Optimization Method and System for Multi-Person Fault Location Based on the Least Expected Time Consumption Division

Abstract

The present invention discloses an optimization method and system for multi-person fault location based on the least expected time-consuming division, belonging to the field of multi-person fault location. The method includes: S1. Obtaining the total order of multi-person fault location; S2. According to the order of the total inspection order, taking out the first unit, dividing the unit among each maintenance personnel, and calculating the increase in fault location time-consuming caused by different divisions, selecting the maintenance personnel with the least increase in time-consuming, dividing the unit to this maintenance personnel, then taking out the next unit, repeating the above division operation until all units are taken out and divided among people, obtaining the multi-person fault location result with the least expected time-consuming division. The present invention realizes the rapid optimization of the fault location scheme and minimizes the fault location time-consuming as much as possible by optimizing the division of the units and order to be inspected.

Description

Technical Field

[0001] The present invention belongs to the field of multi-person fault location, and more specifically, relates to an optimization method and system for multi-person fault location based on the least expected time-consuming division. Background Art

[0002] As the functions of equipment / systems become more powerful and their performances become more advanced, the equipment / systems have become more and more complex. When a certain fault phenomenon occurs in a complex equipment / system, there may be numerous possible fault causes behind it, and the workload of finding the faulty unit is extremely large. Maintenance personnel are an important maintenance resource. In order to find the faulty parts as soon as possible within the specified time for subsequent repair work, a certain number of maintenance personnel need to be configured.

[0003] When fault location is carried out by multiple maintenance personnel, the basic problems faced are: how to divide the units each person is responsible for? How to determine the inspection order of these units? Generally speaking, different units each person is responsible for and different inspection orders result in different consumed times. Currently, there are two ways to solve these two problems: one is to rely on the personal experience of maintenance personnel to answer, and at this time, the quality of the fault location scheme is greatly affected by humans, and it is difficult to stably obtain a high-quality scheme; the other is to use traversal as the main means and combine other optimization techniques to search for an optimized scheme. This method is especially suitable when the total number of units to be inspected is not too large. The inspection order essentially belongs to a permutation problem. Therefore, when the number of units is n, the computational complexity based on traversal is the factorial of n (the total number of units is denoted as n). When facing the fault location of large systems and complex equipment, the value of n ranges from dozens to hundreds, and 10! has reached the order of millions. Therefore, there is an urgent need for a method to quickly optimize the fault location scheme. Summary of the Invention

[0004] Aiming at the defects of the prior art, the purpose of the present invention is to provide an optimization method and system for multi-person fault location based on the least expected time-consuming division, aiming to solve the problem of how to achieve fast optimization of fault location.

[0005] To achieve the above purpose, in the first aspect, the present invention provides an optimization method for multi-person fault location based on the least expected time-consuming division, and the method includes:

[0006] S1. Obtain the total order of multi-person fault location;

[0007] S2. According to the order of the total inspection order, take out the first unit, divide this unit among each maintenance personnel, and calculate the increase in fault location time caused by different divisions. Select the maintenance personnel with the least increase in time consumption, divide this unit among this maintenance personnel, then take out the next unit, and repeat the above division operation until all units are taken out and divided among people, so as to obtain the multi-person fault location result with the least expected time-consuming division.

[0008] Preferably, step S2 includes:

[0009] S21. Initialize the inspection serial number i = 1 + m, initialize the elements of the first column of matrix zM to be 1 to m respectively, and the elements of the first column of matrix dM to be zInd1 to zInd m in sequence. Record that the initial values of each element in the array mdn representing the number of units responsible for each maintenance personnel are all 1. The elements in dM are unit numbers, the elements in zM are the serial numbers of zInd, m represents the number of maintenance personnel, and zInd represents the total order;

[0010] S22. Initialize the serial number j = 1;

[0011] S23. Initialize the temporary array ct = [zM(j, 1:mdn j )i], where zM(j, 1:mdn j ) represents the first mdn j elements of the j-th row vector of matrix zM;

