Fault diagnosis system and method of heater for wind tunnel test

Abstract

The invention provides a fault diagnosis system and method for a heater for a wind tunnel test, and relates to the technical field of heater fault diagnosis, and the system comprises an infrared imaging assembly for monitoring the heater in all directions, and a voiceprint positioning assembly. The heater control module is used for controlling the heater to start and acquiring environment parameters of the heater; the interior of the heater heats air to obtain airflow for a wind tunnel test; when the heater is started, the infrared imaging assembly and the voiceprint positioning assembly are respectively used for acquiring an infrared image and a voiceprint image outside the heater in real time; the switch is used for sending the collected data to the fault diagnosis module; and the fault diagnosis module determines a current test working condition according to the environmental parameters, and compares the environmental parameters, the infrared image and the voiceprint image with historical data under the current test working condition to obtain a fault diagnosis result. According to the scheme, non-contact fault comprehensive monitoring and diagnosis are realized, and the fault diagnosis accuracy of the heater for the wind tunnel test is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of fault diagnosis of wind tunnel tests, and in particular to a fault diagnosis system and method for a heater used in a wind tunnel test. Background Art

[0002] Wind tunnel tests are used to simulate the performance of research objects in airflow. A high-temperature wind tunnel is an experimental device that can simulate the airflow environment and aerodynamic effects of aircraft and spacecraft during high-speed flight. It forms a high-speed airflow by passing high-temperature and high-pressure air through the pipes in the main body of the wind tunnel to simulate the airflow environment of aircraft during high-speed flight. The airflow environment in a high-temperature wind tunnel is generated by a heater. As a special equipment with a high usage rate in high-temperature wind tunnels, the heater is used more than 6,000 times a year, and the operating temperature can reach 1000K~7000K. It runs at full load all year round. Therefore, once the heater fails, it may cause significant losses. For example, damage to the heating element, overheating, shell damage, and sealing ring failure will cause high-temperature gas leakage, seriously affecting the safety of wind tunnel operation.

[0003] Currently, wind tunnel test heaters are mainly maintained annually and after-the-fact maintenance is used. Regular maintenance is to use one month at the beginning of each year to perform equipment maintenance and stop the test. At this time, the heater is in the best condition, and there is even a phenomenon of over-maintenance. After-the-fact maintenance is maintenance performed after the heater has already failed. Since the heater is a high-temperature dangerous equipment, once there is damage, leakage, over-temperature and other failures, the consequences will be disastrous. After the failure occurs, the wind tunnel test will be forced to stop. The hidden dangers are difficult to be discovered in the first time, which affects the efficiency of the wind tunnel test. Therefore, there is an urgent need to provide a fault diagnosis system and method for wind tunnel test heaters. Summary of the invention

[0004] The present invention provides a fault diagnosis system and method for a heater for a wind tunnel test. The system realizes contactless comprehensive fault monitoring and diagnosis, improves the fault diagnosis accuracy of the heater for a wind tunnel test, and reduces the missed detection rate.

[0005] In a first aspect, the present invention provides a fault diagnosis system for a heater for wind tunnel testing, comprising: an infrared imaging component, a voiceprint positioning component, a switch, a heater, a heater control module, and a fault diagnosis module; The heater control module controls the heater to start and obtains the environmental parameters of the heater; the interior of the heater heats the air to obtain the airflow for the wind tunnel test; the environmental parameters include total temperature, air source pressure and total pressure; The infrared imaging component and the voiceprint positioning component are installed around the heater in a non-contact manner to monitor the heater in all directions; when the heater is started, the infrared imaging component and the voiceprint positioning component are used to collect an infrared image and a voiceprint image of the outside of the heater in real time, respectively; The switch is used to send the environmental parameters, the infrared image and the voiceprint image to the fault diagnosis module; The fault diagnosis module is used to determine the current test conditions based on the environmental parameters, and compare the environmental parameters, the infrared image and the voiceprint image with the historical data under the current test conditions to obtain a fault diagnosis result; and when the fault diagnosis result is determined to be a fault, the moment is confirmed as the fault moment, and the fault solution is determined based on the infrared images collected within a preset time period before and after the fault moment.

