CN115293296B - A mechanical equipment fault location optimization method and system - Google Patents
A mechanical equipment fault location optimization method and system Download PDFInfo
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Abstract
本发明公开了一种机械设备故障定位优化方法和系统,属于机械设备故障定位领域。包括:获取各机械件的寿命服从的正态分布密度函数和累计工作时间,并将机械设备的某段工作时期作为任务时间;在任务时间内,对各机械件的寿命服从的正态分布密度函数积分计算,得到任务时间内各机械件发生故障的概率;根据任务时间内各机械件发生故障的概率,计算任务时间内各机械件发生故障的条件概率;将任务时间内各机械件发生故障的条件概率降序排序,排序结果对应的机械件编号的排列,即为优化后的故障定位方案;按照优化后的故障定位方案依次检查各机械件的状态,直至找出发生故障的机械件。本发明能够尽可能少地检查机械件数量完成故障定位。
The invention discloses a mechanical equipment fault location optimization method and system, belonging to the field of mechanical equipment fault location. Including: obtaining the normal distribution density function and the cumulative working time of the service life of each mechanical part, and taking a certain working period of the mechanical equipment as the task time; within the task time, the normal distribution density of the service life of each mechanical part Calculate the function integral to obtain the failure probability of each mechanical part within the task time; calculate the conditional probability of each mechanical part failure within the task time according to the failure probability of each mechanical part within the task time; calculate the failure probability of each mechanical part within the task time Sort in descending order of the conditional probabilities of the sorting results, and the arrangement of the mechanical part numbers corresponding to the sorting results is the optimized fault location scheme; check the status of each mechanical part in turn according to the optimized fault location plan until the faulty mechanical part is found. The invention can check the number of mechanical parts as little as possible to complete fault location.
Description
技术领域technical field
本发明属于机械设备故障定位领域,更具体地,涉及一种机械设备故障定位优化方法和系统。The invention belongs to the field of fault location of mechanical equipment, and more particularly relates to a method and system for optimizing fault location of mechanical equipment.
背景技术Background technique
装备发生故障后,一般要先进行故障定位,然后开展修复工作。所谓故障定位是指找到失效的零部件,该失效件是导致发生故障的原因。当某个故障的背后有多个可能的原因时,由于涉及对多个零部件先后进行正常与否的状态检查(直到找到失效的零部件为止),因此存在着多种故障检查次序,不同的故障检查次序消耗的时间一般并不相同。After the equipment fails, it is generally necessary to locate the fault first, and then carry out the repair work. The so-called fault location refers to finding the failed component, which is the cause of the failure. When there are multiple possible reasons behind a certain fault, since it involves successively checking the status of multiple components (until the failed component is found), there are various fault inspection sequences, different Troubleshooting sequences generally do not take the same amount of time.
在工程上,机械件的寿命一般服从正态分布规律,如:汇流环、齿轮箱、减速器等,用于描述因磨损等原因造成的失效。正态类机械件指寿命服从正态分布的机械件,其密度函数,其中,的物理含义是寿命均值,的物理含义是寿命根方差,描述了寿命在均值附近的集中与分散程度。In engineering, the life of mechanical parts generally obeys the normal distribution law, such as: slip ring, gearbox, reducer, etc., which are used to describe failures caused by wear and tear. Normal mechanical parts mean that the service life obeys the normal distribution The mechanical parts, whose density function ,in, The physical meaning of is the average lifetime, The physical meaning of is the life root variance, which describes the degree of concentration and dispersion of life around the mean.
对机械件进行状态检查时,常常涉及较为繁琐复杂的拆卸、测量以及最后的装配恢复等,因此,在故障定位时如何优化相关机械件的检查次序,尽可能少地检查相关机械件,对实际装备维修工作极具价值。目前,主要依靠维修人员日渐积累的经验,结合某些优化原则来逐步优化故障定位的检查次序。例如,“最有可能发生故障的优先检查”就是一种常见的优化原则,但如何准确量化这种可能性一直是个未能很好解决的难题,维修人员往往只能凭借经验来粗略估计各机械件发生故障的可能性大小,导致优化后的检查次序往往不能达到以最少检查工作量完成故障定位的效果。When checking the status of mechanical parts, it often involves cumbersome and complicated disassembly, measurement, and final assembly restoration. Equipment repair work is extremely valuable. At present, mainly rely on the accumulated experience of maintenance personnel, combined with some optimization principles to gradually optimize the inspection sequence of fault location. For example, "priority inspection with the most probable failure" is a common optimization principle, but how to accurately quantify this possibility has always been a difficult problem that has not been well resolved. Maintenance personnel often can only roughly estimate the failure of each machine based on experience. Due to the possibility of component failure, the optimized inspection sequence often cannot achieve the effect of completing fault location with the least inspection workload.
