Overall maintenance quality assessment method and system for petrochemical plants

Abstract

The present invention provides a method and system for evaluating the overall maintenance quality of a petrochemical device. The evaluation method includes: obtaining the daily maintenance time and daily maintenance workload within a preset time period before the overall maintenance, and determining the daily maintenance cumulative workload corresponding to the daily maintenance cumulative time according to the daily maintenance cumulative time within the preset time period; establishing a cumulative workload prediction model according to the daily maintenance cumulative time and the corresponding daily maintenance cumulative workload; predicting the predicted cumulative workload corresponding to the sliding fixed time period according to the cumulative workload prediction model; determining the corresponding holding time according to the ratio of the actual cumulative workload and the predicted cumulative workload; and evaluating the overall maintenance quality according to the length of the holding time. Through the evaluation method provided by the present invention, the quality of the device after the overall maintenance can be quickly evaluated, effectively guiding the overall maintenance of the enterprise each time, and assisting the enterprise to trace the source and gradually control and reduce the workload of daily maintenance.

Description

Technical Field

[0001] The present invention relates to the technical field of petrochemical plant maintenance, and in particular to a method for evaluating the overall maintenance quality of a petrochemical plant and a system for evaluating the overall maintenance quality of a petrochemical plant. Background Art

[0002] In order to meet the growing demand for domestic energy, petrochemical enterprises have continuously expanded their production scale and improved their production technology, making petrochemical plants increasingly large-scale, continuous and automated, and the structure of petrochemical plants more complex. As the use time increases, petrochemical plants will have more or less some failures, which will have a certain impact on the operation of the enterprise.

[0003] In daily production and operation, in addition to routine maintenance of petrochemical equipment, overall and comprehensive maintenance of petrochemical equipment is also carried out from time to time. If the overall maintenance quality is not high, there will be a lot of inspection and maintenance work left, so that once the petrochemical equipment is turned on, it will face a lot of repair work, increasing the daily maintenance workload, making it more likely to cause serious accident consequences and increase the normal operation risk of the petrochemical equipment. Therefore, the quality of overall maintenance plays an important role in the normal operation of production. However, in the prior art, there is no quantitative method for judging the quality of overall maintenance. Summary of the invention

[0004] In view of the technical problem that the prior art cannot perform quantitative evaluation on overall maintenance, the present invention provides a method for evaluating the quality of overall maintenance of a petrochemical plant and a system for evaluating the quality of overall maintenance of a petrochemical plant, which can quickly evaluate the quality of the plant after overall maintenance, effectively guide the company's overall maintenance each time, and assist the company in tracing the source and gradually controlling and reducing the workload of daily maintenance.

[0005] To achieve the above-mentioned purpose, the first aspect of the present invention provides a method for evaluating the overall maintenance quality of a petrochemical plant, the method comprising: obtaining the daily maintenance time and the daily maintenance workload within a preset time period before the overall maintenance, determining the daily maintenance cumulative workload corresponding to the daily maintenance cumulative time according to the daily maintenance cumulative time within the preset time period; establishing a cumulative workload prediction model according to the daily maintenance cumulative time and the corresponding daily maintenance cumulative workload; obtaining the time value and the day value after the overall maintenance is completed, and inputting the daily maintenance cumulative time corresponding to the time value and the day value into the prediction model; The cumulative workload prediction model predicts the predicted cumulative workload corresponding to the sliding fixed time period, wherein the time value is the sum of the day value calculated from the date of completion of this overall maintenance and the sliding fixed time period, expressed as: P=i+w, i=0, 1, 2, ···n; P is the time value; w is a positive integer representing the sliding fixed time period; i is the day value; the actual cumulative workload within the sliding fixed time period is obtained; according to the ratio of the actual cumulative workload to the predicted cumulative workload, the holding time corresponding to the time value is determined; and the overall maintenance quality is evaluated according to the length of the holding time.

