Mine car hardware reliability assessment method

Abstract

The invention relates to a mine car hardware reliability assessment method, which comprises the following steps of: acquiring failure data of key parts of a mine car, calculating to obtain an empirical function value, sequencing failure time according to a time sequence to obtain a part service life sequence number, namely a failure rank, and calculating an empirical distribution function by an approximate median rank formula; evaluating the reliability of the subsystems, and determining the reliability of the subsystems; constructing a system reliability block diagram, and establishing a mine car system structure tree according to three working logics of series connection, parallel connection and redundancy between mine car systems; and maintenance importance determination: finding out a key subsystem influencing the reliability of the system, and then finding out key parts according to the importance as the direction and path for determining the maintenance importance. According to the method, the influence of high redundancy, maintainability, nonlinearity and other structural characteristics of the mine car on the reliability state is described by using a maintenance importance index. From the part level to the system level, weighted integration is carried out based on the system structure tree model of the maintenance importance degree, and mine car multi-level reliability state evaluation is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of equipment reliability assessment, and in particular to a mine car hardware reliability assessment method. Background Art

[0002] Mine carts are critical equipment for open-pit mineral resource mining and transportation, primarily operating in loading, transporting, and unloading operations. The use of mine carts in mining environments places higher demands on hardware reliability. The often harsh mining environment, characterized by extreme temperatures, high humidity, and high dust levels, poses a significant challenge to the hardware used in mine carts. Mine cart hardware reliability is key to ensuring stable operation in these harsh mining environments. This requires comprehensive design and optimization across multiple aspects, including sensors, steering subsystems, braking subsystems, communication modules, power systems, mechanical components, and protective housings, to meet the unique demands of mining operations. The use of high-quality components, advanced design concepts, and rigorous testing and verification effectively improves mine cart hardware reliability.

[0003] Researchers at home and abroad have applied Markov processes, randomly colored Petri nets, the GO method, graph theory, and fault tree analysis to analyze the reliability of mine cars. In reality, mine car reliability is not only related to the reliability of components and subsystems and the system topology, but also to their position within the system topology. By determining the failure patterns of key mine car components, it is possible to determine when a component will fail, become damaged, or become obsolete. Therefore, based on component failure patterns, the operating life and reliability of the component can be determined. Numerous studies have analyzed the operating life and reliability of components. Identifying system weaknesses before mine car failures occur and proactively optimizing and maintaining reliability are of great practical significance. Summary of the Invention

[0004] In view of the problem that the reliability prediction of mine cars in the prior art is quite different from the actual situation and the prediction reliability is low, the present invention provides a mine car hardware reliability assessment method.

[0005] The technical solution of the present invention provides a method for evaluating the reliability of mining car hardware, comprising the following steps: S1: Obtain failure data of key parts of the mine car, calculate the empirical function value, sort the failure times in chronological order, obtain the part life sequence number, which is the failure rank, and calculate the empirical distribution function using the approximate median rank formula; S2: Subsystem reliability assessment, determining subsystem reliability; S3: System reliability block diagram construction, based on the three working logics of series, parallel and redundancy between the mine car systems to establish the mine car system structure tree; S4: Determine the importance of maintenance: Identify the key subsystems that affect system reliability, and then identify the key parts based on their importance as the direction and approach for determining maintenance importance; Preferably, the S2 step includes the following process: S2-1: Reliable characteristic parameters Pi represents the i-th reliable characteristic parameter of the subsystem. The n characteristic parameters are represented as P1, P2, ..., Pn respectively; the maximum and minimum values are obtained based on historical data; S2-2: Reliable feature data matrix According to K time intervals, T is represented as an n×K matrix

[0006] S2-3: Acquisition of reliable characteristic value observations Obtain reliable feature data , represents the observed value; S2-4: Standardization of reliable feature quantities The normalized data vector is ; S2-5: Calculate the reliability deviation of the subsystem According to the vector and matrix T, calculate the subsystem deviation reliability

[0007] Where, represents the Euclidean norm of the vector; α is the regularization coefficient; S2-6: Calculating Subsystem Reliability according to , calculate the subsystem reliability R: .

[0008] Preferably, the reliability importance in step S4 is mainly composed of three evaluation indicators, U = {risk, detection, contribution}: “Risk” is the degree of unreliability, which indicates the probability that the unit cannot work properly in the interval [0, t]. express; "Detection degree" is a comprehensive evaluation of unit testability, maintainability and maintenance costs, which can be determined fuzzily based on experience. represents the detection degree of unit i at time t; "Contribution" is defined from a maintenance perspective. It focuses on the overall improvement in system reliability after a certain unit of the system is repaired at a certain moment. Units with large contribution should be given priority in subsequent maintenance activities.

