A weibull distribution electromechanical device usage availability determination method and system

Abstract

The application provides a kind of Weibull distribution electromechanical equipment use availability determination method and system, combine Weibull distribution parameter of electromechanical life and maintenance time consumption normal distribution calculation use availability, in the calculation process, for simplifying calculation step will Weibull distribution parameter be converted into the parameter under gamma distribution, calculate the working time of electromechanical equipment consumption different spare parts in three different situations;Three different situations include: maintenance and timely completion case, maintenance is not timely completed case and spare parts guarantee failure case.Finally, the application determines the use availability of electromechanical equipment based on the cumulative value of working time under three different conditions and the preset task time of electromechanical equipment, since the calculation process of the application considers the life distribution parameter of electromechanical unit and maintenance time consumption, the calculation reliability is relatively high, and the use availability obtained has high reference value, which helps to effectively evaluate the useable condition of electromechanical equipment under the current spare parts condition.

Description

Technical Field

[0001] This invention belongs to the field of equipment availability assessment, and more specifically, relates to a method and system for determining the availability of Weibull distributed electromechanical equipment. Background Technology

[0002] When electromechanical equipment malfunctions, repairs restore it to operation, enabling it to continue performing tasks. Spare parts for electromechanical equipment are a crucial maintenance resource and the material basis for maintenance work. Availability is the ratio of the actual cumulative working time of electromechanical equipment to the task time, reflecting the degree to which the equipment is operational during the task period. It is an important indicator for evaluating the effectiveness of spare parts support.

[0003] Patent document CN113065674A discloses a method, system, and electronic device for determining availability. It establishes a maintenance model based on multiple historical maintenance processes of a preset device, dividing maintenance delay times into three categories: spare parts supply delay time, maintenance technical data retrieval delay time, and maintenance procedure consultation delay time. Then, based on a preset delay time statistics table for the preset device, it determines the total maintenance delay time. Finally, it determines the availability of the preset device based on the total maintenance delay time, greatly simplifying the process of calculating availability. While the aforementioned patent document simplifies the availability calculation process, it does not consider the actual lifespan distribution and maintenance time distribution of electromechanical equipment when calculating availability, resulting in unreliable calculation results. Summary of the Invention

[0004] To address the shortcomings of existing technologies, the present invention aims to provide a method and system for determining the availability of Weibull distributed electromechanical equipment. This method addresses the problem that existing availability calculation methods do not incorporate the lifespan distribution and maintenance time distribution of electromechanical equipment, resulting in unreliable calculation results.

[0005] To achieve the above objectives, in a first aspect, the present invention provides a method for determining the availability of electromechanical equipment according to a Weibull distribution, wherein the electromechanical equipment includes multiple electromechanical components, and the lifetime of each electromechanical component follows a Weibull distribution, comprising the following steps:

[0006] Determine the task time of electromechanical equipment, the Welb distribution parameters of the life of each electromechanical component, and the number of spare parts for each electromechanical component; wherein, the maintenance time of each electromechanical component is not zero, and the maintenance time follows the same normal distribution;

[0007] The shape and dimensional parameters of each electromechanical component under the gamma distribution are obtained based on the gamma function and the lifetime Weibull distribution parameters of each electromechanical component; and the total number of spare parts for the electromechanical equipment is determined based on the number of spare parts for each unit in the multiple electromechanical components.

[0008] The first working time of the electromechanical equipment is obtained based on the shape and dimensional parameters of each electromechanical unit under the Weibull distribution, under the condition that the maintenance consumes 0 spare parts and the maintenance is completed in a timely manner; the first working time of the electromechanical equipment is obtained based on the shape and dimensional parameters of each electromechanical unit under the gamma distribution and the parameters of the normal distribution of the maintenance time, under the condition that the maintenance consumes non-zero spare parts and the maintenance is completed in a timely manner.

