Affiliation:
1. MIREA – Russian Technological University
Abstract
The article considers the method of vibration diagnostics of onboard electronic devices based on the analysis of resonant frequencies. An algorithm for diagnosing mechanical defects of the studied blocks and nodes is presented. The structure of the complex of software tools for diagnostics automation and the results of testing the proposed method are presented. The main goal of the research is to improve the accuracy of identification of design defects of on-Board electronic devices. The transition from the analysis of the frequency response to the resonant frequencies that characterize the physical and mechanical parameters of the structure is due to greater stability and lower measurement error of this characteristic. To achieve this goal, a diagnostic model of the method has been developed that allows taking into account the spread of parameters of the electronic tool, both for the serviceable state and for the state with a defect. To estimate the permissible deviations of resonant frequencies from the nominal values, statistical simulation was performed using the Monte Carlo method. It was also possible to increase the reliability of the results of the physical experiment by determining the best position of the accelerometer in terms of the response received. The article provides a structure and description of the algorithm for searching for it. The results of approbation of the considered method on the example of the printed node of the voltage divider of the control unit of the aircraft are presented. In CAD SolidWorks, the serviceable state of the test node was modeled, for which four resonant frequencies were determined, and the state with a defect in the form of a detachment of the attachment. Analysis of the results showed a shift of three values of resonant frequencies relative to the correct state. The conducted series of 10 tests revealed the defect in all 10 cases (with the permissible error of the research result). This indicates a high degree of reliability of the data obtained, the adequacy of the diagnostic model of the method and the correctness of the applied algorithms.
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