[0009] Preferably, the contribution is expressed as Indicates that, assuming the system has n units, the maintenance evaluation matrix It can be expressed as:

[0010] Where, It represents the evaluation value of system component i under maintenance evaluation factor U. The weight of evaluation index can be determined by AHP method.

[0011] Preferably, the method further includes the step of calculating the system reliability: According to the reliability of parts and the importance of each level, the reliability of each level of system elements is calculated from the tree leaf node of the system structure layer by layer. Let the element of a certain layer be s, and the elements of the next layer be e1, e2, ..., em, the maintainability importance of s is ve, the maintainability importance of ei is Vi, the reliability of ei is Ri, and the adjustment coefficient is , the reliability of s is .

[0012] This application proposes a mine car hardware reliability assessment method based on maintenance importance. The maintenance importance metric characterizes the impact of structural characteristics such as high redundancy, maintainability, and nonlinearity on the system reliability status. At the subsystem level, a nonparametric regression method is used to integrate multiple parameters to assess reliability status. From the component level to the system level, a system structure model based on maintenance importance is weighted and integrated to achieve multi-level reliability status assessment of the mine car. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 It is a schematic diagram of the overall process of the present invention. DETAILED DESCRIPTION

[0014] The present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. In this specification, the size ratios in the drawings do not represent the actual size ratios, but are only used to reflect the relative positional relationship and connection relationship between the various components. Components with the same name or the same number represent similar or identical structures and are only for illustrative purposes.

[0015] Figure 1 This is a schematic diagram of the overall process of this application. The mine car hardware reliability assessment method includes the following steps.

[0016] S1: Acquisition of parts-related data.

[0017] Based on the failure data of key parts of the mine car, the empirical function value is calculated. The failure times are sorted in chronological order to obtain the part life sequence number, which is the failure rank. If the failure data is greater than 20, the empirical distribution function is calculated using the approximate median rank formula.

[0018] S2: Subsystem reliability assessment, determine the subsystem reliability.

[0019] S2-1: Reliable characteristic parameters Pi represents the i-th reliable characteristic parameter of the subsystem. The n characteristic parameters are denoted as P1, P2, …, Pn. The maximum and minimum values are obtained based on historical data.

[0020] S2-2: Reliable feature data matrix According to K time intervals, T is expressed as an n×K matrix

[0021] S2-3: Acquisition of reliable characteristic observation values Obtain reliable feature data , Represents the observed value.

[0022] S2-4: Standardization of reliable feature quantities The normalized data vector is .

[0023] S2-5: Calculate the reliability deviation of the subsystem According to the vector and matrix T, calculate the subsystem deviation reliability

[0024] Where, represents the Euclidean norm of the vector; α is the regularization coefficient.

[0025] S2-6: Calculating Subsystem Reliability according to , calculate the subsystem reliability R.

[0026]

[0027] S3: System reliability block diagram construction System reliability assessment requires establishing a mine car system structure tree. This structure organizes elements such as mine car parts and subsystems into a hierarchical relationship. The tree structure also creates a tree-like structure for the elements' operational logic based on functional requirements. Nodes in the tree represent elements at each level. Leaf nodes represent system elements that require no further subdivision. Non-leaf nodes are system elements composed of their child nodes. The root node represents the entire system.

[0028] The working logic between system elements refers to the functional and working logic requirements that must be met by the set of system elements corresponding to its child nodes when a non-leaf node completes its designed function. The mine car system structure tree employs three types of working logic: series, parallel, and redundant. Let a non-leaf node be s, and its child nodes be e1, e2, …, em. In other words, system elements e1, e2, …, em constitute a higher-level system element s, and e1, e2, …, em are the constituent elements of s.

[0029] S4: The importance of maintenance is confirmed.

[0030] When conducting system reliability analysis, identify the key subsystems that affect system reliability, then identify key components based on their importance. This provides direction and approaches for system reliability design, reliability allocation, fault diagnosis, and maintenance and inspection measures. This is done one by one at the system → subsystem → component level.

[0031] Based on the above considerations, this paper introduces a new unit importance metric. Drawing on the probabilistic importance, failure mode criticality, and detection efficiency of fault tree analysis, this metric comprehensively weighs various indicators influencing unit maintenance based on the real-time operation of the mine car system, quantitatively assessing unit importance to provide support for the unit maintenance sequence in subsequent maintenance activities.

[0032] Reliability importance is mainly composed of three evaluation indicators: U = {risk, detection, contribution}.

[0033] (1) “Risk” refers to unreliability, which indicates the probability that the unit cannot work normally in the interval [0, t]. express.

[0034] (2) “Testability” is a comprehensive evaluation of unit testability, maintainability and maintenance costs, which can be determined fuzzily based on experience. represents the detection degree of unit i at time t.

