Reliable life modeling method, estimation method, vehicle, equipment, medium and product

Abstract

The invention discloses a reliable life modeling method, an estimation method, a vehicle, equipment, a medium and a product, and relates to the field of reliability of parts. The modeling method comprises the following steps: calculating the first maintenance time of a certain batch of parts in actual use; obtaining the fault state of the batch of parts during the first maintenance, and calculating the yield during the first maintenance according to the fault state during the first maintenance; calculating the second maintenance time according to the fault state during the first maintenance, the first maintenance time, the reliability requirement and the initial reliable life model; obtaining the fault state of the batch of parts during the second maintenance, and calculating the yield during the second maintenance according to the fault state during the second maintenance; and according to the yield during multiple times of maintenance and the reliability function of the parts, calculating parameters of the reliability function, and further obtaining a final reliable life model. According to the invention, the maintenance time and the maintenance cost are reduced, and the problem of excessive maintenance or insufficient maintenance is avoided.

Description

Technical Field

[0001] The present invention belongs to the technical field of component reliability, and in particular relates to a component reliable life modeling method, a component maintenance cycle estimation method, a rail vehicle, equipment, a storage medium and a product. Background Art

[0002] Rail vehicles, as the transportation equipment of urban rail transit, are in a state of aging for a long time due to factors such as friction, vibration, impact, and corrosion during use. When the aging of a component exceeds a certain degree, it will fail, which may require maintenance and repair, or even endanger the safety of passengers' lives and property. In particular, as urban rail transit places higher and higher requirements on the safety performance of vehicles, the safety and reliability of vehicles have become the key to ensuring the safety and order of rail transit and achieving economic and social benefits. Therefore, the importance of rationally planning vehicle maintenance and overhaul plans is increasing, and how to determine the appropriate overhaul time interval (i.e., overhaul cycle or overhaul interval) is a key issue that needs to be studied.

[0003] At present, the maintenance interval is divided according to the maximum running mileage and the accumulated running time. Regular preventive maintenance is carried out on rail vehicle parts, including daily inspection, biweekly inspection, three-month inspection, scheduled maintenance, frame repair, overhaul and other maintenance operations at various levels. The operation content is complicated and redundant, which takes up too much operating time. In the maintenance work at various levels, the intervals of daily inspection, biweekly inspection and three-month inspection of different projects in different places are the same, while the intervals of frame repair and overhaul are different, but they all comply with the provisions of the "Management Measures for the Operation and Maintenance of Urban Rail Transit Facilities and Equipment", that is, the interval of frame repair shall not exceed 5 years or 800,000 kilometers of mileage, the interval of overhaul shall not exceed 10 years or 1.6 million kilometers of mileage, and the overall service life shall generally not exceed 30 years or 4.8 million kilometers of mileage.

[0004] For example, the interval between overhauls of the subway in city C1 is 5 years or 600,000 kilometers of mileage, and the interval between major overhauls is 10 years or 1.2-1.5 million kilometers of mileage; the subway in city C2 divides overhauls and major overhauls into three-year inspections, minor overhauls, and major overhauls. The three-year inspection interval is 3 years or 340,000-400,000 kilometers of mileage, the minor overhaul interval is 6 years or 620,000-750,000 kilometers of mileage, and the major overhaul interval is 12 years or 1.25-1.5 million kilometers of mileage; the subway vehicles in city C3 are divided into two types, A and B, and their overhaul and major overhaul intervals are different. The overhaul interval of type A is 5 years or 500,000-600,000 kilometers of mileage, and the major overhaul interval is 10 years or 1 million-1.2 million kilometers of mileage; the overhaul interval of type B is 4 years or 750,000-800,000 kilometers of mileage, and the major overhaul interval is 10 years or 1.6 million-1.7 million kilometers of mileage.

[0005] This method of determining the maintenance cycle does not take into account the reliability and actual use of vehicle parts, which can easily lead to insufficient maintenance and excessive maintenance of these parts. The former increases the probability of vehicle failure during normal operation, which is very likely to cause safety accidents, or lead to passenger clearance and decommissioning. It not only poses a safety hazard, but also affects the normal operation of the vehicle due to the need for frequent maintenance of failures, resulting in a decrease in the vehicle's online rate and utilization rate. The latter increases maintenance costs and increases maintenance time, which will also lead to a decrease in the vehicle's online rate and utilization rate; in order to meet the daily peak operation needs, more rail vehicles can only be invested, thereby increasing operating costs. Summary of the invention

[0006] The purpose of the present invention is to provide a reliable life modeling method, an estimation method, a vehicle, equipment, a medium and a product to solve the problem that the traditional maintenance cycle determination method does not take into account the reliability and actual use of parts, resulting in insufficient maintenance or excessive maintenance.