[0012] S24. Calculate the fault location time-consuming of the inspection order ct according to the temporary arrays ct, td, and v, and save its output result tx to mtc j , that is, let mtc j = tx, where td and v represent the inspection time and troubleshooting weight coefficient of each unit based on the total order;

[0013] S25. Update the serial number j = 1 + j. If j ≤ m, enter S23; otherwise, enter S26;

[0014] S26. Find the minimum value in the array mtc, and record its serial number as im. Update mdn im = mdn im + 1, zM(im, mdn im ) = i, dM(im, mdn im ) = zInd i ;

[0015] S27. Update i = 1 + i. If i ≤ n, enter S22; otherwise, enter S28, where n represents the number of units;

[0016] S28. Rearrange the elements in the array mdn in ascending order, save the corresponding serial numbers of the sorting results to I, return the sorting results to mdn, and update the row vectors of matrix zM and matrix dM according to the order I, that is, zM = zM(I, :), dM = dM(I, :).

[0017] Preferably, the method further includes:

[0018] S3. Calculate the fault location time Tx of the optimization solution, specifically as follows:

[0019] S31. Initialize the serial number j = 1;

[0020] S32. Sequentially find all non-zero elements from the j-th row vector of the matrix zM and place them in the temporary array ct;

[0021] S33. Calculate the fault location time of the inspection sequence ct according to the temporary arrays ct, td, and v, and save its output result tx to mtc j , that is, mtc j = tx;

[0022] S34. Update the serial number j = 1 + j. If j ≤ m, enter S32. Otherwise, calculate Output the solution matrix dM and Tx.

[0023] Preferably, calculating the fault location time of the inspection sequence ct includes:

[0024] 1) Initialize the serial number id = 1, the inspection time tx = 0, and record the number of elements in the array ct as cL;

[0025] 2) Initialize the inspection serial number k = ct id , the inspection time tu id = td k , the weight coefficient u id = v k , update

[0026] 3) Update id = id + 1. If id ≤ cL, enter 2). Otherwise, output tx.

[0027] Preferably, the method further includes any one of the following: 1) Output the number of maintenance personnel closest to the expected fault troubleshooting time requirement in ascending order of the number of maintenance personnel; 2) Output the number of people who do not exceed the expected labor cost requirement and have the shortest time in ascending order of the number of maintenance personnel; 3) Output the number of people with the shortest time in ascending order of the number of maintenance personnel.

[0028] Preferably, the types of the units are the same or different, and the types include: electronic units, mechanical units, or electromechanical units.

[0029] To achieve the above object, in a second aspect, the present invention provides a multi-person fault location optimization system based on the least expected time division, including: a processor and a memory; the memory is used to store computer execution instructions; the processor is used to execute the computer execution instructions so that the method described in the first aspect is executed.

[0030] Generally speaking, compared with the prior art, the above technical solution conceived by the present invention has the following beneficial effects:

[0031] The present invention proposes an optimization method and system for multi-person fault location based on the least expected time-consuming division. According to the order of the total inspection order, the first unit is taken out, divided among each maintenance personnel, and the increase in fault location time-consuming caused by different divisions is calculated. The maintenance personnel with the least increase in time-consuming is selected, and the unit is divided among this maintenance personnel. Then the next unit is taken out, and the above division operation is repeated until all units are taken out and divided among people, obtaining the multi-person fault location result with the least expected time-consuming division. The present invention realizes rapid optimization of the fault location scheme and minimizes the fault location time-consuming as much as possible by optimizing the division of units to be inspected and the order. Description of the Drawings

[0032] Figure 1 It is a flowchart of an optimization method for multi-person fault location based on the least expected time-consuming division provided by the present invention.

[0033] Figure 2 It is the situation of 1000 random schemes provided by an embodiment of the present invention. Detailed Embodiment

[0034] In order to make the purpose, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0035] Figure 1 It is a flowchart of an optimization method for multi-person fault location based on the least expected time-consuming division provided by the present invention. As Figure 1 shown, the method includes:

[0036] Step S1. Obtain the total order of multi-person fault location.

