Photo-thermal backboard flatness detection method and device based on multi-source sensor

Abstract

The invention discloses a photothermal backboard flatness detection method and device based on a multi-source sensor, and the method comprises the steps: obtaining target pose data corresponding to a photothermal backboard and a standard dynamic plane, calculating a deviation parameter between each measurement point in the target pose data and a corresponding reference point in the standard dynamic plane, and obtaining a deviation parameter set, determining historical attitude change data, fusing the historical attitude change data with the deviation parameter set to obtain a target flatness distribution diagram, determining flatness parameters corresponding to the target flatness distribution diagram, and if the flatness parameters meet preset parameter conditions, determining the flatness of the target flatness distribution diagram based on the target flatness distribution diagram and the deviation parameter set. And generating a flatness detection report of the photo-thermal backboard. Through the method, the target pose data of the photo-thermal back plate is compared with the standard dynamic plane, so that the determined deviation data set is more accurate, a more accurate target flatness distribution diagram is obtained in combination with the historical pose transformation data, and the accuracy of photo-thermal back plate flatness detection is improved.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of photothermal back plates, and in particular to a photothermal back plate flatness detection method and device based on a multi-source sensor. BACKGROUND

[0002] In the technical field of photothermal back plates, in order to improve energy utilization and promote green development, a solar photothermal collector is usually used to collect solar energy, and the core component of the solar photothermal collector is a photothermal back plate. The flatness of the photothermal back plate directly affects the safety and performance of the solar photothermal collector.

[0003] In a traditional manner, position coordinates corresponding to each measurement point of the photothermal back plate are obtained, the position coordinates corresponding to each measurement point are converted from a sensor coordinate system to a measurement coordinate system, which can be a world coordinate system, and in a preset reference plane, reference points corresponding to the measurement points in the photothermal back plate are obtained. The flatness corresponding to the photothermal back plate is determined by calculating the distance parameters between the measurement points and the reference points.

[0004] In actual application, when the day-night temperature difference is large, the photothermal back plate will locally deform due to changes in temperature and humidity, causing changes in the spatial posture of the photothermal back plate, so that the difference between the measured flatness and the true flatness is too large, resulting in low accuracy of the flatness detection of the photothermal back plate. SUMMARY

[0005] The application provides a photothermal back plate flatness detection method and device based on a multi-source sensor, which improves the accuracy of the flatness detection of the photothermal back plate.

[0006] In a first aspect, the application provides a photothermal back plate flatness detection method based on a multi-source sensor, which comprises: obtaining target pose data corresponding to a photothermal back plate and a standard dynamic plane, wherein the target pose data is time series data collected based on target acquisition configuration; calculating deviation parameters between each measurement point in the target pose data and a corresponding reference point in the standard dynamic plane to obtain a set of deviation parameters; determining historical attitude change data, fusing the historical attitude change data with the set of deviation parameters to obtain a target flatness distribution map; determining a flatness parameter corresponding to the target flatness distribution map, and if the flatness parameter meets a preset parameter condition, generating a flatness detection report of the photothermal back plate based on the target flatness distribution map and the set of deviation parameters.

[0007] In a possible design, the target pose data corresponding to the photothermal back plate is obtained, comprising: acquire three-axis acceleration data and three-axis angular velocity data corresponding to the photothermal backboard; perform time alignment processing on the three-axis acceleration data and the three-axis angular velocity data to obtain initial pose data; convert the initial pose data from a sensor coordinate system to a space reference coordinate system to obtain the target pose data.

[0008] In a possible design, the target pose data is time series data collected based on a target collection configuration, and includes: acquire environmental influence data corresponding to the photothermal backboard, and extract an initial collection frequency and an initial scanning density from the target collection configuration; determine an environmental parameter corresponding to the environmental influence data, determine a preset collection frequency corresponding to a preset environmental parameter consistent with the environmental parameter based on a mapping relationship between preset environmental parameters and preset collection frequencies, and determine the preset collection frequency corresponding to the preset environmental parameter consistent with the environmental parameter as the target collection frequency; collect time series data corresponding to each measurement point in the photothermal backboard based on the target collection frequency and the initial scanning density, and generate the target pose data corresponding to the photothermal backboard.

[0009] In a possible design, the acquisition of the standard dynamic plane corresponding to the photothermal backboard includes: determine a current spatial attitude parameter corresponding to the photothermal backboard from the target pose data; determine a relative displacement vector and a rotation angle difference value based on the current spatial attitude parameter and a preset calibration attitude parameter; determine a first change rate value corresponding to the relative displacement vector and a second change rate value corresponding to the rotation angle difference value, and if the first change rate value is greater than a displacement change rate threshold and the second change rate value is greater than an angle change rate threshold, determine stable orientation change data; generate the standard dynamic plane based on the stable orientation change data and a space transformation matrix, wherein the space transformation matrix is determined based on the current spatial attitude parameter and the preset calibration attitude parameter.

[0010] In a possible design, the generation of the standard dynamic plane based on the stable orientation change data and the space transformation matrix includes: generate an initial standard dynamic plane based on the stable orientation change data and the space transformation matrix; determine a normal vector corresponding to the initial standard dynamic plane, and calculate an angle value between the normal vector and a preset normal vector; If the angle value is greater than a preset angle value, the initial standard dynamic plane is adjusted to obtain the standard dynamic plane.

[0011] In a possible design, the calculation of the deviation parameter set includes: determining respective measurement point coordinates of each measurement point in the target pose data, and determining respective reference point coordinates of each reference point in the standard dynamic plane, where the measurement points in the target pose data and the reference points in the standard dynamic plane correspond one-to-one; calculating a respective relative displacement parameter of each measurement point based on the measurement point coordinates of the measurement point and the corresponding reference point coordinates; and calculating a respective rotation angle difference value of each measurement point based on the measurement point coordinates of the measurement point and the corresponding reference point coordinates; generating the deviation parameter set based on the respective relative displacement parameter and the rotation angle difference value of each measurement point.

