Test method, device and storage medium of high-power electronic fan heat dissipation structure

Abstract

The application discloses a kind of high-power electronic fan heat dissipation structure test method, equipment and storage medium, the method comprises: identifying the heat dissipation module of being composed of multiple heat dissipation structures in high-power electronic fan;Control heat source equipment simulates multiple automobile engines in turn to promote real-time temperature value;If real-time temperature value reaches multiple sampling temperature values in turn, then multiple frames of original infrared image data are collected to high-power electronic fan in turn;In each frame of original infrared image data, filter out the background information related to sampling temperature value, obtain candidate infrared image data;Multiple frames of candidate infrared image data are fused as target infrared image data;According to the multiple frames of target infrared image data of multiple heat dissipation modules, generate heat dissipation performance distribution chart;According to heat dissipation performance distribution chart, generate heat dissipation test report to multiple heat dissipation modules.This embodiment provides objective performance data basis for the design of heat dissipation structure, improves the heat dissipation efficiency of high-power electronic fan.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of computer vision, and in particular to a test method, device and storage medium for a high-power electronic fan heat dissipation structure. BACKGROUND

[0002] With the development of new energy vehicles, the power of automobile motors is getting larger and larger, and the heat generated is also getting larger and larger. Installing 3-4 small-power electronic fans on a car can meet the demand for heat dissipation.

[0003] With the increasing demand of the host factory for thermal management, the host factory now gradually uses one large-power electronic fan to replace the original 3-4 small-power electronic fans, simplifies the overall volume of the electronic fan, and reduces the cost of the electronic fan.

[0004] On the basis of small-power electronic fans, manufacturers develop large-power electronic fans, which need to reconfigure the heat dissipation design of the electronic fan. There are many structures related to heat dissipation in the electronic fan, and the R&D personnel select the heat dissipation structure according to experience. However, there is a certain error in manual experience, which leads to low heat dissipation efficiency of the large-power electronic fan. SUMMARY

[0005] Therefore, the present application provides a test method, device and storage medium for a high-power electronic fan heat dissipation structure, to improve the accuracy of selecting a heat dissipation structure for a high-power electronic fan.

[0006] The first aspect of the present application provides a test method for a high-power electronic fan heat dissipation structure, the high-power electronic fan being a cooling electronic fan for an automobile engine and having a power greater than a threshold value, and the method comprising:

[0007] identifying a heat dissipation module composed of a plurality of heat dissipation structures in the high-power electronic fan;

[0008] controlling the heat source device to simulate a plurality of automobile engine temperature values in sequence when the high-power electronic fan is installed on the heat source device;

[0009] if the real-time temperature value reaches a plurality of sampling temperature values in sequence, then a plurality of frames of original infrared image data are collected for the high-power electronic fan in sequence;

[0010] filtering out background information related to the sampling temperature value in each frame of the original infrared image data to obtain candidate infrared image data;

[0011] fusing a plurality of frames of the candidate infrared image data into target infrared image data;

[0012] The heat dissipation performance distribution map is generated according to multiple frames of the target infrared image data of the multiple heat dissipation modules; and the heat dissipation performance distribution map describes distribution information of heat dissipation performance of the multiple heat dissipation modules in multiple automobile generators.

[0013] A heat dissipation test report is generated according to the heat dissipation performance distribution map and the multiple heat dissipation modules.

[0014] The second aspect of the present application provides a testing device for a high-power electronic fan heat dissipation structure, the high-power electronic fan is an automobile engine cooling electronic fan and has a power greater than a threshold value, and the device comprises:

[0015] A heat dissipation module identification module is configured to identify a heat dissipation module composed of multiple heat dissipation structures in the high-power electronic fan;

[0016] A heat source control module is configured to control a heat source device to simulate multiple automobile engine temperature values in sequence when the high-power electronic fan is installed on the heat source device;

[0017] An original infrared image data acquisition module is configured to acquire multiple frames of original infrared image data of the high-power electronic fan in sequence if the real-time temperature values reach multiple sampling temperature values in sequence;

[0018] A candidate infrared image data generation module is configured to filter out background information related to the sampling temperature values from each frame of the original infrared image data to obtain candidate infrared image data;

[0019] A target infrared image data fusion module is configured to fuse multiple frames of the candidate infrared image data into target infrared image data;

[0020] A heat dissipation performance distribution map generation module is configured to generate a heat dissipation performance distribution map according to multiple frames of the target infrared image data of the multiple heat dissipation modules; and the heat dissipation performance distribution map describes distribution information of heat dissipation performance of the multiple heat dissipation modules in multiple automobile generators;

[0021] A heat dissipation test report generation module is configured to generate a heat dissipation test report according to the heat dissipation performance distribution map and the multiple heat dissipation modules.

[0022] The third aspect of the present application provides an electronic device, which comprises:

[0023] at least one processor; and

[0024] a memory in communication connection with the at least one processor; wherein

[0025] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to perform the test method of the high-power electronic fan heat dissipation structure as described in the first aspect above.

[0026] A fourth aspect of the present application provides a computer-readable storage medium storing a computer program, and the computer program is executed by a processor to implement the test method of the high-power electronic fan heat dissipation structure as described in the first aspect above.

[0027] A fifth aspect of the present application provides a computer program product comprising a computer program, and the computer program is executed by a processor to implement the test method of the high-power electronic fan heat dissipation structure as described in the first aspect above.

[0028] In the embodiment, a heat dissipation module composed of multiple heat dissipation structures in the high-power electronic fan is identified; when the high-power electronic fan is installed to a heat source device, the heat source device is controlled to simulate multiple automobile engines to increase real-time temperature values in sequence; in each simulation process, if the real-time temperature values reach multiple sampling temperature values in sequence, multiple frames of original infrared image data of the high-power electronic fan are collected in sequence; background information related to the sampling temperature values is filtered out from each frame of original infrared image data to obtain candidate infrared image data; the multiple frames of candidate infrared image data are fused into target infrared image data; a heat dissipation performance distribution map is generated according to the multiple frames of target infrared image data of the multiple heat dissipation modules; the heat dissipation performance distribution map describes distribution information of heat dissipation performances of the multiple heat dissipation modules in the multiple automobile engines; and a heat dissipation test report is generated for the multiple heat dissipation modules according to the heat dissipation performance distribution map. The embodiment tests the heat dissipation performances of different heat dissipation structures in the high-power electronic fan in different automobile engines, uses the heat dissipation performance distribution map to reflect the change trend of the heat dissipation performances, provides objective performance data basis for the design of the heat dissipation structure, reduces errors caused by manual experience, and thus improves the heat dissipation efficiency of the high-power electronic fan.

