A complex system health state evaluation method based on task reliability model

Abstract

The application discloses a kind of complex system health state evaluation methods based on task reliability model, comprising the following steps: 1) analysis complex system's task profile, and the task is associated to relevant equipment, and the working mode of equipment and the associated relationship between each equipment are determined, and the system task reliability model is established;2) according to the associated relationship of system task reliability model's series and parallel, weight distribution is carried out;3) complex system health state evaluation is carried out based on system task reliability model.The application carries out health degree evaluation by using complex system reliability model, and according to system actual topological structure and operating condition, the weight calculation method of each equipment of complex system is proposed, the importance of equipment in complex system can be reasonably determined, and the health state evaluation problem of complex system is solved.

Description

Technical Field

[0001] This invention relates to industrial equipment system evaluation technology, and more particularly to a method for evaluating the health status of complex systems based on a task reliability model. Background Technology

[0002] The condition monitoring and health management systems of complex modern industrial equipment have become a focus of attention in both academia and industry. However, current research largely concentrates on the health status assessment of specific types of equipment, making it difficult to effectively analyze the health status of complex systems. Furthermore, the complex coupling relationships between devices within a system are difficult to integrate with the overall system health status analysis, and the impact of a decline in the health status of a particular device on the health status of the entire system is difficult to objectively and accurately assess – these are also existing problems. To address these issues, it is necessary to explore new approaches to health status assessment, thereby supporting equipment usage and renovation decisions and improving the task completion rate of complex system equipment. Summary of the Invention

[0003] The technical problem to be solved by the present invention is to provide a method for evaluating the health status of complex systems based on a task reliability model, addressing the deficiencies in the prior art.

[0004] The technical solution adopted by this invention to solve its technical problem is: a method for evaluating the health status of complex systems based on a task reliability model, comprising the following steps:

[0005] 1) Analyze the task profile of the complex system, associate the tasks with relevant equipment, determine the working mode of the equipment and the series and parallel relationships between the equipment, and establish a system task reliability model;

[0006] 2) Based on the series and parallel relationships in the system task reliability model, the weights are allocated in the following manner;

[0007] 2.1) Use generalized distance to assess the health status of equipment. Calculate the generalized distance X of the equipment. The larger the generalized distance, the lower the health status.

[0008]

[0009] Among them, S i =[s1,s2,s3,…s n ] T , i represents the device serial number, s i The equipment health status evaluation index represents the equipment operation monitoring data corresponding to the equipment operation monitoring data, where n represents the data type of monitoring data.

[0010] Serial number;

[0011] R i =[r1,r2,r3,…rn ] T r i These are the standard values ​​for the monitoring data of each piece of equipment.

[0012] 2.2) If the system task reliability model is a series system reliability model, the weights of the devices within the system are calculated using generalized distance. The larger the generalized distance, the lower the health status of the devices within the system, and the larger their weights. The specific calculation method is as follows:

[0013] The generalized distance between each device is normalized and used as the weight α of the series system, thus achieving the goal of giving higher weights to devices with worse health conditions within the series system.

[0014]

[0015] 2.3) If the system task reliability model is a parallel system reliability model, the weights of the devices within the system are calculated using generalized distance.

[0016] The weight of a parallel system is determined by the health status of the devices within it.

[0017]

[0018] 2.4) If the system task reliability model is a hybrid system reliability model, the model is divided into large loop and small loop. Each small loop is a series or parallel model. First, the weights of each device are calculated in the small loop, and the health of the small loop is calculated. In the large loop, the calculation results of the small loop are used to allocate the weights.

[0019] 2.5) If the system task reliability model is a combined system reliability model, the combined system reliability model is composed of functionally independent branch units and a shared central unit; the specific calculation method is as follows:

[0020] 2.5.1) First, take the proportion b of the total task in the known branch unit as the weight of each branch unit, and then multiply the health status of the equipment in each branch unit by the weight of each branch unit and sum them to calculate the overall health status of the branch unit.

[0021] 2.5.2) Then calculate the generalized distance between the entire branch unit and the central unit and the standard value 100;

[0022] 2.5.3) Using the weight calculation method of the reliability model of a series system, the generalized distance between the branch unit and the central unit is normalized and used as the weight of the two parts;

[0023] 2.6) If the system task reliability model is an r / n(G) system reliability model, convert it into a hybrid system reliability model with parallel large loops and series small loops, and then use the hybrid system reliability model for calculation; the model conversion method is as follows:

[0024] Calculate C(n, r) using permutation and combination algorithms and list all possible permutations; use the result of C(n, r) as the number of parallel paths in the large loop, and each permutation as the series result in the small loop;

[0025] 3) Evaluate the health status of complex systems based on system task reliability models;

[0026] After calculating the weights of each device, the health status of the system is calculated by multiplying the weights by the corresponding device health status and then summing the results.

