Gearbox abnormal state monitoring method and system based on infrared imaging rate of change

Abstract

The application belongs to the technical field of gearboxes, and particularly discloses a gearbox abnormal state monitoring method and system based on infrared imaging rate of change, which collects the surface infrared thermal image of the gearbox in real time, visualizes the gradient distribution of the infrared temperature field, and determines the position information of the calibration points on the gearbox; temperature sensors are arranged at the calibration point positions on the gearbox to obtain the temperature signals of the gearbox; the difference matrix of the temperature signals of the gearbox and the infrared thermal image temperature is calculated to determine whether the maximum value of the difference matrix exceeds the preset first alarm threshold value, and the state of the measured member is preliminarily determined to be abnormal or not; the temperature field gradient image is reconstructed, the maximum temperature in the reconstructed temperature field gradient image is compared with the preset second alarm threshold value, and the state of the measured member is determined to be abnormal or not again. By using the technical scheme, the temperature field is digitally reconstructed and visualized, the gearbox temperature field gradient zone imaging is monitored and analyzed, and the abnormal state of the gearbox is detected.

Description

Technical Field

[0001] The present invention belongs to the technical field of gear boxes and relates to a method and system for monitoring abnormal conditions of a gear box based on infrared imaging change rate. Background Art

[0002] Gearboxes are one of the most fundamental and critical components in mechanical equipment, and their operating conditions directly impact the performance and lifespan of the equipment. During movement and power transmission, the transmission parts within a gearbox experience power losses such as meshing loss, oil churning loss, and windage loss. Furthermore, the components within the gearbox release significant heat during operation.

[0003] If the gearbox's lubrication system can't promptly absorb the heat released by the parts during operation, the temperature of the gearbox's components and the oil will become too high, affecting the normal operation of the gearbox. Gearbox temperature monitoring can help detect and predict internal faults and anomalies, allowing measures to be taken to prevent failures and damage caused by high temperatures.

[0004] Infrared thermal imaging technology is widely used in the field of temperature detection. Compared with traditional temperature sensors, infrared imaging offers advantages such as non-contact, large detection area, intuitive imaging, and real-time monitoring. However, due to factors such as ambient light and object material, infrared thermal imaging temperature measurement accuracy is limited, and it cannot accurately detect abnormal temperature rise in components. Therefore, calibrating and reconstructing the rate of change of infrared imaging to detect abnormal gearbox conditions is of great significance in practical engineering. Summary of the Invention

[0005] The purpose of the present invention is to provide a gearbox abnormal state monitoring method and system based on infrared imaging change rate, calibrate and reconstruct the infrared imaging change rate, and detect the abnormal state of the gearbox.

[0006] In order to achieve the above object, the basic scheme of the present invention is: a gearbox abnormal state monitoring method based on infrared imaging change rate, comprising the following steps:

[0007] Real-time acquisition of infrared thermal imaging of the gearbox surface;

[0008] Based on the image processing algorithm, the infrared thermal imaging change rate matrix is ​​calculated to visualize the infrared temperature field gradient distribution;

[0009] Determine the position information of the calibration points on the gearbox based on the gradient distribution of the infrared temperature field;

[0010] A temperature sensor is set at a calibration point on the gearbox to obtain the temperature signal of the gearbox in real time;

[0011] Calculate the difference matrix of the gear box temperature signal and the infrared thermal imaging temperature, judge whether the maximum value of the difference matrix exceeds the preset first alarm threshold, and preliminarily determine whether the state of the measured part is abnormal;

[0012] Based on the iterative least square method, the calibration function is calculated by fitting the temperature signal of the gear box, so that the square error between the fitting function and the calibration value is minimized, and a calibration matrix is established;

[0013] Combine the calibration matrix with the infrared thermal imaging rate matrix to reconstruct the temperature field gradient image, compare the maximum temperature in the reconstructed temperature field gradient image with the preset second alarm threshold, and determine again whether the state of the measured part is abnormal.

[0014] The working principle and beneficial effects of the basic scheme are that the temperature data during the operation of the gear box is monitored in real time, the infrared temperature field gradient distribution is visualized based on the image processing algorithm, and the calibration point position information is determined based on the temperature gradient.

