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Rail. Eng. Science (2020) 28(2):199–211 https://doi.org/10.1007/s40534-020-00211-0 A preventive opportunistic maintenance method for railway traction power supply system based on equipment reliability 1 1 1 2 2 • • • • • Sheng Lin Nan Li Ding Feng Xiaomin Guo Weiguo Pan 2 3 Jun Wang Chao Yang Received: 13 January 2020 / Revised: 25 April 2020 / Accepted: 27 April 2020 / Published online: 3 June 2020 The Author(s) 2020 Abstract Conventional maintenance mode for the traction of TPSS as the optimization objective, the optimal main- power supply system (TPSS) is to perform scheduled reg- tenance scheme of TPSS is formulated by iterative method ular maintenance activities for power supply equipment, of maintenance strategies. The proposed method is verified while such maintenance mode may result in undue main- by introducing practical maintenance strategies and fault tenance tasks and low efficiency due to different degrada- record data of the traction transformer, circuit breaker and tion processes of different sorts of equipment. To address disconnector in an actual TPSS of a railway administration. this problem, this paper introduces a preventive oppor- Results show that the presented method can make full use tunistic maintenance (POM) method for TPSS based on of the existing fault data to develop a POM scheme for equipment reliability. Firstly, a POM model is established TPSS. It can improve maintenance efficiency and reduce by considering the equipment reliability degradation pro- power outage time, providing guidance to formulate sci- cess based on Weibull distribution. Then, by considering entific maintenance strategies for TPSS. the total power outage time in the planned operation cycle Keywords Electrified railway Opportunistic maintenance interval Preventive opportunistic maintenance & Ding Feng Reliability Traction power supply system Weibull fengding@swjtu.edu.cn distribution Sheng Lin slin@swjtu.edu.cn Nan Li islinan@foxmail.com Xiaomin Guo 1 Introduction guoxiaomin@crscd.com.cn Weiguo Pan At present, the maintenance mode of the railway traction panweiguo@crscd.com.cn power supply system (TPSS) in China is a combination of Jun Wang scheduled maintenance, fault repair and daily inspection, wangjun2293@crscd.com.cn among which the scheduled maintenance works as the Chao Yang dominant maintenance method. Such mode can to some yangchao919@163.com extent guarantee the reliability of TPSS, while it brings School of Electrical Engineering, Southwest Jiaotong about problems of high costs, frequent maintenance and University, Chengdu 610031, China low efficiency [1–3]. Since the maintenance activities of Beijing National Railway Research & Design Institute of equipment rely on manual operation, the entire network or Signal Communication Group Company, Beijing 100070, area needs to be cut off power when equipment is under China maintenance. Therefore, frequent maintenance increases State Grid Neijiang Electric Power Supply Company, the power outage time of the system, which may not only Neijiang 641100, China 123 200 S. Lin et al. affect the operation plans of existing trains, but also sab- guaranteeing the reliability of equipment, Cuckoo opti- otage the ‘‘all-weather operation’’ of the railway and mization algorithm was adopted to solve the maintenance reduce the transportation capacity [4]. Thus, it is of great strategy with the minimum maintenance costs. The above importance to investigate how to improve the maintenance studies mainly explore the maintenance mode of the system efficiency of the TPSS and reduce the system power outage with the goal of reducing the maintenance costs. However, time. the system downtime during maintenance is not included, Current maintenance mode of TPSS in China is mainly which may result in the over-long power outage time and guided by the maintenance specifications formulated by affect the normal operation of the system. China State Railway Group Co., Ltd., and according to For current scheduled maintenance mode applied in such specifications, detailed maintenance schemes for a TPSS, the maintenance of equipment is independent of specific TPSS are then developed considering practical each other and coordination of different equipment is not situations. The maintenance schemes are formulated on considered. Since equipment reliability decreases with the annual, monthly, and daily basis. Firstly, the annual accumulation of service time, and the degradation of the maintenance schemes are formulated according to main- equipment follows a certain pattern, we consider that the tenance specifications of TPSS. Then those schemes are maintenance of multiple equipment can cooperate to be divided and specific maintenance tasks are arranged for repaired simultaneously to improve efficiency. To achieve each month and each week. Finally, a detailed maintenance this, Berg proposed the concept of opportunistic mainte- work ticket for specific equipment is filed, which specifies nance strategy [10]. Such strategy is defined that: when one detailed procedures to implement the maintenance tasks. piece of equipment in the system failed, if the service life Since the equipment operation condition may change dur- of another piece of equipment exceeds a preset limit, both ing its operation, a routine inspection is performed in will be repaired or replaced at the same time [11–13]. addition to scheduled maintenance, and the equipment Zhang et al. [14] and Atashgar et al. [15] made use of the operation condition is then obtained to adjust maintenance system downtime during maintenance, and advanced