Ice thickness estimation module application value detection method, device, equipment and storage medium

Abstract

The present application relates to a method, device, equipment and storage medium for detecting the application value of an ice thickness estimation module, and relates to the technical field of aircraft ice detection and elimination, and detects the application value of ice thickness estimation products under different scene environmental conditions based on wind tunnel tests. It includes the following steps: during an icing test on a test piece in an icing wind tunnel, when a built-in environmental condition occurs in any of a variety of environmental simulation devices, the built-in environmental condition is input into a recommendation model; a target ice thickness estimation module matching the built-in environmental condition is calculated by the recommendation model, a calculation trigger instruction is generated, and the ice thickness is output; the ice thickness is input into a functional module that uses the ice thickness, and the value of the target ice thickness estimation module applied to the built-in environmental condition is detected according to the response result received by the local logic executed by the functional module.

Description

Technical Field

[0001] The present application relates to the technical field of aircraft ice layer detection and elimination, and in particular to a method, device, equipment and storage medium for detecting the application value of an ice layer thickness estimation module. Background Art

[0002] When an aircraft passes through clouds due to low temperature, convection, or excessive water content, ice will quickly freeze on the fuselage. In order to promptly de-ice the fuselage when a certain thickness of ice has formed and to resolve the potential safety hazards caused by ice on the aircraft skin, air inlet, and other locations, relevant technical personnel have provided a variety of solutions or intellectual property rights for detecting the thickness of the aircraft's ice layer, and have formed hardware products based on the corresponding solutions or intellectual property rights and put them into use.

[0003] However, some solutions, or the intellectual property rights corresponding to the solutions, may solve the problem with high accuracy and efficiency during the R&D and testing phase; but after being put into use, the performance is not good. It is found that the reason for the above situation may be that the solutions are not highly adaptable to actual scenarios during actual application. In order to solve this problem, the application value of the products formed based on the intellectual property rights corresponding to these solutions is low, which affects a certain degree of R&D cost and maintenance cost waste. In addition, the application of the solutions in inappropriate scenarios will lead to reduced accuracy in ice thickness prediction, affecting aircraft flight safety. Summary of the invention

[0004] The technical problem to be solved by the present application is to provide a method, device, equipment and storage medium for detecting the application value of an ice thickness estimation module, to detect the application value of an ice thickness estimation module product formed based on a characteristic scheme or intellectual property right under different scenario environmental conditions based on wind tunnel tests, to provide reference data for configuring reasonable ice thickness detection devices for aircraft on different routes, and to provide reference for the production investment of ice thickness detection products, as well as the research and development and maintenance investment of the intellectual property right corresponding to ice thickness detection products, thereby saving costs.

[0005] In a first aspect, an embodiment provides a method for detecting the application value of an ice layer thickness estimation module, which is applied to electronic equipment, the method comprising: during an icing test on a test piece in an icing wind tunnel, when a built-in environmental condition occurs in any one of a plurality of environmental simulation devices, inputting the built-in environmental condition into a recommended model; calculating a target ice layer thickness estimation module matching the built-in environmental condition through the recommended model, and generating a calculation trigger instruction; the calculation trigger instruction is used to control the target ice layer thickness estimation module to run according to a locally stored program logic and output the ice layer thickness; inputting the ice layer thickness into a functional module that uses the ice layer thickness, and detecting the value of applying the target ice layer thickness estimation module to the built-in environmental condition according to a response result received by the functional module executing the local logic.

[0006] In one embodiment, the functional module using the ice thickness includes a display device; inputting the ice thickness to the functional module using the ice thickness, and detecting the value of the target ice thickness estimation module applied to the built-in environmental condition according to a response result received by the functional module executing the local logic, including:

[0007] inputting the ice layer thickness into the display device;

[0008] When the display device displays the ice layer thickness in a preset manner, a user's determination operation on the ice layer thickness based on the display device is collected, and it is determined that the target ice layer thickness estimation module has application value under the built-in environmental conditions.

[0009] In one embodiment, the functional module using the ice thickness includes a de-icing device, the ice thickness is input to the functional module using the ice thickness, and according to the response result received by the functional module executing the local logic, the value of the target ice thickness estimation module applied to the built-in environmental condition is detected, including:

[0010] inputting the ice layer thickness into the deicing device corresponding to the ice layer thickness;

[0011] When it is detected that the de-icing device is operating according to the local device program and a signal of ice removal feedback from the ice layer detection device is received within a preset time, it is determined that the target ice layer thickness estimation module has application value under the built-in environmental conditions; the ice layer detection device is used to detect ice on the surface of the fuselage.

[0012] In one embodiment, the method further comprises:

[0013] Collecting environmental conditions under the built-in environmental conditions and performing feature conversion to obtain environmental condition features; the environmental conditions include temperature, water droplets, water content, ice and snow, incoming flow conditions, liquid water content, and visibility;

[0014] Taking each ice thickness estimation module as the current ice thickness estimation module in turn, obtaining the previous hardware unit that provides input data to the current ice thickness estimation module; calling the input data from the previous hardware unit for calculation when the current ice thickness estimation module is running; the previous hardware unit includes a module, a device, a system, a program and an integrated circuit;

[0015] The target ice thickness estimation module matching the built-in environmental conditions is calculated by the recommended model to generate a calculation trigger instruction, including:

[0016] Using the previous hardware unit to query the target environmental condition feature in the environmental condition features, and weighting the target environmental condition feature in the environmental condition features;

[0017] The recommendation model calculates the matching degree between the current ice thickness estimation module and the environmental condition based on the weighted environmental condition characteristics;

[0018] Selecting the ice layer thickness estimation module with the highest similarity as the target ice layer thickness estimation module;

[0019] A trigger instruction for controlling the target ice layer thickness estimation module is generated.

[0020] In one embodiment, the method further comprises:

[0021] Detecting a previous hardware unit that provides input data to each ice thickness estimation module; when the ice thickness estimation module is running, calling the input data from the previous hardware unit for calculation;

[0022] When the program logic stored in the previous hardware unit is associated with the program logic stored in the target ice thickness estimation module, marking a positive score for the previous hardware unit;

[0023] Inputting the ice thickness into a function module using the ice thickness includes:

[0024] If the score of the target ice layer thickness estimation module corresponding to the previous hardware unit mark is higher than a preset threshold, the ice layer thickness is input to a functional module that uses the ice layer thickness.