[0006] Furthermore, the cumulative workload prediction model is established based on the daily maintenance cumulative time and the corresponding daily maintenance cumulative workload, including: based on the daily maintenance cumulative time and the corresponding daily maintenance cumulative workload, the cumulative workload prediction model is established using a linear regression method or a linear weighted regression method.

[0007] Furthermore, after establishing the cumulative workload prediction model based on the daily maintenance cumulative time and the corresponding daily maintenance cumulative workload, the method also includes: optimizing the cumulative workload prediction model; and using the optimized cumulative workload prediction model to predict the corresponding predicted cumulative workload.

[0008] Furthermore, the cumulative workload prediction model is established based on the daily maintenance cumulative time and the corresponding daily maintenance cumulative workload using a linear regression method or a linear weighted regression method, including: dividing the daily maintenance cumulative time and the corresponding daily maintenance cumulative workload difference into a training set and a verification set; based on the training set, an initial cumulative workload prediction model is established using a linear regression method or a linear weighted regression method; the cumulative workload prediction model is optimized, including: verifying the accuracy of the initial cumulative workload prediction model based on the verification set; when the accuracy is greater than or equal to a preset accuracy, determining the initial cumulative workload prediction model as the optimized cumulative workload prediction model.

[0009] Furthermore, the optimization of the cumulative workload prediction model includes: when the accuracy is less than the preset accuracy, successively extending the daily maintenance cumulative time, and verifying the accuracy of the initial cumulative workload prediction model after each extension of the daily maintenance cumulative time, until the accuracy of the initial cumulative workload prediction model is greater than or equal to the preset accuracy, and using the initial cumulative workload prediction model after extending the daily maintenance cumulative time as the optimized cumulative workload prediction model.

[0010] Furthermore, evaluating the overall maintenance quality effect based on the length of the holding time includes: when the length of the holding time is less than the set time length, judging that the quality of the overall maintenance is poor; when the length of the holding time is greater than or equal to the set time length, judging that the quality of the overall maintenance is good.

[0011] The second aspect of the present invention provides a system for evaluating the overall maintenance quality of a petrochemical plant, the system comprising: a determination module for obtaining the daily maintenance time and the daily maintenance workload within a preset time period before the overall maintenance, and determining the daily maintenance cumulative workload corresponding to the daily maintenance cumulative time according to the daily maintenance cumulative time within the preset time period; a model establishment module for establishing a cumulative workload prediction model according to the daily maintenance cumulative time and the corresponding daily maintenance cumulative workload; a prediction module for obtaining the time value and the day value after the overall maintenance is completed, and inputting the daily maintenance cumulative time corresponding to the time value and the day value into the prediction model respectively. The cumulative workload prediction model predicts the predicted cumulative workload corresponding to the sliding fixed time period, wherein the time value is the sum of the day value calculated from the date of completion of this overall maintenance and the sliding fixed time period, expressed as: P=i+w, i=0, 1, 2, ···n; P is the time value; w is a positive integer representing the sliding fixed time period; i is the day value; the determination module is also used to obtain the actual cumulative workload within the sliding fixed time period; determine the holding time corresponding to the time value according to the ratio of the actual cumulative workload to the predicted cumulative workload; and the evaluation module is used to evaluate the overall maintenance quality according to the length of the holding time.

[0012] Furthermore, the cumulative workload prediction model is established based on the daily maintenance cumulative time and the corresponding daily maintenance cumulative workload, including: based on the daily maintenance cumulative time and the corresponding daily maintenance cumulative workload, the cumulative workload prediction model is established using a linear regression method or a linear weighted regression method.

[0013] Furthermore, after establishing the cumulative workload prediction model based on the daily maintenance cumulative time and the corresponding daily maintenance cumulative workload, the method also includes: optimizing the cumulative workload prediction model; and using the optimized cumulative workload prediction model to predict the corresponding predicted cumulative workload.

