Nonlinear Doubly Wiener Constant-Stress Accelerated Degradation Model Based on Uncertainties and Acceleration Factor Constant Principle

Although Wiener process models with the consideration of uncertainties, which are nonlinearity, random effects, and measurement errors, have been developed for lifetime prediction in the accelerated degradation test (ADT), they fail to describe the real degradation process because these models assume that the drift parameter correlates with the applied stress, while the diffusion parameter is constant. This paper put forward a nonlinear doubly Wiener constant-stress accelerated degradation model, where both diffusion and drift parameters were compatible with the applied stress according to the acceleration factor constant principle. When degradation data were available, we obtained the unknown parameters by applying a maximum likelihood estimation (MLE) algorithm in the constant-stress ADT (CSADT) model taking uncertainties into account. In addition, the proposed model’s effectiveness was validated through an illustrative example, and an application to the traveling wave tube (TWT) was carried out to demonstrate the superiority of our model in practical applications.

Estimation of the Lifespan Distribution of Gold Nanoparticles Stabilized with Lipoic Acid by Accelerated Degradation Tests and Wiener Process

Accelerated degradation tests (ADT) are widely used in the manufacturing industry to obtain information on the reliability of components and materials, through degrading the lifespan of the product by applying an acceleration factor which causes damage to the material. The main objective is to obtain fast information which is modeled to estimate the characteristics of the material life under normal conditions of use and to save time and expenses. The purpose of this work is to estimate the lifespan distribution of gold nanoparticles stabilized with lipoic acid (GNPs@LA) through accelerated degradation tests applying sodium chloride (NaCl) as an acceleration factor. For this, the synthesis of GNPs@LA was carried out, a constant stress ADT (CSADT) was applied, and the non-linear Wiener process was proposed with random effects, error measures and different covariability for the adjustment of the degradation signals. The information obtained with the test and analysis allows us to obtain the life distribution in GNPs@LA, the results make possible to determine the guaranteed time for a possible commercialization and successful application based on the stability of the material. In addition, for the evaluation and selection of the model, the Akaike and Bootstraping criteria were used.

Post mortem validation of DSI compressed sensing with optical imaging

Compressed sensing (CS) has been used to enhance the feasibility of diffusion spectrum imaging (DSI) by reducing the required acquisition time. CS applied to DSI (CS-DSI) attempts to reconstruct diffusion probability density functions (PDFs) from significantly undersampled q-space data. Dictionary-based CS-DSI using L2-regularized algorithms is an intriguing approach that has demonstrated high fidelity reconstructions, fast computation times and inter-subject generalizability when tested on in vivo data. CS-DSI reconstruction fidelity is typically evaluated using the fully sampled data as ground truth. However, it is difficult to gauge how great an error with respect to the fully sampled PDF we can tolerate, without knowing whether that error also translates to substantial loss of accuracy with respect to the true fiber orientations. Here, we obtain direct measurements of axonal orientations in ex vivo human brain tissue at microscopic resolution with polarization-sensitive optical coherence tomography (PSOCT). We employ dictionary-based CS reconstruction methods to DSI data from the same samples, acquired at high max b-value (40000 s/mm2) and with high spatial resolution. We compare the diffusion orientation estimates from both CS and fully sampled DSI to the ground-truth orientations from PSOCT. This allows us to investigate the conditions under which CS reconstruction preserves the accuracy of diffusion orientation estimates with respect to PSOCT. We find that, for a CS acceleration factor of R=3, CS-DSI preserves the accuracy of the fully sampled DSI data. That acceleration is sufficient to make the acquisition time of DSI comparable to that of state-of-the-art single- or multi-shell acquisitions. We also show that, as the acceleration factor increases further, different CS reconstruction methods degrade in different ways. Finally, we find that the signal-to-noise (SNR) of the training data used to construct the dictionary can have an impact on the accuracy of the CS-DSI, but that there is substantial robustness to loss of SNR in the test data.

