Protection module test method and device, electronic equipment and storage medium

Abstract

The invention provides a test method and device of a protection module, electronic equipment and a storage medium, thermal cycle processing is performed on a temperature monitoring element according to a temperature cycle period, and the temperature monitoring element is wrapped by the protection module; acquiring first thickness data and stress data of an outer protection sleeve in the protection module, and acquiring second thickness data of a sealing device in the protection module; and inputting the first thickness data, the second thickness data and the stress data into a state prediction model to predict the stress change and the thickness change of the protection module in a preset duration, and generating test data of the protection module. Compared with the prior art, the operation reliability of the temperature monitoring element can be improved, and the cost of the whole life cycle can be reduced through precise maintenance and design upgrading.

Description

Technical Field

[0001] This disclosure relates to the field of equipment monitoring technology, and in particular to a testing method and apparatus for a protection module, an electronic device, and a storage medium. Background Technology

[0002] In industrial production, electronic equipment operation, and precision instrument monitoring, the stable operation of temperature monitoring components is crucial for ensuring the safe and reliable operation of the system. To prevent temperature monitoring components from failing due to external environmental factors (such as dust, humidity, and mechanical shock), protective modules are typically used to encapsulate and protect them. The performance of the protective module directly determines the service life and monitoring accuracy of the temperature monitoring component, with the structural strength of the outer protective sleeve and the sealing performance of the sealing devices being core indicators. Variations in the thickness of the outer protective sleeve affect its impact and wear resistance, while variations in the thickness of the sealing devices relate to the sealing performance of the protective module. Furthermore, stress changes caused by environmental factors such as temperature cycling during long-term use are a significant cause of protective module failure.

[0003] Currently, industry testing of protective modules often employs phased sampling or single-parameter testing methods. For example, structural strength is judged solely by measuring the initial thickness of the outer protective sleeve, or the effectiveness of sealing devices is assessed through short-term sealing performance tests. These methods have significant limitations: firstly, they fail to comprehensively consider the correlation between the thickness changes and stress states of the outer protective sleeve and sealing devices, making it difficult to fully reflect the overall performance of the protective module; secondly, they lack the ability to predict the performance evolution trend of the protective module within a preset service life, making it impossible to anticipate whether it can continuously meet protection requirements during long-term use. Replacement or repair is often only carried out after the protective module fails, increasing system operation risks and maintenance costs. Therefore, there is an urgent need for a testing method that can comprehensively assess changes in key parameters of the protective module and predict its long-term performance to overcome the limitations of existing testing methods and provide a more accurate evaluation basis for the reliability of protective modules. Summary of the Invention

[0004] This disclosure provides a testing method, apparatus, electronic device, and storage medium for a protection module. Its main objective is to provide a testing method capable of comprehensively evaluating changes in key parameters of the protection module and predicting its long-term performance, thereby overcoming the limitations of existing testing methods and providing a more accurate evaluation basis for the reliability of the protection module.

[0005] According to a first aspect of this disclosure, a testing method for a protection module is provided, comprising:

[0006] The temperature monitoring element is subjected to thermal cycling treatment according to the temperature cycle period, and the temperature monitoring element is wrapped with a protective module.

[0007] Obtain the first thickness data and stress data of the outer protective sleeve in the protection module, and obtain the second thickness data of the sealing device in the protection module;

[0008] The first thickness data, the second thickness data, and the stress data are input into the state prediction model to predict the stress and thickness changes of the protection module within a preset time period, thereby generating test data for the protection module.

[0009] Optionally, the thermal cycling treatment of the temperature monitoring element according to the temperature cycle period includes:

[0010] According to the temperature cycle, different temperature loads are applied to the protection module to simulate the temperature changes during operation of the temperature monitoring element. The temperature cycle includes a heating phase and a cooling phase.

[0011] Optionally, obtaining the first thickness data and stress data of the outer protective sleeve in the protective module includes:

[0012] The stress concentration area of ​​the outer protective sleeve is scanned at a preset frequency using an ultrasonic thickness gauge to generate a first thickness variation curve.

[0013] Strain gauge sensors are installed on the outer protective sleeve to collect local stress data in real time and correlate it with the corresponding temperature value.