[0009] Based on the shape and dimensional parameters of each electromechanical component under the gamma distribution and the parameters of the normal distribution of maintenance time, the second working time of each electromechanical component is determined when the electromechanical equipment consumes non-zero spare parts and the maintenance is not completed in time. The second working times of all electromechanical components are then summed to obtain the total second working time when the electromechanical equipment consumes non-zero spare parts and the maintenance is not completed in time. Wherein, the second working time for each electromechanical component that consumes zero spare parts and the maintenance is not completed in time is 0.

[0010] Based on the shape and dimensional parameters of each electromechanical component under the gamma distribution and the parameters of the normal distribution of maintenance time, the third working time of each electromechanical component when the spare parts support fails under different quantities of spare parts consumed by the electromechanical equipment is determined, and the third working time of all electromechanical components is accumulated to obtain the total third working time of spare parts support failure under different quantities of spare parts consumed by the electromechanical equipment.

[0011] The first working time, the second working time, and the third working time corresponding to the increase of the number of spare parts consumed by electromechanical equipment from 0 to the total number of spare parts are added together, and the final sum is divided by the task time of the electromechanical equipment to obtain the availability of the electromechanical equipment during the task time. When the availability exceeds the preset value, it means that the spare parts quantity setting of each electromechanical component unit of the current electromechanical equipment meets the spare parts guarantee requirements.

[0012] In an optional example, let the task time be T, and the electromechanical equipment include n electromechanical units, the lifetime of the i-th electromechanical unit following a Weibull distribution W(u i ,v i ), u i v is the scale parameter of the Weibull distribution of the i-th electromechanical component unit. i The shape parameter of the Weibull distribution of the i-th electromechanical component unit is s; the number of spare parts for the i-th electromechanical component unit is s. iThe maintenance time of all electromechanical components follows a normal distribution N(c,d), where c is the mean of maintenance time and d is the root variance of maintenance time.

[0013] The shape parameter a of the i-th electromechanical component unit under the gamma distribution i and scale parameter b i They are respectively:

[0014]

[0015] In the formula, Γ() is the gamma function;

[0016] The total number of spare parts for the electromechanical equipment Let r be the number of spare parts consumed by electromechanical equipment, where 0 ≤ r ≤ sn, then the first working time Ts r for:

[0017]

[0018] In the formula, x represents the maintenance time variable, and q(x) represents the probability that the equipment consumes r spare parts under the condition that the maintenance is completed in a timely manner;

[0019] The steps for calculating q(x) are as follows:

[0020] (Q.1) Let the electromechanical component unit number i = 1;

[0021] (Q.2) Calculate the probability array Pd, where the probability array Pd includes S i +1 element, the value of each element is determined by the following formula:

[0022]

[0023] In the formula, t represents the time variable;

[0024] (Q.3) If i = 1, then let array pj = pd; otherwise, pj = pj * pd, where * is the convolution calculation symbol.

[0025] (Q.4) Update i = i + 1. If i ≤ n, then execute (Q.2); otherwise, let q(x) = pj. 1+r Among them, pj 1+r It is the (1+r)th element in array pj.

[0026] In an optional example, the total second working time Tf r The solution process is as follows:

[0027] (3.1) Let the electromechanical component unit number i = 1;

[0028] (3.2) Calculate the second working time Tft when the maintenance of the i-th electromechanical unit is not completed in time. i :

[0029]

[0030] In the formula, y represents the lifespan variable, and D j (y) represents the probability of electromechanical component j failing, and h(y) represents the probability of the equipment consuming r spare parts under the condition that maintenance is not completed in time;

[0031]

[0032] The steps for calculating h(y) are as follows:

[0033] (H.1) Let j = 1;

[0034] (H.2) Calculate the probability array pdd:

[0035] If j = i, the array pdd has s j There are 10 elements, and the value of each element is as follows:

[0036]

[0037] Otherwise, the array pdd has s j Add 1 more elements, each with the following value:

[0038]

[0039] (H.3) If j = 1, then let the array pjj = pdd; otherwise, pjj = pjj * pdd, where * is the convolution calculation symbol.

