Measurement Science and Technology最新文献_第9页

Measurement of Si Pixel Sensor Alignment for the ALICE ITS Detector 测量 ALICE ITS 探测器的硅像素传感器对齐情况

Measurement Science and Technology Pub Date : 2024-05-23 DOI: 10.1088/1361-6501/ad4fae

Ahmad Satya Wicaksana, Esa Prakasa, A. D. Mauro, Siswo Wardoyo

{"title":"Measurement of Si Pixel Sensor Alignment for the ALICE ITS Detector","authors":"Ahmad Satya Wicaksana, Esa Prakasa, A. D. Mauro, Siswo Wardoyo","doi":"10.1088/1361-6501/ad4fae","DOIUrl":"https://doi.org/10.1088/1361-6501/ad4fae","url":null,"abstract":"\u0000 The ALICE experiment is one of the four experiments at the Large Hadron Collider (LHC) designed to investigate the status of matter under very high energy densities produced during heavy-ion collisions. The ALICE Inner Tracking System (ITS) consists of seven concentric cylindrical layers of monolithic silicon pixel sensors known as ALICE Pixel Detector (ALPIDE). The sensors are used to reconstruct the paths of charged particles generated in the collisions. The sensor alignment of the detector must be adjusted to a high precision standard. The adjustment objective is to obtain a detector that can undertake high-resolution measurements. This paper introduces a method for measuring the reference markers utilized in sensor alignment determination. Markers engraved at the chip corners have been detected using the Hough transform, Canny edge detection, and template matching techniques. The distances between two markers are measured to determine the accuracy of the pixel sensor alignment before and after assembly. The proposed methods exhibit an accuracy exceeding 99% and demonstrate high speed analysis. The average processing times for detecting the circle and cross markers are 105.9 ms/image and 113.8 ms/image, respectively. The sensor alignment of the detector must be adjusted to a high precision standard. However, recent studies have shown deviations of up to 5um above the desired value in the measured sensor position. Such deviations do not represent a major issue, nevertheless it is important to measure them in order to speed-up and make more accurate the recursive track-based alignment procedure used to reconstruct the position of each pixel sensor in the tracking detector. The proposed method offers a promising solution to deliver precise and rapid measurements for a large number of examined objects.","PeriodicalId":510602,"journal":{"name":"Measurement Science and Technology","volume":"19 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141105261","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Research on bearing fault diagnosis based on novel MRSVD-CWT and improved CNN-LSTM 基于新型 MRSVD-CWT 和改进型 CNN-LSTM 的轴承故障诊断研究

Measurement Science and Technology Pub Date : 2024-05-23 DOI: 10.1088/1361-6501/ad4fb3

Yuan Guo, Jun Zhou, Zhenbiao Dong, Huan She, Weijia Xu

{"title":"Research on bearing fault diagnosis based on novel MRSVD-CWT and improved CNN-LSTM","authors":"Yuan Guo, Jun Zhou, Zhenbiao Dong, Huan She, Weijia Xu","doi":"10.1088/1361-6501/ad4fb3","DOIUrl":"https://doi.org/10.1088/1361-6501/ad4fb3","url":null,"abstract":"\u0000 As a critical component in mechanical equipment, rolling bearings play a vital role in industrial production. Effective bearing fault diagnosis provides a more reliable guarantee for the safe operation of the industrial output. Traditional data-driven bearing fault diagnosis methods often have problems such as insufficient fault feature extraction and poor model generalization capabilities, resulting in reduced diagnostic accuracy. To solve these problems and significantly improve the diagnosis accuracy, this paper proposes a novel fault diagnosis method based on multi-resolution singular value decomposition (MRSVD), continuous wavelet transform (CWT), improved convolutional neural network (CNN) enhanced by convolutional block attention module (CBAM), and long short-term memory (LSTM). Through MRSVD, the vibration signal is decomposed layer by layer into multiple denoised signals, thus signal noise can be eliminated to the greatest extent to gain the optimal denoised signals; then through CWT, the optimal denoised signals are converted into two-dimensional time-frequency images so that the local and global characteristic information can be fully captured. Finally, through improved CNN-LSTM, feature extraction is greatly enhanced, resulting in high accuracy of fault diagnosis. Lots of experiments are organized to test the performance, and the experimental results show that the proposed method on various datasets has better diagnosis accuracy and generalization ability under different working conditions than other methods.","PeriodicalId":510602,"journal":{"name":"Measurement Science and Technology","volume":"52 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141103206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Research on Bearing Remaining Useful Life Anti-noise Prediction Based on Fusion of Color-Grayscale Time-Frequency Features 基于颜色-灰度-时间-频率特性融合的轴承剩余使用寿命抗噪预测研究