[0025] In one embodiment, after the ice thickness is input to a function module that uses the ice thickness, and after the function module executes a response result received by the local logic, the method further includes:

[0026] If the target ice thickness estimation module is detected to have application value under the built-in environmental condition according to the response result received by executing the local logic of the functional module, the environmental condition corresponding to the built-in environmental condition is used as the historical environmental condition;

[0027] Establishing a correlation between the historical environmental conditions and the target ice thickness estimation module;

[0028] If the specific environment simulation device is detected to perform the historical environmental condition next time, the information of the ice thickness estimation module with which the historical environmental condition has a correlation is input into the recommendation model;

[0029] This execution calculates the target ice thickness estimation module that matches the built-in environmental conditions through the recommendation model, and in the process of generating a calculation trigger instruction, after obtaining the matching degree of each ice thickness estimation module with the historical environmental conditions, the matching degree of the ice thickness estimation module with the correlation is increased.

[0030] In one embodiment, the number of the previous hardware unit is multiple, and the method further includes:

[0031] Convert the output data, the form of collected data, the operating conditions, the execution efficiency and the resource consumption of each hardware unit into features to obtain a first feature;

[0032] Testing the execution efficiency and resource consumption of the electronic device when the current ice thickness estimation module runs according to the logic of the target ice thickness estimation module, and performing feature conversion to obtain a second feature;

[0033] Combining the first feature and the second feature to obtain a hardware condition feature matrix of the current ice thickness estimation module;

[0034] Utilizing the previous hardware unit to query the target environmental condition feature in the environmental condition features, and weighting the target environmental condition feature in the environmental condition features, comprises:

[0035] Calculating the matrix product between the hardware condition feature matrix and the transposed environmental condition feature matrix to obtain a weight parameter;

[0036] The target environmental condition features in the environmental condition features are weighted using the weight parameters.

[0037] In a second aspect, an embodiment provides an ice thickness estimation module application value detection device, which is provided in an electronic device, and the device includes:

[0038] An input module, used for inputting the built-in environmental condition into the recommended model when a built-in environmental condition of any one of the multiple environmental simulation devices occurs during an icing test of the test piece in an icing wind tunnel;

[0039] An instruction generation module, used for calculating the target ice thickness estimation module matching the built-in environmental conditions through the recommended model, and generating a calculation trigger instruction; the calculation trigger instruction is used to control the target ice thickness estimation module to run according to the program logic stored locally, and output the ice thickness;

[0040] A value detection module is used to input the ice thickness to a functional module that uses the ice thickness, and detect the value of the target ice thickness estimation module applied to the built-in environmental condition according to a response result received by the functional module executing the local logic.

[0041] The beneficial effects of this application are:

[0042] The method for detecting the application value of an ice thickness estimation module proposed in the embodiment of the present application simulates specific environmental conditions through an environmental simulation device, and generates conditions corresponding to the built-in environmental conditions, such as supercooled water droplets, snow, ice crystals, and specified incoming flow. The recommendation model selects a target ice thickness estimation module that matches the built-in environmental conditions from multiple ice thickness estimation modules according to the environmental parameters associated with the built-in environmental conditions, and then verifies the accuracy of the ice thickness output by the ice thickness estimation module under the built-in environmental conditions, thereby detecting in what environment the ice thickness estimation module has application value; further, if the ice thickness estimation module has application value under certain environmental conditions, then the logic of the ice thickness estimation module outputting the ice thickness and the data used to run the logic are also applicable under the environmental conditions, so that the detection result of the applicable environmental conditions of the target ice thickness estimation module can further verify whether the logic of the ice thickness estimation module outputting the ice thickness and the environmental conditions applicable to the used data are applicable to specific environmental conditions, that is, the application value of the technical solution or intellectual property rights based on which the ice thickness estimation module operates under specific environmental conditions. Based on the application value of the ice thickness estimation module, the application value of intellectual property under specific environmental conditions can be estimated, and a more economically valuable layout can be made for the investment and maintenance of intellectual property. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 It is a schematic diagram of an application scenario for executing the application value detection method of the ice thickness estimation module of the embodiment of the present application;

[0044] Figure 2 It is a flowchart of the steps of the ice thickness estimation module application value detection method proposed in the embodiment of the present application;

[0045] Figure 3 is a structural diagram of a recommendation model given as an example in this application;

[0046] Figure 4 It is a functional module diagram of the ice thickness estimation module application value detection device proposed in the embodiment of the present application;

[0047] Figure 5 A schematic diagram of the structure of a computing device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0048] The present application is further described in detail below by specific embodiments in conjunction with the accompanying drawings. Wherein similar elements in different embodiments adopt associated similar element numbers. In the following embodiments, many detailed descriptions are intended to enable the present application to be better understood. However, those skilled in the art can easily recognize that some of the features can be omitted in different situations, or can be replaced by other elements, materials, and methods. In some cases, some operations related to the present application are not shown or described in the specification, in order to avoid the core part of the present application being overwhelmed by too much description, and for those skilled in the art, it is not necessary to describe these related operations in detail, and they can fully understand the related operations based on the description in the specification and the general technical knowledge in the art.

[0049] In addition, the features, operations or characteristics described in the specification can be combined in any appropriate manner to form various implementations. At the same time, the steps or actions in the method description can also be interchanged or adjusted in a manner that is obvious to those skilled in the art. Therefore, the various sequences in the specification and the drawings are only for the purpose of clearly describing a certain embodiment and are not meant to be a required sequence, unless otherwise specified that a certain sequence must be followed.

[0050] The serial numbers assigned to the components herein, such as "first", "second", etc., are only used to distinguish the objects described and do not have any order or technical meaning. The "connection" and "coupling" mentioned in this application, unless otherwise specified, include direct and indirect connections (couplings).

[0051] In the field related to aircraft ice thickness detection and aircraft ice removal, products used to detect ice thickness include but are not limited to various devices, systems, applications, etc. These products are hardware products formed based on the intellectual property rights of detecting aircraft ice thickness. The devices, systems, applications and other hardware products are provided with memory and servers. The memory stores program instructions developed for operating logic of the technical solution for detecting ice thickness based on intellectual property protection. The processor calls the program instructions and runs according to the operating logic of the technical solution for detecting ice thickness to detect the thickness of the aircraft.

[0052] For example, the technical solution for detecting ice thickness may include but is not limited to the following methods:

[0053] First, the collected multi-angle images of the aircraft surface are used as the training data set to train a network model for estimating the thickness of the ice layer. The ice thickness of the aircraft in operation is detected through the network model.

[0054] Second, an ultrasonic signal is transmitted to the aircraft in the area to be inspected, and the thickness of the ice layer is calculated based on the ultrasonic information.

[0055] 3. Calculate the position of the laser reflected back to the inside of the aircraft skin after the laser passes through the laser transmission and reflection layer embedded flat in the aircraft skin layer, and calculate the thickness of the ice layer.

[0056] 4. The calibrated light field speckle measurement system is used to restore the local morphology of the ice layer on the aircraft surface, obtain local point clouds at different positions, reconstruct the three-dimensional morphology of the ice layer based on the repeated areas of the local point clouds, and obtain the thickness of the ice layer on the aircraft surface.

