the Yangtze River show that the proposed positioning model and algorithm achieve higher positioning accuracy compared to classical algorithms.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-13"},"PeriodicalIF":5.6,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144550759","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Pure Pulse Voltage-Based Method for Broadband Impedance Spectrum Measurement of Cables 基于纯脉冲电压的电缆宽带阻抗谱测量方法

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2025-06-18 DOI: 10.1109/TIM.2025.3580901

Yaqiang Deng;Bo Zhang

{"title":"A Pure Pulse Voltage-Based Method for Broadband Impedance Spectrum Measurement of Cables","authors":"Yaqiang Deng;Bo Zhang","doi":"10.1109/TIM.2025.3580901","DOIUrl":"https://doi.org/10.1109/TIM.2025.3580901","url":null,"abstract":"The application of broadband impedance spectrum (BIS) has become a high-performance method for localizing minor defects within cables. The primary focus of BIS research has been on improving algorithms for analyzing the spectrum, with less attention given to its acquisition. BIS is typically obtained using frequency-sweeping impedance analyzers (IAs) or vector network analyzers (VNAs), which are often costly. In contrast to frequency-sweeping acquisition methods, this article proposes a cost-effective, pulse voltage-based method to acquire the BIS of cables by relying exclusively on measuring time-domain pulse voltages, without measuring current, under two configurations: with the cable connected to the acquisition system and with it disconnected. To enhance its applicability in practical scenarios, two correction methods are proposed to mitigate the influence of both external extension cables and internal connection cables. The experimental results demonstrate that the proposed method reliably acquires BIS of cables, with a normalized root mean square error (NRMSE) of less than 3% compared with the results obtained by the impedance analyzer.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-8"},"PeriodicalIF":5.6,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144501037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

F2Fusion: Frequency Feature Fusion Network for Infrared and Visible Image via Contourlet Transform and Mamba-UNet F2Fusion：基于Contourlet变换和Mamba-UNet的红外与可见光图像频率特征融合网络

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2025-06-18 DOI: 10.1109/TIM.2025.3580829

Renhe Liu;Han Wang;Kai Hu;Shaochu Wang;Yu Liu

{"title":"F2Fusion: Frequency Feature Fusion Network for Infrared and Visible Image via Contourlet Transform and Mamba-UNet","authors":"Renhe Liu;Han Wang;Kai Hu;Shaochu Wang;Yu Liu","doi":"10.1109/TIM.2025.3580829","DOIUrl":"https://doi.org/10.1109/TIM.2025.3580829","url":null,"abstract":"To integrate complementary thermal and texture information from source infrared (IR) and visible (VIS) images into a comprehensive fused image, traditional multiscale transform algorithms, and deep neural networks have been extensively explored for IR and VIS image fusion (IVIF). However, existing methods often face difficulties combining the strengths of these two approaches, particularly when it comes to balancing the preservation of salient and texture information in challenging conditions such as low light, glare, and overexposure. This article proposes a novel frequency feature fusion network (F2Fusion) that exploits detailed space-frequency transformation through contourlet transform (CT) and multiscale long-range learning via the Mamba-UNet architecture. The Mamba block is embedded into the multiscale encoder and decoder structures to improve feature extraction and image reconstruction performance. The CT operation replaces the conventional pooling layer in the multiscale encoder, converting spatial features into high- and low-frequency subbands. We then introduce a dual-branch frequency feature fusion module to facilitate the fusion of cross-modality illumination information and fine details based on the distinct characteristics of different frequency subbands. In addition, we design a composite loss function, which includes both gradient and salient constraints, to guide the precise synthesis of salient targets and texture regions. Qualitative and quantitative comparisons across three benchmark datasets demonstrate that the proposed method outperforms recent state-of-the-art (SOTA) fusion techniques. Extended experimental results on downstream object detection tasks further validate the distinct advantages of the proposed architecture for fusion through precise frequency decomposition. The code is available at: <uri>https://github.com/lrh-1994/F2Fusion</uri>","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-17"},"PeriodicalIF":5.6,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144511130","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Strategy for State of Charge Estimation of Lithium-Ion Battery via an Adaptive Cubature Kalman Filter Based on Fractional-Order Model 基于分数阶模型的锂离子电池荷电状态估计策略