[0006] In a second aspect, the present invention further provides a fault diagnosis method for a heater for a wind tunnel test, comprising: When the heater is started, the environmental parameters of the heater are obtained, and an infrared image and a voiceprint image of the outside of the heater are collected in real time; The current test condition is determined according to the environmental parameters, and the environmental parameters, the infrared image and the voiceprint image are compared with the historical data under the current test condition to obtain a fault diagnosis result.

[0007] The present invention provides a fault diagnosis system and method for a heater for a wind tunnel test. The system realizes all-round monitoring of the heater for a wind tunnel test by combining an infrared imaging component and a voiceprint positioning component. When the heater is started, comprehensive fault diagnosis can be performed in real time based on the acquired environmental parameters and the collected external infrared images and voiceprint images, thereby providing a contactless fault diagnosis method for the heater for a wind tunnel test, realizing automatic association of multi-state parameters of the heater, improving the accuracy of typical fault diagnosis of the heater, reducing the missed detection rate, and improving the intelligence level of fault diagnosis. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0009] Figure 1 is a schematic diagram of a fault diagnosis system for a heater for a wind tunnel test provided by an embodiment of the present invention; Figure 2is a schematic diagram of another fault diagnosis system for a heater for wind tunnel testing provided by an embodiment of the present invention; Figure 3 is a flow chart of a fault diagnosis method for a heater for a wind tunnel test provided by an embodiment of the present invention; Among them, 10-infrared imaging component, 20-voiceprint positioning component, 30-switch, 40-heater control module, 50-fault diagnosis module. DETAILED DESCRIPTION

[0010] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0011] The specific implementation of the above concept is described below.

[0012] Please refer to Figure 1 , an embodiment of the present invention provides a fault diagnosis system for a heater for wind tunnel testing, the system comprising: an infrared imaging component 10, a voiceprint positioning component 20, a switch 30, a heater control module 40 and a fault diagnosis module 50; The heater control module 40 controls the heater to start and obtains the environmental parameters of the heater; the air inside the heater is heated to obtain the airflow for the wind tunnel test; the environmental parameters include total temperature, air source pressure and total pressure; The infrared imaging component 10 and the voiceprint positioning component 20 are installed around the heater in a non-contact manner to monitor the heater in all directions; when the heater is started, the infrared imaging component 10 and the voiceprint positioning component 20 are used to collect infrared images and voiceprint images of the outside of the heater in real time, respectively; The switch 30 is used to send the environmental parameters, infrared images and voiceprint images to the fault diagnosis module 50; The fault diagnosis module 50 is used to determine the current test conditions based on environmental parameters, and compare the environmental parameters, infrared images and voiceprint images with historical data under the current test conditions to obtain a fault diagnosis result; and when the fault diagnosis result is that a fault exists, the moment is confirmed as the fault moment, and the fault solution is determined based on the infrared images collected within a preset time period before and after the fault moment.

[0013] In the present invention, by combining the infrared imaging component and the voiceprint positioning component, all-round monitoring of the heater for wind tunnel testing is achieved. When the heater is started, a comprehensive fault diagnosis can be performed in real time based on the acquired environmental parameters and the collected external infrared images and voiceprint images, thereby providing a contactless fault diagnosis method for the heater for wind tunnel testing, realizing automatic association of multi-state parameters of the heater, improving the accuracy of typical fault diagnosis of the heater, reducing the missed detection rate, and improving the intelligence level of fault diagnosis.

[0014] In a preferred embodiment, the heater is obtained by connecting at least two stages of heating components in series; each stage of the heating component uses at least two infrared imaging components.

[0015] In a preferred embodiment, the heater includes a heating element, an electrode rod, a heat-bearing layer, a heat-insulating layer, a pressure-bearing layer and a cooling structure; inside the heater, the heating element is used to heat the air, and the cooling structure is used to circulate cooling water to cool the electrode rod.

[0016] In a preferred embodiment, the fault diagnosis result includes the presence of a fault and the presence of no fault; the presence of a fault includes: the presence of abnormal temperature, and the presence of gas or liquid leakage.