[0040] (H.4) Update j = j + 1. If j ≤ n, then execute (H.2); otherwise, let h(y) = pjj. r ;

[0041] (3.3) Update i = 1 + i. If i ≤ n, then execute (3.2); otherwise...

[0042] In an optional example, the total third working time tf r The solution process is as follows:

[0043] (5.1) Let the electromechanical component unit number i = 1;

[0044] (5.2) Calculate the third working time tft of the i-th electromechanical unit when the spare parts support fails when r spare parts are consumed by the electromechanical equipment. i :

[0045] In the formula

[0046]

[0047] Among them, F j (y) is the probability that unit j will fail, and V(y) is the probability that the equipment will consume r spare parts under the condition of failure.

[0048] The steps for calculating V(y) are as follows:

[0049] (V.1) Let j = 1;

[0050] (V.2) Calculate the probability array pD:

[0051] If j = i,

[0052] otherwise,

[0053]

[0054] (V.3) If j = 1, then let array pJ = pD; otherwise, pJ = pJ * pD, where * is the convolution calculation symbol.

[0055] (V.4) Update j = j + 1. If j ≤ n, then execute (V.2); otherwise, let...

[0056] (5.3) Update i = 1 + i. If i ≤ n, then execute (5.2); otherwise, let...

[0057] In an optional example, the use of availability

[0058] In a second aspect, the present invention provides a system for determining the availability of a Weibull-distributed electromechanical device, the electromechanical device comprising a plurality of electromechanical components, each of which has a lifetime following a Weibull distribution, comprising: at least one memory for storing a program; and at least one processor for executing the program stored in the memory, wherein when the program stored in the memory is executed, the processor is used to execute the method described in the first aspect or any possible example of the first aspect.

[0059] Thirdly, this application provides a computer-readable storage medium storing a computer program that, when run on a processor, causes the processor to perform the methods described in the first aspect or any possible example of the first aspect.

[0060] Fourthly, this application provides a computer program product that, when run on a processor, causes the processor to perform the method described in the first aspect or any possible example of the first aspect.

[0061] In summary, the technical solutions conceived by this invention have the following beneficial effects compared with the prior art:

[0062] This invention provides a method and system for determining the availability of electromechanical equipment using a Weibull distribution. It calculates availability by combining the Weibull distribution parameters of the electromechanical component's lifespan with the normal distribution of maintenance time. To simplify the calculation process, the Weibull distribution parameters are converted to parameters under a gamma distribution. The method calculates the working time of the electromechanical equipment consuming different spare parts under three different conditions: timely maintenance, untimely maintenance, and spare parts availability failure. Finally, this invention determines the availability of the electromechanical equipment based on the cumulative value of the working time under these three conditions and the preset task time of the electromechanical component. Because the calculation process of this invention considers the lifespan distribution parameters of the electromechanical component unit and maintenance time, the calculation reliability is relatively high, and the obtained availability has high reference value, helping to effectively assess the usability of electromechanical equipment under current spare parts conditions. Attached Figure Description

[0063] Figure 1 This is a flowchart of the method for determining the availability of Weibull distributed electromechanical equipment provided in an embodiment of the present invention;

[0064] Figure 2 This is a graph showing the availability of spare parts for a series of spare parts schemes, ranging from 1 to 17, calculated using three methods provided in this embodiment of the invention. Detailed Implementation

[0065] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0066] The terms "first" and "second," etc., used in the specification and claims of this invention are used to distinguish different objects, not to describe a specific order of objects. For example, "first response message" and "second response message," etc., are used to distinguish different response messages, not to describe a specific order of response messages.

[0067] In the embodiments of this application, the terms "exemplary" or "for example" are used to indicate that something is an example, illustration, or description. Any embodiment or design that is described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design. Specifically, the use of the terms "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0068] In the description of the embodiments of this application, unless otherwise stated, "multiple" means two or more, for example, multiple processing units means two or more processing units, multiple elements means two or more elements, etc.

[0069] Next, the technical solutions provided in the embodiments of this application will be described.

