A multi-person fault localization optimization method and system based on equivalent checking time

Abstract

The application discloses a multi-person fault positioning optimization method and system based on equivalent checking time and belongs to the field of multi-person fault positioning. The method comprises the following steps: acquiring the state checking consumption time of each unit and the probability of fault occurrence in the task time, taking the ratio of the state checking consumption time and the probability of fault occurrence in the task time as the equivalent checking time of the unit; and arranging the units in ascending order according to the equivalent checking time of each unit to serve as the total checking sequence after multi-person fault positioning optimization. The application can quickly and effectively formulate a fault positioning scheme, accurately estimate the probability distribution of fault positioning time consumption, reduce the average fault positioning time, balance the workload of maintenance personnel and maximize the work efficiency of the maintenance personnel.

Description

Technical Field

[0001] This 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 equivalent inspection time. Background Technology

[0002] When equipment malfunctions, fault location is generally the first step before repair work begins. "Fault location" refers to identifying the failed component that caused the malfunction. As equipment / systems become more powerful and advanced, they also become increasingly complex. When a complex equipment / system exhibits a malfunction, there are numerous possible causes, making the task of locating the faulty unit extremely demanding. Maintenance personnel are a crucial resource; a certain number of personnel are needed to quickly locate the faulty component and initiate subsequent repairs. With the same number of personnel, different inspection sequences generally result in different timeframes.

[0003] When there are many possible causes of failure, the number of possible inspection sequences is staggering. For example, if 10 units need to be inspected, the total number of permutations exceeds 3.6 million, making it difficult to effectively optimize the inspection sequence through traversal. Currently, determining the inspection sequence reasonably and effectively often relies on the personal experience of maintenance personnel. There is an urgent need for a solution that is less time-consuming and distributes the workload of fault location evenly among maintenance personnel. Summary of the Invention

[0004] To address the shortcomings of existing technologies, the present invention aims to provide a multi-person fault location optimization method and system based on equivalent inspection time, which aims to solve the problem of how to formulate a fault location plan that consumes less time and distributes the workload of maintenance personnel evenly.

[0005] To achieve the above objectives, in a first aspect, the present invention provides a multi-person fault location optimization method based on equivalent inspection time, the method comprising:

[0006] S1. Obtain the state check consumption time and the probability of failure during the task time for each unit, and use the ratio of the state check consumption time to the probability of failure during the task time as the equivalent check time for that unit.

[0007] S2. Based on the equivalent inspection time of each unit, arrange each unit in ascending order as the overall inspection order after multi-person fault location optimization.

[0008] Preferably, the method includes:

[0009] S3. Following the overall inspection order, and adopting the principle of balancing the inspection workload of each person, the unit is divided into units and assigned to people in sequence to obtain the inspection order of each person.

[0010] Preferably, step S3 includes:

[0011] S31. Initialize the check index i = 1 + m, and initialize each element in the first column of matrix dM as dM(i, 1) = itp. i The array mdn records the number of units each maintenance worker is responsible for. Each element in the array mdn is initially set to 1. The matrix dM has m rows and stores the unit number. m represents the number of maintenance workers. The array itp represents the optimized total inspection order.

[0012] S32. Initialize personnel serial number j = 1;

[0013] S33. Initialize the temporary array ct = dM(j, 1: mdn) j ), dM(j, 1: mdn j ) is the first mdn of the vector in the j-th row of matrix dM. j One element;

[0014] S34. The workload mt for calculating the temporary array ct j ,include:

[0015] S341. Initialize the temporary array ct to index id = 1, mt j =0, the number of elements in array ct is denoted as cL;

[0016] S342. Initialize unit number k = ct id Update MT j =mt j +tc k The array tc represents the time taken to check the status of each unit;

[0017] S343. Update id = id + 1. If id ≤ cL, proceed to S342; otherwise, proceed to S35.

[0018] S35. Update the sequence number j = 1 + j. If j ≤ m, proceed to S33; otherwise, proceed to S36.

[0019] S36. Find the minimum value in the workload array mt, denoted as im, and update mdn. im =mdn im +1, dM(im, mdn) im )=itp i ;

[0020] S37. Update i = 1 + i. If i ≤ n, proceed to S32, where n represents the number of units in the complex device.