[0012] In a possible design, the fusion of the historical pose change data and the deviation parameter set includes: performing smoothing processing on the deviation parameter set to obtain a smoothed deviation parameter set; determining a smoothed deviation parameter corresponding to the smoothed deviation parameter set, and performing interpolation processing on the smoothed deviation parameter set to obtain a stable deviation parameter set if the smoothed deviation parameter is greater than a preset smoothed deviation parameter; fusing the historical pose change data and the stable deviation parameter set to obtain the target flatness distribution map.

[0013] In a possible design, the determination of the flatness parameter corresponding to the target flatness distribution map includes: determining a respective deviation parameter of each measurement region in the target flatness distribution map; determining a standard deviation and a mean value corresponding to the photothermal backboard based on the respective deviation parameter of each measurement region; determining the standard deviation and the mean value as the flatness parameter.

[0014] In a second aspect, the present application provides a photothermal backboard flatness detection device based on a multi-source sensor, which comprises: an acquisition module configured to acquire target pose data corresponding to a photothermal backboard and a standard dynamic plane, where the target pose data is time series data collected based on a target collection configuration. a calculation module, configured to calculate a deviation parameter between each measurement point in the target posture data and a corresponding reference point in the standard dynamic plane, to obtain a deviation parameter set; a fusion module, configured to determine historical posture change data, and fuse the historical posture change data with the deviation parameter set to obtain a target flatness distribution map; The detection module is used to determine the flatness parameters corresponding to the target flatness distribution map, and if the flatness parameters meet the preset parameter conditions, generate a flatness detection report for the solar thermal backplane based on the target flatness distribution map and the deviation parameter set.

[0015] In one possible design, the acquisition module is specifically used to obtain the three-axis acceleration data and three-axis angular velocity data corresponding to the solar thermal backplane, time-align the three-axis acceleration data and the three-axis angular velocity data to obtain initial posture data, and convert the initial posture data from the sensor coordinate system to the spatial reference coordinate system to obtain the target posture data.

[0016] In one possible design, the acquisition module is also used to obtain the environmental impact data corresponding to the photothermal backplane, and extract the initial acquisition frequency and the initial scanning density from the target acquisition configuration, determine the environmental parameters corresponding to the environmental impact data, determine the preset acquisition frequency corresponding to the preset environmental parameters consistent with the environmental parameters based on the mapping relationship between the preset environmental parameters and the preset acquisition frequency, determine the preset acquisition frequency corresponding to the preset environmental parameters consistent with the environmental parameters as the target acquisition frequency, and acquire the time series data corresponding to each measurement point in the photothermal backplane based on the target acquisition frequency and the initial scanning density to generate the target posture data corresponding to the photothermal backplane.

[0017] In one possible design, the acquisition module is also used to determine the current spatial posture parameters corresponding to the solar thermal backplane from the target posture data, determine the relative displacement vector and the rotation angle difference based on the current spatial posture parameters and the preset calibration posture parameters, determine the first change rate value corresponding to the relative displacement vector, and the second change rate value corresponding to the rotation angle difference, if the first change rate value is greater than the displacement change rate threshold, and the second change rate value is greater than the angle change rate threshold, then determine the stable orientation change data, and generate the standard dynamic plane based on the stable orientation change data and the spatial transformation matrix, wherein the spatial transformation matrix is ​​determined based on the current spatial posture parameters and the preset calibration posture parameters.

[0018] In a possible design, the acquisition module is further configured to generate an initial standard dynamic plane based on the stable orientation change data and the spatial transformation matrix, determine a normal vector corresponding to the initial standard dynamic plane, calculate an angle value between the normal vector and a preset normal vector, and adjust the initial standard dynamic plane to obtain the standard dynamic plane if the angle value is greater than a preset angle value.

[0019] In a possible design, the calculation module is specifically configured to determine respective measurement point coordinates of respective measurement points in the target pose data, and determine respective reference point coordinates of respective reference points in the standard dynamic plane, where the measurement points in the target pose data and the reference points in the standard dynamic plane are in one-to-one correspondence, calculate respective relative displacement parameters of the respective measurement points based on the measurement point coordinates of the respective measurement points and the corresponding reference point coordinates, calculate respective rotation angle difference values of the respective measurement points based on the measurement point coordinates of the respective measurement points and the corresponding reference point coordinates, and generate the deviation parameter set based on the respective relative displacement parameters and the rotation angle difference values of the respective measurement points.

[0020] In a possible design, the fusion module is specifically configured to perform smoothing processing on the deviation parameter set to obtain a smoothed deviation parameter set, determine a smoothed deviation parameter corresponding to the smoothed deviation parameter set, perform interpolation processing on the smoothed deviation parameter set to obtain a stable deviation parameter set if the smoothed deviation parameter is greater than a preset smoothed deviation parameter, and fuse the historical pose change data and the stable deviation parameter set to obtain the target flatness distribution map.

[0021] In a possible design, the detection module is specifically configured to determine respective deviation parameters of respective measurement regions in the target flatness distribution map, determine a standard deviation and a mean value corresponding to the photothermal backboard based on the respective deviation parameters of the respective measurement regions, and determine the standard deviation and the mean value as the flatness parameter.

[0022] In a third aspect, the present application provides an electronic device, comprising: a memory configured to store a computer program; a processor configured to execute the computer program stored in the memory to implement the steps of the flatness detection method for a photothermal backboard based on multiple source sensors.