[0070] Figure 1 This is a flowchart of the method for determining the availability of Weibull distributed electromechanical equipment provided in an embodiment of the present invention; as follows: Figure 1 As shown, it includes the following steps:

[0071] S101, determine the task time of electromechanical equipment, the Welb distribution parameters of the life of each electromechanical component unit, and the number of spare parts for each electromechanical component unit; wherein, the maintenance time of each electromechanical component unit is not 0, and the maintenance time follows the same normal distribution.

[0072] S102, based on the gamma function and the lifetime Weibull distribution parameters of each electromechanical component, obtain the shape parameters and dimensional parameters of each electromechanical component under the gamma distribution; and determine the total number of spare parts for the electromechanical equipment based on the number of spare parts for each unit in the multiple electromechanical components.

[0073] S103, based on the shape and dimensional parameters of each electromechanical component unit under the Weibull distribution, the first working time of the electromechanical equipment under the condition that the maintenance consumes 0 spare parts and the maintenance is completed in a timely manner is obtained; based on the shape and dimensional parameters of each electromechanical component unit under the gamma distribution and the parameters of the normal distribution of the maintenance time, the first working time of the electromechanical equipment under the condition that the maintenance consumes non-zero spare parts and the maintenance is completed in a timely manner is obtained.

[0074] S104, based on the shape and scale parameters of each electromechanical component unit under the gamma distribution and the parameters of the normal distribution of maintenance time, determine the second working time of each electromechanical component unit when the electromechanical equipment consumes non-zero spare parts and the maintenance is not completed in time, and sum the second working times of all electromechanical component units to obtain the total second working time when the electromechanical equipment consumes non-zero spare parts and the maintenance is not completed in time; wherein, the second working time when each electromechanical component consumes zero spare parts and the maintenance is not completed in time is 0;

[0075] S105, based on the shape parameters and scale parameters of each electromechanical component unit under the gamma distribution and the parameters of the normal distribution of maintenance time, determine the third working time of each electromechanical component unit when the spare parts guarantee fails when the electromechanical equipment consumes different quantities of spare parts, and sum up the third working times of all electromechanical components to obtain the total third working time of spare parts guarantee failure when the electromechanical equipment consumes different quantities of spare parts.

[0076] S106, the first working time, the second working time, and the third working time corresponding to the increase of the number of spare parts consumed by the electromechanical equipment from 0 to the total number of spare parts are added together, and the final summation result is divided by the task time of the electromechanical equipment to obtain the availability of the electromechanical equipment during the task time; when the availability exceeds the preset value, it indicates that the spare parts quantity setting of each electromechanical component unit of the current electromechanical equipment meets the spare parts guarantee requirements.

[0077] It should be noted that the lifespan of electromechanical components generally follows a Weibull distribution, such as ball bearings, relays, switches, circuit breakers, magnetrons, potentiometers, gyroscopes, electric motors, aircraft generators, batteries, hydraulic pumps, air turbine engines, gears, valves, and fatigued parts. If a random variable follows a Weibull distribution W(u,v), where u is the scale parameter and v is the shape parameter, its probability density function is...

[0078] The electromechanical equipment of the present invention is composed of multiple electromechanical components of different types. When one of the components fails, it is regarded as a failure of the entire equipment. The equipment is repaired by replacing the faulty component.

[0079] In this invention, the task time T is known, and a certain electromechanical device consists of n electromechanical units, the lifetimes of which respectively follow a Weibull distribution W(u i ,v i The number of spare parts for each unit (s) i The maintenance time follows a normal distribution N(c,d), where c is the mean of the maintenance time and d is the root variance of the maintenance time.

[0080] This invention provides a method for accurately assessing the combined impact of maintenance time and spare parts quantity on availability, with the specific steps as follows:

[0081] (1) Determine the total quantity of spare parts The total number of spare parts consumed, r = 0, parameter parameter

[0082] In the formula, Γ() is the gamma function.