[0015] The temperature data of the selected point position of the box body is measured by the temperature sensor, a calibration data matrix is established, and the temperature image is segmented, fitted and reconstructed based on the infrared rate. By setting the temperature abnormal threshold and the infrared imaging rate threshold, the state of the gear box is comprehensively judged, and then warning or alarm is realized, so as to realize the identification and processing of the abnormal state of the gear box.

[0016] Further, based on the image processing algorithm, the infrared thermal imaging rate matrix is calculated, and the infrared temperature field gradient distribution is visualized, and the specific steps are as follows:

[0017] Obtain the image file of the surface infrared thermal imaging of the gear box and read the image attributes;

[0018] Read the temperature raw data, construct the coordinates and temperature matrix of the pixel points;

[0019] The read temperature raw data is preprocessed to make the image temperature data conform to the actual data;

[0020] Calculate the temperature change rate matrix and determine the isotherm interval;

[0021] Draw the temperature gradient distribution graph by function algorithm.

[0022] By monitoring the temperature data during the operation of the gear box in real time, the infrared temperature field gradient distribution is visualized based on the image processing algorithm.

[0023] Further, the method for obtaining the image file of the surface infrared thermal imaging of the gear box and reading the image attributes is as follows:

[0024] After obtaining the temperature image of the infrared thermal imaging, open the file in binary read-write mode, and position at the last 36 bytes of the file.

[0025] Read the width W and height H of the image from the file, and calculate the number of pixels of the image pixels:

[0026] pixels = W * H;

[0027] Calculate the image data offset offset as:

[0028] offset = -(36 + pixels * 2 + 128);

[0029] The pixel position corresponding to the actual infrared temperature value dfd of the i-th row and j-th column ij is:

[0030] dfd ij = dfd ij / 1000+offset.

[0031] Simple operation, easy to use.

[0032] Further, the temperature change rate matrix is calculated, and the method for determining the isotheral interval is as follows:

[0033] Adjust the global processed temperature matrix to a matrix with a width of w and a height of h:

[0034]

[0035] Wherein, dfd ij represents the infrared actual temperature value corresponding to the pixel position of the i-th row and j-th column;

[0036] All image temperature data are saved in the infrared temperature original data matrix D original , the global minimum value dfd min of the matrix is calculated, and the corresponding coordinate position (a km , b km ) is defined, and the temperature change rate ΔT = is:

[0037]

[0038] Wherein, a ij , b ij ) represents the i-th row and j-th column coordinates of the coordinate matrix; a ij is the horizontal coordinate of the i-th row and j-th column of the pixel coordinate matrix, b ij is the vertical coordinate of the i-th row and j-th column of the pixel coordinate matrix; a km is the horizontal coordinate of the k-th row and m-th column of the pixel coordinate matrix; b km is the horizontal coordinate of the k-th row and m-th column of the pixel coordinate matrix;

[0039] The temperature change rate of each point relative to the lowest point is calculated in sequence, and finally the minimum point is taken as the reference value 1 to obtain the temperature change rate matrix D rate , the global minimum value ΔT min and the maximum value ΔT max of the matrix are obtained, considering the different local temperature change rates, to avoid over-dense local isotheral line drawing, the interval n of the isothermal gradient is determined as:

[0040]

[0041] The temperature equivalent point is searched, the visualization isothermal line graph with an interval of n is obtained by using the function algorithm, the number k and position coordinates (x i ,y i ) of the to-be-calibrated points are determined based on the isothermal line, and i represents the ith calibrated point.

[0042] Considering the different local temperature change rates, the interval of the isothermal gradient is determined to avoid over-dense local isothermal line drawing.

