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Showing papers in "Measurement in 2019"


Journal ArticleDOI
TL;DR: The proposed identification model is based on Mask-RCNN, a deep neural network which incorporates global and local features for pixel-wise segmentation which achieves robustness through critical modifications of the training process and a novel post-processing step which merges bounding boxes from multiple models.

291 citations


Journal ArticleDOI
TL;DR: It is shown how feature representations learned with CNN on large-scale annotated gas turbine normal dataset can be efficiently transferred to fault diagnosis task with limited fault data.

152 citations


Journal ArticleDOI
TL;DR: In this article, a comprehensive state-of-the-art review of Fault Tolerant Control Systems (FTCS) is presented with the latest advances and applications with the aim of accommodating faults in the system components during operation and maintaining stability with little or acceptable degradation in the performance levels.

147 citations


Journal ArticleDOI
TL;DR: The article preprocesses the composite fault with ensemble empirical mode decomposition (EEMD) and then reconstructs the intrinsic mode function with the same time scale and proposes kurtosis spectral entropy as the objective function and uses the proposed method to search the complex fault pulse signals in strong noise environment.

146 citations


Journal ArticleDOI
TL;DR: In order to make the filtering results of Condition Monitoring (CM) data smoother and avoid misjudgment of status when the degradation speed is negative, the measurement error parameter is selected as the standard deviation of CM data in the degradation stage.

146 citations


Journal ArticleDOI
TL;DR: In this article, the effects of tool wear on surface integrity in cutting titanium and nickel alloys are reviewed, including surface topography (surface defects and surface roughness), microstructural alterations (plastic deformation, grain sizes, and white layer), and mechanical properties (microhardness and residual stress).

145 citations


Journal ArticleDOI
TL;DR: Experimental results indicate that CNN features displayed a better classification performance with SVM as simulation results validated output data with an average success of 95.62%.

144 citations


Journal ArticleDOI
TL;DR: Improvement of the quality of lung image and diagnosis of lung cancer by reducing misclassification and efficiency of the system is examined using MATLAB based simulation results.

143 citations


Journal ArticleDOI
TL;DR: This method is tested on 95 mammograms images collected and classified using SVM and it shows that the proposed method is effectively classify the abnormal classes of mammograms.

141 citations


Journal ArticleDOI
TL;DR: An inventive bio-inspired optimization based filtering system is considered for the MI denoising process, the filter named as Bilateral Filter (BF), and Gaussian and spatial weights are chosen by utilizing swarm based optimization that is Dragonfly (DF) and Modified Firefly (MFF) algorithm.

129 citations


Journal ArticleDOI
Meidi Sun1, Hui Wang1, Ping Liu1, Shoudao Huang1, Peng Fan1 
TL;DR: The results for data from the Case Western Reserve University Bearing Data Center show that the proposed SSDAE-TL algorithm is feasible and easy to implement for the fault diagnosis of bearings.

Journal ArticleDOI
TL;DR: A reliable fault diagnosis scheme based on acoustic spectral imaging (ASI) of acoustic emission (AE) signals as a precise health state is presented, which provides a robust classifier technique with high diagnostic accuracy.

Journal ArticleDOI
TL;DR: In this paper, the authors used the Taguchi method for determining number of experiment while variance analysis (ANOVA) deals with which parameter/s is/are effective on output to reduce tool wear and tool breakage.

Journal ArticleDOI
TL;DR: A new transfer learning method called improved joint distribution adaptation (IJDA) is proposed to align both the marginal and conditional distributions of datasets more comprehensively and is developed, which utilizes vibration signals and is mainly composed of three parts.

Journal ArticleDOI
TL;DR: A fault diagnosis method based on integration of Resonance-based Sparse Signal Decomposition (RSSD) and Wavelet Transform (WT) and quality factor optimization using genetic algorithm and sub-band reconstruction to solve the problem of early fault diagnosis of rolling bearing under strong background noise.

Journal ArticleDOI
TL;DR: An integrated leak detection method using acoustic signals based on wavelet transform and Support Vector Machine that achieves high accuracy, effective for leak detection and promising for the development of a real-time monitoring system.

Journal ArticleDOI
TL;DR: In this article, the second generation polyamidoamine dendrimer functionalized magnetic nanoparticles (Fe3O4@G2-PAD) were synthesized and applied for the measuring of Pb2+ and Cd2+ ions in environmental waters.

Journal ArticleDOI
TL;DR: In this paper, the fracture toughness during Mode I loading of concretes containing the 0, 20% and 30% addition of class F fly ash (FA), was investigated. And the results of the research show the usefulness of the Digital Image Correlation (DIC) method in experiments of that type.

Journal ArticleDOI
TL;DR: A method for RUL prediction which depends on a trend feature representing the overall time sequence of degradation, which achieves the smallest root mean square values in prediction of all RUL.

Journal ArticleDOI
TL;DR: An Internet of Things-based medical device for collecting patients’ heart details before and after heart disease is introduced and the HOBDBNN method and IoT-based analysis recognize heart disease with 99.03% accuracy with minimum time complexity.

Journal ArticleDOI
TL;DR: A sliding mode controller based on the exponential reaching law preliminarily and the stability is proved, and the boundedness and convergence of the presented control law are proved by Lyapunov method.

Journal ArticleDOI
TL;DR: The significance of the proposed method is that it is the first of its kind for WTB damage classification and detection for different classes of damage without using transfer learning but by training the model from the image dataset prepared by image augmentation methods and manual editing.

Journal ArticleDOI
TL;DR: A deep convolution neural network method based on Faster R-CNN method is proposed to locate the broken insulators and bird nests in the electric power line using the ResNet-101 network model.

Journal ArticleDOI
TL;DR: In this article, a new fiber optic reflective probe is designed for simultaneous detection of salinity, temperature, and pressure in seawater, which is the first time that these three parameters are measured by an integrated reflex optical fiber sensor.

Journal ArticleDOI
TL;DR: The filtering algorithms’ results revealed that UAV-generated data suitable for extraction of bare earth surface feature on the different type of a terrain reached the 93% true classification on flat surfaces from CSF filtering method.

Journal ArticleDOI
TL;DR: A deep convolutional neural network (DCNN) based data fusion method for health state identification that fuses the raw data from the horizontal and the vertical vibration signals and extracts features automatically and could obtain better identification results than the other methods.

Journal ArticleDOI
TL;DR: This paper developed a model based on a deep convolutional neural network (DCNN) to extract the deep features directly from X-ray images, achieving an accuracy of 97.2%, which is considerably higher than that obtained using the traditional feature extraction methods.

Journal ArticleDOI
TL;DR: A new BC detection approach based on two ensemble learning techniques: the confidence-weighted voting method and the boosting ensemble technique, which was able to improve the performance of the traditional machine learning algorithms applied to BC detection, reaching the accuracy of 100%.

Journal ArticleDOI
TL;DR: A new technique is introduced for denoised the vibration signals and recognizing the bearing faults based on the empirical wavelet transform (EWT) and the result of the simulated signal and different experimental datasets illustrate that the presented work is preferable for the empirical mode decomposition based denoising technique in the early fault detection.

Journal ArticleDOI
TL;DR: A crawling planning method based on big data Gaussian process classification that can give classification results and corresponding probabilities, which represents the feasibility of grasping points in the problem of grab point planning is proposed.