A temperature correction method and device based on infrared dot matrix temperature sensor

Abstract

The present invention discloses a temperature correction method and device based on an infrared dot matrix temperature sensor. The method comprises: using the infrared dot matrix temperature sensor to collect a temperature distribution map of a measured area; obtaining the actual temperature at the geometric center of the measured area using a standard thermometer; obtaining the measured temperature of each pixel based on the temperature distribution map; calculating a center pixel temperature correction coefficient based on the actual temperature at the geometric center of the measured area and the measured temperature; calculating a pixel position correction coefficient based on the position coordinates of the pixels in the temperature distribution map; calculating a pixel position nonlinear correction coefficient based on a pre-fitted nonlinear parameter and the position coordinates of the pixels; and calculating the corrected temperature of the corresponding pixel based on the pixel position nonlinear correction coefficient, the center pixel temperature correction coefficient, the pixel position correction coefficient, and the measured temperature of the pixel. This method can improve the accuracy of infrared temperature measurement within a region.

Description

Technical Field

[0001] The present invention relates to the field of infrared temperature measurement technology, and in particular to a temperature correction method and device based on an infrared dot matrix temperature measurement sensor. Background Art

[0002] Currently, smart substations have become the fundamental model for substation construction. The control cabinets used in the power industry integrate the power distribution, measurement, monitoring, protection, and control functions of power equipment such as circuit breakers, disconnectors, and fully enclosed switchgear (GIS) into a single cabinet. While existing control cabinets save floor space, they integrate multiple power devices, resulting in numerous internal wiring terminals. These terminals can heat up during use due to aging, corrosion, moisture, and leakage, potentially causing fires. Therefore, temperature monitoring of the wiring inside the control cabinet is essential.

[0003] Currently, there are three methods for testing the internal wiring terminals of the control cabinet:

[0004] 1. Electric power personnel regularly use thermometers to conduct manual temperature measurements on site. They measure the temperature at locations where wiring terminals are concentrated or where temperatures are likely to rise to avoid overheating or fire hazards. This method is highly safe and accurate, but because it requires manual measurement, it has the following problems: it can only monitor at regular intervals, not in real time, and is inefficient.

[0005] 2. Use infrared spot thermometers to measure temperature. Install infrared spot thermometers inside the control cabinet to measure temperature. This method allows for placement of infrared spot thermometers in densely populated areas with wiring terminals or locations prone to heat generation. While this method can measure temperatures in high-risk locations within the control cabinet, the spot thermometers have a very narrow measurement range and can often only measure the temperature at a single point. Installing a large number of infrared spot thermometers inside the control cabinet would require significant space and result in high costs.

[0006] 3. Use temperature sensors for measurement. For example, patent document CN104132732B discloses a temperature monitoring system and method for substation control cabinets based on real-time acquisition of panel cabinet temperature. This patent uses a temperature acquisition module installed in the substation control cabinet to collect the temperature inside the substation control cabinet in real time and upload it to the monitoring system via the network. This method uses a temperature sensor for non-contact temperature measurement. Although it can measure the temperature inside the control cabinet, due to the large temperature difference between the temperature at the densely connected terminal blocks and the temperature at the non-densely connected terminal blocks, it is difficult to measure the actual temperature at the densely connected terminal blocks by simply measuring the temperature in the air, resulting in poor measurement results.

[0007] Infrared dot matrix temperature sensors consist of multiple infrared temperature measurement units arranged in an array. They can simultaneously measure the temperature distribution within their covered field of view. However, to achieve the designed measurement accuracy, the infrared dot matrix temperature sensor requires the object being measured to fill its field of view. However, the surface area of ​​each terminal is much smaller than the infrared dot matrix temperature sensor's field of view. In this case, the temperature measured by the infrared dot matrix temperature sensor is not the actual temperature of the terminal. Consequently, temperature deviations can occur, resulting in inaccurate measurements and making it difficult to guarantee effective monitoring. Summary of the Invention

[0008] The present invention provides a temperature correction method and device based on an infrared dot matrix temperature measuring sensor, which can improve the temperature measurement accuracy of the infrared dot matrix temperature measuring sensor and reduce production costs.

[0009] A temperature correction method based on an infrared dot matrix temperature sensor, comprising:

[0010] Use infrared dot matrix temperature sensor to collect the temperature distribution map of the area to be measured;

[0011] Obtaining the actual temperature at the geometric center of the area to be measured using a standard thermometer;

[0012] Obtaining a measured temperature of each pixel according to the temperature distribution map;

[0013] Obtaining a center pixel temperature correction coefficient according to the actual temperature at the geometric center of the area to be measured and the measured temperature at the geometric center of the area to be measured;

[0014] Obtaining a pixel position correction coefficient according to the position coordinates of the pixels in the temperature distribution map;

[0015] Obtaining a pixel position nonlinear correction coefficient based on the pre-fitted nonlinear parameters and the pixel position coordinates;

[0016] The corrected temperature of the corresponding pixel is obtained by calculation according to the pixel position nonlinear correction coefficient, the central pixel temperature correction coefficient, the pixel position correction coefficient and the measured temperature of the pixel.

[0017] Furthermore, the infrared dot matrix temperature sensor includes m rows and n columns of infrared temperature sensing units, each infrared temperature sensing unit corresponds to a pixel in the temperature distribution map, wherein m and n are both greater than or equal to 2.

[0018] Furthermore, the center pixel temperature correction coefficient is a ratio of the actual temperature at the geometric center of the area to be measured to the measured temperature at the geometric center of the area to be measured.