[0043] Further, based on the iterative least square method, a calibration matrix is established, and the specific steps are as follows:

[0044] The loss function S(x) is defined as:

[0045]

[0046] Wherein, r(x) is a residual function; x is a parameter to be solved; A is a sampling value of an input independent variable, that is, an infrared temperature matrix to be calibrated; F is an observed output value, that is, a calibration matrix measured by an infinite temperature sensor;

[0047] Suppose that the actual temperature is continuously changed, and the function can be linearly approximated in a certain field of x, then by Taylor expansion:

[0048] r(x0+Δ)=r(x0)+J r Δ

[0049] Wherein, X0 represents a value that can be linearly approximated, J r is a Jordan canonical form matrix converted from a residual function matrix;

[0050] Solving:

[0051]

[0052] The solution Δ of this problem is:

[0053] Δ=-(J r T J r ) -1 J r T r(x0)

[0054] By continuously iterating x to approximate it to reach the optimal solution, the maximum number of iterations k≤10 is defined:

[0055] x (k+1) =x (k) +αΔ

[0056] Among them, x (k+1) is the value of the k+1th iteration, x (k) is the value of the kth iteration, α is the iteration correction coefficient;

[0057] The fitting correction error based on the iterative least squares method meets the calibration requirements within the allowable range, and the temperature calibration matrix D is obtained. standard :

[0058]

[0059] Among them, w is the image width, h is the image length, d ij Represents the fitted temperature value of the i-th row and j-th column.

[0060] Based on the iterative least squares fitting algorithm, the temperature numerical calibration is performed by continuously iteratively updating the parameters so that the sum of the square errors between the fitting function and the calibration value is minimized.

[0061] Furthermore, based on the calibration matrix D standard , perform unit conversion and bias correction, and finally restore the reconstructed temperature data matrix D final :

[0062] D final =1000×D standard -offset×J

[0063] Where offset is the image data offset, and J represents a matrix of all ones.

[0064] Based on the reconstructed temperature data matrix, the temperature field is reconstructed and the isotherm diagram is drawn to detect whether the maximum temperature exceeds the set threshold, determine whether the gearbox is in an abnormal state, and provide early warning and timely alarm to help employees maintain equipment safety and reduce potential accidents.

[0065] The present invention also provides a gearbox abnormal state monitoring system based on the method of the present invention, comprising an infrared thermal imager, a temperature sensor, a communication module and a host computer;

[0066] The infrared thermal imager is used to thermally image the surface of the gearbox and measure the overall temperature;

[0067] The temperature sensor is installed at a calibration point position of the gear box to collect temperature signals on the gear box, and the temperature sensor is connected with the upper computer through a communication module.

[0068] The system has simple structure, realizes temperature field visualization of the collected infrared temperature image, realizes gear box temperature field gradient zone imaging monitoring, analysis and display, and realizes gear box abnormal state monitoring through temperature correction technology for calibrating and digitizing the temperature field data of the gear box.

[0069] Further, the temperature sensor is detachably connected with the outer wall of the gear box through the magnetic base.

[0070] The temperature sensor is installed through the magnetic base, and is convenient to disassemble.

[0071] Further, the control switch is installed on the gear box, and the output end of the control switch is connected with the control end of the temperature sensor.

[0072] The control switch can control the temperature sensor to start and end collection, and is more flexible to use. BRIEF DESCRIPTION OF DRAWINGS

[0073] Figure 1 is a flowchart of the gear box abnormal state monitoring method based on the infrared imaging change rate of the present application;

[0074] Figure 2 is a flowchart of the infrared temperature field gradient imaging algorithm of the gear box abnormal state monitoring method based on the infrared imaging change rate of the present application;

[0075] Figure 3 is a structural schematic diagram of the gear box abnormal state monitoring system of the present application.

[0076] The reference signs in the drawings of the specification include: gear box 1, infrared thermal imager 2, temperature sensor 3, antenna base 4, magnetic base 5, control switch 6, temperature receiver 7, upper computer 8. DETAILED DESCRIPTION

[0077] The embodiments of the present application are described in detail below, and examples of the embodiments are shown in the drawings, wherein the same or similar reference signs represent the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the drawings are exemplary, only for explaining the present application, and cannot be understood as limiting the present application.

[0078] In the description of the present application, it is understood that the terms "longitudinal", "transverse", "upper", "lower", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer" and the like indicate the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the device or element referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as a limitation of the present application.

[0079] In the description of the present application, unless otherwise specified and limited, it is necessary to explain that the terms "mounting", "connection", "connection" should be understood broadly, for example, it can be mechanical connection or electrical connection, it can be the communication between two elements inside, it can be direct connection, or indirect connection through intermediate medium, and the specific meaning of the above terms can be understood by the person skilled in the art according to the specific circumstances.