[0021] Preferably, the method further includes:

[0022] S4. Calculate the troubleshooting completion time and its probability, and the average troubleshooting time per person;

[0023] S5. By accumulating the average troubleshooting time for each person, the average troubleshooting time for multiple people is obtained; by using the ascending order of troubleshooting completion time, the probability distribution of troubleshooting time is obtained.

[0024] Preferably, step S4 includes:

[0025] S41. Initialize the check sequence number i = 0, and the personnel sequence number j = 1;

[0026] S42. Initialize the average fault location time tm for personnel j. j =0, and assign values ​​from 1 to mdn in the j-th row vector of matrix dM. j The elements are placed in a temporary array ct. The matrix dM has m rows and stores the unit numbers, where m represents the number of maintenance personnel.

[0027] S43. Calculate the average fault location time tm for personnel j. j and workload mt j ,include:

[0028] S431. Initialize tm j =0, the index id of the temporary array ct is 1;

[0029] S432. Update i = i + 1, cell number k = ct id Temporary time array tu id =tc k , Fault location completion time tm j =tm j +pd i td i ;

[0030] S433. Update id = id + 1 if id ≤ mdn j Enter S432; otherwise, the workload of personnel j is mt. j =td i Then enter S44;

[0031] S44. Update sequence number j = 1 + j. If j ≤ m, proceed to S42; otherwise, proceed to S5.

[0032] Preferably, step S5 includes:

[0033] S51. Calculate the mean fault location time for this scheme.

[0034] S52. Sort the elements in array td in ascending order, store the sorting result in tx, and record the element index corresponding to the sorting result in im;

[0035] S53. Calculate the probability array px based on im, and denote the number of elements in array td as nd. Initialize i = 1, including:

[0036] S531. Initialize unit number k = im i pt i =pd k pd represents the conditional probability array, used to calculate probabilities.

[0037] S532. Update i = i + 1. If i ≤ nd, proceed to S531. Otherwise, output the relevant variables of the optimized solution.

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

[0039] To achieve the above objectives, in a second aspect, the present invention provides a multi-user fault location optimization system based on equivalent check time, comprising: a processor and a memory; the memory being used to store computer execution instructions; and the processor being used to execute the computer execution instructions, causing the method described in the first aspect to be executed.

[0040] In summary, the technical solutions conceived by this invention have the following beneficial effects compared with the prior art:

[0041] This invention discloses a multi-person fault location optimization method and system based on equivalent inspection time. It proposes to use the ratio of the state inspection time to the probability of a fault occurring within the task time as the equivalent inspection time of the unit. Based on the equivalent inspection time of each unit, the units are arranged in ascending order as the overall inspection order after multi-person fault location optimization. This method can quickly and effectively formulate fault location plans, accurately estimate the probability distribution of fault location time, reduce the average fault location time, balance the workload of maintenance personnel, and maximize the work efficiency of maintenance personnel. Attached Figure Description

[0042] Figure 1 The flowchart of a multi-person fault location optimization method based on equivalent inspection time provided by the present invention is shown.

[0043] Figure 2 The simulation method and the method of the present invention provided for the embodiments of the present invention yield the tx and px results.

[0044] Figure 3 The average fault location time is provided for 1000 random schemes in the embodiments of the present invention.

[0045] Figure 4 The differences in personnel work among these randomized schemes provided in the embodiments of the present invention. Detailed Implementation

[0046] 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.

[0047] Figure 1 The flowchart illustrates a multi-user fault location optimization method based on equivalent check time, provided by this invention. Figure 1 As shown, the method includes:

[0048] Step S1. Obtain the status check time and the probability of failure during the task time for each unit. Use the ratio of the status check time to the probability of failure during the task time as the equivalent check time for that unit.

[0049] Preferably, the units are of the same or different types, including electronic units, mechanical units, or electromechanical units.

[0050] Step S2. Arrange the units in ascending order according to their equivalent inspection time, and use this as the overall inspection order after multi-person fault location optimization.