[0019] Furthermore, according to the position coordinates of the pixels in the temperature distribution map, a pixel position correction coefficient is calculated, including:

[0020] The geometric center of the area to be measured is set as the origin, the horizontal symmetry axis of the area to be measured is the X axis, and the vertical symmetry axis is the Y axis, to establish a field of view coordinate system;

[0021] Obtaining a maximum column viewing angle of the infrared dot matrix temperature sensor, and calculating a distance from the infrared dot matrix temperature sensor to the geometric center of the area to be measured based on the maximum X coordinate of the area to be measured and the maximum column viewing angle;

[0022] The distance from the infrared dot matrix temperature sensor to the geometric center of the measured area is used as the Z coordinate, and the distance from the pixel to the infrared dot matrix temperature sensor is calculated based on the X coordinate value, Y coordinate value and the Z coordinate of the pixel;

[0023] The ratio of the distance from the pixel to the infrared dot matrix temperature sensor to the Z coordinate is used as the pixel position correction coefficient.

[0024] Furthermore, the nonlinear parameters are obtained by pre-fitting, including:

[0025] Cover the test area with the test field of view of the infrared dot matrix temperature sensor and collect the test temperature distribution map of the test area;

[0026] Obtaining the actual test temperature at the geometric center of the test field of view using a standard thermometer;

[0027] Selecting a plurality of characteristic points on the test temperature distribution diagram, obtaining the test temperatures of the characteristic points, and obtaining the test temperature at the geometric center of the test field of view;

[0028] Taking the geometric center of the test field of view as the origin, the horizontal axis of symmetry of the test field of view as the X axis, and the vertical axis of symmetry as the Y axis, a test field of view coordinate system is established to obtain the pixel coordinates of the multiple feature points;

[0029] Calculate the test center temperature correction coefficient based on the actual test temperature at the geometric center of the test field of view and the test temperature;

[0030] According to the pixel coordinates of each feature point, the feature point position correction coefficient is calculated;

[0031] Calculating a rough correction temperature of the characteristic point according to the test center temperature correction coefficient, the characteristic point position correction coefficient and the test temperature of the characteristic point;

[0032] Establish a coordinate system with the distance from the feature point to the geometric center of the test field of view as the horizontal coordinate and the temperature as the vertical coordinate;

[0033] Marking the feature point rough correction temperature and the test temperature of the feature point in the coordinate system and performing fitting to obtain an exponential function curve;

[0034] The base of the exponential function curve is obtained by calculation as the nonlinear parameter.

[0035] Furthermore, the rough correction temperature of the feature point is the product of the test center temperature correction coefficient, the feature point position correction coefficient and the test temperature of the feature point.

[0036] Furthermore, according to the nonlinear parameters obtained by pre-fitting and the position coordinates of the pixels, the nonlinear correction coefficient of the pixel position is calculated, including:

[0037] Calculating the distance between the pixel and the geometric center of the area to be measured based on the X-coordinate value and the Y-coordinate value of the pixel;

[0038] The nonlinear parameter is used as a base and the distance between the pixel and the geometric center of the area to be measured is used as an exponent to calculate a value to be obtained as the pixel position nonlinear correction coefficient.

[0039] Furthermore, the correction temperature of the corresponding pixel is the product of the pixel position nonlinear correction coefficient, the center pixel temperature correction coefficient, the pixel position correction coefficient and the measured temperature of the pixel.

[0040] A temperature correction device based on an infrared dot matrix temperature sensor, comprising:

[0041] The temperature acquisition module is used to collect the temperature distribution map of the area to be measured using an infrared dot matrix temperature sensor;

[0042] An actual temperature acquisition module is used to obtain the actual temperature at the geometric center of the test area using a standard thermometer;

[0043] A measured temperature acquisition module, configured to obtain the measured temperature of each pixel according to the temperature distribution map;

[0044] a center correction coefficient calculation module, configured to obtain a center pixel temperature correction coefficient based on the actual temperature at the geometric center of the area to be measured and the measured temperature at the geometric center of the area to be measured;

[0045] A position correction coefficient calculation module, configured to obtain a pixel position correction coefficient according to the position coordinates of the pixels in the temperature distribution map;

[0046] A nonlinear correction coefficient calculation module is used to obtain a pixel position nonlinear correction coefficient based on the nonlinear parameters obtained by pre-fitting and the position coordinates of the pixel;

[0047] The correction temperature calculation module is used to calculate the correction temperature of the corresponding pixel according to the pixel position nonlinear correction coefficient, the central pixel temperature correction coefficient, the pixel position correction coefficient and the measured temperature of the pixel.

[0048] Furthermore, the infrared dot matrix temperature sensor includes m rows and n columns of infrared temperature sensing units, each infrared temperature sensing unit corresponds to a pixel in the temperature distribution map, wherein m and n are both greater than or equal to 2.

[0049] Furthermore, the center pixel temperature correction coefficient is a ratio of the actual temperature at the geometric center of the area to be measured to the measured temperature at the geometric center of the area to be measured.