Measurement Science and Technology Pub Date : 2024-05-23 DOI: 10.1088/1361-6501/ad4fb1

Wenchao Jia, Aimin An, Xianjun Du, Yaoke Shi, Bin Gong

{"title":"Research on Bearing Remaining Useful Life Anti-noise Prediction Based on Fusion of Color-Grayscale Time-Frequency Features","authors":"Wenchao Jia, Aimin An, Xianjun Du, Yaoke Shi, Bin Gong","doi":"10.1088/1361-6501/ad4fb1","DOIUrl":"https://doi.org/10.1088/1361-6501/ad4fb1","url":null,"abstract":"\u0000 In contemporary industrial processes, vibration signals collected from bearings often contain significant noise, challenging the efficacy of conventional predictive models in extracting critical degradation features and accurately predicting the remaining useful life (RUL) of bearings. Addressing these challenges, this paper introduces a novel method for predicting bearing RUL under noisy conditions, leveraging a dual-branch multi-scale convolutional attention network (DMCSA) integrated with a dense residual feature fusion network (DRF). Initially, the method applies continuous wavelet trans-form (CWT) to vibration signals to extract color time-frequency image data, followed by grayscale processing to construct a comprehensive color-grayscale time-frequency image dataset, thereby augmenting the model's input features. Enhanced channel and spatial attention mechanisms, combined with multi-scale convolutions, facilitate supe-rior feature extraction and selection. The model's resilience to noise is fortified by in-corporating noise into the training dataset. Subsequently, selected color-gray time-frequency features undergo fusion and relearning through the DRF framework at the model's backend. The crayfish optimization algorithm (COA) is deployed for the astute determination of the model's critical hyperparameters. The proposed DMCSA-DRF model is then applied to predict the health indicator (MSCA-DRF-HI) of the test dataset, culminating in the accurate prediction of the bearings' RUL. Validation experiments demonstrate that our method surpasses comparative models in prediction accuracy un-der diverse noise interferences, signifying a substantial advancement in predictive performance.","PeriodicalId":510602,"journal":{"name":"Measurement Science and Technology","volume":"53 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141103184","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An Integrated High Precision Absolute Angular Displacement Sensor 集成式高精度绝对角位移传感器

Measurement Science and Technology Pub Date : 2024-05-23 DOI: 10.1088/1361-6501/ad4fb5

Bingnan Zhan, Changliang Wu, Xiaokang Liu, Pei Huang, Peiyu Yu

{"title":"An Integrated High Precision Absolute Angular Displacement Sensor","authors":"Bingnan Zhan, Changliang Wu, Xiaokang Liu, Pei Huang, Peiyu Yu","doi":"10.1088/1361-6501/ad4fb5","DOIUrl":"https://doi.org/10.1088/1361-6501/ad4fb5","url":null,"abstract":"\u0000 This paper proposed a high precision absolute angular displacement time grating sensor, and was assembled into an integrated encoder. This absolute angle sensor contains two incremental sensors, namely, N1 measurement period fine measurement component and N2 measurement period coarse measurement component, N1 and N2 are mutually prime, and N1 > N2. The induction electrodes of the fine measurement component adopt differential design to minimize the effects of external electromagnetic interference and common mode interference between different sensing units so as to achieve high precision displacement measurement, the phase difference between two incremental sensor is used for absolute positioning. The reflecting ring design simplifies the structure of the encoder and facilitates sensor integration. The induction output signals of different components are cross connected through leads to the reflecting ring far away from the measurement component to the first harmonic error during the measurement period. The reading heads adopt a round, uniformly distributed design scheme, and the average effect of the whole circumference closed ring sampling scheme is beneficial for improving measurement accuracy and eliminating harmonic errors. A sensor prototype with a diameter of 83mm was manufactured and assembled into an integrated encoder. Experimental results show that the sensor achieve a precision of 12\" over a full 360° measurement range and a resolution of 0.5\", and it can realize absolute positioning.","PeriodicalId":510602,"journal":{"name":"Measurement Science and Technology","volume":"25 23","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141104416","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