[0083] (2) Calculate the average time Ts for timely completion of maintenance. r

[0084]

[0085] The steps for calculating q(x) are as follows:

[0086] (Q.1) Let the unit number i = 1;

[0087] (Q.2) Calculate the probability array pd

[0088]

[0089] (Q.3) If i = 1, then let pj = pd; otherwise, pj = pj * pd, where * is the convolution calculation symbol.

[0090] (Q.4) Update i = i + 1. If i ≤ n, then execute (Q.2); otherwise, let q(x) = pj. 1+r .

[0091] (3) Calculate the average time Tf during which repairs are not completed in a timely manner. r

[0092] (3.1) Let i = 1;

[0093] (3.2) Calculate Tft i

[0094]

[0095]

[0096] The steps for calculating h(y) are as follows:

[0097] (H.1) Let j = 1;

[0098] (H.2) Calculate the probability array pd

[0099] If j = i,

[0100] otherwise,

[0101]

[0102] (H.3) If j = 1, then let pj = pd; otherwise, pj = pj * pd, where * is the convolution calculation symbol.

[0103] (H.4) Update j = j + 1. If j ≤ n, then execute (H.2); otherwise, let h(x) = pj. r .

[0104] (3.3) Update i = 1 + i. If i ≤ n, then execute (3.2); otherwise...

[0105] (4) Update r = r + 1. If r ≤ sn, execute (2). Otherwise, initialize the total number of spare parts consumed, r = 0.

[0106] (5) Calculate the mean time tf of the guarantee failure. r

[0107] (5.1) Let the unit number i = 1;

[0108] (5.2) Calculate tft i

[0109] In the formula

[0110]

[0111] The steps for calculating V(y) are as follows:

[0112] (V.1) Let j = 1;

[0113] (V.2) Calculate the probability array pd

[0114] If j = i, otherwise,

[0115]

[0116] If j = 1, then let pj = pd; otherwise, pj = pj * pd, where * is the convolution calculation symbol.

[0117] (V.4) Update j = j + 1. If j ≤ n, then execute (V.2); otherwise, let... (5.3) Update i = 1 + i. If i ≤ n, then execute (5.2); otherwise, let...

[0118] (5.4) Update r = r + 1. If r ≤ sn, execute (5), otherwise execute (6).

[0119] (6) Output availability

[0120] The following is a specific example: A certain electromechanical equipment consists of 4 identical electromechanical units. The lifespan of each electromechanical unit follows a normal distribution W(100,1.5), W(110,1.7), W(120,1.9), and W(130,2.1). The task time is 200 hours, and the time to repair the fault follows a normal distribution N(10,3). The number of spare parts for each unit is 4, 3, 2, and 1, respectively. Calculate the availability of the equipment at this time.

[0121] Solution: (1) Let the total number of spare parts be... The total number of spare parts consumed, r = 0, parameter a i The values ​​are: 2.169, 2.728, 3.337, and 3.995, respectively, with parameter b. i = respectively: 41.62, 35.98, 31.91, 28.82, 1≤i≤n;

[0122] Repeatedly execute (2) to (4) to calculate the average time Ts for timely completion of maintenance. r The average time Tf for untimely repairs r The calculation results are shown in Table 1.

[0123] Execute (5) multiple times to iterate and calculate the average time tf of the guarantee failure. r The calculation results are shown in Table 1:

[0124] Table 1

[0125]

[0126]

[0127] (6) Determine the availability of use Output Pa.

[0128] The availability of spare parts for the above examples was calculated using current industry methods that ignore maintenance time, the evaluation method of this invention that takes maintenance time into account, and simulation methods, respectively. The results are shown in [the table below]. Figure 2 Table 2.

[0129] Table 2. Availability Results of the Three Methods

[0130]

[0131] Compared to industry practices, Figure 2 Table 2 shows that the evaluation results and simulation results of this invention are in better agreement. Figure 2 It can also be seen that when maintenance takes a long time, the current industry method of ignoring the impact of maintenance time will lead to an "inflated" availability assessment result, and the resulting error should not be underestimated.