the scheme accordingly. Meanwhile, the maintenance mode of maintenance time of some equipment. This sort of simul- emergency repair is also included: when the equipment taneous maintenance mode of multiple equipment effec- endangers the safe operation of the TPSS, immediate tively reduced maintenance costs. Wang et al. [16] maintenance tasks are performed [5]. In conclusion, at researched the preventive maintenance strategy of the present the scheduled maintenance mode, which is devised component-layer of the electric multiple units. By combing according to maintenance specifications of railway the maintenance operation plans of related components administration, is mainly adopted in TPSS. within the opportunistic maintenance mileage, it effec- tively reduced the number of system maintenance down- Regarding the problems of high costs, frequent main- tenance, and low efficiency of scheduled maintenance time. Xie et al. [17] considered the special working mode, many scholars have explored the maintenance environment of wind turbines and adopted the oppor- modes of various systems. Huang et al. [6] proposed a real- tunistic maintenance strategy. By optimizing the preven- time maintenance method for the machine tools on the tive maintenance age and the opportunistic maintenance production line, and established a data-driven model of a age, the system maintenance costs are significantly serial production line for analysing production dynamics, reduced. In the above studies, the opportunistic mainte- which effectively reduced the maintenance costs of nance strategy is applied to optimize the maintenance costs machine tools. Chen et al. [7] established a state-based of the system, but the reliability requirements of the adaptive maintenance model for degraded systems with equipment are not considered during the optimization different operating conditions, and the optimal mainte- process. To solve this problem, Zhao et al. [18] considered nance cost allocation and maintenance threshold was the reliability of each component, and introduced the determined by the maximum availability function. Ref. [8] concept of opportunistic maintenance based on the pre- optimizes the maintenance of the multi-state manufacturing ventive maintenance mode. By cooperating the mainte- system. In view of the limitation of maintenance resources, nance of multiple components, the total costs are a maintenance optimization model considering uncertain significantly reduced. Besnard et al. [19] proposed a maintenance effect is proposed. This model solves the strategy based on opportunistic maintenance for wind tur- optimal maintenance strategy under the constraints of bine components, and utilized the golden section method to maintenance time and costs. Afzali et al. [9] studied the optimize the reliability of opportunistic maintenance. maintenance strategy of substation equipment, and estab- However, the same reliability measurement was adopted lished the indicator model of equipment life efficiency. for all the components, and yet it failed to reflect the dif- Then a method for optimal maintenance of substation ferent reliability requirements of different components. In equipment was proposed. Under the condition of view of this, Zhao et al. [20] proposed a preventive Rail. Eng. Science (2020) 28(2):199–211 A preventive opportunistic maintenance method for railway traction power supply system based… 201 opportunistic maintenance (POM) strategy for wind tur- according to the stepwise distribution of power outage bines considering different reliability requirements of each time. Finally, Sect. 5 presents the conclusions of this paper. component. The reliability maintenance margin was introduced to optimize the opportunistic maintenance interval of components to obtain the minimum mainte- 2 POM theory based on equipment reliability nance costs. But such margin was considered identical for all the components, and thus the differences of the relia- A conceptual framework is presented to clearly demon- bility degradation curves for each component cannot be strate the work of this paper, as shown in Fig. 1. Based on appropriately described. the historical fault data, the Weibull distribution is used to In order to deal with the aforementioned problems, this describe the equipment reliability. With the POM method, paper proposes a POM method for TPSS based on equip- the optimal maintenance strategy for the TPSS is formu- ment reliability. Firstly, the Weibull distribution is used to lated by minimizing the total power outage time in the characterize the reliability degradation process of the planned operation cycle under the constraint of equipment equipment. Then a POM model for the TPSS is established, reliability requirement. Such strategies are then used to and the optimal maintenance scheme is achieved by min- guide on-site maintenance work. imizing the total power outage time during the planned The reliability of power supply equipment in TPSS operation cycle of the TPSS. The contributions of this decreases with service time, and the reliability function paper are as follows: follows a certain probability distribution. TPSS consists of different types of equipment, and each type shows dis- 1. The proposed method makes full use of the historical tinctive failure period and failure process; therefore it is fault data of equipment in TPSS, and introduces the difficult to describe the reliability degradation processes of Weibull distribution to characterize the reliability the equipment using simple exponential distribution or function of the equipment. By combining the current normal distribution [21, 22]. While Weibull distribution maintenance cycle of the equipment, equipment reli- can well reflect the impact of equipment defects and daily ability in accordance with actual requirement is deterioration on its reliability since such distribution is estimated. obtained on the basis of the weakest chain model or series 2. It considers the differences in the degradation pro- model [23]. This paper introduces the two-parameter cesses of different types of equipment. By setting Weibull distribution to describe the degradation trend of corresponding reliability maintenance margin, the the equipment [24, 25]. The reliability function is presented opportunistic maintenance interval of each piece of as follows: equipment is then calculated and the simultaneous maintenance among multiple equipment can be RðtÞ¼ exp ; t [ 0 ; ð1Þ achieved as far as possible within the planned oper- ation cycle. where g represents the scale parameter and m the shape 3. Through the proposed method, POM of power supply parameter. Combining with the historical fault data of the equipment in TPSS can be realized. System downtime equipment, the two parameters are calculated according to is reduced though simultaneous maintenance of mul- the least square method. Figure 2 shows the reliability tiple equipment. Compared with the traditional fixed degradation curve described by the Weibull distribution cycle preventive maintenance mode, the proposed [20]. method can effectively reduce power outage time and The difference of reliability value between two time improve maintenance efficiency. points is defined as the reliability maintenance margin, The paper is organized as follows: In Sect. 2, the POM which describes the degradation trend of the equipment [20]. As shown in Fig. 2, the difference between reliability theory is explained; Weibull distribution is introduced to characterize the reliability degradation process of equip- R and R , denoted by DR, is the reliability maintenance 1 2 margin in this case. Meanwhile, DT represents the length of ment; the reliability maintenance margin is defined to describe the opportunistic maintenance interval of the interval [T , T ], which refers to the operation time related 1 2 to reliability R and R . According to the slope of the equipment. Section 3 establishes the POM model for TPSS 1 2 by minimizing the total power outage time during the reliability degradation curve at T , denoted by k, the rela- planned operation cycle. Section 4 presents a cases study: tionship between DR and DT can be expressed as follows: based on an actual TPSS, the minimum power outage time under different reliability maintenance margins is solved. Then the optimal maintenance scheme is determined Rail. Eng. Science (2020) 28(2):199–211 202 S. Lin et al. Power supply equipment in TPSS Specific maintenance scheme Transformer Disconnector Perform maintenance GIS Pantograph Maintenance- Weibull Historical related data distribution fault data Reliability requirements TPSE reliability Preventive degradation function opportunistic maintenance Preventive Optimization objective: model opportunistic minimum power outage time Develop an optimal maintenance maintenance scheme method Fig. 1 Framework of the POM for TPSS According to the relationship between DR and DT, POM is presented: a minimum reliability R is determined for each piece of equipment, and the corresponding operation M (T ,R ) 1 1 time is regarded as the preventive maintenance time T . N (T ,R ) 2 2 The time prior to T by DT is defined as the POM time, RR – denoted as T ; the interval DT at this time is the oppor- 12 o k = tunistic maintenance interval, and the POM can be per- TT – formed on the equipment within this interval. In this manner the maintenance time of the equipment is extended from a single time point to a time period. This allows the Operating time t maintenance of equipment to cooperate with each other; Fig. 2 Reliability degradation curve thus the simultaneous maintenance can be realized. In actual maintenance, the equipment performance may DR not be fully restored after maintenance [20]. In order to jj k ¼ ¼ RðT Þ characterize the impact of the latest maintenance on the DT m1 m current equipment operation, a repair factor k (0 \ k B 1) m T T 2 2 ¼ exp ð2Þ is introduced to describe the state of the equipment. When g g g k = 1, it means that the equipment is ‘‘fully recovered’’ in m1 m T the latest repair, and we deem the equipment operation ¼ RðT Þ: g g time returns to zero. When 0 \ k \ 1, it means that the equipment performance ‘‘restores to certain degree’’, and Given DR, the opportunistic maintenance interval the operation time is considered to fall back by a certain DT can be determined through Eq. (2); besides, Eq. (2) period. The POM method is presented by analysing typical shows that the length of the opportunistic maintenance power supply equipment operating in a TPSS [26], sche- interval DT can be adjusted by changing the reliability matic diagram shown in Fig. 3. maintenance margin DR. Due to differences in the For equipment a, b, and c, the preventive maintenance reliability function of different equipment, for the same interval for each are denoted by T , T and T , and the a b c DR, the value of DT may be different. When the slope of opportunistic maintenance interval are [T , T ], [T , o(a) p(a) o(b) the reliability curve increases, the value of DT decreases T ] and [T , T ], respectively. During the operation p(b) o(c) p(c) for a fixed DR. While if the slope of that curve decreases, of TPSS, the POM strategy works as follows: DT increases. Rail. Eng. Science (2020) 28(2):199–211 Reliability