Method for optimizing reliability of ultra-deepwater pile hammer system

Abstract

The present invention belongs to the technical field of designs of mechanical parameters or variables in electrical digital data processing. Disclosed is a method for optimizing the reliability of an ultra-deepwater pile hammer system, which method is used for performing reliability analysis on a pile hammer system. The method comprises: performing functional analysis and functional module division on a mechanical system, a power system, a hydraulic system, a pneumatic system and an electronic control system of an ultra-deepwater pile hammer system, viewing the five systems as five first-level subsystems, clarifying important parameters of the first-level subsystems, and further dividing the first-level subsystems into second-level subsystems; and performing criticality analysis on the second-level subsystems, and allocating reliability indexes of the first-level subsystems and the second-level subsystems of the ultra-deepwater pile hammer system and reliability indexes of failure modes of the second-level subsystems, so as to obtain an optimal reliability allocation scheme for the ultra-deepwater pile hammer system. In the present invention, various parameters of first-level systems and second-level systems are combined, and failure modes are taken into consideration, so as to obtain an optimal reliability allocation scheme.

Description

Reliability optimization method for ultra-deepwater pile hammer system

[0001] This application claims priority to the Chinese patent application filed with the China Patent Office on December 14, 2023, with application number 202311714328.5 and invention name “Reliability Optimization Method for Ultra-Deepwater Pile Hammer System”, the entire contents of which are incorporated by reference into this application. Technical Field

[0002] The invention discloses a reliability optimization method for an ultra-deepwater pile hammer system, and belongs to the technical field of design of mechanical parameters or variables in electrical digital data processing. Background Art

[0003] Ultra-deepwater pile hammer systems operate in harsh marine environments characterized by high pressure and high corrosion for extended periods. The enormous reaction forces generated during deepwater pile driving operations demand extremely high reliability. However, global research on the reliability of ultra-deepwater pile hammer systems has been limited to a few narrowly focused studies on vulnerable components or hydraulic control systems, with no systematic reliability studies available. Furthermore, China's research in key technologies such as product design, processing, and control systems lags behind, lacking successful experience to draw upon. Given these shortcomings in China's ultra-deepwater pile hammer system research, it is necessary to conduct reliability research on ultra-deepwater pile hammer systems to accelerate the localization of these systems and ensure their high reliability for deepwater operations. Summary of the Invention

[0004] The purpose of the present invention is to provide a reliability optimization method for an ultra-deepwater pile hammer system, so as to solve the problem of difficulty in reliability analysis of a pile hammer system in the prior art.

[0005] The reliability optimization method of ultra-deepwater pile hammer system includes:

[0006] S1. Perform functional analysis and functional module division of the ultra-deepwater pile hammer system's mechanical system, power system, hydraulic system, pneumatic system, and electronic control system. Treat these five systems as five first-level subsystems, and clarify the key parameters of each first-level subsystem.

[0007] The key parameters of each primary subsystem include the design requirements for complexity, importance, and reliability, the failure mode and severity of its impact on the ultra-deepwater pile hammer system, and the series and parallel relationships between the primary subsystems.

[0008] S2. Further divide each primary subsystem into secondary subsystems. Secondary subsystems are the parts or components that make up the primary subsystem. Identify the important parameters of each secondary subsystem.

[0009] The important parameters of each secondary subsystem include the design requirements of complexity, importance and reliability, the degree of hazard under a certain severity, the probability and hazard of a certain failure mode, and the series and parallel relationships between the secondary subsystems;

[0010] S3. Conduct hazard analysis on the secondary subsystem;

[0011] S4. Establish a first-level subsystem reliability allocation model to allocate reliability indicators for the first-level subsystem of the ultra-deepwater pile hammer;

[0012] S5. Establish a secondary subsystem reliability allocation model to allocate reliability indicators for the secondary subsystem of the ultra-deepwater pile hammer;

[0013] S6. Establish a failure mode reliability allocation model for the secondary subsystem and allocate failure mode reliability indicators for the secondary subsystem of the ultra-deepwater pile hammer;

[0014] S7. Obtain the optimal reliability allocation scheme for the ultra-deepwater pile hammer system.