[0057] Since the calculation logic and input data required for executing the calculation logic of the above-mentioned different methods for detecting ice thickness are different, the matching scene environmental conditions are different. For example, in low visibility environments such as heavy fog, the accuracy of estimating ice thickness by relying on images is low. When the aircraft passes through strong clouds in the far field, the accuracy of measuring ice thickness by transmitting signals is low. The method of estimating ice thickness by laser refraction is affected by light and ice crystal particles. There are also many ways to detect the thickness of ice on aircraft that are affected by various environmental conditions. For example, environmental conditions such as rain, snow, and water droplets will affect the detection of ice thickness. Therefore, it is impossible to foresee the value of the intellectual property protected by the technical solution for detecting ice thickness during the research and development stage, and it is impossible to obtain the product application value formed based on the technical solution in advance, resulting in a certain degree of waste of intellectual property rights, product maintenance and output investment costs.

[0058] In view of the above problems, an embodiment of the present application proposes a method for detecting the application value of an ice thickness estimation module, which matches hardware products for detecting ice thickness that are adapted to different environmental conditions based on wind tunnel tests, and obtains the application value of hardware products for detecting ice thickness with different conditions. That is, it is detected under which environmental scenarios and environmental conditions the hardware products for detecting ice thickness with different conditions have application value, thereby detecting the application value of the corresponding intellectual property rights of the hardware products.

[0059] Figure 1 Schematic diagram of an application scenario of an ice thickness estimation module application value detection method according to an embodiment of the present application. The ice thickness estimation module application value detection method is implemented based on a wind tunnel test in an icing wind tunnel. Figure 1 The icing wind tunnel shown is provided with an environmental condition simulation system, a refrigeration system, a fan power system, a deicing system, etc.; the environmental condition simulation system, the refrigeration system, the fan power system, and the deicing system are all connected to electronic equipment, and the electronic equipment can be an integrated computing resource with computing power such as a computer or a server, and the electronic equipment is provided with or connected to a display. The environmental condition simulation system is provided with a variety of environmental simulation devices, and any environmental simulation device receives a command sent by the electronic equipment and executes a local program to simulate the corresponding environmental conditions.

[0060] In one example of the present application, the environmental simulation device may include a supercooled water droplet simulation test device, a snowmaking device, an ice crystal particle preparation device, etc.

[0061] The supercooled water droplet simulation test device is used to simulate the environmental conditions encountered by an aircraft passing through a cloud layer containing supercooled water droplets. The supercooled water droplet simulation test device can be set in an icing wind tunnel test section. In conjunction with the refrigeration system and the fan power system, the supercooled water droplet simulation test device generates a dynamic water film that adapts to the far-field incoming flow to produce the environmental conditions encountered by the above-mentioned aircraft passing through a cloud layer containing supercooled water droplets. In this example, the "environmental conditions encountered by an aircraft passing through a cloud layer containing supercooled water droplets" are the built-in environmental conditions of the supercooled water droplet simulation test device in the current scenario.

[0062] Figure 2 : is a flowchart of the steps of the ice thickness estimation module application value detection method proposed in the embodiment of the present application, such as Figure 2 As shown, the steps include:

[0063] S11: During the icing test of the test piece in the icing wind tunnel, when a built-in environmental condition occurs in any one of the multiple environmental simulation devices, the built-in environmental condition is input into the recommended model.

[0064] Taking the simulation of an aircraft passing through a cloud layer containing supercooled water droplets as an example, the electronic device can send instructions to the environmental condition simulation system, the refrigeration system, and the fan power system according to the built-in environmental conditions that need to be simulated: cloud conditions. The refrigeration system responds to the corresponding instructions and starts to cool to the specified temperature. The fan power system starts to operate according to the specified incoming flow conditions. After the environmental simulation device receives the instructions for simulating the built-in environmental conditions sent by the electronic device, it starts to start and generate water droplets. The electronic device detects that the above-mentioned environmental condition simulation system, refrigeration system, and fan power system have been running for a certain period of time, and collects environmental parameters in the icing wind tunnel: when the temperature, water content, incoming flow conditions, etc. meet the standards for simulating an aircraft passing through a cloud layer containing supercooled water droplets, the collected environmental parameters are input into the pre-trained recommendation model.

[0065] Build a deep neural network architecture including convolutional layers, fully connected layers based on attention mechanism, pooling layers, normalization layers, long short-term memory network layers and other neural network structures, train the deep neural network architecture, obtain the environmental conditions used to simulate the system, refrigeration system, and fan power system according to the environmental conditions, and calculate the ice thickness estimation module that best matches the current simulated environmental conditions.

[0066] S12: Calculating the target ice layer thickness estimation module that matches the built-in environmental conditions through the recommended model, and generating a calculation trigger instruction; the calculation trigger instruction is used to control the target ice layer thickness estimation module to run according to the program logic stored locally, and output the ice layer thickness.

[0067] The calculation trigger instruction includes information of the target ice thickness estimation module.

[0068] The ice thickness estimation module generally includes a calculation unit, or the target ice thickness estimation module includes a calculation unit, a sensor and a signal generating device, wherein the calculation unit includes a processor and a memory. Taking the ice thickness estimation module that calculates the ice thickness based on laser signals as an example, it includes a laser emitting device, a laser receiving device and a calculation unit. The logic of calculating the ice thickness runs on the processor and circuit integrated inside the calculation unit, for example, generating instructions to control the laser emitting device, and the laser receiving device performs corresponding actions. The above-mentioned program for estimating the ice thickness based on laser signals corresponds to the technical method of intellectual property protection to be detected: "Calculate the position of the laser reflected back to the inside of the aircraft skin after the laser passes through the laser transmission and reflection layer embedded in the aircraft skin layer, and calculate the thickness of the ice layer."

[0069] After the recommended model calculates and obtains a target ice thickness estimation module that matches the current environmental parameters, a trigger instruction for starting the target ice thickness estimation module is generated.

[0070] The recommended model calculates based on the objective environmental conditions that the module that best suits the ice thickness calculation scenario corresponding to the current environmental conditions is the target ice thickness estimation module. Objective data proves that under the current environmental conditions, the various steps of estimating the ice thickness by the target ice thickness estimation module are convenient, economical, and achieve relatively good results. Therefore, it can be determined that setting the target ice thickness estimation module is of application value under the current environmental conditions.

[0071] On this basis, the embodiment of the present application also detects the operating results of the target ice layer thickness estimation module to further determine whether the intellectual property rights adopted by the target ice layer thickness estimation module have application value under the current environmental conditions.

[0072] S13: Inputting the ice thickness to a functional module that uses the ice thickness, and detecting the value of the target ice thickness estimation module applied to the built-in environmental condition according to a response result received by the functional module executing the local logic.