R(t) A preventive opportunistic maintenance method for railway traction power supply system based… 203 Fig. 3 Schematic diagram of preventive opportunistic maintenance (POM) (a) When the operation time of equipment a reaches the 3 POM model for TPSS preventive maintenance time T , the first-round of p(a1) maintenance is performed for the system: equipment a 3.1 The composition of power outage time undergoes the preventive maintenance; the POM is considered for equipment b since the opportunistic Due to the particularity of the TPSS, we desire to reduce maintenance interval of equipment b overlaps with the power outage time as much as possible while ensuring that of equipment a (shown as the shaded part in the reliability of the equipment during maintenance activ- Fig. 3); while equipment c obtains no opportunity of ities. In the formulation of maintenance strategies for maintenance since its opportunistic maintenance TPSS, power outage time has become an important indi- interval does not overlap with that of equipment a. cator. The power outage times of the TPSS for preventive Equipment a and b are fully recovered subsequent to maintenance and POM mode are different. The power this round of maintenance, and the operation times of outage time includes the following two parts: both are considered as zero. 1. Maintenance operation time: The time that mainte- (b) When the operation time reaches T , the second- p(c1) nance personnel spends on repairing the equipment, round of maintenance is performed. It is noted that denoted as T . maint the opportunistic maintenance intervals of equipment 2. Power supply scheduling time: The time prior to power do not overlap, and therefore maintenance is only restoration after the maintenance is completed, performed for equipment c. denoted as T . ps (c) In the third-round of maintenance, equipment a and b are repaired simultaneously for the opportunistic For the power supply equipment in TPSS, the power maintenance interval of them overlapped. outage time of preventive maintenance T includes pmot (d) Similarly, in the fourth-round of maintenance, equip- maintenance operation time T and power supply maint ment a and b undergo POM during the preventive scheduling time T , while the power outage time of POM ps maintenance of equipment c. T only includes maintenance operation time T . omot maint By implementing POM, the number and duration of 3.2 POM model maintenance downtime can be effectively reduced. Each time the equipment is under maintenance following its For a TPSS that consists of n pieces of power supply preventive maintenance plans, a certain period of mainte- equipment, when the reliability of equipment k degrades to nance downtime is required. However, by applying POM, the minimum reliability R , preventive maintenance is p(k) when there is equipment under preventive maintenance, required to maintain the reliability of equipment k. The other equipment can be repaired simultaneously during the corresponding preventive maintenance time is denoted as maintenance downtime. In this manner, during this single T . As for the preventive maintenance mode, when p(k) power outage period, multiple pieces of equipment are equipment reliability degrades to R , preventive main- p(k) repaired, which significantly reduces the total power outage tenance is performed. If equipment k is fully recovered time and improves maintenance efficiency. after maintenance, it will be repaired when its reliability Rail. Eng. Science (2020) 28(2):199–211 204 S. Lin et al. degrades to R again. The preventive maintenance model through adjusting such margins, the opportunistic mainte- p(k) is as follows: nance interval of each piece of equipment can be over- lapped to the greatest extent. Thus, simultaneous M ¼ T=T ðk ¼ 1; 2; ...; nÞ; < k pðkÞ n maintenance among equipment can be maximized to ð3Þ T ¼ T M ; : ptot pmotðkÞ pðkÞ achieve the optimal maintenance strategy of TPSS. At the k¼1 same time, the repair factor k is used to characterize the where M is the number of preventive maintenances of p(k) impact of this maintenance on the next operation of equipment k; T is the planned operation cycle of the TPSS; equipment. The reliability function and reliability require- T is the preventive maintenance cycle of equipment k; T k ptot ment of the equipment are combined to ensure the is the total power outage for preventive maintenance of the rationality of the opportunistic maintenance interval. TPSS; T is the preventive maintenance power outage pmot(k) time of equipment k. 3.3 POM decision process In the preventive maintenance model, the maintenance of equipment is independent of each other and the coor- POM decision for TPSS is an iterative optimization pro- dination of multiple equipment is not considered. As a cess. Firstly, according to the reliability maintenance result, the total power outage time can be long when sev- margin DR of each piece of equipment, combining with (k) eral pieces of equipment need maintenance. While for the the POM method, the preventive maintenance times M p(k) POM method, when preventive maintenance is being per- and POM times M of each are counted until the oper- o(k) formed for equipment k due to its reliability degradation to ation time of the TPSS reaches the planned operation cycle. R , other equipment of which the preventive maintenance Then, through the objective function of the POM model, p(k) time approaches that of equipment k can be repaired the total power outage time of TPSS can be obtained. The simultaneously. The POM model is as follows: total power outage times of the TPSS corresponding to the () z different