Ship mechanical and electrical product accelerated life test stress profile generation method and device, medium and product

Abstract

The invention discloses a ship mechanical and electrical product accelerated life test stress profile generation method and device, a medium and a product, and relates to the field of ship reliability engineering and test.The method comprises the steps that working condition profile data and marine environment stress data of a target ship mechanical and electrical product under a typical navigation task are obtained, and a working condition-environment mapping model is established; according to the designed life target of the target ship mechanical and electrical product, the whole life cycle total damage to the target ship mechanical and electrical product is determined by using the working condition-environment mapping model and the failure physical damage model, an accelerated stress profile is generated by strengthening the stress level with damage equivalence as the principle, an accelerated factor is calculated, and an accelerated life test is performed; and failure data of the failure event is recorded, parameters of the failure physical damage model are calibrated, and the accelerated stress profile is iteratively optimized by using the calibrated failure physical damage model. Accurate and dynamic generation of the accelerated life test stress profile of the ship mechanical and electrical product is realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of ship reliability engineering and testing, in particular to a ship electromechanical product accelerated life test stress profile generation method, device, medium and product. BACKGROUND

[0002] The ship electromechanical product works in a harsh marine environment for a long time, and is subjected to the combined action of vibration, temperature, humidity, salt mist and other stresses, and its reliability is directly related to the safe operation of the ship. Accelerated life test is a key means to evaluate its life and reliability. At present, the following problems exist in this field: The stress profile is disconnected with the real sailing scenario. The traditional method mainly uses standard spectrum or laboratory experience spectrum, and cannot consider the differentiated and time-varying environmental loads borne by the electromechanical product under different sailing conditions of the ship. This leads to that the test load cannot truly reflect the damage accumulation process of the product.

[0003] The acceleration factor determination lacks physical basis and ignores the characteristics of marine environment. In related technologies, the calculation of the acceleration factor mainly depends on the general empirical formula, and cannot be closely related to the key failure physics of the ship electromechanical product in the marine environment, for example, the consideration of electrochemical corrosion fatigue, cavitation wear and other effects caused by the combined action of salt mist and vibration is insufficient. At the same time, the high temperature, high humidity and high salt mist multi-stress field coupling characteristics in the marine environment are not fully reflected in the acceleration model.

[0004] The stress profile is statically solidified. Once the test profile is generated, it is usually fixed during the test process, and when the ship electromechanical product running data is continuously acquired or the product technical state changes, the original profile cannot be updated adaptively, so that the effectiveness and economy of the test method gradually decrease.

[0005] Therefore, there is an urgent need in the art for a dynamic stress profile generation method that can closely couple the sailing conditions of the ship and the failure physics of the marine environment, and has the ability of self-updating. SUMMARY

[0006] The purpose of the present application is to provide a ship electromechanical product accelerated life test stress profile generation method, device, medium and product, so as to realize the accurate and dynamic generation of the ship electromechanical product accelerated life test stress profile.

[0007] To achieve the above purpose, the present application provides the following solutions: In a first aspect, the present application provides a ship electromechanical product accelerated life test stress profile generation method, comprising: Obtaining working condition profile data and corresponding marine environment stress data of a target marine electromechanical product under a typical navigation task; the working condition profile data includes electromechanical product rotating speed, ship speed and sea state level; the marine environment stress data includes ship body vibration, salt mist concentration and temperature data; According to the working condition profile data and the marine environment stress data, a working condition-environment mapping model is established; According to the design life target of the target marine electromechanical product, the working condition-environment mapping model and the failure physical damage model are used to determine the total life cycle damage caused to the target marine electromechanical product; Based on the total life cycle damage, an acceleration stress profile is generated by strengthening stress level based on the principle of damage equivalence, and an acceleration factor is calculated; Based on the acceleration stress profile and the acceleration factor, an accelerated life test is performed, and failure data of all failure events are recorded; the failure data includes failure time and failure mode; According to the failure data of the accelerated life test, the parameters of the failure physical damage model are calibrated, and the calibrated failure physical damage model is used to iteratively optimize the acceleration stress profile.