[0073] The ice thickness functional module is used to receive the ice thickness, perform further operations on the ice thickness, and execute further operations to obtain a response result. If the response result can further prove the correctness of the ice thickness output by the target ice thickness estimation module, it is determined that the target ice thickness estimation module has application value under the current built-in environmental conditions.

[0074] The functional module using the ice layer thickness refers to taking the ice layer thickness as input data and obtaining a module or functional module that can solve other problems after further logical operation.

[0075] For example, in one embodiment, the functional module using the ice thickness may be a de-icing system.

[0076] In one embodiment, the functional module using the ice thickness may be a display device of the interactive system.

[0077] When the functional module using the ice thickness is a deicing system or a deicing device, executing step S13 may be implemented by the following steps:

[0078] S131: Inputting the ice layer thickness into the deicing device corresponding to the ice layer thickness.

[0079] The deicing devices for ice thickness can be different deicing modes of the same deicing system; or the deicing devices for ice thickness can be different deicing systems. The deicing effects of different deicing devices can be calibrated in advance to determine which type of ice layer has a better melting effect for each deicing device. In this embodiment, fuselage icing can be classified based on ice thickness, and deicing devices matching different ice thicknesses can be calibrated in advance.

[0080] The recommendation module recommends the most suitable target ice thickness estimation module for the environmental model device under the currently simulated environmental conditions. Then the ice thickness output by the target ice thickness estimation module should be accurate. Therefore, the deicing system that is most suitable for the currently simulated environmental conditions is used to melt the ice. If the ablation effect is good, it is objectively verified that the target ice thickness estimation module matches the deicing system that is most suitable for the currently simulated environmental conditions, and the target ice thickness estimation module can accurately estimate the ice thickness under the currently simulated environmental conditions.

[0081] S132: Detecting that the de-icing device operates according to the local device program and receiving a signal from the ice layer detection device for ice layer removal within a preset time, determining that the target ice layer thickness estimation module has application value under the built-in environmental conditions; the ice layer detection device is used to detect ice layer on the fuselage surface.

[0082] The ice layer detection device may be a device installed in an icing wind tunnel and used only to detect whether ice has formed on the fuselage. For example, the ice layer detection device may be installed to heat the surface of the aircraft. After the heating stops, the surface temperature is measured as the surface cools, and whether ice has formed on the surface is determined based on the measured temperature. The ice layer detection device returns the detection signal to the electronic device. If the ice layer is eliminated, the target ice layer thickness estimation module detected should have application value under the built-in environmental conditions; if the ice layer is not eliminated, the target ice layer thickness estimation module detected should have no application value under the built-in environmental conditions.

[0083] When the functional module using the ice thickness is a display device, executing step S13 may be implemented by the following steps:

[0084] S13-1: Inputting the ice layer thickness into the display device.

[0085] S13-2: When the display device displays the ice layer thickness in a preset manner, a user's determination operation on the ice layer thickness based on the display device is collected, and it is determined that the target ice layer thickness estimation module has application value under the built-in environmental conditions.

[0086] The display device can display the ice thickness output by the target ice thickness estimation module in the form of a graph, a curve or text. At the same time, the display device can also retrieve pre-stored data for display, for example, it can capture the ice thickness calibration value obtained by manually detecting the ice thickness after the aircraft undergoes a wind tunnel test based on the built-in environmental conditions in the database. The display device simultaneously displays the ice thickness output by the target ice thickness estimation module and the ice thickness calibration value, and can also display the difference between the two.

[0087] If a corresponding signal of a user confirmation operation on the ice thickness output by the target ice layer thickness estimation module is received, it is determined that the target ice layer thickness estimation module has application value under the built-in environmental conditions; if a corresponding signal of a user confirmation operation on the ice layer thickness output by the target ice layer thickness estimation module is not received, it is determined that the target ice layer thickness estimation module should not have application value under the built-in environmental conditions.

[0088] The method for detecting the application value of the ice thickness estimation module proposed in the embodiment of the present application simulates specific environmental conditions through an environmental simulation device, and generates conditions corresponding to the built-in environmental conditions, such as supercooled water droplets, snow, ice crystals, and designated incoming flow. The recommendation model selects a target ice thickness estimation module that matches the built-in environmental conditions from multiple ice thickness estimation modules according to the environmental parameters associated with the built-in environmental conditions, and then verifies the accuracy of the ice thickness output by the ice thickness estimation module under the built-in environmental conditions, thereby detecting under what environment the ice thickness estimation module has application value; if the ice thickness estimation module has application value under certain environmental conditions, then the logic of the ice thickness estimation module outputting the ice thickness and the data used to run the logic are also applicable under the environmental conditions, so that the detection result of the applicable environmental conditions of the target ice thickness estimation module can further verify whether the logic of the ice thickness estimation module outputting the ice thickness and the environmental conditions applicable to the adopted data are applicable to specific environmental conditions, that is, to detect the application value of the ice thickness estimation module under specific environmental conditions. According to the application value of the ice thickness estimation module under specific environmental conditions obtained by the above detection, a more economically valuable layout can be made for the investment and maintenance of products or product technical solutions and product-related intellectual property rights.

[0089] The present application embodiment also proposes an implementation method of a target ice thickness estimation module that is matched with built-in environmental conditions by using a recommended model for calculation; step S12 includes sub-steps:

[0090] S121: Collect environmental conditions under the built-in environmental conditions and perform feature conversion to obtain environmental condition features; the environmental conditions include temperature, water droplets, water content, ice and snow, flow conditions, liquid water content and visibility.

[0091] For example, after the environmental simulation device starts running for a period of time, the temperature, water droplets, water content, snow, flow conditions, liquid water content and visibility can be collected at preset intervals, the collected parameters can be converted into features, and the features can be encoded in the time dimension to obtain the environmental condition features represented in the form of a matrix. K .

[0092] ;

[0093] in, Indicates the first time of collecting environmental conditions, , ,... Each is a characteristic of an environmental condition; for example, is the temperature characteristic, is the water drop feature, is the characteristic of the incoming flow condition, is the liquid water content characteristic, is the visibility feature, Refers to the time when the environmental conditions were collected for the mth time.

[0094] S122: taking each ice layer thickness estimation module as a current ice layer thickness estimation module in turn, and obtaining a previous hardware unit that provides input data to the current ice layer thickness estimation module.

[0095] When the current ice thickness estimation module is running, the input data is called from the previous hardware unit for calculation; the previous hardware unit includes a module, a device, a system, a program and an integrated circuit.

[0096] The matching degree between each ice thickness estimation module and the built-in environmental conditions is calculated, and then a target ice thickness estimation module with the highest matching degree is selected from multiple ice thickness estimation modules.

[0097] For example, if the ice thickness estimation module collects multi-angle image data and inputs it into a network model, and detects the ice thickness of the aircraft in operation through the network model, then the corresponding previous hardware unit includes an image acquisition unit. If the ice thickness estimation module detects the ice thickness through ultrasonic signals, then the previous hardware unit includes an ultrasonic transmitter and an ultrasonic collector.