CAC-YOLOv8: Real-Time Bearing Defect Detection based on channel attenuation and expanded receptive field strategy CAC-YOLOv8：基于信道衰减和扩展感受野策略的实时轴承缺陷检测

Measurement Science and Technology Pub Date : 2024-05-23 DOI: 10.1088/1361-6501/ad4fb6

Bushi Liu, Yue Zhao, Bolun Chen, Cuiying Yu, Kailu Chang

{"title":"CAC-YOLOv8: Real-Time Bearing Defect Detection based on channel attenuation and expanded receptive field strategy","authors":"Bushi Liu, Yue Zhao, Bolun Chen, Cuiying Yu, Kailu Chang","doi":"10.1088/1361-6501/ad4fb6","DOIUrl":"https://doi.org/10.1088/1361-6501/ad4fb6","url":null,"abstract":"\u0000 Bearing defect detection plays a crucial role in the intelligent production of chemical transmission equipment, where timely identification and handling of defective bearings are essential. However, in practical large-scale industrial production, product surface defects are often complex, diverse, and exhibit significant variations in appearance, posing severe challenges to the discriminative ability and detection efficiency of bearing defect detection algorithms. This paper proposes a real-time bearing surface defect detection algorithm, CAC-YOLOv8, which designs the Channel Attenuation Network (CAN) and Compound Pooling Pyramid Spatial Pyramid Pooling Fast (CPPSPPF) structure. Specifically, the model introduces the Channel Attenuation Network to achieve parallel feature extraction, deep feature processing, and feature fusion under different channel numbers, capturing critical features related to bearing defects and thereby improving computational efficiency. Subsequently, based on the concept of overlapped receptive fields, a CPPSPPF structure is constructed, utilizing multiple iterations of max-pooling operations with smaller pooling kernel sizes to prevent information loss while expanding the receptive field, thereby strengthening the capturing ability of features at different scales. The experimental results indicate that the proposed CAC-YOLOv8 bearing surface defect detection algorithm, compared to the YOLOv8 model, achieved a 0.3% improvement in mAP@0.5, reduced model size by 14.4%, and enhanced model inference speed by 33.3%. This enables the CAC-YOLOv8 model to significantly improve the real-time performance of bearing defect detection while maintaining high-precision detection. The performance in practical industrial detection demonstrates that the proposed approach has achieved outstanding results in both speed and accuracy.","PeriodicalId":510602,"journal":{"name":"Measurement Science and Technology","volume":"59 39","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141102807","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Iterative feature mode decomposition: A novel adaptive denoising method for mechanical fault diagnosis 迭代特征模式分解：用于机械故障诊断的新型自适应去噪方法

Measurement Science and Technology Pub Date : 2024-05-23 DOI: 10.1088/1361-6501/ad4fb2

Xiaolong Ruan, Rui Yuan, Zhang Dang, Yong Lv, Xiaolong Jing

{"title":"Iterative feature mode decomposition: A novel adaptive denoising method for mechanical fault diagnosis","authors":"Xiaolong Ruan, Rui Yuan, Zhang Dang, Yong Lv, Xiaolong Jing","doi":"10.1088/1361-6501/ad4fb2","DOIUrl":"https://doi.org/10.1088/1361-6501/ad4fb2","url":null,"abstract":"\u0000 Remaining useful life prediction of rolling bearings highly relies on feature extraction of signals. The use of denoising algorithms helps to better eliminate noise and extract features, thereby constructing health indicators to predict remaining useful life. This paper proposes a novel adaptive denoising method based on iterative feature mode decomposition ( FMD) toI accurately and efficiently extract fault features. The feature mode decomposition (FMD) employs correlation kurtosis (CK) as the objective function for iterative filter bank updates, enabling rapid identification of fault features. To achieve IFMD, the sparrow search algorithm combines sine-cosine algorithm and cauchy variation (SCSSA) to optimize two key parameters in FMD. During the continuous iteration process of the SCSSA algorithm, filter length and number of modes were determined. IFMD does not require empirical setting of initial parameters. During iterative process, the signal is accurately decomposed and the noise is eliminated. Compared with other optimization algorithms, SCSSA has obvious advantages in iterative rate and global optimization. The envelope spectrum feature energy ratio (ES-FER) is used to select decomposed modes, and the mode with the largest ES-FER is chosen as the optimal mode. Bearing fault diagnosis is realized by envelope spectrum analysis of the optimal mode. The numerical simulations and experimental verifications both validate the effectiveness and superiority of the proposed IFMD in mechanical fault diagnosis.","PeriodicalId":510602,"journal":{"name":"Measurement Science and Technology","volume":"8 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141105548","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Considerations on measurement of bidirectional transmittance distribution function of thick samples over a wide range of viewing zenith angles 在宽视角范围内测量厚样品双向透射率分布函数的考虑因素

