Search

Accelerated degradation test (ADT) is considered as a method for obtaining product degradation data in a short period of time, and the life and reliability of the product are inferred under the conditions of use.In order to ensure the effectiveness of ADT, guaranting that the failure mechanism of the product under each accelerated stress is consistent with the failure mechanism under normal stress is necessary. Therefore, it is necessary to carry out an accelerated degradation failure mechanism consistency discriminant test. At present, the determination of the test variables in the accelerated degradation failure mechanism consistency discriminant test is mainly based on experience, and lacks a set of experimental optimal methods with theoretical basis. In this paper, in order to solve the above problems, save sample capacity and reduce testing time, D-Optimality for step stress is applied to optimal design of accelerated degradation failure mechanism consistency discriminant test based on Wiener process.First, we apply Wiener process to describe an accelerated degradation failure mechanism consistency discriminant test. Then, we apply D-Optimality for step stress that by using the expenditure function and the decision variable function as restrictions, the sample capacity, the optimal total test time and the optimal time at each stress level are given. At last, a case study is used to illustrate the proposed method.

Accelerated degradation test (ADT) is an important mean to obtain products’ degradation data, perform life prediction and assess reliability. An effective ADT needs to ensure failure mechanism consistency of products between various accelerated stresses and normal stress. Thus, a new test method for failure mechanism consistency of accelerated degradation test based on wiener process is proposed in this paper. Frist, degradation modeling for products based on Wiener process is established, and the link between the drift parameter of the Wiener process and accelerated stresses is set up by using accelerated models, such as Arrhenius equation. The relationship among drift parameters under different accelerated stresses is deduced based on the hypothesis that failure mechanism of products under different stresses is consistent when corresponding failure activation energies are invariant. Then, test samples are constructed separately under different stresses and assumed to satisfy a normal distribution, and t statistic is used for these samples to test failure mechanisms consistency. Finally, the accelerated storage degradation data of a certain type of resistor are used as an example to calculate failure mechanism variation interval of this resistor, which verifies the effectiveness of the method proposed in this paper.

Substation equipment temperature is one of the important criteria to reflect its normal work in[1], this article through the new UHF-RFID sensor temperature measures substation equipment, the new passive wireless sensor through the work of two frequency bands to solve the energy supply. The results show that this method can accurately predict the temperature of the primary equipment of the substation, diagnose fault and monitor equipment in real time by using the neural network and the seven main factors that affect the temperature of the primary equipment of the substation.