[0007] The present invention solves the above technical problems through the following technical solutions: a component reliable life modeling method, comprising:

[0008] Constructing an initial reliable life model of the component;

[0009] Calculate the first overhaul time of a batch of parts in actual use according to reliability requirements and initial reliable life model;

[0010] Obtaining the failure status of the batch of parts during the first overhaul, and calculating the yield rate during the first overhaul according to the failure status of the batch of parts during the first overhaul;

[0011] The second overhaul time is calculated based on the fault status of the batch of parts during the first overhaul, the first overhaul time, the reliability requirements and the initial reliable life model;

[0012] Obtaining the failure status of the batch of parts during the second overhaul, and calculating the yield rate during the second overhaul according to the failure status of the batch of parts during the second overhaul;

[0013] Repeat the calculation steps of the overhaul time and the yield rate during overhaul to obtain the overhaul time and yield rate at K overhaul times;

[0014] The parameters of the reliability function are calculated according to the yield rate at K times of overhaul and the reliability function of the component, and then the final reliable life model of the component is obtained.

[0015] Furthermore, constructing an initial reliable life model of the component includes:

[0016] Constructing a reliability function of the component according to its service life distribution function;

[0017] Obtaining first failure time data of a plurality of the components in actual use;

[0018] The initial parameters of the reliability function are estimated according to the first failure time data of the plurality of components, thereby obtaining an initial reliable life model.

[0019] Furthermore, the specific formula for calculating the yield rate during the i-th maintenance is:

[0020]

[0021] Among them, η i represents the yield rate at the i-th maintenance, M Si represents the number of normal parts at the time of the i-th maintenance, M Fi represents the number of faulty parts during the i-th maintenance.

[0022] Furthermore, the i+1th overhaul time is calculated according to the fault state of the batch of parts at the i-th overhaul, the i-th overhaul time, the reliability requirement and the initial reliable life model, including:

[0023] Calculate the maintenance time interval of each component in the batch according to the i-th maintenance time, reliability requirements and initial reliable life model;

[0024] Take the minimum value of the maintenance time intervals of all parts in the batch;

[0025] The (i+1)th maintenance time is calculated based on the minimum value and the (i)th maintenance time.

[0026] Furthermore, the calculation of the maintenance time interval of each component in the batch according to the i-th maintenance time, reliability requirements and the initial reliable life model includes:

[0027] For each normal component, it must meet the first condition during the i+1th maintenance:

[0028] P(t>τ i +Δτ ij |T>τ i )≥α;

[0029] Among them, P(t>τ i +Δτ ij |T>τ i ) indicates that the reliable life T of normal component j exceeds the i-th maintenance time τ i The probability that the failure time exceeds the i+1th maintenance time under the condition; α represents the reliability; Δτ ij represents the i-th maintenance time interval of component j, τ i+1 =τi +Δτ ij , τ i+1 Indicates the i+1th maintenance time;

[0030] Calculate the i-th maintenance time interval of each normal component according to the first condition and the initial reliable life model;

[0031] For each faulty component, the i-th maintenance time interval of each faulty component is calculated according to the reliability requirements and the initial reliable life model.

[0032] Furthermore, the modeling method also includes calculating the maintenance time of the batch of parts using the final reliable life model, specifically including:

[0033] The K+1th overhaul time is calculated based on the failure status of the batch of parts at the Kth overhaul, the Kth overhaul time, the reliability requirements and the final reliable life model.

[0034] Based on the same concept, the present invention provides a method for estimating a component maintenance cycle, comprising:

[0035] Constructing a final reliable life model of the component using the component reliable life modeling method as described above;

[0036] The maintenance time of the component is calculated according to the final reliable life model and the reliability requirement of the component.

[0037] Furthermore, the maintenance time of the component is calculated according to the final reliable life model and the reliability requirement of the component, including:

[0038] Calculating the reliable life of the component according to the final reliable life model and the reliability requirements of the component, and taking the reliable life as the first maintenance time of the component;

[0039] Obtaining the fault status of the component during the first inspection;

[0040] Calculate the second overhaul time based on the fault state of the component at the time of the first overhaul, the first overhaul time, the reliability requirements and the final reliable life model;

[0041] The steps of acquiring the fault status of the component and calculating the maintenance time are repeated to calculate each maintenance time of the component.