[0014] Furthermore, the cumulative workload prediction model is established based on the daily maintenance cumulative time and the corresponding daily maintenance cumulative workload using a linear regression method or a linear weighted regression method, including: dividing the daily maintenance cumulative time and the corresponding daily maintenance cumulative workload difference into a training set and a verification set; based on the training set, an initial cumulative workload prediction model is established using a linear regression method or a linear weighted regression method; the cumulative workload prediction model is optimized, including: verifying the accuracy of the initial cumulative workload prediction model based on the verification set; when the accuracy is greater than or equal to a preset accuracy, determining the initial cumulative workload prediction model as the optimized cumulative workload prediction model.

[0015] Furthermore, the optimization of the cumulative workload prediction model includes: when the accuracy is less than the preset accuracy, successively extending the daily maintenance cumulative time, and verifying the accuracy of the initial cumulative workload prediction model after each extension of the daily maintenance cumulative time, until the accuracy of the initial cumulative workload prediction model is greater than or equal to the preset accuracy, and using the initial cumulative workload prediction model after extending the daily maintenance cumulative time as the optimized cumulative workload prediction model.

[0016] Furthermore, evaluating the overall maintenance quality effect based on the length of the holding time includes: when the length of the holding time is less than the set time length, judging that the quality of the overall maintenance is poor; when the length of the holding time is greater than or equal to the set time length, judging that the quality of the overall maintenance is good.

[0017] A third aspect of the present invention provides a computer storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the above-mentioned method for evaluating the overall maintenance quality of a petrochemical plant.

[0018] Through the technical solution provided by the present invention, the present invention has at least the following technical effects:

[0019] The overall maintenance quality assessment method of the petrochemical device of the present invention is used to obtain the daily maintenance time and daily maintenance workload within the preset time period before the overall maintenance, and determine the daily maintenance cumulative workload corresponding to the daily maintenance cumulative time according to the daily maintenance cumulative time. A cumulative workload prediction model is established using the daily maintenance cumulative time and the corresponding daily maintenance cumulative workload. After the overall maintenance is completed, the predicted cumulative workload of the sliding fixed time period is predicted using the cumulative workload prediction model, and compared with the actual cumulative workload in the sliding fixed time period, the holding time corresponding to the day value is determined, and the overall maintenance quality is evaluated according to the length of the holding time.

[0020] The overall maintenance quality assessment method for petrochemical plants provided by the present invention can quickly assess the quality of the plant after overall maintenance, effectively guide the overall maintenance of the enterprise each time, and assist the enterprise in tracing the source and gradually controlling and reducing the workload of daily maintenance.

[0021] Other features and advantages of the present invention will be described in detail in the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 A flow chart of a method for evaluating the overall maintenance quality of a petrochemical plant provided by an embodiment of the present invention;

[0023] Figure 2 A schematic diagram of a petrochemical plant overall maintenance quality assessment system provided by an embodiment of the present invention.

[0024] Description of Reference Numerals

[0025] 201 - determination module, 202 - model building module, 203 - prediction module, 204 - evaluation module. DETAILED DESCRIPTION

[0026] The specific implementation of the embodiment of the present invention is described in detail below in conjunction with the accompanying drawings. It should be understood that the specific implementation described here is only used to illustrate and explain the embodiment of the present invention, and is not used to limit the embodiment of the present invention.

[0027] It should be noted that, in the absence of conflict, the embodiments of the present invention and the features in the embodiments may be combined with each other.

[0028] In the present invention, unless otherwise specified, directional words such as "up, down, top, bottom" are usually used with reference to the directions shown in the drawings or are used to describe the relative positional relationships of components in the vertical, perpendicular or gravity direction.

[0029] The present invention will be described in detail below with reference to the accompanying drawings and in conjunction with embodiments.