[0014] Optionally, obtaining the second thickness data of the sealing device in the protection module includes:

[0015] At the end of each thermal cycle, the sealing device penetrating the insulation area is scanned non-contactly.

[0016] Extract the thickness distribution of at least three axial sections and calculate the thickness attenuation rate as the second thickness data.

[0017] Optionally, the method further includes:

[0018] Acquire historical first thickness data, historical second thickness data, and historical stress data, and preprocess them to generate training data;

[0019] Based on the training data, the state prediction model to be trained is iteratively trained to obtain a well-trained state prediction model.

[0020] Optionally, the method further includes:

[0021] When the predicted rate of stress change exceeds the safety threshold, the deformation compensation of the outer protective sleeve is automatically increased.

[0022] When the thickness decay rate reaches a critical point, the micro-injection device is controlled to replenish the sealing medium to the sealing device.

[0023] According to a second aspect of this disclosure, a text generation apparatus is provided, comprising:

[0024] A processing unit is used to perform thermal cycling treatment on a temperature monitoring element according to a temperature cycle cycle, and the temperature monitoring element is wrapped with a protective module.

[0025] The acquisition unit is used to acquire the first thickness data and stress data of the outer protective sleeve in the protection module, and to acquire the second thickness data of the sealing device in the protection module;

[0026] The generation unit is used to input the first thickness data, the second thickness data, and the stress data into the state prediction model to predict the stress change and thickness change of the protection module within a preset time period, and generate the test data of the protection module.

[0027] Optionally, the processing unit is further configured to:

[0028] According to the temperature cycle, different temperature loads are applied to the protection module to simulate the temperature changes during operation of the temperature monitoring element. The temperature cycle includes a heating phase and a cooling phase.

[0029] Optionally, the acquisition unit includes:

[0030] The first generation module is used to scan the stress concentration area of ​​the outer protective sleeve at a preset frequency using an ultrasonic thickness gauge to generate a first thickness variation curve.

[0031] The acquisition module is used to install strain gauge sensors at the outer protective sleeve to acquire local stress data in real time and correlate it with the corresponding temperature value.

[0032] Optionally, the acquisition unit further includes:

[0033] A scanning module is used to perform a non-contact scan of the sealing device that penetrates the insulation area at the end of each thermal cycle.

[0034] The extraction module is used to extract the thickness distribution of at least three axial sections and calculate the thickness attenuation rate as the second thickness data.

[0035] Optionally, the device further includes:

[0036] The preprocessing unit is used to acquire historical first thickness data, historical second thickness data, and historical stress data, and to preprocess them to generate training data.

[0037] The training unit is used to iteratively train the state prediction model to be trained based on the training data to obtain a trained state prediction model.

[0038] Optionally, the device further includes:

[0039] A triggering unit is used to automatically trigger an increase in the deformation compensation of the outer protective sleeve when the predicted rate of stress change exceeds a safety threshold.

[0040] The control unit is used to control the micro-injection device to replenish the sealing medium to the sealing device when the thickness decay rate reaches a critical point.

[0041] According to a third aspect of this disclosure, an electronic device is provided, comprising:

[0042] At least one processor; and

[0043] A memory communicatively connected to the at least one processor; wherein,

[0044] The memory stores instructions that can be executed by the at least one processor, which, when executed, enables the at least one processor to perform the test method for the protection module described in the first aspect above.

[0045] According to a fourth aspect of this disclosure, a non-transitory computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to cause the computer to execute the test method of the protection module described in the first aspect above.

[0046] According to a fifth aspect of this disclosure, a computer program product is provided, including a computer program that, when executed by a processor, implements a test method for the protection module as described in the first aspect above.

[0047] This disclosure provides a testing method, apparatus, electronic device, and storage medium for a protective module. The method involves thermally cycling a temperature monitoring element, which is encased in a protective module, according to a temperature cycle. First thickness and stress data of the outer protective sleeve within the protective module are acquired, along with second thickness data of the sealing device within the protective module. The first thickness data, second thickness data, and stress data are input into a state prediction model to predict stress and thickness changes in the protective module over a preset time period, generating test data for the protective module. Compared to related technologies, this disclosure continuously accumulates test data and feeds it back into the design phase, thereby continuously improving the durability, sealing, and temperature shock resistance of the protective module, extending its service life. This method, through dynamic testing simulating real-world environments, comprehensive capture of multi-dimensional parameters, and forward-looking analysis of the prediction model, empowers the entire process of protective module development, from "state assessment" to "lifespan prediction" and then to "design optimization." Ultimately, this not only improves the operational reliability of the temperature monitoring element but also reduces the total lifespan cost through precise maintenance and design upgrades, demonstrating strong practical value.