[0015] S3 includes using the improved quantitative analysis method to analyze the criticality of the secondary subsystem, the criticality of the parts C p The calculation formula is:

[0016] Where C p is the criticality of the part, k is the total number of part failure modes, λ p is the occurrence rate of each failure mode of the parts in the i-th failure mode, α i is the percentage of the occurrence rate of the i-th failure mode of the part to the sum of the occurrence rates of all failure modes of the part, β i is the conditional probability that the i-th failure mode of the component leads to system failure, 0≤β i ≤1,s i is the severity of the i-th failure mode of the part, and t is the average working time of the part.

[0017] S4 involves allocating the reliability index of the first-level subsystem of the ultra-deepwater pile hammer using the improved AGREE reliability allocation method:

[0018] Where, is the modified importance of the jth subsystem, m is the number of parts of the jth subsystem, k is the number of failure modes of the vth part, n is the number of parts of the overall system, C pv is the criticality of the vth component, θ j is the criticality of the jth subsystem, and θ is the criticality of the entire system.

[0019] S5 involves allocating reliability indicators of the ultra-deepwater pile hammer secondary subsystem using the FMECA-based reliability allocation method:

[0020] Where, P jv is the reliability index of the vth component of the jth subsystem, P j Assign a reliability index to the jth subsystem, ω j is the weight of each component of the j-th subsystem relative to the subsystem after normalization, ω jv is the weight of the vth component of the jth subsystem relative to the subsystem after normalization, C pm is the criticality of the mth component.

[0021] S6 includes the reliability allocation of each basic failure mode of the parts using the distribution method of expected values. The basic failure modes of the parts are all in series relationship, and the reliability of the parts is allocated only when the specified failure probability is less than the expected failure probability. The reliability allocation formula is:

[0022] Where q ip Assign a value to the unreliability of each failure mode of the i-th fault, q iy is the expected occurrence rate of the i-th failure mode, q sq The failure rate value specified for the part, q sy is the expected failure rate of the part, R ip Assign a value to the reliability of the i-th failure mode, q ip Assign a value to the unreliability of each failure mode i.

[0023] S7 includes selecting the best value from each result according to the secondary subsystem hazard analysis result, the primary subsystem reliability index allocation result, the secondary subsystem reliability index allocation result, and the secondary subsystem failure mode reliability index allocation result to form an optimal reliability allocation plan.

[0024] Compared with the prior art, the present invention has the following beneficial effects: the present invention combines various parameters of the primary system and the secondary system, considers the failure mode, and obtains the optimal reliability allocation solution. DETAILED DESCRIPTION

[0025] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention are described clearly and completely below. Obviously, the embodiments described are only some of the embodiments of the present invention, not all of them. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0026] The reliability optimization method of ultra-deepwater pile hammer system includes:

[0027] S1. Perform functional analysis and functional module division of the ultra-deepwater pile hammer system's mechanical system, power system, hydraulic system, pneumatic system, and electronic control system. Treat these five systems as five first-level subsystems, and clarify the key parameters of each first-level subsystem.

[0028] The key parameters of each primary subsystem include the design requirements for complexity, importance, and reliability, the failure mode and severity of its impact on the ultra-deepwater pile hammer system, and the series and parallel relationships between the primary subsystems.

[0029] S2. Further divide each primary subsystem into secondary subsystems. Secondary subsystems are the parts or components that make up the primary subsystem. Identify the important parameters of each secondary subsystem.