[0008] In an embodiment, according to the working condition profile data and the marine environment stress data, a working condition-environment mapping model is established, specifically including: The working condition profile data is segmented by using a sliding window method, the window size is set to 1 minute, the step size is set to 1 minute, the average speed and sea state level in the window time are counted as working condition characteristics, and segmented data is obtained; The working condition characteristics of each segmented data are calculated by using a K-means clustering algorithm, and the working condition of each segmented data is identified; the working condition is high sea state high speed navigation, high sea state medium speed navigation, high sea state low speed navigation, low sea state high speed navigation, low sea state medium speed navigation or low sea state low speed navigation; The top three working conditions in the statistical window are selected as typical working conditions, the average speed in each typical working condition statistical window is calculated as a working condition parameter characteristic, and the average sea state level in each typical working condition statistical window is calculated as an environmental stress characteristic; According to the working condition parameter characteristics and the environmental stress characteristics, a working condition-environment mapping model is established by combining a random forest regression model.

[0009] In an embodiment, the working condition-environment mapping model is: E=f(O,S); Wherein, E is an environmental stress characteristic vector, O is a working condition parameter characteristic vector, and S is a sea state parameter.

[0010] In an embodiment, according to the design life target of the target ship electromechanical product, the total life cycle damage caused to the target ship electromechanical product is determined by using the working condition-environment mapping model and the failure physical damage model, specifically comprising: By failure mode and effects analysis, the key failure modes of the target ship electromechanical product in the marine environment are determined, and the corresponding failure physical damage model is selected for each key failure mode; the key failure modes include surface corrosion, structural fracture and material aging; According to the design life target of the target ship electromechanical product, the environmental stress time history corresponding to the mission profile in the life cycle is randomly synthesized by using the working condition-environment mapping model; By using the failure physical damage model, the damage amount in different stages is determined according to the duration and stress composition of each stage profile; The total life cycle damage caused to the target ship electromechanical product in the environmental stress time history in the life cycle is obtained by superimposing the damage amounts in different stages.

[0011] In an embodiment, based on the total life cycle damage, an accelerated stress profile is generated by strengthening the stress level based on the principle of damage equivalence, specifically comprising: Based on the principle of damage equivalence, the stress level of the initial accelerated stress profile is iteratively optimized by increasing the vibration level and strengthening the salt spray frequency, so that the damage caused by the initial accelerated stress profile in the duration is equal to the total life cycle damage, and the accelerated stress profile is generated.

[0012] In an embodiment, the calculation formula of the acceleration factor is: AF=L / T_lab; Wherein, AF is the acceleration factor; L is the design life target; T_lab is the duration of the accelerated stress profile.

[0013] In an embodiment, according to the failure data of the accelerated life test, the parameters of the failure physical damage model are calibrated, and the accelerated stress profile is iteratively optimized by using the calibrated failure physical damage model, specifically comprising: The failure data and the total life cycle damage are compared to obtain a comparison result; According to the comparison result, the parameters of the failure physical damage model are inversely calibrated by using the maximum likelihood estimation method to obtain the calibrated failure physical damage model, and the accelerated stress profile is updated by returning to "according to the design life target of the target ship electromechanical product, the total life cycle damage caused to the target ship electromechanical product is determined by using the working condition-environment mapping model and the failure physical damage model".

[0014] In a second aspect, the present application provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the ship electromechanical product accelerated life test stress profile generation method described above.

[0015] In a third aspect, the present application provides a computer readable storage medium having a computer program stored thereon, wherein the computer program is executed by a processor to implement the ship electromechanical product accelerated life test stress profile generation method described above.