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2025-06-18 DOI: 10.1109/TIM.2025.3580841

Chuang Yang;Jianchang Liu;Zhe Gao;Dandan Song;Wanting Yang;Honghai Wang

{"title":"A Strategy for State of Charge Estimation of Lithium-Ion Battery via an Adaptive Cubature Kalman Filter Based on Fractional-Order Model","authors":"Chuang Yang;Jianchang Liu;Zhe Gao;Dandan Song;Wanting Yang;Honghai Wang","doi":"10.1109/TIM.2025.3580841","DOIUrl":"https://doi.org/10.1109/TIM.2025.3580841","url":null,"abstract":"Accurate state of charge (SOC) estimation of lithium-ion battery (LIB) is beneficial for battery management systems (BMS) to optimize the management of LIB, which has significant implications for the operation of electric vehicles. In this article, SOC estimation of LIB is achieved via an adaptive cubature Kalman filter (ACKF) based on the fractional-order model (FOM), where FOM consists of one parallel resistance-constant phase pairs and one Warburg unit (FO-RCW). The parameters and orders in FO-RCW model are identified via multiswarm cooperative particle swarm optimizer (MCPSO) based on the experimental data. The sigmoid function is employed to address potential boundary exceedance issue of SOC and order. The parameters and orders of the LIB model are operation-dependent, varying under different working conditions, therefore, the augmented vector method is adopted, integrating the identified model parameters and orders (as initial value), and SOC into a augmented state vector. Subsequently, an ACKF based on the FO-RCW model is proposed to achieve SOC estimation and online parameter and order estimation. Finally, the effectiveness and superiority of ACKF based on FO-RCW model are validated via experiments.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-11"},"PeriodicalIF":5.6,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144519291","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Robotic Intracorporeal Palpation With a Miniature Force-Sensing Probe for Minimally Invasive Surgery 用于微创手术的微型力传感探针机器人体内触诊

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2025-06-18 DOI: 10.1109/TIM.2025.3580873

Tangyou Liu;Xiaowen Zhang;Chao Zhang;Tiantian Wang;Shuang Song;Jiaole Wang;Liao Wu

{"title":"Robotic Intracorporeal Palpation With a Miniature Force-Sensing Probe for Minimally Invasive Surgery","authors":"Tangyou Liu;Xiaowen Zhang;Chao Zhang;Tiantian Wang;Shuang Song;Jiaole Wang;Liao Wu","doi":"10.1109/TIM.2025.3580873","DOIUrl":"https://doi.org/10.1109/TIM.2025.3580873","url":null,"abstract":"Intraoperative tissue palpation is crucial in surgical procedures to ensure operational safety and clinical outcomes. However, current robotic minimally invasive surgery (MIS) fundamentally decouples surgeons’ haptic perception from tissue interaction, posing substantial challenges for intracorporeal stiffness assessment. To address this limitation, we present an intracorporeal robotic palpation framework integrating our team’s recently developed vision-based multiaxis force sensing module. This miniature sensing module (<inline-formula> <tex-math>$phi 5$ </tex-math></inline-formula> mm) enables real-time tissue interaction force measurement during endoscopic operations. The proposed system employs teleoperated robotic control with remote center of motion (RCM) constraints to ensure safe instrument manipulation. It continuously correlates tissue deformation data with contact forces to reconstruct spatial stiffness distributions. Through iterative palpation maneuvers, the system dynamically updates the stiffness map of target anatomical regions. Comprehensive validation experiments were conducted using ex vivo chicken tissues under simulated MIS conditions, demonstrating: 1) the system’s capability to reconstruct heterogeneous tissue stiffness distributions by resolving contact forces and tissue deformation estimation and 2) effective implementation of the proposed framework to MIS considering RCM constraint. These results substantiate the clinical viability of the miniature force-sensing module for robotic intracorporeal palpation and establish a paradigm for enhancing haptic feedback in MIS applications.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-10"},"PeriodicalIF":5.6,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144502849","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multiview Contrastive Shapelet Learning: A Novel Semi-Supervised Approach for Explainable Machine Fault Diagnosis With Insufficient Annotated Data 多视图对比Shapelet学习：一种新的半监督方法，用于缺乏注释数据的可解释机器故障诊断