[0029] It should be understood that the content described in this part is not intended to identify key or important features of the embodiments of the present application, nor is it used to limit the scope of the present application. Other features of the present application will become apparent from the following description. BRIEF DESCRIPTION OF DRAWINGS

[0030] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without creative labor.

[0031] Figure 1 is a flow chart of a test method of a high-power electronic fan heat dissipation structure provided by the embodiment one of the present application.

[0032] Figure 2 is a front view of a high-power electronic fan provided by the embodiment one of the present application.

[0033] Figure 3 is a back view of a high-power electronic fan provided by the embodiment one of the present application.

[0034] Figure 4 is an exploded view of a high-power electronic fan provided by the embodiment one of the present application.

[0035] Figure 5 is a running state curve diagram of a high-power electronic fan provided by the embodiment one of the present application.

[0036] Figure 6 is an example diagram of a temperature control function provided by the embodiment one of the present application.

[0037] Figure 7 is a structural schematic diagram of a test device of a high-power electronic fan heat dissipation structure provided by the embodiment two of the present application.

[0038] Figure 8 is a structural schematic diagram of an electronic device provided by the embodiment three of the present application. DETAILED DESCRIPTION

[0039] In order to make the personnel in the art better understand the present application scheme, the technical scheme in the embodiment of the present application will be described clearly and completely below by combining the drawings in the embodiment of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by the person skilled in the art without creative labor should belong to the scope of protection of the present application.

[0040] It should be noted that the terms "first", "second" and the like in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily indicate a specific order or sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can cover the order of implementation other than those illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device including a series of steps or units does not necessarily limit to those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0041] Embodiment One

[0042] Referring to Figure 1 , a flow chart of a testing method of a high-power electronic fan heat dissipation structure provided by Embodiment One of the present application is shown, which can be executed by a high-power electronic fan heat dissipation structure testing device, which can be realized in the form of hardware and / or software, and can be configured in an electronic device. As shown in Figure 1 , the method comprises:

[0043] Step 101, identifying a heat dissipation module composed of multiple heat dissipation structures in a high-power electronic fan.

[0044] In this embodiment, the high-power electronic fan is an automobile engine cooling electronic fan, wherein high-power refers to power greater than a threshold value (e.g. 1400W).

[0045] Specifically, high-power automotive electronic fan (refrigeration) refers to a fan product composed of fan blades as the main body and matched with metal supporting plates and other accessories for automobile engine cooling heat dissipation.

[0046] High-power automotive electronic fan (refrigeration) prevents automobile engine overheating and maintains the optimal working temperature of the air conditioning system by discharging hot air and promoting efficient heat exchange, ensuring the smooth and reliable operation of the automobile engine and air conditioning function.

[0047] Exemplarily, the maximum air volume of one 1500W high-power electronic fan is usually greater than the air volume of three 800W low-power electronic fans (i.e. greater than 12000m³ / h at 100Pa), and the maximum air volume of one 2000W high-power electronic fan is usually greater than the air volume of four 800W low-power electronic fans (i.e. greater than 16000m³ / h at 100Pa).

[0048] The heat dissipation structures (i.e. parts for heat dissipation) in different models of high-power electronic fans have certain differences, and there are multiple size options for the same type of heat dissipation structure. The heat dissipation module (i.e. a system in which multiple heat dissipation structures cooperatively dissipate heat) composed of multiple heat dissipation structures (including heat dissipation structures of the same type but different sizes) has certain differences.

[0049] In one heat dissipation design, as Figure 2 , Figure 3 and Figure 4As shown, the parts of a certain high-power electronic fan include a fan cover 401, a rear cover 402, a wire harness 403, a PCBA (Printed Circuit Board Assembly) 404, a rotor 405, a stator 406, a housing 407, a fan blade 408, and the like.

[0050] In the present design, the winding (heat dissipation structure) surface is increased with a heat-conducting silica gel gasket and contacts a heat-conducting boss at a corresponding position of the housing for heat transfer and heat dissipation, and the housing surface is increased with a heat dissipation rib, which can reduce the winding temperature rise.

[0051] The fan blade surface is increased with a ventilation hole at a corresponding position of the winding, and the ventilation hole surface is increased with a wind guide angle. The fan blade surface is an air suction surface. The fan blade rotates to dissipate heat to the housing surface heat dissipation rib through the ventilation hole, further reducing the winding temperature rise.

[0052] In other heat dissipation designs, the heat of the conductive track can be transferred to the cover through the conductive filler and discharged to the outside, the tangential descending airflow can be generated inside the hub to remove the motor heat, the electronic circuit can be pressed against the heat dissipation rear cover by using an elastic element, there can be a gasket between the cover and the brush support, and the like.

[0053] In the present embodiment, the R&D personnel can design and produce multiple high-power electronic fans, each of which is configured with a unique design number. Each high-power electronic fan has a heat dissipation module composed of multiple heat dissipation structures. When testing the heat dissipation of multiple high-power electronic fans, the multiple high-power electronic fans are sequentially connected as lower computers to an upper computer, and the heat dissipation module in the high-power electronic fan is identified using the design number.

[0054] Step 102, when the high-power electronic fan is installed in the heat source device, the heat source device simulates multiple automobile engines to increase the real-time temperature value in turn.

[0055] In actual application, the heat source device is connected to the upper computer. The heat source device is a semi-closed container, which is configured with semiconductor refrigerating sheets, resistance heaters, temperature sensors, infrared cameras and other components, which provide a test environment for the high-power electronic fan heat dissipation test.

[0056] Since the high-power electronic fan is actually installed in multiple automobile engines (especially the automobile engines developed by the manufacturer of the high-power electronic fan), multiple operating environments are formed. Generally, the corresponding control algorithm is designed according to the characteristics of the multiple automobile engines. However, the heat dissipation effect of the high-power electronic fan differs under different operating environments and different control algorithms. Therefore, when the current high-power electronic fan to be tested is installed in the heat source device, the upper computer can use the PID (Proportion, Integration and Derivative) algorithm to control the temperature change of the heat source device, simulate the automobile engine to increase the real-time temperature value, and improve the simulation degree of the test.