[0016] In a fourth aspect, the present application provides a computer program product comprising a computer program, wherein the computer program is executed by a processor to implement the ship electromechanical product accelerated life test stress profile generation method described above.

[0017] According to the specific embodiments provided by the present application, the present application has the following technical effects: The present application provides a ship electromechanical product accelerated life test stress profile generation method, device, medium and product, the method comprising: obtaining working condition profile data and corresponding marine environment stress data of a target ship electromechanical product under a typical navigation task; establishing a working condition-environment mapping model according to the working condition profile data and the marine environment stress data; determining total damage to the target ship electromechanical product throughout its life cycle according to a design life target of the target ship electromechanical product, using the working condition-environment mapping model and a failure physical damage model; generating an accelerated stress profile by strengthening stress levels based on the total damage throughout the life cycle and on the principle of damage equivalence, and calculating an acceleration factor; performing an accelerated life test based on the accelerated stress profile and the acceleration factor, and recording failure data of all failure events; calibrating parameters of the failure physical damage model according to the failure data of the accelerated life test, and iteratively optimizing the accelerated stress profile using the calibrated failure physical damage model. The present application establishes a working condition-environment mapping model, so that the generated accelerated stress profile can accurately reflect the real load history of the product under a specific navigation task and sea conditions, greatly improving the relevance and authenticity of the test. Key parameters such as salt mist concentration and corrosion influence factor are introduced according to the characteristics of the marine environment, making the failure physical damage model more close to the actual working scenario of the ship electromechanical product, and the acceleration factor calculation more scientific and reliable. Through the closed-loop mechanism of test-feedback-calibration, the accelerated stress profile can be continuously updated and optimized with the accumulation of ship operation data and the discovery of new failure modes, significantly improving the long-term effectiveness of the test method. BRIEF DESCRIPTION OF DRAWINGS

[0018] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 A flowchart illustrating a method for generating stress profiles in accelerated life testing of marine electromechanical products, provided in an embodiment of this application; Figure 2 A flowchart illustrating the practical application of the method for generating stress profiles for accelerated life testing of marine electromechanical products provided in this application; Figure 3 A flowchart of an iterative optimization process based on the damage equivalence principle provided for an embodiment of this application; Figure 4 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. Detailed Implementation

[0020] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0021] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0022] To address the problems of poor test fidelity, inaccurate acceleration factors, and rigid test methods in traditional accelerated life tests of marine electromechanical products, which are caused by the disconnect between stress profiles and actual navigation conditions and failure physics, and the lack of self-updating capabilities, this application provides a method for generating stress profiles for accelerated life tests of marine electromechanical products (such as pumps, fans, motors, etc.). This method can be dynamically updated to continuously optimize the accuracy and efficiency of the test.

[0023] In one exemplary embodiment, such as Figure 1 and Figure 2 As shown in the figure, a method for generating stress profiles for accelerated life testing of marine electromechanical products is provided, including the following steps: S1: Obtain the operating condition profile data of the target ship's electromechanical products under typical navigation missions and the corresponding marine environmental stress data; the operating condition profile data includes the rotational speed of the electromechanical products, the ship's speed, and the sea state level; the marine environmental stress data includes hull vibration, salt spray concentration, and temperature data.

[0024] S2: Based on the working condition profile data and the marine environmental stress data, establish a working condition-environment mapping model.

[0025] In one embodiment, S2 specifically includes: S21: The operating condition profile data is segmented using a sliding window method. The window size is set to 1 minute and the step size is 1 minute. The average speed and sea state level within the window time are used as operating condition features to obtain the segmented data.

[0026] S22: The K-means clustering algorithm is used to calculate the working condition characteristics of each segmented data and identify the working condition of each segmented data; the working condition is high sea state high speed navigation, high sea state medium speed navigation, high sea state low speed navigation, low sea state high speed navigation, low sea state medium speed navigation, or low sea state low speed navigation.