[0050] Furthermore, the position correction coefficient calculation module obtains the pixel position correction coefficient according to the position coordinates of the pixels in the temperature distribution map, including:

[0051] The geometric center of the area to be measured is set as the origin, the horizontal symmetry axis of the area to be measured is the X axis, and the vertical symmetry axis is the Y axis, to establish a field of view coordinate system;

[0052] Obtaining a maximum column viewing angle of the infrared dot matrix temperature sensor, and calculating a distance from the infrared dot matrix temperature sensor to the geometric center of the area to be measured based on the maximum X coordinate of the area to be measured and the maximum column viewing angle;

[0053] The distance from the infrared dot matrix temperature sensor to the geometric center of the measured area is used as the Z coordinate, and the distance from the pixel to the infrared dot matrix temperature sensor is calculated based on the X coordinate value, Y coordinate value and the Z coordinate of the pixel;

[0054] The ratio of the distance from the pixel to the infrared dot matrix temperature sensor to the Z coordinate is used as the pixel position correction coefficient.

[0055] Furthermore, the nonlinear correction coefficient calculation module pre-fits to obtain nonlinear parameters, including:

[0056] Cover the test area with the test field of view of the infrared dot matrix temperature sensor and collect the test temperature distribution map of the test area;

[0057] Obtaining the actual test temperature at the geometric center of the test field of view using a standard thermometer;

[0058] Selecting a plurality of characteristic points on the test temperature distribution diagram, obtaining the test temperatures of the characteristic points, and obtaining the test temperature at the geometric center of the test field of view;

[0059] Taking the geometric center of the test field of view as the origin, the horizontal axis of symmetry of the test field of view as the X axis, and the vertical axis of symmetry as the Y axis, a test field of view coordinate system is established to obtain the pixel coordinates of the multiple feature points;

[0060] Calculate the test center temperature correction coefficient based on the actual test temperature at the geometric center of the test field of view and the test temperature;

[0061] According to the pixel coordinates of each feature point, the feature point position correction coefficient is calculated;

[0062] Calculating a rough correction temperature of the characteristic point according to the test center temperature correction coefficient, the characteristic point position correction coefficient and the test temperature of the characteristic point;

[0063] Establish a coordinate system with the distance from the feature point to the geometric center of the test field of view as the horizontal coordinate and the temperature as the vertical coordinate;

[0064] Marking the feature point rough correction temperature and the test temperature of the feature point in the coordinate system and performing fitting to obtain an exponential function curve;

[0065] The base of the exponential function curve is obtained by calculation as the nonlinear parameter.

[0066] Furthermore, the rough correction temperature of the feature point is the product of the test center temperature correction coefficient, the feature point position correction coefficient and the test temperature of the feature point.

[0067] Furthermore, the nonlinear correction coefficient calculation module calculates the pixel position nonlinear correction coefficient according to the pre-fitted nonlinear parameters and the pixel position coordinates, including:

[0068] Calculating the distance between the pixel and the geometric center of the area to be measured based on the X-coordinate value and the Y-coordinate value of the pixel;

[0069] The nonlinear parameter is used as a base and the distance between the pixel and the geometric center of the area to be measured is used as an exponent to calculate a value to be obtained as the pixel position nonlinear correction coefficient.

[0070] Furthermore, the correction temperature of the corresponding pixel is the product of the pixel position nonlinear correction coefficient, the center pixel temperature correction coefficient, the pixel position correction coefficient and the measured temperature of the pixel.

[0071] An electronic device includes a processor and a storage device, wherein the storage device stores a plurality of instructions, and the processor is used to read the instructions and execute the above method.

[0072] The temperature correction method and device based on the infrared dot matrix temperature sensor provided by the present invention have at least the following beneficial effects:

[0073] (1) An infrared dot matrix temperature sensor is used for temperature measurement. Within the coverage range of its field of view, the measured temperature is corrected by the central temperature of the area to be measured and the position relationship of each pixel. Only one infrared dot matrix temperature sensor and one actual measurement of the central temperature are needed to achieve temperature measurement at various positions in a large area. The obtained corrected temperature error is small, which is particularly suitable for temperature measurement of terminal blocks in control cabinets, effectively reducing production costs.

[0074] (2) When measuring a surface area that is much smaller than the field of view of the infrared dot matrix thermometer, the temperature measured by the infrared dot matrix thermometer is approximately inversely proportional to the distance. By calculating and fitting the correlation coefficient based on the position and distance, and fitting the correction coefficient based on the center temperature of the field of view, the final corrected temperature error is small, which meets the requirements of terminal block temperature measurement. BRIEF DESCRIPTION OF THE DRAWINGS

[0075] Figure 1 The present invention provides a flow chart of an embodiment of a temperature correction method based on an infrared dot matrix temperature sensor.

[0076] Figure 2 The present invention provides a flow chart of an embodiment of the field of view in the temperature correction method based on the infrared dot matrix temperature sensor.

[0077] Figure 3 The present invention provides a flow chart of an embodiment of calculating pixel position correction coefficients in a temperature correction method based on an infrared dot matrix temperature sensor.

[0078] Figure 4 The present invention provides a flow chart of an embodiment of fitting nonlinear parameters in a temperature correction method based on an infrared dot matrix temperature sensor.

[0079] Figure 5 This is a flow chart of an embodiment of a temperature correction device based on an infrared dot matrix temperature sensor provided by the present invention. DETAILED DESCRIPTION

[0080] In order to better understand the above technical solution, the above technical solution will be described in detail below with reference to the accompanying drawings and specific implementation methods.

