Multi-Fractal Weibull Adaptive Model for the Remaining Useful Life Prediction of Electric Vehicle Lithium Batteries

In this paper, an adaptive remaining useful life prediction model is proposed for electric vehicle lithium batteries. Capacity degradation of the electric car lithium batteries is modeled by the multi-fractal Weibull motion. The varying degree of long-range dependence and the 1/f characteristics in the frequency domain are also analyzed. The age and state-dependent degradation model is derived, with the associated adaptive drift and diffusion coefficients. The adaptive mechanism considers the quantitative relations between the drift and diffusion coefficients. The unit-to-unit variability is considered a random variable. To facilitate the application, the convergence of the RUL prediction model is proved. Replacement of the lithium battery in the electric car is recommended according to the remaining useful life prediction results. The effectiveness of the proposed model is shown in the case study.

Novel laser tracking measurement system based on the position sensitive detector

The rapid development of modern industrial technology has led to the increase of machinery precision. Laser tracking measurement systems represent a novel type of coordinate measurement method, which was developed on the basis of metrology. In this paper, we aim to define a single-station 3D coordinate rotating laser tracking measurement system based on the principle of the space coordinate method. In view of the current architecture and optical path of the system, we establish the ideal mathematical model of the system and derive the coordinate expression for arbitrary measured points in the measurement space. The output response of the photoelectric position detector to the rotating laser and the linearity of the position signal in the detection circuit have been detected via a concrete experiment. A laser tracking system was used to track the target mirror mounted on the coordinate measuring machine measuring spindle. It is shown that stable tracking is possible during the 3D movement of a cat's eye retroreflector if its velocity is 0.2 m/s and the distance to the moving object is 1-2 m. The corresponding velocity of the object must be 0.4 m/s. Our system provides a feasible implementation method for the tracking of the moving target space position.

Bendlet Transform Based Adaptive Denoising Method for Microsection Images

Magnetic resonance imaging (MRI) plays an important role in disease diagnosis. The noise that appears in MRI images is commonly governed by a Rician distribution. The bendlets system is a second-order shearlet transform with bent elements. Thus, the bendlets system is a powerful tool with which to represent images with curve contours, such as the brain MRI images, sparsely. By means of the characteristic of bendlets, an adaptive denoising method for microsection images with Rician noise is proposed. In this method, the curve contour and texture can be identified as low-frequency components, which is not the case with other methods, such as the wavelet, shearlet, and so on. It is well known that the Rician noise belongs to a high-frequency channel, so it can be easily removed without blurring the clarity of the contour. Compared with other algorithms, such as the shearlet transform, block matching 3D, bilateral filtering, and Wiener filtering, the values of Peak Signal to Noise Ratio (PSNR) and Structural Similarity Index Measure (SSIM) obtained by the proposed method are better than those of other methods.