[0017] Specifically, for example, in a wind tunnel test, a heater obtained by connecting five-stage heating components in series is used to heat the air, and the temperature can reach 1100K, so as to obtain an airflow for a high-temperature wind tunnel test. Each stage of the heating component is composed of a heating element, an electrode rod, a heat-bearing layer, a thermal insulation layer, a pressure-bearing layer, a cooling structure and a flange. Each stage of the heating component has 18 electrode rods, one end of which is connected to 380V high voltage electricity, and the other end is connected to the internal heating element. The flange runs through the interior of the heater, and requires insulating ceramic insulation and sealing ring sealing. At the same time, the cooling water is guided to the electrode rod with the help of the cooling structure, and effective cooling is achieved through heat exchange, which can not only ensure the cooling efficiency, but also avoid the risk of fluid leakage through the rigid structure of the pressure-bearing layer. The heating element is located in the temperature-bearing layer, and there is a thermal insulation layer outside the temperature-bearing layer, and there is a pressure-bearing layer outside the thermal insulation layer. Therefore, for this type of heater, liquid leakage, gas leakage and temperature abnormalities may occur during its operation.

[0018] In a more preferred embodiment, the resolution of the infrared imaging component is not less than 256*192, and the frame rate is not less than 25fps; the frequency band of the voiceprint positioning component is 5kHz~72kHz.

[0019] like Figure 1 As shown, there may be several infrared imaging devices and voiceprint positioning devices, which are specifically determined by the heater used in the wind tunnel test. Specifically, following the previous example, Figure 2As shown in the figure, 10 infrared imaging devices and 1 voiceprint positioning device are used in the fault diagnosis system. The resolution of the infrared imaging device is not less than 256*192, the frame rate is not less than 25fps, the temperature measurement distance is 3m, and the measurement range covers 0~300℃; every two infrared imaging devices monitor the first-level heating component, so as to achieve all-round monitoring of the electrode rod of the heater. The voiceprint positioning device has the functions of sound source positioning and visual imaging, covering the frequency band of 5kHz~72kHz, and the field of view is: horizontal ≥60°, vertical ≥45°. The voiceprint positioning device is installed at a horizontal distance of 10m and a height of 10m from the heater, and at a position of 45° when looking down, so as to achieve all-round sound source monitoring of the five-level heater.

[0020] It should be noted that the heater of the present invention can be a high-temperature pressure-bearing heater or a direct-connected heater, and can also perform fault diagnosis on leakage of normal temperature and high-pressure containers.

[0021] In a preferred embodiment, the infrared imaging component, the voiceprint positioning component, and the heater control module are deployed in different network segments, such as Figure 2 As shown, different network switches are used to avoid network conflicts between device systems and improve system network stability; wherein the fault monitoring and diagnosis server is a fault diagnosis module.

[0022] In a preferred embodiment, the fault diagnosis module includes an operating condition determination unit and a temperature diagnosis unit; The working condition determination unit is used to compare the environmental parameters with the historical environmental parameters in the historical data to determine the current test working condition; wherein the historical data records the historical environmental parameters corresponding to each test working condition and the historical temperature range of each electrode rod during normal operation; The temperature diagnosis unit is used to determine the temperature value of each electrode rod based on the infrared image under the current test condition, and compare the temperature value of each electrode rod with the historical temperature range under the current test condition. When the temperature value is not within the historical temperature range, the fault diagnosis result is determined to be a temperature anomaly.

[0023] It should be noted that the historical environmental parameters corresponding to each test condition are the environmental parameters when there is no fault. Continuing from the previous example, when the gas temperature inside the heater reaches 1100K under the current test condition, the historical temperature range of the electrode rod when the heater is operating normally is about 100°C. That is, the historical temperature range is the normal temperature threshold range of the electrode rod. If it exceeds this range, it is considered that there is a temperature abnormality and the heater is working abnormally. Due to different performances under different test conditions, the temperature value of the outside of the heater is different under different test conditions.

[0024] In a preferred embodiment, the operating condition determination unit is used to perform the following operations: When the environmental parameters are the same as the historical environmental parameters, the current test conditions of the environmental parameters are determined to be the test conditions corresponding to the historical environmental parameters; wherein the environmental parameters include total temperature and total pressure of the gas source; When the environmental parameters do not exist in the historical data, the first historical environmental parameter closest to the environmental parameter is determined from the historical data, and it is judged whether the difference between the first historical environmental parameter and the environmental parameter does not exceed the preset threshold. If so, the current test condition of the environmental parameter is determined to be the test condition corresponding to the first historical environmental parameter; otherwise, the current test condition is generated and stored in the historical data.