[0030] Example 1

[0031] Please refer to Figure 1 In a first aspect, the present invention provides a method for evaluating the overall maintenance quality of a petrochemical device, the method comprising the following steps: obtaining the daily maintenance time and daily maintenance workload within a preset time period before the overall maintenance, determining the daily maintenance cumulative workload corresponding to the daily maintenance cumulative time according to the daily maintenance cumulative time within the preset time period; establishing a cumulative workload prediction model according to the daily maintenance cumulative time and the corresponding daily maintenance cumulative workload; obtaining the time value and day value after the completion of the overall maintenance, respectively inputting the daily maintenance cumulative time corresponding to the time value and the day value into the cumulative workload prediction model, and predicting the predicted cumulative workload corresponding to the sliding fixed time period, wherein the time value is the sum of the day value calculated from the date of completion of this overall maintenance and the sliding fixed time period, expressed as: P=i+w, i=0, 1, 2, ···n; P is the time value; w is a positive integer representing the sliding fixed time period; i is the day value; obtaining the actual cumulative workload within the sliding fixed time period; determining the holding time corresponding to the time value according to the ratio of the actual cumulative workload to the predicted cumulative workload; and evaluating the overall maintenance quality according to the length of the holding time.

[0032] Specifically, in an implementation manner of the present invention, before overall maintenance, work application data for petrochemical equipment is exported through the enterprise work permit management system, a preset time period is selected from the data, and the daily maintenance time and daily maintenance workload of the petrochemical equipment within the preset time period are obtained. Starting from the first day of the preset time period, the accumulated daily maintenance workload is counted, and a cumulative workload prediction model is established using the accumulated time and the accumulated daily maintenance workload corresponding to the accumulated time.

[0033] After the overall maintenance of a petrochemical plant is completed, the daily maintenance workload will be greatly reduced. If the growth of the daily maintenance workload is compared after the overall maintenance, the accuracy of the evaluation will be affected. Therefore, in the embodiment of the present invention, the effect of the overall maintenance is judged according to the growth of the daily maintenance workload within a fixed time period after the overall maintenance. After the overall maintenance is completed, the operation application data of the petrochemical plant after the overall maintenance is obtained through the enterprise operation permit management system, and a sliding fixed time period w is set, such as w=7, which means taking 7 days, and the time value P and the day value i are determined, i=0, 1, 2, ···n, such as i=2, which means the second day after the overall maintenance, P=i+w=9, which means the ninth day after the overall maintenance, and according to the cumulative workload prediction model, the time value P is input respectively to predict the predicted cumulative workload corresponding to the time value P, and the day value i is input to predict the predicted cumulative workload corresponding to the day value, and the predicted cumulative workload within the sliding fixed time period w is obtained after subtraction.

[0034] Then, through the operation application data of the petrochemical unit, the actual operation cumulative amount corresponding to the time value P and the day value i is obtained respectively, and the actual operation cumulative amount within the sliding fixed time period w is obtained after subtraction. The ratio of the actual cumulative operation amount to the predicted cumulative operation amount is calculated. If the ratio of the actual cumulative operation amount to the predicted cumulative operation amount is less than or equal to the set value, such as the set value is 1.2, it means that the daily operation amount after the overall maintenance is the same as the daily operation amount before the overall maintenance or less than the daily operation amount before the overall maintenance, then the value of the day value i is increased, and the predicted operation cumulative amount after the increase is predicted again, and the actual cumulative operation amount after the increase is calculated. When the ratio of the actual cumulative operation amount to the predicted cumulative operation amount is greater than the set value, it means that the daily operation amount after the overall maintenance is higher than the daily operation amount before the overall maintenance, and the corresponding holding time T is determined, that is, T = i + w. The overall maintenance quality can be evaluated according to the length of the holding time.

[0035] The overall maintenance quality assessment method for petrochemical equipment provided by the present invention can quickly assess the quality of the equipment after overall maintenance, effectively guide the overall maintenance of the enterprise each time, and assist the enterprise to trace the source and gradually control and reduce the workload of daily maintenance.

[0036] Furthermore, the cumulative workload prediction model is established based on the daily maintenance cumulative time and the corresponding daily maintenance cumulative workload, including: based on the daily maintenance cumulative time and the corresponding daily maintenance cumulative workload, the cumulative workload prediction model is established using a linear regression method or a linear weighted regression method.

[0037] Specifically, in an embodiment of the present invention, after determining the cumulative time of daily maintenance and the corresponding cumulative workload of daily maintenance, a machine learning prediction method can be loaded to establish a cumulative workload prediction model. In an embodiment of the present application, at least a linear regression method or a linear weighted regression method can be used to establish a cumulative workload prediction model.