[0048] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this disclosure, nor is it intended to limit the scope of this disclosure. Other features of this disclosure will become readily apparent from the following description. Attached Figure Description

[0049] The accompanying drawings are provided to better understand this solution and do not constitute a limitation of this disclosure. Wherein:

[0050] Figure 1 A flowchart illustrating a testing method for a protection module provided in an embodiment of this disclosure;

[0051] Figure 2 A schematic diagram of the structure of a testing device for a protection module provided in an embodiment of this disclosure;

[0052] Figure 3 A schematic block diagram of an example electronic device provided for embodiments of this disclosure. Detailed Implementation

[0053] The exemplary embodiments of this disclosure are described below with reference to the accompanying drawings, including various details of the embodiments to aid understanding, and should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this disclosure. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0054] The following description, with reference to the accompanying drawings, describes a testing method and apparatus for a protection module, an electronic device, and a storage medium according to embodiments of the present disclosure.

[0055] Figure 1 This is a flowchart illustrating a testing method for a protection module provided in an embodiment of this disclosure.

[0056] like Figure 1 As shown, the method includes the following steps:

[0057] Step 101: Perform thermal cycling treatment on the temperature monitoring element according to the temperature cycle cycle. The temperature monitoring element is wrapped with a protective module.

[0058] In this embodiment, thermal cycling of the temperature monitoring element according to a temperature cycle period refers to simulating the temperature change environment that the temperature monitoring element may encounter during the actual operation of the steam turbine. A specific temperature cycle period is set (this period can be determined based on the steam turbine's start-up and shutdown patterns, the range and frequency of temperature fluctuations during operation; for example, simulating the process of gradually rising from room temperature during turbine startup to high operating temperature, and then back to room temperature during shutdown as one cycle, or setting the corresponding cycle duration and temperature range based on factors such as diurnal temperature differences and seasonal temperature changes in actual operating conditions). The temperature monitoring element, encased in a protective module, is placed in an environmental test device with precisely controllable temperature, and repeatedly subjected to heating, heat preservation, and cooling operations according to the preset cycle period. The temperature monitoring element can be a thermocouple or similar device used for monitoring the cylinder temperature of the steam turbine. The protective module is a structure designed to protect the element, such as including a corrosion-resistant outer sheath (e.g., a ceramic tube, 304 stainless steel corrugated pipe) and high-temperature resistant sealant filling the gaps, providing physical isolation and protection for the temperature monitoring element during thermal cycling. This thermal cycling process simulates the thermal stress experienced by temperature monitoring elements due to repeated temperature changes in actual use. It allows us to examine the protective performance of the protection module against internal temperature monitoring elements under continuous temperature alternation, as well as its structural stability under stresses such as thermal expansion and contraction. This lays the foundation for subsequent reliability assessment of the protection module.

[0059] Step 102: Obtain the first thickness data and stress data of the outer protective sleeve in the protection module, and obtain the second thickness data of the sealing device in the protection module.

[0060] In this embodiment, acquiring the first thickness and stress data of the outer protective sleeve in the protective module, as well as the second thickness data of the sealing device in the protective module, is a key data acquisition operation performed during or after the thermal cycling treatment of the temperature monitoring element encasing the protective module. The outer protective sleeve, as an important component of the protective module, can be a structure with corrosion resistance and wear resistance, such as a 304 stainless steel corrugated pipe. Its first thickness data can be obtained using high-precision thickness gauges (such as ultrasonic thickness gauges or laser thickness gauges). During measurement, multiple measurements should be taken at several key locations on the outer protective sleeve (such as the interfaces at both ends and the easily worn area in the middle) and the average value should be taken to ensure data accuracy. This data reflects changes in the structural integrity of the outer protective sleeve after thermal cycling, such as whether thickness reduction occurs due to thermal expansion and contraction. The stress data of the outer protective sleeve can be obtained by attaching strain gauges to its surface or by using non-destructive testing techniques (such as X-ray stress analyzers) to assess the magnitude and distribution of stress generated inside the outer protective sleeve due to alternating temperature changes during thermal cycling, and to determine whether it is within the safe stress range that the material can withstand. The sealing device can be a high-temperature resistant sealant (such as cylinder grease) filled between the outer protective sleeve and the temperature monitoring element. Obtaining the second thickness data requires measuring the filling area of ​​the sealing device within the gap using tools suitable for measuring minute gaps (such as an optical microscope with a micrometer, or a dedicated gap thickness gauge). This reflects the thickness change of the sealing device after thermal cycling, for example, whether shrinkage or aging due to high temperatures leads to thickness reduction, thus affecting sealing performance. Obtaining this data provides a foundation for subsequent analysis of the structural stability and protective effect of the protection module under thermal cycling.