[0035] (3) “Contribution” is defined from the maintenance perspective. It focuses on the overall improvement of system reliability after a certain unit of the system is repaired (the unit is restored to a new state or optimal state). Units with large contribution should be given priority in subsequent maintenance activities. express.

[0036] Assuming that the system has n units, the maintenance evaluation matrix It can be expressed as:

[0037] Where, It represents the evaluation value of system component i under maintenance evaluation factor U. The weight of evaluation index can be determined by AHP method.

[0038] S5: System reliability calculation.

[0039] According to the reliability of parts and the importance of each level, the reliability of each level of system elements is calculated from the tree leaf node of the system structure layer by layer. Let the element of a certain layer be s, and the elements of the next layer be e1, e2, ..., em, the maintainability importance of s is ve, the maintainability importance of ei is Vi, the reliability of ei is Ri, and the adjustment coefficient is , the reliability of s is

[0040] Currently, weighted methods are primarily used for mine car reliability assessment. However, these methods often fail to adequately reflect the high redundancy and repairability of mine car systems, and the weighting parameters of the reliability assessment model are overly reliant on expert experience. To address these issues, a mine car reliability assessment method based on maintenance importance is proposed. This method uses the maintenance importance metric to characterize the impact of the mine car's structural characteristics, such as high redundancy, repairability, and nonlinearity, on the system's reliability status. At the subsystem level, a nonparametric regression method is used to integrate multiple parameters to assess the reliability status. From the component level to the system level, a system structure model based on maintenance importance is weighted and integrated to achieve multi-level reliability assessment of mine cars.

[0041] The above content only describes the preferred embodiments of the present invention and does not limit the scope of the present invention. Without departing from the design spirit of the present invention, various modifications and improvements made to the technical solution of the present invention by ordinary technicians in this field should fall within the scope of protection determined by the claims of the present invention.

Claims

1. A mine car hardware reliability assessment method, characterized in that: The steps include: S1: Obtain failure data of key parts of the mine car, calculate the empirical function value, sort the failure times in chronological order, obtain the part life sequence number, which is the failure rank, and calculate the empirical distribution function using the approximate median rank formula; S2: Subsystem reliability assessment, determining subsystem reliability; S3: System reliability block diagram construction, based on the three working logics of series, parallel and redundancy between the mine car systems to establish the mine car system structure tree; S4: Determine the importance of maintenance: Identify the key subsystems that affect system reliability, and then identify the key parts based on their importance as the direction and approach to determine the importance of maintenance.

2. The mine car hardware reliability assessment method according to claim 1, wherein: The S2 step includes the following process: S2-1: Reliable characteristic parameters Pi represents the i-th reliable characteristic parameter of the subsystem. The n characteristic parameters are represented as P1, P2, ..., Pn respectively; the maximum and minimum values are obtained based on historical data; S2-2: Reliable feature data matrix According to K time intervals, T is expressed as an n×K matrix S2-3: Acquisition of reliable characteristic observation values Obtain reliable feature data , represents the observed value; S2-4: Standardization of reliable feature quantities The normalized data vector is ; S2-5: Calculate the reliability deviation of the subsystem According to the vector and matrix T, calculate the subsystem deviation reliability Where, represents the Euclidean norm of the vector; α is the regularization coefficient; S2-6: Calculating Subsystem Reliability according to , calculate the subsystem reliability R: 。 3. The mine car hardware reliability evaluation method according to claim 1, characterized in that: The reliability importance in step S4 is mainly composed of three evaluation indicators, U = {risk, detection, contribution}: "Risk" is the degree of unreliability, which indicates the probability that the unit cannot work properly in the interval [0, t]. express; "Detection degree" is a comprehensive evaluation of unit testability, maintainability and maintenance costs, which can be determined fuzzily based on experience. represents the detection degree of unit i at time t; "Contribution" is defined from a maintenance perspective. It focuses on the overall improvement in system reliability after a certain unit in the system is repaired at a certain moment. Units with large contributions should be given priority in subsequent maintenance activities.

4. The mine car hardware reliability evaluation method according to claim 3, characterized in that: Contribution Indicates that, assuming the system has n units, the maintenance evaluation matrix It can be expressed as: Where, It represents the evaluation value of system component i under maintenance evaluation factor U. The weight of evaluation index can be determined by AHP method.

5. The mine car hardware reliability assessment method according to claim 1, wherein: It also includes the system reliability calculation steps: According to the reliability of parts and the importance of each level, the reliability of each level of system elements is calculated from the tree leaf node of the system structure layer by layer. Let the element of a certain layer be s, and the elements of the next layer be e1, e2, ..., em, the maintainability importance of s is ve, the maintainability importance of ei is Vi, the reliability of ei is Ri, and the adjustment coefficient , the reliability of s is 。

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