[0025] It should be noted that the infrared imaging component and the voiceprint positioning component collect data in real time, but only after receiving the specified OPC signal (such as the heater start signal, the heater shut-down signal), they start or stop data storage, and record and store all environmental parameters of the heating equipment during operation: total temperature, total pressure of the gas source, heater power, etc. In this way, it avoids collecting irrelevant data when the heater is not working, improves the quality and effectiveness of the data, and reduces false alarms.

[0026] In the present invention, total temperature and total pressure of the gas source are important environmental parameters that affect the heating conditions of the heater. Therefore, the system automatically obtains the OPC signal (total temperature, total pressure of the gas source pressure) of the environmental parameters of the heater, and adaptively selects the corresponding threshold value from the database of historical environmental parameters as the current test condition of the current heater. In this way, the total temperature and total pressure of the gas source pressure of the environmental parameters are used as index values. If there is no corresponding total temperature and total pressure of the gas source pressure in the historical environmental parameters, the test condition where the threshold value corresponding to the total temperature and total pressure of the gas source pressure is relatively close is found. For example, the threshold value is that the fluctuation range of the total temperature does not exceed 50K, and the fluctuation range of the total pressure of the gas source pressure does not exceed 0.5Mpa. If there is still no suitable threshold value within this range, the system will remind the administrator of the new condition, directly generate the current test condition, and set the threshold value of the current test condition.

[0027] In a preferred embodiment, the temperature diagnosis unit is used to perform the following operations: Under the current test conditions, determine whether the temperature value is the one measured during the first wind tunnel test of the heater on that day; If not, the corresponding fault-free historical temperature interval under the current test condition is used as the normal threshold. When the temperature value is within the normal threshold, the fault diagnosis result is determined to be normal operation; when the temperature value is not within the normal threshold, the fault diagnosis result is determined to be a temperature abnormality.

[0028] It should be noted that the historical temperature range of the electrode rod is the temperature value outside the heater. As mentioned in the previous example, when operating normally without faults, the temperature value is about 100°C.

[0029] In the present invention, since the temperature of the heater during the first wind tunnel test is different from the temperature during the subsequent stable operation, the temperature value at the electrode rod is also different. When the temperature value is within the normal threshold value under the current test conditions, it is considered that the heater is working normally; otherwise, the heater is working abnormally. At the same time, in this process, the normal threshold value can also be optimized and updated by accumulating the measured temperature values.

[0030] In a preferred embodiment, the fault diagnosis module includes an operating condition determination unit and a leakage diagnosis unit; The working condition determination unit is used to compare the environmental parameters with the historical environmental parameters in the historical data to determine the current test working condition; wherein the historical data records the historical environmental parameters corresponding to each test working condition and the historical infrared images and historical voiceprint images marked with the fault diagnosis results; The leakage diagnosis unit is used to compare the infrared image under the current test condition with the historical infrared image, and to compare the voiceprint image under the current test condition with the historical voiceprint image, to obtain a fault diagnosis result.

[0031] In the present invention, the infrared image and the voiceprint image under the current test condition are analyzed by the leakage diagnosis unit to determine the final fault diagnosis result.

[0032] In a preferred embodiment, the fault diagnosis module is used to perform the following operations: After preprocessing the infrared image, an infrared image to be identified is obtained; Inputting the infrared image to be identified into a pre-trained first identification model and outputting a fault diagnosis result; The first recognition model is obtained by training at least two groups of first sample sets, each of which includes a historical infrared image as input and a fault diagnosis result of the historical infrared image as output; the fault diagnosis result is the presence of a fault or the absence of a fault.

[0033] In a preferred embodiment, the fault diagnosis module is used to perform the following operations: Dividing the voiceprint image according to the structure of the heater to obtain a voiceprint image composed of several sub-images; After preprocessing the voiceprint image composed of several sub-images, the pre-trained second recognition model is input to output a fault diagnosis result; the fault diagnosis result is the presence of a fault or no fault; The second recognition model is obtained by training at least two groups of second sample sets, each of which includes a historical voiceprint image divided into several sub-images as input and a fault diagnosis result for each sub-image as output.

