CN107958206B - Temperature measurement data preprocessing method for aircraft surface heat flow identification device - Google Patents
Temperature measurement data preprocessing method for aircraft surface heat flow identification device Download PDFInfo
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- CN107958206B CN107958206B CN201711086206.0A CN201711086206A CN107958206B CN 107958206 B CN107958206 B CN 107958206B CN 201711086206 A CN201711086206 A CN 201711086206A CN 107958206 B CN107958206 B CN 107958206B
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
- G06F2218/02—Preprocessing
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- G01K—MEASURING TEMPERATURE; MEASURING QUANTITY OF HEAT; THERMALLY-SENSITIVE ELEMENTS NOT OTHERWISE PROVIDED FOR
- G01K7/00—Measuring temperature based on the use of electric or magnetic elements directly sensitive to heat ; Power supply therefor, e.g. using thermoelectric elements
- G01K7/02—Measuring temperature based on the use of electric or magnetic elements directly sensitive to heat ; Power supply therefor, e.g. using thermoelectric elements using thermoelectric elements, e.g. thermocouples
Abstract
The invention provides a method for preprocessing temperature measurement data of an aircraft surface heat flow identification device, and belongs to the technical field of measurement and processing of thermal parameters of aerospace flight tests. The method comprises the steps of firstly carrying out local distortion point (local jumping point) elimination on temperature rise measurement data of the heat flow identification device, then carrying out smoothing processing on the measurement data by utilizing a smoothing processing method of averaging N adjacent data points, and finally obtaining temperature measurement data meeting the heat flow identification requirement. And the N value is determined according to the related parameters of the temperature sensor and the temperature curve characteristics. The invention can effectively improve the influence of temperature step and local jumping point on the heat flow identification result and improve the accuracy and reliability of the heat flow identification result.
Description
Technical Field
The invention relates to a method for preprocessing temperature measurement data of an aircraft surface heat flow identification device, which is suitable for preprocessing measurement data of a current hypersonic aircraft flight test and belongs to the technical field of measurement and processing of thermal parameters of aerospace flight tests.
Background
The aerodynamic heating environment on the surface of the hypersonic aircraft is severe, the aircraft heat insulation prevention system faces severe challenges, and strict requirements are provided for the design precision and the conservation quantity of the aircraft heat insulation prevention system. The accurate prediction of the pneumatic heating environment and distribution is the premise and the foundation of realizing the fine design of the heat insulation prevention system. At present, due to the current situation of the pneumatic thermal environment prediction technology, the thermal environment prediction method cannot achieve good precision, and the capability of ground test equipment cannot reproduce real flight environment at present. In this context, it is becoming increasingly urgent to develop a thermal environment prediction method by conducting measurements of the heat flux on the surface of the aircraft through flight tests.
However, the hypersonic aircraft has a very harsh surface thermal environment and a long flight time, and is limited by the temperature resistance limit of the sensor, the size of a product and the measurement precision, so that the conventional heat flow sensor is difficult to directly measure at present, and is gradually difficult to adapt to the measurement requirement of long-time high heat flow. The aerodynamic heat identification is a heat flow indirect measurement method, and surface heat flow information is obtained by inversion through a mathematical method by measuring the temperature rise between heat-proof material layers or measuring the temperature rise of a heat flow identification device. Because of better environmental adaptability, relatively simple measurement structure and relatively small product size, pneumatic heat identification methods and corresponding heat flow identification devices are increasingly researched and applied.
According to the principle of heat flow identification, the temperature rise measurement data of the sensing element is a prerequisite and key for heat flow identification. The temperature rise information measuring process of the sensitive element comprises the following steps: the electric signal information is firstly obtained by a thermocouple arranged in the sensitive element and then converted into temperature information by an amplifier and a converter. For example, the number of adopted codes of a sensor used by the current aerospace craft is generally 8, namely 255 divisions are formed in the range, and under the condition that the measured value is obviously smaller than the maximum value of the range, the temperature measurement data can generate an obvious step phenomenon, as shown in fig. 2(a), the range of the temperature sensor is 0-200 ℃, each division value is about 0.8 ℃, and as the measured value does not exceed 30 ℃ at most, the temperature rise measurement result has an obvious step phenomenon. In addition, the temperature measurement result may have a local distortion condition due to the influence of electromagnetic interference, power stability and instantaneous vibration and impact of the aircraft in the process of amplification and transformation of the electric signal, and fig. 2(b) shows a temperature measurement result of a certain flight test, so that a trip point exists in the temperature measurement result locally. The step phenomenon and the local jump point of the temperature measurement result both influence the heat flow identification process, so that the heat flow identification result is distorted, the temperature measurement result needs to be preprocessed before the heat flow identification work is carried out, reasonable input conditions are provided for heat flow identification, and the accuracy of the heat flow identification result is improved.