[0081] refer to Figure 1 In some embodiments, a temperature calibration method based on an infrared dot matrix temperature sensor is provided, comprising:

[0082] S1. Use an infrared dot matrix temperature sensor to collect the temperature distribution map of the area to be measured;

[0083] S2. Obtaining the actual temperature at the geometric center of the test area using a standard thermometer;

[0084] S3. Obtaining a measured temperature of each pixel according to the temperature distribution map;

[0085] S4. Obtaining a center pixel temperature correction coefficient according to the actual temperature at the geometric center of the area to be measured and the measured temperature at the geometric center of the area to be measured;

[0086] S5. Obtaining a pixel position correction coefficient according to the position coordinates of the pixels in the temperature distribution map;

[0087] S6. Obtaining a pixel position nonlinear correction coefficient based on the pre-fitted nonlinear parameters and the pixel position coordinates;

[0088] S7. Calculate and obtain the corrected temperature of the corresponding pixel based on the pixel position nonlinear correction coefficient, the center pixel temperature correction coefficient, the pixel position correction coefficient, and the measured temperature of the pixel.

[0089] Specifically, refer to Figure 2 In step S1, the infrared dot matrix temperature sensor includes m rows and n columns of infrared temperature sensing units, each infrared temperature sensing unit corresponds to a pixel in the temperature distribution map, wherein m and n are both greater than or equal to 2.

[0090] Furthermore, in step S2, the actual temperature at the geometric center of the area to be measured is obtained by a standard thermometer, and the actual temperature is used as a calculation parameter for the subsequent correction coefficient.

[0091] Furthermore, in step S3, the measured temperature of each pixel is obtained according to the temperature distribution map, that is, the measured temperature value collected by each infrared temperature sensing unit.

[0092] Furthermore, in step S4, a center pixel temperature correction coefficient is calculated based on the actual temperature and the measured temperature at the geometric center of the measured area. Specifically, the center pixel temperature correction coefficient is the ratio of the actual temperature at the geometric center of the measured area to the measured temperature at the geometric center of the measured area, as shown in the following formula:

[0093] K c =T c ÷T ic ; (1)

[0094] Among them, T c is the actual temperature at the geometric center of the measured area, T ic is the measured temperature at the geometric center of the measured area, K c is the center pixel temperature correction coefficient.

[0095] The measured temperature at the center of the measured area is relatively accurate, so it is used as the calculation basis for other pixel temperatures, and the ratio of the actual temperature at the geometric center of the measured area to the measured temperature is used as the center pixel temperature correction coefficient.

[0096] Further, refer to Figure 3 In step S5, the pixel position correction coefficient is calculated based on the position coordinates of the pixels in the temperature distribution map, including:

[0097] S51, setting the geometric center of the area to be measured as the origin, the horizontal axis of symmetry of the area to be measured as the X axis, and the vertical axis of symmetry as the Y axis, to establish a field of view coordinate system;

[0098] S52: Obtain a maximum column viewing angle of the infrared dot matrix temperature sensor, and calculate a distance from the infrared dot matrix temperature sensor to the geometric center of the area to be measured based on the maximum X coordinate in the field of view coordinate system and the maximum column viewing angle;

[0099] S53, taking the distance from the infrared dot matrix temperature sensor to the geometric center of the area to be measured as the Z coordinate, and calculating the distance from the pixel to the infrared dot matrix temperature sensor based on the X coordinate value, Y coordinate value, and the Z coordinate of the pixel;

[0100] S54: Using the ratio of the distance from the pixel to the infrared dot matrix temperature sensor to the Z coordinate as a pixel position correction coefficient.

[0101] Specifically, in step S51, the geometric center of the area to be measured is set as the origin, the horizontal axis of symmetry of the area to be measured is used as the X axis, and the vertical axis of symmetry of the area to be measured is used as the Y axis to establish a field of view coordinate system.

[0102] In step S52, the line connecting the infrared dot matrix temperature sensor to the geometric center of the area to be measured is used as the central axis. Figure 2 , obtain the angle between the central axis and the line connecting the maximum column coordinate on the X-axis to the infrared dot matrix temperature sensor. This angle is the maximum column viewing angle of the infrared dot matrix temperature sensor. Based on the maximum column viewing angle θ of the infrared dot matrix temperature sensor and the maximum X-coordinate of the area to be measured, the distance from the infrared dot matrix temperature sensor to the geometric center of the area to be measured can be calculated:

[0103] Z=X max / tanθ; (2)

[0104] Where Z represents the distance from the infrared dot matrix temperature sensor to the geometric center of the area to be measured, X max represents the maximum X coordinate, and θ represents the maximum column viewing angle of the infrared dot matrix temperature sensor.

[0105] The calculated distance from the infrared dot matrix temperature sensor to the geometric center of the area to be measured is not the distance in the actual physical space, but the distance calculated in the field of view coordinate system with the set coordinate spacing as the unit.

[0106] Furthermore, in step S53, the distance from the infrared dot matrix temperature sensor to the geometric center of the area to be measured is taken as the Z coordinate, and the distance from the pixel to the infrared dot matrix temperature sensor is calculated according to the X coordinate value, Y coordinate value and the Z coordinate of the pixel: (X 2 +Y 2 +Z 2 ) 1 / 2 .

[0107] Furthermore, in step S54, the ratio of the distance from the pixel to the infrared dot matrix temperature sensor to the Z coordinate is used as the pixel position correction coefficient, that is:

[0108] K l =((X 2 +Y 2 +Z 2 ) 1 / 2 ) / Z; (3)

[0109] Among them, K l is the pixel position correction coefficient, X is the X coordinate value of the pixel, Y is the Y coordinate value of the pixel, and Z is the Z coordinate.

[0110] When measuring a surface area that is much smaller than the field of view of the infrared dot matrix thermometer, the temperature measured by the infrared dot matrix thermometer is approximately inversely proportional to the distance. Based on this, the ratio of the distance from the pixel to the infrared dot matrix temperature sensor to the Z coordinate is used as the pixel position correction coefficient.