[0027] S23: Select the three operating conditions with the most statistical windows as typical operating conditions, calculate the average speed within the statistical window of each typical operating condition as the operating condition parameter feature, and the average sea state level within the statistical window of each typical operating condition as the environmental stress feature.

[0028] S24: Based on the operating condition parameter characteristics and the environmental stress characteristics, and combined with the random forest regression model, an operating condition-environment mapping model is established. The operating condition-environment mapping model is as follows: E=f(O,S); Where E is the environmental stress characteristic vector, O is the operating condition parameter characteristic vector, and S is the sea state parameter.

[0029] In this embodiment, the environmental load spectrum based on the ship's navigation condition profile is first constructed: Step 1.1 Data Acquisition: Using shipborne sensors, data loggers, and ship navigation data recording systems, collect the operating condition profile data of the target ship's electromechanical products under typical navigation missions and their corresponding multi-source environmental stress data (marine environmental stress data). The operating condition profile data includes the rotational speed of the electromechanical products, ship speed, sea state level, etc., while the marine environmental stress data includes hull vibration, salt spray concentration, temperature data, etc.

[0030] Step 1.2: Working Condition Block Division and Feature Extraction: The collected working condition profile data is segmented and clustered to identify the corresponding working condition blocks, including six typical working conditions: high sea state high-speed navigation, high sea state medium-speed navigation, high sea state low-speed navigation, low sea state high-speed navigation, low sea state medium-speed navigation, and low sea state low-speed navigation. The three working condition blocks with the highest number of statistical windows are selected as typical working condition blocks. The average speed within the statistical window of each typical working condition block is calculated as the working condition parameter feature, and the average sea state level within the statistical window of each typical working condition block is used as the environmental stress feature.

[0031] The process of segmenting and clustering the working condition profile data is as follows: First, a sliding window method is used to segment the operating condition profile data. The window size is set to 1 minute, and the step size is 1 minute. The average speed and sea state level within the statistical window time are used as operating condition features. The operating condition features of each statistical window represent the relatively stable state within that time period, thus completing the segmentation of the operating condition data. Then, the K-means clustering algorithm is used to calculate the operating condition features of each segmented data, where the number of clusters K is defined as 6, completing the clustering calculation for each operating condition.

[0032] Step 1.3 Establish the operating condition-environment mapping model: Based on the results of Step 1.2, establish a quantitative mapping relationship between operating condition profile parameters (including average speed, average main engine power, etc.) and marine environmental stress parameters (including sea surface wind speed, sea surface temperature, sea surface humidity, etc.). Considering that there is a certain interaction between operating condition profile parameters and marine environmental stress parameters, a random forest regression model that can handle nonlinear relationships is selected to complete the establishment of the mapping relationship model.

[0033] S3: Based on the design life target of the target ship's electromechanical products, use the operating condition-environment mapping model and the failure physical damage model to determine the total life cycle damage caused to the target ship's electromechanical products.

[0034] In one embodiment, S3 specifically includes: S31: Through failure mode and effects analysis, determine the key failure modes of the target ship's electromechanical products in the marine environment, and select the corresponding physical damage model for each key failure mode; the key failure modes include surface corrosion, structural fracture and material aging.

[0035] S32: Based on the design life target of the target ship's electromechanical products, the environmental stress time history corresponding to the mission profile throughout the entire life cycle is randomly synthesized using the operating condition-environment mapping model. The mission profile refers to the operating condition curve of the target ship's electromechanical products over time.

[0036] S33: Using the aforementioned failure physical damage model, determine the damage amount in different stages based on the duration of each stage profile and stress composition.

[0037] S34: Obtain the total life-cycle damage to the target ship's electromechanical products during the entire life-cycle environmental stress time history by superimposing the damage amounts in different stages.

[0038] S4: Based on the total damage over the entire life cycle and the principle of damage equivalence, an accelerated stress profile is generated by increasing the stress level, and the acceleration factor is calculated.