发明内容Contents of the invention
针对现有技术的缺陷和改进需求,本发明的目的在于提供一种机械设备故障定位优化方法和系统,旨在解决不能可靠地获得最少检查机械件数量情况下的故障定位方案的问题。In view of the defects and improvement needs of the prior art, the purpose of the present invention is to provide a mechanical equipment fault location optimization method and system, aiming to solve the problem that the fault location solution cannot be reliably obtained under the condition of the minimum number of inspected mechanical parts.
为实现上述目的,第一方面,本发明提供了一种机械设备故障定位优化方法,所述机械设备包括多个机械件,所述机械件的寿命均服从于正态分布,整个任务时间内任意时刻最多一个机械件发生故障,故障排查时各机械件的状态检查的次序独立不相关,各机械件故障排查时拆卸复杂程度一致,该方法包括:In order to achieve the above object, in the first aspect, the present invention provides a method for optimizing fault location of mechanical equipment. The mechanical equipment includes a plurality of mechanical parts, and the service life of the mechanical parts is subject to a normal distribution. At most one mechanical part breaks down at any one time, and the order of status inspection of each mechanical part is independent and irrelevant during troubleshooting, and the disassembly complexity of each mechanical part is consistent during troubleshooting. The method includes:
S1.获取各机械件的寿命服从的正态分布密度函数和累计工作时间,并将机械设备的某段工作时期作为任务时间;S1. Obtain the normal distribution density function and the cumulative working time of the service life of each mechanical part, and use a certain working period of the mechanical equipment as the task time;
S2.在任务时间内,结合各机械件的累计工作时间,对其寿命服从的正态分布密度函数积分计算,得到任务时间内各机械件发生故障的概率;S2. During the task time, combined with the cumulative working time of each mechanical part, the integral calculation of the normal distribution density function subject to its life expectancy is obtained, and the probability of failure of each mechanical part within the task time is obtained;
S3.根据任务时间内各机械件发生故障的概率,计算任务时间内各机械件发生故障的条件概率;S3. According to the failure probability of each mechanical part within the task time, calculate the conditional probability of each mechanical part failure within the task time;
S4.将任务时间内各机械件发生故障的条件概率降序排序,排序结果对应的机械件编号排列,即为优化后的故障定位方案;S4. Sort the conditional probabilities of failures of each mechanical part within the task time in descending order, and arrange the numbers of the mechanical parts corresponding to the sorting results, which is the optimized fault location scheme;
S5.按照优化后的故障定位方案依次检查各机械件的状态,直至找出发生故障的机械件。S5. Check the status of each mechanical part sequentially according to the optimized fault location scheme until the faulty mechanical part is found.
优选地,步骤S2包括以下子步骤:Preferably, step S2 includes the following sub-steps:
S21.设置机械件编号;S21. Set the mechanical part number ;
S22.计算任务时间内机械件发生故障的概率:S22. Calculate task time Internal Mechanical Parts probability of failure :
当时,when hour,
; ;
当时,when hour,
; ;
其中,表示机械件的数量,表示机械件的条件概率,表示机械件的寿命均值,表示机械件的寿命根方差,表示机械件的累计工作时间;in, Indicates the number of mechanical parts, Indicates mechanical parts The conditional probability of Indicates mechanical parts average lifespan, Indicates mechanical parts The lifetime root variance of Indicates mechanical parts cumulative working hours;
S23.,若,进入S22,否则,进入步骤S3。S23. ,like , go to S22, otherwise, go to step S3.
优选地,任务时间内各机械件发生故障的条件概率的计算公式如下:Preferably, the conditional probability of failure of each mechanical part within the task time The calculation formula is as follows:
。 .