[0132] Based on the methods described in the above embodiments, this application provides a system for determining the availability of Weibull distributed electromechanical equipment. The system may include: at least one memory for storing a program and at least one processor for executing the program stored in the memory. When the program stored in the memory is executed, the processor performs the methods described in the above embodiments.

[0133] Based on the methods in the above embodiments, this application provides a computer-readable storage medium storing a computer program that, when run on a processor, causes the processor to execute the methods in the above embodiments.

[0134] Based on the methods in the above embodiments, this application provides a computer program product that, when run on a processor, causes the processor to execute the methods in the above embodiments.

[0135] It is understood that the processor in the embodiments of this application may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. A general-purpose processor may be a microprocessor or any conventional processor.

[0136] The method steps in the embodiments of this application can be implemented in hardware or by a processor executing software instructions. The software instructions can consist of corresponding software modules, which can be stored in random access memory (RAM), flash memory, read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), registers, hard disks, portable hard disks, CD-ROMs, or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor, enabling the processor to read information from and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and the storage medium can reside in an ASIC.

[0137] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted through the computer-readable storage medium. The computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid-state disk (SSD)).

[0138] It is understood that the various numerical designations used in the embodiments of this application are merely for descriptive convenience and are not intended to limit the scope of the embodiments of this application.

[0139] Those skilled in the art will readily understand that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for determining the availability of electromechanical equipment according to a Weibull distribution, wherein the electromechanical equipment comprises multiple electromechanical components, and the lifetime of each electromechanical component follows a Weibull distribution, characterized in that... Includes the following steps: Determine the task time of electromechanical equipment, the Welb distribution parameters of the life of each electromechanical component, and the number of spare parts for each electromechanical component; wherein, the maintenance time of each electromechanical component is not zero, and the maintenance time follows the same normal distribution; The shape and dimensional parameters of each electromechanical component under the gamma distribution are obtained based on the gamma function and the lifetime Weibull distribution parameters of each electromechanical component; and the total number of spare parts for the electromechanical equipment is determined based on the number of spare parts for each unit in the multiple electromechanical components. The first working time of the electromechanical equipment is obtained based on the shape and dimensional parameters of each electromechanical unit under the Weibull distribution, under the condition that the maintenance consumes 0 spare parts and the maintenance is completed in a timely manner; the first working time of the electromechanical equipment is obtained based on the shape and dimensional parameters of each electromechanical unit under the gamma distribution and the parameters of the normal distribution of the maintenance time, under the condition that the maintenance consumes non-zero spare parts and the maintenance is completed in a timely manner. Based on the shape and dimensional parameters of each electromechanical component under the gamma distribution and the parameters of the normal distribution of maintenance time, the second working time of each electromechanical component is determined when the electromechanical equipment consumes non-zero spare parts and the maintenance is not completed in time. The second working times of all electromechanical components are then summed to obtain the total second working time when the electromechanical equipment consumes non-zero spare parts and the maintenance is not completed in time. Wherein, the second working time for each electromechanical component that consumes zero spare parts and the maintenance is not completed in time is 0. Based on the shape and dimensional parameters of each electromechanical component under the gamma distribution and the parameters of the normal distribution of maintenance time, the third working time of each electromechanical component when the spare parts support fails under different quantities of spare parts consumed by the electromechanical equipment is determined, and the third working time of all electromechanical components is accumulated to obtain the total third working time of spare parts support failure under different quantities of spare parts consumed by the electromechanical equipment. The first working time, the second working time, and the third working time corresponding to the increase of the number of spare parts consumed by electromechanical equipment from 0 to the total number of spare parts are added together, and the final sum is divided by the task time of the electromechanical equipment to obtain the availability of the electromechanical equipment during the task time. When the availability exceeds the preset value, it means that the spare parts quantity setting of each electromechanical component unit of the current electromechanical equipment meets the spare parts guarantee requirements.

