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Sample expansion-based unbalanced data multi-dimensional parameter estimating method

A technology of unbalanced data and parameter estimation, applied in electrical digital data processing, special data processing applications, calculations, etc., can solve problems such as severe stress coupling, complex failure mechanism, and various failure modes

Active Publication Date: 2018-07-06
BEIHANG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, civil aircraft hydraulic pumps have many failure modes, complex failure mechanisms, severe stress coupling and variable stress load spectrum, so the traditional constant stress accelerated life test method is no longer applicable

Method used

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  • Sample expansion-based unbalanced data multi-dimensional parameter estimating method
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  • Sample expansion-based unbalanced data multi-dimensional parameter estimating method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0115] The effectiveness of the above method is verified by the accelerated life test example below.

[0116] (1) Accelerated life test sample

[0117] The first group of test samples is accelerated life test samples, and there are 2 pumps for accelerated life test:

[0118] Pump 1 is a new pump, according to the accelerated life test load spectrum shown in Table 1, it fails in 187.1 hours.

[0119] Table 1 Pump 1 accelerated life test load spectrum

[0120]

[0121] Pump 2 is a new pump, according to the accelerated life test load spectrum shown in Table 2, it will fail after 188.6 hours of acceleration.

[0122] Table 2 Pump 2 accelerated life test load spectrum

[0123]

[0124] (2) Reuse samples

[0125] In order to improve the accuracy of parameter estimation, three non-life test samples are introduced as multiplex samples:

[0126] Pump 3 runs for 425 hours according to the long-term test load spectrum shown in Table 3, and then accelerates to fail for 357.3 h...

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PUM

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Abstract

The invention discloses a sample expansion-based unbalanced data multi-dimensional parameter estimating method and is applied to the field of airborne equipment reliability. The sample expansion-basedunbalanced data multi-dimensional parameter estimating method combines multiplex samples and derivative samples to effectively expand the sample space; the multiplex samples have certain initial damage before accelerated lift test is implemented, so that data statistics should be implemented after accumulated damage caused by an initial load spectrum is converted; the load spectrum of the derivative samples is different from that of normal samples, so that data acquired under different load strength should not apply the unified data statistical weight but be provided with different weights according to different load strengths; by means of the methods of grouped resampling and load strength coefficient normal weighting, different types of samples can be comprehensively parameter-estimated, so that he problem of unbalanced data small sample parameter estimation can be solved.

Description

technical field [0001] The invention belongs to the field of aviation airborne equipment reliability, and in particular relates to a multi-dimensional parameter estimation method for unbalanced data based on sample expansion. Background technique [0002] Modern aircraft require ultra-high reliability and long life. As the core component of the aircraft hydraulic system, aviation hydraulic pumps have stricter requirements than ordinary hydraulic system hydraulic pumps. The hydraulic pump provides high-pressure oil of up to 21-35MPa for the aircraft hydraulic system, which is used to drive the flight control surface or retract the landing gear, etc. Its structure is complex, powerful, and its life and reliability requirements are getting higher and higher. Once the hydraulic pump of the aircraft fails, it will cause the aircraft hydraulic system to work abnormally, and cause the aircraft to crash, which will bring huge economic losses and adverse social impact. Therefore, mo...

Claims

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Application Information

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IPC IPC(8): G06F17/50
CPCG06F30/15G06F30/17G06F2119/04
Inventor 张超王少萍马仲海孙旭
Owner BEIHANG UNIV
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