reliability maintenance margin DR of each piece X (k) min T ¼ maxfT ; T gðk; h ¼ 1; 2; .. .; nÞ ; otot pmotðkÞ omotðhÞ of equipment are compared to obtain the minimum power i¼1 outage time. Finally, the maintenance scheme correspond- ð4Þ ing to the minimum power outage time is obtained, including equipment reliability maintenance margin DR , (k) s.t. maintenance time, and the specific equipment that needs to DRðkÞ be repaired at each maintenance time. The flow chart is > T T ¼ ðk ¼ 1; 2; ...; nÞ ; pðkÞ oðkÞ > m 1 ðkÞ mðkÞ shown in Fig. 4. > pðkÞ pðkÞ The POM decision process of TPSS is mainly divided gðkÞ gðkÞ into four steps as follows. kRT ¼ R ðk ¼ 1; 2; ...; nÞ ; > pðkÞ pðkÞ Step 1: Input data. It mainly includes the planned kRT ¼ R ðk ¼ 1; 2; ...; nÞ; > oðkÞ oðkÞ > P : n z ¼ M : operation cycle T of the TPSS, historical fault data, relia- pðkÞ k¼1 bility requirements and reliability maintenance margins of ð5Þ n pieces of equipment. In addition, the parameters related The objective function of the model is shown in Eq. (4), to power outage time are also obtained. where T is the total power outage time of POM; T otot omot(h) Step 2: Acquisition of equipment maintenance interval. is the POM power outage time of the equipment h; z is the The Weibull distribution is used to characterize the relia- number of preventive maintenances within the planned bility function of the equipment, and the POM method is operation cycle of the TPSS. In each preventive applied to the TPSS. The maintenance interval of each maintenance, compare the power outage time of piece of equipment is determined by the reliability main- preventive maintenance (T ) with that of POM pmot(k) tenance margin. (T ), and select the longer time as the standard for omot(h) Step 3: Establishment of decision model for POM this maintenance. Finally, by adding up the power outage strategy. After determining the reliability maintenance time of all preventive maintenances the total power outage margin of each piece of equipment, preventive mainte- time of POM can be obtained. nance or POM is performed for the equipment according to The constraints of the model are shown in Eq. (5). The the cooperation of the opportunistic maintenance interval slope of the reliability function is combined with the of such equipment, and the preventive maintenance times opportunistic maintenance interval, and the reliability M and POM times M of the equipment are counted p(k) o(k) maintenance margin is used to characterize the oppor- until the operation time of the TPSS reaches the planned tunistic maintenance interval. Different reliability mainte- operation cycle. Finally, according to the power outage nance margins are specified for different equipment, and time parameters, the corresponding system power outage Rail. Eng. Science (2020) 28(2):199–211 A preventive opportunistic maintenance method for railway traction power supply system based… 205 Fig. 4 The flow chart of POM strategy for TPSS time, maintenance time and the equipment that needs to be 4 Case study repaired at each maintenance time are obtained. Step 4: Formulation of the optimal maintenance scheme. 4.1 Input data of model Update the reliability maintenance margin of each piece of equipment until such margin of all equipment meets the 4.1.1 Fault data of power supply equipment in TPSS requirements. Compare the system power outage time under different reliability maintenance margins, and choose Typical power supply equipment in TPSS including the maintenance scheme corresponding to the minimum transformer, circuit breaker and disconnector is introduced power outage time, which is the optimal maintenance for the case study. The statistical data of these power scheme for the TPSS. supply facilities of the same batch under the same technical specifications were collected. These data were acquired Rail. Eng. Science (2020) 28(2):199–211 206 S. Lin et al. from a power supply section in China Railway Adminis- manufacturing shall meet strict requirements. It is highly tration from June 2016 to June 2019. The fault tables of reliable and equipment failure hardly occurs. Therefore, in equipment can be obtained after filtering and sorting the order to avoid excessive maintenance of the transformer, its fault data, as given in Tables 1, 2 and 3. maintenance cycle is set to 1.15 years. Considering the Based on the fault data of the power supply equipment, frequent action of the circuit breaker, it is prone to failure the least square method is used to solve the Weibull during operation [28]. To avoid insufficient maintenance of parameters of each piece of equipment. Then the reliability the circuit breaker, the maintenance cycle is set to functions of the transformer, circuit breaker and discon- 0.85 years. Because the differences in the preventive nector are, respectively, obtained as follows: maintenance cycle of each piece of equipment can better reflect the advantages of POM, the maintenance cycle of 2:99 R ðtÞ¼ exp ; ð6Þ 1 the disconnector is considered as 1 year. Given the main- 2:01 tenance cycle of each piece of equipment, combined with 3:04 the equipment reliability function R(t) represented by the R ðtÞ¼ exp ; ð7Þ 1:33 two-parameter Weibull distribution in Eq. (1), the relia- bility requirement of the equipment in actual operation can 3:15 R ðtÞ¼ exp : ð8Þ 3 be obtained. 