Method for predicting failure rate of vehicle-mounted information terminal in entire life cycle

Abstract

The invention relates to a method for predicting the failure rate of a vehicle-mounted information terminal in an entire life cycle and belongs to the technical field of life prediction, in particular to prediction of failure rate of a vehicle-mounted information terminal in an entire life cycle. The method comprises the following steps of: 1) determining the entire life cycle of the vehicle-mounted information terminal; 2) determining the failure criterion of the vehicle-mounted information terminal; 3) constructing a comprehensive environmental stress acceleration factor model; 4) collecting comprehensive environmental stress high-acceleration life test data; 5) constructing a failure rate model; 6) constructing a vehicle-mounted information terminal performance degradation model in combination with the failure rate model; 7) constructing a life dynamic prediction model based on a grey theory; and 8) predicting the failure rate and the remaining life of an actual time node under the entire life cycle of the vehicle-mounted information terminal. The method has the benefits that through systematically applying the gradually-increased environmental stress and the working stress, the detection cycle is shortened to simulate the failure and expose the weak link in the design; and through analyzing the performance conditions in all work periods, the reliability indexes of products in all work periods are provided.

Description

technical field [0001] The invention discloses a method for predicting the failure rate of a vehicle-mounted information terminal within a full life cycle, which belongs to the technical field of life prediction, in particular to a method for predicting the failure rate of a vehicle-mounted information terminal within a full life cycle. Background technique [0002] Under normal working conditions, life test methods are often used to estimate various reliability characteristics of products. This method is not an appropriate method for products with a particularly long life. Because it takes a long time to test, and it is too late to complete the life test. New products are designed, and old products will be eliminated. Therefore, this method is incompatible with the rapid development of products. [0003] Accelerated life test is an effective way to quickly evaluate the life and reliability indicators of long-life and high-reliability products. The key to evaluating the l...

AI Technical Summary

Problems solved by technology

[0016] When predicting from given historical data (white system), since part of the information of the "grey system" is known, the result of short-term forecasting is relatively close to the actual data; However, when making long-term forecasts based on historical data, since the information of the "black system" is completely unknown and the number of forecast steps is too large, the internal evolution law between historical data and the "black system" becomes relatively blurred, resulting in The deviation between the predicted results and the actual data curve becomes larger

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