阅读说明：本技术 一种基于传递函数辨识的动态热流测试方法 (Dynamic heat flow testing method based on transfer function identification ) 是由 王辉 朱新新 朱涛 杨凯 程光辉 于 2019-10-21 设计创作，主要内容包括：本发明公开了一种基于传递函数辨识的动态热流测试方法,包括：利用基准热流传感器及热流传感器标定试验平台,得到标定的输入热流数据；制作基于一维传热体假设的热流传感器,结合已知的标定输入热流数据和热流传感器对应的温度响应测试数据,辨识出基于一维传热体假设的热流传感器的离散传递函数；最后根据辨识获得的离散传递函数,求出其脉冲响应时间序列,并结合Beck规则算法,得到线性动态热流的测试方法。本发明的基于传递函数辨识的动态热流测试方法,具有不依赖热流传感器热物性参数,也不依赖其加工尺寸和热电偶测温精确度,有效解决了动态热流测试不确定问题,同时具有提高有效测试时间,降低热流传感器加工难度和加工成本的优点。(The invention discloses a dynamic heat flow testing method based on transfer function identification, which comprises the following steps: calibrating the test platform by using the reference heat flow sensor and the heat flow sensor to obtain calibrated input heat flow data; manufacturing a heat flow sensor based on the assumption of a one-dimensional heat transfer body, and identifying a discrete transfer function of the heat flow sensor based on the assumption of the one-dimensional heat transfer body by combining known calibration input heat flow data and temperature response test data corresponding to the heat flow sensor; and finally, solving an impulse response time sequence according to the discrete transfer function obtained by identification, and combining a Beck rule algorithm to obtain the linear dynamic heat flow testing method. The dynamic heat flow testing method based on transfer function identification disclosed by the invention has the advantages that the method does not depend on the thermophysical parameters of the heat flow sensor, the processing size and the thermocouple temperature measurement accuracy, the uncertain problem of dynamic heat flow testing is effectively solved, the effective testing time is prolonged, and the processing difficulty and the processing cost of the heat flow sensor are reduced.)

1. A dynamic heat flow test method based on transfer function identification is characterized by comprising the following steps:

step one, calibrating the square wave heat flow amplitude of a heat flow sensor calibration test platform: the heat flow sensor calibration test platform provides square-waveform input heat flow; then, a reference heat flow sensor is used for testing the absolute heat flow q of the amplitude of the square wave heat flow_cAnd testing the absolute heat flow q_cThe amplitude of the square wave heat flow is input as the calibration of the heat flow sensor based on the assumption of the one-dimensional heat transfer body;

step two, synchronously acquiring a spectral path photodiode signal s (k) of square waveform input heat flow with the amplitude value calibrated by taking the sampling time interval as delta T and temperature data T of a first thermocouple pair temperature measuring point of the heat flow sensor based on the assumption of a one-dimensional heat transfer body₁(k) (ii) a Normalizing the s (k) signal to reflect the nominal heat flow waveform, and combining the signal with the known nominal input square wave heat flow amplitude q_cObtaining a dynamic calibration input heat flow q (k) of the heat flow sensor based on the assumption of the one-dimensional heat transfer body;

step three, adopting a least square optimization algorithm, and combining the heat flow sensor dynamic calibration input heat flow q (k) based on the assumption of the one-dimensional heat transfer body and temperature data T₁(k) According to the optimal objective functionAdjustment ofThe parameter θ ═ abcd in the equation]So as to estimate the temperatureWith measured temperature T₁(k) The mean square error is minimum, thereby obtaining the optimal parameter vector theta^*＝[a^*b^*c^*d^*](ii) a Wherein N is the total estimated or total acquired data logarithm;

step four, obtaining the optimal parameter vector theta according to the step three^*Obtaining a discrete transfer function G of the heat flow sensor based on the assumption of one-dimensional heat transfer body^*(z) that is