[0037] The method for obtaining the total order of multi-person fault location is not limited, and can be artificially specified, or a total order optimization method, preferably, a total order optimization method based on equivalent inspection time, or a total order optimization method based on a comprehensive value.

[0038] Preferably, the types of the units are the same or different, and the types include: electronic units, mechanical units or electromechanical units.

[0039] The present invention stipulates that: (1) A certain equipment consists of multiple units. For the convenience of description, the life of each unit is described by time. (2) At any moment, at most one unit fails. When a certain unit fails, it will affect the normal operation of the equipment, and some failure phenomena will occur in the equipment. At this time, repair work needs to be carried out. (3) When confirming the failure, the order of checking the status of these units is independent and irrelevant, that is: there is no situation where there is a specific requirement for the checking order such as "unit A must be checked first and then unit B". (4) The life distribution law of each unit, the time consumed for checking the status (normal or not) of each unit, and the time of the upcoming task are known. (5) Each maintenance personnel has the ability to check all units, but each person can only check one unit at a time. (6) All maintenance personnel start checking at the same time; after a maintenance personnel completes the inspection of a unit and its status is normal, they continue to check the next unit in the inspection order; when a person checks out a faulty unit, the inspection stops, and the subsequent process enters the repair stage of the faulty part.

[0040] Taking an electronic device as an example in the present invention, the life of electronic units follows an exponential distribution Exp(u). The physical meaning of the parameter u is the mean life, and the probability density function of the exponential distribution is The relevant variable conventions are as follows: The number of maintenance personnel is denoted as m; the number of units is denoted as n; the life of unit i follows an exponential distribution Exp(u i ); the time consumed for checking the status of unit i is denoted as tc i ; the task time is denoted as Tw. These variables are all known quantities.

[0041] Step S2. According to the order of the total inspection order, take out the first unit, divide this unit among each maintenance personnel, and calculate the increase in the failure location time caused by different divisions. Select the maintenance personnel with the least increase in time consumption, divide this unit among this maintenance personnel, then take out the next unit, and repeat the above division operation until all units are taken out and divided among people, obtaining the multi-person failure location result with the least expected time consumption.

[0042] In the present invention, the array composed of the unit numbers checked in sequence during failure location is called the inspection order (abbreviation: order), and the units responsible for each person to check and their inspection order are called the failure location plan (abbreviation: plan).

[0043] Preferably, step S2 includes:

[0044] S21. Initialize the inspection serial number i = 1 + m, initialize the elements of the first column of the matrix zM to be 1 to m respectively, and the elements of the first column of the matrix dM are correspondingly zInd1 to zInd m, the initial value of each element in the array mdn recording the number of units responsible for each maintenance personnel is 1. The elements in dM are unit numbers, the elements in zM are the sequence numbers of zInd, m represents the number of maintenance personnel, and zInd represents the total order;

[0045] S22. Initialize the sequence number j = 1;

[0046] S23. Initialize the temporary array ct = [zM(j, 1:mdn j )i], zM(j, 1:mdn j ) represents the first mdn j elements of the j-th row vector of the matrix zM;

[0047] S24. Calculate the fault location time-consuming of the inspection order ct according to the temporary arrays ct, td, and v, and save its output result tx to mtc j , that is, let mtc j = tx, td and v represent the inspection time and troubleshooting weight coefficient of each unit based on the total order;

[0048] S25. Update the sequence number j = 1 + j. If j ≤ m, enter S23, otherwise, enter S26;

[0049] S26. Find the minimum value in the array mtc, and record its sequence number as im. Update mdn im = mdn im + 1, zM(m, mdn im ) = i, dM(im, mdn im ) = zInd i ;

[0050] S27. Update i = 1 + i. If i ≤ n, enter S22, otherwise, enter S28, where n represents the number of units;

[0051] S28. Rearrange the elements in the array mdn in ascending order, save the corresponding sequence numbers of the sorting results to I, return the sorting results to mdn, and update the row vectors of the matrix zM according to the order I, and update the row vectors of the matrix dM according to the order I, that is, zM = zM(I, :), dM = dM(I, :).