[0023] In a fourth aspect, a computer readable storage medium stores a computer program, and the computer program is executed by a processor to implement the steps of the flatness detection method for a photothermal backboard based on multiple source sensors.

[0024] The above-mentioned aspects and the technical effects that can be achieved by the aspects are described above in relation to the first aspect or the various possible solutions of the first aspect, and will not be repeated here. BRIEF DESCRIPTION OF DRAWINGS

[0025] Figure 1 A flow chart of a method for detecting the flatness of a photothermal backplane based on a multi-source sensor is provided in the present application. Figure 2 A structural schematic diagram of a device for detecting the flatness of a photothermal backplane based on a multi-source sensor is provided in the present application. Figure 3 A structural schematic diagram of an electronic device is provided in the present application. DETAILED DESCRIPTION

[0026] In order to make the purposes, technical solutions and advantages of the present application clearer, the present application will be described in further detail below with reference to the accompanying drawings. The specific operation methods in the method embodiments can also be applied to the device embodiments or system embodiments. It should be noted that in the description of the present application, "multiple" is understood as "at least two". The "and / or" describes the association relationship of the associated objects, which means that there can be three relationships, for example, A and / or B can represent the three cases of A alone, A and B together, and B alone. A is connected to B, which means that A is directly connected to B and A is connected to B through C. In addition, in the description of the present application, "first", "second", etc. are used only for the purpose of distinguishing the description, and cannot be understood as indicating or implying relative importance, nor can it be understood as indicating or implying order.

[0027] In the prior art, the position coordinates corresponding to each measurement point of the photothermal backplane are obtained, the position coordinates corresponding to each measurement point are converted from the sensor coordinate system to the measurement coordinate system, which can be the world coordinate system, and in the preset reference plane, the reference points corresponding to the measurement points in the photothermal backplane are obtained, the distance parameters between the measurement points and the reference points are calculated to determine the flatness corresponding to the photothermal backplane. When the day-night temperature difference is large, the photothermal backplane will change locally due to changes in temperature and humidity, causing changes in the spatial attitude of the photothermal backplane, resulting in a large difference between the measured flatness and the true flatness, and leading to low accuracy of the flatness detection of the photothermal backplane.

[0028] To solve the problems described above, the embodiment of the present application provides a light-thermal backboard flatness detection method based on a multi-source sensor, which realizes accurate detection of the light-thermal backboard flatness. The method and device of the embodiment of the present application are based on the same technical concept. Since the principles of the problems solved by the method and device are similar, the embodiments of the device and the method can be mutually referred to, and the repeated parts will not be described again.

[0029] In the following, the embodiment one of the present application is described in detail with reference to the accompanying drawings.

[0030] With reference to Figure 1 The present application provides a light-thermal backboard flatness detection method based on a multi-source sensor, which can realize accurate detection of the light-thermal backboard flatness. The implementation process of the method is as follows: Step S1: Obtain target pose data corresponding to the light-thermal backboard and a standard dynamic plane.

[0031] In order to ensure the accuracy of the light-thermal backboard flatness detection, the system needs to obtain three-axis acceleration data and three-axis angular velocity data corresponding to the light-thermal backboard through the inertial sensor. Both the three-axis acceleration data and the three-axis angular velocity data are marked with a time stamp. The three-axis acceleration data and the three-axis angular velocity data are time-aligned to obtain initial pose data.

[0032] For example: the three-axis acceleration data includes: 0.4 m / s² for the x-axis, 0.2 m / s² for the y-axis, and 0.08 m / s² for the z-axis. The three-axis angular velocity data includes: 0.1 degrees per second around the x-axis, 0.12 degrees per second around the y-axis, and 0.03 degrees per second around the z-axis.

[0033] In one possible design, in order to reduce the influence of noise, the system needs to fuse the three-axis acceleration data and the three-axis angular velocity data to obtain the initial pose data. The fusion method can be a Kalman filter method. Since the Kalman filter method is a well-known technology to those skilled in the art, it will not be described in detail here.

[0034] Determine the acceleration vector corresponding to the initial pose data, calculate the included angle between the acceleration vector and the gravity direction, and if the included angle is less than a preset included angle, it represents that the light-thermal backboard is in a relatively stable state. Then, the initial pose data is converted from the sensor coordinate system to the space reference coordinate system to obtain the target pose data. The embodiment of the present application can realize the conversion of the coordinate system based on the quaternion method, thereby avoiding the singularity problem of Euler angles.

[0035] For example: the deflection angle of a certain measurement point in the sensor coordinate system is 1.5 degrees, the pitch angle is 1.0 degree, and the roll angle is 0.5 degree. The deflection angle of 1.5 degrees, the pitch angle of 1.0 degree, and the roll angle of 0.5 degree are converted from the sensor coordinate system to the space reference coordinate system to obtain the deflection angle of 2.0 degrees, the pitch angle of 1.3 degrees, and the roll angle of 0.7 degrees.

[0036] Further, when collecting target pose data, the embodiment of the present application can collect time sequence data corresponding to the light-heat backboard based on the target collection configuration. In order to prevent the influence of environmental interference on flatness detection, environmental influence data corresponding to the light-heat backboard needs to be obtained. The environmental influence data can be illumination intensity, temperature and humidity. The environmental influence data can also be set according to actual conditions, which will not be described here.

[0037] The initial collection frequency and the initial scanning density are extracted from the target collection configuration. The embodiment of the present application pre-stores environmental parameters corresponding to different environmental influence data. Thus, the environmental parameters corresponding to the environmental influence data are determined, and the embodiment of the present application pre-stores a mapping relationship between the preset environmental parameters and the preset collection frequency. The environmental parameters are matched with the pre-stored preset environmental parameters to obtain the preset environmental parameters consistent with the environmental parameters. The preset collection frequency corresponding to the matched preset environmental parameters is determined as the target collection frequency corresponding to the environmental parameters.

