Accelerated degradation test (ADT) is generally used to accelerate degradation processes in products to estimate their lifespan and to assess their reliability in a short period of time. How to perform the failure mechanism consistency test is crucial in the application of the ADT method. Existing failure mechanism consistency test methods assume that degradation rates among individual products are the same. However, these methods do not take degradation dispersions caused by manufacturing technologies into consideration. To address this issue, a failure mechanism consistency test method for ADT based on the activation energy invariant method and the likelihood ratio test is proposed. First, a degradation modeling method for ADT is introduced. Then, the logarithmic maximum likelihood function values of the degradation models are estimated based on the two‐step maximum likelihood estimation (MLE) method. Finally, the decision rule is proposed based on the likelihood ratio test. The method mentioned above is, then, used on the real degradation data of carbon‐film resistors and bullet O‐rings, and its effectiveness is verified. Furthermore, based on the failure mechanism change point in RTV5370 siloxane rubbers, the simulated degradation data are degenerated to compare the proposed method with the method not considering individual differences in different ADT programs and degradation dispersions.

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Accelerated degradation test (ADT) is an effective technique to quantitatively evaluate the life characteristics of high-reliability and long-life products. And the consistency of failure mechanism under different accelerated stress levels is the premise of ADT. In order to identify the consistency of failure mechanism as early as possible and improve the identification accuracy, an incipient consistency identification method of failure mechanism based on improved grey theory is proposed in this paper. Firstly, we reconstruct the background value through the calculation of the integral in the interval. Then the new information priority principle is introduced to improve the construction of initial values in the conventional grey theory. Subsequently, combined with the equal dimension model, the integrated scheme is employed to analyze the enhancement testing data of a resistor in a switching power supply to identify the mutation point of failure mechanism. Compared with the conventional GM (1,1) model, the proposed method has smaller residual, and another identification based on degradation model is also constructed to verify the feasibility and creditability of the proposed method.

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