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2025-06-18 DOI: 10.1109/TIM.2025.3580850

Zhicheng Wang;Jc Ji;Yadong Xu;Sheng Li;Beibei Sun;Xiaolong Yang

{"title":"Multiview Contrastive Shapelet Learning: A Novel Semi-Supervised Approach for Explainable Machine Fault Diagnosis With Insufficient Annotated Data","authors":"Zhicheng Wang;Jc Ji;Yadong Xu;Sheng Li;Beibei Sun;Xiaolong Yang","doi":"10.1109/TIM.2025.3580850","DOIUrl":"https://doi.org/10.1109/TIM.2025.3580850","url":null,"abstract":"Rotating machinery plays a vital role in modern industry, whose failures may cause sudden damage to the equipment and affect the reliability and safety of the whole mechanical system. Although numerous deep learning-based methods have emerged in industrial fault diagnosis, most of them suffer from two key limitations. First, the majority of these techniques are predicated on the assumption of abundant data availability. In practical industrial settings, however, labeled samples are limited, rendering these methods ineffective under such constraints. Second, a significant limitation of these intelligent methods lies in their lack of interpretability, which hampers their applicability in high-reliability fault diagnosis systems. To address these problems, this article proposes a multiview contrastive shapelet learning (MCSL) framework for semi-supervised fault diagnosis of rotating machinery. MCSL leverages both a supervised contrastive learning (SCL) module and a self-supervised contrastive learning (SSCL) module to comprehensively exploit labeled and unlabeled vibration signals. In SCL, a shapelet learner block is used to extract key explainable patterns from labeled vibration signals. Subsequently, the SCL algorithm is employed to minimize the feature distance between the original sequence and the extracted shapelets. In SSCL, several data augmentation techniques are first applied. Then, the augmented data are fed into the shapelet learner block. Furthermore, an interactive convolutional block is employed to extract multiscale features. The parameters of the MCSL model are updated within an integrated training framework. Through experimental validation utilizing both public and self-collected datasets, it is evident that MCSL not only outperforms state-of-the-art methods in diagnostic accuracy, but also demonstrates enhanced interpretability, underscoring its significant potential for industrial applications.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-11"},"PeriodicalIF":5.6,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144502851","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Super-Resolution Reconstruction of Infrared Images With Edge-Enhanced and Variable Activation Network 基于边缘增强和可变激活网络的红外图像超分辨率重建

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2025-06-18 DOI: 10.1109/TIM.2025.3580862

Lei Hu;Jianwen Xie;Jiachen Ruan;Yunhong Li;Yongmei Zhang

{"title":"Super-Resolution Reconstruction of Infrared Images With Edge-Enhanced and Variable Activation Network","authors":"Lei Hu;Jianwen Xie;Jiachen Ruan;Yunhong Li;Yongmei Zhang","doi":"10.1109/TIM.2025.3580862","DOIUrl":"https://doi.org/10.1109/TIM.2025.3580862","url":null,"abstract":"Infrared images have less available information compared to visible images, and the applying of high-frequency details and edge information can directly influence the quality of super-resolution (SR) reconstruction of infrared images. However, most existing SR methods have a single activation mode for high-frequency features and over-dependently increase the network depth to improve performance. To address these problems, we design a variable GELU (VGELU), which introduces a learnable parameter a based on GELU to suppress low-frequency features and noise by adaptively changing the slope of GELU in high-frequency feature extraction. In addition, we propose an attention-enhanced CATS-RCF (ACR) network in the strong edge feature extraction module (SEFEM), which introduces coordinate attention based on CATS-RCF (CR) to enhance the edge weights of infrared low-resolution (LR) images and improve the effect of edge extraction. To fully fuse high-frequency features and edge information, we further design an edge feature fusion block (EFFB), which effectively fuses edge information from different dimensions. Our edge-enhanced and variable activation network (EVAN) is constructed by applying the proposed VGELU, SEFEM with EFFB. The comprehensive experiments demonstrate the superiority of our EVAN over other comparison methods.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-15"},"PeriodicalIF":5.6,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144502865","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Intelligent Measurement Method of Transmission Line Sag Based on Image and Laser Ranging Fusion 基于图像与激光测距融合的传输线垂度智能测量方法