[0038] For example, the actual temperature is 36 degrees Celsius, the actual humidity exceeds 80%, the initial collection rate is 1 time per minute, the preset temperature is 30 degrees Celsius, the preset humidity is 70%, and the preset collection frequency is 2 times per minute. 36>30, 80%>70%, the system automatically increases 1 time per minute to 2 times per minute to monitor environmental changes more frequently.

[0039] The time sequence data corresponding to each measurement point in the light-heat backboard is collected according to the target collection frequency and the initial scanning density, and the target pose data is generated based on all the time sequence data.

[0040] In order to realize the flatness detection of the light-heat backboard, the embodiment of the present application also needs to obtain the standard dynamic plane corresponding to the light-heat backboard. The specific acquisition process is as follows: The current spatial attitude parameter corresponding to the light-heat backboard is determined from the target pose data. The current spatial attitude parameter is the degree of freedom spatial state of the light-heat backboard in the spatial reference coordinate system. The current spatial attitude parameter includes a position parameter and an attitude parameter. The position parameter can be represented by coordinates, and the attitude parameter can be represented in any one of the forms of quaternions, rotation matrices and Euler angles. The preset calibration attitude parameter is determined. Based on the preset calibration attitude parameter, each reference point can be determined, and a preset dynamic plane can be further generated based on each reference point. Based on the current spatial attitude parameter and the preset calibration attitude parameter, a relative displacement vector and a rotation angle difference value are determined. The relative displacement vector reflects the height offset of the light-heat backboard surface in different regions, and the rotation angle difference value represents the inclination degree of the light-heat backboard relative to the preset calibration plane.

[0041] The mapping relationship between the measurement point and the reference point can be achieved based on vertical projection, the measurement point is projected vertically in the preset dynamic plane, the projected point is determined as the reference point, thereby establishing the mapping relationship between the measurement point and the reference point, or determining the distance between the measurement point and each reference point within the preset distance range, screening the reference point corresponding to the minimum distance, establishing the mapping relationship between the reference point with the minimum distance and the measurement point, and then determining the relative position vector corresponding to the measurement point and the reference point. The rotation angle difference between the local photothermal backboard and the preset calibration plane can be calculated based on the quaternion. The local photothermal backboard can be the area corresponding to a single measurement point.

[0042] The application embodiment in the present application calculates the rotation angle difference between the local photothermal backboard and the preset calibration plane based on the quaternion, which is well known to those skilled in the art. Therefore, it is not described in detail here.

[0043] Further, the first change rate value corresponding to the relative displacement vector is determined, and the second change rate value corresponding to the rotation angle difference is determined. The displacement change rate threshold is the derivative of the relative displacement vector between the measurement point and the corresponding reference point with respect to time, and the angle change rate threshold is the derivative of the rotation angle difference between the measurement point and the corresponding reference point in the photothermal backboard with respect to time. The change rate value corresponding to the relative displacement vector can be determined based on the laser Doppler velocimetry method, and the change rate value corresponding to the rotation angle difference can be determined based on the fiber gyroscope.

[0044] When the first change rate value is greater than the displacement change rate threshold, and when the second change rate value is greater than the angle change rate threshold, the displacement change rate threshold can be 0.01 m / s, and the angle change rate threshold can be 0.5 degrees / s. The three-axis acceleration data and the three-axis angular velocity data are extracted from the target pose data, and the three-axis acceleration data and the three-axis angular velocity data are smoothed to obtain stable orientation change data.

[0045] In one possible design, the deflection angle of the photothermal backboard is determined from the stable orientation change data. If the deflection angle is greater than a preset deflection angle, the driving motor is adjusted to correct the direction of the photothermal backboard, thereby improving the positioning accuracy and response capability of the photothermal backboard in a dynamic environment.

[0046] The first homogeneous matrix corresponding to the preset calibration attitude parameter is determined, and the second homogeneous matrix corresponding to the current space attitude parameter is determined. The inverse matrix of the first homogeneous matrix and the second homogeneous matrix is multiplied to obtain a space matrix. The space matrix is determined as a space transformation matrix, and based on the stable orientation transformation data and the space transformation matrix, a standard dynamic plane is generated. The standard dynamic plane is a plane that moves smoothly in time in the space reference coordinate system.

[0047] In a possible design, based on the stable orientation change data and the spatial transformation matrix, an initial standard dynamic plane is generated, a normal vector corresponding to the initial standard dynamic plane is determined, an angle value between the normal vector and a preset normal vector is calculated, if the angle value is less than a preset angle value, it means that the initial standard dynamic plane meets the preset plane accuracy, and the initial standard dynamic plane is determined as the standard dynamic plane, if the angle value is greater than the preset angle value, the initial standard dynamic plane is adjusted until the angle value is less than the preset angle value, and the adjusted initial standard dynamic plane is determined as the standard dynamic plane.

[0048] Through the above method, the target acquisition configuration of the target pose data is determined based on the environmental influence data, avoiding the influence of the environmental influence data on the flatness detection, ensuring the accuracy of the target pose data, and obtaining the standard dynamic plane, ensuring the accuracy of the standard dynamic plane, which is conducive to the accuracy of the flatness detection of the photothermal backboard.

[0049] Step S2: Calculate the deviation parameter between each measurement point in the target pose data and the corresponding reference point in the standard dynamic plane to obtain a set of deviation parameters.

