Measurement

Papers
(The H4-Index of Measurement is 79. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2020-10-01 to 2024-10-01.)
ArticleCitations
A hybrid deep transfer learning model with machine learning methods for face mask detection in the era of the COVID-19 pandemic524
Bearing fault diagnosis based on vibro-acoustic data fusion and 1D-CNN network320
A review on state of health estimations and remaining useful life prognostics of lithium-ion batteries210
Fault detection of wind turbine based on SCADA data analysis using CNN and LSTM with attention mechanism206
Few-shot transfer learning for intelligent fault diagnosis of machine191
A hybrid deep-learning model for fault diagnosis of rolling bearings188
An optimized VMD method and its applications in bearing fault diagnosis181
Fault diagnosis of electric impact drills using thermal imaging181
Convolutional neural network based bearing fault diagnosis of rotating machine using thermal images176
Digital image colorimetry on smartphone for chemical analysis: A review175
Deep learning for prognostics and health management: State of the art, challenges, and opportunities172
Pneumonia detection in chest X-ray images using convolutional neural networks and transfer learning171
Recent developments in biosensors for healthcare and biomedical applications: A review168
Development of a YOLO-V3-based model for detecting defects on steel strip surface158
A review of the application of deep learning in intelligent fault diagnosis of rotating machinery153
Fault diagnosis of rotating machinery based on recurrent neural networks144
Fiber-optic sensors based on Vernier effect142
Transferable convolutional neural network based remaining useful life prediction of bearing under multiple failure behaviors130
Structural health monitoring methods of cables in cable-stayed bridge: A review129
Deep learning through LSTM classification and regression for transmission line fault detection, diagnosis and location in large-scale multi-machine power systems127
Deep learning-based prognostic approach for lithium-ion batteries with adaptive time-series prediction and on-line validation125
Deep learning and wavelet transform integrated approach for short-term solar PV power prediction123
Automatic defect detection and segmentation of tunnel surface using modified Mask R-CNN122
Combination of X-ray tube and GMDH neural network as a nondestructive and potential technique for measuring characteristics of gas-oil–water three phase flows121
A new deep transfer learning network based on convolutional auto-encoder for mechanical fault diagnosis120
Rolling bearing fault diagnosis with combined convolutional neural networks and support vector machine120
Transfer learning for remaining useful life prediction of multi-conditions bearings based on bidirectional-GRU network117
Automatic laser profile recognition and fast tracking for structured light measurement using deep learning and template matching115
An integrated method based on hybrid grey wolf optimizer improved variational mode decomposition and deep neural network for fault diagnosis of rolling bearing114
Predicting the compressive strength of concrete containing metakaolin with different properties using ANN112
A hybrid attention improved ResNet based fault diagnosis method of wind turbines gearbox111
Investigation of signal behaviors for sensor fusion with tool condition monitoring system in turning110
Intelligent monitoring and diagnostics using a novel integrated model based on deep learning and multi-sensor feature fusion109
Effective IoT-based deep learning platform for online fault diagnosis of power transformers against cyberattacks and data uncertainties108
Bearing fault diagnosis and prognosis using data fusion based feature extraction and feature selection108
Skin disease detection and segmentation using dynamic graph cut algorithm and classification through Naive Bayes classifier107
DCC-CenterNet: A rapid detection method for steel surface defects107
A new bearing fault diagnosis method based on signal-to-image mapping and convolutional neural network107
Coordinated approach fusing time-shift multiscale dispersion entropy and vibrational Harris hawks optimization-based SVM for fault diagnosis of rolling bearing107
Fault diagnosis for small samples based on attention mechanism106
Rolling bearing fault diagnosis using variational autoencoding generative adversarial networks with deep regret analysis105
Intelligent fault diagnosis of rolling bearings under imbalanced data conditions using attention-based deep learning method105
A BiGRU method for remaining useful life prediction of machinery104
Development of tool condition monitoring system in end milling process using wavelet features and Hoelder’s exponent with machine learning algorithms104
An image recognition method for the deformation area of open-pit rock slopes under variable rainfall102
Bearing fault diagnosis based on EMD and improved Chebyshev distance in SDP image101
Simulation of hydraulic transplanting robot control system based on fuzzy PID controller101
Split-core magnetoelectric current sensor and wireless current measurement application99
Autoencoder-based representation learning and its application in intelligent fault diagnosis: A review98
A novel deep convolution multi-adversarial domain adaptation model for rolling bearing fault diagnosis97
Optimization of VMD using kernel-based mutual information for the extraction of weak features to detect bearing defects97
Attention mechanism in intelligent fault diagnosis of machinery: A review of technique and application96
Fault feature extraction and diagnosis of rolling bearings based on wavelet thresholding denoising with CEEMDAN energy entropy and PSO-LSSVM95
Actual bearing compound fault diagnosis based on active learning and decoupling attentional residual network95
Remaining useful life prediction of roller bearings based on improved 1D-CNN and simple recurrent unit94
A novel denoising method for vibration signal of hob spindle based on EEMD and grey theory94
A CNN-SVM study based on selected deep features for grapevine leaves classification94
Control framework for cooperative robots in smart home using bio-inspired neural network93
Evaluation of fracture processes under shear with the use of DIC technique in fly ash concrete and accurate measurement of crack path lengths with the use of a new crack tip tracking method93
Long-term gear life prediction based on ordered neurons LSTM neural networks93
RDD-YOLO: A modified YOLO for detection of steel surface defects92
Applicability of time-domain feature extraction methods and artificial intelligence in two-phase flow meters based on gamma-ray absorption technique91
An adaptive data fusion strategy for fault diagnosis based on the convolutional neural network90
Interpretable filter based convolutional neural network (IF-CNN) for glucose prediction and classification using PD-SS algorithm89
Optimization and analysis of process parameters for flank wear, cutting forces and vibration in turning of AISI 5140: A comprehensive study86
Deep learning-based tool wear prediction and its application for machining process using multi-scale feature fusion and channel attention mechanism86
State-of-the-art review on advancements of data mining in structural health monitoring85
Recent advances and trends of predictive maintenance from data-driven machine prognostics perspective83
Investigation of microstructure of C-S-H and micro-mechanics of cement pastes under NH4NO3 dissolution by 29Si MAS NMR and microhardness82
Stress relaxation behaviour of marble under cyclic weak disturbance and confining pressures82
Rolling bearing fault diagnosis based on multi-channel convolution neural network and multi-scale clipping fusion data augmentation82
Predicting electrical power output of combined cycle power plants using a novel artificial neural network optimized by electrostatic discharge algorithm82
A convolutional neural network-based method for workpiece surface defect detection82
Streamlined bridge inspection system utilizing unmanned aerial vehicles (UAVs) and machine learning82
Tool wear mechanism and prediction in milling TC18 titanium alloy using deep learning81
Routing in wireless sensor networks using machine learning techniques: Challenges and opportunities81
Fault detection and diagnosis in electric motors using 1d convolutional neural networks with multi-channel vibration signals80
Improved generative adversarial network for vibration-based fault diagnosis with imbalanced data80
Geometrical deviation modeling and monitoring of 3D surface based on multi-output Gaussian process80
OORNet: A deep learning model for on-board condition monitoring and fault diagnosis of out-of-round wheels of high-speed trains79
Light neural network with fewer parameters based on CNN for fault diagnosis of rotating machinery79
Deep convolution domain-adversarial transfer learning for fault diagnosis of rolling bearings79
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