[0030] The important parameters of each secondary subsystem include the design requirements of complexity, importance and reliability, the degree of hazard under a certain severity, the probability and hazard of a certain failure mode, and the series and parallel relationships between the secondary subsystems;

[0031] S3. Conduct hazard analysis on the secondary subsystem;

[0032] S4. Establish a first-level subsystem reliability allocation model to allocate reliability indicators for the first-level subsystem of the ultra-deepwater pile hammer;

[0033] S5. Establish a secondary subsystem reliability allocation model to allocate reliability indicators for the secondary subsystem of the ultra-deepwater pile hammer;

[0034] S6. Establish a failure mode reliability allocation model for the secondary subsystem and allocate failure mode reliability indicators for the secondary subsystem of the ultra-deepwater pile hammer;

[0035] S7. Obtain the optimal reliability allocation scheme for the ultra-deepwater pile hammer system.

[0036] S3 includes using the improved quantitative analysis method to analyze the criticality of the secondary subsystem, the criticality of the parts C p The calculation formula is:

[0037] Where C p is the criticality of the part, k is the total number of part failure modes, λ p is the occurrence rate of each failure mode of the parts in the i-th failure mode, α i is the percentage of the occurrence rate of the i-th failure mode of the part to the sum of the occurrence rates of all failure modes of the part, β i is the conditional probability that the i-th failure mode of the component leads to system failure, 0≤β i ≤1,si is the severity of the i-th failure mode of the part, and t is the average working time of the part.

[0038] S4 involves allocating the reliability index of the first-level subsystem of the ultra-deepwater pile hammer using the improved AGREE reliability allocation method:

[0039] Where, is the modified importance of the jth subsystem, m is the number of parts of the jth subsystem, k is the number of failure modes of the vth part, n is the number of parts of the overall system, C pv is the criticality of the vth component, θ j is the criticality of the jth subsystem, and θ is the criticality of the entire system.

[0040] S5 involves allocating reliability indicators of the ultra-deepwater pile hammer secondary subsystem using the FMECA-based reliability allocation method:

[0041] Where, P jv is the reliability index of the vth component of the jth subsystem, P j Assign a reliability index to the jth subsystem, ω j is the weight of each component of the j-th subsystem relative to the subsystem after normalization, ω jv is the weight of the vth component of the jth subsystem relative to the subsystem after normalization, C pm is the criticality of the mth component.

[0042] S6 includes the reliability allocation of each basic failure mode of the parts using the distribution method of expected values. The basic failure modes of the parts are all in series relationship, and the reliability of the parts is allocated only when the specified failure probability is less than the expected failure probability. The reliability allocation formula is:

[0043] Where q ip Assign a value to the unreliability of each failure mode of the i-th fault, q iy is the expected occurrence rate of the i-th failure mode, q sq The failure rate value specified for the part, q sy is the expected failure rate of the part, R ip Assign a value to the reliability of the i-th failure mode, q ip Assign a value to the unreliability of each failure mode i.

[0044] S7 includes selecting the best value from each result according to the secondary subsystem hazard analysis result, the primary subsystem reliability index allocation result, the secondary subsystem reliability index allocation result, and the secondary subsystem failure mode reliability index allocation result to form an optimal reliability allocation plan.

[0045] In the embodiment, when performing a criticality analysis on the secondary subsystem, commonly used criticality analysis methods include qualitative criticality matrix diagram method, quantitative criticality matrix diagram method, risk priority number method, cost priority number method, and fuzzy risk priority number method. They have their own characteristics and scope of application. When performing a failure criticality analysis on pile hammer components, they need to be adjusted and improved. The traditional quantitative criticality analysis is based on the criticality of the failure mode C. m C r Perform analysis:

[0046] Where n is the total number of failure modes of a part under a certain severity; C r C is the degree of hazard of parts under certain severity; mi is the criticality of the i-th failure mode of the component; p is the occurrence rate of each failure mode of the parts in the i-th failure mode, 10 -6 ·h -1 ; α i is the percentage of the occurrence rate of the i-th failure mode of the part to the sum of the occurrence rates of all failure modes of the part; β i is the conditional probability that the i-th failure mode of the component leads to system failure, 0≤β i ≤1, assuming that the failure mode of any component will lead to system failure, so β i The values ​​are all taken as 1; t is the average working time of the parts, h.