[0039] In one embodiment, based on the total damage over the entire life cycle and adhering to the principle of damage equivalence, an accelerated stress profile is generated by increasing the stress level, specifically including: Based on the principle of damage equivalence, the stress level of the initial accelerated stress profile is iteratively optimized by increasing the vibration level and strengthening the salt spray frequency, so that the damage caused by the initial accelerated stress profile over the duration is equal to the total damage over the entire life cycle, thus generating the accelerated stress profile.

[0040] The formula for calculating the acceleration factor is: AF = L / T_lab; Where AF is the acceleration factor; L is the design life target; and T_lab is the duration of the accelerated stress profile.

[0041] In this embodiment, after constructing the condition-environment mapping model, damage equivalence and acceleration profile generation based on marine environment failure physics are performed: Step 2.1 Determination of Key Failure Modes and Damage Models: Through failure mode and effects analysis, the key failure modes of marine electromechanical products in the marine environment are determined. Key failure modes include surface corrosion, structural fracture, material aging, etc., and corresponding physical damage models are selected for each key failure mode (damage amount is a function of time, and parameters related to material, environment and other factors are hyperparameters, which can generally be set by consulting literature and standards).

[0042] Step 2.2 Calculation of total life cycle damage: Based on the design life target L (usually mean time between failures) and service profile of the ship's electromechanical products, the environmental stress time history S_ship(t) corresponding to the mission profile is randomly synthesized using the operating condition-environment mapping model. Using the failure physical damage model selected in Step 2.1, the damage amount in different stages is calculated based on the duration and stress composition of each stage profile, and the total life cycle damage D_total caused to the ship's electromechanical products within S_ship(t) is obtained by superimposing the data.

[0043] Step 2.3 Accelerated Test Profile Generation and Acceleration Factor Calculation: An accelerated stress profile S_lab(t) with enhanced working conditions is constructed by increasing the working conditions and environmental stress. Its duration T_lab is much shorter than the design life target L, ensuring damage equivalence, i.e., D_lab = D_total, where D_lab is the damage caused by S_lab(t) within time T_lab. Based on the damage equivalence principle, the stress level of S_lab(t) is iteratively optimized by increasing the vibration magnitude and strengthening the salt spray frequency, ensuring that D_lab = D_total holds true. The iterative optimization process based on the damage equivalence principle is as follows: Figure 3As shown, the acceleration factor is calculated using AF=L / T_lab. By setting the acceleration factor, the degradation process of the product is accelerated, thereby accelerating the life test.

[0044] S5: Based on the accelerated stress profile and the accelerated factor, conduct accelerated life tests and record failure data for all failure events; the failure data includes failure time and failure mode.

[0045] S6: Based on the failure data from the accelerated life test, calibrate the parameters of the failure physical damage model, and iteratively optimize the accelerated stress profile using the calibrated failure physical damage model.

[0046] In one embodiment, S6 specifically includes: S61: Compare the failure data with the total damage over the entire life cycle to obtain a comparison result. In practical applications, failure data is usually characteristic data reflecting the amount of damage. The current amount of damage can be located through the failure data values. Therefore, the comparison result is actually the result of comparing the current amount of damage with the total damage over the entire life cycle.

[0047] S62: Based on the comparison results, the parameters of the failure physical damage model are calibrated in reverse using the maximum likelihood estimation method to obtain the calibrated failure physical damage model, and the "total life-cycle damage caused to the target ship's electromechanical products is determined by using the working condition-environment mapping model and the failure physical damage model according to the design life target of the target ship's electromechanical products" is returned, and the accelerated stress profile is updated.

[0048] In this embodiment, after the stress profile is generated, the stress profile is dynamically updated: Step 3.1 Test Implementation and Data Feedback: Use the generated accelerated stress profile S_lab(t) to conduct accelerated life tests and record the occurrence time and failure mode of all failure events.