Wherein, a^*,b^*,c^*,d^*Discrete transfer function coefficients for the heat flow sensor based on a one-dimensional heat transfer body assumption;

step five, discrete transfer function G of the heat flow sensor based on one-dimensional heat transfer body hypothesis^*(z) calculating a heat flow sensor impulse response sequence w based on the one-dimensional heat conductor hypothesis_j(ii) a According to the obtained impulse response sequence w_j(j is more than or equal to 0 and less than or equal to r), and establishing a dynamic heat flow test expression by combining a Beck future time step rule method:

when T is₂≤T_max

Wherein p is the number of future time steps;heat flow sensor impulse response sequence w based on one-dimensional heat transfer body hypothesis_j(j is more than or equal to 0 and less than or equal to r) and combining the estimated heat flow data at the (M-1) th moment and the previous momentCalculated by iterative algorithms, i.e.In the formulaT₁The temperature value measured by the first thermocouple to the temperature measuring point; t is₂The temperature value measured by the second thermocouple to the temperature measuring point; t is_maxIs the maximum allowable temperature value;

step six, according to the obtained dynamic heat flow test expression, utilizing the first thermocouple pair of the heat flow sensor based on the assumption of the one-dimensional heat transfer body to measure the temperature T₁The input heat flow q can be tested and calculated; when T is satisfied₂≤T_maxThe effective test time for the heat flow sensor based on the one-dimensional heat conductor assumption is determined.

2. The dynamic heat flow test method based on transfer function identification of claim 1, wherein the heat flow sensor based on one-dimensional heat transfer body hypothesis comprises:

the heat exchanger comprises a cylindrical heat transfer body, wherein a first thermocouple pair is arranged in the center of a first end part of the cylindrical heat transfer body, a second thermocouple pair is arranged in the center of an end face of a second end part of the cylindrical heat transfer body, a lateral heat insulation layer is arranged on the outer side of an arc-shaped wall of the cylindrical heat transfer body, and a heat transfer body bottom heat insulation layer is arranged on the end face of the second end part of the cylindrical heat transfer body.

3. The transfer function identification based dynamic heat flow testing method of claim 2, wherein the first thermocouple pair is proximate to the end face of the first end.

4. The dynamic heat flow testing method based on transfer function identification of claim 2, wherein the lateral thermal insulation layer is an air layer, and the bottom thermal insulation layer is a high temperature resistant phlogopite sheet.

5. The method of claim 1, wherein the coefficient a in the discrete transfer function g (z) is a coefficient of a^*,b^*,c^*,d^*The calibration data of the heat flow sensor based on the assumption of the one-dimensional heat transfer body can be obtained, and the specific process is as follows:

the relationship between the estimated output temperature response of the heat flow sensor and the input heat flow based on the assumption of one-dimensional heat transfer body can be approximately expressed asQ (k) is a known calibration dynamic input heat flow in a heat flow sensor calibration test based on the assumption of a one-dimensional heat transfer body;a first thermocouple of the heat flow sensor is used for estimating the temperature response of a temperature measuring point based on the assumption of a one-dimensional heat transfer body; using least squares optimization algorithm, when the temperature of the discrete transfer function outputs the estimated valueTemperature response actual test data T of heat flow sensor closest to assumption based on heat transfer body₁(k) Time, identified parameter vector theta^*＝[a^*b^*c^*d^*]For an optimum value, i.e. an optimum objective functionIs minimum, estimate temperatureWith measured temperature T₁(k) The mean square error is the minimum value, from which the coefficient a in the discrete transfer function G (z) can be determined^*,b^*,c^*,d^*(ii) a N is the total estimate or total log of acquired data.

Technical Field

The invention belongs to the technical field of ground heat protection test of hypersonic velocity devices, and particularly relates to a dynamic heat flow test method based on transfer function identification.

Background

In a simulated heat prevention test of a hypersonic speed ground, due to the ultrahigh temperature and high scouring effect of an electric arc flow field, it is often very difficult to directly and accurately test the temperature of the outer surface of a sensor by using a thermocouple. Therefore, a zero point calorimeter with an embedded thermocouple is often used for dynamic cold wall heat flow measurement of an arc flow field test flow field. However, the thermal physical parameters of the heat transfer body are difficult to accurately obtain, the processing size of the zero point position and the temperature measuring point of the corresponding thermocouple are difficult to accurately control, and the temperature measuring error and the time lag of the thermocouple are considered, so that great uncertainty can be brought to the heat flow test; in addition, the heat flow test method of the zero point calorimeter is based on the one-dimensional heat transfer semi-infinite body assumption, so the effective test time is short and is usually less than 0.5 second. The invention provides a novel dynamic heat flow testing method based on one-dimensional heat transfer aiming at the situation.