优选地,该方法还包括:Preferably, the method also includes:
得到优化后的故障定位方案后,计算故障定位方案的平均检查机械件数量:After obtaining the optimized fault location scheme, calculate the average number of inspection mechanical parts of the fault location scheme :
其中,为任务时间内各机械件发生故障的条件概率降序排序结果,表示中的第个元素。in, is the result of sorting the conditional probabilities of failures of each mechanical part in descending order within the task time, express in the first elements.
为实现上述目的,第二方面,本发明提供了一种机械设备故障定位优化系统,包括:包括处理器和存储器;所述处理器用于存储计算机执行指令;所述处理器用于执行所述计算机执行指令,使得第一方面所述的方法被执行。In order to achieve the above object, in the second aspect, the present invention provides a mechanical equipment fault location optimization system, including: including a processor and a memory; the processor is used to store computer-executed instructions; the processor is used to execute the computer-executed An instruction, so that the method described in the first aspect is executed.
总体而言,通过本发明所构思的以上技术方案,能够取得以下有益效果:Generally speaking, through the above technical solutions conceived by the present invention, the following beneficial effects can be obtained:
本发明提供了一种机械设备故障定位优化方法和系统,通过积分计算任务时间内各机械件发生故障的概率,进一步计算任务时间内各机械件发生故障的条件概率,将这些任务时间内各机械件发生故障的条件概率降序排序,排序结果对应的机械件编号排列,即为优化后的故障定位方案,从而实现尽可能少地检查机械件数量完成故障定位,其对应的平均检查机械件数量有助于确定维修管理工作中维修人员数量、修理工具和维修工时等。The present invention provides a mechanical equipment failure location optimization method and system. The failure probability of each mechanical part within the task time is calculated by integral calculation, and the conditional probability of failure of each mechanical part within the task time is further calculated. The conditional probabilities of failures of parts are sorted in descending order, and the numbering of mechanical parts corresponding to the sorting results is the optimized fault location scheme, so as to realize the fault location by checking the number of mechanical parts as little as possible, and the corresponding average number of checked mechanical parts is It helps to determine the number of maintenance personnel, repair tools and maintenance man-hours in the maintenance management work.
附图说明Description of drawings
图1为本发明实施例提供的一种机械设备故障定位优化方法流程图。Fig. 1 is a flow chart of a mechanical equipment fault location optimization method provided by an embodiment of the present invention.
图2为本发明实施例提供的仿真验证结果示意图。FIG. 2 is a schematic diagram of a simulation verification result provided by an embodiment of the present invention.
具体实施方式detailed description
为了使本发明的目的、技术方案及优点更加清楚明白,以下结合附图及实施例,对本发明进行进一步详细说明。应当理解,此处所描述的具体实施例仅仅用以解释本发明,并不用于限定本发明。此外,下面所描述的本发明各个实施方式中所涉及到的技术特征只要彼此之间未构成冲突就可以相互组合。In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not constitute a conflict with each other.
本发明涉及的机械设备包括多个机械件,所述机械件的寿命均服从于正态分布,整个任务时间内任意时刻最多一个机械件发生故障,故障排查时各机械件的状态检查的次序独立不相关,各机械件故障排查时拆卸复杂程度一致。图1为本发明实施例提供的一种机械设备故障定位优化方法流程图。如图1所示,该方法包括:The mechanical equipment involved in the present invention includes a plurality of mechanical parts, and the service life of the mechanical parts is subject to a normal distribution. At most one mechanical part fails at any time during the entire task time, and the order of the state inspection of each mechanical part is independent during troubleshooting. Irrelevant, the disassembly complexity of each mechanical part is the same when troubleshooting. Fig. 1 is a flow chart of a mechanical equipment fault location optimization method provided by an embodiment of the present invention. As shown in Figure 1, the method includes:
步骤S1.获取各机械件的寿命服从的正态分布密度函数和累计工作时间,并将机械设备的某段工作时期作为任务时间。Step S1. Obtain the normal distribution density function and the cumulative working time of the service life of each mechanical part, and use a certain working period of the mechanical equipment as the task time.
本发明的5条约定:5 stipulations of the present invention:
(1)某装备由多个机械类机械件组成,为便于描述,以时间来描述各机械件的寿命。(1) A certain equipment is composed of multiple mechanical parts. For the convenience of description, the life of each mechanical part is described in terms of time.