[0042] Based on the same concept, the present invention provides a rail vehicle, on which components are provided, and the maintenance time of the components is estimated using the component maintenance cycle estimation method as described above.

[0043] Based on the same concept, the present invention also provides an electronic device, including a memory, a processor, and a computer program / instructions stored in the memory, wherein the processor executes the computer program / instructions to implement the component reliable life modeling method or the component maintenance cycle estimation method as described above.

[0044] Based on the same concept, the present invention also provides a computer-readable storage medium having a computer program / instruction stored thereon. When the computer program / instruction is executed by a processor, the component reliable life modeling method or component maintenance cycle estimation method as described above is implemented.

[0045] Based on the same concept, the present invention also provides a computer program product, including a computer program / instruction, which, when executed by a processor, implements the component reliable life modeling method or component maintenance cycle estimation method as described above.

[0046] Beneficial Effects

[0047] Compared with the prior art, the advantages of the present invention are:

[0048] The present invention, based on the initial reliable life model, calculates the next maintenance time through the fault state of the parts during each maintenance, the last maintenance time and the reliability requirements, updates the parameters of the reliable life model based on the yield rate during multiple maintenances, and obtains the final reliable life model; while ensuring that the parts always work within a higher reliability range, the maintenance time and maintenance cost are reduced, and the problem of excessive or insufficient maintenance is avoided.

[0049] The present invention establishes a reliability function according to the service life data of components, and estimates parameters according to historical failure data and the reliability function to obtain an initial reliable life model, thereby ensuring the correctness of reliable life evaluation and further improving the correctness of maintenance time estimation.

[0050] Based on the constructed reliable life model, the present invention determines the detection time for each time in a sequential manner, requires a small amount of data, and the calculation is fast and simple. It can realize the dynamic adjustment of the maintenance time interval of parts, so that the parts can maintain working at a high reliability for a long time, thereby improving safety and reliability. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the technical solution of the present invention, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only one embodiment of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0052] Figure 1It is a flow chart of the reliable life modeling method of parts in an embodiment of the present invention. DETAILED DESCRIPTION

[0053] The following is a clear and complete description of the technical solutions in the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0054] The technical solution of the present application is described in detail with specific embodiments below. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments.

[0055] Example 1

[0056] like Figure 1 As shown, a component reliable life modeling method provided by an embodiment of the present invention includes the following steps:

[0057] Step 1: Construct an initial reliable life model for components.

[0058] In a specific embodiment of the present invention, constructing an initial reliable life model of a component includes:

[0059] Step 1.1: Construct the reliability function of the component based on its service life distribution function.

[0060] For example, it is assumed that the service life distribution function of a component is an exponential function, specifically:

[0061] D(t)=P(T≤t)=1-e -λt (1)

[0062] Where D(t) represents the service life distribution function, P(T≤t) represents the probability that the service life T is less than or equal to the failure time t, and λ represents the parameter to be determined. The reliability function of the component is:

[0063] R(t)=1-D(t)=e -λt (2)

[0064] Among them, R(t) represents the reliability of the component and t represents time.

[0065] Step 1.2: Obtain the first failure time data of n components in actual use.

[0066] For example, n components are put into use on a rail vehicle, and the first failure time data of these n components are obtained in actual use. In this embodiment, 100,000 kilometers is used as the unit of the first failure time data, that is, when the rail vehicle has traveled a certain number of kilometers, the component has the first failure. The first failure time data of n components in actual use are shown in Table 1, and in this embodiment, n=30.

[0067] Table 1 First failure time data of 30 parts in actual use (unit: 100,000 kilometers)

[0068] 3.578 1.277 2.896 4.123 2.868 1.260 1.082 0.301 0.211 0.088 3.666 4.895 5.023 2.369 3.213 4.125 1.865 2.789 3.652 4.256 4.123 5.201 3.842 5.314 4.665 3.645 5.936 4.251 2.689 4.197

[0069] Step 1.3: Estimate the initial parameters of the reliability function based on the first failure time data of n components, and then obtain the initial reliable life model.

[0070] Based on the first failure time data of n components, the maximum likelihood estimation method is used to obtain the estimated value of parameter λ: λ = 0.308, and the initial reliable life model is obtained as follows:

[0071] R(t)=e -0.308t (3)

[0072] Step 2: Calculate the first maintenance time of a batch of parts in actual use based on the reliability requirements and the initial reliable life model.