[0098] The last hardware unit that called data when the current ice thickness estimation module was running can be obtained by reading the ice thickness estimation module operation log or detecting the ice thickness estimation module interface. After obtaining the last hardware unit, the relevant state of the last hardware unit executing the local program can be collected to obtain the first feature; the relevant state of the current ice thickness estimation module running the local logic and reading data from the last hardware unit can be collected to obtain the second feature.

[0099] If the number of the previous hardware unit is multiple, the following steps may be performed after executing step S122:

[0100] S12-1: Convert the output data of each hardware unit, the form of collected data, operating conditions, execution efficiency and resource consumption into features to obtain a first feature.

[0101] For example, the output data of the previous hardware unit of a certain ice thickness estimation module is image features, the operating condition of the hardware unit is that the visibility is greater than Lkm, and the execution efficiency of the hardware unit in processing image data is , the resources consumed are . If the image features are represented as cells, then the first feature of a hardware unit is It can be expressed as , the value of i is an integer greater than zero.

[0102] S12-2: Testing the execution efficiency and resource consumption of the electronic device when the current ice thickness estimation module runs according to the program logic stored in the target ice thickness estimation module, and performing feature conversion to obtain a second feature.

[0103] Referring to the above example, the execution efficiency of the electronic device when reading the image features from the previous hardware unit is detected and the resources consumed are , according to the above method, we get the second feature .

[0104] S12-3: Combining the first feature and the second feature to obtain a hardware condition feature matrix of the current ice thickness estimation module.

[0105] Hardware Condition Feature Matrix Q It can be expressed as, .

[0106] S123: Utilize the previous hardware unit to query the target environmental condition feature in the environmental condition features, and weight the target environmental condition feature in the environmental condition features.

[0107] The target environmental condition is a feature that the previous hardware unit pays more attention to under the built-in environmental condition simulated by the environmental simulation device. The target ice thickness estimation module that matches the current built-in environmental condition is inferred based on the target environmental condition feature. It not only pays attention to whether the local operation of the ice thickness estimation module is suitable for the current environmental condition, but also pays attention to whether the overall operation of the ice thickness estimation module is suitable for the current environmental condition, especially the operation behavior of the upstream hardware that provides input data for the ice thickness estimation module.

[0108] Based on the obtained hardware condition feature matrix Q and environmental conditions K , an example of the present application provides a specific method for implementing step S123; step S123 includes sub-steps S1231 and S1232;

[0109] S1231: Calculate the matrix product between the hardware condition feature matrix and the transposed environmental condition feature matrix to obtain a weight parameter.

[0110] Figure 3 is a structural diagram of a recommendation model given as an example in this application, such as Figure 3 As shown in Figure 2, the recommendation model includes a first input layer and a second input layer. The first input layer is built based on a long short-term memory neural network (LSTM). K Input the first input layer, the first input layer can mine the temporal correlation of environmental condition features, the second input layer is built based on a multi-layer perceptron (MLP), and the hardware condition feature matrix is ​​input into the second input layer. The first input layer and the second input layer are connected to a convolutional neural network built based on the attention mechanism. K and Q Perform matrix calculation to obtain the weight parameter α for weighted operation of the input features, expressed as the following formula:

[0111] . T Express K Perform a transpose operation, Overall expression The shrinkage dimension, Express Perform dimensionality reduction operations. SoftMax represents normalization operations.

[0112] S1232: Perform a weighting operation on the target environmental condition features in the environmental condition features using the weight parameters.

[0113] The assignment of the environmental condition feature sequence to the first input layer can be expressed as ; , It is the value of the corresponding event feature.

[0114] , ,to ,as well as , , It is the value corresponding to the environmental characteristics.

[0115] The weighting operation of the target environmental condition feature in the environmental condition feature can be expressed by the following formula:

[0116] .

[0117] Step S124: the recommendation model calculates the matching degree between the current ice thickness estimation module and the environmental condition based on the weighted environmental condition characteristics.

[0118] Continue to refer Figure 3 The convolutional neural network built based on the attention mechanism is connected with the fully connected mapping layer (Linear), the residual link normalization layer (Add&Norm), and the output layer. The output layer can be built based on the feedforward neural network layer (FeedforwardMultilayerPerceptron, FNN). The convolutional neural network built based on the attention mechanism outputs V The target environmental condition characteristics in the algorithm are weighted so that the subsequent matching degree calculation pays more attention to the environmental characteristics that are adapted to the operation mechanism of the current ice thickness estimation module, thereby outputting a more accurate matching degree.

[0119] This application can be used as an example and K Perform matrix calculation to obtain the matching degree between the current ice thickness estimation module and the corresponding scene of the built-in environmental conditions.

[0120] After the convolutional neural network constructed by the attention mechanism outputs the corresponding matching degrees of all ice thickness estimation modules, they are input into the fully connected mapping layer after being processed by the residual link normalization layer. On this basis, the fully connected mapping layer can screen out the ice thickness estimation module with the highest matching degree, which is the target ice thickness estimation module for calculating the ice thickness under the current built-in environmental conditions.

[0121] S125: Select the ice layer thickness estimation module with the highest similarity as the target ice layer thickness estimation module.

[0122] S126: Generate a trigger instruction for controlling the target ice layer thickness estimation module.

[0123] The feed-forward neural network layer generates trigger instructions based on the screened target ice thickness estimation module.

[0124] A trigger instruction is sent to a target ice thickness estimation module. The target ice thickness estimation module responds to the trigger instruction, starts running a local program for calculating ice thickness, controls relevant interfaces or sensors to collect data, and outputs ice thickness. The local program for calculating ice thickness is set according to the protected intellectual property scheme for calculating ice thickness.

[0125] In the process of training the recommendation network, specific environmental condition samples and algorithm samples are collected. The algorithm samples are multiple methods for calculating ice thickness. Then, the scores of various methods for calculating ice thickness in the corresponding environmental scenarios when the environmental condition samples are met are calibrated. The scores can be determined based on the difference between the ice thickness obtained by the ice thickness calculation method and the actual ice thickness. The difference objectively indicates whether the method for calculating ice thickness matches the corresponding environmental scenario when the environmental condition samples are met. Then, various methods for calculating ice thickness are sorted based on the difference, and the ice thickness calculation method with the highest score is output. The ice thickness calculation method with the highest score is marked as M.

[0126] The activation function of the convolutional neural network built based on the attention mechanism is set to . Given the loss function for calculating the loss value: , according to the loss function, adjust the relevant parameters in the convolutional network built based on the attention mechanism until the loss function converges. y is the matching degree of the convolutional neural network output under the control of the activation function, It is the score of the ice thickness calculation method corresponding to the current algorithm sample. Indicates the score of the method for calculating ice thickness corresponding to the algorithm sample with the highest matching degree of the output of the fully connected mapping layer.

