Method and system for evaluating in-service risk of rotating equipment

Abstract

The invention discloses a method and system for evaluating the in-service risk of rotating equipment, and the method comprises the steps: respectively obtaining the correlation between each type of inherent characteristics and the severity of a first risk caused by each type of inherent characteristics, and the correlation between each type of operation characteristics and the severity of a second risk caused by each type of operation characteristics for different types of rotating equipment; thereby establishing different scoring criteria for describing the intrinsic characteristic relative to the first risk severity and the operating characteristic relative to the second risk severity; obtaining the correlation between the operation management characteristics of different types of rotating equipment and the influence of the operation management characteristics on the severity of various risks, thereby forming a correction coefficient matrix for correcting various risk scores; and analyzing the first score, the second score and the correction coefficient of the to-be-assessed equipment according to the actual inherent characteristics, the operation characteristics and the operation management characteristics of the to-be-assessed equipment based on each scoring standard and the correction coefficient matrix, thereby generating a risk assessment result. According to the invention, accurate evaluation of the in-service risk of the rotating equipment is realized.

Description

Technical Field

[0001] The present invention belongs to the technical field of equipment risk assessment, and in particular, relates to a method and system for assessing the in-service risk of rotating equipment. Background Art

[0002] Nowadays, with the expansion of the application scope of rotating equipment, it is particularly important to ensure the safe operation of rotating equipment.

[0003] The prior art discloses a risk assessment system based on main grid fault analysis, which relates to the technical field of risk assessment systems, including: a main grid environment monitoring system, wherein the main grid environment monitoring system is connected to a risk assessment calculation system for wireless data transmission, the risk assessment calculation system is connected to a risk assessment comparison system for data transmission, and the risk assessment comparison system is connected to a risk assessment confirmation system for data transmission. The system can monitor the personnel responsible for risk assessment and avoid delays in the preparation of risk protection measures if the corresponding personnel responsible for risk assessment fail to observe the risk assessment data within the prescribed time to conduct corresponding risk assessments and prepare corresponding risk prevention measures. Once a power grid failure occurs, the delay in risk prevention measures will cause large economic losses.

[0004] The prior art discloses a risk assessment method, device and storage medium thereof, the method comprising: receiving an identification code of a mobile device from a terminal device; obtaining installation and use information of an application corresponding to the identification code and generating category information of the application; generating a risk assessment level corresponding to the identification code based on the installation and use information and category information of the application, and sending the risk assessment level to the terminal device. The method categorizes and profiles the application of a user applying for a credit based on the above information, and performs multi-dimensional profiling based on the financial consumption habits of the user applying for a credit, and can obtain accurate assessment results of the credit and fraud risks of the user applying for a credit.

[0005] In addition, the prior art also discloses a risk identification method, a risk identification device and a computer system for mobile devices, the method comprising: obtaining device data of the mobile device to be tested; determining a device fingerprint identifier based on the device data; performing a first match between the device fingerprint identifier and a device blacklist to obtain a first matching result; if the first matching result is successful, determining that the mobile device to be tested has a risk; and, if the first matching result is a failure, processing the device data using a device risk assessment model to determine whether the mobile device to be tested has a risk.

[0006] Based on the analysis of existing technologies and the actual operation of rotating equipment in the industry, the methods used in the industry to evaluate rotating equipment risks (or similar content) mainly include the following types:

[0007] (1) Reliability-centered maintenance (RCM). RCM is a method for making decisions on equipment maintenance based on reliability theory and through failure mode and effects analysis (FMEA). Since rotating equipment has more parts and more opportunities for maintenance than static equipment, RCM is usually used for risk assessment. In the process of using RCM for risk assessment, it is necessary to first conduct a failure mode and effects analysis (FMEA) to obtain all possible failure modes and effects of the equipment, and then make maintenance decisions based on the results of FMEA. In other words, its essence is to control failures with higher risks (consequences), so it can also be regarded as a risk assessment method.

[0008] (2) Conventional risk assessment methods do not distinguish between equipment. They usually conduct risk assessment based on a risk matrix, rely on relatively vague judgment conditions to evaluate a certain event (failure, malfunction), and then derive the risk of the equipment through various risks. The evaluation results are relatively vague.

[0009] (3) Targeted risk assessments for a specific device or activity are usually more specific, the process is relatively simple, and the implementation methods are not uniform. Therefore, the evaluation results are usually not universal and representative.

[0010] In summary, the existing technology requires high professional experience of the assessors when conducting risk assessment on equipment, and the evaluation rules are difficult for non-professional assessors to grasp and are not clear and convenient enough. In addition, the complex evaluation process (RCM) is difficult to operate, while the evaluation results obtained by the overly simple evaluation process (risk matrix) are unreliable, and different people may produce different results using the same method. Summary of the invention

[0011] In order to solve the above problems, an embodiment of the present invention provides a method for evaluating the in-service risks of rotating equipment, including: for different types of rotating equipment, respectively obtaining the correlation between each type of inherent characteristics and the severity of the first risk caused by it, and the correlation between each type of operating characteristics and the severity of the second risk caused by it, so as to establish a first scoring standard for describing the severity of the inherent characteristics relative to the first risk, and a second scoring standard for describing the severity of the operating characteristics relative to the second risk; obtaining the correlation between the operating management characteristics of different types of rotating equipment and their impact on the severity of each type of risk, so as to form a correction coefficient matrix for correcting each risk score; based on each scoring standard and the correction coefficient matrix, according to the actual inherent characteristics, operating characteristics and operating management characteristics of the equipment to be evaluated, the first score, the second score and the correction coefficient of the equipment to be evaluated are analyzed, so as to generate a risk assessment result.

[0012] Preferably, the inherent characteristics include but are not limited to: supply stability, equipment complexity coefficient, standby status, maintenance complexity, power and load matching; the operating characteristics include but are not limited to: production importance, medium hazard, equipment newness coefficient, process fluctuation, equipment switching interval and mean time between failures; and the operating management characteristics include but are not limited to: preventive work management coefficient, equipment operating status perception coefficient, management redundancy coefficient and fault cause management coefficient.