[0034] Specifically, the preprocessing involved in the fault diagnosis module includes operations such as image denoising, image quality evaluation, and image enhancement to ensure the provision of high-quality images with distinct features. In order to complete the training of the first recognition model and the second recognition model, an expansion sample algorithm can also be used for historical infrared images and historical voiceprint images to achieve sample expansion and increase the number of samples.

[0035] In the present invention, when the fault diagnosis result of any recognition model is that there is a fault, it is determined that the heater has a fault. For the second recognition model, the voiceprint image is further refined and divided. As described in the previous example, the voiceprint image is divided into five areas, each area corresponds to a primary heating component, and a voiceprint image composed of five sub-images is obtained, so as to further determine the specific heating component where the fault occurs based on the second recognition model.

[0036] Specifically, since there is an obvious difference between the sound frequency measured when there is a leak and the ambient noise frequency measured when there is no leak, the voiceprint positioning component can preliminarily determine whether a leak has occurred through the collected leakage sign signal. If the leakage sign signal is collected, it is considered that a leak has occurred. In order to determine whether the heater is leaking, further judgment can be made based on the second recognition model; if the leakage sign signal is not collected, it is considered that no leakage has occurred, but in order to confirm whether there is a false alarm, further judgment can be made based on the second recognition model.

[0037] In a preferred embodiment, the fault diagnosis module is further configured to perform the following operations: For the current test condition, when the fault diagnosis result is obtained for the first time that a fault exists, the moment is confirmed as the fault moment; Taking the fault moment as the central moment, obtaining infrared images collected within a preset time period before and after the fault moment, and sorting them in chronological order to obtain an infrared image sequence; Extracting features from each infrared image in the infrared image sequence to obtain an infrared feature sequence composed of infrared feature information of each infrared image in chronological order; wherein the infrared feature sequence includes a temperature gradient feature sequence, a shape feature sequence and a texture feature sequence; Determine the highest temperature value and its target position from the temperature gradient characteristic sequence, and calculate the temperature change rate at the target position per unit time; Determine the shape of the high-temperature area where the target position is located from the shape feature sequence, and calculate the area diffusion rate per unit time; wherein the temperature range of the high-temperature area is the maximum temperature value ± a preset temperature threshold; Determine the leakage direction based on the shape of the high temperature area that changes with time in the shape feature sequence; Determine the maximum gradient value and the minimum gradient value along the leakage direction from the texture feature sequence; Determine a fault score based on the historical temperature range, maximum temperature value, temperature change rate, shape of the high temperature area at the target position, area diffusion rate, maximum gradient value, and minimum gradient value of the heater exterior under the current test condition; A fault level is determined according to the fault score, and a fault case is determined based on the fault level, so as to determine a fault solution through the fault case.

[0038] It should be noted that the infrared feature information includes temperature gradient features, shape features and texture features.

[0039] In a preferred embodiment, the fault score is determined by the following formula: in, M Score the fault; T max is the maximum temperature value; T a , T b They are the starting temperature value and ending temperature value of the historical temperature range respectively; V T is the temperature change rate; α is the thermal inertia coefficient of the material; A is the area of ​​the high temperature region, P is the perimeter of the high temperature area; V S is the area diffusion rate; G max is the maximum gradient value; G min is the minimum gradient value; λ 1 , λ 2 , λ 3 , λ 4 are weight coefficients, and λ 1 + λ 2 + λ 3 + λ 4 =1.

[0040] Specifically, the failure time is taken as the central time t , get the preset time Δ before and after the fault moment t The infrared images collected in the time are sorted in chronological order to obtain an infrared image sequence; that is, the infrared image sequence is t 1 =t -Δ t arrive t 2 = t +Δ t It should be noted that the highest temperature value in the temperature gradient characteristic sequence is from t 1 arrive t 2 The highest temperature value determined in all infrared images within the time period T max ; By counting the temperature gradient characteristics of each infrared image, the target position is obtained t 2 Time to t 1 The temperature change rate at the moment. According to the shape area of ​​all infrared images in the shape feature sequence in the high temperature area, calculate t 2 Time to t 1 The temperature change rate at the moment is the area diffusion rate per unit time. The temperature range of the high temperature area is the highest temperature value T max ±Preset temperature threshold ε . The diffusion rate in a certain direction is the largest leakage direction; then from t 1 arrive t 2 The maximum gradient value and the minimum gradient value in the leakage direction are determined from the texture feature sequence within the time length.

