CN112834161B - Wind tunnel measurement data processing method based on feature extraction - Google Patents
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- 238000012360 testing method Methods 0.000 claims abstract description 47
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- 238000012935 Averaging Methods 0.000 claims abstract description 12
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Abstract
The invention discloses a wind tunnel measurement data processing method based on feature extraction, which relates to the technical field of wind tunnel measurement data processing, and is characterized in that: the method specifically comprises the following steps: s1, defining pressure data of different measuring points of an engine as a function P (x, t); s2, taking wind tunnel spray pipe data as a reference, and extracting characteristics of measurement data by adopting a filtering technology; and S3, data processing, namely performing time shifting, averaging, dimensionless and error analysis processing on the data of the engine measuring points according to the step S2. According to the invention, the time characteristics of the measured data function are extracted by establishing the measured data function conforming to the real physical process of the wind tunnel engine test, the data can be accurately and efficiently processed based on the extracted characteristics, and the errors of the test data obtained by processing can be reduced while the processing efficiency and convenience are improved by performing time shifting, averaging, dimensionless and error analysis processing on the data.
Description
Technical Field
The invention relates to the technical field of wind tunnel measurement data processing, in particular to a wind tunnel measurement data processing method based on feature extraction.
Background
The scramjet engine is used as a propulsion power device, and can economically and reliably realize hypersonic speed flying targets. Currently, under the high Mach number flight condition above Ma8, the main equipment of the scramjet ground test is a wind tunnel. The device can simulate real flight conditions and generate test air flow with high enthalpy, but is limited by the working principle of the device, and the effective time of the test air flow driven by shock waves is only in the order of milliseconds. In such a short time, how to quickly and accurately extract real and effective measurement data from massive raw data obtained by measuring the sensor so as to evaluate the combustion characteristics and the propulsion performance of the engine is an important technical problem to be solved in the field of wind tunnel engine test.
At present, data of measuring points at different positions of an engine are generally simply selected for averaging at the same time in a certain period, physical processes and time delay of airflow flowing through the measuring points are not considered, data stabilization time caused by arrangement of sensors at the measuring points are not considered, and therefore larger errors exist in test data processed by the method, and real engine working characteristics cannot be reflected. In order to reduce errors as much as possible and improve processing efficiency and convenience, the invention aims to provide a wind tunnel measurement data processing method based on feature extraction so as to solve the problems.
Disclosure of Invention
According to the aerodynamic principle of the wind tunnel, under the Lagrange coordinate system, test data (pressure, heat flow, temperature and the like) are established as a binary function of measuring point positions and measuring moments, a real gas flow physical process in an engine test is described by the function, a filtering technology is applied to extract time characteristics of the function, and then data time shifting, averaging, dimensionless and error analysis are carried out based on the extracted characteristics, so that high accuracy and high efficiency processing of mass data can be realized.
The technical aim of the invention is realized by the following technical scheme: the wind tunnel measurement data processing method based on feature extraction specifically comprises the following steps:
s1, defining a data function, and defining pressure data of different measuring points of an engine as a function P (x, t) under a Lagrange coordinate system, wherein x represents the measuring point positions, and if the number of the measuring points is 100, the value range of x is as follows: [1,2 … ] and t represents measurement time, if the measurement time is 1 second, and the measurement frequency is 1MHz, the value range of t is as follows: [1,2, … 106];
s2, extracting data features based on a filtering technology, taking wind tunnel spray pipe data as a reference, extracting features of measurement data by adopting the filtering technology, and then further processing engine measuring point data;
s3, data processing, namely processing the data of the engine measuring points according to the step S2, specifically comprising the following steps:
1) The time shift processing is respectively carried out on the data of each measuring point of the engine, and the calculation formula of the time shift length of each measuring point of the engine is as follows: Δt (X) =t (X, B) -T (0, B), wherein T (0, B) represents a test start time of the wind tunnel nozzle position measurement point, and T (X, B) represents a test start time of the engine measurement point;
2) The measured value of the engine measuring point is subjected to dimensionless treatment by adopting the measured value of the wind tunnel jet pipe, and the calculation formula of the dimensionless treatment is as follows:
3) The pressure data in the effective test time is subjected to averaging treatment, and the calculation formula of the averaging treatment is as follows:
4) The maximum measured value and the minimum measured value of each measuring point of the engine in the effective test time are adopted to calculate an error band, and the calculation formula of the error band is as follows:
according to the processing of the engine measuring point data in the steps 1) to 4), the pressure value of each measuring point of the engine is expressed as:
further, in the process of extracting the features of the measurement data in step S2, the position of the wind tunnel nozzle is defined as a number 0 measurement point, and the data features of the number 0 measurement point are 5 time points as follows: t (0, A) represents the measurement start time, P (0, A) represents the nozzle pressure at the measurement start time, T (0, B) represents the test start time, P (0, B) represents the nozzle pressure at the test start time, T (0, C) represents the nozzle pressure at which the test air flow reaches the stabilization time, P (0, C) represents the nozzle pressure at which the test air flow reaches the stabilization time, T (0, D) represents the test effective time end time, P (0, D) represents the nozzle pressure at the test effective time end time, T (0, E) represents the measurement end time, and P (0, E) represents the nozzle pressure at the measurement end time.
