查看更多>>摘要：? 2022 Elsevier LtdDuring the surface topography measurements, changes in the ambient temperature affect the elongation of both the tested object and the measuring device. This influence is insignificant and often negligible, when measuring a single two-dimensional profile, which lasts from a few to several minutes. However, during spatial measurements lasting over several hours, changes in the ambient temperature cause texture mapping errors. The research included assessment of impact of changes in the ambient temperature of a tactile profilometer on the results of surface topography measurements. In the paper methodology of surface topography measurements under controlled temperature conditions is described. Thermal influence of the environment on the errors in mapping of surface topography were also determined. Measurements were carried out in a specially designed climatic chamber. Results of multiple measurements of the same reference surface profile in constant and variable thermal conditions of the environment were presented. Such procedure allowed for the presentation of a two-dimensional transverse profile of a generated surface, varying as a function of temperature. Generated surfaces were parameterized and compared with each other. The results of the research allowed us to state that changes in the ambient temperature during the measurements of the surface topography affect the mapping errors of the measured structure. Temperature changes and measurement results are strongly linearly correlated with each other.
查看更多>>摘要：? 2021Aiming at the unreasonable frequency spectrum boundary division while empirical wavelet transform is applied to the fault diagnosis of rolling bearings, we propose to extract the amplitude spectrum of the transfer function from the frequency spectrum of the signal, then the minimum bandwidth is controlled to reasonably divide the frequency spectrum. In order to overcome the difficulty of selecting the optimal empirical mode (EM), Weighted Time-Frequency Energy Ratio (WTFER) which fuses the impulsiveness and sparsity of the fault signal in the time domain and envelope spectrum domain is proposed. Combining the improved frequency spectrum segmentation method with WTFER, we further propose a tower boundaries distribution diagram which is similar to Fast Kurtogram and named it Ewtfergram. Simulated and experimental results show that Ewtfergram is able to divide the frequency spectrum more reasonably, and WFTER is more robust than kurtosis, squared envelope spectrum (SES) entropy as well as weighted kurtosis (a weighted fusion of kurtosis and SES kurtosis).
查看更多>>摘要：? 2022 Elsevier LtdAt present, torque sensors are commonly used in industry to measure the idle torque of the Rotary Vector (RV) reducer. Since the additional torque from the measuring instrument itself is included in the torque sensor's measurement results, the torque sensor's reading value cannot be used as the actual no-load operation torque of the RV reducer. In this paper, the characteristics of the additional torque produced by the instrument and the no-load running characteristics of the RV reducer are analyzed. A method of using singular value decomposition (SVD) filtering and motor current signature analysis (MCSA) to test the no-load running torque is proposed to eliminate the influence of additional torque caused by the inevitable structure problems of the instrument. The measurement steps of no-load running torque using the proposed method are introduced, and the measurement experiment from low speed to high speed is carried out under no-load conditions. The experiment results show that the measurement error of the proposed method is less than 0.01Nm. It provides a reference for the measurement and evaluation of RV reducer torque performance in no-load operation.
查看更多>>摘要：? 2022 Elsevier LtdRolling bearing fault diagnosis based on deep learning has low accuracy under strong noise conditions and weak interpretation of the diagnosis results, which reduces the trust in its industrial applications. An Efficient Multi-Scale Convolutional Neural Network (EMSCNN) with anti-noise based on visualization methods of interpretability is proposed to solve the questions. First, an improved visualization method—Smooth Global Gradient Class Activation Mapping (SGG-CAM) is proposed to analyze the anti-noise ability of modules. Then, SGG-CAM is used to analyze the anti-noise mechanism of the Multi-Scale Dilate (MS-D) module and Residual Channel Attention (RCA) module from the perspective of interpretability. Meanwhile, the EMSCNN network based on the MS-D module and RCA module is established. Besides, Frequency Slice Wavelet Transform (FSWT) is used to generate time–frequency images for enriching the sample information. Experimental results on the bearing datasets show that the presented method is more accurate than other methods under strong noise.
查看更多>>摘要：? 2022A new digital image processing method based on color images was developed to analyze the coating quality of asphalt mixtures with moisture damage. The asphalt coating ratio can be measured automatically and objectively, improving the accuracy of boiling test (ASTM D3625). This method is based on RGB color model and the characteristic color pixels representing virgin aggregate are directly utilized to search the damaged areas. The developed color image processing was compared to the two existing digital imaging methods. The selection of threshold value was a subjective process in the binary image processing. The problem of the grayscale-based image processing was the lack of a reasonable method to obtain the representative image of virgin aggregate. Also, the light reflection on asphalt and the shadow between aggregates might lead to grave errors. In contrast, the proposed method could avoid those issues and realize the objective inspection of stripping in asphalt mixtures.