[0073] In order to ensure that the components always work at a high reliability level and the rail vehicles operate safely, and to avoid over-maintenance and under-maintenance, the reliability α is set to 0.9 (i.e., the reliability requirement). Substituting 0.9 into formula (3), we can solve for the reliable life T α :

[0074]

[0075] Reliable life T α As the first maintenance time of a batch of parts in actual use, that is, the first maintenance time τ1 = T α =0.342, indicating that the first maintenance time node is 34200 kilometers. It should be noted that this batch of parts is not the same as the n parts in Table 1.

[0076] Step 3: Obtain the failure status of the batch of parts during the first overhaul, and calculate the yield rate during the first overhaul based on the failure status of the batch of parts during the first overhaul.

[0077] The batch of parts is applied to the rail vehicle, and when the rail vehicle travels τ1 = 34200 kilometers, the fault status of the batch of parts is detected. Assuming that the number of the batch of parts is 10, the fault status of each part is shown in Table 2, where S indicates that the corresponding part is normal, and F indicates that the corresponding part is faulty.

[0078] Table 2 Failure status of batch parts

[0079]

[0080] It can be seen from Table 2 that during the first overhaul, parts #1 to #7 are in normal state, and parts #8 to #10 are in faulty state, that is, in the interval [0, τ1], there are 3 faulty parts (#8, #9, #10) and 7 normal parts (#1, #2, #3, #4, #5, #6, #7). In this embodiment, the specific formula for the yield rate during the i-th overhaul is:

[0081]

[0082] Among them, η i represents the yield rate at the i-th maintenance, M Si represents the number of normal parts at the time of the i-th maintenance, M Fi represents the number of faulty parts during the i-th overhaul. According to formula (5), the yield rate during the first overhaul can be calculated:

[0083]

[0084] Step 4: Calculate the second overhaul time based on the failure status of the batch of parts during the first overhaul, the first overhaul time, the reliability requirements and the initial reliable life model.

[0085] In a specific embodiment of the present invention, the i+1th overhaul time is calculated according to the fault state of the batch of parts at the i-th overhaul, the i-th overhaul time, the reliability requirement and the initial reliable life model, including:

[0086] Step 4.1: Calculate the maintenance time interval of each component in the batch according to the i-th maintenance time, reliability requirements and initial reliable life model; wherein the maintenance time interval of each component refers to the interval between the i-th maintenance time and the i+1-th maintenance time;

[0087] Step 4.2: Take the minimum value of the maintenance time intervals of all parts in the batch;

[0088] Step 4.3: Calculate the (i+1)th maintenance time based on the minimum value in step 4.2 and the (i)th maintenance time.

[0089] For component j in this batch, in order to ensure that its reliability is not less than α before the second overhaul, an interval Δτ is required 1j The second overhaul is carried out afterwards. The normal parts (#1, #2, #3, #4, #5, #6, #7) during the first overhaul are not disturbed. Therefore:

[0090] P(t>τ1+Δτ 1j |T>τ1)≥α,j=1,2,3,4,5,6,7 (6)

[0091] Among them, P(t>τ1+Δτ 1j |T>τ1) represents the probability that the failure time exceeds the second overhaul time when the reliable life exceeds the first overhaul time, that is, the probability that no failure occurs during the second overhaul; Δτ 1j Represents the first maintenance time interval of component j (i.e. the interval between the first maintenance time and the second maintenance time).

[0092] according to It can be solved that the first maintenance time interval of each normal component is: Δτ 11 =Δτ 12 =Δτ 13 =Δτ 14 =Δτ 15 =Δτ 16 =Δτ 17 =0.342. The faulty parts (#8, #9, #10) during the first overhaul need to be replaced or repaired and then used as normal parts. Since the reliability requirement is R(t)≥α, when α=0.9, by solving the equation:

[0093] R(Δτ 1j )=α,j=8,9,10 (7)

[0094] Solved: Δτ 1j =0.342,j=8,9,10.

[0095] In order to ensure that the reliability of each component before the second overhaul is not less than α, the overhaul time interval between the first overhaul time and the second overhaul time is Δτ1=min j {Δτ 1j}=0.342, which means that the mileage between the first maintenance time node and the second maintenance time node is 34200 kilometers. Therefore, the second maintenance time is τ2=τ1+Δτ1=0.342+0.342=0.684, which means that the mileage of the rail vehicle at the second maintenance time node is 68400 kilometers.