In summary, the invention has the following beneficial effects: according to the invention, the time characteristics of the measured data function are extracted by establishing the measured data function conforming to the real physical process of the wind tunnel engine test, the data can be accurately and efficiently processed based on the extracted characteristics, and the errors of the test data obtained by processing can be reduced while the processing efficiency and convenience are improved by performing time shifting, averaging, dimensionless and error analysis processing on the data.
Drawings
FIG. 1 is a flow chart of an embodiment of the present invention;
FIG. 2 is a schematic illustration of a wind tunnel engine test;
FIG. 3 is a schematic view of feature extraction of wind tunnel nozzle measurement data based on filtering technology in an embodiment of the invention.
Detailed Description
The invention is described in further detail below with reference to fig. 1-3.
Examples: the wind tunnel measurement data processing method based on feature extraction, as shown in fig. 1, specifically comprises the following steps:
s1, defining a data function, and defining pressure data of different measuring points of an engine as a function P (x, t) under a Lagrange coordinate system, wherein x represents the measuring point positions, and if the number of the measuring points is 100, the value range of x is as follows: [1,2 … ] and t represents measurement time, if the measurement time is 1 second, and the measurement frequency is 1MHz, the value range of t is as follows: [1,2, … ] 106.
S2, extracting data features based on a filtering technology, taking wind tunnel spray pipe data as a reference, extracting features of measurement data by adopting the filtering technology, and then further processing engine measuring point data. In this step, according to the working principle of the wind tunnel, the wind tunnel test airflow can be regarded as a control body integrally flowing into the engine from the wind tunnel jet pipe downstream, the measured data of the jet pipe and the engine have the same time characteristics, and the characteristic extraction schematic diagram of the measured data of the wind tunnel jet pipe based on the filtering technology is shown in fig. 2.
S3, data processing, namely processing the data of the engine measuring points according to the step S2, specifically comprising the following steps:
1) The time shift processing is respectively carried out on the data of each measuring point of the engine, and the calculation formula of the time shift length of each measuring point of the engine is as follows: Δt (X) =t (X, B) -T (0, B), where T (0, B) represents the test start time of the wind tunnel nozzle position measurement point, and T (X, B) represents the test start time of the engine measurement point. In this embodiment, the effective time of the wind tunnel is only in the millisecond level, the test airflow has typical transient operating characteristics, and the airflow parameters measured by the engine measuring points and the measured values of the wind tunnel nozzle have specific time delay, so as to accurately grasp the time correlation, and thus time shift processing is performed on the data of each measuring point of the engine.