2. The method according to claim 1, characterized in that, Let the task time be T, and the electromechanical equipment include n electromechanical units. The lifetime of the i-th electromechanical unit follows a Weibull distribution W(u i ,v i ), u i v is the scale parameter of the Weibull distribution of the i-th electromechanical component unit. i The shape parameter of the Weibull distribution of the i-th electromechanical component unit is s; the number of spare parts for the i-th electromechanical component unit is s. i The maintenance time of all electromechanical components follows a normal distribution N(c,d), where c is the mean of maintenance time and d is the root variance of maintenance time. The shape parameter a of the i-th electromechanical component unit under the gamma distribution i and scale parameter b i They are respectively: In the formula, Γ() is the gamma function; The total number of spare parts for the electromechanical equipment Let r be the number of spare parts consumed by electromechanical equipment, where 0 ≤ r ≤ sn, then the first working time Ts r for: In the formula, x represents the maintenance time variable, and q(x) represents the probability that the equipment consumes r spare parts under the condition that the maintenance is completed in a timely manner; The steps for calculating q(x) are as follows: (Q.1) Let the electromechanical component unit number i = 1; (Q.2) Calculate the probability array Pd, where the probability array Pd includes S i +1 element, the value of each element is determined by the following formula: In the formula, t represents the time variable; (Q.3) If i = 1, then let array pj = pd; otherwise, pj = pj * pd, where * is the convolution calculation symbol. (Q.4) Update i = i + 1. If i ≤ n, then execute (Q.2); otherwise, let q(x) = pj. 1+r Among them, pj 1+r It is the (1+r)th element in array pj.

3. The method according to claim 2, characterized in that, The total second working time Tf r The solution process is as follows: (3.1) Let the electromechanical component unit number i = 1; (3.2) Calculate the second working time Tft when the maintenance of the i-th electromechanical unit is not completed in time. i : In the formula, y represents the lifespan variable, and D j (y) represents the probability of electromechanical component j failing, and h(y) represents the probability of the equipment consuming r spare parts under the condition that maintenance is not completed in time; The steps for calculating h(y) are as follows: (H.1) Let j = 1; (H.2) Calculate the probability array pdd: If j = i, the array pdd has s j There are 10 elements, and the value of each element is as follows: Otherwise, the array pdd has s j Add 1 more elements, each with the following value: (H.3) If j = 1, then let the array pjj = pdd; otherwise, pjj = pjj * pdd, where * is the convolution calculation symbol. (H.4) Update j = j + 1. If j ≤ n, then execute (H.2); otherwise, let h(y) = pjj. r ; (3.3) Update i = 1 + i. If i ≤ n, then execute (3.2); otherwise...

4. The method according to claim 3, characterized in that, The total third working time tf r The solution process is as follows: (5.1) Let the electromechanical component unit number i = 1; (5.2) Calculate the third working time tft of the i-th electromechanical unit when the spare parts support fails when r spare parts are consumed by the electromechanical equipment. i : In the formula Among them, F j (y) is the probability that unit j will fail, and V(y) is the probability that the equipment will consume r spare parts under the condition of failure. The steps for calculating V(y) are as follows: (V.1) Let j = 1; (V.2) Calculate the probability array pD: If j = i, otherwise, (V.3) If j = 1, then let array pJ = pD; otherwise, pJ = pJ * pD, where * is the convolution calculation symbol. (V.4) Update j = j + 1. If j ≤ n, then execute (V.2); otherwise, let... (5.3) Update i = 1 + i. If i ≤ n, then execute (5.2); otherwise, let...

5. The method according to claim 4, characterized in that, The availability of use 6. A system for determining the availability of electromechanical equipment according to a Weibull distribution, wherein the electromechanical equipment comprises multiple electromechanical units, and the lifetime of each electromechanical unit follows a Weibull distribution, characterized in that... include: At least one memory for storing programs; At least one processor is configured to execute a program stored in the memory, wherein when the program stored in the memory is executed, the processor is configured to perform the method as described in any one of claims 1-5.

7. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is run on the processor, it causes the processor to perform the method as described in any one of claims 1-5.

8. A computer program product, characterized in that, When the computer program product is run on a processor, the processor causes the processor to perform the method as described in any one of claims 1-5.

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