[0049] Step 3.2 Model parameter calibration: Compare the failure data observed in the experiment with the total damage over the entire life cycle, and use the maximum likelihood estimation method to calibrate the parameters of the failure physical damage model in step 2.1.

[0050] Step 3.3 Profile Iteration Optimization: Using the calibrated failure physical damage model, repeat steps 2.2 and 2.3 to generate a more accurate accelerated stress profile S_lab_new(t) for subsequent testing or product design improvements.

[0051] The method for generating stress profiles for accelerated life testing of marine electromechanical products provided in this application has the following beneficial effects: High channel fidelity: By establishing a "ship operating condition-marine environment" mapping model, the generated stress profile can accurately reflect the actual load history of the product under specific navigation missions and sea conditions, greatly improving the relevance and authenticity of the test.

[0052] Marine environmental adaptability: In response to the characteristics of the marine environment, key parameters such as salt spray concentration and corrosion influencing factors are introduced to make the failure physics model closer to the actual working scenario of ship electromechanical products, and to make the calculation of acceleration factors more scientific and reliable.

[0053] Dynamic Adaptation: Through a closed-loop mechanism of "experiment-feedback-calibration", the stress profile can be continuously updated and optimized as ship operation data is accumulated and new failure modes are discovered, which significantly improves the long-term effectiveness and economy of the test method.

[0054] Highly practical for engineering applications: This method is closely integrated with actual ship operations, and the generated stress profiles have direct guiding significance for the design verification, reliability improvement, and spare parts strategy formulation of ship electromechanical products.

[0055] In one exemplary embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the above-described method for generating stress profiles for accelerated life testing of marine electromechanical products.

[0056] In one exemplary embodiment, a computer-readable storage medium is provided storing a computer program that, when executed by a processor, implements the above-described method for generating stress profiles for accelerated life testing of marine electromechanical products.

[0057] In one exemplary embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the above-described method for generating stress profiles for accelerated life testing of marine electromechanical products.

[0058] In one exemplary embodiment, a computer device is provided, which may be a server or a terminal, and its internal structure diagram may be as follows. Figure 4As shown, the computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements a method for generating stress profiles for accelerated life testing of marine electromechanical products.

[0059] Those skilled in the art will understand that Figure 4 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0060] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0061] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0062] The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0063] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0064] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for generating stress profiles in accelerated life testing of marine electromechanical products, characterized in that, include: The system acquires operating condition profile data of the target ship's electromechanical products under typical navigation missions and corresponding marine environmental stress data. The operating condition profile data includes the rotational speed of the electromechanical products, the ship's speed, and the sea state. The marine environmental stress data includes hull vibration, salt spray concentration, and temperature data. Based on the operating condition profile data and the marine environmental stress data, an operating condition-environment mapping model is established; Based on the design life target of the target ship's electromechanical products, the total life-cycle damage to the target ship's electromechanical products is determined using the operating condition-environment mapping model and the failure physical damage model. Based on total damage over the entire life cycle and adhering to the principle of damage equivalence, an accelerated stress profile is generated by increasing the stress level, and the acceleration factor is calculated. Based on the accelerated stress profile and the acceleration factor, accelerated life tests were conducted, and failure data for all failure events were recorded. The failure data includes failure time and failure mode; Based on the failure data from accelerated life testing, the parameters of the failure physical damage model are calibrated, and the accelerated stress profile is iteratively optimized using the calibrated failure physical damage model.