[0057] In one embodiment of the present application, step 102 can include the following steps:

[0058] Step 1021, collect the running data of the automobile engine.

[0059] In the present embodiment, for various automobile engines to which the current high-power electronic fan to be tested is actually installed, the running data of the automobile engine when it is actually running can be collected through channels such as manufacturers.

[0060] Among them, the running data includes the starting duration of the automobile engine (i.e. the length of the interval between the sampling time of the running data and the starting time of the automobile engine) and the sample temperature value of the automobile engine.

[0061] Generally, the heat accumulation of the automobile (especially the new energy automobile) in the initial stage of starting is not obvious, and the heat dissipation capacity of the high-power electronic fan can be fully tested, especially the heat dissipation effect of the heat dissipation module and the control algorithm. After the automobile is started for a period of time, the heat accumulation is obvious, and the heat generation speed is much greater than the heat dissipation speed of the high-power electronic fan. At this time, the high-power electronic fan usually uses the maximum power for heat dissipation, and is not suitable for testing the heat dissipation capacity of the high-power electronic fan. Therefore, in the present embodiment, the running data of the automobile engine in the initial stage of starting can be collected by limiting the starting duration, so as to improve the quality of testing the heat dissipation capacity of the high-power electronic fan.

[0062] Step 1022, divide a plurality of time intervals adapted to the automobile engine.

[0063] In the present embodiment, a plurality of time intervals adapted to the automobile engine can be divided on the time axis according to the running characteristics of the automobile engine.

[0064] The so-called adaptation means being suitable for controlling the temperature change of the automobile engine.

[0065] In specific implementation, the running data further includes the operation data of the vehicle-mounted equipment (such as air conditioner, refrigerator, etc.) in the automobile to which the plurality of automobile engines belong. The operation of the vehicle-mounted equipment in the automobile (especially the new energy automobile) by the user will affect the energy consumption of the automobile, and thus affect the sample temperature value of the automobile engine.

[0066] Then, the time nodes can be determined on the time axis, and the set of time nodes can be represented as T={t0,t1,t2,……,t i ,……,t n}; Wherein t i is the i-th time node, and the initial time node t0 is 0.

[0067] In the current latest (i.e. the largest time stamp) time node tn Based on this, a preset baseline duration Step0 is added to obtain intermediate nodes. These intermediate nodes can then be represented as t. j =t n +Step0, the intermediate node is a transition node for calculating new time nodes, ensuring the minimum interval between time nodes.

[0068] The startup time is a period of time before the intermediate node (i.e., t). j -Δt, where Δt represents the number of operation data N within the time period. now The current quantity is written to the cache queue, and the largest quantity N in the historical operation data is selected from the quantities of all previous operations stored in the cache queue. max The smallest number N in history min .

[0069] The largest number N of historical operation data max The minimum number N of historical operation data min Divide the difference between the values ​​by the preset weight w to obtain the adjustment coefficient, and calculate the number N of the current operation data. now The product of the adjustment coefficient and the adjustment step size is used as the adjustment step size Step1. Therefore, the adjustment step size can be expressed as Step1 = N. now ×(N max -N min ) / w.

[0070] By adjusting the step size based on the intermediate node, a new time node t is obtained. n+1 That is, t n+1 =t j +Step 1, and delete the current intermediate node t j .

[0071] Determine the time interval (t) between two adjacent time nodes n , t n+1 The time range is adapted to the car engine.

[0072] On the one hand, the adjustment coefficient is dynamically adjusted based on the fluctuation range between the largest and smallest historical operation data. When the fluctuation range of operation data is large, it indicates that there are significant differences in the operation habits of different users. In this case, the adjustment coefficient is increased, thereby indirectly increasing the time interval to reduce the impact of differences in operation habits. When the fluctuation range of operation data is small, it indicates that the operation habits of different users are relatively similar. In this case, the adjustment coefficient is decreased, thereby indirectly decreasing the time interval to highlight the heat generated under the same or similar operation habits.

[0073] On the other hand, considering that the heat generation has a certain hysteresis, in the case of frequent user operation, the time interval is increased, and in the case of sparse user operation, the time interval is reduced, so as to set a suitable reaction time for heat generation.

[0074] The embodiment restricts the time interval in two aspects, sets a reasonable time interval, and improves the simulation degree of simulating the real-time temperature value of the automobile engine.

[0075] Step 1023, write the sample temperature value into the time interval where the start-up duration is located.

[0076] In the embodiment, the start-up duration in each operation data is compared with each time interval, if the start-up duration falls into a certain time interval, the time interval can be used as a bucket, and the sample temperature value corresponding to the start-up duration is written into the bucket (time interval).

[0077] Step 1024, calculate the average value of the sample temperature value in the time interval as the reference temperature value.

[0078] For the same bucket (time interval), the average value of the sample temperature value in the bucket (time interval) can be calculated, which is recorded as the reference temperature value.

[0079] Step 1025, fit the variables in the temperature control function to minimize the difference between the temperature control function and the reference point.

[0080] The heat source device has configured a temperature control function (such as a polynomial function, an S-shaped curve function (such as a Sigmoid function, a hyperbolic tangent function), etc.), and the temperature control function has multiple variables to be fitted.

[0081] In the embodiment, a two-dimensional reference point is set for each time interval, the reference point includes the sample time at the midpoint of the time interval and the reference temperature value, and the difference between the temperature control function and the reference point (such as the sum of the distances between each reference point and the temperature control function) is minimized as the optimization target. Fit the variables in the temperature control function to minimize the difference between the temperature control function and the reference point.

[0082] Step 1026, if the fitting is completed, the heat source device is controlled according to the temperature control function to simulate the real-time temperature value of the automobile engine in turn.

[0083] If the temperature control functions of various automobile engines are fitted, the heat source device can be controlled according to the temperature control function to simulate the real-time temperature value of various automobile engines in turn.

[0084] Step 103, if the real-time temperature value reaches the multiple sampling temperature values in turn, the high-power electronic fan collects multiple frames of original infrared image data in turn.

[0085] In the embodiment, multiple sampling temperature values can be set at intervals of fixed length (such as 1℃), and in the process of simulating multiple automobile engine temperature value increases by the heat source device, if the real-time temperature value reaches a certain sampling temperature value, the host computer can call the infrared camera to collect original infrared image data of the high-power electronic fan at each sampling temperature value.