[0041] It should be noted that α Related to the specific heat capacity and thermal conductivity of the material used in the heater, used to adjust the sensitivity of the temperature change rate; where, α The smaller it is, the more sensitive it is to rapid temperature rise and it is suitable for metal materials; α The larger it is, the more it will suppress the temperature rise noise and is suitable for thermal insulation materials. is the shape complexity factor. The larger the value, the more irregular the shape is, the easier it is to have jet flow, and thus the higher the degree of failure.

[0042] In the present invention, the degree of temperature anomaly is quantified by the maximum temperature value and the historical temperature interval, eliminating environmental interference; the hyperbolic tangent function is used to constrain the influence of rapid temperature changes, the shape influence is determined by the shape complexity factor, and the temperature change rate is directly linearly coupled with the shape complexity to consider the synergistic amplification effect of the two; at the same time, the logarithmic function is used to suppress the excessive influence of the area diffusion rate, and the maximum gradient value and the minimum gradient value are used to characterize the inhomogeneity of the temperature field, thereby obtaining a fault score. The higher the fault score, the more serious the fault and the higher the fault level.

[0043] In a preferred embodiment, determining a fault case based on the fault level, and determining a fault solution through the fault case includes: Selecting the fault cases included in the fault level under the test condition from the fault case library; the fault case library records the fault cases at each fault level under any test condition, and the fault cases include the fault phenomenon, fault diagnosis result and fault solution; For each fault case, the following are performed: comparing the fault infrared image including the fault phenomenon in the fault case with the infrared image under the current test condition to obtain the similarity; The fault solution included in the fault case corresponding to the minimum similarity is determined as the current fault solution.

[0044] In a preferred embodiment, the fault diagnosis module further includes an output unit and an alarm unit; the output unit is used to display the fault diagnosis result; the alarm unit is used to alarm when the fault diagnosis result is that a fault exists. Specifically, the fault diagnosis module can be a device such as a server that implements the above functions.

[0045] Please refer to Figure 3 The embodiment of the present invention provides a fault diagnosis method for a heater for a wind tunnel test. The method is implemented based on any system embodiment of the specification. The method includes: Step 300, when the heater is started, the environmental parameters of the heater are obtained, and an infrared image and a voiceprint image of the outside of the heater are collected in real time; Step 302, determining the current test condition according to the environmental parameters, and comparing the environmental parameters, the infrared image and the voiceprint image with the historical data under the current test condition to obtain a fault diagnosis result.

[0046] For step 302, the current test condition is determined according to the environmental parameters, and the environmental parameters, infrared images and voiceprint images are compared with the historical data under the current test condition to obtain the fault diagnosis results, including: S1, when the environmental parameters are the same as the historical environmental parameters, determine the current test conditions of the environmental parameters as the test conditions corresponding to the historical environmental parameters; wherein the environmental parameters include total temperature and total pressure of the gas source; When the environmental parameter does not exist in the historical data, determine the first historical environmental parameter closest to the environmental parameter from the historical data, and judge whether the difference between the first historical environmental parameter and the environmental parameter does not exceed the preset threshold value. If so, determine that the current test condition of the environmental parameter is the test condition corresponding to the first historical environmental parameter; otherwise, generate the current test condition and store it in the historical data; S2, under the current test conditions, determine whether the temperature value is measured during the first wind tunnel test of the heater on that day; If not, the corresponding fault-free historical temperature interval under the current test condition is used as the normal threshold. When the temperature value is within the normal threshold, the fault diagnosis result is determined to be normal operation; when the temperature value is not within the normal threshold, the fault diagnosis result is determined to be temperature abnormality. S3, preprocessing the infrared image to obtain an infrared image to be identified; Inputting the infrared image to be identified into a pre-trained first identification model and outputting a fault diagnosis result; The first recognition model is obtained by training at least two groups of first sample sets, each of which includes a historical infrared image as an input and a fault diagnosis result of the historical infrared image as an output; the fault diagnosis result is the presence of a fault or the absence of a fault; S4, dividing the voiceprint image according to the structure of the heater to obtain a voiceprint image composed of a plurality of sub-images; After preprocessing the voiceprint image composed of several sub-images, the pre-trained second recognition model is input to output a fault diagnosis result; the fault diagnosis result is the presence of a fault or no fault; The second recognition model is obtained by training at least two groups of second sample sets, each group of second sample sets includes as input a historical voiceprint image divided into a plurality of sub-images and as output a fault diagnosis result for each sub-image; S5, when the fault diagnosis result is that a fault exists, the fault level is determined according to the infrared image of the current test condition, and a fault case is determined based on the fault level, so as to determine a fault solution through the fault case.