1:46 Table 4 gives the Weibull distribution parameters of the Reliability degradation curves of these types of equipment, reliability requirements, maintenance operation equipment are shown in Fig. 5. time, and power supply scheduling time. In the case study, the equipment features high reliability The reliability degradation curves of the equipment in Fig. 5 describe the degradation law of equipment of the requirement and long planned operation cycle. Multiple iterations will be carried out during the maintenance same batch under the same technical specifications, which is not applicable to each piece of independent equipment. If decision; thus the value of repair factor k has a huge impact such batch of equipment is not maintained during opera- on the outcome of the decision. In order to facilitate the tion, the reliability degradation law can be described by the simulation and calculation of the model, in this paper we curves above. consider the repair factor k =1. 4.1.2 Parameter setting for each type of equipment 4.2 The solution process of POM model In the case study part, by referring to the ‘‘High-speed Given the reliability maintenance margin of the equipment, Railway Traction Substation Operation and Maintenance DR , DR and DR , the opportunistic maintenance (1) (2) (3) Regulations’’ and combining the actual situation of TPSS, interval [T , T ] of each piece of equipment can be o(k) p(k) obtained. Since the value of DR determines the oppor- the planned operation cycle is regarded as 20 years [27]. (k) According to the current maintenance rules for TPSS, the tunistic maintenance time of the equipment and meanwhile specified maintenance cycles for transformer, circuit DR is a non-zero value according to the definition of (k) breaker and disconnector are 1 year, but the actual main- POM, the minimum value of DR is set to 0.02. In addi- (k) tenance cycle can be expanded and contracted by 15% on tion, according to the results of multiple tests, to avoid this basis [5]. Based on this, the preventive maintenance over-repair of the equipment, we set the maximum value of cycle of each piece of equipment is adjusted so as to better DR as 0.2 to limit the opportunistic maintenance interval (k) realize POM of the power supply equipment. As the key for the equipment. According to the flow chart of POM equipment of the TPSS, the transformer’s design and strategy, the POM times M and preventive maintenance o(k) Table 1 Transformers fault data Basic information Fault conditions Serial number Fault time Cause of fault Commissioning date 1 2017-08-03 Oil leakage at welding point of flange connection 2016-06-15 2 2017-08-29 Gas relay oil leakage 3 2017-12-28 Oil leakage of butterfly valve 4 2018-01-08 Oil leakage on top of high-pressure casing 5 2018-12-29 Terminal box Temperature controller fails to heat up 6 2019-04-28 Oil tank gasket broken Rail. Eng. Science (2020) 28(2):199–211 A preventive opportunistic maintenance method for railway traction power supply system based… 207 Table 2 Circuit breakers fault data Basic information Fault conditions Serial number Fault time Serial number Fault time Commissioning date 1 2017-01-07 11 2017-07-21 2016-06-15 2 2017-01-24 12 2017-07-25 3 2017-02-14 13 2017-08-11 4 2017-03-29 14 2017-10-14 5 2017-04-24 15 2017-10-16 6 2017-05-22 16 2017-10-19 7 2017-06-12 17 2017-10-27 8 2017-06-17 18 2017-12-12 9 2017-07-01 19 2019-04-07 10 2017-07-08 20 2019-04-23 Table 3 Disconnectors fault data Basic information Fault conditions Serial number Fault time Serial number Fault time Commissioning date 1 2017-01-23 9 2017-11-02 2016-06-15 2 2017-02-25 10 2017-11-05 3 2017-03-11 11 2017-11-20 4 2017-06-25 12 2017-12-11 5 2017-08-07 13 2017-12-28 6 2017-08-13 14 2018-01-05 7 2017-09-28 15 2019-06-30 8 2017-10-12 times M of each piece of equipment can be obtained. p(k) Transformer Combining with the objective function of the model, the Circuit breaker 0.8 total power outage time T of POM can be obtained. otot Disconnector Finally, the distribution of total power outage time is rep- 0.6 resented by the scatter diagram, as shown in Fig. 6. In Fig. 6, the coordinate (DR , DR , DR ) represents (1) (2) (3) 0.4 the reliability maintenance margin of transformer, circuit breaker and disconnector, respectively. The colour of each 0.2 point in the space reflects the total power outage time of the TPSS. As shown in the figure, the distribution of power outage time is block-shaped. When DR , DR and DR (1) (2) (3) 0 0.5 1 1.5 2 2.5 3 3.5 4 change within a certain range, the corresponding power Operating time t (year) outage time remains the same. When DR and DR (1) (3) Fig. 5 Reliability degradation curves of equipment Table 4 Related data for equipment Equipment Reliability requirements m g Maintenance operation time (h) T (h) ps Transformer 0.83 2.01 2.99 2.00 0.03 Circuit breaker 0.77 1.33 3.04 1.67 Disconnector 0.74 1.46 3.15 1.50 Rail. Eng. Science (2020) 28(2):199–211 Reliability R(t) 208 S. Lin et al. Power outage time (h) showing a downward trend. For a small value of DR , (k) corresponding opportunistic maintenance interval DT is (k) 0.2 85 small. In this case it is similar to the normal preventive maintenance, and the advantages of POM cannot be fully 0.15 expressed. This results in a longer power outage time. 75 When DR increases, the corresponding opportunistic (k) maintenance interval DT increases. There is a good (k) 0.1 chance that the opportunistic maintenance interval among different equipment overlap; thus it is more likely to 0.05 implement simultaneous maintenance and reduce power outage time. The curve of the minimum power outage time 0 for the circuit breaker is a straight line. This is due to that 0.2 the circuit breaker compared with other equipment, has the 0.1 0.2 50 0.15 0.1 shortest preventive maintenance cycle and undergoes the 0.05 most preventive maintenance. The cooperation among equipment has been maximized, and the