[0038] Furthermore, after establishing the cumulative workload prediction model based on the daily maintenance cumulative time and the corresponding daily maintenance cumulative workload, the method also includes: optimizing the cumulative workload prediction model; and using the optimized cumulative workload prediction model to predict the corresponding predicted cumulative workload.

[0039] Specifically, considering that the amount of data collected within a preset time period will affect the accuracy of the cumulative workload prediction model, and the daily maintenance workload of petrochemical equipment is random, it will also affect the accuracy of the cumulative workload prediction model. Therefore, in an embodiment of the present invention, after the cumulative workload prediction model is established, the cumulative workload prediction model is optimized, and then the optimized cumulative workload prediction model is used to predict the corresponding predicted cumulative workload.

[0040] The method for evaluating the overall maintenance quality of a petrochemical plant provided by the present invention can improve the accuracy of the cumulative workload prediction model and accurately evaluate the quality of overall maintenance.

[0041] Furthermore, the cumulative workload prediction model is established based on the daily maintenance cumulative time and the corresponding daily maintenance cumulative workload using a linear regression method or a linear weighted regression method, including: dividing the daily maintenance cumulative time and the corresponding daily maintenance cumulative workload difference into a training set and a verification set; based on the training set, an initial cumulative workload prediction model is established using a linear regression method or a linear weighted regression method; the cumulative workload prediction model is optimized, including: verifying the accuracy of the initial cumulative workload prediction model based on the verification set; when the accuracy is greater than or equal to a preset accuracy, determining the initial cumulative workload prediction model as the optimized cumulative workload prediction model.

[0042] Specifically, in an implementation manner of the present invention, the daily maintenance cumulative time and the corresponding daily maintenance cumulative workload are divided into a training set and a verification set according to a certain ratio, such as 90% or 80%. The training set is used to establish an initial cumulative workload prediction model, and the verification set is used to verify the accuracy of the initial cumulative workload prediction model. The cumulative time is input into the cumulative workload prediction model, and the corresponding daily maintenance cumulative time is predicted. The predicted time is compared with the actual daily maintenance cumulative workload. When the accuracy is greater than or equal to the preset accuracy, the initial cumulative workload prediction model is determined as the optimized cumulative workload prediction model.

[0043] The method for evaluating the overall maintenance quality of a petrochemical plant provided by the present invention can improve the accuracy of the cumulative workload prediction model and accurately evaluate the quality of overall maintenance.

[0044] Furthermore, the optimization of the cumulative workload prediction model includes: when the accuracy is less than the preset accuracy, successively extending the daily maintenance cumulative time, and verifying the accuracy of the initial cumulative workload prediction model after each extension of the daily maintenance cumulative time, until the accuracy of the initial cumulative workload prediction model is greater than or equal to the preset accuracy, and using the initial cumulative workload prediction model after extending the daily maintenance cumulative time as the optimized cumulative workload prediction model.

[0045] Specifically, in the embodiment of the present invention, when the accuracy is less than the preset accuracy, the length of the preset time period is extended, the daily maintenance cumulative time is increased, and the accuracy of the initial cumulative workload prediction model after the extension is calculated again. If it is still less than the preset accuracy, the daily maintenance cumulative time is extended again. The above steps are repeated until the accuracy of the initial cumulative workload prediction model is greater than or equal to the preset accuracy, and the initial cumulative workload prediction model after the daily maintenance cumulative time is extended is used as the optimized cumulative workload prediction model.

[0046] The overall maintenance quality assessment method for petrochemical plants provided by the present invention can expand the amount of initial data collected by the model, improve the accuracy of the cumulative workload prediction model, accurately assess the quality of overall maintenance, and effectively guide the overall maintenance of the enterprise each time.

[0047] Furthermore, evaluating the overall maintenance quality effect based on the length of the holding time includes: when the length of the holding time is less than the set time length, judging that the quality of the overall maintenance is poor; when the length of the holding time is greater than or equal to the set time length, judging that the quality of the overall maintenance is good.