At present, an effective preprocessing method for the non-smooth temperature measurement data with step characteristics in the hypersonic flight test is lacked. The data preprocessing research is carried out by adopting a common data fitting method and a data smoothing method, and the result shows that: the data fitting method such as a polynomial fitting method has a very smooth processing result curve, is well matched with an original data curve in a macroscopic view, but can smooth or ignore the tiny change of a temperature rise curve, so that the heat flow identification result is distorted; data smoothing methods, such as various types of smoothing filtering methods, are not satisfactory for processing measured data with step characteristics due to the difficulty in determining some characteristic parameters of the filtering method (such as the number of data points used, the width of the filtered data, etc.).
Disclosure of Invention
The technical problem to be solved by the invention is as follows: aiming at the problems that the quality of the measured data of the existing heat flow identification assembly is not high and the measured data is difficult to be used as an effective input condition for heat flow identification, the method for preprocessing the temperature measured data of the aircraft surface heat flow identification device is provided, reasonable temperature data input can be provided for heat flow identification, the influence of temperature step and local jump point on a heat flow identification result is effectively improved, and the accuracy and reliability of the heat flow identification result are improved.
The technical solution of the invention is as follows: a method for preprocessing temperature measurement data of an aircraft surface heat flow identification device comprises the following steps: smoothing the temperature measurement data by averaging the adjacent data points to obtain preprocessed temperature data
The specific smoothing method is as follows:
wherein n ismaxThe number of all data points is N, the number of preset smooth processing points is a positive integer.
Preferably, the following treatment can be added before the step:
and analyzing the change rule and trend of the temperature curve obtained by the measurement of the aircraft surface heat flow identification device, and eliminating skip points in the temperature measurement data.
The data point number N is determined by the following method:
(1) carrying out statistical analysis on the temperature measurement data curve, and determining the temperature change range delta T and the measurement time length delta T of the temperature measurement data;
(2) measuring range T of the temperature sensor used according to the temperature measurement dataRAnd the sum-and-number of digits is NdCalculating the measured division value delta of the temperature sensorT；
(3) Measuring division value delta according to temperature change range delta T and temperature sensorTCalculating the number m of steps of the temperature measurement datastep；
(4) According toMeasuring time length delta t and step number m of temperature measuring datastepAnd the sampling rate f of the editor, and the number N of the preprocessed smooth data points is calculated.
The temperature sensor measures a division value deltaTThe specific calculation formula is as follows:
number of steps m of temperature measurement datastepThe specific calculation formula is as follows:
the specific calculation formula of the number N of the preprocessed smooth data points is as follows:
compared with the prior art, the invention has the beneficial effects that:
(1) the temperature measurement data of the heat flow identification device for the flight test is smoothed by adopting an adjacent data point averaging method, so that the data quality of the temperature measurement data serving as the heat flow identification input condition is improved;
(2) the invention further provides a method for determining the number N of the smooth data points, and the heat flow identification is carried out by utilizing the temperature measurement data after the pretreatment is finished according to the number N of the smooth data points, so that the influence of temperature steps and local jumping points on the heat flow identification result can be effectively improved, and the accuracy and the reliability of the heat flow identification result are improved.