[0111] Further, refer to Figure 4 In step S6, pre-fitting to obtain nonlinear parameters includes:

[0112] S61, covering the test area with the test field of view of the infrared dot matrix temperature sensor, and collecting a test temperature distribution map of the test area;

[0113] S62. Obtaining the actual test temperature at the geometric center of the test field of view using a standard thermometer;

[0114] S63, selecting a plurality of characteristic points on the test temperature distribution diagram, obtaining the test temperatures of the characteristic points, and obtaining the test temperature at the geometric center of the test field of view;

[0115] S64, establishing a test view field coordinate system with the geometric center of the test view field as the origin, the horizontal symmetry axis of the test view field as the X axis, and the vertical symmetry axis as the Y axis, to obtain the pixel coordinates of the multiple feature points;

[0116] S65, calculating a test center temperature correction coefficient based on the actual test temperature at the geometric center of the test field of view and the test temperature;

[0117] S66, calculating and obtaining a feature point position correction coefficient based on the pixel coordinates of each feature point;

[0118] S67, calculating and obtaining a rough correction temperature of the characteristic point according to the test center temperature correction coefficient, the characteristic point position correction coefficient, and the test temperature of the characteristic point;

[0119] S68. Establish a coordinate system with the distance from the feature point to the geometric center of the test field of view as the abscissa and the temperature as the ordinate;

[0120] S69, marking the feature point rough correction temperature and the test temperature of the feature point in the coordinate system and performing fitting to obtain an exponential function curve;

[0121] S610: Calculate and obtain the base of the exponential function curve as the nonlinear parameter.

[0122] Specifically, in step S61, Figure 2 As shown, the test field of view of the infrared dot matrix temperature sensor covers the test area, and a test temperature distribution map of the test area is collected. In the test temperature distribution map, each pixel is the test temperature obtained by each infrared temperature sensing unit in the infrared dot matrix temperature sensor.

[0123] Furthermore, in step S62, the actual test temperature at the geometric center of the test field of view is obtained by a standard thermometer, and the actual test temperature at the geometric center of the test field of view is used as a parameter for subsequent calculation of the correction coefficient.

[0124] Furthermore, in step S63, a plurality of characteristic points are selected on the test temperature distribution map, and the test temperatures of the characteristic points are obtained, and the test temperature at the geometric center of the test field of view is obtained. Specifically, the plurality of characteristic points are evenly distributed on the test temperature distribution map, and the test temperature of each characteristic point is obtained from the test temperature distribution map.

[0125] Furthermore, in step S64, the geometric center of the test field of view is taken as the origin, that is, the horizontal axis of symmetry of the test field of view is taken as the X-axis, the vertical axis of symmetry is taken as the Y-axis, and each infrared temperature sensing unit is taken as a unit to establish a test field of view coordinate system and obtain the pixel coordinates of the multiple feature points.

[0126] Furthermore, in step S65, a test center temperature correction coefficient is calculated based on the actual test temperature and the test temperature at the geometric center of the test field of view. Specifically, the calculation can be performed using formula (1), that is, the test center temperature correction coefficient is the ratio of the actual test temperature at the geometric center of the test field of view to the test temperature at the geometric center of the test field of view.

[0127] Furthermore, in step S66, the feature point position correction coefficient is calculated based on the pixel coordinates of each feature point. Specifically, the calculation is performed according to formula (3). The distance from the feature point to the infrared dot matrix temperature sensor is calculated based on the X coordinate value, Y coordinate value and the Z coordinate of the feature point, and then the ratio of the distance to the Z coordinate is used as the feature point position correction coefficient.

[0128] Furthermore, in step S67, a rough correction temperature of the characteristic point is calculated based on the test center temperature correction coefficient, the characteristic point position correction coefficient, and the test temperature of the characteristic point. The rough correction temperature of the characteristic point is the product of the test center temperature correction coefficient, the characteristic point position correction coefficient, and the test temperature of the characteristic point, that is:

[0129] T (a,b),q = K c '×K l '×T (a,b) ; (4)

[0130] Among them, T (a,b),q is the rough correction temperature of the feature point in row a and column b, K c ' is the test center temperature correction coefficient, K l ' is the feature point position correction coefficient, T (a,b) is the test temperature of the characteristic point in row a and column b.

[0131] Furthermore, in step S68, a coordinate system is established with the distance from the feature point to the geometric center of the test field of view as the abscissa and the temperature as the ordinate.

[0132] In step S69, the rough correction temperatures T of the plurality of characteristic points obtained by calculation are (a,b),q , rather than its test temperature T (a,b) They are not equal, so the feature point rough correction temperature and the test temperature of the feature point are marked in the coordinate system and fitted to obtain an exponential function curve, the independent variable of the exponential function is the distance from the feature point to the geometric center of the test field of view, and the dependent variable is temperature.

[0133] In step S610 , the base of the exponential function curve is calculated, and the base is the nonlinear parameter.

[0134] Furthermore, in step S6, the pixel position nonlinear correction coefficient is calculated based on the pre-fitted nonlinear parameters and the pixel position coordinates, including:

[0135] S611, calculating the distance between the pixel and the geometric center of the area to be measured according to the X coordinate value and the Y coordinate value of the pixel;

[0136] S612: Using the nonlinear correction coefficient as a base and the distance between the pixel and the geometric center of the area to be measured as an exponent, a value obtained by calculation is used as the nonlinear correction coefficient for the pixel position.