[0050] After determining the standard dynamic plane, the measurement point coordinates corresponding to each measurement point in the target pose data are determined, and the reference point coordinates of the reference points corresponding to each measurement point are determined. There is a mapping relationship between the measurement points and the reference points. The relative displacement parameters between the measurement point coordinates of each measurement point and the corresponding reference point coordinates are calculated. In order to determine the deviation between the photothermal backboard and the standard dynamic plane, the plane pose data corresponding to the standard dynamic plane needs to be determined. The pose data corresponding to each measurement point is determined from the target pose data, and the pose data of the reference points corresponding to each measurement point is determined from the plane pose data. Based on the pose data corresponding to the measurement points and the pose data of the reference points, the rotation angle difference between the measurement points and the reference points is calculated. Based on the relative displacement parameters and the rotation angle difference corresponding to each measurement point, a set of deviation parameters is generated.

[0051] Through the above method, the standard dynamic plane corresponding to the photothermal backboard is determined. The standard dynamic plane can adjust the attitude in real time due to the deformation caused by the temperature change of the photothermal backboard, so that the standard dynamic plane is close to the actual attitude of the photothermal backboard, ensuring the accuracy of the flatness detection of the photothermal backboard.

[0052] Step S3: Determine the historical attitude change data, fuse the historical attitude change data and the set of deviation parameters to obtain a target flatness distribution map.

[0053] In order to improve the adaptability of the system, the historical attitude change data is needed, which is the attitude change sequence of the light and heat backboard over time. In order to prevent the deviation parameter set from containing abnormal measurement points, the deviation parameters in the deviation parameter set need to be smoothed to obtain a smoothed deviation parameter set. The historical attitude change data and the deviation data set are fused to obtain a target flatness distribution map, so as to quantify the cumulative effect of the historical deformation on the current attitude, and further improve the accuracy of the light and heat backboard flatness detection.

[0054] The smoothing process in the embodiments of the application can be realized based on the average value filtering method. Since the average value filtering method is a known technology for those skilled in the art, it will not be described in detail here.

[0055] In a possible design, the deviation parameter set is smoothed to obtain a smoothed deviation parameter set, thereby filtering random noise and improving the authenticity of the smoothed deviation parameter set of the light and heat backboard. The smoothed deviation parameter corresponding to the smoothed deviation parameter set can be the average value or standard deviation of all deviation parameters in the smoothed deviation parameter set. If the smoothed deviation parameter is greater than a preset smoothed deviation parameter, the smoothed deviation parameter set is interpolated to obtain a stable deviation parameter set. The historical attitude change data and the stable deviation parameter set are fused to obtain a target flatness distribution map.

[0056] For example, the deviation parameter sequence of the A region is 0.8, 0.9, 1.2, and 0.7 cm, which is smoothed to 0.85 cm after average value filtering, thereby reflecting a more stable deviation trend.

[0057] If the smoothed deviation parameter in the smoothed deviation parameter set is 1.5 cm higher than the preset deviation parameter 1.0 cm, the smoothed deviation data is grid processed by a two-dimensional interpolation algorithm. After interpolation, a 100x100 grid is generated, each grid point corresponds to a deviation parameter, which is the average value of all deviation parameters in the network. An intuitive target flatness distribution map is generated based on the deviation parameter corresponding to each grid point. The target flatness distribution map can clearly show the distribution rule of the high deviation region.

[0058] By the above method, the historical attitude change data and the deviation parameter set are fused to obtain a target flatness distribution map, thereby determining the continuity rule of the dynamic process of the light and heat backboard attitude change based on the target flatness distribution map, which is beneficial to improve the accuracy of the light and heat backboard flatness detection.

[0059] Step S4: Determine the flatness parameter corresponding to the target flatness distribution map. If the flatness parameter meets the preset parameter condition, generate a flatness detection report of the light and heat backboard based on the target flatness distribution map and the deviation parameter set.

[0060] In order to realize the optimization of the target flatness distribution map, it is necessary to determine the flatness parameters corresponding to the target flatness distribution map, and the determination process of the flatness parameters is as follows: Determine the deviation parameters corresponding to each measurement area in the target flatness distribution map. The measurement area can be an area corresponding to a measurement point, or an area corresponding to multiple measurement points. When the measurement area contains multiple measurement points, the deviation parameter of the measurement area is the average value of the deviation parameters corresponding to the multiple measurement points. Based on the deviation parameters corresponding to each measurement area, the standard deviation and the average value corresponding to the light-thermal backboard are calculated. Since the calculation process of the standard deviation and the average value is known to those skilled in the art, it is not described in detail here. The standard deviation and the average value are determined as the flatness parameters, and the quantification of the flatness is realized through the standard deviation and the average value.

[0061] For example, the standard deviation of the target flatness distribution map is 0.3 cm, and the average value is 0.7 cm, indicating that the surface is overall flat but locally has slight undulations.

[0062] The preset parameter condition in the embodiment of the application can be that the actual difference between the standard deviation and the average value is less than the preset difference. If the flatness parameters meet the preset parameter condition, it means that the actual difference is less than the preset difference, then the relative displacement parameters and the rotation angle difference values are extracted from the deviation parameter set, and based on the target flatness distribution map, the relative displacement parameters and the rotation angle difference values, a flatness detection report of the light-thermal backboard is generated.

[0063] If the flatness parameters do not meet the preset parameter condition, it means that the actual difference is greater than the preset difference, then the target acquisition configuration is updated to obtain an updated target acquisition configuration, the target pose data is re-acquired based on the updated target acquisition configuration to obtain updated target pose data, and the flatness detection report corresponding to the updated target pose data is determined according to the above process. Since the determination process of the flatness detection report corresponding to the updated target pose data is consistent with the process described above, it is not described in detail here.

[0064] It should be noted that when re-acquiring the target pose data, it is necessary to ensure that the environmental influence data of the re-acquired target pose data is consistent with the environmental influence data of the target pose data, so as to avoid introducing new interference factors.