[0052] Preferably, the method further includes: Step S3. Calculate the fault location time-consuming Tx of the optimization plan. Specifically as follows:

[0053] S31. Initialize the sequence number j = 1;

[0054] S32. Sequentially find all non-zero elements from the j-th row vector of the matrix zM and place them in the temporary array ct;

[0055] S33. Calculate the fault location time consumption of the inspection sequence ct based on the temporary arrays ct, td, and v, and save the output result tx to mtc j , that is, mtc j = tx;

[0056] S34. Update the serial number j = 1 + j. If j ≤ m, enter S32; otherwise, calculate Output the solution matrix dM and Tx.

[0057] Preferably, the calculation of the fault location time consumption of the inspection sequence ct includes:

[0058] 1) Initialize the serial number id = 1, the inspection time consumption tx = 0, and record the number of elements in the array ct as cL;

[0059] 2) Initialize the inspection serial number k = ct id , the inspection time tu id = td k , the weight coefficient u id = v k , and update

[0060] 3) Update id = id + 1. If id ≤ cL, enter 2); otherwise, output tx.

[0061] Preferably, the method further includes any one of the following: 1) Output the number of maintenance personnel closest to the expected fault troubleshooting time requirement in ascending order of the number of maintenance personnel; 2) Output the number of people who do not exceed the expected labor cost requirement and have the shortest time in ascending order of the number of maintenance personnel; 3) Output the number of people with the shortest time in ascending order of the number of maintenance personnel.

[0062] The present invention also provides a multi-person fault location optimization system based on the least expected time consumption division, including: a processor and a memory; the memory is used to store computer execution instructions; the processor is used to execute the computer execution instructions so that the above method is executed.

[0063] Embodiment

[0064] It is known that a certain component is composed of 20 electronic units, the task time is 100 hours, and there are 4 maintenance personnel. The relevant information is shown in Table 1. Using the above method, optimize and formulate a fault location plan, and calculate the average fault location time of this plan.

[0065] Table 1

[0066]

[0067]

[0068] 1) Traverse and calculate the probability of failure Pf for each unit, and the results are shown in Table 2.

[0069] 1.1) Let i = 1.

[0070] 1.2) Integrate and calculate Pf i , let

[0071] When k = i,

[0072] When k ≠ i,

[0073] 2) Traverse and calculate the weight coefficient w according to the unit number, and the results are shown in Table 2.

[0074] 2.1) Let i = 1;

[0075] 2.2)

[0076] 2.3) Let i = i + 1. If i ≤ n, execute 2.2), otherwise, execute 3).

[0077] 3) Determine the basic inspection order zInd, and the results are shown in Table 2.

[0078] 3.1) Let it store the unit numbers from 1 to n. The current number of elements in array A is denoted as nA, and let the number i = 1.

[0079] 3.2) When nA ≥ 2, execute 3.2.1), otherwise, execute 3.3).

[0080] 3.2.1) Let the unit number k = A1, the optimized inspection order array zInd i = A1, the intermediate variable a = tc k , b = w k , and let j = 2;

[0081] 3.2.2) Let the unit number k = A j , the intermediate variable c = tc k , d = w k ;

[0082] 3.2.3) If ad > bc holds, then update zInd i = k, a = c, b = d, and then execute 3.2.4); otherwise, directly execute 3.2.4).

[0083] 3.2.4) Let j = j + 1. If j ≤ nA, execute 3.2.2), otherwise, execute 3.2.5);

[0084] 3.2.5) Put zInd iDelete from A, set nA = nA - 1, set i = i + 1, and execute 3.2).

[0085] 3.3) Set zInd i = A1. The array zInd stores the numbers of each unit.

[0086] 4) Calculate the intermediate variables td and v according to zInd. The results are shown in Table 2.

