Automatic interpretation method for engine testing data

Abstract

The invention provides an automatic interpretation method for engine testing data. The method comprises the following steps that the relevancy analysis is carried out on each engine performance parameter and several incoming flow pneumatic parameters, and major parameters for influencing the engine performance parameter fluctuation are determined; the major parameters are engine model input parameters, the testing data in the same batch is used for correcting an engine theoretical model, and a semi-solid model of the engine is obtained; during the engine testing data interpretation, the engine semi-solid model is used for calculating the engine performance parameters under different incoming flow work conditions in real time, and in addition, the engine performance parameters are used as the interpretation standard value for carrying out automatic interpretation. The method according to the embodiment of the invention has the advantages that the missile turbine engine testing data interpretation efficiency is improved, the testing data interpretation accuracy is improved, and the quality and the reliability of delivery products are ensured.

Description

technical field [0001] The invention relates to the technical field of missile turbine engines, in particular to an automatic interpretation method for engine test data. Background technique [0002] Before the delivery of missile turbine engine products, it is necessary to conduct a test run of the whole machine (simulating the actual flight speed). The performance of the engine and the quality of the product are evaluated by analyzing and interpreting the test data obtained during the test run. [0003] At present, the interpretation of the test data of the turbo engine for bombs is manual interpretation, that is, through the technical personnel's experience interpretation of each test data and each feature of the test data to evaluate the technical state of the engine, however, manual judgment has the following defects: 1. The interpretation efficiency is low. There are nearly a hundred monitoring parameters during the test run of the turbo engine used in bombs. The workl...

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Problems solved by technology

[0003] At present, the interpretation of the test data of the turbo engine for bombs is manual interpretation, that is, through the technical personnel's experience interpretation of each test data and each feature of the test data to evaluate the technical state of the engine, however, manual judgment has the following defects: 1. The interpretation efficiency is low. There are nearly a hundred monitoring parameters during the test run of the turbo engine used in bombs. The workload of manual interpretation is heavy and the interpretation efficiency is low. 2. The quality of the product is difficult to guarantee, which is greatly affected by uncertain factors such as the technical level of the personnel and the mental state of the personnel. Insufficient technical understanding and personnel negligence are likely to occur in the interpretation process, resulting in quality problems such as misjudgments and missed judgments, which seriously affect the quality of delivered products

However, there are the following defects: 1. The reliability of data interpretation is low. In order to prevent too many false alarms in the interpretation process, the threshold value range given is generally wide (generally covering all working conditions of the engine), and the wide range The threshold value cannot effectively identify the abnormal data with small-scale fluctuations, and the reliability of the interpretation results is low; 2. It is impossible to interpret the fluctuation parameters. During the test run of the turbo engine, the fluctuation of the parameters is simulated by the connected tube test bench. Normal parameter fluctuations affected by inlet total temperature and total pressure fluctuations, as well as abnormal parameter fluctuations caused by failure of a certain part of the engine system, because the fluctuation amplitudes of the two are similar, the original threshold interpretation cannot effectively distinguish between the two

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