[0048] Specifically, in the embodiment of the present invention, when the length of the holding time is less than the set time length, such as the holding time is less than 8 days, it means that the daily maintenance amount of the petrochemical device in less than 8 days is more than the amount of work before the overall maintenance, and the quality of the overall maintenance is judged to be poor. When the length of the holding time is greater than or equal to the set time length, such as greater than or equal to 8 days, it means that the overall maintenance can be maintained for a long time, and the quality of the overall maintenance is judged to be good.

[0049] The method for evaluating the overall maintenance quality of a petrochemical plant provided by the present invention can evaluate the quality of the overall maintenance according to the length of the maintenance time, so that the staff can effectively understand the effect of the overall maintenance and effectively guide the subsequent overall maintenance.

[0050] Please refer to Figure 2 According to a second aspect of the present invention, a system for evaluating the overall maintenance quality of a petrochemical device is provided. The system for evaluating the overall maintenance quality of a petrochemical device comprises: a determination module 201 for obtaining the daily maintenance time and the daily maintenance workload within a preset time period before the overall maintenance, and determining the daily maintenance cumulative workload corresponding to the daily maintenance cumulative time according to the daily maintenance cumulative time within the preset time period; a model establishment module 202 for establishing a cumulative workload prediction model according to the daily maintenance cumulative time and the corresponding daily maintenance cumulative workload; a prediction module 203 for obtaining the time value and the day value after the overall maintenance is completed, and respectively calculating the daily maintenance cumulative time and the daily maintenance cumulative workload corresponding to the time value and the day value. The cumulative workload prediction model is input during the period of time to predict the predicted cumulative workload corresponding to the sliding fixed time period, wherein the time value is the sum of the day value calculated from the date of completion of this overall maintenance and the sliding fixed time period, expressed as: P=i+w, i=0, 1, 2, ···n; P is the time value; w is a positive integer representing the sliding fixed time period; i is the day value; the determination module is also used to obtain the actual cumulative workload within the sliding fixed time period; according to the ratio of the actual cumulative workload to the predicted cumulative workload, determine the holding time corresponding to the time value; the evaluation module 204 is used to evaluate the overall maintenance quality according to the length of the holding time.

[0051] Furthermore, the cumulative workload prediction model is established based on the daily maintenance cumulative time and the corresponding daily maintenance cumulative workload, including: based on the daily maintenance cumulative time and the corresponding daily maintenance cumulative workload, the cumulative workload prediction model is established using a linear regression method or a linear weighted regression method.

[0052] Furthermore, after establishing the cumulative workload prediction model based on the daily maintenance cumulative time and the corresponding daily maintenance cumulative workload, the method also includes: optimizing the cumulative workload prediction model; and using the optimized cumulative workload prediction model to predict the corresponding predicted cumulative workload.

[0053] Furthermore, the cumulative workload prediction model is established based on the daily maintenance cumulative time and the corresponding daily maintenance cumulative workload using a linear regression method or a linear weighted regression method, including: dividing the daily maintenance cumulative time and the corresponding daily maintenance cumulative workload difference into a training set and a verification set; based on the training set, an initial cumulative workload prediction model is established using a linear regression method or a linear weighted regression method; the cumulative workload prediction model is optimized, including: verifying the accuracy of the initial cumulative workload prediction model based on the verification set; when the accuracy is greater than or equal to a preset accuracy, determining the initial cumulative workload prediction model as the optimized cumulative workload prediction model.

[0054] Furthermore, the optimization of the cumulative workload prediction model includes: when the accuracy is less than the preset accuracy, successively extending the daily maintenance cumulative time, and verifying the accuracy of the initial cumulative workload prediction model after each extension of the daily maintenance cumulative time, until the accuracy of the initial cumulative workload prediction model is greater than or equal to the preset accuracy, and using the initial cumulative workload prediction model after extending the daily maintenance cumulative time as the optimized cumulative workload prediction model.