[0061] Step 103: Input the first thickness data, the second thickness data, and the stress data into the state prediction model to predict the stress change and thickness change of the protection module within a preset time period, and generate test data for the protection module.

[0062] In this embodiment, the first thickness data, the second thickness data, and the stress data are input into a state prediction model, aiming to perform a forward-looking analysis of the future state of the protection module. The state prediction model can be constructed based on thickness and stress change data accumulated by the protection module during historical thermal cycling. It combines the input current first thickness data (reflecting the current structural thickness of the outer protective sleeve, such as a 304 stainless steel bellows), the second thickness data (reflecting the current filling thickness of sealing devices, such as high-temperature resistant sealant), and stress data (characterizing the mechanical load state borne by the outer protective sleeve). Through an algorithm, it simulates the stress evolution trend and thickness decay law of the protection module under continuous temperature cycling within a preset time period (this preset time period can be set according to the actual needs such as the planned operating cycle and maintenance interval of the turbine, for example, a quarter, half a year, or a year). This prediction generates test data containing information such as stress values, outer protective sleeve thickness values, and sealing device thickness values ​​of the protection module at different time points within the preset time period. These test data can intuitively reflect the structural stability and protective performance changes of the protection module during future use. For example, they can predict whether the outer protective sleeve will crack due to excessive stress within a preset time period, or whether the thickness of the sealing device will be excessively thinned due to aging or high temperature, leading to sealing failure. This provides data support for judging whether the protection module's ability to protect temperature monitoring elements (such as thermocouples used for turbine cylinder temperature monitoring) can meet the usage requirements within a preset time period, and thus provides a basis for subsequent maintenance and replacement decisions.

[0063] This disclosure provides a testing method for a protective module. A temperature monitoring element, encased in a protective module, undergoes thermal cycling treatment according to a temperature cycle period. First thickness and stress data of the outer protective sleeve within the protective module are acquired, along with second thickness data of the sealing device within the protective module. The first thickness data, second thickness data, and stress data are input into a state prediction model to predict stress and thickness changes in the protective module over a preset time period, generating test data for the protective module. Compared to related technologies, this disclosure continuously accumulates test data and feeds it back into the design phase, thereby continuously improving the durability, sealing, and temperature shock resistance of the protective module, extending its service life. This method, through dynamic testing simulating real-world environments, comprehensive capture of multi-dimensional parameters, and forward-looking analysis of the predictive model, empowers the entire process of protective module development, from "state assessment" to "lifespan prediction" and then to "design optimization." Ultimately, it not only improves the operational reliability of the temperature monitoring element but also reduces the total lifespan cost through precise maintenance and design upgrades, demonstrating strong practical value.

[0064] In some embodiments of this disclosure, the thermal cycling treatment of the temperature monitoring element according to the temperature cycle includes: applying different temperature loads to the protection module according to the temperature cycle to simulate the temperature changes during operation of the temperature monitoring element, wherein the temperature cycle includes a heating phase and a cooling phase.

