Parameter-Adaptive TVF-EMD Feature Extraction Method Based on Improved GOA.

In order to separate the sub-signals and extract the feature frequency in the signal accurately, we proposed a parameter-adaptive time-varying filtering empirical mode decomposition (TVF-EMD) feature extraction method based on the improved grasshopper optimization algorithm (IGOA). The method not only improved the local optimal problem of GOA, but could also determine the bandwidth threshold and B-spline order of TVF-EMD adaptively. Firstly, a nonlinear decreasing strategy was introduced in this paper to adjust the decreasing coefficient of GOA dynamically. Then, energy entropy mutual information (EEMI) was introduced to comprehensively consider the energy distribution of the modes and the dependence between the modes and the original signal, and the EEMI was used as the objective function. In addition, TVF-EMD was optimized by IGOA and the optimal parameters matching the input signal were obtained. Finally, the feature frequency of the signal was extracted by analyzing the sensitive mode with larger kurtosis. The optimization experiments of 23 sets of benchmark functions showed that IGOA not only enhanced the balance between exploration and development, but also improved the global and local search ability and stability of the algorithm. The analysis of the simulation signal and bearing signal shows that the parameter-adaptive TVF-EMD method can separate the modes with specific physical meanings accurately. Compared with ensemble empirical mode decomposition (EEMD), variational mode decomposition (VMD), TVF-EMD with fixed parameters and GOA-TVF-EMD, the decomposition performance of the proposed method is better. The proposed method not only improved the under-decomposition, over-decomposition and modal aliasing problems of TVF-EMD, but could also accurately separate the frequency components of the signal and extract the included feature information, so it has practical significance in mechanical fault diagnosis.

Development of three-wavelength CCD image pyrometer used for the temperature field measurements of continuous casting billets.

This paper develops an imaging based three-color pyrometer for the monitoring of temperature distribution in a continuous casting billet. A novel optical device, together with an embedded electronic system, is designed to sequentially collect a dark image and three thermal images with specified wavelengths on a same monochromatic charge-coupled-device (CCD). The three thermal images provide the basis for the determination of target temperature, while the dark image is used to online eliminate the dark noise of CCD with a differential method. This image pyrometer is not only independent of target emissivity but also overcomes the dissimilarity of measuring accuracy between the micro-sensors of CCD resulted from the non-uniformity of pixels' intensity response and the vignetting of optical system. Furthermore, a precise two-color temperature field measuring model on the CCD pyrometer is established, based on which a self-adaptive light-integration mechanism is presented. Compared with the traditional fixed light-integration method, the measuring range of the pyrometer is greatly extended and its sensitivity in low temperature segment is improved. The test results in a steel factory demonstrate that the pyrometer is capable of meeting the requirement of surface temperature measurements about casting billets. Reliability and accuracy of measurement results are also discussed herein.

Note: Vignetting calibration and temperature correction for casting billets.

A method for calibration of vignetting coefficient is proposed in this paper to solve the distortion of temperature measurement using a CCD-based pyrometer. On this basis, a hybrid temperature measurement system, which comprises of an array CCD camera with high resolution and a single spot colorimetric thermometer, is introduced to eliminate the influences of surface striped iron oxide scale, dust, and emissivity on temperature measurement for casting billets. Currently, the system has been successfully applied and verified in some continuous casting production lines. The vignetting estimation error of 0.052 and the maximum temperature measurement fluctuation of 5 °C were achieved in these measurements.

Evaluation and improvement in the accuracy of a charge-coupled-device-based pyrometer for temperature field measurements of continuous casting billets.

This paper presents a radiometric high-temperature field measurement model based on a charge-coupled-device (CCD). According to the model, an intelligent CCD pyrometer with a digital signal processor as the core is developed and its non-uniformity correction algorithm for reducing the differences in accuracy between individual pixel sensors is established. By means of self-adaptive adjustment for the light-integration time, the dynamic range of the CCD is extended and its accuracy in low-temperature range is improved. The non-uniformity correction algorithm effectively reduces the accuracy differences between different pixel sensors. The performance of the system is evaluated through a blackbody furnace and an integrating sphere, the results of which show that the dynamic range of 400 K is obtained and the accuracy in low temperature range is increased by 7 times compared with the traditional method based on the fixed light-integration time. In addition, the differences of accuracy between the on-axis pixel and the most peripheral pixels are decreased from 19.1 K to 2.8 K. Therefore, this CCD pyrometer ensures that the measuring results of all pixels tend to be equal-accuracy distribution across the entire measuring ranges. This pyrometric system has been successfully applied to the temperature field measurements in continuous casting billets.