[0137] Specifically, in step S611, the distance s between the pixel and the geometric center of the area to be measured is calculated based on the X coordinate value and the Y coordinate value of the pixel, that is:

[0138] s=(X 2 +Y 2 ) 1 / 2 ; (5)

[0139] Wherein, s is the distance between the pixel and the geometric center of the field of view, X is the X coordinate value of the pixel, and Y is the Y coordinate value of the pixel.

[0140] Furthermore, in step S622, the nonlinear parameter is used as a base, and the distance between the pixel and the geometric center of the area to be measured is used as an exponent to calculate a value as the pixel position nonlinear correction coefficient, specifically:

[0141] K a =a s ; (6)

[0142] Where a is the nonlinear parameter obtained by fitting, s is the distance between the pixel and the geometric center of the field of view, K a is the nonlinear correction coefficient of the pixel position.

[0143] Furthermore, in step S7, the correction temperature of the corresponding pixel is the product of the pixel position nonlinear correction coefficient, the center pixel temperature correction coefficient, the pixel position correction coefficient and the measured temperature of the pixel, specifically:

[0144] T (i，j) '= K c ×K l ×K a ×T (i，j) ; (7)

[0145] Among them, T (i，j) ' represents the corrected temperature of the pixel at row i and column j, K a is the pixel position nonlinear correction coefficient, K cis the center pixel temperature correction coefficient, K l Pixel position correction coefficient, T (i，j) is the measured temperature of the pixel at row i and column j.

[0146] The above method is further explained below through specific application scenarios.

[0147] Assume that the infrared dot matrix temperature sensor consists of 24 rows and 24 columns of infrared temperature sensing units, and each infrared temperature sensing unit outputs a measured temperature value as a pixel.

[0148] The measured temperature at the geometric center of the field of view measured by the infrared dot matrix temperature sensor is 47°C, and the actual temperature at the geometric center of the field of view collected by the standard thermometer is 53.2°C.

[0149] The pixel coordinates of the specific position to be measured are (10, 10), the measurement temperature is 22°C, and the maximum column coordinate of the field of view is X max is 12, and the maximum column viewing angle θ is 37.5°.

[0150] Center pixel temperature correction coefficient K c =53.2÷47=1.13.

[0151] Z coordinate Z = X max ÷tanθ=12÷tan37.5=15.64.

[0152] Pixel position correction coefficient K l =((X 2 +Y 2 +Z 2 ) 1 / 2 )÷Z=((10 2 +10 2 +15.64 2 ) 1 / 2 )÷15.64=1.32.

[0153] The distance s between the pixel and the geometric center of the field of view = (X 2 +Y 2 ) 1 / 2 =(102+102)1 / 2=14.14.

[0154] The nonlinear parameter obtained by fitting is 1.012, so the pixel position nonlinear correction coefficient K a =1.012 s =1.012 14.14 =1.18.

[0155] Finally calculate the corrected temperature:

[0156] T (10,10) '=Kc ×K l ×K a ×T (10,10) =1.13×1.32×1.18

[0157] ×22=38.72℃

[0158] After measurement, the corrected temperature is 38.72℃.

[0159] The measured temperature of the corresponding terminal is 40.2℃, with an error of 3.7%. The error is extremely small and the measurement is valid.

[0160] refer to Figure 5 In some embodiments, a temperature calibration device based on an infrared dot matrix temperature sensor is provided, comprising:

[0161] The temperature acquisition module 201 is used to acquire the temperature distribution map of the area to be measured using an infrared dot matrix temperature sensor;

[0162] The actual temperature acquisition module 202 is used to obtain the actual temperature at the geometric center of the test area using a standard thermometer;

[0163] A measured temperature acquisition module 203 is configured to obtain the measured temperature of each pixel according to the temperature distribution map;

[0164] A center correction coefficient calculation module 204 is configured to obtain a center pixel temperature correction coefficient based on the actual temperature at the geometric center of the area to be measured and the measured temperature at the geometric center of the area to be measured;

[0165] A position correction coefficient calculation module 205 is used to obtain a pixel position correction coefficient according to the position coordinates of the pixels in the temperature distribution map;

[0166] The nonlinear correction coefficient calculation module 206 is used to calculate the nonlinear correction coefficient of the pixel position according to the nonlinear parameters obtained by pre-fitting and the position coordinates of the pixel;

[0167] The correction temperature calculation module 206 is configured to calculate the correction temperature of the corresponding pixel based on the pixel position nonlinear correction coefficient, the center pixel temperature correction coefficient, the pixel position correction coefficient, and the measured temperature of the pixel.

[0168] Furthermore, the infrared dot matrix temperature sensor includes m rows and n columns of infrared temperature sensing units, each infrared temperature sensing unit corresponds to a pixel in the temperature distribution map, wherein m and n are both greater than or equal to 2.

[0169] Furthermore, the center pixel temperature correction coefficient is a ratio of the actual temperature at the geometric center of the area to be measured to the measured temperature at the geometric center of the area to be measured.

[0170] Furthermore, the position correction coefficient calculation module 205 calculates the pixel position correction coefficient according to the position coordinates of the pixels in the temperature distribution map, including:

[0171] The geometric center of the area to be measured is set as the origin, the horizontal symmetry axis of the area to be measured is the X axis, and the vertical symmetry axis is the Y axis, to establish a field of view coordinate system;

[0172] Obtaining a maximum column viewing angle of the infrared dot matrix temperature sensor, and calculating a distance from the infrared dot matrix temperature sensor to the geometric center of the area to be measured based on the maximum X coordinate of the area to be measured and the maximum column viewing angle;

[0173] The distance from the infrared dot matrix temperature sensor to the geometric center of the measured area is used as the Z coordinate, and the distance from the pixel to the infrared dot matrix temperature sensor is calculated based on the X coordinate value, Y coordinate value and the Z coordinate of the pixel;

[0174] The ratio of the distance from the pixel to the infrared dot matrix temperature sensor to the Z coordinate is used as the pixel position correction coefficient.