[0051] Preferably, the method includes: S3. According to the overall inspection order, the unit is divided into people in sequence according to the principle of balancing the inspection workload of each person, so as to obtain the inspection order of each person.

[0052] Preferably, step S3 includes:

[0053] S31. Initialize the elements in the first column of matrix dM: dM(i, 1) = itp i The array mdn records the number of units each maintenance worker is responsible for. Each element in the array mdn is initialized to 1. The initial inspection sequence number i = 1 + m is initialized. The matrix dM has m rows and stores the unit number. m represents the number of maintenance workers. The array itp represents the optimized total inspection sequence.

[0054] S32. Initialize personnel serial number j = 1;

[0055] S33. Initialize the temporary array ct = dM(j, 1: mdn) j ), dM(j, 1: mdn j ) is the first mdn of the vector in the j-th row of matrix dM. j One element;

[0056] S34. The workload mt for calculating the temporary array ct j ,include:

[0057] S341. Initialize id = 1, mt j =0, the number of elements in array ct is denoted as cL;

[0058] S342. Initialize k = ct jd ,mt j =mt j +tc k ;

[0059] S343. Update id = id + 1. If id ≤ cL, proceed to S342; otherwise, proceed to S35.

[0060] S35. Update the sequence number j = 1 + j. If j ≤ m, proceed to S33; otherwise, proceed to S36.

[0061] S36. Find the minimum value in the workload array mt, denoted as im, and update mdn. im =mdn im +1, dM(im, mdn) im )=itp i ;

[0062] S37. Update i = 1 + i. If i ≤ n, proceed to S32, where n represents the number of units in the complex device.

[0063] Preferably, the method further includes: step S4. Calculating the fault investigation completion time and its probability, and the average troubleshooting time per person.

[0064] Preferably, step S4 includes:

[0065] S41. Initialize the check sequence number i = 0, and the personnel sequence number j = 1;

[0066] S42. Initialize the average fault location time tm for personnel j. j =0, and assign values ​​from 1 to mdn in the j-th row vector of matrix dM. j The elements are placed in a temporary array ct. The matrix dM has m rows and stores the unit numbers, where m represents the number of maintenance personnel.

[0067] S43. Calculate the average fault location time tm for personnel j. j and workload mt j ,include:

[0068] S431. Initialize tm j =0, id=1;

[0069] S432. Update i = i + 1, cell number k = ctid Temporary time array tu id =tc k The conditional probability of finding the faulty component during the i-th inspection. Fault location completion time tm j =tm j +pd i td i ;

[0070] S433. Update id = id + 1 if id ≤ mdn j Enter S432; otherwise, the workload of personnel j is mt. j =td i Then enter S44;

[0071] S44. Update sequence number j = 1 + j. If j ≤ m, proceed to S42; otherwise, proceed to S5.

[0072] Step S5. By accumulating the average troubleshooting time for each person, the average troubleshooting time for multiple people is obtained; by using the ascending order of troubleshooting completion time, the probability distribution of troubleshooting time is obtained.

[0073] Preferably, step S5 includes:

[0074] S51. Calculate the mean fault location time for this scheme.

[0075] S52. Sort the elements in array td in ascending order, store the sorting result in tx, and record the element index corresponding to the sorting result in im;

[0076] S53. Calculate the probability array px based on im, and denote the number of elements in array td as nd. Initialize i = 1, including:

[0077] S531. Initialize k = im i pt i =pd k Calculate the probability

[0078] S532. Update i = i + 1. If i ≤ nd, proceed to S531. Otherwise, output the relevant variables of the optimized solution.

[0079] This invention provides a multi-user fault location optimization system based on equivalent check time, comprising: a processor and a memory; the memory for storing computer execution instructions; and the processor for executing the computer execution instructions, thereby causing the above-described method to be executed.