[0013] Preferably, in the process of collecting each type of inherent characteristics, it includes: the supply stability is obtained according to the maturity of the rotating equipment; the equipment complexity coefficient is obtained according to the structural complexity of the rotating equipment; the standby condition is obtained according to the number of standby machines of the rotating equipment; the maintenance complexity is obtained according to the maintenance complexity of the rotating equipment; the power is obtained according to the rated power of the rotating equipment; and the load matching is obtained according to the load matching compliance of the rotating equipment.

[0014] Preferably, in the process of collecting each type of operating characteristics, it includes: the production importance is obtained according to the degree of failure of other equipment in the device caused by the failure of the rotating equipment; the medium hazard is obtained according to the toxicity and flammability of the medium carried by the rotating equipment; the equipment newness coefficient is obtained according to the service life of the rotating equipment; the process fluctuation is obtained according to the influence of the current process on the load of the rotating equipment; the equipment switching interval is obtained according to the length of the regular switching interval of the rotating equipment; and the mean time between failures is obtained according to the actual maintenance cycle of the rotating equipment.

[0015] Preferably, in the process of collecting the operation management characteristics, it includes: the preventive work management coefficient is obtained according to the strategy formulation status of the preventive work of the rotating equipment; the equipment operation status perception coefficient is obtained according to the operation status monitoring method of the rotating equipment; the management redundancy coefficient is obtained according to the configuration status of the management personnel of the rotating equipment; and the fault cause management coefficient is obtained according to the degree of understanding of the fault cause of the rotating equipment.

[0016] Preferably, the step of analyzing the first score of the current equipment includes: scoring the supply stability, the equipment complexity coefficient, the standby condition, the maintenance complexity, the power and the load matching in the actual inherent characteristics according to the first scoring standard, and configuring a corresponding weight for each scoring result according to the importance of each inherent characteristic, and using a weighted algorithm to obtain the first score, wherein the weight of the supply stability is 0.1, the weight of the equipment complexity coefficient is 0.3, the weight of the standby condition is 0.3, the weight of the maintenance complexity is 0.2, the weight of the power is 0.05, and the weight of the load matching is 0.05.

[0017] Preferably, the step of analyzing the second score of the current equipment includes: scoring the production importance, the medium hazard, the equipment newness coefficient, the process fluctuation, the equipment switching interval and the mean time between failures in the actual operating characteristics according to the second scoring standard, and configuring a corresponding weight for each scoring result according to the importance of each operating characteristic, and using a weighted algorithm to obtain the second score, wherein the weight of the production importance is 0.2, the weight of the medium hazard is 0.3, the weight of the equipment newness coefficient is 0.2, the weight of the process fluctuation is 0.1, the weight of the equipment switching interval is 0.1, and the weight of the mean time between failures is 0.1.

[0018] Preferably, the first score is calculated using the following expression:

[0019] R1=0.1D1+0.3D2+0.3D3+0.2D4+0.05D5+0.05D6

[0020] Among them, R1 represents the first score, D1 represents supply stability, D2 represents equipment complexity coefficient, D3 represents standby status, D4 represents maintenance complexity, D5 represents power, and D6 represents load matching.

[0021] Preferably, the second score is calculated using the following expression:

[0022] R2=0.2D′1+0.3D′2+0.2D′3+0.1D′4+0.1D′5+0.1D′6

[0023] Among them, R2 represents the second score, D′1 represents production importance, D′2 represents medium hazard, D′3 represents equipment newness coefficient, D′4 represents process fluctuation, D′5 represents equipment switching interval, and D′6 represents mean time between failures.

[0024] Preferably, the correction coefficient matrix is ​​calculated using the following expression:

[0025] M′=F1·F2·F3·F4

[0026] Among them, M′ represents a single correction coefficient in the correction coefficient matrix, F1 represents the preventive work management coefficient, F2 represents the equipment operation status perception coefficient, F3 represents the management redundancy coefficient, and F4 represents the fault cause management coefficient.

[0027] Preferably, the risk assessment result is obtained using the following expression:

[0028] R=(R1+R2)·M

[0029] Wherein, R represents the total risk score, R1 represents the first score, R2 represents the second score, and M represents the correction factor of the rotating equipment to be evaluated.

[0030] On the other hand, the present invention also provides a system for evaluating the in-service risks of rotating equipment, the system comprising the following modules: a scoring standard formulation module, which is used to obtain, for different types of rotating equipment, the correlation between each type of inherent characteristics and the severity of the first risk caused by it, and the correlation between each type of operating characteristics and the severity of the second risk caused by it, thereby establishing a first scoring standard for describing the inherent characteristics relative to the severity of the first risk, and a second scoring standard for describing the operating characteristics relative to the severity of the second risk; a correction coefficient matrix generation module, which is used to obtain the correlation between the operating management characteristics of different types of rotating equipment and their impact on the severity of each type of risk, thereby forming a correction coefficient matrix for correcting each risk score; a risk assessment module, which is used to analyze the first score, second score and correction coefficient of the equipment to be evaluated based on each scoring standard and the correction coefficient matrix, according to the actual inherent characteristics, operating characteristics and operating management characteristics of the equipment to be evaluated, thereby generating a risk assessment result.

[0031] Compared with the prior art, one or more embodiments of the above scheme may have the following advantages or beneficial effects:

[0032] The present invention proposes a method and system for evaluating the in-service risk of rotating equipment. The method is a semi-quantitative evaluation method, which comprehensively determines the in-service risk of the rotating equipment to be evaluated based on the inherent risk and operation risk of the rotating equipment. First, for different types of rotating equipment, the correlation between each type of inherent characteristics and the first risk severity caused by it, and each type of operation characteristics and the second risk severity caused by it are respectively obtained, so as to establish different scoring standards for describing the inherent characteristics relative to the first risk severity and the operation characteristics relative to the second risk severity; then, for different types of rotating equipment, the correlation between the operation management characteristics of different types of rotating equipment and their influence on the severity of each type of risk is obtained, so as to form a correction coefficient matrix for correcting each risk score; finally, based on the established scoring standards and the formed correction coefficient matrix, according to the actual inherent characteristics, operation characteristics and operation management characteristics of the current equipment to be evaluated, the first score, the second score and the correction coefficient of the equipment to be evaluated are analyzed, so as to generate the risk assessment result of the current equipment. The present invention is mainly used to evaluate the in-service risk of rotating equipment in the petrochemical industry, has the convenience of easy operation, and obtains accurate in-service risk assessment results of rotating equipment.