[0086] Step 104, filtering out background information related to the sampling temperature value in each frame of original infrared image data to obtain candidate infrared image data.

[0087] In actual application, the heat generated by the heat source device is gradually transferred to the high-power electronic fan, and the high-power electronic fan dissipates heat in cooperation with hardware (heat dissipation module) and software (control algorithm). At this time, the real-time temperature value of the heat source device reaching the sampling temperature value is used as prior knowledge to perform semantic analysis on the corresponding original infrared image data, filter out background information related to the sampling temperature value, and obtain candidate infrared image data related to high-power electronic fan heat dissipation.

[0088] In an embodiment of the application, step 104 can include the following steps:

[0089] Step 1041, for each frame of original infrared image data, calculating the average gray value and the fluctuation gray value of the original infrared image data.

[0090] In the embodiment, each frame of original infrared image data can be traversed to calculate the average gray value G avg and the fluctuation gray value G flu of the original infrared image data.

[0091] Wherein, the average gray value G avg is the average value of the gray values of each pixel point in the original infrared image data, and the fluctuation gray value G flu is the standard deviation of the gray values of each pixel point in the original infrared image data.

[0092] Step 1042, calculating the temperature difference heat dissipation coefficient of the high-power electronic fan according to the average gray value, the fluctuation gray value and the sampling temperature value.

[0093] In the embodiment, the temperature difference heat dissipation coefficient C t of the high-power electronic fan can be calculated according to the average gray value G avg , the fluctuation gray value G flu and the sampling temperature value T0.

[0094] Wherein, the temperature difference heat dissipation coefficient C t reflects the heat dissipation capability of the high-power electronic fan between the test environment and the surrounding environment.

[0095] For example, when the voltage of a high-power electric fan is constant (e.g., constant at 26.01V), various sensors can be used to detect the current A and airflow W of the high-power electric fan. The heat output f1(A,W) of the high-power electric fan can be determined based on the heat output A and airflow W of the high-power electric fan. For example, the heat output f1(A,W) of the high-power electric fan can be determined by substituting the current A and airflow W of the high-power electric fan into a preset first conversion function or by looking up a table.

[0096] Furthermore, such as Figure 5 As shown, a comparison is made between two high-power electronic fans, A and B. The current determines the input power of the high-power electronic fan, the air volume is the active power in the output power of the high-power electronic fan, and the reactive power in the output power of the high-power electronic fan is mainly converted into heat.

[0097] When the current increases, the input power increases. If the efficiency of the motor in a high-power electric fan remains unchanged, the air volume and heat generation will increase simultaneously. If the efficiency of the motor in a high-power electric fan decreases (e.g., due to overload), more energy in the input power will be converted into heat. In this case, an increase in current may lead to a significant increase in heat generation, but the increase in air volume will be limited or even unchanged.

[0098] Increased airflow usually means increased output power. If the input power increases simultaneously and the efficiency remains stable, the heat generation will increase with the increase in input power. If the airflow remains unchanged (e.g., the fan is stalled and the blades cannot rotate), the output power is 0, and all the input power is converted into heat. At this time, the current will increase sharply and the heat generation will soar.

[0099] In addition, the fluctuation coefficient f2(W) is determined by substituting the air volume W of the high-power electronic fan into the preset second conversion function (especially the nonlinear function) or by looking up a table.

[0100] Among them, the fluctuation coefficient reflects the basic ability of a high-power electronic fan to dissipate heat through airflow. The fluctuation coefficient is positively correlated with the airflow of a high-power electronic fan. That is, the greater the airflow of a high-power electronic fan, the greater the fluctuation coefficient, and vice versa.

[0101] At average gray value G avg Based on this, add the volatility coefficient f2(W) and the volatility gray value G. flu The product of the two values ​​yields the estimated gray value G. pre That is, G pre =G avg + f2(W)×G flu The estimated grayscale value is mapped to the estimated temperature value T1 using methods such as table lookup.

[0102] The ratio between the heat generation and the deviation temperature value is calculated as the temperature difference heat dissipation coefficient C of the high-power electronic fan t ; wherein the deviation temperature value is the difference between the estimated temperature value and the sampling temperature value, and then C t =f1(A,W) / (T1-T0).

[0103] Step 1043, mapping the sampling temperature value to a sampling gray value.

[0104] In this embodiment, the sampling temperature value can be mapped to a sampling gray value by means of a lookup table or the like.

[0105] Step 1044, for each pixel point in the original infrared image data, calculating the ratio between the deviation gray value and the weighting gray value as the new gray value of each pixel point in the original infrared image data.

[0106] In this embodiment, each pixel point in the original infrared image data can be traversed, and the deviation gray value and the weighting gray value are calculated respectively.

[0107] Wherein the deviation gray value is the gray value G old of the pixel point in the original infrared image data minus the product of the temperature difference heat dissipation coefficient C t and the sampling gray value G sample , and the weighting gray value is the product of the fluctuation gray value G flu and the quadratic root of the temperature difference heat dissipation coefficient C t .

[0108] The ratio between the deviation gray value and the weighting gray value is calculated as the new gray value G new of each pixel point in the original infrared image data, and then the new gray value of the pixel point can be expressed as: G new =(G old -C t ×G sample ) / (G flu ×Sqr(C t )), wherein Sqr represents the quadratic root.

[0109] Step 105, fusing the multiple frames of candidate infrared image data into target infrared image data.

[0110] In this embodiment, for the multiple frames of candidate infrared image data collected in the same automobile engine, they can be fused into a new frame of target infrared image data.

[0111] In specific implementation, the temperature control function can be divided into multiple temperature control intervals by means of equal intervals or according to the inflection points of the temperature control function.

[0112] Exemplarily, as shown in the figure, if the temperature control function is an S-shaped curve function, which is convenient for controlling the temperature change of the heat source device, the temperature control function is divided into a first function interval M1, a second function interval M2 and a third function interval M3 in sequence as the temperature control interval, that is, the second function interval M2 is located in front of the first function interval M1, and the third function interval M3 is located in front of the second function interval M2. Figure 6

[0113] Among them, the slope of the second function interval M2 is greater than the slope of the first function interval M1 and the slope of the third function interval M3.