change of DR (k) Fig. 6 The total power outage time corresponding to the maintenance will not lead to any change of power outage time. The margin of each piece of equipment power outage time of the TPSS is determined by the pre- ventive maintenance times M and the POM times M p(k) o(k) change as independent variables, respectively, the power of each piece of equipment. M and M are affected by p(k) o(k) outage time is decreasing; when DR changes, the power (2) the reliability maintenance margin DR , but will not (k) outage time remains unchanged. The influence of setting change in real-time with the change of DR . Therefore, the (k) DR , DR and DR each as independent variable on the (1) (2) (3) maintenance times corresponding to DR in a certain (k) total power outage time of TPSS is discussed below. range is fixed; that is, the power outage time remains Figure 7 depicts that when the reliability maintenance unchanged. As a result, the distribution of the power outage margin of the transformer DR is set as independent (1) time is block-shaped in Fig. 6 and the power outage time variable, the power outage time decreases from 67.14 h. curves in Fig. 7 are stepwise changed. When DR [ 0.13, the minimum power outage time is (1) According to the minimum power outage time curves 48.72 h. When the reliability maintenance margin of the corresponding to the reliability maintenance margin of the circuit breaker DR is set as independent variable, the (2) three types of equipment, the minimum power outage time minimum power outage time in the system is 48.72 h. in the three curves is 48.72 h. From this, it can be deter- When the disconnector reliability maintenance margin mined that the minimum power outage time of the TPSS in DR is set as independent variable, the minimum power (3) this case is 48.72 h. Because the power outage time dis- outage time of the system decreases from 72.9 h. When tribution of the TPSS is block-shaped, the minimum power DR [ 0.11, the minimum power outage time is 48.72 h. (3) outage time does not correspond to a single value of the The curves of the minimum power outage time of the reliability maintenance margin. By analysing Fig. 6, the transformer and the disconnector have the same trend, both equipment reliability maintenance margin corresponding to the minimum power outage time of the TPSS can be rep- resented in Fig. 8. (0.07 , 72.9) Transformer The shaded part in Fig. 8 is the range of equipment Circuit breaker reliability maintenance margin corresponding to the mini- (0.09 , 67.14) Disconnector mum power outage time. It is worth noting that the values of the reliability maintenance margin of the circuit breaker and that of the disconnector, denoted by DR and DR (2) (3) respectively, are not completely continuous in Fig. (b). When 0.16 B DR B 0.20, the value of DR is limited to (2) (3) [0.10, 0.14] and [0.18, 0.20]. Apart from the above con- (0.14 , 48.72) ditions, the values of the reliability and maintenance mar- gin of each piece of equipment are continuous. The values 0 0.04 0.08 0.12 0.16 0.2 of DR in the shaded part of the figure correspond to the (k) Reliability maintenance margin ΔR minimum power outage time of the TPSS. The optimiza- tion results of the POM strategy are explained in Table 5. Fig. 7 Minimum power outage time curves of each piece of equipment Rail. Eng. Science (2020) 28(2):199–211 Total power outage time T (h) Transformer ΔR otot (1) A preventive opportunistic maintenance method for railway traction power supply system based… 209 Fig. 8 Range of equipment reliability maintenance margin corresponding to the minimum power outage time Since a larger value of the reliability maintenance time. In current maintenance mode of TPSS, the preventive margin DR corresponds to a larger opportunistic main- maintenance method is mainly adopted for power supply (k) tenance interval DT , and it is more likely to implement equipment, and the preventive maintenance times and total (k) simultaneous maintenance. Therefore, each piece of power outage time of each piece of equipment can be equipment obtains the maximum maintenance interval obtained through preventive maintenance models. In when DR = 0.20, the corresponding maintenance relia- Table 6, the results of optimal decision-making for POM (k) bility interval is given in Table 5, which is in line with the method are compared with the results of preventive current maintenance reliability requirements. maintenance. In Table 6, the total number of preventive maintenances 4.3 Analysis of maintenance strategy results for the POM method is 24, which is 36 times less than the total number of 60 times without considering the POM. The minimum power outage time of the TPSS is calculated Although the maintenance number for each piece of for the POM model. Although the minimum power outage equipment in POM has increased, multiple pieces of time corresponds to multiple sets of reliability maintenance equipment can be maintained simultaneously under certain margin DR , the final maintenance scheme is consistent. circumstances, and the total power outage time of the TPSS (k) The specific maintenance scheme for POM is shown in has decreased significantly. The power outage time has Fig. 9. been reduced from 104.21 to 48.72 h, and the POM strat- Figure 9 shows that during the planned operation cycle egy has saved 55.49 h compared to preventive mainte- of the TPSS, each piece of equipment has been repaired 24 nance. The time saved mainly includes the power supply times, of which only the circuit breaker underwent pre- scheduling time and the maintenance time of transformer ventive maintenance, and the