[0033] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the description, claims and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0035] Figure 1 It is a step diagram of a method for evaluating in-service risks of rotating equipment according to an embodiment of the present application.

[0036] Figure 2 It is a schematic diagram of the overall structure of a system for evaluating the in-service risk of rotating equipment according to an embodiment of the present application. DETAILED DESCRIPTION

[0037] The following will describe the implementation methods of the present invention in detail with reference to the accompanying drawings and embodiments, so that the implementation process of how the present invention applies technical means to solve technical problems and achieve technical effects can be fully understood and implemented accordingly. It should be noted that as long as there is no conflict, the various embodiments of the present invention and the various features in the embodiments can be combined with each other, and the technical solutions formed are all within the protection scope of the present invention.

[0038] In addition, the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be performed in an order different from that shown here.

[0039] Nowadays, with the expansion of the application scope of rotating equipment, it is particularly important to ensure the safe operation of rotating equipment.

[0040] The prior art discloses a risk assessment system based on main grid fault analysis, which relates to the technical field of risk assessment systems, including: a main grid environment monitoring system, wherein the main grid environment monitoring system is connected to a risk assessment calculation system for wireless data transmission, the risk assessment calculation system is connected to a risk assessment comparison system for data transmission, and the risk assessment comparison system is connected to a risk assessment confirmation system for data transmission. The system can monitor the personnel responsible for risk assessment and avoid delays in the preparation of risk protection measures if the corresponding personnel responsible for risk assessment fail to observe the risk assessment data within the prescribed time to conduct corresponding risk assessments and prepare corresponding risk prevention measures. Once a power grid failure occurs, the delay in risk prevention measures will cause large economic losses.

[0041] The prior art discloses a risk assessment method, device and storage medium thereof, the method comprising: receiving an identification code of a mobile device from a terminal device; obtaining installation and use information of an application corresponding to the identification code and generating category information of the application; generating a risk assessment level corresponding to the identification code based on the installation and use information and category information of the application, and sending the risk assessment level to the terminal device. The method categorizes and profiles the application of a user applying for a credit based on the above information, and performs multi-dimensional profiling based on the financial consumption habits of the user applying for a credit, and can obtain accurate assessment results of the credit and fraud risks of the user applying for a credit.

[0042] In addition, the prior art also discloses a risk identification method, a risk identification device and a computer system for mobile devices, the method comprising: obtaining device data of the mobile device to be tested; determining a device fingerprint identifier based on the device data; performing a first match between the device fingerprint identifier and a device blacklist to obtain a first matching result; if the first matching result is successful, determining that the mobile device to be tested has a risk; and, if the first matching result is a failure, processing the device data using a device risk assessment model to determine whether the mobile device to be tested has a risk.

[0043] Based on the analysis of existing technologies and the actual operation of rotating equipment in the industry, the methods used in the industry to evaluate rotating equipment risks (or similar content) mainly include the following types:

[0044] (1) Reliability-centered maintenance (RCM). RCM is a method for making decisions on equipment maintenance based on reliability theory and through failure mode and effects analysis (FMEA). Since rotating equipment has more parts and more opportunities for maintenance than static equipment, RCM is usually used for risk assessment. In the process of using RCM for risk assessment, it is necessary to first conduct a failure mode and effects analysis (FMEA) to obtain all possible failure modes and effects of the equipment, and then make maintenance decisions based on the results of FMEA. In other words, its essence is to control failures with higher risks (consequences), so it can also be regarded as a risk assessment method.

[0045] (2) Conventional risk assessment methods do not distinguish between equipment. They usually conduct risk assessment based on a risk matrix, rely on relatively vague judgment conditions to evaluate a certain event (failure, malfunction), and then derive the risk of the equipment through various risks. The evaluation results are relatively vague.

[0046] (3) Targeted risk assessments for a specific device or activity are usually more specific, the process is relatively simple, and the implementation methods are not uniform. Therefore, the evaluation results are usually not universal and representative.

[0047] In summary, the existing technology requires high professional experience of the assessors when conducting risk assessment on equipment, and the evaluation rules are difficult for non-professional assessors to grasp and are not clear and convenient enough. In addition, the complex evaluation process (RCM) is difficult to operate, while the evaluation results obtained by the overly simple evaluation process (risk matrix) are unreliable, and different people may produce different results using the same method.

[0048] Therefore, in order to solve the above problems, the embodiment of the present invention proposes a method and system for evaluating the in-service risk of rotating equipment. The method is a semi-quantitative evaluation method, which comprehensively determines the in-service risk of the rotating equipment to be evaluated based on the inherent risk and operation risk of the rotating equipment. First, for different types of rotating equipment, the correlation between each type of inherent characteristics and the first risk severity caused by it, and each type of operation characteristics and the second risk severity caused by it are respectively obtained, so as to establish different scoring standards for describing the inherent characteristics relative to the first risk severity and the operation characteristics relative to the second risk severity; then, for different types of rotating equipment, the correlation between the operation management characteristics of different types of rotating equipment and their influence on the severity of each type of risk is obtained, so as to form a correction coefficient matrix for correcting each risk score; finally, based on the established scoring standards and the formed correction coefficient matrix, according to the actual inherent characteristics, operation characteristics and operation management characteristics of the current equipment to be evaluated, the first score, the second score and the correction coefficient of the equipment to be evaluated are analyzed, so as to generate the risk assessment result of the current equipment. The present invention is mainly used to evaluate the in-service risk of rotating equipment in the petrochemical industry, has the convenience of easy operation, and obtains accurate in-service risk assessment results of rotating equipment.

[0049] Embodiment 1

[0050] According to the equipment characteristics related to the in-service risks of rotating equipment, the present invention divides the factors affecting the severity of the in-service risks of rotating equipment into inherent characteristics, operating characteristics and operation management characteristics, and establishes evaluation standards for describing the severity of the risks associated with corresponding characteristics based on the inherent characteristics, operating characteristics and operation management characteristics, so as to achieve accurate evaluation of the in-service risks of rotating equipment.

[0051] Figure 1 is a step diagram of a method for evaluating the in-service risk of rotating equipment according to an embodiment of the present application. Figure 1 To illustrate the various steps of this method.