[0096] Step 5: Obtain the failure status of the batch of parts during the second overhaul, and calculate the yield rate during the second overhaul based on the failure status of the batch of parts during the second overhaul.

[0097] When the rail vehicle travels τ2=68400 kilometers, the fault status of the batch of parts is detected. It can be seen from Table 2 that during the second overhaul, parts #1, #3 to #7, and #10 are in normal state, and parts #2, #8, and #9 are in faulty state, that is, in the interval [0, τ2], there are 6 faulty parts and 6 normal parts. Among them, the number of faulty parts (#2, #8, #9, #10) is 6 because: parts #8 and #9 fail in both the interval [0, τ1] and the interval [0, τ2], so parts #8 and #9 need to be counted twice; part #10 fails in the interval [0, τ1], so it needs to be counted once; part #2 fails in the interval [0, τ2], so it needs to be counted once; the number of normal parts (#1, #3, #4, #5, #6, #7) is 6 because: part #10 fails in the interval [0, τ1], so part #10 needs to be removed from the normal parts in the interval [0, τ2]. According to formula (5), the yield rate during the second overhaul can be calculated:

[0098] Step 6: Repeat steps 4 and 5 to calculate the third overhaul time and the yield rate at the third overhaul.

[0099] Firstly, the third overhaul time is calculated according to the failure status of the batch of parts during the second overhaul, the second overhaul time, the reliability requirements and the initial reliable life model.

[0100] For component j in this batch, in order to ensure that its reliability is not less than α before the third overhaul, an interval Δτ is required 2j The third overhaul is then carried out. The normal parts (#1, #3, #4, #5, #6, #7, #10) during the second overhaul are not disturbed. Therefore:

[0101] P(t>τ2+Δτ 2j |T>τ2)≥α,j=1,3,4,5,6,7,10 (8)

[0102] Among them, P(t>τ2+Δτ 2j |T>τ2) represents the probability that the failure time exceeds the third overhaul time when the reliable life exceeds the second overhaul time, that is, the probability that no failure occurs during the third overhaul; Δτ 2j Represents the second maintenance time interval of component j (i.e. the interval between the second maintenance time and the third maintenance time).

[0103] according to It can be solved that the second maintenance time interval for each normal component is: Δτ 21 =Δτ 23 =Δτ 24 =Δτ 25 =Δτ 26 =Δτ 27 =Δτ 210 =0.342. The faulty parts (#2, #8, #9) during the second overhaul should be replaced or repaired. Since the reliability requirement is R(t)≥α, when α=0.9, by solving the equation:

[0104] R(Δτ 2j )=α,j=2,8,9 (9)

[0105] Solved: Δτ 2j =0.342,j=2,8,9.

[0106] In order to ensure that the reliability of each component before the third overhaul is not less than α, the overhaul time interval between the second overhaul time and the third overhaul time is Δτ2=min j {Δτ 2j}=0.342, which means that the mileage between the second and third maintenance time nodes is 34,200 kilometers. Therefore, the third maintenance time is τ3=τ2+Δτ2=0.684+0.342=1.026, which means that the third maintenance time node is the rail vehicle mileage of 102,600 kilometers.

[0107] Secondly, the failure status of the batch of parts during the third overhaul is obtained, and the yield rate during the third overhaul is calculated according to the failure status of the batch of parts during the third overhaul.

[0108] When the rail vehicle travels τ3 = 102600 kilometers, the fault status of the batch of parts is detected. As shown in Table 2, during the third overhaul, parts #1 to #4, #6 to #9 are in normal status, and parts #5 and #10 are in faulty status, that is, in the interval [0, τ3], there are 8 faulty parts and 5 normal parts. The number of faulty parts (#2, #5, #8, #9, #10) is 8 because: parts #8 and #9 fail in both the interval [0, τ1] and the interval [0, τ2], so parts #8 and #9 need to be counted twice; parts #10 fail in both the interval [0, τ1] and the interval [0, τ3], so parts #10 need to be counted twice; parts #2 If a component fails in the interval [0,τ2], then component #2 needs to be counted once; if component #5 fails in the interval [0,τ3], then component #5 needs to be counted once; the number of normal components (#1, #3, #4, #6, #7) is 5 because: component #2 fails in the interval [0,τ2], component #9 fails in the interval [0,τ1] and [0,τ2], and component #10 fails in the interval [0,τ1] and [0,τ3]. Therefore, components #2, #9, and #10 need to be removed from the normal components in the interval [0,τ3]. According to formula (5), the yield rate at the third overhaul can be calculated:

[0109] Step 7: Calculate the parameters of the reliability function based on the yield rate during the three inspections and the reliability function of the component, and then obtain the final reliable life model of the component.