Drawings
FIG. 1 is a flow chart of a method for preprocessing temperature measurement data according to the present invention;
FIG. 2(a) is a graph of temperature measurement data according to an embodiment of the present invention;
FIG. 2(b) is a graph of temperature measurement data with trip points according to an embodiment of the present invention;
FIG. 3 is a diagram illustrating the temperature variation range Δ T and the measurement duration Δ T according to an embodiment of the present invention;
FIG. 4(a) is an overall view of raw data, polynomial fit data and smoothed data according to an embodiment of the present invention;
FIG. 4(b) is a partial view of raw data, polynomial fit data and smoothed data according to an embodiment of the present invention;
FIG. 5(a) is an overall diagram of the original data and the smoothed data of different point data according to the embodiment of the present invention;
FIG. 5(b) is a partial enlarged view of the original data and the smooth data with different points according to the embodiment of the present invention;
FIG. 6 is a diagram of identification results based on different point number smoothing data according to an embodiment of the present invention;
FIG. 7 is a comparison of the identification results of the present invention based on raw data, polynomial fit data and smoothed data with flight angle of attack.
Detailed Description
The present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.
Aiming at the problems existing in the aspect of preprocessing the measurement data of the conventional heat flow identification device, the invention provides a preprocessing method for the temperature measurement data of the aircraft surface heat flow identification device according to the analysis and research. The method is technically characterized in that: the temperature rise measurement data of the heat flow identification device is subjected to local distortion point (local jumping point) elimination, and then the measurement data is subjected to smoothing treatment by using a smoothing treatment method of averaging N adjacent data points (N value is determined according to related parameters of a sensor and temperature curve characteristics), and finally the temperature measurement data meeting the heat flow identification requirement is obtained. The specific process is as follows:
and s1, analyzing the change rule and trend of the temperature curve obtained by the aircraft surface heat flow identification device, and eliminating the jump points in the temperature measurement data.
s2 smoothing the temperature measurement data by using the average method of the adjacent data points before and after smoothing the number N of the data points to obtain preprocessed temperature data
The specific smoothing method is as follows:
wherein n ismaxThe number of all data points.
Preferably, the invention further provides that the measuring range T is based on the temperature sensorRNumber of picking and editing positions N of picking and editing devicedThe sampling rate f of the editor, the temperature variation range delta T and the measurement duration delta T are used for determining the number N of smooth data points to be preprocessed, and the method specifically comprises the following steps:
(1) analyzing and counting the temperature measurement data curve, and determining the temperature change range delta T and the measurement time length delta T of the temperature measurement data;
fig. 3 is a schematic diagram illustrating a temperature variation range Δ T and a measurement duration Δ T of a temperature measurement data curve of a typical flight test heat flow identification device, where an abscissa represents time T, an ordinate represents temperature T, a temperature rise of the curve in the diagram represents Δ T, and the measurement duration is Δ T.
The starting time of the temperature measurement data is t1End time t2Starting temperature T1End time of T2And the temperature rise is delta T ═ T2-T1L, measurement duration Δ t ═ t2-t1。
(2) According to the measuring range T of the temperature sensorRCalculating the measured division value delta of the temperature sensorT：
(3) Measuring division value delta according to temperature change range delta T and temperature sensorTCalculating the number m of steps of the temperature measurement datastep：
(4) Measuring time delta t according to temperature measuring data and step number m of temperature measuring datastepAnd sampling rate f of the encoder, calculating and preprocessingNumber of smooth data points N:
example (b):
fig. 4(a) and 4(b) show overall and local graphs of raw data, polynomial fitting data and smoothed data of a typical flight test heat flow identification device respectively, and it can be seen from the graphs that, macroscopically, the processing results of both methods are better matched with the curves of the raw data, but locally, the preprocessing results of the invention are more matched with the raw data, and can more accurately reflect the change of the raw data.
Fig. 5(a) and 5(b) show the whole and partial enlarged views of the original temperature measurement data and the smooth data of different point data of the typical flight test heat flow identification device respectively. The temperature results of smoothing treatment by using 200, 400 and 800 adjacent data points are given, the smoothing treatment results of different points are almost consistent in macroscopic view, and the three points have slight differences as seen from a local enlarged view. Fig. 6 shows a comparison of the heat flow identification results corresponding to different points, and it can be known from the comparison that the heat flow identification results obtained by performing data smoothing processing on different numbers of data points are obviously different. If the number of data points used for smoothing is not enough, the phenomenon of severe jump of the heat flow identification result is not enough to be improved, for example, the heat flow identification result with N being 200 shows; the more the number of data points used for smoothing processing is, the more obvious the smoothing effect on the drastic change of the heat flow is, and when N is 800, the step change of the heat flow is smoothed. Therefore, for the data point smoothing method, how many data points (i.e. the selection of N value) are used for smoothing is a key issue. Therefore, when the temperature rise curve is subjected to smooth pretreatment, the number of data points adopted during the smooth pretreatment of the data needs to be reasonably selected.