2) In order to eliminate errors caused by test airflow parameters among different train numbers, the measured values of the wind tunnel spray pipes are adopted to carry out dimensionless treatment on the measured values of the engine measuring points, and the calculation formula of the dimensionless treatment is as follows:
3) In order to eliminate the influence of combustion oscillation on engine performance evaluation, pressure data in effective test time is subjected to averaging treatment, and a calculation formula of the averaging treatment is as follows:
4) To characterize the data error, the error band is calculated by adopting the maximum measured value and the minimum measured value of each measuring point of the engine in the effective test time, and the calculation formula of the error band is as follows:
according to the processing of the engine measuring point data in the steps 1) to 4), the pressure value of each measuring point of the engine is expressed as:
in the process of extracting the characteristics of the measurement data in the step S2, the position of the wind tunnel nozzle is defined as a number 0 measuring point, and the data characteristics of the number 0 measuring point are 5 time points as follows: t (0, A) represents the measurement start time, P (0, A) represents the nozzle pressure at the measurement start time, T (0, B) represents the test start time, P (0, B) represents the nozzle pressure at the test start time, T (0, C) represents the nozzle pressure at which the test air flow reaches the stabilization time, P (0, C) represents the nozzle pressure at which the test air flow reaches the stabilization time, T (0, D) represents the test effective time end time, P (0, D) represents the nozzle pressure at the test effective time end time, T (0, E) represents the measurement end time, and P (0, E) represents the nozzle pressure at the measurement end time. The data of 5 moments A to E are directly read out from the measurement data of the wind tunnel jet pipe. Similarly, each station of the engine has the 5 characteristic data, but the specific times of A-E of each station are different.
In the above embodiment of the present invention, by establishing a measurement data function conforming to a real physical process of a wind tunnel engine test, and then extracting a time feature of the measurement data function by a filtering method, data processing can be accurately and efficiently performed based on the extracted feature, and errors of test data obtained by processing can be reduced while improving processing efficiency and convenience by performing time shift, averaging, dimensionless and error analysis processing on the data.
The present embodiment is only for explanation of the present invention and is not to be construed as limiting the present invention, and modifications to the present embodiment, which may not creatively contribute to the present invention as required by those skilled in the art after reading the present specification, are all protected by patent laws within the scope of claims of the present invention.
Claims (1)
1. The wind tunnel measurement data processing method based on feature extraction is characterized by comprising the following steps of: the method specifically comprises the following steps:
s1, defining a data function, and defining pressure data of different measuring points of an engine as a function P (x, t) under a Lagrange coordinate system, wherein x represents the measuring point positions, and if the number of the measuring points is 100, the value range of x is as follows: [1,2 … ] and t represents measurement time, if the measurement time is 1 second, and the measurement frequency is 1MHz, the value range of t is as follows: [1,2, … 106];
s2, extracting data features based on a filtering technology, taking wind tunnel spray pipe data as a reference, extracting features of measurement data by adopting the filtering technology, and then further processing engine measuring point data;
s3, data processing, namely processing the data of the engine measuring points according to the step S2, specifically comprising the following steps:
1) The time shift processing is respectively carried out on the data of each measuring point of the engine, and the calculation formula of the time shift length of each measuring point of the engine is as follows: Δt (x) =t (x, B) -T (0, B), where T (0, B) represents a test start time of the wind tunnel nozzle position measurement point, and T (x, B) represents a test start time of the engine measurement point;
2) The measured value of the engine measuring point is subjected to dimensionless treatment by adopting the measured value of the wind tunnel jet pipe, and the calculation formula of the dimensionless treatment is as follows:
3) The pressure data in the effective test time is subjected to averaging treatment, and the calculation formula of the averaging treatment is as follows:
4) The maximum measured value and the minimum measured value of each measuring point of the engine in the effective test time are adopted to calculate an error band, and the calculation formula of the error band is as follows:
according to the processing of the engine measuring point data in the steps 1) to 4), the pressure value of each measuring point of the engine is expressed as:
in the process of extracting the characteristics of the measurement data in the step S2, the position of the wind tunnel spray pipe is defined as a No. 0 measuring point, and the data characteristics of the No. 0 measuring point are 5 time points as follows: t (0, A) represents the measurement start time, P (0, A) represents the nozzle pressure at the measurement start time, T (0, B) represents the test start time, P (0, B) represents the nozzle pressure at the test start time, T (0, C) represents the nozzle pressure at which the test air flow reaches the stabilization time, P (0, C) represents the nozzle pressure at which the test air flow reaches the stabilization time, T (0, D) represents the test effective time end time, P (0, D) represents the nozzle pressure at the test effective time end time, T (0, E) represents the measurement end time, and P (0, E) represents the nozzle pressure at the measurement end time.
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