(2)在任意时刻,至多有1个机械件发生故障。当某机械件发生故障时会影响装备的正常工作,装备会出现某些故障现象,此时需要进行开展修理工作。(2) At any moment, at most one mechanical part fails. When a mechanical part breaks down, it will affect the normal operation of the equipment, and some failures will occur in the equipment, and repair work is required at this time.
(3)在进行故障定位时,对这些机械件进行状态检查的次序是独立不相关的,即:不存在“必须先检查机械件A、然后再检查机械件B”这类对检查次序有特定要求的情况。(3) When performing fault location, the order of checking the status of these mechanical parts is independent and irrelevant, that is, there is no such thing as "must check the mechanical part A first, and then check the mechanical part B". required situation.
(4)已知各机械件的寿命分布规律、各机械件的累计工作时间和即将执行任务的时间,可以是任意一段工作时期。(4) Knowing the life distribution law of each mechanical part, the cumulative working time of each mechanical part and the time to perform the task, it can be any working period.
(5)各机械件故障排查时拆卸复杂程度一致。(5) The disassembly complexity of each mechanical part is consistent during troubleshooting.
本发明的相关变量约定如下:机械件数量记为;机械件编号记为;机械件的寿命服从正态分布;机械件的累计工作时间记为;任务时间记为。The relevant variables of the present invention are agreed as follows: the number of mechanical parts is denoted as ; The number of the mechanical part is recorded as ; mechanical parts The life expectancy obeys a normal distribution ; mechanical parts The cumulative working hours of ; The task time is recorded as .
步骤S2.在任务时间内,结合各机械件的累计工作时间,对其寿命服从的正态分布密度函数积分计算,得到任务时间内各机械件发生故障的概率。Step S2. During the task time, combined with the cumulative working time of each mechanical part, the integral calculation of the normal distribution density function subject to its service life is performed to obtain the failure probability of each mechanical part within the task time.
优选地,步骤S2包括以下子步骤:Preferably, step S2 includes the following sub-steps:
S21.设置机械件编号。S21. Set the mechanical part number .
S22.计算任务时间内机械件发生故障的概率:S22. Calculate task time Internal Mechanical Parts probability of failure :
当时,when hour,
; ;
当时,when hour,
; ;
其中,表示机械件的数量,表示机械件的条件概率,表示机械件的寿命均值,表示机械件的寿命根方差,表示机械件的累计工作时间。in, Indicates the number of mechanical parts, Indicates mechanical parts The conditional probability of Indicates mechanical parts average lifespan, Indicates mechanical parts The lifetime root variance of Indicates mechanical parts cumulative working hours.
S23.,若,进入S22,否则,进入步骤S3。S23. ,like , go to S22, otherwise, go to step S3.
步骤S3.根据任务时间内各机械件发生故障的概率,计算任务时间内各机械件发生故障的条件概率。Step S3. According to the failure probability of each mechanical part within the task time, the conditional probability of failure of each mechanical part within the task time is calculated.
优选地,任务时间内各机械件发生故障的条件概率的计算公式如下:Preferably, the conditional probability of failure of each mechanical part within the task time The calculation formula is as follows:
。 .
步骤S4.将任务时间内各机械件发生故障的条件概率降序排序,排序结果对应的机械件编号排列,即为优化后的故障定位方案。Step S4. Sort the conditional probabilities of failures of each mechanical part within the task time in descending order, and arrange the numbers of the mechanical parts corresponding to the sorting results, which is the optimized fault location scheme.
对数组中的元素,按照从大到小进行排序得到,数组该排序的编号组成数组,的物理含义是由各机械件编号组成的检查次序,是优化后的故障定位方案。pairs of arrays The elements in are sorted from large to small to get , the array The sorted numbers form an array , The physical meaning of is the inspection order composed of the numbers of each mechanical part, which is an optimized fault location scheme.
步骤S5.按照优化后的故障定位方案依次检查各机械件的状态,直至找出发生故障的机械件。Step S5. Check the status of each mechanical part sequentially according to the optimized fault location scheme until the faulty mechanical part is found.