[0052] like Figure 1 As shown, in step S110, for different types of rotating equipment, the correlation between each type of inherent characteristic and the severity of the first risk caused by it, and the correlation between each type of operating characteristic and the severity of the second risk caused by it are obtained respectively, so as to establish a first scoring standard for describing the severity of the inherent characteristic relative to the first risk, and a second scoring standard for describing the severity of the operating characteristic relative to the second risk.

[0053] Specifically, for different types of rotating equipment, the inherent characteristics, operating characteristics and the operating management characteristics described below of each device regarding the severity of the risk are determined. Then, the severity of the first risk caused by each type of inherent characteristics is divided into multiple levels according to the severity, and the severity of the corresponding first risk is characterized by the inherent characteristics corresponding to each level, so as to obtain the correlation between each type of inherent characteristics and the severity of the first risk caused by it. Then, according to the scoring standard that the higher the severity of the first risk, the higher the score, the scores are respectively given to each type of inherent characteristics corresponding to each level to quantify the severity of the first risk, and a first scoring standard for describing the inherent characteristics relative to the severity of the first risk is established as shown in Table 1.

[0054] Table 1 Inherent risk assessment table

[0055]

[0056]

[0057] Next, the severity of the second risk caused by each type of operating characteristic is divided into multiple levels according to the severity, and the severity of the corresponding second risk is characterized by the operating characteristics corresponding to each level, so as to obtain the correlation between each type of operating characteristic and the severity of the second risk caused by it. Then, according to the scoring standard that the higher the severity of the second risk, the higher the score, the various types of operating characteristics corresponding to each level are scored respectively to quantify the severity of the second risk, and establish the second scoring standard for describing the operating characteristics relative to the severity of the second risk as shown in Table 2.

[0058] Table 2 Operational risk assessment table

[0059]

[0060]

[0061] Further, after establishing the first scoring standard and the second scoring standard, in step S120, the correlation between the operation management characteristics of different types of rotating equipment and their impact on the severity of each type of risk is obtained, thereby forming a correction coefficient matrix for correcting the scores of each risk. In the embodiment of the present application, the impact of the operation management characteristics of different types of rotating equipment on the first risk severity and the second risk severity is divided into multiple levels, and the operation management characteristics corresponding to each level are used to characterize the corresponding impact on the first risk severity, and the corresponding impact on the second risk severity, so as to obtain the correlation between the operation management characteristics of different types of rotating equipment and their impact on the severity of each type of risk. Then, the greater the impact, the higher the score, and the operation management characteristics corresponding to each level are scored separately to quantify the impact on the severity of each type of risk, and the equipment management coefficient value standard shown in Table 3 is formed, thereby forming a correction coefficient matrix for correcting the scores of each risk.

[0062] Table 3 Equipment management coefficient value standard

[0063]

[0064] In the embodiment of the present application, inherent risk is the risk caused by the rotating equipment itself due to factors such as structure and process flow position, which is related to the inherent characteristics of the rotating equipment and usually does not change with the service cycle and operation. Inherent characteristics include but are not limited to: supply stability, equipment complexity coefficient, standby machine situation, maintenance complexity, power and load matching. Operation risk is a comprehensive consideration of various risks generated by the rotating equipment during operation, which is related to the use and working environment of the rotating equipment and will change with the service cycle and operation. Operation characteristics include but are not limited to: production importance, medium hazard, equipment newness coefficient, process fluctuation, equipment switching interval and mean time between failures. Operation management characteristics are related to the management of the rotating equipment, and are a comprehensive consideration of the impact of auxiliary systems, professional management and related systems on the severity of risks during the operation of the rotating equipment to correct the severity of the risks of the in-service equipment. Operation management characteristics include but are not limited to: preventive work management coefficient, equipment operation status perception coefficient, management redundancy coefficient and fault cause management coefficient.

[0065] In the process of collecting each type of inherent characteristics, supply stability is obtained according to the maturity of the rotating equipment; the equipment complexity coefficient is obtained according to the structural complexity of the rotating equipment; the standby condition is obtained according to the number of standby machines of the rotating equipment; the maintenance complexity is obtained according to the maintenance complexity of the rotating equipment; the power is obtained according to the rated power of the rotating equipment; and the load matching is obtained according to the load matching compliance of the rotating equipment. In the embodiment of the present application, supply stability is obtained by taking values ​​of the maturity of the rotating equipment; the equipment complexity coefficient is obtained by taking values ​​of the structural complexity of the rotating equipment; the standby condition is obtained by taking values ​​of the existing standby condition of the rotating equipment; the maintenance complexity is obtained by taking values ​​of the maintenance complexity of the rotating equipment; the power is directly obtained according to the rated power of the rotating equipment; and the load matching is obtained by taking values ​​of the load matching condition of the rotating equipment.

[0066] In the process of collecting each type of operating characteristics, production importance is obtained according to the degree of failure of other equipment in the device caused by the failure of the rotating equipment; medium hazard is obtained according to the toxicity and flammability of the medium carried by the rotating equipment; the equipment newness coefficient is obtained according to the service life of the rotating equipment; process fluctuation is obtained according to the degree of influence of the current process on the load of the rotating equipment; the equipment switching interval is obtained according to the duration of the regular switching interval of the rotating equipment; and the mean time between failures is obtained according to the actual maintenance cycle of the rotating equipment. In the embodiment of the present application, production importance is obtained by taking values ​​of the subsequent consequences of the device caused by the failure of the rotating equipment; medium hazard is obtained by taking values ​​of the toxicity and flammability of the medium carried by the rotating equipment; the equipment newness coefficient is obtained by taking values ​​of the service life of the rotating equipment; process fluctuation is obtained by taking values ​​of the influence of the process (production) on the load of the rotating equipment; the equipment switching interval is obtained by taking values ​​of the duration of the regular switching interval of the rotating equipment; and the mean time between failures is obtained by taking values ​​of the actual maintenance cycle of the rotating equipment.