[0047] Traditional criticality analysis ultimately determines the criticality of a component under a specified severity level. This analysis fails to comprehensively evaluate component criticality and provides no guidance for component reliability research. To address this issue, an improved quantitative criticality analysis method is proposed, incorporating the severity of component failure modes into the analysis. This method shifts the analysis objective from the criticality of a component under a specific severity level to the overall criticality of the component. This allows for focused prevention and improvement measures for components with higher criticality levels, thereby improving the overall system safety.

[0048] Combined with the reliability data of the ultra-deepwater pile hammer system components and their failure modes (the failure mode incidence rates of some components refer to general reliability data), the ultra-deepwater pile hammer mechanical system is taken as an example to solve the criticality of the mechanical system components, as shown in Table 1.

[0049] Table 1 Criticality table of mechanical system parts

[0050] In Table 1, S i and C p All of them are indicators that are evaluated by the size of the value. They have no units and are evaluated and judged by the value.

[0051] When allocating the reliability index of the first-level subsystem of the ultra-deepwater pile hammer, the AGREE allocation method is:

[0052] Where C i is the complexity of the ith subsystem; W i is the importance of the ith subsystem; R S (t) is the reliability design index of the system; R i (t) is the reliability of the ith subsystem after allocation.

[0053] Among them, the importance of the i-th subsystem W i and complexity C i Definition:

[0054] Where N i is the number of times the upper system fails after the failure of the i-th subsystem; r i is the number of failures of the i-th subsystem; n i is the number of main parts of the ith subsystem; N is the number of main parts of the entire system.

[0055] The traditional AGREE reliability allocation method defines a subsystem's importance as the ratio of the number of system failures caused by a subsystem failure to the number of failures caused by that subsystem failure. Therefore, the importance of each subsystem is equal to 1, making comparison meaningless. In practical engineering, however, the importance of a subsystem must take into account multiple factors, such as failure rate, failure risk, and average operating time. To make the AGREE method's allocation results more reliable, this paper proposes an improved AGREE reliability allocation method by modifying the subsystem's importance based on component criticality analysis.

[0056] The traditional AGREE reliability allocation method allocates the reliability design indicators of the system preliminary design to each subsystem. The improved AGREE reliability allocation method allocates the reliability of the system and conducts comparative analysis. The basic parameters of the AGREE allocation method are shown in Table 2.

[0057] Table 2 AGREE allocation method parameters

[0058] In Table 2, complexity, criticality, and the two importances are all indicators evaluated by the size of the values. They have no units and are evaluated and judged based on the values.

[0059] The reliability allocation results of the improved and traditional AGREE reliability allocation methods are shown in Table 3.

[0060] Table 3 Subsystem reliability distribution results

[0061] In Table 3, reliability is an indicator evaluated by the size of the value. It has no unit and is evaluated and judged by the value.

[0062] Combined with the hazard analysis of the ultra-deepwater pile hammer system, the reliability distribution results of each component are obtained, as shown in Table 4.

[0063] Table 4 Component reliability distribution results

[0064] In Table 4, C pv 、ω jv Reliability is an indicator evaluated by the size of the value. It has no unit and is evaluated and judged by the value. The expected failure rate of each part is shown in Table 5.

[0065] Table 5 Parts failure rate prediction table

[0066] The reliability index assigned to the parts in Table 4 is set as the reliability design index, which is compared with the expected failure rate of the parts in Table 5. The reliability of each basic failure mode of the parts is allocated. The allocation results are shown in Table 6.