优选地,该方法还包括:Preferably, the method also includes:
得到优化后的故障定位方案后,计算故障定位方案的平均检查机械件数量:After obtaining the optimized fault location scheme, calculate the average number of inspection mechanical parts of the fault location scheme :
其中,为任务时间内各机械件发生故障的条件概率降序排序结果,表示中的第个元素。in, is the result of sorting the conditional probabilities of failures of each mechanical part in descending order within the task time, express in the first elements.
本发明提供了一种机械设备故障定位优化系统,包括:包括处理器和存储器;所述处理器用于存储计算机执行指令;所述处理器用于执行所述计算机执行指令,使得上述方法被执行。The present invention provides a mechanical equipment fault location optimization system, comprising: a processor and a memory; the processor is used to store computer-executed instructions; the processor is used to execute the computer-executed instructions, so that the above method is executed.
实施例:已知某机械设备由5个机械件组成,各机械件的相关信息如表1所示,即将执行150小时的任务。采用上述方法,设计该部件发生故障后的故障定位方案,计算对相关机械件的检查次序和完成故障定位所需的平均机械件检查数量。Example: It is known that a certain mechanical equipment is composed of 5 mechanical parts, and the relevant information of each mechanical part is shown in Table 1, and a task of 150 hours is about to be performed. Using the above method, design the fault location scheme after the component fails, and calculate the inspection order of the relevant mechanical parts and the average number of mechanical parts inspections required to complete the fault location.
表1 各机械件的相关信息Table 1 Relevant information of each mechanical part
1)遍历计算各机械件发生故障的概率,机械件1至机械件5,机械件发生故障的概率分别为:0.033、0.017、0.399、0.010和0.539。1) Traverse calculation of the failure probability of each mechanical part , mechanical part 1 to mechanical part 5, the probabilities of failure of mechanical parts are: 0.033, 0.017, 0.399, 0.010 and 0.539 respectively.
2)遍历计算各机械件发生故障的条件概率,机械件1至机械件5,机械件的条件概率分别为:0.03、0.02、0.40、0.01和0.54。2) Traversing and calculating the conditional probability of failure of each mechanical part , mechanical part 1 to mechanical part 5, the conditional probabilities of mechanical parts are: 0.03, 0.02, 0.40, 0.01 and 0.54 respectively.
3)对数组中的元素,按照从大到小进行排序得到[0.54 0.40 0.030.02 0.01],该排序对应的机械件编号组成数组[5 3 1 2 4],即:优化后的故障定位方案为按照机械件5、机械件3、机械件1、机械件2、机械件4的次序检查各机械件状态,直至找到故障原因为止。3) pairs of arrays The elements in are sorted from large to small to get [0.54 0.40 0.030.02 0.01], the numbers of mechanical parts corresponding to this sort form an array [5 3 1 2 4], that is, the optimized fault location scheme is to check the status of each mechanical part in the order of mechanical part 5,
4)令=1.56,即:故障定位方案的平均检查机械件数量为1.56。4) order =1.56, that is: fault location scheme The average number of inspected mechanical parts is 1.56.
5)输出、。5) output , .
可建立仿真模型验证上述方法的正确性,仿真模型简述如下:A simulation model can be established to verify the correctness of the above method. The simulation model is briefly described as follows:
(1)产生个随机数,,服从机械件的寿命分布规律,且要求所有的成立,则各机械件的剩余寿命。(1) produce random numbers , , obedience mechanical parts The lifetime distribution law of , and requires all established, the remaining life of each mechanical part .
(2)在所有中寻找最小数,对应的序号记为,即:。(2) in all Find the minimum number in , and the corresponding serial number is recorded as ,which is: .
(3)若成立,则本次仿真有效,查找故障机械件在故障定位方案中的位置,位置序号记为,则在本次模拟故障定位中共检查个机械件。(3) If If it is established, the simulation is valid, and the position of the faulty mechanical part in the fault location scheme is found, and the position number is recorded as , then check in this simulated fault location mechanical parts.
在大量多次模拟后,可统计得到故障定位检查机械件数量的均值。After a large number of simulations, the average value of the number of fault location inspection mechanical parts can be obtained statistically.