查看更多>>摘要：? 2022 Elsevier LtdSediment in the flowing water are normally considered an obstacle for hydropower plants (HPPs). The operation and management of HPPs have been a significant challenge in sediment-laden rivers. In mountainous regions like the Himalayas, frequent rainfalls and glacial and sub-glacial hydrological activities during the monsoon season transport high sediment in streams. In these regions, HPPs face high erosion of the hydraulic turbines due to sediment abrasion, resulting in efficiency losses, frequent maintenance and shut down of power plants. The present study covers a comprehensive review of the recently developed techniques for the continuous measurement of suspended sediment concentration (SSC), and particle size distribution (PSD). Further, the study discusses the measurement strategies of suspended sediment properties, sediment erosion in the hydraulic turbine, its efficiency loss, and financial implications, focusing mainly on the Himalayas. Finally, the research gaps of the study are discussed, and its future scope is recommended.
查看更多>>摘要：? 2022 Elsevier LtdPartial discharge (PD) is one of the main reasons of insulation deterioration in power equipment. How to efficiently and accurately recognize as well as assess the PD is an important guarantee for the stable operation of power equipment. Aiming at the problems of low accuracy of single information defect recognition and condition assessment results, the PD experiments about different typical defects of epoxy insulators are carried out in this paper. On this basis, different ultra high frequency (UHF) and ultrasonic feature information are extracted from time resolved partial discharge (TRPD) and phase resolved partial discharge (PRPD) analysis modes. Furthermore, an SDAE-LDDC multi-information fusion algorithm is built to recognize the defect types, with excellent recognition accuracy (over 94%). Based on the pulse current signal, the severity of PD was classified. The feature information that successfully assesses the severity of PD is selected by combining the maximum correlation and minimal redundancy criterion (m-RMR) with support vector machine (SVM). The performance of selected feature information is tested by fuzzy comprehensive evaluation algorithm, and the assessment results of different feature information are combined using the improved Dempster/Shafer (D-S) evidence theory, which improves the accuracy of condition assessment.
查看更多>>摘要：? 2022 Elsevier LtdArtificial intelligence method does not need artificial operation to extract fault characteristics, and greatly reduces the error of human operation. According to the principle of convolution neural network, a new method of optimal convolution neural network (CNN) model is proposed. Firstly, according to the principle of symmetrized dot pattern (SDP), the vibration signal is transformed into a symmetrical image in polar coordinates, which is also called snowflake image. Then, the SDP images are input into the input layer of the convolutional neural network, and the model can diagnose the fault type automatically. By adjusting the number of convolution layers and the size of convolution kernel, the convolution neural network model is determined according to a new index involving accuracy and time ratio. Finally, the test set is used to validate the robustness of the method under different bearing operating conditions.
查看更多>>摘要：? 2022 Elsevier LtdThis paper presents a procedure for integrating external stand-alone measurement with the Takaya APT Flying Probe machine (FP). The proposed approach can serve as a guide for merging other types of external test and measurement devices (T&M). The work context resides in a measurement inaccuracy situation reported at a production facility, by one of the most important worldwide automotive manufacturers. In the case of some printed circuit boards (PCBs), the FP machine generated erroneous results when measuring values for different in-circuit-mounted capacitors and inductors. The aim of our work was to resolve this situation. Thus, an integration solution which extends FP measurement capabilities was investigated and deployed. Developed applications operate as an extension of the FP software interface and can be included as a single step within the classical FP test program. Capacitors in the 1 nF to 100 nF ranges were tested. The solution proves viable for measurements on the 10 nF to 100 nF range, where the maximum relative error was 5.28%. Inductors with nominal values in the range 3.3 μH to 100 μH were evaluated with maximum relative errors of 10%. The presented solution proved to be well-suited for testing capacitors higher than 10 nF, while excellent results could be observed in the case of evaluated inductors. A statistical measurement accuracy evaluation demonstrates the appropriateness of such a solution.
查看更多>>摘要：? 2022 Elsevier LtdHigh-frequency ultraweak magnetic field measurements are essential. We demonstrate a scalar rubidium atomic magnetometer with effective measurement bandwidth of kilohertz and sensitivity of subpicotesla operating at a temperature of 365 K in an ambient field of 50 μT. The Faraday rotation signal is enhanced by a more simplified optical multipass cell compared to previous works. We developed an approach of continuous or burst sampling mode to maximize the frequency capability of the system, and propose a scheme of precise control pulse series as well as an analytical methods of data processing. Experimental results show that high contrast atomic spin projection noise and free induction decay signal are observed, and a sampling rate of 2 kHz along with the sensitivity of 0.7 pT/Hz1/2 between 20 and 1000 Hz have been achieved. It would help further research in physics and biomedical investigations that need high bandwidth magnetometers or sensor arrays in the earth's field.
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