[0110] The yield rate during the three inspections is taken as the reliability (as shown in formula (10)), and linear fitting or least squares or maximum likelihood method is used to obtain λ=1.1, and K=3 in this embodiment.

[0111]

[0112] The final reliable life model is obtained:

[0113] R(t)=e -1.1t (11)

[0114] Step 8: Calculate the fourth overhaul time based on the failure status of the batch of parts at the third overhaul, the third overhaul time, the reliability requirements and the final reliable life model.

[0115] After the third overhaul, in order to ensure that the reliability is not less than α before the fourth overhaul, an interval Δτ is required 3j For the third overhaul:

[0116] ① For parts #1, #3, #4, #6, and #7, which have been used normally for τ3 time, they must still meet the reliability requirements before the next overhaul, that is, they must meet the following requirements:

[0117] P(t>τ3+Δτ 3j |T>τ3)≥α,j=1,3,4,6,7 (12)

[0118] Where P(t>τ3+Δτ 3j |T>τ3) represents the probability that the failure time exceeds the fourth overhaul time when the reliable life exceeds the third overhaul time, that is, the probability that no failure occurs during the fourth overhaul; Δτ 3j It represents the third maintenance time interval of component j (i.e. the interval between the third maintenance time and the fourth maintenance time).

[0119] according to It can be solved that the third maintenance time interval for each normal component is: Δτ 31 =Δτ 33 =Δτ 34 =Δτ 36 =Δτ 37 =0.096.

[0120] ② For parts #5 and #10, they were in a faulty state during the third overhaul and became normal parts after replacement or repair. Therefore, R(Δτ 3j )=α,j=5,10, the solution is: Δτ 3j =0.096,j=5,10.

[0121] ③For parts #2, #8, and #9, they are replaced after the second overhaul and are in normal condition during the third overhaul. Therefore, the time that parts #2, #8, and #9 have been used is Δτ2. To meet the reliability requirements before the next overhaul, the equation must be satisfied:

[0122] P(T>Δτ2+Δτ 3j |T>Δτ2)≥α,i=2,8,9 (13)

[0123] Solving for Δτ 32 =Δτ 38 =Δτ 39 =0.096.

[0124] In order to ensure that the reliability of each component before the fourth overhaul is not less than α, the interval between the third overhaul time and the fourth overhaul time is That is, the mileage between the third and fourth overhaul time points is 9,600 kilometers. Therefore, the fourth overhaul time is τ4 = τ3 + Δτ3 = 1.118, that is, the mileage of the rail vehicle at the fourth overhaul time point is 111,800 kilometers.

[0125] Step 9: Calculate the kth overhaul time based on the failure status of the batch of parts at the k-1th overhaul, the k-1th overhaul time, the reliability requirements and the final reliable life model.

[0126] In a specific embodiment of the present invention, the k-th overhaul time is calculated according to the fault state of the batch of parts at the k-1-th overhaul, the k-1-th overhaul time, the reliability requirement and the final reliable life model, including:

[0127] Step 9.1: Calculate the maintenance time interval of each component in the batch according to the k-1th maintenance time, reliability requirements and the final reliable life model; wherein the maintenance time interval of each component refers to the interval between the k-1th maintenance time and the kth maintenance time;

[0128] Step 9.2: Take the minimum value of the maintenance time intervals of all parts in the batch;

[0129] Step 9.3: Calculate the kth maintenance time based on the minimum value in step 9.2 and the k-1th maintenance time.

[0130] Example 2

[0131] A method for estimating a component maintenance cycle provided by an embodiment of the present invention comprises the following steps:

[0132] Step 1: construct a final reliable life model of the component using the component reliable life modeling method in Example 1 of the present application;

[0133] Step 2: Calculate the maintenance time of the components according to the final reliable life model and the reliability requirements of the components, wherein the number of the components to be maintained can be 1 or more.

[0134] In a specific embodiment of the present invention, the maintenance time of a component is calculated according to the final reliable life model and the reliability requirements of the component, including:

[0135] Step 2.1: Calculate the reliable life of the component based on the final reliable life model and the reliability requirements of the component, and use the reliable life as the first maintenance time of the component.

