Heat flow identification method based on step response calibration

Abstract

The invention discloses a heat flow identification method based on step response calibration. The method comprises the following steps: step 1, calibrating step response (t) of a heat conductor; step2, assuming that q (t) is a constant in each t, and setting the component of the ith [ti, t + 1] as qi; step 3, dispersing Y (t) and (t) to obtain Y = Xq; step 4, performing singular value decomposition on X; step 5, performing truncation on the singular value decomposition to obtain Xnew; step 6, replacing X with Xnew, and performing inversion through the matrix to obtain q; step 7, calculating Rand S; step 8, drawing an L curve, and setting an Ns value corresponding to the maximum curvature of the L curve as the optimal singular value number Nopt; and step 9, carrying out noise reduction onthe vi to obtain a step 10, and replacing the vi with the finally obtained heat flow. According to the calibration method and the heat flow identification method provided by the invention, the uncertainty of an identification result can be effectively reduced, and higher heat flow calculation precision is achieved.

Description

technical field [0001] The invention relates to a high-precision identification method for heat flow, in particular to a method for back-calculating surface heat flow through the step response of a temperature measuring point inside a calibration structure. Background technique [0002] For the heat flow measurement in the extreme service environment of the thermal protection system of the re-entry vehicle, the measurement device installed on the surface will bear a greater risk of failure, and it is difficult to achieve a long-term stable measurement of the heat flow on the surface of the structure. On the contrary, the measurement of the internal temperature of the structure has higher reliability and stability, and is easier to realize. Currently, a widely used method is to calculate the surface heat flow by solving the inverse problem model by measuring the temperature at several locations inside the structure. However, the traditional method needs to know the input par...

AI Technical Summary

Problems solved by technology

However, the traditional method needs to know the input parameters such as the position of the temperature measuring point, the thermophysical parameters of the material, the structure size and the surface emissivity when calculating the heat flow, and these parameters need to be obtained through experimental measurement, which will increase the uncertainty of the results

In addition, thermocouple temperature measurement will be affected by factors such as signal hysteresis and local heat loss, which will introduce measurement errors and reduce the accuracy of heat flow calculations.

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