[0065] For example, the target acquisition frequency in the target acquisition configuration is 1000 times per second, the initial scanning density is 10 points per square centimeter, the determined actual difference is 2.5 centimeters, the preset difference is 1.0 centimeter, and 2.5 centimeters > 1.0 centimeter. At this time, the target acquisition frequency is increased from 1000 times per second to 2000 times per second, and the initial scanning density is adjusted from 10 points per square centimeter to 20 points per square centimeter. The updated target acquisition configuration can capture more subtle surface changes of the light-heat backboard, especially in areas with large local fluctuations at the edge of the light-heat backboard, ensuring more comprehensive data coverage.

[0066] Through the above method, the target acquisition configuration is determined based on the environmental influence data, and the target pose data of the light-heat backboard is obtained based on the target acquisition configuration. The target acquisition configuration can be adjusted based on the environmental influence data, ensuring the accuracy of the target pose data, and determining a dynamic standard dynamic plane. The standard dynamic plane is more consistent with the actual pose change of the light-heat backboard. The historical attitude change data and the deviation parameter set are fused to generate a target flatness distribution map. The attitude of the light-heat backboard is predicted based on the target flatness distribution map, thereby ensuring the accuracy of the light-heat backboard flatness detection.

[0067] Based on the same inventive concept, the present application also provides a light-heat backboard flatness detection device based on a multi-source sensor. The encryption transmission device is used to realize the function of a light-heat backboard flatness detection method based on a multi-source sensor. Referring to Figure 2 , the device comprises: The acquisition module 201 is configured to acquire target pose data corresponding to a light-heat backboard and a standard dynamic plane. The target pose data is time series data collected based on a target acquisition configuration. The calculation module 202 is configured to calculate the deviation parameters between each measurement point in the target pose data and the corresponding reference point in the standard dynamic plane, and obtain a deviation parameter set. The fusion module 203 is configured to determine historical attitude change data, fuse the historical attitude change data with the deviation parameter set, and obtain a target flatness distribution map. The detection module 204 is configured to determine a flatness parameter corresponding to the target flatness distribution map. If the flatness parameter meets a preset parameter condition, a flatness detection report of the light-heat backboard is generated based on the target flatness distribution map and the deviation parameter set.

[0068] In a possible design, the acquisition module 201 is specifically configured to acquire three-axis acceleration data and three-axis angular velocity data corresponding to the photothermal backboard, perform time alignment processing on the three-axis acceleration data and the three-axis angular velocity data to obtain initial pose data, and convert the initial pose data from a sensor coordinate system to a space reference coordinate system to obtain the target pose data.

[0069] In a possible design, the acquisition module 201 is further configured to acquire environmental influence data corresponding to the photothermal backboard, extract an initial acquisition frequency and an initial scanning density from the target acquisition configuration, determine an environmental parameter corresponding to the environmental influence data, determine a preset acquisition frequency corresponding to a preset environmental parameter consistent with the environmental parameter based on a mapping relationship between preset environmental parameters and preset acquisition frequencies, determine the preset acquisition frequency corresponding to the preset environmental parameter consistent with the environmental parameter as the target acquisition frequency, and acquire time sequence data corresponding to each measurement point in the photothermal backboard based on the target acquisition frequency and the initial scanning density to generate the target pose data corresponding to the photothermal backboard.

[0070] In a possible design, the acquisition module 201 is further configured to determine a current space attitude parameter corresponding to the photothermal backboard from the target pose data, determine a relative displacement vector and a rotation angle difference value based on the current space attitude parameter and a preset calibration attitude parameter, determine a first change rate value corresponding to the relative displacement vector and a second change rate value corresponding to the rotation angle difference value, determine stable orientation change data if the first change rate value is greater than a displacement change rate threshold value and the second change rate value is greater than an angle change rate threshold value, and generate the standard dynamic plane based on the stable orientation change data and a space transformation matrix, where the space transformation matrix is determined based on the current space attitude parameter and the preset calibration attitude parameter.

[0071] In a possible design, the acquisition module 201 is further configured to generate an initial standard dynamic plane based on the stable orientation change data and the space transformation matrix, determine a normal vector corresponding to the initial standard dynamic plane, calculate an angle value between the normal vector and a preset normal vector, adjust the initial standard dynamic plane to obtain the standard dynamic plane if the angle value is greater than a preset angle value.

[0072] In a possible design, the calculation module 202 is specifically configured to determine respective measurement point coordinates of respective measurement points in the target pose data, and determine respective reference point coordinates of respective reference points in the standard dynamic plane, the measurement points in the target pose data correspond to the reference points in the standard dynamic plane in a one-to-one manner, calculate respective relative displacement parameters of the respective measurement points based on the measurement point coordinates of the respective measurement points and the corresponding reference point coordinates, calculate respective rotation angle difference values of the respective measurement points based on the measurement point coordinates of the respective measurement points and the corresponding reference point coordinates, and generate the set of deviation parameters based on the respective relative displacement parameters and the rotation angle difference values of the respective measurement points.

[0073] In a possible design, the fusion module 203 is specifically configured to perform smoothing processing on the set of deviation parameters to obtain a set of smoothed deviation parameters, determine a smoothed deviation parameter corresponding to the set of smoothed deviation parameters, perform interpolation processing on the set of smoothed deviation parameters to obtain a set of stable deviation parameters if the smoothed deviation parameter is greater than a preset smoothed deviation parameter, and fuse the historical pose change data and the set of stable deviation parameters to obtain the target flatness distribution map.