[0080] Example

[0081] This embodiment stipulates: (1) A certain equipment is composed of multiple electronic units. For ease of description, the lifespan of each unit is described by time. (2) At any given time, at most one unit will fail. When a unit fails, it will affect the normal operation of the equipment, and the equipment will exhibit certain fault phenomena. At this time, repair work needs to be carried out. (3) When confirming a fault, the order of checking the status of these units is independent and unrelated. That is, there is no situation where there is a specific requirement for the order of checks, such as "unit A must be checked first, and then unit B must be checked". (4) The lifespan distribution of each unit, the time consumed for checking the status of each unit (whether it is normal or not), and the time of the task to be performed 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; if the status of a unit is normal after the maintenance personnel completes the check, they will continue to check the next unit in the order of checks within their scope of responsibility; when a person checks a faulty unit, the check stops, and the subsequent phase moves to the repair stage of the faulty component.

[0082] The relevant variables in this embodiment are defined as follows: the number of maintenance personnel is denoted as m; the number of units is denoted as n; the lifespan of unit i follows an exponential distribution Exp(u i The time consumed in checking the state of unit i is denoted as tc. i The task time is denoted as Tw. All these variables are known quantities.

[0083] A component consists of 20 electronic units, with a task duration of 100 hours and 3 maintenance personnel. Relevant information is shown in Table 1. Using the method described above, optimize the fault location plan, calculate its fault location effectiveness, and estimate the probability of finding the faulty component within 60 minutes.

[0084] Table 1

[0085]

[0086] 1) Traverse and calculate the equivalent check time array tp, and the results are shown in Table 2.

[0087] 1.1) Let the unit number i = 1;

[0088] 1.2) Calculation In the formula, Pf i Let i be the probability of unit i failing.

[0089]

[0090] When k = i When k≠i

[0091] 1.3) Let i = i + 1. If i ≤ n, execute 1.2); otherwise, execute 3).

[0092] 2) Determine the sequence number array ipt, and the results are shown in Table 2.

[0093] Sort the elements in array tp in ascending order, and store the corresponding element indices in array itp. Array itp stores the cell numbers. For example, if ip = [12.6 6.3 3.4], after sorting in ascending order, itp = [3 2 1].

[0094] Table 2

[0095]

[0096] 3) Assign inspection units to each repairman. The array mdn = 8, 6, 6. The unit number and order of inspection for each person are stored in the scheme matrix dM. The results of dM are shown in Table 3.

[0097] 3.1) Initialize each element in the first column of matrix dM: dM(i, 1) = itp i .

[0098] The initial value of each element in the array mdn, which records the number of units each maintenance worker is responsible for, is 1.

[0099] Let the check sequence number i = 1 + m.

[0100] 3.2) Let the sequence number j = 1.

[0101] 3.3) Let the temporary array ct = dM(j, 1: mdn) j ), dM(j, 1: mdn j ) is the first mdn of the vector in the j-th row of matrix dM. j Each element.

[0102] 3.4) The workload mt for calculating the temporary array ct j :

[0103] 3.4.1) Let id = 1, mt j =0, the number of elements in array ct is denoted as cL;

[0104] 3.4.2) Let k = ct id ,mt j =mt j +tc k ;

[0105] 3.4.3) Let id = id + 1. If id ≤ cL, then execute 3.4.2); otherwise execute 3.5.

[0106] 3.5) Let the sequence number j = 1 + j. If j ≤ m, execute 3.3); otherwise, execute 3.6.

[0107] 3.6) Find the minimum value in array mt, denoted by its index im, and let mdn im =mdn im +1, dM(im, mdn) im )=itp i The dM contains the cell number.

[0108] 3.7) Let i = 1 + i. If i ≤ n, execute 3.2); otherwise, execute 4).

[0109] Table 3

[0110]

[0111] 4) Calculate the working status of each maintenance personnel. The average fault time (tm) for each personnel is 21.9 min, 25.6 min, and 23.0 min, respectively, and the workload (mt) is 209 min, 230 min, and 225 min, respectively. td and pd are shown in Table 4.

[0112] 4.1) Let the index i = 0 and the index j = 1.

[0113] 4.2) The average fault location time tm for personnel j j =0, and assign values ​​from 1 to mdn in the j-th row vector of matrix dM. j The elements are placed in a temporary array ct.

