Reliability life evaluation method of long-life electronic device under multiple stresses based on depth belief network
A technology of deep belief network and electronic devices, applied in biological neural network models, instruments, electrical digital data processing, etc., can solve problems such as shortening evaluation time, limited performance of single stress accelerated derivation model, long test time, etc., to reduce Cost of experimentation, avoiding the risk of getting stuck in data overfitting, the effect of reducing usage
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[0044] The following will combine figure 1 The method for evaluating the reliability of long-life electronic components of the present invention is further described in detail.
[0045] The method for evaluating the reliability of long-life electronic components of the present invention is based on certain assumptions, which include:
[0046] Hypothesis 1: The performance degradation process of the product is monotonic, that is, the performance degradation is irreversible.
[0047] Hypothesis 2: Under each accelerated stress, the failure mechanism and failure mode of the product remain unchanged.
[0048] Hypothesis 3: Accelerated degradation data have the same distribution form at different comprehensive stress levels, and the pseudo-failure life of products under different stress levels obtained through the data obeys the same distribution form.
[0049] Hypothesis 4: The residual life of the product only depends on the cumulative failure part and the comprehensive stress ...
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