Evaluating the Reliability Testing Acceleration Factor Based on VLSI Chip Infrared Image Analysis

A new approach for evaluating the acceleration factor of forced reliability tests of very large scale integrated circuits (VLSI) is presented. The approach is based on subjecting the VLSI chip to an infrared image analysis. Currently, the VLSI reliability testing acceleration factor is evaluated based on the Arrhenius law, according to which this factor depends on the chip temperature. The chip temperature, in turn, is represented by the sum of the chip package temperature and the product of the maximum dissipated power and the chip-to-package thermal resistance. The drawback of the existing method is that the calculation is carried out for only a single chip temperature value that was obtained analytically. But the VLSI is a complex system, and it is not correct to judge about the testing acceleration factor proceeding from a single chip temperature value. It is proposed to calculate the VLSI reliability testing acceleration factor based on the temperatures at many points on the VLSI chip surface. This will make it possible to take into account the test sequence influence on the temperature distribution over the chip surface, thereby helping select the test sequences so that to obtain the maximal and uniform chip heating. Owing to the proposed method, it becomes possible to evaluate the testing acceleration factor more accurately and also to potentially increase it by choosing the test sequence. A more accurate evaluation of the acceleration factor allows the reliability tests reliability to be improved. The proposed method for evaluating the acceleration factor was validated experimentally. The workplace is described, the calculations of the reliability testing acceleration factors using two approaches are carried out, and their comparison is given.

An Improved Inverse-Time Over-Current Protection Method for a Microgrid with Optimized Acceleration and Coordination

This paper presents an improved inverse-time over-current protection method based on the compound fault acceleration factor and the beetle antennae search (BAS) optimization method for a microgrid. The proposed method can not only significantly increase the operation speed of the inverse-time over-current protection but also improve the protection coordination by considering the possible influential factors in terms of microgrid operation modes, distributed generation (DG) integration status, fault types, and positions, which are marked as the most challenging problems for over-current protection of a microgrid. In this paper, a new Time Dial Setting (TDS) of inverse-time protection is developed by applying a compound fault acceleration factor, which can notably accelerate the speed of protection by using low-voltage and short-circuit impedance during the fault. In order to improve the protection coordination, the BAS algorithm is then used to optimize the protection parameters of the pick-up current, TDS, and the inverse time curve shape coefficient. Finally, case studies and various evaluations based on DIgSILENT/Power Factory are carried out to illustrate the effectiveness of the proposed method.

Optimal Robot Motion for Accelerated Life Testing of a 6-DoF Industrial Robot

In order to verify the reliability of drive components for industrial robots, component-level life tests must be accompanied by a system-level life test using actual robots in which predefined robot motions are repeated throughout the test. To properly verify the durability of drive components through a system-level life test, it is important to design test modes so that the required test time is the same for all joint drive components of the robot, and it is necessary to design test modes with a high acceleration factor so as to shorten the required test time as much as possible. To solve this problem, the present research proposes a method for designing robot motions that makes the accelerated life test time for all the drive components of the robot equal. In particular, we solve a dynamic based motion optimization problem for an industrial 6-DoF (degrees-of-freedom) robot that minimizes the AM-GM (arithmetic mean to geometric mean) ratio of the acceleration factors of each joint. The results show that C2-continuous test modes with the same acceleration factor, which is inversely proportional to the cycle time of the robot motion, can be derived.

Acceleration Factors and Life Predictions

Acceleration factors (AF) are key to designing an effective accelerated life test (ALT). They represent the ratio of the time in field to the time in test for a particular event to occur (typically a failure event related to a specific failure mechanism). Time to failure for a device generally correlates with the amount of stress applied (the higher the stress, the quicker the device will fail), and failure models exist to mathematically define that correlation for various failure mechanisms. This allows for use of a higher stress in test than in the field, thereby providing an acceleration factor that shortens the time in test to demonstrate a failure-free time period. ALT can take the form of qualitative or quantitative testing. The latter is used to determine the life characteristics of the device with some reliability and confidence level. Usage rate acceleration and higher stress acceleration can be used. It is important to consider the design limits of the device based on its specification and material properties, and limit the stress levels in test so as not to induce failure mechanisms that the device would not otherwise have experienced in the field. ALT results are used to make life predictions for the device tested. With no failures, the test results demonstrate the required reliability and confidence level metrics for the failure mechanism of interest. With several failures, a reliability software tool can be used with the appropriate analysis method, rank method, and confidence bounds method chosen in order to extrapolate to an expected life in test. The equivalent field life is based on multiplying the expected life in test by the AF. If the field stress and/or test stress are not constant, there are multiple acceleration factors to utilize. As a result, an equivalent acceleration factor needs to be calculated and used as the AF when predicting equivalent field life.