[0067] In the process of collecting operation management characteristics, the preventive work management coefficient is obtained according to the strategy formulation status of the preventive work of the rotating equipment; the equipment operation state perception coefficient is obtained according to the operation state monitoring method of the rotating equipment; the management redundancy coefficient is obtained according to the configuration status of the management personnel of the rotating equipment; and the fault cause management coefficient is obtained according to the degree of understanding of the fault cause of the rotating equipment. In the embodiment of the present application, the preventive work management coefficient is obtained by taking the value of the implementation of the preventive work of the rotating equipment; the equipment operation state perception coefficient is obtained by taking the value of the state monitoring system and full-time personnel of the rotating equipment; the management redundancy coefficient is obtained by taking the value of the manpower invested in equipment management by the enterprise; and the fault cause management coefficient is obtained by taking the value of the enterprise fault improvement mechanism of the rotating equipment.

[0068] In the embodiment of the present application, the correction coefficient matrix is ​​calculated using the following expression:

[0069] M′=F1·F2·F3·F4 (1)

[0070] Among them, M′ represents a single correction coefficient in the correction coefficient matrix, F1 represents the preventive work management coefficient, F2 represents the equipment operation status perception coefficient, F3 represents the management redundancy coefficient, and F4 represents the fault cause management coefficient.

[0071] Further, in step S130, based on each scoring standard and the correction coefficient matrix, according to the actual inherent characteristics, operating characteristics and operation management characteristics of the equipment to be evaluated, the first score, the second score and the correction coefficient of the equipment to be evaluated are analyzed, so as to generate a risk assessment result. Specifically, after obtaining the aforementioned first scoring standard, the second scoring standard and the correction coefficient matrix, the present embodiment first determines the actual inherent characteristics, operating characteristics and operation management characteristics of the equipment to be evaluated, and then analyzes the first score of the current equipment according to the first scoring standard, analyzes the second score of the current equipment according to the second scoring standard, and analyzes the correction coefficient of the current equipment according to the correction coefficient matrix. Finally, the total risk score characterizing the current equipment to be evaluated is calculated using the first score, the second score and the correction coefficient of the current equipment to be evaluated, and the risk state corresponding to the total risk score is generated as the risk assessment result. Accordingly, the present invention calculates the total risk score of the rotating equipment based on the constructed scoring standard and the formed correction coefficient matrix, which reduces the experience and ability requirements of the risk assessment personnel. Even non-professionals can carry out risk assessment according to the prompts without subjective judgment or deep technical experience requirements. That is to say, the evaluation method disclosed in the present invention does not require high technical experience. If the developed information program is used, the standardized risk evaluation of rotating equipment can be conveniently and quickly performed. Moreover, if the equipment itself does not change, the evaluation result will not change with the change of the evaluator. Furthermore, if the equipment information is improved in advance according to the rules, the system can also realize automatic evaluation.

[0072] In the step of analyzing the first score of the current equipment, according to the first scoring standard, the supply stability, equipment complexity coefficient, standby machine situation, maintenance complexity, power and load matching in the actual inherent characteristics are scored respectively, and according to the importance of each inherent characteristic, a corresponding weight is configured for each scoring result, and a weighted algorithm is used to obtain a first score. In the embodiment of the present application, based on the actual inherent characteristics of the current equipment to be evaluated, according to the first scoring standard, the supply stability, equipment complexity coefficient, standby machine situation, maintenance complexity, power and load matching in the current actual inherent characteristics are scored respectively. Since the supply stability, equipment complexity coefficient, standby machine situation, maintenance complexity, power and load matching have different severity levels of the risks caused. Therefore, after obtaining the scoring results of supply stability, equipment complexity coefficient, standby machine situation, maintenance complexity, power and load matching, according to the importance of each inherent characteristic (that is, the severity of the risk caused by each inherent characteristic), a corresponding weight is configured for each scoring result, so as to calculate the first score using a weighted algorithm. It can be seen that the present invention fully considers the importance of different inherent characteristics, and the first score obtained is more objective, which lays a foundation for accurately evaluating the in-service risk of rotating equipment. Among them, the weight of supply stability is 0.1, the weight of equipment complexity coefficient is 0.3, the weight of standby condition is 0.3, the weight of maintenance complexity is 0.2, the weight of power is 0.05, and the weight of load matching is 0.05.

[0073] In the embodiment of the present application, the first score is calculated using the following expression:

[0074] R1=0.1D1+0.3D2+0.3D3+0.2D4+0.05D5+0.05D6 (2)

[0075] Among them, R1 represents the first score, D1 represents supply stability, D2 represents equipment complexity coefficient, D3 represents standby status, D4 represents maintenance complexity, D5 represents power, and D6 represents load matching.

[0076] In the step of analyzing the second score of the current equipment, the production importance, medium hazard, equipment newness coefficient, process fluctuation, equipment switching interval and mean time between failures in the actual operation characteristics are scored according to the second scoring standard, and the corresponding weight is configured for each scoring result according to the importance of each operation characteristic, and the weighted algorithm is used to obtain the second score. In the embodiment of the present application, based on the actual operation characteristics of the current equipment to be evaluated, the production importance, medium hazard, equipment newness coefficient, process fluctuation, equipment switching interval and mean time between failures in the current actual operation characteristics are scored according to the second scoring standard. Since the severity of the risks caused by production importance, medium hazard, equipment newness coefficient, process fluctuation, equipment switching interval and mean time between failures are not the same, therefore, after obtaining the scoring results of production importance, medium hazard, equipment newness coefficient, process fluctuation, equipment switching interval and mean time between failures, the embodiment configures the corresponding weight for each scoring result according to the importance of each operation characteristic (that is, the severity of the risks caused by each operation characteristic), so as to calculate the second score by using the weighted algorithm. It can be seen that the present invention fully considers the importance of different operating characteristics, and the second score obtained is more objective, which lays a foundation for accurately evaluating the in-service risk of rotating equipment. Among them, the weight of production importance is 0.2, the weight of medium hazard is 0.3, the weight of equipment newness coefficient is 0.2, the weight of process fluctuation is 0.1, the weight of equipment switching interval is 0.1, and the weight of mean time between failures is 0.1.

[0077] In the embodiment of the present application, the second score is calculated using the following expression:

[0078] ″ ″ ″

[0079] R2=0.2D1+0.3D2+0.2D3+0.1D4+0.1D5+0.1D6 (3)

[0080] Among them, R2 represents the second score, D′1 represents production importance, D′2 represents medium hazard, D′3 represents equipment newness coefficient, D′4 represents process fluctuation, D′5 represents equipment switching interval, and D′6 represents mean time between failures.