[0065] Specifically, when performing thermal cycling treatment on the temperature monitoring element according to the temperature cycle cycle, different temperature loads are applied to the protection module according to the temperature cycle cycle. The core is to accurately simulate the temperature change process of the temperature monitoring element during actual turbine operation, thereby verifying the protection performance of the protection module under dynamic temperature environment. The temperature cycle cycle includes a heating phase and a cooling phase, which are set according to the operating characteristics of the turbine: the heating phase simulates the turbine startup process, starting from ambient temperature and gradually increasing the temperature at a certain rate (this rate can refer to the actual temperature rise rate of the turbine cylinder during startup, for example, tens to hundreds of degrees per hour) until it reaches the high temperature during normal turbine operation (such as several hundred degrees Celsius or even higher, depending on the turbine model and operating parameters), and maintaining this high temperature for a certain period to simulate the continuous high-temperature environment during stable turbine operation; the cooling phase corresponds to the turbine shutdown process, gradually reducing the temperature from the operating high temperature to ambient temperature at a set rate, similarly referencing the actual cooling rate during turbine shutdown to ensure that the cooling process matches the actual operating conditions. Through this cycle of heating and cooling, the temperature monitoring element (such as a thermocouple) wrapped with the protective module (such as a structure containing a 304 stainless steel corrugated outer protective sleeve and high-temperature resistant sealant) can be fully exposed under temperature loads close to actual operation. This fully exposes potential problems that may arise due to thermal expansion and contraction and repeated temperature stress, providing a more realistic test basis for subsequent evaluation of the reliability of the protective module.

[0066] In some embodiments of this disclosure, obtaining the first thickness data and stress data of the outer protective sleeve in the protective module includes: scanning the stress concentration area of ​​the outer protective sleeve at a preset frequency using an ultrasonic thickness gauge to generate a first thickness change curve; and deploying strain gauge sensors at the outer protective sleeve to collect local stress data in real time and correlate it with the corresponding temperature value.

[0067] Specifically, the acquisition of the first thickness data and stress data of the outer protective sleeve in the protection module is achieved in the following way: For the outer protective sleeve (such as corrosion-resistant structures such as 304 stainless steel corrugated pipes), an ultrasonic thickness gauge is used to scan its stress concentration area. The stress concentration area can be determined according to the structural characteristics of the outer protective sleeve, such as the interface at both ends, the part with micro-cracks on the surface, or the area where stress is easily accumulated due to abrupt changes in shape. During scanning, a preset frequency is set (this frequency can be adjusted according to the material thickness, material characteristics and required measurement accuracy of the outer protective sleeve to ensure that subtle changes in thickness can be accurately captured). The thickness value at different positions is recorded in real time by the reflection signal of the ultrasonic waves emitted by the ultrasonic thickness gauge in the measured area, thereby generating a first thickness change curve that reflects the thickness of the stress concentration area of ​​the outer protective sleeve as the scanning position changes. This curve can intuitively show the thickness distribution of the area after thermal cycling treatment and whether there is local thinning. Simultaneously, strain gauge sensors are installed at key locations of the outer protective sleeve (such as the aforementioned stress concentration areas and other locations prone to stress changes). These strain gauge sensors must be adapted to the temperature environment of the outer protective sleeve (e.g., high-temperature resistant strain gauges to match the high-temperature conditions during turbine operation and thermal cycling). The strain gauge sensors detect the minute deformations generated by the outer protective sleeve during thermal cycling in real time, and then convert them into local stress data. During this process, the temperature value at the corresponding moment is recorded simultaneously (this temperature value can be collected by the thermal cycling equipment or additional temperature sensors), and the local stress data is correlated with the corresponding temperature value to analyze the variation law of local stress of the outer protective sleeve under different temperature conditions, providing data support for subsequent evaluation of its mechanical stability.

[0068] In some embodiments of this disclosure, obtaining the second thickness data of the sealing device in the protection module includes: performing a non-contact scan of the sealing device penetrating the insulation cotton area at the end of each thermal cycle; extracting the thickness distribution of at least three axial sections; and calculating the thickness attenuation rate as the second thickness data.

[0069] Specifically, the acquisition of the second thickness data of the sealing device in the protection module is carried out as follows: The sealing device can be a high-temperature resistant sealant filled between the outer protective sleeve and the temperature monitoring element. It is a key component for achieving sealing protection in the area penetrating the insulation cotton, and is prone to aging, shrinkage, or wear due to temperature cycling. Therefore, at the end of each thermal cycle, a non-contact scanning device (such as an optical 3D scanner or laser thickness gauge, avoiding physical disturbance to the sealing device) is used to scan the sealing device penetrating the insulation cotton area to obtain its overall morphological data. After scanning, at least three axial sections are extracted from the scanning results (sections evenly distributed along the length of the sealing device, such as sections at both ends and the middle, ensuring coverage of the main area of ​​the sealing device). The thickness distribution of the sealing device in each section is analyzed. By comparing the thickness values ​​before and after thermal cycling, the thickness attenuation of each section is calculated. Combined with the number of thermal cycles or the processing time, the thickness attenuation rate is obtained. This attenuation rate is used as the second thickness data to quantitatively reflect the degree of thickness change of the sealing device under thermal cycling, providing a basis for evaluating the stability of its sealing performance.