[0055] Furthermore, evaluating the overall maintenance quality effect based on the length of the holding time includes: when the length of the holding time is less than the set time length, judging that the quality of the overall maintenance is poor; when the length of the holding time is greater than or equal to the set time length, judging that the quality of the overall maintenance is good.

[0056] A third aspect of the present invention provides a computer storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the above-mentioned method for evaluating the overall maintenance quality of a petrochemical plant.

[0057] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, the present invention will not further describe various possible combinations.

[0058] In addition, various embodiments of the present invention may be arbitrarily combined, and as long as they do not violate the concept of the present invention, they should also be regarded as the contents disclosed by the present invention.

Claims

1. A method for evaluating the overall maintenance quality of a petrochemical plant, characterized in that: The overall maintenance quality assessment method of the petrochemical plant comprises: Obtaining the daily maintenance time and daily maintenance workload within a preset time period before the overall maintenance, and determining the daily maintenance cumulative workload corresponding to the daily maintenance cumulative time according to the daily maintenance cumulative time within the preset time period; Establishing a cumulative workload prediction model based on the daily maintenance cumulative time and the corresponding daily maintenance cumulative workload; The time value and day value after the completion of the overall maintenance are obtained, and the daily maintenance cumulative time corresponding to the time value and day value are respectively input into the cumulative workload prediction model to predict the predicted cumulative workload corresponding to the sliding fixed time period, where the time value is the sum of the day value calculated from the date of completion of this overall maintenance and the sliding fixed time period, expressed as: P=i+w, i=0, 1, 2, ... n; P is the time value; w is a positive integer representing the sliding fixed time period; i is the day value; Obtaining the actual cumulative workload within the sliding fixed time period; Determining a holding time corresponding to the time value according to a ratio of the actual cumulative workload to the predicted cumulative workload; The overall maintenance quality is evaluated based on the length of the holding time.

2. The method for evaluating the overall maintenance quality of a petrochemical plant according to claim 1, characterized in that: The method of establishing a cumulative workload prediction model based on the daily maintenance cumulative time and the corresponding daily maintenance cumulative workload includes: According to the daily maintenance cumulative time and the corresponding daily maintenance cumulative workload, the cumulative workload prediction model is established by using a linear regression method or a linear weighted regression method.

3. The method for evaluating the overall maintenance quality of a petrochemical plant according to claim 2, characterized in that: After the cumulative daily maintenance workload prediction model is established according to the daily maintenance cumulative time and the corresponding daily maintenance cumulative workload, the following further comprises: Optimizing the cumulative workload prediction model; The optimized cumulative workload prediction model is used to predict the corresponding predicted cumulative workload.

4. The method for evaluating the overall maintenance quality of a petrochemical plant according to claim 3, characterized in that: The cumulative workload prediction model is established by using a linear regression method or a linear weighted regression method according to the daily maintenance cumulative time and the corresponding daily maintenance cumulative workload, including: Divide the daily maintenance cumulative time and the corresponding daily maintenance cumulative workload difference into a training set and a verification set; According to the training set, a linear regression method or a linear weighted regression method is used to establish an initial cumulative workload prediction model; The optimizing the cumulative workload prediction model includes: Verifying the accuracy of the initial cumulative workload prediction model according to the verification set; When the accuracy is greater than or equal to a preset accuracy, the initial cumulative workload prediction model is determined as the optimized cumulative workload prediction model.

5. The method for evaluating the overall maintenance quality of a petrochemical plant according to claim 4, characterized in that: The optimizing the cumulative workload prediction model includes: When the accuracy is less than the preset accuracy, the daily maintenance cumulative time is extended sequentially, and the accuracy of the initial cumulative workload prediction model after each extension of the daily maintenance cumulative time is verified until the accuracy of the initial cumulative workload prediction model is greater than or equal to the preset accuracy. The initial cumulative workload prediction model after the extension of the daily maintenance cumulative time is used as the optimized cumulative workload prediction model.