[0127] The embodiment of the present application also proposes that the previous hardware unit that provides input data for each ice thickness estimation module can be obtained; the program logic stored in the previous hardware unit of the ice thickness estimation module is associated with the program logic stored in the target ice thickness estimation module, and it is preliminarily determined that the target ice thickness estimation module has initial conditions that have application value under built-in environmental conditions.

[0128] Based on the above concept, another method for detecting the application value of an ice thickness estimation module proposed in an embodiment of the present application includes the following steps:

[0129] S201: Detecting the last hardware unit that provides input data to each ice thickness estimation module; when the ice thickness estimation module is running, calling the input data from the last hardware unit for calculation.

[0130] S202: During an icing test on a test piece in an icing wind tunnel, when a built-in environmental condition occurs in any one of the multiple environmental simulation devices, the built-in environmental condition is input into a recommended model.

[0131] S203: Calculate the target ice thickness estimation module matching the built-in environmental conditions through the recommended model, and generate a calculation trigger instruction; the calculation trigger instruction is used to control the target ice thickness estimation module to run according to the logic of the local corresponding intellectual property to be detected, and output the ice thickness.

[0132] S204: When the program logic stored in the previous hardware unit is associated with the program logic stored in the target ice thickness estimation module, a positive score is marked for the previous hardware unit.

[0133] The attribution of each ice thickness estimation module to the previous hardware unit can be stored locally in advance. In the process of executing the method for detecting the application value of the intellectual property rights corresponding to the underlying logic of the product operation based on the product implementation results, the recommendation module outputs a calculation trigger instruction, and can also add an output layer based on the fully connected layer in the original structure of the recommendation module to output the target ice thickness estimation module. For the target ice thickness estimation module output by the recommendation module, the attribution of the previous hardware unit stored locally is retrieved.

[0134] Whether the program logic stored in the previous hardware unit is associated with the program logic stored in the target ice thickness estimation module can be used to determine whether the hardware unit and the target ice thickness estimation module are technically related. For example, the output of the previous hardware unit can be directly input into the target ice thickness estimation module without data conversion or other processing. In this case, the program logic stored in the previous hardware unit is associated with the program logic stored in the target ice thickness estimation module.

[0135] When the program logic stored in the previous hardware unit is not associated with the program logic stored in the target ice thickness estimation module, a negative score is marked for the previous hardware unit.

[0136] S205: If the score of the target ice thickness estimation module corresponding to the previous hardware unit mark is higher than a preset threshold, the ice thickness is input into a functional module that uses the ice thickness, and the value of the target ice thickness estimation module applied to the built-in environmental condition is detected based on the response result received by the local logic executed by the functional module.

[0137] The embodiment of the present application provides a method for adaptively adjusting the recommendation module. Assuming that the current method for detecting the application value of the ice thickness estimation module is executed for the jth time, the environmental simulation device simulates the built-in environmental condition A, the recommendation module calculates the ice thickness estimation module A that matches the built-in environmental condition A, generates a calculation trigger instruction for the ice thickness estimation module A, sends the calculation trigger instruction to the ice thickness estimation module A, and the ice thickness estimation module A responds to the instruction to calculate the current ice thickness and outputs the ice thickness to the functional module that uses the ice thickness. The functional module receives a response result received by executing local logic, determines that the target ice thickness estimation module is adapted to the built-in environmental condition based on the response result, and further determines that the target ice thickness estimation module has application value under the built-in environmental condition, thereby taking the built-in environmental condition as the historical environmental condition and establishing an association with the ice thickness estimation module A; the data range of the association is the same as the matching degree.

[0138] The correlation degree of the ice thickness estimation module A is input into the recommended model.

[0139] In the j+nth execution of the ice thickness estimation module application value detection method, it can be determined whether the built-in environmental conditions simulated by the environmental simulation device are the same as the historical environmental conditions. When the built-in environmental conditions are the same as the historical environmental conditions, after the recommendation model obtains the matching degree of each ice thickness estimation module with the historical environmental conditions, the matching degree of the ice thickness estimation module A can be superimposed with the correlation degree to obtain a new matching degree of the ice thickness estimation module A; the ice thickness estimation module A with the updated matching degree is then sorted together with other ice thickness estimation modules to screen out the ice thickness estimation module with the highest matching degree.

[0140] After inputting the ice thickness to a function module using the ice thickness and executing a response result received by the local logic according to the function module, the method further includes:

[0141] If the target ice thickness estimation module is detected to have application value under the built-in environmental condition according to the response result received by executing the local logic of the functional module, the environmental condition corresponding to the built-in environmental condition is used as the historical environmental condition;

[0142] Establishing a correlation between the historical environmental conditions and the target ice thickness estimation module;

[0143] If the specific environment simulation device is detected to perform the historical environmental condition next time, the information of the ice thickness estimation module with which the historical environmental condition has a correlation is input into the recommendation model;

[0144] This execution calculates the target ice thickness estimation module that matches the built-in environmental conditions through the recommendation model, and in the process of generating a calculation trigger instruction, after obtaining the matching degree of each ice thickness estimation module with the historical environmental conditions, the matching degree of the ice thickness estimation module with the correlation is increased.

[0145] Figure 4 : is a functional module diagram of the ice thickness estimation module application value detection device proposed in the embodiment of the present application, such as Figure 4 As shown, the ice thickness estimation module application value detection device includes:

[0146] An input module 41 is used for inputting the built-in environmental condition into the recommended model when a built-in environmental condition of any one of the multiple environmental simulation devices occurs during an icing test of the test piece in an icing wind tunnel;

[0147] An instruction generation module 42 is used to calculate the target ice thickness estimation module matching the built-in environmental conditions through the recommended model, and generate a calculation trigger instruction; the calculation trigger instruction is used to control the target ice thickness estimation module to run according to the program logic stored locally, and output the ice thickness;

[0148] The value detection module 43 is used to input the ice thickness to the functional module using the ice thickness, and detect the value of the target ice thickness estimation module applied to the built-in environmental condition according to the response result received by the functional module executing the local logic.

[0149] Figure 4 The ice thickness estimation module application value detection device provided in the embodiment shown can be used to implement the present invention Figures 1 to 3 The technical solution of the method embodiment shown, its implementation principle and technical effects can be further referred to the relevant description in the method embodiment.

[0150] Optionally, the functional module using the ice thickness includes a display device; and the value detection module includes:

[0151] A first input submodule, used for inputting the ice layer thickness into the display device;

[0152] The display submodule is used to collect the user's determination operation on the ice layer thickness based on the display device when the display device displays the ice layer thickness in a preset manner, and determine that the target ice layer thickness estimation module has application value under the built-in environmental conditions.