[0070] In some embodiments of this disclosure, the state prediction model is trained by: acquiring historical first thickness data, historical second thickness data, and historical stress data, and preprocessing them to generate training data; and iteratively training the state prediction model to be trained based on the training data to obtain a trained state prediction model.

[0071] Specifically, when training the state prediction model, the first step is to acquire historical first-thickness data, historical second-thickness data, and historical stress data. This historical data originates from monitoring data accumulated during past thermal cycling treatments of protective modules (including outer protective sleeves such as 304 stainless steel bellows and sealing devices such as cylinder sealing grease) surrounding similar temperature monitoring elements (such as thermocouples used for turbine cylinder temperature monitoring). The historical first-thickness data represents the thickness measurements of the outer protective sleeve at different times, the historical second-thickness data represents the thickness records of the sealing devices at the corresponding times, and the historical stress data represents the stress monitoring results of the outer protective sleeve during the corresponding thermal cycling phase. This historical data is then preprocessed. The preprocessing process may include data cleaning (removing outliers caused by measurement errors, such as thickness or stress values ​​that significantly exceed reasonable ranges), data standardization (converting thickness and stress data of different magnitudes to a unified data range so that the model can better learn data patterns), and time series alignment (ensuring a one-to-one correspondence between thickness and stress data within the same thermal cycling cycle), thereby generating training data that meets the model training requirements. Subsequently, based on these training data, the state prediction model to be trained (which can be constructed using algorithms capable of processing time series data, such as long short-term memory networks) is iteratively trained. During the training process, training data is continuously input into the model to be trained. By comparing the difference between the prediction results output by the model and the actual historical data, the internal parameters of the model are adjusted. This process is repeated until the prediction error of the model is reduced to a preset threshold, and finally a trained state prediction model is obtained. This model can accurately predict the stress and thickness changes of the protection module within a preset time period based on the input current data.

[0072] In some embodiments of this disclosure, when the predicted rate of stress change exceeds a safety threshold, the deformation compensation of the outer protective sleeve is automatically increased; when the thickness attenuation rate reaches a critical point, the micro-injection device is controlled to replenish the sealing medium to the sealing device.

[0073] Specifically, when the stress change rate of the outer protective sleeve is predicted to exceed the safety threshold by the state prediction model, the system will automatically trigger an operation to increase the deformation compensation of the outer protective sleeve. The outer protective sleeve can be a structure with a certain elastic deformation capacity, such as a 304 stainless steel corrugated pipe. The increase in its deformation compensation can be achieved by adjusting the corrugation spacing of the corrugated pipe and optimizing the buffer structure of its connection parts. The elastic characteristics of the corrugated pipe itself are used to absorb the additional stress generated by temperature cycling, avoiding stress concentration that could lead to cracking or damage to the outer protective sleeve, thereby maintaining its protective function for internal temperature monitoring elements (such as thermocouples). When the thickness decay rate of the sealing device is predicted to reach a critical point, the micro-injection device will be controlled to replenish the sealing medium to the sealing device. The sealing device is a structure that fills the gap between the outer protective sleeve and the temperature monitoring element. Its sealing medium can be made of high-temperature and corrosion-resistant materials such as cylinder sealing grease. The micro-injection device accurately replenishes the sealing medium to the decay area of ​​the sealing device through a preset injection channel to restore its thickness and sealing performance, prevent corrosive substances or water vapor in the insulation mud from penetrating to the surface of the temperature monitoring element due to sealing failure, and ensure the stable operation of the element.

[0074] It should be noted that the embodiments of this disclosure may include multiple steps. For ease of description, these steps are numbered, but these numbers are not a limitation on the execution time slots or execution order between the steps; these steps can be implemented in any order, and the embodiments of this disclosure do not limit this.