Disclosure of Invention

An object of the present invention is to solve at least the above problems and/or disadvantages and to provide at least the advantages described hereinafter.

To achieve these objects and other advantages in accordance with the purpose of the invention, there is provided a dynamic heat flow test method based on transfer function identification, including:

step one, calibrating the square wave heat flow amplitude of a heat flow sensor calibration test platform: the heat flow sensor calibration test platform provides square-waveform input heat flow; then, a reference heat flow sensor is used for testing the absolute heat flow q of the amplitude of the square wave heat flow_cAnd testing the absolute heat flow q_cThe amplitude of the square wave heat flow is input as the calibration of the heat flow sensor based on the assumption of the one-dimensional heat transfer body;

step two, synchronously acquiring a spectral path photodiode signal s (k) of square waveform input heat flow with the amplitude value calibrated by taking the sampling time interval as delta T and temperature data T of a first thermocouple pair temperature measuring point of the heat flow sensor based on the assumption of a one-dimensional heat transfer body₁(k) (ii) a Normalizing the s (k) signal to reflect the nominal heat flow waveform, and combining the signal with the known nominal input square wave heat flow amplitude q_cCan be made ofObtaining a dynamic calibration input heat flow q (k) of a heat flow sensor based on the assumption of a one-dimensional heat transfer body;

step three, adopting a least square optimization algorithm, and combining the heat flow sensor dynamic calibration input heat flow q (k) based on the assumption of the one-dimensional heat transfer body and temperature data T₁(k) According to the optimal objective functionAdjustment ofThe parameter θ ═ a b c d in the equation]So as to estimate the temperatureWith measured temperature T₁(k) The mean square error is minimum, thereby obtaining the optimal parameter vector theta^*＝[a^* b^* c^* d^*](ii) a Wherein N is the total estimated or total acquired data logarithm;

step four, obtaining the optimal parameter vector theta according to the step three^*Obtaining a discrete transfer function G of the heat flow sensor based on the assumption of one-dimensional heat transfer body^*(z) that is

Wherein, a^*,b^*,c^*,d^*Discrete transfer function coefficients for the heat flow sensor based on a one-dimensional heat transfer body assumption;

step five, discrete transfer function G of the heat flow sensor based on one-dimensional heat transfer body hypothesis^*(z) calculating a heat flow sensor impulse response sequence w based on the one-dimensional heat conductor hypothesis_j(ii) a According to the obtained impulse response sequence w_j(j is more than or equal to 0 and less than or equal to r), and establishing a dynamic heat flow test expression by combining a Beck future time step rule method:

when T is₂≤T_max

Wherein p is the number of future time steps;heat flow sensor impulse response sequence w based on one-dimensional heat transfer body hypothesis_j(j is more than or equal to 0 and less than or equal to r) and combining the estimated heat flow data at the (M-1) th moment and the previous momentCalculated by iterative algorithms, i.e.In the formulaT₁The temperature value measured by the first thermocouple to the temperature measuring point; t is₂The temperature value measured by the second thermocouple to the temperature measuring point; t is_maxIs the maximum allowable temperature value;

step six, according to the obtained dynamic heat flow test expression, utilizing the first thermocouple pair of the heat flow sensor based on the assumption of the one-dimensional heat transfer body to measure the temperature T₁The input heat flow q can be tested and calculated; when T is satisfied₂≤T_maxThe effective test time for the heat flow sensor based on the one-dimensional heat conductor assumption is determined.

Preferably, the heat flow sensor based on the one-dimensional heat transfer body assumption includes:

the heat exchanger comprises a cylindrical heat transfer body, wherein a first thermocouple pair is arranged in the center of a first end part of the cylindrical heat transfer body, a second thermocouple pair is arranged in the center of an end face of a second end part of the cylindrical heat transfer body, a lateral heat insulation layer is arranged on the outer side of an arc-shaped wall of the cylindrical heat transfer body, and a heat transfer body bottom heat insulation layer is arranged on the end face of the second end part of the cylindrical heat transfer body.

Preferably, the first thermocouple pair is located near an end face of the first end portion.

Preferably, the lateral heat insulation layer is an air layer, and the bottom heat insulation layer is a high-temperature-resistant phlogopite sheet.