[0153] Optionally, the functional module using the ice layer thickness includes a deicing device; and the value detection module includes:

[0154] a second input submodule, inputting the ice layer thickness into the deicing device corresponding to the ice layer thickness;

[0155] The signal receiving submodule is used to determine that the target ice thickness estimation module has application value under the built-in environmental conditions when it detects that the de-icing device is operating according to the local device program and receives the signal of ice removal fed back by the ice detection device within a preset time; the ice detection device is used to detect ice on the surface of the fuselage.

[0156] Optionally, the device further comprises:

[0157] A collection submodule, used to collect environmental conditions under the built-in environmental conditions and perform feature conversion to obtain environmental condition features; the environmental conditions include temperature, water droplets, water content, ice and snow, incoming flow conditions, liquid water content and visibility;

[0158] A query submodule is used to sequentially use each ice thickness estimation module as a current ice thickness estimation module, query the calling interface of the current ice thickness estimation module, and obtain the previous hardware unit that provides input data to the current ice thickness estimation module; when the current ice thickness estimation module is running, the input data is called from the previous hardware unit for calculation; the previous hardware unit includes a module, a device, a system, a program, and an integrated circuit;

[0159] The instruction generation module specifically includes:

[0160] A feature query submodule, configured to query a target environmental condition feature in the environmental condition features by using the previous hardware unit through the recommendation module, and weight the target environmental condition feature in the environmental condition features;

[0161] A weighted calculation submodule, used for calculating the matching degree between the current ice thickness estimation module and the environmental condition based on the weighted environmental condition characteristics through the recommendation model;

[0162] A selection submodule, configured to select the ice thickness estimation module with the highest similarity through the recommendation model and determine it as the target ice thickness estimation module;

[0163] The instruction generation submodule is used to generate a trigger instruction for controlling the target ice layer thickness estimation module.

[0164] Optionally, the device further comprises:

[0165] A hardware unit detection module is used to detect the last hardware unit that provides input data to each ice thickness estimation module; when the ice thickness estimation module is running, the input data is called from the last hardware unit for calculation;

[0166] a marking module, configured to mark a positive score for the previous hardware unit when the program logic stored in the previous hardware unit is associated with the program logic stored in the target ice thickness estimation module;

[0167] The value detection module is specifically used to input the ice thickness into a functional module that uses the ice thickness if the score of the target ice thickness estimation module corresponding to the previous hardware unit mark is higher than a preset threshold, and detect the value of the target ice thickness estimation module applied to the built-in environmental condition according to the response result received by the local logic executed by the functional module.

[0168] Optionally, the device further comprises:

[0169] The adaptive adjustment module is used to run the following steps after each execution of step S13 of the ice thickness estimation module application value detection method: if the target ice thickness estimation module is detected to have application value under the built-in environmental conditions according to the response result received by the local logic executed by the functional module, the environmental conditions corresponding to the built-in environmental conditions are used as historical environmental conditions; and the historical environmental conditions are associated with the target ice thickness estimation module.

[0170] The adaptive adjustment module is also used to, during each execution of the ice thickness estimation module application value detection method, if it is detected that a specific environmental simulation device performs the historical environmental condition, input the information of the ice thickness estimation module with a correlation with the historical environmental condition into the recommendation model; during this execution, the target ice thickness estimation module that matches the built-in environmental condition is calculated through the recommendation model, and in the process of generating a calculation trigger instruction, after obtaining the matching degree of each ice thickness estimation module with the historical environmental condition, the matching degree of the ice thickness estimation module with a correlation is increased.

[0171] Optionally, the device further comprises:

[0172] The feature acquisition module is used to convert the output data of each hardware unit, the form of the collected data, the operating conditions, the execution efficiency and the resource consumption into features to obtain a first feature; test the execution efficiency and resource consumption of the electronic device when the current ice thickness estimation module runs according to the logic of the intellectual property to be detected, and perform feature conversion to obtain a second feature; combine the first feature and the second feature to obtain a hardware condition feature matrix of the current ice thickness estimation module;

[0173] The weighted calculation submodule is specifically used to calculate the matrix product between the hardware condition feature matrix and the transposed environmental condition feature matrix to obtain a weight parameter; and to perform a weighted operation on the target environmental condition feature in the environmental condition features using the weight parameter.

[0174] Regarding the various modules / units included in the various devices described in the above embodiments, they can be software modules / units, or hardware modules / units, or they can be partially software modules / units and partially hardware modules / units. For example, for various devices applied to or integrated in a chip, the various modules / units included therein can all be implemented in the form of hardware such as circuits, or at least some of the modules / units can be implemented in the form of software programs, which run on a processor integrated inside the chip, and the remaining modules / units can be implemented in the form of hardware such as circuits; for various devices applied to or integrated in a chip module, the various modules / units included therein can all be implemented in the form of hardware such as circuits, and different modules / units can be located in the same component of the chip module (such as a chip, circuit module, etc.) or in different components, or at least some of the modules / units can be implemented in the form of software programs. The software program may be implemented in the form of a program, which runs on a processor integrated in the chip module, and the remaining modules / units may be implemented in the form of hardware such as circuits; for each device applied to or integrated in the electronic terminal device, each module / unit contained therein may be implemented in the form of hardware such as circuits, and different modules / units may be located in the same component (for example, a chip, a circuit module, etc.) or in different components in the electronic terminal device, or at least some modules / units may be implemented in the form of a software program, which runs on a processor integrated in the electronic terminal device, and the remaining (if any) modules / units may be implemented in the form of hardware such as circuits.

[0175] Figure 5 A structural diagram of a computing device provided in an embodiment of the present application, the computing device 500 includes a processor 510, a memory 511, and a computer program stored in the memory 511 and executable on the processor 510. The processor 510 implements the steps in the aforementioned method embodiment when executing the program. The computing device provided in the embodiment can be used to execute the technical solution of the method embodiment shown above, and its implementation principle and technical effects can be further referenced to the method.

[0176] In one embodiment of the present application, a computer storage medium is provided. The storage medium is a readable storage medium. A program is stored on the storage medium. The stored program includes a method that can be loaded by a processor and process any of the above embodiments.

[0177] Those skilled in the art will appreciate that all or part of the functions of the various methods in the above-mentioned embodiments can be implemented by hardware or by computer programs. When all or part of the functions in the above-mentioned embodiments are implemented by computer programs, the program can be stored in a computer storage medium, and the storage medium can include: a read-only memory, a random access memory, a disk, an optical disk, a hard disk, etc., and the program is executed by a computer to implement the above-mentioned functions. For example, the program is stored in the memory of the device, and when the program in the memory is executed by the processor, all or part of the above-mentioned functions can be implemented. In addition, when all or part of the functions in the above-mentioned embodiments are implemented by computer programs, the program can also be stored in a storage medium such as a server, another computer, a disk, an optical disk, a flash disk or a mobile hard disk, and can be downloaded or copied and saved in the memory of the local device, or the system of the local device is updated, and when the program in the memory is executed by the processor, all or part of the functions in the above-mentioned embodiments can be implemented.

