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Showing papers in "Measurement in 2021"


Journal ArticleDOI
TL;DR: A hybrid model using deep and classical machine learning for face mask detection will be presented, and the SVM classifier achieved 99.64 % testing accuracy in RMFD.

540 citations


Journal ArticleDOI
TL;DR: A new method is put forward that fuses multi-modal sensor signals, i.e. the data collected by an accelerometer and a microphone, to realize more accurate and robust bearing-fault diagnosis.

199 citations


Journal ArticleDOI
TL;DR: Fault diagnosis based on thermal images can find application for protecting of rotating machinery and engines through fault diagnosis method based on analysis of thermal images BCAoID.

166 citations


Journal ArticleDOI
Ling Xiang1, Penghe Wang1, Xin Yang1, Aijun Hu1, Hao Su1 
TL;DR: A new method is proposed for fault detection of wind turbine, in which the convolutional neural network cascades to the long and short term memory network (LSTM) based on attention mechanism, which verifies the effectiveness of the proposed method.

130 citations


Journal ArticleDOI
TL;DR: The SOH estimations and RUL prognostics of lithium-ion batteries are reviewed by analyzing the research status, and the respective methods are divided into specific groups and the advantages and limitations of the battery management system application are discussed.

124 citations


Journal ArticleDOI
TL;DR: The analysis results demonstrated that the proposed hybrid deep learning model can achieve higher detection accuracy than CNN and gcForest, which may be favorable to practical applications.

119 citations


Journal ArticleDOI
TL;DR: It has been concluded that infrared thermography can be used in a non-contact way to automatically identify the faults that help to detect early warnings, irrespective of speeds and hence ensures reduced system shutdowns causing by bearing failure.

116 citations


Journal ArticleDOI
TL;DR: This article highlights the recent advances being made in the development of materials for the fabrication of biosensors for healthcare and biomedical applications.

109 citations


Journal ArticleDOI
TL;DR: In this article, a fan-beam photon attenuation based system, including one X-ray tube and two sodium iodide crystal detectors, combined with group method of data handling (GMDH) neural network is proposed to recognize type of flow regime and predict gas-oil-water volume fractions of a three phase flow.

104 citations


Journal ArticleDOI
TL;DR: Three different types of liquid–gas two-phase flow regimes, namely annular, stratified, and homogenous were simulated in various gas volumetric percentages ranging from 5% to 90%.

98 citations


Journal ArticleDOI
TL;DR: Nowadays, DIC on smartphone must be further refined with controlled geometry and standard lighting sources to become robust and reliable analytical procedures.

Journal ArticleDOI
Cheng Han1, Xianguang Kong1, Gaige Chen1, Qibin Wang1, Rongbo Wang1 
TL;DR: In the proposed method, a convolutional neural network is employed to extract the degradation features and multiple-kernel maximum mean discrepancies are integrated into optimization objective to reduce distribution discrepancy.

Journal ArticleDOI
TL;DR: A model-free tracking controller for a cooperative mobile-manipulators to perform tasks individually and cooperatively and a nature-inspired metaheuristic algorithm inspired by the food searching nature of the beetles, ZNNBAS is presented.

Journal ArticleDOI
TL;DR: Monitoring of the cutting area with different type of sensors requires confirmation for composing sensor fusion to obtain longer tool life and high-quality product to enable more reliable, robust and consistent machining.

Journal ArticleDOI
TL;DR: The proposed coordinated VMD-TSMDE-VHHO-SVM approach to fault diagnosis for rolling bearings can achieve better diagnosis performance than other comparative ones.

Journal ArticleDOI
TL;DR: A convolutional neural network model is established to extract fault features from grey images and realize fault classification and a novel signal-to-image mapping (STIM) is proposed to convert the one-dimensional vibration signals into two-dimensional grey images, which greatly reduce the human involvement.

Journal ArticleDOI
TL;DR: A new deep transfer learning network based on convolutional auto-encoder (CAE-DTLN) to implement the mechanical fault diagnosis in target domain without labeled data to overcome the effect of noise.

Journal ArticleDOI
TL;DR: The working principles and mechanism of the fiber-optic sensors based on the Vernier effect are presented, and the research progress and applications of such sensors are summarized and discussed.

Journal ArticleDOI
TL;DR: This paper presents a novel decoupling attentional residual network for compound fault diagnosis that achieves the same diagnosis performance by utilizing only 150 labeled compound fault samples as using all 1200 labeled samples, which greatly reduces the labeling workload of domain experts.

Journal ArticleDOI
TL;DR: The proposed CNN-SVM system is applied in bearing fault diagnosis, which takes the time domain diagram of bearing vibration data as the system input and has the advantages of less time-consuming, high precision and strong generalization ability.

Journal ArticleDOI
TL;DR: A novel method based on recurrent neural networks (RNNs) is proposed to identify fault types in rotating machinery and exhibits the robustness against the noise.

Journal ArticleDOI
TL;DR: In this article, the optical and contactless DIC technique was used for the examination of fracture processes in concrete with fly ash under shear loading, and the results showed that unmodified concrete are characterised by greater brittleness, whereas composites made on the basis of the binary binder behave as quasi-plastic materials in the fracture process.

Journal ArticleDOI
TL;DR: An effort was made to monitor the flank wear using wavelet analysis by extracting the Hoelder’s exponent as a feature and using various machine learning algorithms to forecast the tool condition and the results revealed that HE along with wavelet coefficients performed better than statistical features.

Journal ArticleDOI
TL;DR: A novel tunnel defect inspection method based on the Mask R-CNN is proposed, and a detailed study of the PAFPN and the edge detection branch is performed, and the experiment results show their robustness and accuracy in tunnel defect detection and segmentation.

Journal ArticleDOI
TL;DR: A novel data augmentation method named variational autoencoding generative adversarial networks with deep regret analysis is proposed to improve the fault diagnosis ability and has better effectiveness and robustness than typical data synthesis based fault diagnosis methods.

Journal ArticleDOI
TL;DR: A hybrid attention improved residual network (HA-ResNet) based method is proposed to diagnose the fault of wind turbines gearbox by highlighting the essential frequency bands of wavelet coefficients and the fault features of convolution channels.

Journal ArticleDOI
TL;DR: In this paper, the static and dynamic theory of cables is summarized and the traditional and innovative monitoring methods of cable force are analyzed, especially the recent emerging intelligent methods are provided for the future development of cable-stayed bridges.

Journal ArticleDOI
TL;DR: An algorithm based on deep learning is proposed in this paper to realize the recognition of different types of rail profiles and realizes accurate positioning and fast tracking of various types of laser stripes.

Journal ArticleDOI
TL;DR: A novel Energy-Efficient Heterogeneous Fault Management scheme has been proposed to manage these heterogeneous faults in IWSN and the diagnosis accuracy rate is enhanced up to 17% as compared with existing techniques.

Journal ArticleDOI
TL;DR: A new deep convolution residual feature extractor is constructed to extract high-level features, which can avoid gradient problems such as gradient disappearance and gradient divergence during training DCDATL, thus improving the convergence and non-linear approximation ability of DCD ATL.