[0114] In this example, the first function interval M1 is the gradual start of the automobile engine and the vehicle-mounted device, and the temperature slowly rises. The second function interval M2 is the normal operation of the automobile engine and the vehicle-mounted device, and the temperature rapidly rises. The third function interval M3 is the heat accumulation, and the temperature tends to the upper limit.

[0115] According to the temperature control interval in which the sampling temperature value corresponding to the candidate infrared image data is located, the candidate infrared image data is configured with a weight. The weights are normalized so that the sum of the weights is 1.

[0116] Exemplarily, if the sampling temperature value corresponding to the candidate infrared image data is located in the first function interval, the candidate infrared image data is configured with a first numerical value as the weight.

[0117] If the sampling temperature value corresponding to the candidate infrared image data is located in the second function interval, the candidate infrared image data is configured with a second numerical value as the weight.

[0118] If the sampling temperature value corresponding to the candidate infrared image data is located in the third function interval, the candidate infrared image data is configured with a third numerical value as the weight.

[0119] Among them, the third numerical value is greater than the first numerical value, and the first numerical value is greater than the second numerical value.

[0120] Because the second function interval M2 is more conducive to testing the heat dissipation capacity of the high-power electronic fan, the candidate infrared image data corresponding thereto is configured with a higher weight.

[0121] According to the weight, the multiple frames of candidate infrared image data are superimposed into target infrared image data, that is, the sum of the products between the gray values of the pixel points located at the same position in the multiple frames of candidate infrared image data and the weight is taken as the gray value of the pixel point located at the same position in the target infrared image data.

[0122] Step 106, generating a heat dissipation performance distribution map according to the multiple frames of target infrared image data of the multiple heat dissipation modules.

[0123] ​In the embodiment, the multi-frame target infrared image data of the multiple heat dissipation modules in the multiple automobile engines is analyzed to generate a heat dissipation performance distribution map.

[0124] The heat dissipation performance distribution map describes the distribution information of the heat dissipation performance of the multiple heat dissipation modules in the multiple automobile engines.

[0125] In a specific implementation, the discriminator can be loaded, wherein the discriminator belongs to a deep learning model, is trained using two frames of sample infrared image data of high-power electronic fans, and is generated in the same way as the target infrared image data. The labels of the two frames of sample infrared image data are the pros and cons of the heat dissipation performance, and the Pairwise method can be used for training.

[0126] For the same kind of heat dissipation module, the target infrared image data generated for the two kinds of automobile engines is input into the discriminator to generate first pros and cons information of the heat dissipation performance, wherein the first pros and cons information represents the pros and cons of the heat dissipation performance of the same kind of heat dissipation module in the two kinds of automobile engines.

[0127] The first pros and cons information is used to generate first ranking information of the heat dissipation performance of the same kind of heat dissipation module in the multiple automobile engines.

[0128] For the same kind of automobile engine, the target infrared image data generated for the two kinds of heat dissipation modules is input into the discriminator to generate second pros and cons information of the heat dissipation performance, wherein the second pros and cons information represents the pros and cons of the heat dissipation performance of the two kinds of heat dissipation modules in the same kind of automobile engine.

[0129] The second pros and cons information is used to generate second ranking information of the heat dissipation performance of the multiple heat dissipation modules in the same kind of automobile engine.

[0130] The coordinate points composed of the first ranking information and the second ranking information are marked in the coordinate system to obtain the heat dissipation performance distribution map.

[0131] The first ranking information is the horizontal axis coordinate, and the second ranking information is the vertical axis coordinate, or the first ranking information is the vertical axis coordinate, and the second ranking information is the horizontal axis coordinate.

[0132] Exemplarily, the coordinate points composed of the first ranking information and the second ranking information are shown in the following table:

[0133] ;

[0134] The first value in the coordinate point is the first ranking information, and the second value is the second ranking information.

[0135] The heat dissipation performance is an abstract concept, and the coordinate points composed of the first ranking information and the second ranking information intuitively show the heat dissipation performance of different heat dissipation modules in a ranking manner.

[0136] In step 107, a heat dissipation test report is generated for the plurality of heat dissipation modules according to the heat dissipation performance distribution map.

[0137] In this embodiment, the heat dissipation performance distribution map can be written into the heat dissipation test report generated for the plurality of heat dissipation modules for reference by the researchers.

[0138] In general, for a specific type of automobile engine, the heat dissipation module with coordinate points tending to the origin (0, 0) can be selected, and the heat dissipation module performs better in terms of heat dissipation performance for the automobile engine.

[0139] Further, the data (i.e., coordinate points) of the heat dissipation performance distribution map, the description information of various heat dissipation modules, the description information of various automobile engines, and other materials can be input into the LLM (Large Language Model), and the LLM generates heat dissipation test summary information with the aid of the knowledge base of automobile engines and automobile heat dissipation fans. The heat dissipation performance distribution map and the heat dissipation test summary information are written into the heat dissipation test report generated for the plurality of heat dissipation modules, which facilitates the researchers to write and modify the heat dissipation test report.

[0140] In this embodiment, a heat dissipation module composed of a plurality of heat dissipation structures in a high-power electronic fan is identified. When the high-power electronic fan is installed on a heat source device, the heat source device is controlled to simulate a plurality of automobile engines to increase the real-time temperature value in sequence. During each simulation process, if the real-time temperature value reaches a plurality of sampling temperature values in sequence, a plurality of frames of original infrared image data of the high-power electronic fan are collected in sequence. The background information related to the sampling temperature values is filtered out from each frame of original infrared image data to obtain candidate infrared image data. The plurality of frames of candidate infrared image data are fused into target infrared image data. A heat dissipation performance distribution map is generated according to the plurality of frames of target infrared image data of the plurality of heat dissipation modules. The heat dissipation performance distribution map describes the distribution information of the heat dissipation performance of the plurality of heat dissipation modules in the plurality of automobile engines. A heat dissipation test report is generated for the plurality of heat dissipation modules according to the heat dissipation performance distribution map. This embodiment tests the heat dissipation performance of different heat dissipation structures in the high-power electronic fan in different automobile engines, uses the heat dissipation performance distribution map to reflect the trend of the heat dissipation performance, provides an objective performance data basis for the design of the heat dissipation structure, reduces the error caused by manual experience, and thus improves the heat dissipation efficiency of the high-power electronic fan.