It is preferable that the first and second liquid crystal layers are formed of,said discrete transfer function G^*Coefficient a in (z)^*,b^*,c^*,d^*The calibration data of the heat flow sensor based on the assumption of the one-dimensional heat transfer body can be obtained, and the specific process is as follows:

the relationship between the estimated output temperature response of the heat flow sensor and the input heat flow based on the assumption of a one-dimensional heat transfer body can be approximately expressed as:q (k) is a known calibration input heat flow in a heat flow sensor calibration test based on the assumption of a one-dimensional heat transfer body;outputting an estimated value for the temperature response of a first thermocouple of the heat flow sensor to a temperature measuring point based on the assumption of the one-dimensional heat transfer body; using least squares optimization algorithm, when the temperature of the discrete transfer function outputs the estimated valueTemperature response test data T of heat flow sensor closest to actual one-dimensional heat transfer body hypothesis₁(k) Time, identified parameter vector theta^*＝[a^*b^*c^*d^*]To an optimum value, i.e. an objective functionIs minimized, thereby determining a discrete transfer function G^*Coefficient a in (z)^*,b^*,c^*,d^*(ii) a N is the total estimate or total log of acquired data.

The invention at least comprises the following beneficial effects:

the dynamic heat flow testing method based on the heat flow calibration test identification of the heat flow sensor provided by the invention does not depend on the thermophysical property parameters of the heat flow sensor, and does not depend on the processing size and the thermocouple temperature measurement accuracy, thereby effectively solving the problem of uncertain dynamic heat flow testing, simultaneously improving the effective testing time and reducing the processing difficulty and the processing cost of the heat flow sensor.

Additional advantages, objects, and features of the invention will be set forth in part in the description which follows and in part will become apparent to those having ordinary skill in the art upon examination of the following or may be learned from practice of the invention.

Description of the drawings:

FIG. 1 is a schematic diagram of a heat transfer structure of a heat flow sensor based on a one-dimensional heat transfer assumption according to the present invention;

wherein, 1-cylindrical heat transfer body; 11-a first end portion; 12-a second end; 2-a first thermocouple pair; 3-a second thermocouple pair; 4-lateral thermal insulation layer; 5-bottom heat insulation layer.

FIG. 2 is a schematic diagram of an impulse response sequence obtained according to an identified discrete transfer function provided by the present invention;

FIG. 3 is a schematic diagram illustrating validity verification of a dynamic heat flow testing method based on transfer function identification according to the present invention;

the specific implementation mode is as follows:

the present invention is further described in detail below with reference to the attached drawings so that those skilled in the art can implement the invention by referring to the description text.

It will be understood that terms such as "having," "including," and "comprising," as used herein, do not preclude the presence or addition of one or more other elements or groups thereof.

A dynamic heat flow test method based on transfer function identification comprises the following steps:

step one, calibrating the square wave heat flow amplitude of a heat flow sensor calibration test platform: the heat flow sensor calibration test platform provides square-waveform input heat flow; then, a reference heat flow sensor is used for testing the absolute heat flow q of the amplitude of the square wave heat flow_cAnd testing the absolute heat flow q_cThe amplitude of the heat flow of the square wave is used as the calibration input of the heat flow sensor based on the assumption of the one-dimensional heat transfer body as shown in FIG. 1;

step two, synchronously acquiring a spectral path photodiode signal s (k) of square waveform input heat flow with the amplitude value calibrated by taking the sampling time interval as delta t and measuring the temperature point by a first thermocouple of the heat flow sensor based on the assumption of a one-dimensional heat transfer bodyTemperature data T of₁(k) (ii) a Normalizing the s (k) signal to reflect the nominal heat flow waveform, and combining the signal with the known nominal input square wave heat flow amplitude q_cObtaining a dynamic calibration input heat flow q (k) of the heat flow sensor based on the assumption of the one-dimensional heat transfer body;

step three, adopting a least square optimization algorithm, and combining the heat flow sensor dynamic calibration input heat flow q (k) based on the assumption of the one-dimensional heat transfer body and temperature data T₁(k) The relationship between the estimated output temperature response of the heat flow sensor based on the assumption of a one-dimensional heat conductor and the input heat flow is approximated as:q (k) is a known calibration dynamic input heat flow in a heat flow sensor calibration test based on the assumption of a one-dimensional heat transfer body;based on the one-dimensional heat transfer body hypothesis, the temperature response estimation value of the first thermocouple of the heat flow sensor to the temperature measuring point is obtained according to the optimal objective functionAdjustment ofThe parameter θ ═ a b c d in the equation]Make the optimal objective functionThe value of (c) is minimal. At this time, the temperature is estimatedWith measured temperature T₁(k) The mean square error is the minimum value, thereby obtaining the optimal parameter vector theta^*＝[a^* b^* c^* d^*](ii) a N is total estimation or total collection data logarithm;

step four, obtaining the optimal parameter vector theta according to the step three^*Obtaining the discrete transfer function of the heat flow sensor based on the assumption of one-dimensional heat transfer bodyNumber G^*(z) that is