[0075] Corresponding to the aforementioned testing method for the protection module, this disclosure also proposes a testing apparatus for the protection module. Since the apparatus embodiments of this disclosure correspond to the aforementioned method embodiments, details not disclosed in the apparatus embodiments can be referred to the aforementioned method embodiments, and will not be repeated here.

[0076] Figure 2 This is a schematic diagram of the structure of a testing device for a protection module provided in an embodiment of the present disclosure, as shown below. Figure 2 As shown, it includes:

[0077] Processing unit 21 is used to perform thermal cycling treatment on temperature monitoring element according to temperature cycle period, wherein the temperature monitoring element is wrapped with a protective module.

[0078] The acquisition unit 22 is used to acquire the first thickness data and stress data of the outer protective sleeve in the protection module, and to acquire the second thickness data of the sealing device in the protection module.

[0079] The generation unit 23 is used to input the first thickness data, the second thickness data and the stress data into the state prediction model to predict the stress change and thickness change of the protection module within a preset time period, and generate the test data of the protection module.

[0080] It should be noted that the foregoing explanation of the method embodiments also applies to the apparatus of this embodiment, and the principle is the same, so it is not limited in this embodiment.

[0081] According to embodiments of this disclosure, this disclosure also provides an electronic device, a readable storage medium, and a computer program product.

[0082] Figure 3 A schematic block diagram of an example electronic device 300 that can be used to implement embodiments of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0083] like Figure 3 As shown, the electronic device 300 includes a computing unit 301, which can perform various appropriate actions and processes based on a computer program stored in ROM (Read-Only Memory) 302 or a computer program loaded from storage unit 308 into RAM (Random Access Memory) 303. The RAM 303 can also store various programs and data required for the operation of the electronic device 300. The computing unit 301, ROM 302, and RAM 303 are interconnected via a bus 304. An I / O (Input / Output) interface 305 is also connected to the bus 304.

[0084] Multiple components in electronic device 300 are connected to I / O interface 305, including: input unit 306, such as keyboard, mouse, etc.; output unit 307, such as various types of displays, speakers, etc.; storage unit 308, such as disk, optical disk, etc.; and communication unit 309, such as network card, modem, wireless transceiver, etc. Communication unit 309 allows electronic device 300 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0085] The computing unit 301 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 301 include, but are not limited to, CPUs (Central Processing Units), GPUs (Graphics Processing Units), various special-purpose AI (Artificial Intelligence) computing chips, various computing units running machine learning model algorithms, DSPs (Digital Signal Processors), and any suitable processor, controller, microcontroller, etc. The computing unit 301 performs the various methods and processes described above, such as the testing methods for the protection module. For example, in some embodiments, the testing methods for the protection module may be implemented as computer software programs tangibly contained in a machine-readable medium, such as storage unit 308. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 300 via ROM 302 and / or communication unit 309. When the computer program is loaded into RAM 303 and executed by the computing unit 301, one or more steps of the methods described above may be performed. Alternatively, in other embodiments, the computing unit 301 may be configured to perform the test methods of the aforementioned protection module by any other suitable means (e.g., by means of firmware).

[0086] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, FPGAs (Field Programmable Gate Arrays), ASICs (Application-Specific Integrated Circuits), ASSPs (Application-Specific Standard Products), SOCs (System-on-Chips), CPLDs (Complex Programmable Logic Devices), computer hardware, firmware, software, and / or combinations thereof. These various implementations may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0087] The program code used to implement the methods of this disclosure may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0088] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, RAM, ROM, EPROM (Electrically Programmable Read-Only Memory) or flash memory, optical fiber, CD-ROM (Compact Disc Read-Only Memory), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0089] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (Cathode-Ray Tube) or LCD (Liquid Crystal Display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0090] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication (e.g., communication networks) of any form or medium. Examples of communication networks include LANs (Local Area Networks), WANs (Wide Area Networks), the Internet, and blockchain networks.

[0091] Computer systems can include clients and servers. Clients and servers are generally geographically separated and typically interact via communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. A server can be a cloud server, also known as a cloud computing server or cloud host, a hosting product within the cloud computing service ecosystem, addressing the shortcomings of traditional physical hosts and VPS (Virtual Private Server, or simply "VPS") services, such as high management difficulty and weak business scalability. Servers can also be servers for distributed systems or servers incorporating blockchain technology.