6. The method for evaluating the overall maintenance quality of a petrochemical plant according to claim 5, characterized in that: The evaluating the effect of the overall maintenance quality according to the length of the holding time includes: When the holding time is shorter than the set time, it is determined that the quality of the overall maintenance is poor; When the length of the holding time is greater than or equal to the set time length, it is determined that the quality of the overall maintenance is good.

7. A petrochemical plant overall maintenance quality assessment system, characterized in that: The overall maintenance quality assessment system of the petrochemical plant includes: A determination module, used to obtain the daily maintenance time and the daily maintenance workload within a preset time period before the overall maintenance, and determine the daily maintenance cumulative workload corresponding to the daily maintenance cumulative time according to the daily maintenance cumulative time within the preset time period; A model building module, used to build a cumulative workload prediction model according to the daily maintenance cumulative time and the corresponding daily maintenance cumulative workload; The prediction module is used to obtain the time value and the day value after the overall maintenance is completed, and input the daily maintenance cumulative time corresponding to the time value and the day value into the cumulative workload prediction model respectively, and predict the predicted cumulative workload corresponding to the sliding fixed time period, wherein the time value is the sum of the day value calculated from the date of completion of the overall maintenance and the sliding fixed time period, expressed as: P=i+w, i=0, 1, 2, ... n; P is the time value; w is a positive integer representing the sliding fixed time period; i is the day value; The determination module is further used to obtain an actual accumulated workload within the sliding fixed time period; determine a holding time corresponding to the time value according to a ratio of the actual accumulated workload to the predicted accumulated workload; An evaluation module is used to evaluate the overall maintenance quality according to the length of the holding time.

8. The overall maintenance quality assessment system for petrochemical plants according to claim 7, characterized in that: The method of establishing a cumulative workload prediction model based on the daily maintenance cumulative time and the corresponding daily maintenance cumulative workload includes: According to the daily maintenance cumulative time and the corresponding daily maintenance cumulative workload, the cumulative workload prediction model is established by using a linear regression method or a linear weighted regression method.

9. The petrochemical plant overall maintenance quality assessment system according to claim 8, characterized in that: After the cumulative daily maintenance workload prediction model is established according to the daily maintenance cumulative time and the corresponding daily maintenance cumulative workload, the following further comprises: Optimizing the cumulative workload prediction model; The optimized cumulative workload prediction model is used to predict the corresponding predicted cumulative workload.

10. The petrochemical plant overall maintenance quality assessment system according to claim 9, characterized in that: The cumulative workload prediction model is established by using a linear regression method or a linear weighted regression method according to the daily maintenance cumulative time and the corresponding daily maintenance cumulative workload, including: Divide the daily maintenance cumulative time and the corresponding daily maintenance cumulative workload difference into a training set and a verification set; According to the training set, a linear regression method or a linear weighted regression method is used to establish an initial cumulative workload prediction model; The optimizing the cumulative workload prediction model includes: Verifying the accuracy of the initial cumulative workload prediction model according to the verification set; When the accuracy is greater than or equal to a preset accuracy, the initial cumulative workload prediction model is determined as the optimized cumulative workload prediction model.

11. The petrochemical plant overall maintenance quality assessment system according to claim 10, characterized in that: The optimizing the cumulative workload prediction model includes: When the accuracy is less than the preset accuracy, the daily maintenance cumulative time is extended sequentially, and the accuracy of the initial cumulative workload prediction model after each extension of the daily maintenance cumulative time is verified until the accuracy of the initial cumulative workload prediction model is greater than or equal to the preset accuracy. The initial cumulative workload prediction model after the extension of the daily maintenance cumulative time is used as the optimized cumulative workload prediction model.

12. The petrochemical plant overall maintenance quality assessment system according to claim 11, characterized in that: The evaluating the effect of the overall maintenance quality according to the length of the holding time includes: When the holding time is shorter than the set time, it is determined that the quality of the overall maintenance is poor; When the length of the holding time is greater than or equal to the set time length, it is determined that the quality of the overall maintenance is good.

13. A computer storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for evaluating the overall maintenance quality of a petrochemical plant as described in any one of claims 1 to 6 is implemented.

Images