Measurement Science and Technology Pub Date : 2024-05-23 DOI: 10.1088/1361-6501/ad4faf

Robin Erik Aschan, F. Manoocheri, E. Ikonen

{"title":"Considerations on measurement of bidirectional transmittance distribution function of thick samples over a wide range of viewing zenith angles","authors":"Robin Erik Aschan, F. Manoocheri, E. Ikonen","doi":"10.1088/1361-6501/ad4faf","DOIUrl":"https://doi.org/10.1088/1361-6501/ad4faf","url":null,"abstract":"\u0000 We delve into theoretical and experimental considerations for determining the spectral bidirectional transmittance distribution function (BTDF) of thick samples across a broad viewing zenith angle range. Nominally, BTDF is defined as the ratio of transmitted radiance to incident irradiance measured from the same plane. However, when employing thick samples for BTDF measurements, the viewing plane of the transmitted beam may shift from the front to the rear surface of the sample, altering the measurement geometry compared to using the sample front surface as the reference plane. Consequently, the viewing zenith angle from the sample rear surface increases relative to the sample front surface, and the sample-to-detector-aperture distance decreases by an amount corresponding to the sample thickness. We introduce a method for determining the BTDF of thick samples, considering the transformation of practical measurement results to a scenario where the measurements are conducted at a very large distance from the sample. To validate the method, we utilize a BTDF facility equipped with two instruments that significantly differ in their sample-to-detector-aperture distances. We evaluate the impact of a 2 mm sample thickness on the BTDF by assessing the ratio of transmitted and incident radiant fluxes as a function of viewing zenith angle relative to the sample rear surface. The evaluation is conducted in the wavelength range from 550 nm to 1450 nm in 300 nm steps, and in the viewing zenith angle range from -70° to 70° in 5° steps. Measurements are performed in-plane at an incident zenith angle of 0°. It is concluded that consistent determination of BTDF of a thick sample is possible by converting the experimental parameters of the real measurements at relatively short distances from the sample to correspond to those that would be obtained from measurements at very large distances from the sample.","PeriodicalId":510602,"journal":{"name":"Measurement Science and Technology","volume":"52 30","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141103052","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Versatile Simplistic Correction of T-Higrow Sensors for Improved Soil Moisture Measurement Accuracy 多功能简易修正 T 型生长传感器，提高土壤水分测量精度

Measurement Science and Technology Pub Date : 2024-05-23 DOI: 10.1088/1361-6501/ad4fb7

Q. Abdelal, Muhammad Rasool Al-Kilani

{"title":"Versatile Simplistic Correction of T-Higrow Sensors for Improved Soil Moisture Measurement Accuracy","authors":"Q. Abdelal, Muhammad Rasool Al-Kilani","doi":"10.1088/1361-6501/ad4fb7","DOIUrl":"https://doi.org/10.1088/1361-6501/ad4fb7","url":null,"abstract":"\u0000 The use of soil moisture sensors for irrigation can help reduce water and energy consumption and risks of groundwater contamination, which are essential aspects for pursuing sustainable development goals. However, increased adoption of this technology is limited by calibration requirements, technical complexities, and sensor costs. In this work, a simplified method for reducing the measurement error of a recently released low-cost soil sensor (T-Higrow) is presented. The method only requires measurements of a dry sample from the target soil, which are inputted into a simple correction formula to reduce the measurement error at higher moisture levels. The requirements of the proposed method are simple enough for most labs or extension services. This method was compared to the commonly used linear, polynomial, and logarithmic regression models based on repeated bench-scale experiments within 0-35% moisture range in silt and sandy loam soils and in silica sand. Uncorrected sensor readings correlated well with soil moisture (r: 0.94-0.98), but with significant overestimation (25-60% error). The simplified correction method showed comparable error reduction to regression models across all soil types. All methods reduced error down to 2-10% (0.02-0.1 cm3/cm3) and maintained high correlations (r >0.94), except for logarithmic regression which reduced correlation by around 3%. Variability amongst sensor measurements was generally low (Standard Deviation: 0.01-0.03) particularly at moisture ranges below 20%, this was also the case for sensor-to-sensor variability (Standard Deviation: 0.01-0.03). Sensor evaluation and calibration works are needed to increase the accessibility to this technology for improved water and energy conservation.","PeriodicalId":510602,"journal":{"name":"Measurement Science and Technology","volume":"45 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141103501","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An adaptive frequency-based C/N0-constrained multipath extraction and mitigation method for GNSS pseudorange measurements 用于全球导航卫星系统伪距测量的基于频率的自适应 C/N0 约束多径提取和减缓方法