[0175] Furthermore, the nonlinear correction coefficient calculation module 206 pre-fits to obtain nonlinear parameters, including:

[0176] Cover the test area with the test field of view of the infrared dot matrix temperature sensor and collect the test temperature distribution map of the test area;

[0177] Obtaining the actual test temperature at the geometric center of the test field of view using a standard thermometer;

[0178] Selecting a plurality of characteristic points on the test temperature distribution diagram, obtaining the test temperatures of the characteristic points, and obtaining the test temperature at the geometric center of the test field of view;

[0179] Taking the geometric center of the test field of view as the origin, the horizontal axis of symmetry of the test field of view as the X axis, and the vertical axis of symmetry as the Y axis, a test field of view coordinate system is established to obtain the pixel coordinates of the multiple feature points;

[0180] Calculate the test center temperature correction coefficient based on the actual test temperature at the geometric center of the test field of view and the test temperature;

[0181] According to the pixel coordinates of each feature point, the feature point position correction coefficient is calculated;

[0182] Calculating a rough correction temperature of the characteristic point according to the test center temperature correction coefficient, the characteristic point position correction coefficient and the test temperature of the characteristic point;

[0183] Establish a coordinate system with the distance from the feature point to the geometric center of the test field of view as the horizontal coordinate and the temperature as the vertical coordinate;

[0184] Marking the feature point rough correction temperature and the test temperature of the feature point in the coordinate system and performing fitting to obtain an exponential function curve;

[0185] The base of the exponential function curve is obtained by calculation as the nonlinear parameter.

[0186] Furthermore, the rough correction temperature of the feature point is the product of the test center temperature correction coefficient, the feature point position correction coefficient and the test temperature of the feature point.

[0187] Furthermore, the nonlinear correction coefficient calculation module 206 calculates the pixel position nonlinear correction coefficient according to the pre-fitted nonlinear parameters and the pixel position coordinates, including:

[0188] Calculating the distance between the pixel and the geometric center of the area to be measured based on the X-coordinate value and the Y-coordinate value of the pixel;

[0189] The nonlinear parameter is used as a base and the distance between the pixel and the geometric center of the area to be measured is used as an exponent to calculate a value to be obtained as the pixel position nonlinear correction coefficient.

[0190] Furthermore, the correction temperature of the corresponding pixel is the product of the pixel position nonlinear correction coefficient, the center pixel temperature correction coefficient, the pixel position correction coefficient and the measured temperature of the pixel.

[0191] Please refer to the above embodiments for the specific working principle, which will not be described here in detail.

[0192] In some embodiments, an electronic device is also provided, including a processor and a storage device, wherein the storage device stores a plurality of instructions, and the processor is configured to read the instructions and execute the above method.

[0193] The temperature calibration method and device based on the infrared dot matrix temperature sensor provided in the above embodiment have at least the following beneficial effects:

[0194] (1) An infrared dot matrix temperature sensor is used for temperature measurement. Within the coverage range of its field of view, the measured temperature is corrected by the center temperature of the field of view and the position relationship of each pixel. Only one infrared dot matrix temperature sensor and one actual measurement of the center temperature are needed to achieve temperature measurement at various positions in a large area. The corrected temperature error is small, which is particularly suitable for temperature measurement of terminal blocks in control cabinets, effectively reducing production costs.

[0195] (2) When measuring a surface area that is much smaller than the field of view of the infrared dot matrix thermometer, the temperature measured by the infrared dot matrix thermometer is approximately inversely proportional to the distance. By calculating and fitting the correlation coefficient based on the position and distance, and fitting the correction coefficient based on the center temperature of the field of view, the final corrected temperature error is small, which meets the requirements of terminal block temperature measurement.

[0196] Although preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they are aware of the basic inventive concepts. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the invention. Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the invention. Thus, the present invention is intended to include such changes and modifications as fall within the scope of the claims and their equivalents.

Claims

1. A temperature correction method based on an infrared dot matrix temperature sensor, characterized in that: include: Use infrared dot matrix temperature sensor to collect the temperature distribution map of the area to be measured; Obtaining the actual temperature at the geometric center of the area to be measured using a standard thermometer; Obtaining a measured temperature of each pixel according to the temperature distribution map; Obtaining a center pixel temperature correction coefficient according to the actual temperature at the geometric center of the area to be measured and the measured temperature at the geometric center of the area to be measured; Obtaining a pixel position correction coefficient based on the position coordinates of the pixels in the temperature distribution map: setting the geometric center of the area to be measured as the origin, the horizontal axis of symmetry of the area to be measured as the X-axis, and the vertical axis of symmetry as the Y-axis to establish a field of view coordinate system; Obtaining a maximum column viewing angle of the infrared dot matrix temperature sensor, calculating a distance from the infrared dot matrix temperature sensor to the geometric center of the area to be measured based on the maximum X coordinate of the area to be measured and the maximum column viewing angle; using the distance from the infrared dot matrix temperature sensor to the geometric center of the area to be measured as a Z coordinate, calculating a distance from the pixel to the infrared dot matrix temperature sensor based on the X coordinate value, Y coordinate value, and Z coordinate of the pixel; and using a ratio of the distance from the pixel to the infrared dot matrix temperature sensor to the Z coordinate as a pixel position correction coefficient; Obtaining a pixel position nonlinear correction coefficient based on the pre-fitted nonlinear parameters and the pixel position coordinates: calculating a distance between the pixel and the geometric center of the area to be measured based on the X and Y coordinate values ​​of the pixel; The nonlinear parameter is used as a base number and the distance between the pixel and the geometric center of the area to be measured is used as an exponent to calculate a value as the pixel position nonlinear correction coefficient; The corrected temperature of the corresponding pixel is obtained by calculation according to the pixel position nonlinear correction coefficient, the central pixel temperature correction coefficient, the pixel position correction coefficient and the measured temperature of the pixel.