[0047] The content of the above method is based on the same concept as the embodiment of the system of the present invention. For the specific content, please refer to the description in the embodiment of the system of the present invention, and it will not be repeated here.

[0048] It should be noted that, in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0049] A person of ordinary skill in the art can understand that all or part of the steps of implementing the above method embodiments can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps of the above method embodiments; and the aforementioned storage medium includes: ROM, RAM, magnetic disk or optical disk, etc., various media that can store program codes.

[0050] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A fault diagnosis system for a heater for a wind tunnel test, characterized in that: include: Infrared imaging components, voiceprint positioning components, switches, heater control modules and fault diagnosis modules; The heater control module controls the heater to start and obtains the environmental parameters of the heater; the interior of the heater heats the air to obtain the airflow for the wind tunnel test; the environmental parameters include total temperature, air source pressure and total pressure; The infrared imaging component and the voiceprint positioning component are installed around the heater in a non-contact manner to monitor the heater in all directions; when the heater is started, the infrared imaging component and the voiceprint positioning component are used to collect an infrared image and a voiceprint image of the outside of the heater in real time, respectively; The switch is used to send the environmental parameters, the infrared image and the voiceprint image to the fault diagnosis module; The fault diagnosis module is used to determine the current test conditions based on the environmental parameters, and compare the environmental parameters, the infrared image and the voiceprint image with the historical data under the current test conditions to obtain a fault diagnosis result; and when the fault diagnosis result is that a fault exists, the moment is confirmed as the fault moment, and the fault solution is determined based on the infrared images collected within a preset time period before and after the fault moment.

2. The system according to claim 1, characterized in that The heater is obtained by connecting at least two heating components in series; each heating component adopts at least two infrared imaging components; and / or, The heater comprises a heating element, an electrode rod, a heat-bearing layer, a heat-insulating layer, a pressure-bearing layer and a cooling structure; inside the heater, the heating element is used to heat the air, and the cooling structure is used to circulate cooling water to cool the electrode rod.

3. The system according to claim 2, characterized in that The fault diagnosis module includes an operating condition determination unit and a temperature diagnosis unit; The working condition determination unit is used to compare the environmental parameters with the historical environmental parameters in the historical data to determine the current test working condition; wherein the historical data records the historical environmental parameters corresponding to each test working condition and the historical temperature range of each electrode rod during normal operation; The temperature diagnosis unit is used to determine the temperature value of each electrode rod based on the infrared image under the current test condition, and compare the temperature value of each electrode rod with the historical temperature range under the current test condition. When the temperature value is not within the historical temperature range, the fault diagnosis result is determined to be that there is a temperature anomaly.

4. The system according to claim 1, characterized in that The fault diagnosis module includes an operating condition determination unit and a leakage diagnosis unit; The working condition determination unit is used to compare the environmental parameters with the historical environmental parameters in the historical data to determine the current test working condition; wherein the historical data records the historical environmental parameters corresponding to each test working condition and the historical infrared images and historical voiceprint images marked with the fault diagnosis results; The leakage diagnosis unit is used to compare the infrared image under the current test condition with the historical infrared image, and to compare the voiceprint image under the current test condition with the historical voiceprint image, to obtain the fault diagnosis result.