[0027] According to the above scheme, the calculation of the system's health status in step 3) is as follows:

[0028] 3.1) For series and parallel systems, the calculation is performed by directly multiplying the weight α by the equipment health degree h and then summing the results.

[0029]

[0030] 3.2) For a hybrid system, first calculate the health of the smaller loops (series or parallel), and then calculate the health of the larger loops (parallel or series).

[0031] 3.3) For a series system, first calculate the health of the branch units, and then calculate the health of the entire system by treating the branch units and shared units as a series system;

[0032] 3.4) For the r / n(G) system, convert it to a hybrid model before calculating the health status.

[0033] The beneficial effects of this invention are:

[0034] (1) Using a reliability model of a complex system to evaluate health status is consistent with the actual working conditions of the system and solves the problem of health status assessment of complex systems.

[0035] (2) Based on the actual topology and operation of the system, a method for calculating the weights of each device in a complex system is proposed, which can reasonably determine the importance of each device in a complex system;

[0036] (3) Using simple and clear calculation methods to calculate the health status of complex systems is beneficial to the implementation of complex system engineering and reduces the time for health status assessment of complex systems. Attached Figure Description

[0037] The present invention will be further described below with reference to the accompanying drawings and embodiments. In the accompanying drawings:

[0038] Figure 1 This is a flowchart of a method according to an embodiment of the present invention;

[0039] Figure 2 This is a schematic diagram of the reliability model breakdown of a hybrid system according to an embodiment of the present invention;

[0040] Figure 3 This is a schematic diagram of the reliability model conversion of the r / n(G) system according to an embodiment of the present invention;

[0041] Figure 4 This is a schematic diagram of the reliability model conversion of the Helian system according to an embodiment of the present invention. Detailed Implementation

[0042] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0043] like Figure 1 As shown, a method for evaluating the health status of complex systems based on a task reliability model includes the following steps:

[0044] (1) Determine the task profile of the complex system. Based on the function and usage scenario of the complex system, determine the task profile of the complex system and determine the usage mode of the complex system;

[0045] The complex system is a system composed of a moderate number of electromechanical devices;

[0046] (2) Construct a reliability model for complex system tasks;

[0047] Establish a reliability model for a complex system based on its composition, configuration, connections between devices, and functional transfer relationships.

[0048] (3) Determine the evaluation indicators for each device in the complex system and collect data. Select important evaluation indicators that can reflect the health status of each device, collect actual operating data of the devices, and form a device dataset. The dataset for the i-th device is S. i .

[0049] S i =[s1,s2,s3,…s n ] T

[0050] (4) Determine the standard values ​​for each equipment indicator. By consulting relevant equipment data and conducting big data statistics, determine the standard values ​​for each indicator under good working condition for each piece of equipment. The standard value set for the i-th equipment is R.i .

[0051] R i =[r1,r2,r3,…r n ] T

[0052] (5) Calculate the generalized distance between the sampled values ​​and the standard values. Calculate the generalized distance based on the previously calculated device dataset and standard value set, using the formula shown below.

[0053]

[0054] (6) Determine the reliability model type of the complex system task, and calculate the weight of each device in the complex system according to the system model type. There are a total of 4 model types.

[0055] Type 1: Reliability Model for Series Systems. The generalized distances between each device are normalized, and the normalized result is used as the weight of each device. The calculation formula is shown below.

[0056]

[0057] Type 2: Parallel System Reliability Model. The generalized distances of each device are normalized after taking the reciprocal, and the normalized result is used as the weight of each device. The calculation formula is shown below.

[0058]

[0059] Type 3: Hybrid System Reliability Model. This type of model breaks down the reliability model of a hybrid system into multiple series and parallel models. Taking a specific hybrid system structure as an example, it is broken down into two series small loops and one parallel large loop. The breakdown is as follows: Figure 2 As shown.

[0060] First, calculate the weight of each device in the series structure of small loops using the calculation formula of type one; then calculate the health of the two small loops A and B respectively using the formula in (7) for calculating the health of complex systems; then calculate the generalized distance between the health of the two small loops A and B and the standard health of 100; finally, calculate the weight of A and B in the parallel structure of large loops using the calculation formula of type two.