[0081] In the embodiment of the present application, the risk assessment result is obtained using the following expression:

[0082] R=(R1+R2)·M (4)

[0083] Wherein, R represents the total risk score, R1 represents the first score, R2 represents the second score, and M represents the correction factor of the rotating equipment to be evaluated.

[0084] This embodiment calculates a total risk score with a value between 2 and 2048. Based on the calculated total risk scores of different rotating equipment at the same time, the rotating equipment with the highest risk among the same type of rotating equipment can be found, and by calculating the total risk score for the same rotating equipment in real time, the in-service risk change of the current rotating equipment can be obtained.

[0085] Embodiment 2

[0086] In a specific embodiment of the present application, according to the first scoring standard, the second scoring standard and the correction coefficient matrix described in Example 1, combined with the characteristic parameters of the current rotating device to be evaluated as shown in Table 4, the first score, the second score and the correction coefficient of the current rotating device to be evaluated are determined:

[0087] Table 4

[0088]

[0089] First of all, the rotating equipment to be evaluated has been operating normally for 5 years. The equipment is of mature design and has a large number of suppliers, more than 50, and the supply stability is 1 point. The equipment to be evaluated is a large and complex equipment with more than 30 parts and components, and the equipment complexity coefficient is 4 points. The equipment to be evaluated has no backup machine, and the backup machine situation is 4 points. The equipment to be evaluated is a large and complex equipment, and the maintenance period is more than one day, and the maintenance complexity is 4 points. The rated power of the equipment to be evaluated is 5200kw, and the power is 4 points. The equipment to be evaluated has been running at 95% load for a long time, and the compliance is more than 90%, and the load matching is 1 point. The first score of the rotating equipment to be evaluated is obtained by calculation: R1=1*0.1+4*0.3+4*0.3+4*0.2+4*0.05+1*0.05=3.55.

[0090] Next, the rotating equipment to be evaluated is a core equipment. Its shutdown will cause the whole unit to stop working, and there is no spare machine. The production importance is 4 points. Ethylene belongs to Class A flammable medium, and the medium hazard is 4 points. The equipment to be evaluated has been in service for 5 years, and the equipment newness coefficient is 3 points. The equipment to be evaluated has been running at 95% load for a long time, with an average fluctuation of no more than ±5%, and the process fluctuation is 1 point. The equipment to be evaluated has no spare machine and does not switch. The equipment switching interval is 4 points. The equipment to be evaluated continues to operate normally, with an average trouble-free time of 42 months, and the average trouble-free time is 1 point. The second score of the rotating equipment to be evaluated is obtained by calculation: R2=4*0.2+4*0.3+3*0.2+1*0.1+4*0.1+1*0.1=3.2.

[0091] Finally, the rotating equipment to be evaluated is a core equipment, which has a separate preventive work strategy and performs preventive maintenance, and the preventive work management coefficient is 1. The equipment to be evaluated is equipped with a condition monitoring system, but the company has no dedicated personnel to perform it, so the equipment operation status perception coefficient is 2. The equipment to be evaluated is a special care equipment, and a special special care team has been established, with a management redundancy coefficient of 1. The company has established clear fault cause analysis standards. The equipment to be evaluated has no faults since it was put into service, but similar equipment has undergone fault cause analysis, and the fault cause management coefficient is 2. The correction coefficient of the rotating equipment to be evaluated is calculated as: M = 1*2*1*2 = 4.

[0092] The total risk score of the equipment to be evaluated is calculated using the first score, the second score and the correction factor: R = (3.55 + 3.2) * 4 = 27. In other words, the total risk score of the rotating equipment to be evaluated is 27, which can be used to conduct risk assessment with other rotating equipment evaluated by this method, and can also be used to compare the total risk scores of the same equipment at different times, so as to guide the enterprise to control and reduce the risk of equipment.

[0093] Furthermore, a year later, the rotating equipment was risk assessed again. During the two risk assessments, the company set up a specialist in the condition monitoring system in order to improve the level of equipment management. Apart from that, there were no other changes. In other words, there are only two differences between this assessment and the one a year ago. The first is the equipment newness coefficient. The service life of the equipment to be assessed has increased from 5 years to 6 years, but the score for this item remains at 3 points and has not changed. The second is the equipment operating status perception coefficient. Since a dedicated person has been set up for condition monitoring, the value of this item has changed from 2 to 1. Therefore, the current total risk score of the equipment to be assessed becomes: R = (3.55 + 3.2) * 2 = 13.5.

[0094] Next, any new rotating equipment of the same period other than the evaluated rotating equipment one year later is selected for in-service risk assessment. According to the first scoring standard, the second scoring standard and the correction coefficient matrix described in Example 1, combined with the characteristic parameters of the current new rotating equipment shown in Table 5, the first score, the second score and the correction coefficient of the current new rotating equipment are determined:

[0095] Table 5

[0096]

[0097] First, the new rotating equipment has been operating normally for 16 years. The equipment is of mature design and has a large number of suppliers, more than 50, and the supply stability is 1 point. The equipment to be evaluated is complex equipment with no more than 30 parts and components, and the equipment complexity coefficient is 3 points. The equipment to be evaluated has a backup machine with the same capacity, and the backup machine situation is 1 point. The equipment to be evaluated is complex equipment, and the maintenance period is less than one day, and the maintenance complexity is 3 points. The rated power of the equipment to be evaluated is 700kw, and the power is 2 points. The equipment to be evaluated has been running at 95% load for a long time, and the compliance is more than 90%, and the load matching is 1 point. The first score of the new rotating equipment is 2.05 through calculation.

[0098] Next, the current new rotating equipment belongs to the core equipment, but the current equipment to be evaluated has a backup machine. Its shutdown will only cause the current equipment to be evaluated to stop operating, and the production importance is 1 point. Crude oil belongs to Class C flammable medium, and the medium hazard is 2 points. The current equipment to be evaluated has been in service for 16 years, and the equipment newness coefficient is 4 points. The current equipment to be evaluated has been running at 95% load for a long time, with an average fluctuation of no more than ±5%, and the process fluctuation is 1 point. The regular switching time of the current equipment to be evaluated is 3 months, and the equipment switching interval is 1 point. The current equipment to be evaluated is basically running smoothly, with an average trouble-free time of 22 months, and the average trouble-free time is 3 points. Through calculation, the second score of the current new rotating equipment is 2.1.