Measurement Science and Technology Pub Date : 2024-05-23 DOI: 10.1088/1361-6501/ad4fb8

Ruofan Liu, Wanqing Li, Xuewei Huang, Jiangbo Song, ZHiqiang Dai, Xiangwei Zhu

{"title":"An adaptive frequency-based C/N0-constrained multipath extraction and mitigation method for GNSS pseudorange measurements","authors":"Ruofan Liu, Wanqing Li, Xuewei Huang, Jiangbo Song, ZHiqiang Dai, Xiangwei Zhu","doi":"10.1088/1361-6501/ad4fb8","DOIUrl":"https://doi.org/10.1088/1361-6501/ad4fb8","url":null,"abstract":"\u0000 The multipath effect poses an inevitable challenge for Global Navigation Satellite System (GNSS) receivers, particularly pronounced in smart devices, which are nevertheless the most common means through which the general public accesses GNSS positioning. So we propose a novel adaptive method for extracting multipath errors, which fully exploits the multipath frequency characteristics, multipath repeatability, and the correlation between multipath errors and carrier to- -noise ratio (C/N0). This approach aims to enhance the susceptibility of smart devices to multipath influences. Specifically, this method uses the code minus carrier (CMC) method to calculate the noisy multipath error,multipath to constrain the frequency range,exploits the correlation between C/N0 andemploys the ensemble empirical modedecomposition (EEMD) method to decompose the error signal, and utilizes the Hilbert–Huangtransform (HHT) method to obtain the frequency information of the signal component.multipath Inrepeatability, the proposed method can effectively improve the correlation ofmultipath signals by up to 0.79. By applying the extraction method, the positioning performance of smart devices can be improved by 13.9%. Therefore, the proposed method extracts multipath error more accurately and is highly usable in low-cost devices and real-time applications.","PeriodicalId":510602,"journal":{"name":"Measurement Science and Technology","volume":"16 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141105395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Prediction model of bearing fault remaining useful life based on weighted variable loss degradation characteristics 基于加权可变损耗退化特征的轴承故障剩余使用寿命预测模型

Measurement Science and Technology Pub Date : 2024-05-22 DOI: 10.1088/1361-6501/ad4f00

Tianyi Yu, Shunming Li, Jiantao Lu

{"title":"Prediction model of bearing fault remaining useful life based on weighted variable loss degradation characteristics","authors":"Tianyi Yu, Shunming Li, Jiantao Lu","doi":"10.1088/1361-6501/ad4f00","DOIUrl":"https://doi.org/10.1088/1361-6501/ad4f00","url":null,"abstract":"\u0000 In the prediction of bearing fault remaining useful life (RUL), the identification and feature extraction of early bearing faults are very important. In order to improve the accuracy of early fault RUL prediction, a bearing fault RUL prediction model based on weighted variable loss degradation characteristics is proposed. The model is composed of a stack denoising autoencoder (SDAE) module guided by variable loss, a signal-to-noise feature adaptive weighting module and a Long-short Term Memory (LSTM) degradation characteristics extraction and regression output module. Firstly, this model improves the ability of SDAE model to extract weak fault features by ascending dimension learning and variable loss function. Then, an adaptive weighting matrix is generated according to the test signal to modulate the weight vector of SDAE. Finally, the hidden layer features of SDAE were input into LSTM model to extract the bearing state degradation features and realize the RUL prediction of bearing faults. The experimental results show that the proposed model can accurately predict the RUL of the test data in the early fault stage and the fault development stage. The proposed model can give early fault warning to the bearing state.","PeriodicalId":510602,"journal":{"name":"Measurement Science and Technology","volume":"51 24","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141111141","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0