[0114] 4.3) Calculate the average fault location time tm for personnel j. j and workload mt j ,include:

[0115] 4.3.1) Initialize tm j =0, id=1;

[0116] 4.3.2) Let i = i + 1, and the unit number k = ct id Temporary time array tu id =tc k conditional probability Fault location completion time tm j =tm j +pd i td i ;

[0117] 4.3.3) Let id = id + 1, if id ≤ mdn j If the above is not executed (4.3.2), then the workload of personnel j is mt.j =td i Then proceed to S44.

[0118] 4.4) Let the sequence number j = 1 + j. If j ≤ m, execute 4.2); otherwise, execute 5).

[0119] 5) Calculate the fault location effectiveness of the scheme. The average fault location time of this scheme is Tx = 70.5 min. The reordered tx and px are shown in Table 4.

[0120] 5.1) Let the mean fault location time of this scheme be...

[0121] 5.2) Sort the elements in array td in ascending order, and store the sorting result in tx. Record the index of the element corresponding to the sorting result in im. For example, td = [25 12 30], then tx = [12 25 30], and im = [2 1 3].

[0122] 5.3) Calculate the probability array px based on im. Let nd be the number of elements in array td, and let i = 1.

[0123] 5.3.1) Let k = im i pt i =pd k Let probability

[0124] 5.3.2) Let i = i + 1. If i ≤ nd, execute 5.3.1); otherwise, execute 6).

[0125] Table 4

[0126]

[0127]

[0128] 6) Output the relevant variables dM, mt, tx, px, and Tx of the optimized solution.

[0129] In the j-th row vector of matrix dM, from 1 to mdn j The elements are the unit number and inspection order that maintenance personnel j is responsible for inspecting, and mt j This refers to the employee's workload. px i It is in time tx i The probability of finding the faulty component within the system, and Tx is the average fault location time for this solution. From tx... i px i The time consumption of this fault location scheme is described from a different perspective than Tx.

[0130] According to dM, the optimized solution is as follows: Maintenance personnel 1 is responsible for inspecting 8 units, sequentially inspecting units 15, 8, 13, 7, 20, 10, 19, and 12, with a workload of 209 minutes; Maintenance personnel 2 is responsible for inspecting 6 units, sequentially inspecting units 6, 4, 9, 18, 17, and 1, with a workload of 230 minutes; Maintenance personnel 3 is responsible for inspecting 6 units, sequentially inspecting units 11, 3, 14, 16, 2, and 5, with a workload of 225 minutes. The difference in workload between maintenance personnel is 21 minutes. The average fault location time for this solution is 70.5 minutes. From tx and px, we can determine the probability of finding the faulty component within the specified time using this solution. Since the approximate time intervals of 60 minutes in TX are 56 and 64, and the corresponding probabilities in px are 0.571 and 0.668, the probability of finding the faulty component within 60 minutes is between 0.571 and 0.668, approximately 0.6.

[0131] A simulation model can be established to verify the correctness of the above method. The simulation model is briefly described as follows:

[0132] (1) Generate n random numbers simT i , 1≤i≤n, simT i It follows the lifetime distribution law of unit i.

[0133] (2) In all simT i Find the smallest number in the set, and denote the corresponding index as g, i.e.: simT g ≤simT i , 1≤i≤n.

[0134] (3) If simT m If <Tw is true, then this simulation is valid. Based on the sequence number g and the inspection order of each person in the plan, we can determine which repairman found the faulty part and obtain the fault location time in this simulation. From the inspection order of each repairman, we can obtain the maximum workload time for each person.

[0135] After numerous simulations, the average fault location time can be statistically obtained.

[0136] Figure 2 The simulation method and the method of the present invention provided for embodiments of the present invention yield the tx and px results. For example... Figure 2 As shown, the simulation result of the average fault location time of the above optimized scheme is 72.0 min, which is highly consistent with the result of this method.