[0067] Table 6 Failure mode reliability distribution results

[0068] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents, and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. The reliability optimization method of ultra-deepwater pile hammer system is characterized by: include: S1. Perform functional analysis and functional module division on the mechanical system, power system, hydraulic system, pneumatic system and electronic control system of the ultra-deepwater pile hammer system, regard the five systems as five first-level subsystems, and clarify the important parameters of each first-level subsystem; The important parameters of each primary subsystem include the design requirements of complexity, importance and reliability, the failure mode and the severity of the impact on the ultra-deepwater pile hammer system, and the series and parallel relationship between each primary subsystem; S2. Each primary subsystem is further divided into secondary subsystems. The secondary subsystems are the parts or components that make up the primary subsystem, and the important parameters of each secondary subsystem are clarified; The important parameters of each secondary subsystem include the design requirements of complexity, importance and reliability, the degree of hazard under a certain severity, the probability and hazard of a certain failure mode, and the series and parallel relationship between each secondary subsystem; S3. Conduct criticality analysis on the secondary subsystem; S4. Establish a reliability allocation model for the first-level subsystem and allocate reliability indicators for the first-level subsystem of the ultra-deepwater pile hammer; S5. Establish a secondary subsystem reliability allocation model to allocate reliability indicators of the secondary subsystem of the ultra-deepwater pile hammer; S6. Establish a failure mode reliability allocation model for the secondary subsystem and allocate the failure mode reliability index of the secondary subsystem of the ultra-deepwater pile hammer; S7. Obtain the optimal reliability allocation scheme for the ultra-deepwater pile hammer system.

2. The method for optimizing the reliability of an ultra-deepwater pile hammer system according to claim 1, characterized in that: S3 includes using the improved quantitative analysis method to analyze the criticality of the secondary subsystem, and the criticality of the parts C p The calculation formula is: In the formula, C p is the criticality of the part, k is the total number of part failure modes, λ p is the occurrence rate of each failure mode of the parts in the i-th failure mode, α i is the percentage of the occurrence rate of the i-th failure mode of the part to the sum of the occurrence rates of all failure modes of the part, β i is the conditional probability that the i-th failure mode of the component leads to system failure, 0≤β i ≤1,s i is the severity of the i-th failure mode of the part, and t is the average working time of the part.

3. The method for optimizing the reliability of an ultra-deepwater pile hammer system according to claim 2, characterized in that: S4 includes using the improved AGREE reliability allocation method to allocate the reliability index of the first-level subsystem of the ultra-deepwater pile hammer: In the formula, is the modified importance of the jth subsystem, m is the number of parts of the jth subsystem, k is the number of failure modes of the vth part, n is the number of parts of the overall system, C pv is the criticality of the vth component, θ j is the criticality of the jth subsystem, and θ is the criticality of the overall system.

4. The method for optimizing the reliability of an ultra-deepwater pile hammer system according to claim 3, characterized in that: S5 includes the use of FMECA-based reliability allocation method to allocate reliability indicators of the ultra-deepwater pile hammer secondary subsystem: Where P jv is the reliability index of the vth component of the jth subsystem, P j Assign a reliability index to the jth subsystem, ω j is the weight of each component of the j-th subsystem relative to the subsystem after normalization, ω jv is the weight of the vth component of the jth subsystem relative to the subsystem after normalization, C pm is the criticality of the mth part.

5. The method for optimizing the reliability of an ultra-deepwater pile hammer system according to claim 4, characterized in that: S6 includes reliability allocation for each basic failure mode of a part using the distribution method of expected value. Each basic failure mode of a part is in series relationship, and reliability allocation is performed on the part only when the specified failure probability is less than the expected failure probability. The reliability allocation formula is: In the formula, q ip Assign a value to the unreliability of each failure mode of the ith type, q iy is the expected value of the occurrence rate of the ith failure mode, q sq is the failure rate value specified for the part, q sy is the expected failure rate of the part, R ip Assign a value to the reliability of the ith failure mode, q ip Assign a value to the unreliability of each ith failure mode.

6. The method for optimizing the reliability of an ultra-deepwater pile hammer system according to claim 5, characterized in that: S7 includes selecting the best value from each result according to the secondary subsystem hazard analysis result, the primary subsystem reliability index allocation result, the secondary subsystem reliability index allocation result, and the secondary subsystem failure mode reliability index allocation result to form an optimal reliability allocation plan.

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