[0061] Type 4: r / n(G) system reliability model. The r / n(G) system reliability model can be converted into a hybrid system reliability model. Taking a certain r / n(G) system reliability model as an example, the conversion to a hybrid system reliability model is as follows: Figure 3 As shown. After the conversion, the weights are calculated according to the reliability model of a Type III hybrid system.

[0062] Type 5: Reliability Model for Parallel Systems. The reliability model for parallel systems is a combination of models that can be converted into reliability models for parallel and series systems. In the parallel system, the weight α of each device can be directly obtained by using the ratio b of the task in the branch unit to the total task. The conversion is as follows: Figure 4 As shown. After the conversion, the health of the parallel part A can be calculated first, then the generalized distance between the health of A and C and the standard health of 100 can be calculated, and finally the weights of A and B can be calculated in the series model using the normalization calculation formula of type one.

[0063] (7) Calculate the health of the complex system. Calculate the health of the complex system based on the weights of each device calculated in (6) and the health of the device itself. The calculation formula is shown below.

[0064]

[0065] It should be understood that those skilled in the art can make improvements or modifications based on the above description, and all such improvements and modifications should fall within the protection scope of the appended claims.

Claims

1. A method for evaluating the health status of complex systems based on a task reliability model, characterized in that, Includes the following steps: 1) Analyze the task profile of the complex system, associate the tasks with relevant equipment, determine the working mode of the equipment and the series and parallel relationships between the equipment, and establish a system task reliability model; 2) Based on the series and parallel relationships in the system task reliability model, the weights are allocated in the following manner; 2.1) Use generalized distance to assess the health status of equipment. Calculate the generalized distance X of the equipment. The larger the generalized distance, the lower the health status. Among them, S i =[s1,s2,s3,…s n ] T , i represents the device serial number, s i The equipment operation monitoring data corresponding to the evaluation indicators of equipment health status, where n represents the type of monitoring data; R i =[r1,r2,r3,…r n ] T r i These are the standard values ​​for the monitoring data of each piece of equipment. 2.2) If the system task reliability model is a series system reliability model, the weights of the devices in the system are calculated using generalized distance; the specific calculation method is as follows: 2.3) If the system task reliability model is a parallel system reliability model, the weights of the devices within the system are calculated using generalized distance. 2.4) If the system task reliability model is a hybrid system reliability model, the model is divided into large loop and small loop. Each small loop is a series or parallel model. First, the weights of each device are calculated in the small loop, and the health of the small loop is calculated. In the large loop, the calculation results of the small loop are used to allocate the weights. 2.5) If the system task reliability model is a combined system reliability model, the combined system reliability model is composed of functionally independent branch units and a shared central unit; the specific calculation method is as follows: 2.5.1) First, take the proportion b of the total task in the known branch unit as the weight of each branch unit, and then multiply the health status of the equipment in each branch unit by the weight of each branch unit and sum them to calculate the overall health status of the branch unit. 2.5.2) Then calculate the generalized distance between the entire branch unit and the central unit and the standard value 100; 2.5.3) Using the weight calculation method of the reliability model of a series system, the generalized distance between the branch unit and the central unit is normalized and used as the weight of the two parts; 2.6) If the system task reliability model is an r / n(G) system reliability model, convert it into a hybrid system reliability model with parallel large loops and series small loops, and then use the hybrid system reliability model for calculation; the model conversion method is as follows: Calculate C(n, r) using permutation and combination algorithms and list all possible permutations; use the result of C(n, r) as the number of parallel paths in the large loop, and each permutation as the series result in the small loop; 3) Evaluate the health status of complex systems based on system task reliability models; After calculating the weights of each device, the health status of the system is calculated by multiplying the weights by the corresponding device health status and then summing the results.

2. The method for evaluating the health status of complex systems based on a task reliability model according to claim 1, characterized in that, Step 3) involves calculating the system's health status, as follows: 3.1) For series and parallel systems, the weight α is used directly. i Equipment health h i The calculation is performed by multiplying and then summing the results. 3.2) For a hybrid system, calculate the health of the smaller loops first, and then calculate the health of the larger loops. 3.3) For a series system, first calculate the health of the branch units, and then calculate the health of the entire system by treating the branch units and shared units as a series system; 3.4) For the r / n(G) system, convert it to a hybrid model before calculating the health status.

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