上述实施例的全部故障定位方案数量为120。采用上述仿真模型,可模拟得到这120个方案的检查机械件数量均值。图2为本发明实施例提供的仿真验证结果示意图。如图2所示,这些方案中,最大检查机械件数量为4.43,最小检查机械件数量为1.57,该值与本发明方法的最优方案结果1.56极为吻合,本发明方法的优化效果明显。The number of all fault location solutions in the above embodiment is 120. Using the above simulation model, the average number of inspection mechanical parts of the 120 schemes can be simulated. FIG. 2 is a schematic diagram of a simulation verification result provided by an embodiment of the present invention. As shown in Figure 2, among these schemes, the maximum number of inspection mechanical parts is 4.43, and the minimum number of inspection mechanical parts is 1.57, which is very consistent with the optimal solution result 1.56 of the method of the present invention, and the optimization effect of the method of the present invention is obvious.
大量仿真验证结果表明:本发明方法能综合考虑装备的可靠性(各机械件的寿命分布规律)、装备的健康状态(累计工作时间)和任务时间等因素的影响,得到的优化方案能显著减少检查机械件数量,有效避免了不合理故障定位方案造成的较为繁重的机械件检查工作。A large number of simulation verification results show that the method of the present invention can comprehensively consider the influence of factors such as the reliability of the equipment (the life distribution of each mechanical part), the health status of the equipment (accumulated working time) and the task time, and the obtained optimization scheme can significantly reduce Check the number of mechanical parts, effectively avoiding the relatively heavy inspection of mechanical parts caused by unreasonable fault location schemes.
本领域的技术人员容易理解,以上所述仅为本发明的较佳实施例而已,并不用以限制本发明,凡在本发明的精神和原则之内所作的任何修改、等同替换和改进等,均应包含在本发明的保护范围之内。It is easy for those skilled in the art to understand that the above descriptions are only preferred embodiments of the present invention, and are not intended to limit the present invention. Any modifications, equivalent replacements and improvements made within the spirit and principles of the present invention, All should be included within the protection scope of the present invention.
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Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JPH11160400A (en) * | 1997-09-24 | 1999-06-18 | Nec Corp | Estimation method for failure part in sequential circuit and candidate extraction in estimation of failure part as well as method and apparatus for weighting thereof |
CN104517195A (en) * | 2015-01-04 | 2015-04-15 | 上海杰之能信息科技有限公司 | Fault localization automated method for motor train unit |
WO2019049406A1 (en) * | 2017-09-08 | 2019-03-14 | 株式会社日立製作所 | Failure probability evaluation system |
CN111044847A (en) * | 2019-12-30 | 2020-04-21 | 河南工程学院 | Complex power distribution network fault tolerance online fault positioning method based on probability evaluation |
CN112445635A (en) * | 2019-09-04 | 2021-03-05 | 无锡江南计算技术研究所 | Data-driven adaptive checkpoint optimization method |
Family Cites Families (2)
Publication number | Priority date | Publication date | Assignee | Title |
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JP6865189B2 (en) * | 2018-03-16 | 2021-04-28 | 株式会社日立製作所 | Failure probability evaluation system and method |
CN110135596A (en) * | 2019-04-18 | 2019-08-16 | 中国电力科学研究院有限公司 | A method and device for risk assessment and fault location of a relay protection system |
-
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Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JPH11160400A (en) * | 1997-09-24 | 1999-06-18 | Nec Corp | Estimation method for failure part in sequential circuit and candidate extraction in estimation of failure part as well as method and apparatus for weighting thereof |
CN104517195A (en) * | 2015-01-04 | 2015-04-15 | 上海杰之能信息科技有限公司 | Fault localization automated method for motor train unit |
WO2019049406A1 (en) * | 2017-09-08 | 2019-03-14 | 株式会社日立製作所 | Failure probability evaluation system |
CN112445635A (en) * | 2019-09-04 | 2021-03-05 | 无锡江南计算技术研究所 | Data-driven adaptive checkpoint optimization method |
CN111044847A (en) * | 2019-12-30 | 2020-04-21 | 河南工程学院 | Complex power distribution network fault tolerance online fault positioning method based on probability evaluation |
Non-Patent Citations (1)
Title |
---|
《海底光缆故障点电场定位技术》;胡俊波;《光纤与电缆及其应用技术》;20080430;全文 * |
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