[0074] In a possible design, the detection module 204 is specifically configured to determine respective deviation parameters of respective measurement regions in the target flatness distribution map, determine a standard deviation and an average value corresponding to the photothermal backboard based on the respective deviation parameters of the respective measurement regions, and determine the standard deviation and the average value as the flatness parameter.

[0075] Based on the same inventive concept, the embodiment of the present application also provides an electronic device, which can realize the functions of the foregoing photothermal backboard flatness detection device based on multiple source sensors, and the electronic device is not limited to the foregoing Figure 3 , and the electronic device comprises: at least one processor 301 and a memory 303 connected with the at least one processor 301, and the specific connection medium between the processor 301 and the memory 303 is not limited in the embodiment of the present application, Figure 3 In the embodiment of the present application, the connection between the processor 301 and the memory 303 is taken as an example of connection through a bus 300. The bus 300 is represented by a thick line in Figure 3 , and the connection mode between other components is only schematically illustrated and is not limited. The bus 300 can be divided into an address bus, a data bus, a control bus and the like, and for the convenience of representation, Figure 3 In the embodiment of the present application, only one thick line is used to represent the bus 300, but it does not mean that there is only one bus or only one type of bus. Alternatively, the processor 301 can also be referred to as a controller, and the name is not limited.

[0076] In the embodiments of the present application, the memory 303 stores instructions executable by the at least one processor 301, and the at least one processor 301 can execute the foregoing method for detecting flatness of a photothermal backplane based on a multi-source sensor by executing the instructions stored in the memory 303. The processor 301 can realize the functions of various modules of the apparatus shown in the embodiments of the present application. Figure 2 The functions of various modules of the apparatus shown in the embodiments of the present application.

[0077] The processor 301 is the control center of the apparatus, can connect various parts of the control device through various interfaces and lines, and can realize the overall monitoring of the system by running or executing the instructions stored in the memory 303 and calling the data stored in the memory 303, thereby realizing the functions and processing data of the system.

[0078] In a possible design, the processor 301 can include one or more processing units, and the processor 301 can integrate an application processor and a modem processor, where the application processor mainly processes an operating system, a user interface, and an application program, and the modem processor mainly processes wireless communication. It can be understood that the modem processor can also not be integrated into the processor 301. In some embodiments, the processor 301 and the memory 303 can be implemented on the same chip, and in some embodiments, they can also be implemented on separate chips respectively.

[0079] The processor 301 can be a general-purpose processor, for example, a central processing unit (CPU), a digital signal processor, an application-specific integrated circuit, a field programmable gate array, or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component, and can realize or execute the methods, steps, and logic block diagrams disclosed in the embodiments of the present application. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method for detecting flatness of a photothermal backplane based on a multi-source sensor disclosed in the embodiments of the present application can be directly embodied as execution of a hardware processor or execution of a combination of hardware and software modules in the processor.

[0080] The memory 303, as a non-volatile computer readable storage medium, can be used to store non-volatile software programs, non-volatile computer executable programs and modules. The memory 303 can include at least one type of storage medium, for example, can include flash memory, hard disk, multimedia card, card type memory, random access memory (RAM), static random access memory (SRAM), programmable read-only memory (PROM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), magnetic storage, magnetic disk, optical disk, etc. The memory 303 is any other medium capable of carrying or storing desired program code in the form of instructions or data structures and capable of being accessed by a computer, but is not limited thereto. The memory 303 in the embodiments of the present application can also be a circuit or any other device capable of realizing a storage function, used for storing program instructions and / or data.

[0081] By designing and programming the processor 301, the code corresponding to the light-thermal backboard flatness detection method based on multiple source sensors introduced in the foregoing embodiments can be solidified into the chip, so that the chip can execute the light-thermal backboard flatness detection method based on multiple source sensors when running. Figure 1 The processor 301 is designed and programmed to perform the light-thermal backboard flatness detection method based on multiple source sensors in the embodiments shown. How to design and program the processor 301 is a technology known to those skilled in the art, which will not be described here.

[0082] Based on the same inventive concept, the embodiments of the present application also provide a storage medium storing computer instructions, when the computer instructions run on a computer, the computer instructions make the computer execute the light-thermal backboard flatness detection method based on multiple source sensors discussed above.

[0083] In some possible implementations, the various aspects of the light-thermal backboard flatness detection method based on multiple source sensors provided by the present application can also be implemented in the form of a program product, which includes program code for causing the control device to execute the steps of the light-thermal backboard flatness detection method based on multiple source sensors according to various exemplary embodiments of the present application described above in the specification when the program product runs on the device.

[0084] Those skilled in the art will appreciate that embodiments of the present application can be readily used as software, hardware, or a combination of software and hardware. In one

[0085] The present application is described in reference to the flow diagrams and / or block diagrams of methods, apparatus (systems) and computer program products according to this application. It will be understood that each block of the flow diagrams and / or block diagrams, and combinations of blocks in the flow diagrams and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flow diagrams and / or block diagrams block or blocks. Figure 1 one or more functions specified in the flow diagram and / or block diagram block or blocks. Figure 1 one or more functions specified in the flow diagram and / or block diagram block or blocks.

[0086] These computer program instructions can also be stored in a computer- readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instructions which implement the flow diagram and / or block diagram block or blocks. Figure 1 one or more functions specified in the flow diagram and / or block diagram block or blocks. Figure 1 one or more functions specified in the flow diagram and / or block diagram block or blocks.

[0087] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the flow diagram and / or block diagram block or blocks. Figure 1 one or more functions specified in the flow diagram and / or block diagram block or blocks. Figure 1 one or more functions specified in the flow diagram and / or block diagram block or blocks.