[0137] In the above example, a large number of schemes were randomly generated, and the fault location time of these schemes was simulated. Figure 3This describes the average fault location time for 1000 randomized schemes provided in this embodiment of the invention. Figure 3 As shown, the minimum time taken was 84.1 min, the maximum time taken was 353.6 min, the average time taken was 172.4 min, and the root variance of the time taken was 44.7. Figure 4 The personnel workload differences (described by the difference between the maximum and minimum workload of personnel) provided in these randomized schemes for embodiments of the present invention are as follows: Figure 4 As shown, the average workload difference is 42.1 minutes, indicating that the method of the present invention has significantly better balance in allocating personnel inspection workload than these random schemes. Extensive simulation results demonstrate that the optimization effect of the method of the present invention is significant. It can quickly and effectively formulate fault location schemes, accurately estimate the probability distribution of fault location time, reduce the average fault location time, balance the workload of maintenance personnel, and maximize the work efficiency of maintenance personnel. The present invention can quickly achieve local optima, even when the number of units n and the number of personnel m are both large, it can quickly provide optimization results in minutes.

[0138] 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 multi-person fault location optimization method based on equivalent inspection time, characterized in that, The method includes: S1. Obtain the state check consumption time and the probability of failure during the task time for each unit, and use the ratio of the state check consumption time to the probability of failure during the task time as the equivalent check time for that unit. S2. Arrange the units in ascending order according to the equivalent inspection time of each unit, and use this as the overall inspection order after multi-person fault location optimization; S3. According to the overall inspection order, and based on the principle of balancing the inspection workload of each person, the unit is divided into people in turn to obtain the inspection order of each person; Specifically, step S3 includes: S31. Initialize the check sequence number Initialize matrix Elements in column 1 Record the number of units each maintenance worker is responsible for. All elements in the matrix are initially set to 1. have Okay, it stores the unit number. An array representing the number of maintenance personnel. Indicates the optimized overall check order; S32. Initialize personnel serial numbers ; S33. Initialize the temporary array , It is a matrix No. The front of the row vector One element; S34. Calculate the temporary array workload ,include: S341. Initialize the temporary array subscript , array The number of elements in the array is denoted as ; S342. Initialize Unit Numbering ,renew array Indicates the time taken to check the status of each unit; S343 Update ,like If yes, proceed to S342; otherwise, proceed to S35. S35. Update serial number ,like If yes, proceed to S33; otherwise, proceed to S36. S36. In the workload array Find the minimum value and denote its index as . ,renew , ; S37 Update ,like Enter S32, This indicates the number of units in a complex device.

2. The method as described in claim 1, characterized in that, The method also includes: S4. Calculate the troubleshooting completion time and its probability, and the average troubleshooting time per person; S5. By accumulating the average troubleshooting time for each person, the average troubleshooting time for multiple people is obtained; by using the ascending order of troubleshooting completion time, the probability distribution of troubleshooting time is obtained.

3. The method as described in claim 2, characterized in that, Step S4 includes: S41. Initialize the check sequence number Personnel serial number ; S42. Initialize personnel Mean time to locate fault , matrix The In a row vector, from 1 to The elements are placed in a temporary array. In the matrix have Okay, it stores the unit number. Indicates the number of maintenance personnel; S43. Computing personnel Mean time to locate fault and workload ,include: S431. Initialization temporary array subscript ; S432 Update Unit number Temporary time array conditional probability Fault location completion time , ; S433 Update ,like Enter S432, otherwise, personnel workload Then enter S44; S44. Update serial number ,like If yes, proceed to S42; otherwise, proceed to S5.

4. The method as described in claim 3, characterized in that, Step S5 includes: S51. Calculate the mean fault location time for this scheme. ; S52. Convert the array The elements in the array are sorted in ascending order, and the sorting results are stored in [location]. In the sorting result, the element index is recorded in... middle; S53. According to Calculate the probability array for completion array The number of elements in the middle is denoted as ,initialization ,include: S531. Initialize Unit Numbering , , This represents a conditional probability array, used to calculate probabilities. ; S532 Update ,like If the condition is met, proceed to S531; otherwise, output the relevant variables of the optimized solution.

5. The method as described in claim 1, characterized in that, The units may be of the same or different types, including electronic units, mechanical units, or electromechanical units.

6. A multi-user fault location optimization system based on equivalent check time, characterized in that, include: Processor and memory; The memory is used to store computer-executed instructions; The processor is configured to execute the computer execution instructions, causing the method described in any one of claims 1 to 5 to be executed.

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