[0141] Embodiment Two

[0142] Reference Figure 7, shows a structural schematic diagram of a test device of a high-power electronic fan heat dissipation structure provided by the embodiment two of the application. The high-power electronic fan is an automobile engine cooling electronic fan, and the power is greater than a threshold value, such as Figure 7 As shown in the figure, the device comprises:

[0143] A heat dissipation module identification module 701 is configured to identify a heat dissipation module composed of multiple heat dissipation structures in the high-power electronic fan.

[0144] A heat source control module 702 is configured to control a heat source device to simulate multiple automobile engine real-time temperature values in sequence when the high-power electronic fan is installed to the heat source device.

[0145] An original infrared image data acquisition module 703 is configured to acquire multiple frames of original infrared image data of the high-power electronic fan in sequence if the real-time temperature values reach multiple sampling temperature values in sequence.

[0146] A candidate infrared image data generation module 704 is configured to filter out background information related to the sampling temperature values in each frame of the original infrared image data to obtain candidate infrared image data.

[0147] A target infrared image data fusion module 705 is configured to fuse multiple frames of the candidate infrared image data into target infrared image data.

[0148] A heat dissipation performance distribution map generation module 706 is configured to generate a heat dissipation performance distribution map according to multiple frames of the target infrared image data of multiple heat dissipation modules; the heat dissipation performance distribution map describes distribution information of heat dissipation performance of multiple heat dissipation modules in multiple automobile engines.

[0149] A heat dissipation test report generation module 707 is configured to generate a heat dissipation test report of multiple heat dissipation modules according to the heat dissipation performance distribution map.

[0150] In an embodiment of the application, the heat source device is configured with a temperature control function; the temperature control function has multiple variables.

[0151] The heat source control module 702 comprises:

[0152] An operation data acquisition module is configured to acquire operation data of the automobile engine for various automobile engines; the operation data comprises a starting duration of the automobile engine and a sample temperature value of the automobile engine.

[0153] A time interval division module is configured to divide multiple time intervals adapted to the automobile engine.

[0154] A time interval writing module is configured to write the sample temperature value into the time interval where the starting duration is located.

[0155] A reference temperature value calculation module is configured to calculate an average of the sample temperature values in the time interval as a reference temperature value;

[0156] A temperature control function fitting module is configured to fit the variable in the temperature control function so as to minimize the difference between the temperature control function and a reference point; the reference point includes a sample time located at the midpoint of the time interval and the reference temperature value;

[0157] A temperature control module is configured to control the heat source device to simulate the real-time temperature value of the automobile engine in sequence according to the temperature control function if the fitting is completed.

[0158] In an embodiment of the present application, the operation data of the automobile engine further includes operation data of a vehicle-mounted device in the automobile to which the automobile engine belongs, and the time interval division module includes:

[0159] A time node determination module is configured to determine a time node; the initial time node is 0;

[0160] An intermediate node determination module is configured to increase a preset reference time length on the basis of the current latest time node to obtain an intermediate node;

[0161] A quantity statistics module is configured to count the number of the operation data located within a period of time before the intermediate node;

[0162] An adjustment coefficient calculation module is configured to divide the difference between the historically maximum number and the historically minimum number by a preset weight to obtain an adjustment coefficient;

[0163] An adjustment step calculation module is configured to calculate the product between the current number and the adjustment coefficient as an adjustment step;

[0164] A node update module is configured to increase the adjustment step on the basis of the intermediate node to obtain a new time node, and delete the intermediate node;

[0165] A time interval determination module is configured to determine a time interval between two adjacent time nodes and adapt the time interval to the automobile engine.

[0166] In an embodiment of the present application, the candidate infrared image data generation module 704 includes:

[0167] a gray value calculation module, configured to calculate an average gray value and a fluctuation gray value for each frame of the original infrared image data, wherein the average gray value is an average of gray values of each pixel in the original infrared image data, and the fluctuation gray value is a standard deviation of the gray values of each pixel in the original infrared image data;

[0168] a temperature difference heat dissipation coefficient calculation module, configured to calculate a temperature difference heat dissipation coefficient of the high-power electronic fan according to the average gray value, the fluctuation gray value and the sampling temperature value;

[0169] a sampling gray value mapping module, configured to map the sampling temperature value into a sampling gray value;

[0170] a gray value updating module, configured to calculate a ratio between a deviation gray value and a weighting gray value as a new gray value of each pixel in the original infrared image data, wherein the deviation gray value is a difference between the gray value of the pixel in the original infrared image data and a product of the temperature difference heat dissipation coefficient and the sampling gray value, and the weighting gray value is a product between the fluctuation gray value and a square root of the temperature difference heat dissipation coefficient.

[0171] In an embodiment of the present application, the temperature difference heat dissipation coefficient calculation module comprises:

[0172] a heat generation amount determination module, configured to determine the heat generation amount of the high-power electronic fan according to a heat generation amount of the high-power electronic fan and an air volume of the high-power electronic fan;

[0173] a predicted gray value calculation module, configured to add a product between a fluctuation coefficient and the fluctuation gray value to the average gray value to obtain a predicted gray value, wherein the fluctuation coefficient is positively correlated with the air volume;

[0174] a predicted temperature value calculation module, configured to map the predicted gray value into a predicted temperature value;

[0175] a temperature difference heat dissipation coefficient determination module, configured to calculate a ratio between the heat generation amount and a deviation temperature value as the temperature difference heat dissipation coefficient of the high-power electronic fan, wherein the deviation temperature value is a difference between the predicted temperature value and the sampling temperature value.

[0176] In an embodiment of the present application, the target infrared image data fusion module 705 comprises:

[0177] a temperature control interval division module, configured to divide the temperature control function into a plurality of temperature control intervals;

[0178] a weight configuration module, configured to configure a weight for the candidate infrared image data according to the temperature control interval in which the sampling temperature value corresponding to the candidate infrared image data is located;

[0179] an infrared image data superposition module, configured to superimpose multiple frames of the candidate infrared image data into target infrared image data according to the weight.

[0180] In an embodiment of the present application, the temperature control interval division module is further configured to:

[0181] If the temperature control function is an S-shaped curve function, the temperature control function is sequentially divided into a first function interval, a second function interval and a third function interval as temperature control intervals;

[0182] The slope of the second function interval is greater than the slope of the first function interval and the slope of the third function interval.