[0088] Obviously, numerous modifications and variations of the present application are possible in light of the above teachings. It is therefore to be understood that within the scope of the apparatus and methods disclosed herein, equivalents and substitutions thereof could be made by one of ordinary skill in the art without departing from the spirit and scope of the application. Any and all such modifications and variations are intended to be included herein within the scope of the present application and the present expressive equivalents thereof.

Claims

1. A method for detecting the flatness of a photothermal backplane based on multi-source sensors, characterized in that, The method comprises the following steps: acquiring target pose data corresponding to the photothermal backboard and a standard dynamic plane, wherein the target pose data is time series data collected based on a target collection configuration; calculating deviation parameters between each measurement point in the target pose data and a corresponding reference point in the standard dynamic plane to obtain a set of deviation parameters; determining historical attitude change data, fusing the historical attitude change data with the set of deviation parameters to obtain a target flatness distribution map; determining a flatness parameter corresponding to the target flatness distribution map, and if the flatness parameter meets a preset parameter condition, generating a flatness detection report of the photothermal backboard based on the target flatness distribution map and the set of deviation parameters.

2. The method of claim 1, wherein, The acquisition of the target pose data corresponding to the photothermal backboard comprises: acquiring three-axis acceleration data and three-axis angular velocity data corresponding to the photothermal backboard; performing time alignment processing on the three-axis acceleration data and the three-axis angular velocity data to obtain initial pose data; converting the initial pose data from a sensor coordinate system to a space reference coordinate system to obtain the target pose data.

3. The method of claim 1, wherein, The target pose data is time series data collected based on a target collection configuration, comprising: acquiring environmental influence data corresponding to the photothermal backboard, and extracting an initial collection frequency and an initial scanning density from the target collection configuration; determining an environmental parameter corresponding to the environmental influence data, determining a preset collection frequency corresponding to a preset environmental parameter consistent with the environmental parameter based on a mapping relationship between preset environmental parameters and preset collection frequencies, and determining the preset collection frequency corresponding to the preset environmental parameter consistent with the environmental parameter as a target collection frequency; collecting time series data corresponding to each measurement point in the photothermal backboard based on the target collection frequency and the initial scanning density to generate the target pose data corresponding to the photothermal backboard.

4. The method of claim 1, wherein, The acquisition of the standard dynamic plane corresponding to the photothermal backboard comprises: determining a current spatial attitude parameter corresponding to the photothermal backboard from the target pose data; determining a relative displacement vector and a rotation angle difference value based on the current spatial attitude parameter and a preset calibration attitude parameter; determining a first change rate value corresponding to the relative displacement vector and a second change rate value corresponding to the rotation angle difference value, and if the first change rate value is greater than a displacement change rate threshold value and the second change rate value is greater than an angle change rate threshold value, determining stable orientation change data; generating the standard dynamic plane based on the stable orientation change data and a space transformation matrix.

5. The method of claim 4, wherein, The generation of the standard dynamic plane based on the stable orientation change data and the space transformation matrix comprises: generating an initial standard dynamic plane based on the stable orientation change data and the space transformation matrix; determining a normal vector corresponding to the initial standard dynamic plane, and calculating an angle value between the normal vector and a preset normal vector; if the angle value is greater than a preset angle value, adjusting the initial standard dynamic plane to obtain the standard dynamic plane.

6. The method of claim 1, wherein, The calculating the deviation parameters between each measurement point in the target pose data and the corresponding reference point in the standard dynamic plane obtains a deviation parameter set, comprising: determining the respective measurement point coordinates of each measurement point in the target pose data, and determining the respective reference point coordinates of each reference point from the standard dynamic plane, wherein the measurement points in the target pose data correspond one-to-one to the reference points in the standard dynamic plane; calculating the respective relative displacement parameters of each measurement point based on the measurement point coordinates of the respective measurement points and the corresponding reference point coordinates; and calculating the respective rotation angle difference values of each measurement point based on the measurement point coordinates of the respective measurement points and the corresponding reference point coordinates; generating the deviation parameter set based on the respective relative displacement parameters and the rotation angle difference values of each measurement point.

7. The method of claim 1, wherein, The fusing the historical attitude change data with the deviation parameter set obtains a target flatness distribution map, comprising: smoothing the deviation parameter set to obtain a smoothed deviation parameter set; determining the smoothed deviation parameter corresponding to the smoothed deviation parameter set, and if the smoothed deviation parameter is greater than a preset smoothed deviation parameter, interpolating the smoothed deviation parameter set to obtain a stable deviation parameter set; fusing the historical attitude change data with the stable deviation parameter set to obtain the target flatness distribution map.

8. The method of claim 1, wherein, The determining the flatness parameter corresponding to the target flatness distribution map comprises: determining the respective deviation parameters of each measurement region in the target flatness distribution map; determining the standard deviation and the mean value corresponding to the photothermal backboard based on the respective deviation parameters of each measurement region; determining the standard deviation and the mean value as the flatness parameter.

9. A multi-source sensor-based photothermal backplane flatness detection device, characterized in that, Comprising: an acquisition module configured to acquire target pose data corresponding to a photothermal backboard and a standard dynamic plane, wherein the target pose data is time series data collected based on a target collection configuration; a calculation module configured to calculate deviation parameters between each measurement point in the target pose data and the corresponding reference point in the standard dynamic plane, to obtain a deviation parameter set; a fusion module configured to determine historical attitude change data, and fuse the historical attitude change data with the deviation parameter set to obtain a target flatness distribution map; a detection module configured to determine a flatness parameter corresponding to the target flatness distribution map, and if the flatness parameter meets a preset parameter condition, generate a flatness detection report of the photothermal backboard based on the target flatness distribution map and the deviation parameter set.

10. An electronic device, comprising: Comprising: a memory configured to store a computer program; a processor configured to execute the computer program stored on the memory, to implement the method steps of any one of claims 1-8.

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