Wherein, a^*,b^*,c^*,d^*Discrete transfer function coefficients for the heat flow sensor based on a one-dimensional heat transfer body assumption;

step five, taking the single pulse with the time interval delta t and the amplitude value 1 as a discrete transfer function G of the heat flow sensor based on the assumption of the one-dimensional heat transfer body^*(z) input quantity, calculating the impulse response sequence w of the heat flow sensor based on the assumption of the one-dimensional heat transfer body_j(ii) a According to the obtained impulse response sequence w_j(j is more than or equal to 0 and less than or equal to r), and establishing a dynamic heat flow test expression by combining a Beck future time step rule method:

when T is₂≤T_max

Wherein p is the number of future time steps;heat flow sensor impulse response sequence w based on heat transfer body hypothesis_j(j is more than or equal to 0 and less than or equal to r) and combining the estimated heat flow data at the (M-1) th moment and the previous momentCalculated by iterative algorithms, i.e.In the formulaT₁The temperature value measured by the first thermocouple to the temperature measuring point; t is₂The temperature value measured by the second thermocouple to the temperature measuring point; t is_maxIs the maximum allowable temperature value;

as shown in fig. 2, a sampling time interval is 0.001s, a dimensionless arc value corresponding to the impulse response sequence is obtained through a discrete transfer function, and a variation relation diagram of the sampling point number and the dimensionless arc value is obtained by taking the sampling point number as an abscissa and the dimensionless arc value as an ordinate;

step six, according to the obtained dynamic heat flow test expression, utilizing the first thermocouple pair of the heat flow sensor based on the assumption of the one-dimensional heat transfer body to measure the temperature T₁The input heat flow q can be tested and calculated; when T is satisfied₂≤T_maxThe effective test time for the heat flow sensor based on the one-dimensional heat conductor assumption is determined.

According to the validity verification diagram of the dynamic heat flow testing method based on transfer function identification shown in fig. 3, the tested heat flow can be compared with the actual input heat flow to obtain the method.

In the above technical solution, the heat flow sensor based on the assumption of the one-dimensional heat transfer body includes:

the heat exchanger comprises a cylindrical heat transfer body 1, wherein a first thermocouple pair 2 is arranged in the center of a first end part 11 of the cylindrical heat transfer body 1, a second thermocouple pair 3 is arranged in the center of a second end part end surface 12 of the cylindrical heat transfer body, a lateral heat insulation layer 4 is arranged on the outer side of an arc-shaped wall of the cylindrical heat transfer body 1, and a heat transfer body bottom heat insulation layer 5 is arranged on the end surface of a second end part 12 of the cylindrical heat transfer body 1. In this way, the heat flux sensor based on the heat transfer body hypothesis can simplify the applicable conditions for describing the dynamic heat flux testing method based on the transfer function identification.

In the above technical solution, the first thermocouple pair 2 is close to the end face of the first end portion 11. In this way, the end surface of the first thermocouple pair near the first end can improve the response speed.

In the technical scheme, the lateral heat insulation layer 4 is an air layer, and the bottom heat insulation layer 5 is a high-temperature-resistant phlogopite sheet. By adopting the mode, the lateral heat insulation layer and the bottom heat insulation layer are arranged on the cylindrical heat transfer body, so that the influence of boundary conditions on the heat flow sensor based on the assumption of the one-dimensional heat transfer body is favorably reduced, and the accuracy of a dynamic heat flow test is improved.

While embodiments of the invention have been described above, it is not limited to the applications set forth in the description and the embodiments, which are fully applicable in various fields of endeavor to which the invention pertains, and further modifications may readily be made by those skilled in the art, it being understood that the invention is not limited to the details shown and described herein without departing from the general concept defined by the appended claims and their equivalents.