[0080] The present application discloses a gearbox abnormal state monitoring method based on infrared imaging rate of change, as shown in Figure 1 The method comprises the following steps:

[0081] Real-time acquisition of the surface infrared thermal imaging of the gearbox;

[0082] Based on the image processing algorithm, the infrared thermal imaging rate of change matrix is calculated, and the infrared temperature field gradient distribution is visualized;

[0083] Based on the infrared temperature field gradient distribution, the calibration point position information on the gearbox is determined;

[0084] Temperature sensors are set at the calibration point positions on the gearbox, and the temperature signal ΔM i of the gearbox is acquired in real time;

[0085] The difference matrix of the gearbox temperature signal and the infrared thermal imaging temperature is calculated, whether the maximum value of the difference matrix exceeds the preset first alarm threshold is judged, and whether the state of the measured member is abnormal is preliminarily determined;

[0086] Based on the iterative least square method, the calibration function is calculated by fitting the temperature signal of the gearbox, the square error between the fitting function and the calibration value is minimized, and the calibration matrix is established;

[0087] The temperature field gradient image is reconstructed by combining the calibration matrix and the infrared thermal imaging rate of change matrix, the maximum temperature in the reconstructed temperature field gradient image is compared with the preset second alarm threshold, and whether the state of the measured member is abnormal is determined again (the first determination is a preliminary determination based on the infrared imaging original data, since the data of the infrared imaging original data matrix needs to be reconstructed, the second comparison is based on the reconstructed temperature matrix. The objects of the two determinations are different, but both use whether the maximum value exceeds the threshold to determine whether the state is abnormal).

[0088] In a preferred scheme of the present application, as shown in Figure 2 Based on the image processing algorithm, the infrared thermal imaging rate of change matrix is calculated, and the infrared temperature field gradient distribution is visualized, and the specific steps are as follows:

[0089] An image file of the surface infrared thermal imaging of the gear box is obtained, and the image attribute is read;

[0090] The temperature original data is read, and the coordinates of the pixel points and the temperature matrix are constructed (the temperature image obtained by the infrared imager is imported into matlab, the jpg format file is opened in binary read-write, the temperature data matrix is extracted by using the image processing algorithm, three reference position points l, m, and n in the three infrared fields are set, the three points are not on the same straight line in the infrared image, one of the three points is selected to form a line which is always perpendicular to the other two points, and the point is defined as the coordinate matrix origin (0, 0). The actual distance between the three points is measured, the pixel distance of the three points in the infrared image is read, the scale is calculated, and the coordinates of each pixel point (a ij ,b ij ) are converted in turn to construct the pixel point coordinate matrix);

[0091] The read temperature original data is preprocessed (such as unit conversion, m℃ to ℃, and the whole is divided by 1000; the image offset is calculated, and the temperature matrix is reduced by the offset), so that the image temperature data conforms to the actual data;

[0092] The temperature rate of change matrix is calculated, and the isotheral interval is determined;

[0093] The temperature gradient distribution graph is drawn by a function algorithm.

[0094] By monitoring the temperature data during the operation of the gear box in real time, the infrared temperature field gradient distribution can be visualized based on the image processing algorithm.

[0095] In a preferred scheme of the present application, the method for obtaining the image file of the surface infrared thermal imaging of the gear box and reading the image attribute is as follows:

[0096] After obtaining the temperature image of the infrared thermal imaging, the file is opened in binary read-write mode, and positioning is performed at the last 36 bytes of the file.

[0097] Read the width W and height H of the image from the file (read as int16 type), and calculate the number of pixels of the image pixels:

[0098] pixels = W * H;

[0099] Calculate the image data offset offset as:

[0100] offset = -(36 + pixels * 2 + 128);

[0101] The original data unit is m℃, the global processing is converted to ℃, and the actual infrared temperature value dfd corresponding to the pixel position of the i-th row and the j-th column ij :

[0102] dfd ij = dfd ij / 1000+offset;

[0103] First, calculate the image data offset, the original data unit of the infrared temperature image is millidegrees Celsius, in order to unify the unit, divide the temperature value extracted from the infrared image by 1000 to convert it to the unit of Celsius, and then add the offset to obtain the actual infrared temperature value dfd ij .