[0099] Finally, the new rotating equipment is currently a core equipment, but there is no separate preventive work strategy. Only preventive maintenance work is performed on this type of equipment, and the preventive work management coefficient is 2. The equipment to be evaluated is currently equipped with a condition monitoring system, and the company has a dedicated person to monitor it. The equipment operation status perception coefficient is 1. The equipment to be evaluated is not a special care equipment, but it is managed by a dedicated equipment management personnel, and the management redundancy coefficient is 2. The company has established clear fault cause analysis standards. The equipment to be evaluated has no faults since it was put into service, but similar equipment has undergone fault cause analysis, and the fault cause management coefficient is 2. The correction coefficient of the current new rotating equipment is 8 through calculation.

[0100] The total risk score of the equipment to be evaluated is calculated to be 33.2 using the first score, second score and correction coefficient of the equipment to be evaluated. In other words, the total risk score of the new rotating equipment is 33.2. Compared with the total risk score of 13.5 of another equipment in the same period, the total risk score of this equipment is obviously higher, and the main reason for this is the management coefficient. Therefore, if the enterprise wants to reduce the total risk score of this equipment, it should focus on improving the corresponding management level.

[0101] Embodiment 3

[0102] Based on the method for evaluating the in-service risk of rotating equipment described in the first embodiment, an embodiment of the present invention further provides a system for evaluating the in-service risk of rotating equipment. Figure 2 The overall structure diagram of the system for evaluating the in-service risk of rotating equipment according to the embodiment of the present application is shown in FIG. The structure and function of the system for evaluating the in-service risk of rotating equipment according to the embodiment of the present application are described in detail below in conjunction with the embodiment of the present application.

[0103] The system for evaluating the in-service risk of rotating equipment of the present invention at least includes: a scoring standard formulation module 21, a correction coefficient matrix generation module 22 and a risk assessment module 23. Specifically, the scoring standard formulation module 21 is used to obtain the correlation between each type of inherent characteristics and the severity of the first risk caused by it, and the correlation between each type of operating characteristics and the severity of the second risk caused by it, respectively, for different types of rotating equipment, so as to establish a first scoring standard for describing the inherent characteristics relative to the severity of the first risk, and a second scoring standard for describing the operating characteristics relative to the severity of the second risk; the correction coefficient matrix generation module 22 is used to obtain the correlation between the operating management characteristics of different types of rotating equipment and their impact on the severity of each type of risk, so as to form a correction coefficient matrix for correcting each risk score; the risk assessment module 23 is used to analyze the first score, the second score and the correction coefficient of the equipment to be evaluated based on the scoring standards established by the scoring standard formulation module 21 and the correction coefficient matrix generated by the correction coefficient matrix generation module 22, according to the actual inherent characteristics, operating characteristics and operating management characteristics of the equipment to be evaluated, so as to generate a risk assessment result.

[0104] The present invention proposes a method and system for evaluating the in-service risk of rotating equipment. The method is a semi-quantitative evaluation method, which comprehensively determines the in-service risk of the rotating equipment to be evaluated based on the inherent risk and operation risk of the rotating equipment. First, for different types of rotating equipment, the correlation between each type of inherent characteristics and the first risk severity caused by it, and each type of operation characteristics and the second risk severity caused by it are respectively obtained, so as to establish different scoring standards for describing the inherent characteristics relative to the first risk severity and the operation characteristics relative to the second risk severity; then, for different types of rotating equipment, the correlation between the operation management characteristics of different types of rotating equipment and their influence on the severity of each type of risk is obtained, so as to form a correction coefficient matrix for correcting each risk score; finally, based on the established scoring standards and the formed correction coefficient matrix, according to the actual inherent characteristics, operation characteristics and operation management characteristics of the current equipment to be evaluated, the first score, the second score and the correction coefficient of the equipment to be evaluated are analyzed, so as to generate the risk assessment result of the current equipment. The present invention has realized storage and use in electronic media, and is mainly used to evaluate the in-service risks of rotating equipment in the petrochemical industry. Compared with RCM, it does not require evaluators to have a high level of professional and technical skills, the evaluation process and complexity are greatly reduced, the specific rules are relatively clear and easy to understand, and it is easy to operate. At the same time, the evaluation rules of the present invention are unified, and there is no need for personnel to make their own judgments. There are fewer human interference factors, and accurate and stable rotating equipment in-service risk assessment results are obtained. At the same time, compared with the targeted risk assessment of specific equipment or activities, the applicability of the present invention is more extensive, and a unified standard is established for comparisons between similar equipment (rotating equipment), and horizontal comparisons can be carried out on different equipment, as well as vertical comparisons on the same equipment.

[0105] The above description is only a specific implementation case of the present invention, and the protection scope of the present invention is not limited thereto. Any modification or replacement of the present invention by any technician familiar with the present technology within the technical specifications described in the present invention should be within the protection scope of the present invention.

[0106] Of course, the present invention may have many other embodiments. Without departing from the spirit and essence of the present invention, those skilled in the art may make various corresponding changes and modifications based on the present invention, but these corresponding changes and modifications should all fall within the scope of protection of the claims of the present invention.

[0107] It should be understood by those skilled in the art that the modules or steps of the present invention described above can be implemented by a general-purpose computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, and optionally, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present invention is not limited to any specific combination of hardware and software.

[0108] Although the embodiments disclosed in the present invention are as above, the above contents are only embodiments adopted for facilitating the understanding of the present invention and are not intended to limit the present invention. Any technician in the technical field to which the present invention belongs can make any modifications and changes in the form and details of the implementation without departing from the spirit and scope disclosed in the present invention, but the patent protection scope of the present invention shall still be subject to the scope defined in the attached claims.