[0183] The weight configuration module is further configured to:

[0184] If the sampling temperature value corresponding to the candidate infrared image data is located in the first function interval, a first numerical value is configured as the weight for the candidate infrared image data.

[0185] If the sampling temperature value corresponding to the candidate infrared image data is located in the second function interval, a second numerical value is configured as the weight for the candidate infrared image data.

[0186] If the sampling temperature value corresponding to the candidate infrared image data is located in the third function interval, a third numerical value is configured as the weight for the candidate infrared image data.

[0187] The third numerical value is greater than the first numerical value, and the first numerical value is greater than the second numerical value.

[0188] In an embodiment of the present application, the heat dissipation performance distribution map generation module 706 comprises:

[0189] a discriminator loading module, configured to load a discriminator; the discriminator is trained using two frames of sample infrared image data of the high-power electronic fan, and the labels marked for the two frames of sample infrared image data are the pros and cons of heat dissipation performance;

[0190] a first pros and cons information generation module, configured to input the target infrared image data generated for two types of automobile engines into the discriminator to generate first pros and cons information of heat dissipation performance for the same type of heat dissipation module.

[0191] The first ranking information generation module is configured to generate first ranking information of heat dissipation performance of the same type of heat dissipation module in the plurality of automobile engines by using the plurality of first merit / demerit information.

[0192] The second merit / demerit information generation module is configured to generate second merit / demerit information of heat dissipation performance of the same type of automobile engine by inputting the target infrared image data generated for the two types of heat dissipation modules into the discriminator.

[0193] The second ranking information generation module is configured to generate second ranking information of heat dissipation performance of the plurality of heat dissipation modules in the same type of automobile engine by using the plurality of second merit / demerit information.

[0194] The coordinate point marking module is configured to mark the coordinate points formed by the first ranking information and the second ranking information into a coordinate system to obtain a heat dissipation performance distribution diagram.

[0195] The test device for the high-power electronic fan heat dissipation structure provided by the embodiment of the application can execute the test method for the high-power electronic fan heat dissipation structure provided by any embodiment of the application, and has the corresponding function modules and beneficial effects of executing the test method for the high-power electronic fan heat dissipation structure.

[0196] Embodiment three

[0197] Referring to Figure 8 , a structural schematic diagram of an electronic device provided by an embodiment of the application is shown. The electronic device is intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The components shown here, their connections, and their functions, as well as their implementation, are merely examples and are not intended to limit the implementations of the application described herein and / or claimed.

[0198] As Figure 8 shown, the electronic device 10 includes at least one processor 11, and a memory, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., which is in communication with the at least one processor 11, wherein the memory stores a computer program that can be executed by the at least one processor. The processor 11 can execute various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 into the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0199] A plurality of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a magnetic disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network, such as the Internet, and / or various telecommunication networks.

[0200] The processor 11 can be various general and / or special purpose processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 performs various methods and processes described above, such as the test method of the high-power electronic fan heat dissipation structure.

[0201] In some embodiments, the test method of the high-power electronic fan heat dissipation structure can be implemented as a computer program tangibly embodied in a computer readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed onto the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded onto the RAM 13 and executed by the processor 11, one or more steps of the test method of the high-power electronic fan heat dissipation structure described above can be performed. Alternatively, in other embodiments, the processor 11 can be configured to perform the test method of the high-power electronic fan heat dissipation structure by any other appropriate means, such as by means of firmware.

[0202] Various implementations of the systems and techniques described above can be realized in digital electronic circuitry, integrated circuitry, a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), a system on a chip (SOC), a programmable logic device (CPLD), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include implementation in one or more computer programs that are executable and / or interpretable on a programmable system including at least one programmable processor, which can be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device.

[0203] Computer programs for implementing the methods of the present application can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer program, when executed, enables the functions / acts specified in the flowcharts and / or block diagrams to be implemented. The computer program can be executed entirely on a machine, partially on a machine, partially on a machine as a standalone software package and partially on a remote machine or entirely on a remote machine or server.

[0204] In the context of the present application, a computer-readable storage medium can be a tangible medium that can contain or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. A computer-readable storage medium can include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium can be a machine-readable signal medium. More specific examples of a machine-readable storage medium will include one or more lines of a program of instructions in a transitory signal, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0205] To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the electronic device. Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form, including acoustic, speech, or tactile input.

[0206] The systems and techniques described here can be implemented in a computing system that includes a back end component, e.g., as a data server, or that includes a middleware component, e.g., an application server, or that includes a front end component, e.g., a user computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the systems and techniques described here, or any combination of such back end, middleware, or front end components. The components of the system can be interconnected by any form or medium of digital data communication, e.g., a communication network. Examples of communication networks include a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0207] The computing system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. A server can be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system, to solve the defects of large management difficulty and weak business scalability in traditional physical host and VPS service.

[0208] Embodiment four

[0209] The embodiment of the application further provides a computer program product, which comprises a computer program, and the computer program is executed by a processor to realize the test method of the high-power electronic fan heat dissipation structure provided in any embodiment of the application.

[0210] The computer program code implementing the application can be written in one or more programming languages or combinations of languages including object oriented languages such as Java, Smalltalk, C++ or conventional procedural programming languages such as the "C" programming language or similar programming languages. The program code can execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection can be made to an external computer (for example, through the Internet using an Internet Service Provider). In an embodiment of the application, the remote computer can be a server or another desktop computer.

[0211] It should be understood that the various forms of flow shown above can be used to reorder, add, or remove steps. For example, the steps recited in the present application can be performed in parallel, in series, or in a different order, as long as the desired results of the technical solutions of the present application can be achieved, which are not limited herein.