[0092] It's important to note that artificial intelligence (AI) is the study of enabling computers to simulate certain human thought processes and intelligent behaviors (such as learning, reasoning, thinking, and planning). It encompasses both hardware and software technologies. AI hardware technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, and big data processing. AI software technologies primarily include computer vision, speech recognition, natural language processing, machine learning / deep learning, big data processing, and knowledge graph technologies.

[0093] The various numerical designations such as "first," "second," etc., used in this disclosure are merely for ease of description and are not intended to limit the scope of the embodiments of this disclosure, nor do they indicate a sequential order.

[0094] At least one of the features described in this disclosure can also be described as one or more, and multiple features can be two, three, four or more, and this disclosure does not impose any limitations. In the embodiments of this disclosure, for a technical feature, the technical features in that technical feature are distinguished by "first", "second", "third", "A", "B", "C" and "D", etc., and there is no sequential order or size order among the technical features described by "first", "second", "third", "A", "B", "C" and "D".

[0095] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this disclosure can be achieved, and this is not limited herein.

[0096] The specific embodiments described above do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.

Claims

1. A testing method for a protection module, characterized in that, include: The temperature monitoring element is subjected to thermal cycling treatment according to the temperature cycle period, and the temperature monitoring element is wrapped with a protective module. Obtain the first thickness data and stress data of the outer protective sleeve in the protection module, and obtain the second thickness data of the sealing device in the protection module; The first thickness data, the second thickness data, and the stress data are input into the state prediction model to predict the stress and thickness changes of the protection module within a preset time period, thereby generating test data for the protection module.

2. The test method for the protection module according to claim 1, characterized in that, The thermal cycling treatment of the temperature monitoring element according to the temperature cycle period includes: According to the temperature cycle, different temperature loads are applied to the protection module to simulate the temperature changes during operation of the temperature monitoring element. The temperature cycle includes a heating phase and a cooling phase.

3. The testing method for the protection module according to claim 1, characterized in that, The acquisition of the first thickness data and stress data of the outer protective sleeve in the protective module includes: The stress concentration area of ​​the outer protective sleeve is scanned at a preset frequency using an ultrasonic thickness gauge to generate a first thickness variation curve. Strain gauge sensors are installed on the outer protective sleeve to collect local stress data in real time and correlate it with the corresponding temperature value.

4. The test method for the protection module according to claim 1, characterized in that, The acquisition of the second thickness data of the sealing device in the protection module includes: At the end of each thermal cycle, the sealing device penetrating the insulation area is scanned non-contactly. Extract the thickness distribution of at least three axial sections and calculate the thickness attenuation rate as the second thickness data.

5. The testing method for the protection module according to claim 1, characterized in that, The method further includes: Acquire historical first thickness data, historical second thickness data, and historical stress data, and preprocess them to generate training data; Based on the training data, the state prediction model to be trained is iteratively trained to obtain a well-trained state prediction model.

6. The testing method for the protection module according to claim 1, characterized in that, The method further includes: When the predicted rate of stress change exceeds the safety threshold, the deformation compensation of the outer protective sleeve is automatically increased. When the thickness decay rate reaches a critical point, the micro-injection device is controlled to replenish the sealing medium to the sealing device.

7. A testing device for a protection module, characterized in that, include: A processing unit is used to perform thermal cycling treatment on a temperature monitoring element according to a temperature cycle cycle, and the temperature monitoring element is wrapped with a protective module. The acquisition unit is used to acquire the first thickness data and stress data of the outer protective sleeve in the protection module, and to acquire the second thickness data of the sealing device in the protection module; The generation unit is used to input the first thickness data, the second thickness data, and the stress data into the state prediction model to predict the stress change and thickness change of the protection module within a preset time period, and generate the test data of the protection module.

8. An electronic device, characterized in that, include: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the test method of the protection module according to any one of claims 1-6.

9. A non-transitory computer-readable storage medium storing computer instructions, characterized in that, The computer instructions are used to cause the computer to execute the test method for the protection module according to any one of claims 1-6.

10. A computer program product, characterized in that, It includes a computer program that, when executed by a processor, implements the test method for the protection module according to any one of claims 1-6.

Images