2. The method for generating stress profiles for accelerated life testing of marine electromechanical products according to claim 1, characterized in that, Based on the aforementioned working condition profile data and the aforementioned marine environmental stress data, a working condition-environment mapping model is established, specifically including: The working condition profile data is segmented using a sliding window method. The window size is set to 1 minute and the step size is 1 minute. The average speed and sea state level within the window time are used as working condition features to obtain the segmented data. The K-means clustering algorithm is used to calculate the working condition characteristics of each segmented data and identify the working condition of each segmented data; the working conditions are high sea state high speed navigation, high sea state medium speed navigation, high sea state low speed navigation, low sea state high speed navigation, low sea state medium speed navigation, or low sea state low speed navigation. The three operating conditions with the most statistical windows were selected as typical operating conditions. The average speed within the statistical window of each typical operating condition was calculated as the operating condition parameter characteristic, and the average sea state level within the statistical window of each typical operating condition was used as the environmental stress characteristic. Based on the operating condition parameter characteristics and the environmental stress characteristics, and combined with the random forest regression model, an operating condition-environment mapping model is established.

3. The method for generating stress profiles for accelerated life testing of marine electromechanical products according to claim 1, characterized in that, The working condition-environment mapping model is as follows: E=f(O,S); Where E is the environmental stress characteristic vector, O is the operating condition parameter characteristic vector, and S is the sea state parameter.

4. The method for generating stress profiles for accelerated life testing of marine electromechanical products according to claim 1, characterized in that, Based on the design life target of the target ship's electromechanical products, the total life-cycle damage caused to the target ship's electromechanical products is determined using the operating condition-environment mapping model and the failure physical damage model, specifically including: Failure Mode and Effects Analysis (FMEA) was used to identify the key failure modes of the target ship's electromechanical products in a marine environment, and corresponding physical damage models were selected for each key failure mode. The key failure modes included surface corrosion, structural fracture, and material aging. Based on the design life target of the target ship's electromechanical products, the environmental stress time history corresponding to the mission profile throughout the entire life cycle is randomly synthesized using the working condition-environment mapping model. Using the aforementioned failure physical damage model, the damage amount in different stages is determined based on the duration of each stage profile and the stress composition. The total life-cycle damage to the target ship's electromechanical products is obtained by superimposing the damage amounts at different stages over the entire life-cycle environmental stress time history.

5. The method for generating stress profiles for accelerated life testing of marine electromechanical products according to claim 1, characterized in that, Based on total damage over the entire life cycle and adhering to the principle of damage equivalence, an accelerated stress profile is generated by increasing the stress level, specifically including: Based on the principle of damage equivalence, the stress level of the initial accelerated stress profile is iteratively optimized by increasing the vibration level and strengthening the salt spray frequency, so that the damage caused by the initial accelerated stress profile over the duration is equal to the total damage over the entire life cycle, thus generating the accelerated stress profile.

6. The method for generating stress profiles for accelerated life testing of marine electromechanical products according to claim 1, characterized in that, The formula for calculating the acceleration factor is: AF = L / T_lab; Where AF is the acceleration factor; L is the design life target; and T_lab is the duration of the accelerated stress profile.

7. The method for generating stress profiles for accelerated life testing of marine electromechanical products according to claim 1, characterized in that, Based on the failure data from accelerated life testing, the parameters of the failure physical damage model are calibrated, and the accelerated stress profile is iteratively optimized using the calibrated failure physical damage model. Specifically, this includes: The failure data is compared with the total damage over the entire life cycle to obtain the comparison results; Based on the comparison results, the parameters of the failure physical damage model are calibrated in reverse using the maximum likelihood estimation method to obtain the calibrated failure physical damage model, and the "total life-cycle damage caused to the target ship's electromechanical products is determined based on the design life target of the target ship's electromechanical products using the operating condition-environment mapping model and the failure physical damage model" is returned, updating the accelerated stress profile.

8. A computer device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the method for generating stress profiles for accelerated life testing of marine electromechanical products according to any one of claims 1-7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the method for generating stress profiles for accelerated life testing of marine electromechanical products as described in any one of claims 1-7.

10. A computer program product, comprising a computer program, characterized in that, When executed by a processor, the computer program implements the method for generating stress profiles for accelerated life testing of marine electromechanical products as described in any one of claims 1-7.

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