[0212] The above detailed description does not constitute a limitation on the protection scope of the present application. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent replacements, and improvements made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A method for testing a high-power electronic fan cooling structure, characterized in that, The high-power electronic fan is an electronic fan for cooling an automobile engine, and the power is greater than a threshold value, the threshold value including 1400W, and the method includes: identifying a heat dissipation module composed of a plurality of heat dissipation structures in the high-power electronic fan; collecting operation data of the automobile engine for various automobile engines when the high-power electronic fan is installed to a heat source device; the heat source device is configured with a temperature control function; the temperature control function has a plurality of variables; the operation data includes a starting time length of the automobile engine and a sample temperature value of the automobile engine; dividing a plurality of time intervals adapted to the automobile engine; writing the sample temperature value into the time interval in which the starting time length is located; calculating an average value of the sample temperature value in the time interval as a reference temperature value; fitting the variables in the temperature control function to minimize the difference between the temperature control function and a reference point; the reference point includes a sample time located at the midpoint of the time interval and the reference temperature value; if the fitting is completed, controlling the heat source device to simulate the real-time temperature value of the automobile engine in sequence according to the temperature control function; if the real-time temperature value reaches a plurality of sampling temperature values in sequence, collecting a plurality of frames of original infrared image data for the high-power electronic fan in sequence; filtering out background information related to the sampling temperature value in each frame of the original infrared image data to obtain candidate infrared image data; fusing a plurality of frames of the candidate infrared image data into target infrared image data; generating a heat dissipation performance distribution map according to a plurality of frames of the target infrared image data of a plurality of heat dissipation modules; the heat dissipation performance distribution map describes the distribution information of the heat dissipation performance of a plurality of heat dissipation modules in a plurality of automobile generators; generating a heat dissipation test report for a plurality of heat dissipation modules according to the heat dissipation performance distribution map.

2. The method of claim 1, wherein, The operation data further includes operation data of a vehicle-mounted device in a vehicle to which the automobile engine belongs, and the dividing a plurality of time intervals adapted to the automobile engine includes: determining a time node; the initial time node is 0; increasing a preset reference time length on the basis of the current latest time node to obtain an intermediate node; counting the number of operation data within a period of time before the intermediate node of the starting time length; dividing the difference between the largest historical number and the smallest historical number by a preset weight to obtain an adjustment coefficient; calculating the product between the current number and the adjustment coefficient as an adjustment step; increasing the adjustment step on the basis of the intermediate node to obtain a new time node, and deleting the intermediate node; determining that the time interval between the adjacent two time nodes is adapted to the automobile engine.

3. The method of claim 1, wherein, The filtering out of background information related to the sampling temperature value in each frame of the original infrared image data to obtain candidate infrared image data includes: For each frame of the original infrared image data, an average gray value and a fluctuation gray value are calculated for the original infrared image data; the average gray value is an average of gray values of each pixel point in the original infrared image data, and the fluctuation gray value is a standard deviation of the gray values of each pixel point in the original infrared image data; A temperature difference heat dissipation coefficient is calculated for the high-power electronic fan according to the average gray value, the fluctuation gray value and the sampling temperature value; The sampling temperature value is mapped to a sampling gray value; For each pixel point in the original infrared image data, a ratio between a deviation gray value and a weighting gray value is calculated as a new gray value for each pixel point in the original infrared image data; the deviation gray value is a difference between the gray value of the pixel point in the original infrared image data and a product of the temperature difference heat dissipation coefficient and the sampling gray value, and the weighting gray value is a product between the fluctuation gray value and a square root of the temperature difference heat dissipation coefficient.

4. The method of claim 3, wherein, The calculation of the temperature difference heat dissipation coefficient for the high-power electronic fan according to the average gray value, the fluctuation gray value and the sampling temperature value comprises: The heat generation of the high-power electronic fan is determined according to the heat generation and an air volume of the high-power electronic fan; A pre-estimated gray value is obtained by adding a product between a fluctuation coefficient and the fluctuation gray value to the average gray value; the fluctuation coefficient is positively correlated with the air volume; The pre-estimated gray value is mapped to a pre-estimated temperature value; A ratio between the heat generation and a deviation temperature value is calculated as the temperature difference heat dissipation coefficient of the high-power electronic fan; the deviation temperature value is a difference between the pre-estimated temperature value and the sampling temperature value.

5. The method of claim 1, wherein, The fusion of the multiple frames of the candidate infrared image data into the target infrared image data comprises: The temperature control function is divided into multiple temperature control intervals; The candidate infrared image data is configured with a weight according to a temperature control interval in which the sampling temperature value corresponding to the candidate infrared image data is located; The multiple frames of the candidate infrared image data are superimposed into the target infrared image data according to the weight.

6. The method of claim 5, wherein The temperature control function is divided into multiple temperature control intervals, comprising: If the temperature control function is an S-shaped curve function, the temperature control function is sequentially divided into a first function interval, a second function interval and a third function interval as temperature control intervals; The slope of the second function interval is greater than the slope of the first function interval and the slope of the third function interval; The candidate infrared image data is configured with a weight according to a temperature control interval in which the sampling temperature value corresponding to the candidate infrared image data is located, comprising: If the sampling temperature value corresponding to the candidate infrared image data is located in the first function interval, the candidate infrared image data is configured with a first numerical value as the weight; If the sampling temperature value corresponding to the candidate infrared image data is located in the second function interval, the candidate infrared image data is configured with a second numerical value as the weight; If the sampling temperature value corresponding to the candidate infrared image data is located in the third function interval, a third numerical value is configured as a weight for the candidate infrared image data; The third numerical value is greater than the first numerical value, and the first numerical value is greater than the second numerical value.

7. The method according to any one of claims 1 to 6, characterized in that, The generating of the heat dissipation performance distribution map according to the plurality of frames of target infrared image data of the plurality of heat dissipation modules comprises: loading a discriminator; the discriminator is trained using two frames of sample infrared image data of the high-power electronic fan, and the labels marked on the two frames of sample infrared image data are the pros and cons of heat dissipation performance; For the same kind of heat dissipation module, the target infrared image data generated for the two kinds of automobile engines is input into the discriminator to generate the first pros and cons information of heat dissipation performance; Using a plurality of first pros and cons information, the first ranking information of the heat dissipation performance of the same kind of heat dissipation module in a plurality of automobile engines is generated; For the same kind of automobile engine, the target infrared image data generated for the two kinds of heat dissipation modules is input into the discriminator to generate the second pros and cons information of heat dissipation performance; Using a plurality of second pros and cons information, the second ranking information of the heat dissipation performance of the plurality of heat dissipation modules in the same kind of automobile engine is generated; The coordinate points composed of the first ranking information and the second ranking information are marked in the coordinate system to obtain the heat dissipation performance distribution map.

8. An electronic device, comprising: The electronic device comprises: at least one processor; and a memory connected in communication with the at least one processor; wherein The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to execute the test method of the high-power electronic fan heat dissipation structure according to any one of claims 1-7.

9. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, and the computer program is executed by the processor to realize the test method of the high-power electronic fan heat dissipation structure according to any one of claims 1-7.

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