5. The system according to claim 3, characterized in that The operating condition determination unit is used to perform the following operations: When the environmental parameter is the same as the historical environmental parameter, determining the current test condition of the environmental parameter as the test condition corresponding to the historical environmental parameter; When the environmental parameter does not exist in the historical data, determine the first historical environmental parameter closest to the environmental parameter from the historical data, and judge whether the difference between the first historical environmental parameter and the environmental parameter does not exceed a preset threshold value; if so, determine that the current test condition of the environmental parameter is the test condition corresponding to the first historical environmental parameter; otherwise, generate the current test condition and store it in the historical data; The temperature diagnosis unit is used to perform the following operations: Under the current test condition, determining whether the temperature value is measured during the first wind tunnel test of the heater on that day; If not, the fault-free historical temperature interval corresponding to the current test condition is used as the normal threshold. When the temperature value is within the normal threshold, the fault diagnosis result is determined to be normal operation; when the temperature value is not within the normal threshold, the fault diagnosis result is determined to be a temperature anomaly.

6. The system according to claim 1, characterized in that The fault diagnosis module is used to perform the following operations: After preprocessing the infrared image, an infrared image to be identified is obtained; Inputting the infrared image to be identified into a pre-trained first identification model, and outputting the fault diagnosis result; The first recognition model is obtained by training at least two groups of first sample sets, each of which includes a historical infrared image as input and a fault diagnosis result of the historical infrared image as output; the fault diagnosis result is the presence of a fault or the absence of a fault; and / or, Dividing the voiceprint image according to the structure of the heater to obtain a voiceprint image composed of a plurality of sub-images; After preprocessing the voiceprint image composed of several sub-images, a pre-trained second recognition model is input to output the fault diagnosis result; the fault diagnosis result is the presence of a fault or no fault; The second recognition model is obtained by training at least two groups of second sample sets, each of which includes a historical voiceprint image divided into several sub-images as input and a fault diagnosis result for each sub-image as output.

7. The system according to claim 1, characterized in that The fault diagnosis module is also used to perform the following operations: For the current test condition, when the fault diagnosis result is obtained for the first time that a fault exists, confirming the moment as the fault moment; Taking the fault moment as the central moment, acquiring infrared images collected within a preset time period before and after the fault moment, and sorting them in chronological order to obtain an infrared image sequence; Extracting features from each infrared image in the infrared image sequence to obtain an infrared feature sequence composed of infrared feature information of each infrared image in chronological order; wherein the infrared feature sequence includes a temperature gradient feature sequence, a shape feature sequence, and a texture feature sequence; Determine the highest temperature value and its target position from the temperature gradient characteristic sequence, and calculate the temperature change rate at the target position per unit time; Determine the shape of the high temperature area where the target position is located from the shape feature sequence, and calculate the area diffusion rate per unit time; wherein the temperature range of the high temperature area is the maximum temperature value ± a preset temperature threshold; determining the leakage direction according to the shape of the high temperature area that changes with time in the shape feature sequence; Determine the maximum gradient value and the minimum gradient value along the leakage direction from the texture feature sequence; Determine a fault score according to the historical temperature range of the heater exterior, the highest temperature value, the temperature change rate, the shape of the high temperature area where the target position is located, the area diffusion rate, the maximum gradient value, and the minimum gradient value of the current test condition; A fault level is determined according to the fault score, and a fault case is determined based on the fault level, so as to determine a fault solution through the fault case.

8. The system according to any one of claims 1 to 7, characterized in that: The resolution of the infrared imaging component is not less than 256*192, and the frame rate is not less than 25fps; the frequency band of the voiceprint positioning component is 5kHz~72kHz; and / or, The fault diagnosis result includes the presence of a fault and the presence of no fault; the presence of a fault includes: the presence of abnormal temperature, and the presence of gas or liquid leakage.

9. The system according to any one of claims 1 to 7, characterized in that: The fault diagnosis module also includes an output unit and an alarm unit; the output unit is used to display the fault diagnosis result; the alarm unit is used to issue an alarm when the fault diagnosis result indicates that a fault exists.

10. A fault diagnosis method for a heater for wind tunnel testing based on the system according to any one of claims 1 to 9, characterized in that: include: When the heater is started, the environmental parameters of the heater are obtained, and an infrared image and a voiceprint image of the outside of the heater are collected in real time; The current test condition is determined according to the environmental parameters, and the environmental parameters, the infrared image and the voiceprint image are compared with the historical data under the current test condition to obtain a fault diagnosis result.

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