[0136] Taking formula (11) in Example 1 as the final reliable life model of this embodiment, the calculation formula of the reliable life is:

[0137]

[0138] Among them, T α represents the reliable life of the component, and α represents the reliability of the component.

[0139] Step 2.2: Obtain the failure status of the component during the first overhaul.

[0140] Step 2.3: Calculate the second overhaul time based on the failure status of the component during the first overhaul, the first overhaul time, the reliability requirements and the final reliable life model.

[0141] When the component is in normal state, in order to ensure that its reliability is not less than α before the second overhaul, the second overhaul needs to be carried out after an interval of Δτ1. Therefore, the component needs to meet the following conditions:

[0142] P(t>τ1+Δτ1|T>τ1)≥α (15)

[0143] Among them, P(t>τ1+Δτ1|T>τ1) represents the probability that the failure time of a component exceeds the second maintenance time when the reliable life T of the component exceeds the first maintenance time τ1; Δτ1 represents the first maintenance time interval of the component, τ2=τ1+Δτ1, τ2 represents the second maintenance time.

[0144] When the component is in a faulty state, the first maintenance time interval of the component is calculated according to the final reliable life model and reliability requirements. The specific formula is:

[0145] R(Δτ1)=α (16)

[0146] By solving formula (16), we can find the first maintenance time interval when the component is in a faulty state.

[0147] When the number of parts is 1, the second maintenance time τ2 of the part can be calculated based on the first maintenance time interval of the part and the first maintenance time τ1.

[0148] When there are multiple parts, take the minimum value of the first maintenance time interval of all parts, and calculate the second maintenance time τ2 of the parts based on the minimum value and the first maintenance time τ1.

[0149] Step 2.4: Repeat steps 2.2 and 2.3 to calculate each overhaul time of the parts.

[0150] Example 3

[0151] Although not shown, an embodiment of the present invention further provides a rail vehicle, on which components are provided, and the component maintenance period estimation method in the embodiment of the present application is used to estimate the maintenance time of the component.

[0152] Although not shown, an embodiment of the present invention further provides an electronic device, which includes: a memory, a processor, and a computer program / instructions stored on the memory, and the processor executes the computer program / instructions to implement the component reliable life modeling method or the component maintenance cycle estimation method in the embodiment of the present application.

[0153] Although not shown, the electronic device includes a processor, which can perform various appropriate operations and processes according to the program and / or data stored in the read-only memory (ROM) or the program and / or data loaded from the storage portion into the random access memory (RAM). The processor can be a multi-core processor, or it can include multiple processors. In some embodiments, the processor can include a general main processor and one or more special coprocessors, such as a central processing unit, a graphics processing unit (GPU), a neural network processor (NPU), a digital signal processor (DSP), etc. In RAM, various programs and data required for device operation are also stored. The processor, ROM and RAM are connected to each other via a bus. The input / output (I / O) interface is also connected to the bus.

[0154] The processor and memory are used together to execute the program / instructions stored in the memory. When the program / instructions are executed by the computer, the methods, steps or functions described in the above embodiments can be implemented.

[0155] Although not shown, an embodiment of the present invention further provides a computer-readable storage medium having a computer program / instruction stored thereon, which, when executed by a processor, implements the component reliable life modeling method or component maintenance cycle estimation method in the embodiment of the present application.

[0156] Readable storage media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include temporary computer-readable media (transitory media), such as modulated data signals and carrier waves.

[0157] Although not shown, an embodiment of the present invention further provides a computer program product, including: a computer program / instruction, which, when executed by a processor, implements the component reliable life modeling method or component maintenance cycle estimation method in the embodiment of the present application.

[0158] What is disclosed above is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of changes or modifications within the technical scope disclosed in the present invention, which should be covered within the protection scope of the present invention.

Claims

1. A component reliability life modeling method, characterized in that: The modeling method comprises: Constructing an initial reliable life model of the component; Calculate the first overhaul time of a batch of parts in actual use according to reliability requirements and initial reliable life model; Obtaining the failure status of the batch of parts during the first overhaul, and calculating the yield rate during the first overhaul according to the failure status of the batch of parts during the first overhaul; The second overhaul time is calculated based on the fault status of the batch of parts during the first overhaul, the first overhaul time, the reliability requirements and the initial reliable life model; Obtaining the failure status of the batch of parts during the second overhaul, and calculating the yield rate during the second overhaul according to the failure status of the batch of parts during the second overhaul; Repeat the calculation steps of the overhaul time and the yield rate during overhaul to obtain the overhaul time and yield rate at K overhaul times; The parameters of the reliability function are calculated according to the yield rate at K times of overhaul and the reliability function of the component, and then the final reliable life model of the component is obtained.