2. The method according to claim 1, characterized in that The infrared dot matrix temperature sensor includes m rows and n columns of infrared temperature sensing units, each infrared temperature sensing unit corresponds to a pixel in the temperature distribution map, wherein m and n are both greater than or equal to 2.

3. The method according to claim 1, characterized in that The center pixel temperature correction coefficient is the ratio of the actual temperature at the geometric center of the area to be measured to the measured temperature at the geometric center of the area to be measured.

4. The method according to claim 1, wherein Pre-fitting to obtain nonlinear parameters, including: Cover the test area with the test field of view of the infrared dot matrix temperature sensor and collect the test temperature distribution map of the test area; Obtaining the actual test temperature at the geometric center of the test field of view using a standard thermometer; Selecting a plurality of characteristic points on the test temperature distribution diagram, obtaining the test temperatures of the characteristic points, and obtaining the test temperature at the geometric center of the test field of view; Taking the geometric center of the test field of view as the origin, the horizontal axis of symmetry of the test field of view as the X axis, and the vertical axis of symmetry as the Y axis, a test field of view coordinate system is established to obtain the pixel coordinates of the multiple feature points; Calculate the test center temperature correction coefficient based on the actual test temperature at the geometric center of the test field of view and the test temperature; According to the pixel coordinates of each feature point, the feature point position correction coefficient is calculated; Calculating a rough correction temperature of the characteristic point according to the test center temperature correction coefficient, the characteristic point position correction coefficient and the test temperature of the characteristic point; Establish a coordinate system with the distance from the feature point to the geometric center of the test field of view as the horizontal coordinate and the temperature as the vertical coordinate; Marking the feature point rough correction temperature and the test temperature of the feature point in the coordinate system and performing fitting to obtain an exponential function curve; The base of the exponential function curve is obtained by calculation as the nonlinear parameter.

5. The method according to claim 4, characterized in that The rough correction temperature of the feature point is the product of the test center temperature correction coefficient, the feature point position correction coefficient and the test temperature of the feature point.

6. The method according to claim 1, characterized in that The correction temperature of the corresponding pixel is the product of the pixel position nonlinear correction coefficient, the center pixel temperature correction coefficient, the pixel position correction coefficient and the measured temperature of the pixel.

7. A temperature calibration device based on an infrared dot matrix temperature sensor applied to the method according to any one of claims 1 to 6, characterized in that: include: The temperature acquisition module is used to collect the temperature distribution map of the area to be measured using an infrared dot matrix temperature sensor; An actual temperature acquisition module is used to obtain the actual temperature at the geometric center of the test area using a standard thermometer; A measured temperature acquisition module, configured to obtain the measured temperature of each pixel according to the temperature distribution map; a center correction coefficient calculation module, configured to obtain a center pixel temperature correction coefficient based on the actual temperature at the geometric center of the area to be measured and the measured temperature at the geometric center of the area to be measured; A position correction coefficient calculation module is used to obtain a pixel position correction coefficient based on the position coordinates of the pixels in the temperature distribution map: the geometric center of the area to be measured is set as the origin, the horizontal symmetry axis of the area to be measured is the X axis, and the vertical symmetry axis is the Y axis, to establish a field of view coordinate system; Obtaining a maximum column viewing angle of the infrared dot matrix temperature sensor, calculating a distance from the infrared dot matrix temperature sensor to the geometric center of the area to be measured based on the maximum X coordinate of the area to be measured and the maximum column viewing angle; using the distance from the infrared dot matrix temperature sensor to the geometric center of the area to be measured as a Z coordinate, calculating a distance from the pixel to the infrared dot matrix temperature sensor based on the X coordinate value, Y coordinate value, and Z coordinate of the pixel; and using a ratio of the distance from the pixel to the infrared dot matrix temperature sensor to the Z coordinate as a pixel position correction coefficient; A nonlinear correction coefficient calculation module is used to obtain a nonlinear correction coefficient for a pixel position based on the pre-fitted nonlinear parameters and the pixel position coordinates: and calculate the distance between the pixel and the geometric center of the area to be measured based on the X and Y coordinate values ​​of the pixel; The nonlinear parameter is used as a base number and the distance between the pixel and the geometric center of the area to be measured is used as an exponent to calculate a value as the pixel position nonlinear correction coefficient; The correction temperature calculation module is used to calculate the correction temperature of the corresponding pixel according to the pixel position nonlinear correction coefficient, the central pixel temperature correction coefficient, the pixel position correction coefficient and the measured temperature of the pixel.

8. An electronic device, characterized in that: The method comprises a processor and a storage device, wherein the storage device stores a plurality of instructions, and the processor is configured to read the instructions and execute the method according to any one of claims 1 to 6.

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