查看更多>>摘要：? 2022 Elsevier LtdFringe projection profilometry (FPP) has been widely applied to measure objects, but for measurement of the high-reflectivity surfaces is still a tricky problem. In this paper, a new high-dynamic-range (HDR) technique by using a transparent screen as an optical mask for the camera is proposed. Specially, a transparent screen is placed in front of the camera, and each camera pixel's intensity can be precisely controlled by adjusting its corresponding screen pixel's intensity. Experiments has verified the effectiveness of our method: the dynamic range of the 4-step phase-shift method is increased from 48.13 dB to 71.83 dB, and a fewer number of projection patterns compared with the other techniques. The significance of this study is that our method can be easily combined with the other HDR technologies to obtain a greater dynamic range for the structured light technique.
查看更多>>摘要：? 2022 Elsevier LtdThe vibration signal of faulty rolling bearing of rotating machine carries a large amount of information reflecting its fault categories. However, compound fault features are easily mixed together, and can cause missed diagnosis and misjudgment, which is still a challenging task in mechanical fault diagnosis. A compound fault detection method using wavelet scattering transform (WST) and an improved soft threshold denoising algorithm is proposed to extract compound faults in bearings. First, the wavelet scattering transform is used to calculate the original scattering coefficients from vibration signals. Second, the improved soft threshold denoising algorithm is applied to obtain the renewable scattering coefficients, which are further employed to reconstruct the denoising signals. Third, process the envelope spectrum analysis on the denoising signal to extract fault features. Finally, both the simulations and experiments in associate with comparison investigations proved that this method can effectively detect compound faults in bearings.
查看更多>>摘要：? 2022 Elsevier LtdExcellent active obstacle detection capability is critical to operate fully automatic trains safely and reliably. There are some problems exist in the traditional sensor-based obstacle detection approaches, such as low detection accuracy, sluggish detection speed and a limited number of obstacle types. In this work, a fast and accurate object detector termed improved R-CNN is proposed by introducing new up-sampling parallel structure and context extraction module (CEM) into the architecture of R-CNN. Furthermore, transfer learning is applied to inherit the COCO dataset's pre-training weight. The network is trained on track lines and test lines with nine types of obstacles. The data is evaluated and statistically cleansed, and the fine-tuning anchor improves the network's flexibility within the dataset. With the input size of 1330 px × 800 px, the test results show that the improved R-CNN model achieves an accuracy of 90.6% and a detection speed of 11 FPS. In comparison to other state-of-the-art detectors, the model has great performance in obstacle identification of rail track and achieves a good balance between detection speed and accuracy.
查看更多>>摘要：? 2022Measurement of light output from ultraviolet (UV) light-based devices is critical to understanding the capability of the device. Optical sensors such as radiometers and dosimeters can possess different angular responses and are sensitive to many parameters in the measurement set-up. This work has been designed to quantify the effect of multiple parameters on the measurements obtained from optical sensors to provide inputs for validating measured data for ultraviolet sources. Multiple light sources operating in the ultraviolet range have been measured and a comparison between different sensors is presented. The angular response has been evaluated for each detector and compared with an ideal cosine response. Two of the six sensors studied displayed a near cosine response. A change of angle of acceptance with wavelength was observed for the ThorLabs S120VC and ILT W Optic diffuser. Due to use of artificial heating, the effect of measured intensities on the sensor as a function of temperature was seen to be insignificant but provided an understanding of how temperature of the sensor can influence measured data. Finally, the effect of ambient light and the integration time on the measured data were investigated. The effect of ambient light proved to be significant, when not considered in measurement of low light signals sources while the effect of choosing an ideal integration time has been seen to impact the measurements obtained. A measured difference of 43% was observed between a saturated and unsaturated sensor.
查看更多>>摘要：? 2022 The AuthorsDue to the interference of various irrelevant information in the environment, the early bearing fault features are difficult to detect. To enhance the fault-associated feature extraction performance in the process of bearing fault diagnosis, a signal processing method named enhanced optimal gradient product filtering (EOGPF) is proposed. First, the filtering capabilities of eight morphological gradient operators are investigated and compared to excavate the optimal morphological operators. Then, a new optimal gradient product operator (OGPO) is developed to improve the extraction performance of bearing fault-induced transient impulse information in the vibration signal. Finally, a novel EOGPF method combining noise removal and feature extraction is proposed to diagnose bearing faults. The OGPO-based morphological filtering is applied to remove noise and extract fault-induced impulse features from the vibration signals. Moreover, a two-stage denoising strategy based on median filtering and autocorrelation is used to enhance the noise removal performance of OGPO-based morphological filtering when processing the signal with strong noise interference. The analysis results of simulation signal, bearing accelerated life test data and measured railway bearing data verify the EOGPF can effectively enhance the extraction performance of fault-associated features. The comparison results of the EOGPF with several existing methods show its superiority in bearing fault diagnosis.
查看更多>>摘要：? 2022 Elsevier LtdTo ensure the long-term safe and reliable operation of mechanical equipment, it is necessary to carry out fault diagnosis of key components in the mechanical system. A rotor fault diagnosis method based on non-fuzzy solution weighted BP-AdaBoost (NFSW-BP-AdaBoost) is proposed in this paper. First, the rotor vibration signal is transformed into a high-dimensional feature set. Then, the VC value is used to obtain the high-dimensional feature sequence. Finally, the NFSW-BP-AdaBoost method is used to diagnose the type and degree of rotor fault. The core of this article is to analyze the fuzzy solution of the combined binary classifier applied to multi-classification problems in decision-making, and put forward the non-fuzzy solution coefficient to weigh the conclusion of the combined multi-classifier, highlighting the sensitivity to the non-fuzzy solutions of each multi-classifier. The experimental analysis results show that the recognition rate of the classification method for fault types can reach more than 97%.
查看更多>>摘要：? 2022 Elsevier LtdFor lithium-ion batteries, accelerated degradation test (ADT) plays a pivotal role for their long cycle life and high reliability. In some applications, the degradation of batteries is affected by the electrical stresses. Hence, the extended Eyring model applied with the temperature coupling other non-thermal stress, is not appropriate. Motivated by this idea, a non-linear polynomial method with stress coupling analysis (NLP-SCA) model for double electrical variables is proposed as it can extend the application scenarios of current acceleration model. Meanwhile, the NLP-SCA is also developed with better goodness-of-fit compared with the models, by which the stress couplings are ignored. For the life estimation with normal condition, four evaluation criterions (root mean square error, R-Squared, sum of squares due to error, and the mean absolute error) calculated with the proposed model increase by 45.37%, 42.15%, 3.94% and 8.17% separately, compared to the general polynomial acceleration model and exponential acceleration model.
查看更多>>摘要：? 2022 Elsevier LtdThe Kaiser effect(KE) was investigated considering strain energy density factor theory in fracture mechanics and the formation mechanism of the independence of effect direction. The results were as follows: Felicity ratio (FR) increased with increasing rotation angle, indicating that the memory of the original rock stress was affected by the rotation angle. Thus, the directional independence of the KE was directly related to the rotation angle. In theoretical calculations, the directional independence of the KE was directly related to the relative value of critical stress. The change in the relative value of the critical stress increased the difficulty of cracking, affecting the accuracy of the KE point. Poisson's ratio considerably affected the FR value, and the in situ stress values of the KE method on various types of rock samples differed. The results of the study can provide insight into the KE mechanism and development of effective methods.
NSTL
Elsevier