[0104] In a preferred scheme of the present application, the temperature change rate matrix is calculated, and the method for determining the isotheral interval is as follows:

[0105] The temperature matrix after global processing is adjusted to a matrix with a width of w and a height of h:

[0106]

[0107] Wherein, dfd ij represents the actual infrared temperature value corresponding to the pixel position of the i-th row and the j-th column;

[0108] All image temperature data are saved in the infrared temperature original data matrix D original , the global minimum value dfd min of the matrix is calculated, and the corresponding coordinate position (a km , b km ) is calculated, and the temperature change rate ΔT = is defined as:

[0109]

[0110] Wherein, (a ij , b ij ) represents the i-th row and j-th column coordinates of the coordinate matrix; a ij is the horizontal coordinate of the i-th row and j-th column of the pixel coordinate matrix, and bij is the vertical coordinate of the pixel point coordinate matrix in the i-th row and j-th column; a km is the horizontal coordinate of the pixel point coordinate matrix in the k-th row and m-th column; b km is the horizontal coordinate of the pixel point coordinate matrix in the k-th row and m-th column;

[0111] The temperature change rates of each point relative to the lowest point are sequentially calculated, and finally the minimum value point is taken as a reference value 1 to obtain a temperature change rate matrix D rate , the global minimum value ΔT min and the maximum value ΔT max of the matrix are obtained, considering that the local temperature change rates are different, in order to avoid that the local isotherms are drawn too densely, the interval n of the isotherm gradient is determined as:

[0112]

[0113] The temperature equivalent points are searched, the visualization isotherm graph with an interval of n is obtained by using a function algorithm, the number k and the position coordinates (x i , y i ) of the to-be-calibrated points are determined based on the isotherms, and i represents the i-th calibration point.

[0114] In a preferred scheme of the present application, a calibration matrix is established based on an iterative least square method, and the specific steps are as follows:

[0115] The loss function S(x) is defined as:

[0116]

[0117] Wherein, r(x) is a residual function; x is a parameter to be solved; A is a sampling value of an input independent variable, that is, an infrared temperature matrix to be calibrated; F is an observed output value, that is, a calibration matrix measured by an infinite temperature sensor;

[0118] It is assumed that the actual temperature is continuously changed, and the function can be linearly approximated in a certain field of x, so that there is:

[0119] r(x0+Δ)=r(x0)+J r Δ

[0120] Wherein, X0 represents a value that can be linearly approximated, and J r is a Jordan standard matrix converted from a residual function matrix;

[0121] Solving:

[0122]

[0123] The solution Δ of this problem is:

[0124] Δ=-(J r TJ r ) -1 J r T r(x0)

[0125] By continuously iterating x to approximate it to reach the optimal solution, the maximum number of iterations k≤10 is defined:

[0126] x (k+1) =x (k) +αΔ

[0127] Among them, x (k+1) is the value of the k+1th iteration, x (k) is the value of the kth iteration, α is the iteration correction coefficient;

[0128] The fitting correction error based on the iterative least squares method meets the calibration requirements within the allowable range, and the temperature calibration matrix D is obtained. standard :

[0129]

[0130] Among them, w is the image width, h is the image length, d ij Represents the fitted temperature value of the i-th row and j-th column.

[0131] Preferably, based on the calibration matrix D standard , perform unit conversion and bias correction, and finally restore the reconstructed temperature data matrix D final (Regenerate temperature image):

[0132] D final =1000×D standard -offset×J

[0133] Where offset is the image data offset, and J is a matrix of all ones. The coefficient is 1000, and the unit is converted to millidegrees Celsius. This is the inverse operation of the initial processing to regenerate the temperature image.

[0134] Finally, based on the reconstructed temperature matrix, the temperature field is reconstructed and an isotherm diagram is drawn to detect whether the maximum temperature exceeds the set threshold, determine whether the gearbox is in an abnormal state, and issue early warnings and timely alarms to help employees maintain equipment safety and reduce potential accidents.

[0135] The present invention also provides a gearbox abnormal state monitoring system based on the method of the present invention, such as Figure 3 As shown, it includes an infrared thermal imager 2, a temperature sensor 3, a communication module and a host computer 8. The infrared thermal imager 2 is used to thermally image the surface of the gearbox 1 and measure the overall temperature. The infrared thermal imager 2 is equipped with a tripod for easy installation and positioning.