[0178] The above specific examples are used to illustrate the present application, which is only used to help understand the present application and is not intended to limit the present application. For technicians in the technical field to which the present application belongs, they can also make some simple deductions, deformations or substitutions based on the ideas of the present application.

Claims

1. A method for detecting the application value of an ice thickness estimation module, characterized in that: Applied to electronic equipment, the method comprises: During the icing test of the test piece in the icing wind tunnel, when a built-in environmental condition occurs in any one of the multiple environmental simulation devices, the built-in environmental condition is input into the recommended model; The target ice thickness estimation module that matches the built-in environmental conditions is calculated by the recommended model to generate a calculation trigger instruction; the calculation trigger instruction is used to control the target ice thickness estimation module to run according to the program logic stored locally and output the ice thickness; inputting the ice thickness to a function module using the ice thickness, and detecting the value of the target ice thickness estimation module applied to the built-in environmental condition according to a response result received by the function module executing the local logic; The method further comprises: Collecting environmental conditions under the built-in environmental conditions and performing feature conversion to obtain environmental condition features; the environmental conditions include temperature, water droplets, water content, ice and snow, incoming flow conditions, liquid water content, and visibility; Taking each ice thickness estimation module as the current ice thickness estimation module in turn, obtaining the previous hardware unit that provides input data to the current ice thickness estimation module; calling the input data from the previous hardware unit for calculation when the current ice thickness estimation module is running; the previous hardware unit includes a module, a device, a system, a program and an integrated circuit; The target ice thickness estimation module matching the built-in environmental conditions is calculated by the recommended model to generate a calculation trigger instruction, including: Using the previous hardware unit to query the target environmental condition feature in the environmental condition features, and weighting the target environmental condition feature in the environmental condition features; Calculating the matching degree between the current ice thickness estimation module and the environmental condition based on the weighted target environmental condition characteristics through the recommendation model; Select the ice layer thickness estimation module with the highest similarity as the target ice layer thickness estimation module; generating a trigger instruction for controlling the target ice layer thickness estimation module; The number of the previous hardware unit is multiple, and the method further includes: Convert the output data, the form of collected data, the operating conditions, the execution efficiency and the resource consumption of each hardware unit into features to obtain a first feature; Testing the execution efficiency and resource consumption of the electronic device when the current ice thickness estimation module runs according to the logic of the target ice thickness estimation module, and performing feature conversion to obtain a second feature; Combining the first feature and the second feature to obtain a hardware condition feature matrix of the current ice thickness estimation module; Utilizing the previous hardware unit to query the target environmental condition feature in the environmental condition features, and weighting the target environmental condition feature in the environmental condition features, comprises: Calculating the matrix product between the hardware condition feature matrix and the transposed environmental condition feature matrix to obtain a weight parameter; Using the weight parameter, performing a weighting operation on the target environmental condition feature among the environmental condition features; The functional module using the ice thickness includes a display device; inputting the ice thickness to the functional module using the ice thickness, and detecting the value of the target ice thickness estimation module applied to the built-in environmental condition according to the response result received by the local logic executed by the functional module, including: inputting the ice layer thickness into the display device; When the display device displays the ice layer thickness in a preset manner, a user's determination operation on the ice layer thickness based on the display device is collected, and it is determined that the target ice layer thickness estimation module has application value under the built-in environmental conditions.

2. The method according to claim 1, characterized in that The functional module using the ice thickness also includes a de-icing device, inputting the ice thickness to the functional module using the ice thickness, and detecting the value of the target ice thickness estimation module applied to the built-in environmental condition according to the response result received by the functional module executing the local logic, including: inputting the ice thickness to the de-icing device corresponding to the ice thickness; When it is detected that the de-icing device operates according to the local logic and a signal indicating that the ice layer has been removed is received from the ice layer detection device within a preset time, it is determined that the target ice layer thickness estimation module has application value under the built-in environmental conditions; the ice layer detection device is used to detect ice layer on the surface of the fuselage.

3. The method according to claim 1, characterized in that The method further comprises: Detecting a previous hardware unit that provides input data to each ice thickness estimation module; when the ice thickness estimation module is running, calling the input data from the previous hardware unit for calculation; When the program logic stored in the previous hardware unit is associated with the program logic stored in the target ice thickness estimation module, marking a positive score for the previous hardware unit; Inputting the ice thickness into a function module using the ice thickness includes: If the score of the target ice layer thickness estimation module corresponding to the previous hardware unit mark is higher than a preset threshold, the ice layer thickness is input to a functional module that uses the ice layer thickness.

4. The method according to claim 1, characterized in that: After inputting the ice thickness to a function module using the ice thickness and executing a response result received by the local logic according to the function module, the method further includes: If the target ice thickness estimation module is detected to have application value under the built-in environmental condition according to the response result received by executing the local logic of the functional module, the environmental condition corresponding to the built-in environmental condition is used as the historical environmental condition; Establishing a correlation between the historical environmental conditions and the target ice thickness estimation module; If the specific environment simulation device is detected to perform the historical environmental condition next time, the information of the ice thickness estimation module with which the historical environmental condition has a correlation is input into the recommendation model; This execution calculates the target ice thickness estimation module that matches the built-in environmental conditions through the recommendation model, and in the process of generating a calculation trigger instruction, after obtaining the matching degree of each ice thickness estimation module with the historical environmental conditions, the matching degree of the ice thickness estimation module with the correlation is increased.

5. An ice thickness estimation module application value detection device using the ice thickness estimation module application value detection method according to any one of claims 1 to 4, characterized in that: Set in an electronic device, the device includes: An input module, used for inputting the built-in environmental condition into the recommended model when a built-in environmental condition of any one of the multiple environmental simulation devices occurs during an icing test of the test piece in an icing wind tunnel; An instruction generation module, used for calculating the target ice thickness estimation module matching the built-in environmental conditions through the recommended model, and generating a calculation trigger instruction; the calculation trigger instruction is used to control the target ice thickness estimation module to run according to the program logic stored locally, and output the ice thickness; A value detection module is used to input the ice thickness to a functional module that uses the ice thickness, and detect the value of the target ice thickness estimation module applied to the built-in environmental condition according to a response result received by the functional module executing the local logic.

6. A computing device, characterized in that It comprises at least one processor and at least one memory connected to the processor; the memory stores program instructions for being executed by the processor, and the processor calls the program instructions to execute any method according to claims 1 to 5.

7. A computer storage medium storing computer instructions, characterized in that: The computer instructions enable the computer to execute the method according to any one of claims 1 to 5.

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