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2025-06-18 DOI: 10.1109/TIM.2025.3580837

Qiangbao Ouyang;Yu Fang;Xintian Liu;Diqing Fan;Hao Yang;Xin Wu;Xingzhi Ren

{"title":"Intelligent Measurement Method of Transmission Line Sag Based on Image and Laser Ranging Fusion","authors":"Qiangbao Ouyang;Yu Fang;Xintian Liu;Diqing Fan;Hao Yang;Xin Wu;Xingzhi Ren","doi":"10.1109/TIM.2025.3580837","DOIUrl":"https://doi.org/10.1109/TIM.2025.3580837","url":null,"abstract":"Existing sag measurement systems are often hindered by complex workflows and heavy reliance on manual assistance. An intelligent sag measurement method, integrating image data and laser ranging technology, is proposed. Based on this method, an intelligent sag measurement system is developed to enable automatic coordinate collection and sag calculation. The method uses a laser rangefinder to measure distances on the transmission line, which is converted into 3-D coordinates using angular relationships from a spatial position model. Acatenary model is then applied to fit the data and calculate the sag value. In the system, a sag measurement algorithm is designed to automatically determine horizontal and pitch rotation parameters. Horizontal rotation angles are calculated by uniformly controlling rotation distances based on the number of measurement points. For pitch rotation, an AutoML-optimized BP neural network is constructed, using laser distances and image pixel differences as inputs. Model performance is evaluated using an absolute error threshold. The experimental results show that the proposed pitch angle prediction model achieves a coverage rate of 99.040% within the error tolerance range. The average mean absolute error (MAE) of the sag intelligent measurement system is 0.111 m, the average root mean square error (RMSE) is 0.140 m, and the average standard deviation is 0.129 m. The measurement time is improved by 24.390% compared to a total station.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-15"},"PeriodicalIF":5.6,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144502871","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Uncertainties of Data-Driven Models: Theory and Application to Condition Monitoring 数据驱动模型的不确定性：理论及其在状态监测中的应用

IF 5.6 2区工程技术

IEEE Transactions on Instrumentation and Measurement Pub Date : 2025-06-18 DOI: 10.1109/TIM.2025.3580883

Yun-Peng Zhu;Zepeng Liu;Zi-Qiang Lang;Hatim Laalej

{"title":"Uncertainties of Data-Driven Models: Theory and Application to Condition Monitoring","authors":"Yun-Peng Zhu;Zepeng Liu;Zi-Qiang Lang;Hatim Laalej","doi":"10.1109/TIM.2025.3580883","DOIUrl":"https://doi.org/10.1109/TIM.2025.3580883","url":null,"abstract":"Abnormal operational conditions often induce intrinsic uncertainties, making them valuable for health monitoring of the underlying system. However, assessing intrinsic uncertainties for online condition monitoring of manufacturing and process engineering, especially when various practical working loads are applied, has proven a challenging problem. The present study strives to address this problem by quantifying intrinsic uncertainties through system identification and nonlinear frequency analysis. First, the concerned system is represented by data-driven Nonlinear Auto-Regressive with eXogenous input (NARX) models accounting uncertainties in model coefficients. This is achieved by using a newly developed Bayesian linear regression-based orthogonal least squares (BLROLSs) algorithm from the system input and output measurements. The BLROLS algorithm is transparent and auto-tuned to ensure the NARX model has stable long-term predictions. After that, nonlinear frequency response functions (NOFRFs) features are derived from the NARX models to quantify system intrinsic uncertainties for condition monitoring. The concept of NOFRFs is an extension of the frequency response function (FRF) for linear systems to nonlinear cases, which have been proven as powerful physically interpretable indicators that are independent of working loads and sensitive to faulty conditions. Finally, an experimental study on the online monitoring of machining cutting tools was conducted, demonstrating the effectiveness of the proposed approach in addressing engineering problems.","PeriodicalId":13341,"journal":{"name":"IEEE Transactions on Instrumentation and Measurement","volume":"74 ","pages":"1-11"},"PeriodicalIF":5.6,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144502873","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0