[0136] The temperature sensor 3 is installed at a calibration point of the gear box 1 to collect a temperature signal on the gear box 1, and is electrically connected to the upper computer 8 through a communication module. The communication module can adopt an antenna seat 4 and a temperature receiver 7, the antenna seat 4 transmits data of the temperature sensor 3, and the temperature receiver 7 (such as Zigbee) receives the temperature data transmitted by the antenna seat 4 and transmits to the upper computer 8. The upper computer 8 can adopt a computer or the like to receive, store, analyze and display data.

[0137] The system has the characteristics of infrared temperature gradient display, high collection efficiency, accurate temperature calibration and the like, and realizes imaging monitoring, analysis, display and compensation correction of the temperature field gradient zone of the gear box 1 by carrying out temperature field digital reconstruction and visual modeling on the collected infrared image, which well meets the temperature monitoring requirement of the gear box 1 in industrial application.

[0138] In a preferred scheme of the present application, the gear box 1 abnormal state monitoring system further comprises a magnetic seat 5, and the temperature sensor 3 is detachably connected to the outer wall of the gear box 1 through the magnetic seat 5.

[0139] The temperature sensor 3 is installed on the gear box 1 through the wireless magnetic attraction method of the magnetic seat 5, and is convenient to disassemble.

[0140] In a preferred scheme of the present application, the gear box 1 abnormal state monitoring system further comprises a control switch 6, the control switch 6 is fixedly installed (such as welded, bonded or the like) on the gear box 1, and an output end of the control switch 6 is electrically connected to a control end of the temperature sensor 3.

[0141] The control switch 6 can control the temperature sensor 3 to start and end collection, and is more flexible to use.

[0142] In the description of the present application, the description of the terms "one embodiment", "some embodiments", "example", "specific example" or "some examples" means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In the present application, the illustrative description of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0143] Although the embodiments of the present application have been shown and described, those skilled in the art can understand that various changes, modifications, replacements and variations can be made to the embodiments without departing from the principles and purposes of the present application, and the scope of the present application is defined by the claims and their equivalents.

Claims

1. A method for monitoring abnormal condition of a gearbox based on infrared imaging change rate, characterized in that: The steps include: Real-time acquisition of infrared thermal imaging of the gearbox surface; Based on the image processing algorithm, the infrared thermal imaging change rate matrix is ​​calculated to visualize the infrared temperature field gradient distribution; Determine the position information of the calibration points on the gearbox based on the gradient distribution of the infrared temperature field; A temperature sensor is set at a calibration point on the gearbox to obtain the temperature signal of the gearbox in real time; Calculate the difference matrix between the gearbox temperature signal and the infrared thermal imaging temperature, determine whether the maximum value of the difference matrix exceeds the preset first alarm threshold, and preliminarily determine whether the state of the tested part is abnormal; Based on the iterative least squares method, the calibration function is fitted to the temperature signal of the gearbox to minimize the sum of square errors between the fitting function and the calibration value, and a calibration matrix is ​​established. Combining the calibration matrix with the infrared thermal imaging change rate matrix, the temperature field gradient image is reconstructed. The maximum temperature in the reconstructed temperature field gradient image is compared with the preset second alarm threshold to determine again whether the state of the test piece is abnormal; Based on the iterative least squares method, the calibration matrix is ​​established. The specific steps are: Define the loss function S(x) as: Among them, r(x) is the residual function; x is the substitution parameter; A is the sample value of the input independent variable, that is, the infrared temperature matrix to be calibrated; F is the observed output value, that is, the calibration matrix measured by the temperature sensor; Assuming that the actual temperature changes continuously and the function can be linearly approximated in a certain range of x, the Taylor expansion is: r(x0+Δ)=r(x0)+J r Δ Among them, x0 represents the value that can be linearly approximated, J r The Jordan standard form matrix transformed from the residual function matrix; Solution: The solution to this problem is: Δ=-(J r T J r ) -1 J r T r(x0) By continuously iterating x to approximate it to reach the optimal solution, the maximum number of iterations k≤10 is defined: x (k+1) =x (k) +aD Among them, x (k+1) is the value of the k+1th iteration, x (k) is the value of the kth iteration, α is the iteration correction coefficient; Δ is the offset relative to x0; The fitting correction error based on the iterative least squares method meets the calibration requirements within the allowable range, and the temperature calibration matrix D is obtained. standard : Among them, w is the image width, h is the image length, d ij Represents the fitted temperature value of row i and column j; Based on the calibration matrix D standard , perform unit conversion and bias correction, and finally restore the reconstructed temperature data matrix D final : D final =1000×D standard -offset×J Where offset is the image data offset, and J represents a matrix of all ones.