2. The component reliability life modeling method according to claim 1, characterized in that: Constructing an initial reliable life model of the component, including: Constructing a reliability function of the component according to its service life distribution function; Obtaining first failure time data of a plurality of the components in actual use; The initial parameters of the reliability function are estimated according to the first failure time data of the plurality of components, thereby obtaining an initial reliable life model.

3. The component reliability life modeling method according to claim 1, characterized in that: The specific formula for calculating the yield rate during the i-th maintenance is: Among them, η i represents the yield rate at the i-th maintenance, M Si represents the number of normal parts at the time of the i-th maintenance, M Fi represents the number of faulty parts during the i-th maintenance.

4. The component reliability life modeling method according to claim 1, characterized in that: The i+1th overhaul time is calculated based on the fault state of the batch of parts at the i-th overhaul, the i-th overhaul time, the reliability requirements and the initial reliable life model, including: Calculate the maintenance time interval of each component in the batch according to the i-th maintenance time, reliability requirements and initial reliable life model; Take the minimum value of the maintenance time intervals of all parts in the batch; The (i+1)th maintenance time is calculated based on the minimum value and the (i)th maintenance time.

5. The component reliability life modeling method according to claim 4, characterized in that: The calculation of the maintenance time interval of each component in the batch according to the i-th maintenance time, reliability requirements and the initial reliable life model includes: For each normal component, it must meet the first condition during the i+1th maintenance: P(t>τ i +Δt ij |T>t i )≥a; Among them, P(t>τ i +Δτ ij |T>τ i ) indicates that the reliable life T of normal component j exceeds the i-th maintenance time τ i The probability that the failure time exceeds the i+1th maintenance time under the condition; α represents the reliability; Δτ ij represents the i-th maintenance time interval of component j, τ i+1 =τ i +Δτ ij , τ i+1 Indicates the i+1th maintenance time; Calculate the i-th maintenance time interval of each normal component according to the first condition and the initial reliable life model; For each faulty component, the i-th maintenance time interval of each faulty component is calculated according to the reliability requirements and the initial reliable life model.

6. The component reliable life modeling method according to any one of claims 1 to 5, characterized in that: The modeling method further includes calculating the maintenance time of the batch of parts using the final reliable life model, specifically including: The K+1th overhaul time is calculated based on the failure status of the batch of parts at the Kth overhaul, the Kth overhaul time, the reliability requirements and the final reliable life model.

7. A method for estimating the maintenance cycle of a component, characterized in that: The estimation method includes: Constructing a final reliable life model of the component using the component reliable life modeling method as described above; The maintenance time of the component is calculated according to the final reliable life model and the reliability requirement of the component.

8. The method for estimating parts maintenance cycle according to claim 7, characterized in that: Calculating the maintenance time of the component according to the final reliable life model and the reliability requirements of the component, including: Calculating the reliable life of the component according to the final reliable life model and the reliability requirements of the component, and taking the reliable life as the first maintenance time of the component; Obtaining the fault status of the component during the first inspection; Calculate the second overhaul time based on the fault state of the component at the time of the first overhaul, the first overhaul time, the reliability requirements and the final reliable life model; The steps of acquiring the fault status of the component and calculating the maintenance time are repeated to calculate each maintenance time of the component.

9. A rail vehicle, on which parts are provided, characterized in that the parts use the parts maintenance cycle estimation method as described in claim 7 or 8 to estimate the maintenance time.

10. An electronic device comprising a memory, a processor, and a computer program / instruction stored in the memory, characterized in that the processor executes the computer program / instruction to implement the component reliable life modeling method as described in any one of claims 1 to 6 or the component maintenance cycle estimation method as described in claim 7 or 8.

11. A computer-readable storage medium having a computer program / instruction stored thereon, characterized in that when the computer program / instruction is executed by a processor, the component reliable life modeling method as described in any one of claims 1 to 6 or the component maintenance cycle estimation method as described in claim 7 or 8 is implemented.

12. A computer program product, comprising a computer program / instruction, characterized in that when the computer program / instruction is executed by a processor, it implements the component reliable life modeling method as described in any one of claims 1 to 6 or the component maintenance cycle estimation method as described in claim 7 or 8.

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