Fig. 7 is a comparison of the heat flow identification results based on the original data, the polynomial fitting data and the smooth data, and the distribution of the flight angle of attack is also given in the figure, so that it can be seen that the heat flow identification results present a severe jump phenomenon and severe distortion due to the existence of the temperature step in the original data, the jump phenomenon of the identification results of the original measured data is effectively eliminated by the identification results of the preprocessed data, the amplitude and the variation trend of the heat flow identification results are well preserved, and the heat flow has an obvious step-like variation with the angle of attack, which conforms to the real physical phenomenon that the heat flow varies with the change of the angle of attack; the heat flow identification result of the polynomial fitting data is too smooth, the heat flow amplitude and the change trend are both smoothed, and a large distortion phenomenon exists.
The analysis proves that the method for smoothing the data can better reflect the change of the temperature rise curve relatively, and the accuracy and the reliability of the heat flow identification result are higher.
The measurement data preprocessing method provided by the invention can provide reasonable temperature data input for heat flow identification, effectively improves the influence of temperature step and local jumping point on the heat flow identification result, and improves the accuracy and reliability of the heat flow identification result.
The data preprocessing method provided by the invention is not only suitable for the measurement data of the heat flow identification device, but also suitable for the temperature measurement data obtained by other types of temperature measuring devices and other heat-related measurement data. The above-mentioned embodiments are merely illustrative of the present invention, and should not be construed as limiting the present invention, so that all embodiments similar to the inventive concept are within the scope of the present invention.
Parts of the specification which are not described in detail are within the common general knowledge of a person skilled in the art.
Claims (4)
1. A method for preprocessing temperature measurement data of an aircraft surface heat flow identification device is characterized by comprising the following steps: smoothing the temperature measurement data by averaging the adjacent data points to obtain preprocessed temperature data
The specific smoothing method is as follows:
wherein n ismaxThe number of all data points is N, the number of preset smooth processing points is a positive integer;
the data point number N is determined by the following method:
(1) carrying out statistical analysis on the temperature measurement data curve, and determining the temperature change range delta T and the measurement time length delta T of the temperature measurement data;
(2) measuring range T of the temperature sensor used according to the temperature measurement dataRAnd the sum-and-number of digits is NdCalculating the measured division value delta of the temperature sensorT；
(3) Measuring division value delta according to temperature change range delta T and temperature sensorTCalculating the number m of steps of the temperature measurement datastep；
(4) The number of steps m according to the measurement time length delta t and the temperature measurement datastepAnd sampling rate f of the editor, calculating the number N of the preprocessed smooth data points:
the specific calculation formula of the number N of the preprocessed smooth data points is as follows:
2. the method for preprocessing the temperature measurement data of the heat flow identification device on the surface of the aircraft according to claim 1, wherein the following processing is added before the step:
and analyzing the change rule and trend of the temperature curve obtained by the measurement of the aircraft surface heat flow identification device, and eliminating skip points in the temperature measurement data.
3. The method of claim 1, wherein the temperature sensor measures a division ΔTThe specific calculation formula is as follows:
4. the method of claim 1, wherein the number of steps m of the temperature measurement data is mstepThe specific calculation formula is as follows:
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| CN105548250A (en) * | 2016-01-13 | 2016-05-04 | 北京机电工程研究所 | Heat flow control method, device and system for aerothermodynamic experiment of aircraft |
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| CN105068032A (en) * | 2015-08-13 | 2015-11-18 | 湖南大学 | Photovoltaic convergence box current acquisition channel temperature drift coefficient calibration method |
| CN105548250A (en) * | 2016-01-13 | 2016-05-04 | 北京机电工程研究所 | Heat flow control method, device and system for aerothermodynamic experiment of aircraft |
| CN106021181A (en) * | 2016-05-17 | 2016-10-12 | 中国电子科技集团公司第四十研究所 | Adjacent point correlativity mean noise reduction method implemented for FFT data |
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