2. The method for monitoring abnormal condition of a gearbox based on infrared imaging change rate according to claim 1, characterized in that: Based on the image processing algorithm, the infrared thermal imaging change rate matrix is ​​calculated to visualize the infrared temperature field gradient distribution. The specific steps are as follows: Obtain the infrared thermal imaging image file of the gearbox surface and read the image attributes; Read the original temperature data and construct the pixel coordinates and temperature matrix; Preprocess the read temperature raw data to make the image temperature data consistent with the actual data; Calculate the temperature change rate matrix and determine the isotherm interval; The temperature gradient distribution diagram is drawn through the function algorithm.

3. The method for monitoring abnormal condition of a gearbox based on infrared imaging change rate according to claim 2, characterized in that: The method for obtaining the infrared thermal imaging image file of the gearbox surface and reading the image attributes is: After obtaining the temperature image of infrared thermal imaging, open the file in binary read-write mode and locate the 36 bytes from the end of the file; Read the width W and height H of the image from the file and calculate the number of pixels in the image: pixels = W* pixels = W * H; Calculate the image data offset as: offset=-(36+pixels*2+128); The actual infrared temperature value dfd corresponding to the pixel position in the i-th row and j-th column ij for: dfd ij =dfd ij / 1000+offset。 4. The method for monitoring abnormal condition of a gearbox based on infrared imaging change rate according to claim 3, characterized in that: The method for calculating the temperature change rate matrix and determining the isotherm interval is as follows: Resize the globally processed temperature matrix into a matrix with width w and height h: Among them, dfd ij Indicates the actual infrared temperature value corresponding to the pixel position in the i-th row and j-th column; All image temperature data are stored in the infrared temperature raw data matrix D original Find the global minimum value dfd of the matrix min And the corresponding coordinate position (a km ,b km ), define the temperature change rate ΔT as: Among them, (a ij , b ij ) represents the coordinate of the i-th row and j-th column of the coordinate matrix; a ij is the horizontal coordinate of the pixel point coordinate matrix in row i and column j, b ij is the vertical coordinate of the pixel point coordinate matrix in row i and column j; a km is the horizontal coordinate of the kth row and mth column of the pixel coordinate matrix; b km The horizontal coordinate of the kth row and mth column of the pixel coordinate matrix; Calculate the temperature change rate of each point relative to the lowest point in turn, and finally take the minimum point as the reference value 1 to obtain the temperature change rate matrix D rate , find the global minimum value ΔT of the matrix min and maximum ΔT max , taking into account the different local temperature change rates, in order to avoid over-dense drawing of local isotherms, the interval n of the isothermal gradient is determined as: Search for temperature equal value points, use the function algorithm to visualize the isotherm graph with an interval of n, and determine the number k of points to be calibrated and the position coordinates (x i ,y i ), i represents the i-th calibration point.

5. A gearbox abnormal state monitoring system based on the method according to any one of claims 1 to 4, characterized in that: Including infrared thermal imager, temperature sensor, communication module and host computer; The infrared thermal imager is used to thermally image the surface of the gearbox and measure the overall temperature; The temperature sensor is installed at a calibration point position of the gear box and is used to collect temperature signals on the gear box. The temperature sensor is connected to the host computer through a communication module.

6. The gearbox abnormal state monitoring system according to claim 5, characterized in that: It also includes a magnetic base, and the temperature sensor is detachably connected to the outer wall of the gear box through the magnetic base.

7. The gearbox abnormal state monitoring system according to claim 5, characterized in that: It also includes a control switch, which is installed on the gear box, and the output end of the control switch is connected to the control end of the temperature sensor.

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