[0087] 4.1) Set i = 1.

[0088] 4.2) Set k = zInd i , td i = tc k , v i = w k .

[0089] 4.3) Set i = i + 1. If i ≤ n, execute 4.2), otherwise, execute 5).

[0090] Table 2

[0091]

[0092]

[0093] 5) Divide the repair units for each repairman and determine the inspection order. The relevant results are saved in the matrices dM and zM.

[0094] 5.1) Set the inspection serial number i = 1 + m. The elements in the first column of the intermediate matrix zM are 1 to m respectively, and the elements in the first column of the scheme matrix dM are zInd1 to zInd m correspondingly in sequence. The initial values of the elements in the array mdn recording the number of units responsible for each repairman are all 1.

[0095] 5.2) Set the serial number j = 1.

[0096] 5.3) Set the temporary array ct = [zM(j, 1:mdn j )i]. zM(j, 1:mdn j ) are the first mdn j elements of the j-th row vector of the matrix zM.

[0097] 5.4) Input the temporary array ct, td, v, call the module S, and save its output result tx to mtc j , that is, set mtc j = tx.

[0098] 5.5) Set the serial number j = 1 + j. If j ≤ m, execute 5.3), otherwise, execute 5.6).

[0099] 5.6) Find the minimum value in the array mtc, and record its serial number as im. Let mdn im = mdn im + 1, zM(im, mdn im ) = i, dM(im, mdn im ) = zInd i .

[0100] 5.7) Let i = 1 + i. If i ≤ n, execute 5.2); otherwise, execute 6).

[0101] 6) Rearrange the elements in the array mdn in ascending order, and save the serial numbers corresponding to the sorting results into I = 1, 3, 2, 4. Rearrange mdn to 4, 4, 5, 7: Let the row vectors of the matrix zM be rearranged and updated in the order of I, and the row vectors of the solution matrix dM be rearranged and updated in the order of I. The result of zM is shown in Table 3, and the result of dM is shown in Table 4.

[0102] Table 3

[0103]

[0104] Table 4

[0105]

[0106] 7) Calculate the fault location time Tx of the optimized solution as 45.0.

[0107] 7.1) Let the serial number j = 1.

[0108] 7.2) Sequentially find all non-zero elements from the j-th row vector of the matrix zM and place them in the temporary array ct.

[0109] 7.3) Input the temporary arrays ct, td, v, and call module S, and save its output result tx into mtc j , that is, let mtc j = tx.

[0110] 7.4) Let the serial number j = 1 + j. If j ≤ m, execute 7.2); otherwise, let execute 8).

[0111] 8) After optimization, output the solution matrix dM and Tx. From dM, the optimized solution is as follows: Maintenance personnel 1 is responsible for sequentially inspecting units 8, 7, 6, 14; maintenance personnel 2 is responsible for sequentially inspecting units 12, 19, 17, 1; maintenance personnel 3 is responsible for sequentially inspecting units 11, 13, 20, 16, 18; maintenance personnel 4 is responsible for sequentially inspecting units 10, 15, 2, 4, 5, 3, 9. The average fault location time of this solution is 45.0 minutes.

[0112] The input parameters of module S are ct, td, and v, which are used to calculate the fault location time-consuming for checking sequence ct, specifically as follows:

[0113] 1) Let id = 1, tx = 0, and the number of elements in array ct be denoted as cL;

[0114] 2) Let k = ct id , tu id = td k , u id = v k ,

[0115] 3) Let id = id + 1. If id ≤ cL, then execute S.2); otherwise, output tx.

[0116] A simulation model can be established to verify the correctness of the above method. The simulation model is briefly described as follows:

[0117] (1) Generate n random numbers simT i , 1 ≤ i ≤ n, and simT i obeys the lifetime distribution law of unit i.

[0118] (2) Find the minimum number among all simT i , and the corresponding serial number is denoted as g, that is: simT g ≤ simT i , 1 ≤ i ≤ n.