Claims

1. A method for assessing the in-service risk of rotating equipment, characterized in that: include: For different types of rotating equipment, respectively obtain the correlation between each type of inherent characteristic and the severity of the first risk caused by it, and the correlation between each type of operating characteristic and the severity of the second risk caused by it, so as to establish a first scoring standard for describing the severity of the inherent characteristic relative to the first risk, and a second scoring standard for describing the severity of the operating characteristic relative to the second risk; Obtain the correlation between the operation and management characteristics of different types of rotating equipment and their impact on the severity of various risks, so as to form a correction coefficient matrix for correcting the risk scores of each type; Based on each scoring standard and the correction coefficient matrix, according to the actual inherent characteristics, operating characteristics and operating management characteristics of the equipment to be evaluated, the first score, the second score and the correction coefficient of the equipment to be evaluated are analyzed to generate a risk assessment result.

2. The method according to claim 1, characterized in that The inherent characteristics include, but are not limited to: supply stability, equipment complexity factor, standby status, maintenance complexity, power and load matching; The operating characteristics include, but are not limited to: production importance, medium hazard, equipment newness factor, process fluctuation, equipment switching interval and mean time between failures; and The operation management characteristics include, but are not limited to: a preventive work management coefficient, an equipment operation status perception coefficient, a management redundancy coefficient, and a fault cause management coefficient.

3. The method according to claim 2, characterized in that In the process of collecting each type of inherent characteristics, include: Said supply stability is obtained according to the maturity of the rotating equipment; The equipment complexity coefficient is obtained according to the structural complexity of the rotating equipment; The standby machine status is obtained according to the number of standby machines of the rotating equipment; The maintenance complexity is obtained according to the maintenance complexity of the rotating equipment; The power is obtained according to the rated power of the rotating equipment; and The load matching property is obtained according to the load matching compliance of the rotating equipment.

4. The method according to claim 2, characterized in that: In the process of collecting each type of operational characteristics, include: The production importance is obtained according to the degree of failure of other equipment in the device where the rotating equipment is located caused by the failure of the rotating equipment; The medium hazard is obtained according to the toxicity and flammability of the medium carried by the rotating equipment; The equipment newness coefficient is obtained based on the service life of the rotating equipment; The process fluctuation is obtained according to the influence of the current process on the load of the rotating equipment; The device switching interval is obtained according to the duration of the periodic switching interval of the rotating device; and The mean time between failures is obtained according to the actual maintenance cycle of the rotating equipment.

5. The method according to claim 2, characterized in that: The process of collecting the operation management characteristics includes: The preventive work management coefficient is obtained according to the strategy formulation state of the preventive work of the rotating equipment; The equipment operation state perception coefficient is obtained according to the operation state monitoring method of the rotating equipment; The management redundancy coefficient is obtained according to the configuration status of the management personnel of the rotating equipment; and The fault cause management coefficient is obtained according to the degree of understanding of the fault cause of the rotating equipment.

6. The method according to any one of claims 2 to 5, characterized in that: The step of analyzing the first score of the current device includes: According to the first scoring standard, the supply stability, the equipment complexity coefficient, the standby machine status, the maintenance complexity, the power and the load matching in the actual inherent characteristics are scored respectively, and according to the importance of each inherent characteristic, a corresponding weight is assigned to each scoring result, and a weighted algorithm is used to obtain the first score, wherein, The weight of the supply stability is 0.1, the weight of the equipment complexity coefficient is 0.3, the weight of the standby condition is 0.3, the weight of the maintenance complexity is 0.2, the weight of the power is 0.05, and the weight of the load matching is 0.

05.

7. The method according to claim 6, characterized in that The step of analyzing the second score of the current device includes: According to the second scoring standard, the production importance, the medium hazard, the equipment newness coefficient, the process fluctuation, the equipment switching interval and the mean time between failures in the actual operation characteristics are scored respectively, and according to the importance of each operation characteristic, a corresponding weight is assigned to each scoring result, and a weighted algorithm is used to obtain the second score, wherein, The weight of the production importance is 0.2, the weight of the medium hazard is 0.3, the weight of the equipment newness coefficient is 0.2, the weight of the process fluctuation is 0.1, the weight of the equipment switching interval is 0.1, and the weight of the mean time between failures is 0.

1.

8. The method according to claim 6, characterized in that The first score is calculated using the following expression: R1=0.1D1+0.3D2+0.3D3+0.2D4+0.05D5+0.05D6 Among them, R1 represents the first score, D1 represents supply stability, D2 represents equipment complexity coefficient, D3 represents standby status, D4 represents maintenance complexity, D5 represents power, and D6 represents load matching.

9. The method according to claim 7, characterized in that: The second score is calculated using the following expression: R2=0.2D′1+0.3D′2+0.2D′3+0.1D′4+0.1D′5+0.1D′6 Among them, R2 represents the second score, D′1 represents production importance, D′2 represents medium hazard, D′3 represents equipment newness coefficient, D′4 represents process fluctuation, D′5 represents equipment switching interval, and D′6 represents mean time between failures.

10. The method according to any one of claims 2 to 9, characterized in that: The correction coefficient matrix is ​​calculated using the following expression: M′=F1·F2·F3·F4 Among them, M′ represents a single correction coefficient in the correction coefficient matrix, F1 represents the preventive work management coefficient, F2 represents the equipment operation status perception coefficient, F3 represents the management redundancy coefficient, and F4 represents the fault cause management coefficient.

11. The method according to any one of claims 1 to 10, characterized in that: The risk assessment result is obtained using the following expression: R=(R1+R2)·M Wherein, R represents the total risk score, R1 represents the first score, R2 represents the second score, and M represents the correction factor of the rotating equipment to be evaluated.

12. A system for assessing the in-service risk of rotating equipment, characterized in that: The system includes the following modules: A scoring standard formulation module, which is used to obtain, for different types of rotating equipment, the correlation between each type of inherent characteristic and the severity of the first risk caused by it, and the correlation between each type of operating characteristic and the severity of the second risk caused by it, so as to establish a first scoring standard for describing the severity of the inherent characteristic relative to the first risk, and a second scoring standard for describing the severity of the operating characteristic relative to the second risk; A correction coefficient matrix generation module is used to obtain the correlation between the operation management characteristics of different types of rotating equipment and their impact on the severity of various risks, thereby forming a correction coefficient matrix for correcting various risk scores; The risk assessment module is used to analyze the first score, the second score and the correction coefficient of the device to be evaluated based on each scoring standard and the correction coefficient matrix, according to the actual inherent characteristics, operating characteristics and operating management characteristics of the device to be evaluated, so as to generate a risk assessment result.

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