[0119] (3) If simT g < Tw holds, then this simulation is valid. According to the serial number g and the inspection sequence of each person in the plan, determine which repairman finds the faulty part, and the fault location time of this simulation can be obtained.

[0120] After a large number of simulations, the average fault location time can be statistically obtained. The simulation result of the average fault location time of the above optimization plan is 46.1, which is extremely consistent with the result of this method.

[0121] In the above example, one million plans are randomly generated, and the fault location time-consuming of these plans is simulated. The minimum time-consuming is 60.1, the average time-consuming is 142.3, and the root variance of the time-consuming is 48.2. Figure 2 This is the situation of 1000 random plans provided in the embodiment of the present invention. Figure 2 A large number of simulation results in

[0122] Those skilled in the art can easily understand that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent replacements, and improvements made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. An optimization method for multi - person fault location based on the least expected time - consuming division, characterized in that, The method includes: S1. Obtain the total order of multi-person fault location; S2. According to the order of the total inspection order, take out the first unit, divide the unit among each maintenance personnel, calculate the increase in fault location time caused by different divisions, select the maintenance personnel with the least increase in time consumption, divide the unit among this maintenance personnel, then take out the next unit, and repeat the above division operation until all units are taken out and divided among people, obtaining the multi-person fault location result with the least expected time consumption; Step S2 includes: S21. Initialize the inspection sequence number , initialize the matrix The elements of the first column of are 1 to respectively, and the elements of the first column of matrix ~ are correspondingly in sequence as . Initialize the elements of the array recording the number of units responsible for each maintenance personnel to 1. The elements in dM are unit numbers, and the elements in zM are the sequence numbers of zInd. represents the number of maintenance personnel, and zInd represents the total order; S22. Initialize the serial number ; S23. Initialize the temporary array , represents the matrix the first elements of the row vector; S24. Calculate the troubleshooting time of the inspection order and and from the temporary array, and output the result to save it to That is, let , and represent the inspection time and troubleshooting weight coefficient of each unit based on the total order; S25. Update serial number If , go to S23; otherwise, go to S26; S26. Find the minimum value in the array and record its serial number as , update , , ; S27. Update If , go to S22; otherwise, go to S28. Indicates the number of units; S28. Rearrange the elements in the array in ascending order, and save the corresponding serial numbers of the sorting results into , return the sorting result to , and make the row vectors of the matrix be rearranged and updated in the order of , and the row vectors of the matrix be rearranged and updated in the order of , that is , .

2. The method according to claim 1, wherein The method further includes: S3. Calculate the fault location time of the optimization solution , which is specifically as follows: S31. Initialize the serial number ; S32. From the matrix find all non-zero elements in the row vectors in sequence and place them in the temporary array ; S33. Calculate the troubleshooting time of the inspection order according to the temporary array , , , and output the result of the troubleshooting time to and save it to , that is ; S34. Update serial number If , enter S32; otherwise, calculate , and output the solution matrix and .

3. The method according to claim 1 or 2, characterized in that, The described calculation check order The fault location time-consuming, including: 1) Initialize the serial number , check the time-consuming , the array The number of elements in is denoted as ; 2) Initialize the check sequence number , check time , weight coefficient , update ; 3) Update If , go to 2), otherwise, output .

4. The method according to claim 2, wherein The method further includes any one of the following: 1) From the smallest to the largest number of maintenance personnel, output the number of maintenance personnel closest to the expected fault troubleshooting time requirement; 2) From the smallest to the largest number of maintenance personnel, output the number of people that does not exceed the expected labor cost requirement and has the shortest time; 3) From the smallest to the largest number of maintenance personnel, output the number of people with the shortest time.

5. The method according to claim 1, characterized in that The types of the units are the same or different, and the types include: electronic units, mechanical units, or electromechanical units.

6. A multi - person fault location optimization system based on the least expected time - consuming division, characterized in that, It includes: A processor and a memory; The memory is used to store computer execution instructions; The processor is used to execute the computer execution instructions, so that the method described in any one of claims 1 to 5 is executed.

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