transformer and disconnector and disconnector during preventive maintenance of the only underwent POM. This is because the differences equipment, which makes up 53.2% of the total power among the preventive maintenance cycle of transformer, outage time. Obviously, the POM strategy can make full circuit breaker and disconnector are small. When the pre- use of the maintenance operation time and reduce the total ventive maintenance time of each piece of equipment is power outage time of the TPSS. advanced, it is easy to achieve simultaneous maintenance among the equipment, thereby saving more power outage Table 5 Optimization results of the POM strategy (when 0.16 B DR B 0.20, DR = [0.14, 0.18]) (2) (3) Equipment T (year) DR [T , T ] (year) DT (year) [R , R ] T (h) (k) (k) o(k) p(k) (k) p(k) o(k) otot Transformer 1.15 0.12 B DR B 0.20 [0.65, 1.15] 0.50 [0.83, 0.96] 48.72 (1) Circuit breaker 0.85 0.02 B DR B 0.20 [0.58, 0.85] 0.27 [0.77, 0.92] (2) Disconnector 1.00 0.10 B DR B 0.20 [0.71, 1.00] 0.29 [0.74, 0.90] (3) Rail. Eng. Science (2020) 28(2):199–211 210 S. Lin et al. Fig. 9 Specific maintenance scheme for POM of TPSS Table 6 Comparison of preventive maintenance and preventive opportunistic maintenance (POM) results Equipment Traditional preventive maintenance Preventive opportunistic maintenance M T (h) M M T (h) p o p Transformer 17 104.21 24 0 48.72 Circuit breaker 23 0 24 Disconnector 20 24 0 the current scheduled maintenance mode, but also 5 Conclusions saves power outage time. In this paper, a preventive opportunistic maintenance method based on equipment reliability for the traction Acknowledgements This work was supported in part by the National power supply system is proposed, with the goal of mini- Natural Science Foundation of China under Grant (51907166), the Science and Technology Project of CHINA RAILWAY under Grant mizing the total power outage time during the planned (2017J001-F & N2018G023) and the Sichuan Science and Technol- operation cycle of the TPSS. By applying the fault data of ogy Program under Grant (2018GZ0020). transformer, circuit breaker and disconnector in an actual power supply section as input, the POM model is verified Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, and analysed. Following conclusions are obtained: adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the 1. The proposed method uses the Weibull distribution to source, provide a link to the Creative Commons licence, and indicate characterize the reliability function of the power if changes were made. The images or other third party material in this supply equipment and obtains the opportunistic main- article are included in the article’s Creative Commons licence, unless tenance interval by defining the reliability maintenance indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended margin, which can implement the POM for the use is not permitted by statutory regulation or exceeds the permitted equipment while ensuring the reliability requirement. use, you will need to obtain permission directly from the copyright 2. POM method, by implementing simultaneous mainte- holder. To view a copy of this licence, visit http://creativecommons. nance among multiple pieces of equipment, signifi- org/licenses/by/4.0/. cantly reduces the number of system downtimes. It provides a good basis for the operation and mainte- nance unit to formulate equipment maintenance pro- References grams and achieve simultaneous maintenance. 3. The proposed method takes into account the mainte- 1. Feng D, Lin S, He ZY et al (2017) A technical framework of nance correlation among different power supply PHM and active maintenance for modern high-speed railway equipment, which not only improves the efficiency of traction power supply systems. Int J Rail Transp 5(3):145–169 Rail. Eng. Science (2020) 28(2):199–211 A preventive opportunistic maintenance method for railway traction power supply system based… 211 2. Feng D, Lin S, He ZY et al (2018) Optimization method with 15. Atashgar K, Abdollahzadeh H (2016) Reliability optimization of prediction-based maintenance strategy for traction power supply wind farms considering redundancy and opportunistic mainte- equipment based on risk quantification. IEEE Trans Transp nance strategy. Energy Convers Manag 112:445–458 Electrific 4(4):961–970 16. Wang H, Xiong L, He Y et al (2019) Optimization of oppor- 3. Wang Q, Lin S, Li T et al (2020) Intelligent proactive mainte- tunistic maintenance for electric multiple unit component con- nance system for high-speed railway traction power supply sys- sidering failure risk. J Chin Railway Soc 41(3):79–85 tem. IEEE Trans Ind Inform (Early Access). https://doi.org/10. 17. Xie LB, Rui XM, Li S et al (2019) Maintenance optimization of 1109/TII.2020.2974872 offshore wind turbines based on an opportunistic maintenance 4. Lin S, Feng D, Sun XJ (2019) Traction power-supply system risk strategy. Energies 12(14):2650 assessment for high-speed railways considering train 18. Zhao HS, Xu FH, Liang BT et al (2019) A condition-based timetable effects. IEEE Trans Rel 68(3):810–818 opportunistic maintenance strategy for multi-component system. 5. TG/GD122—2015 high-speed railway traction substation opera- Struct Health Monit 18(1):270–283 tion and maintenance rules, China Railway Corporation, Beijing, 19. Besnard F, Patriksson M, Stromberg AB et al (2011) A stochastic China model for opportunistic maintenance planning of offshore wind 6. Huang J, Chang Q, Zou J et al (2018) A real-time maintenance farms. In: Proceedings of IEEE Power Tech 2011 conference, policy for multi-stage manufacturing systems considering Norway, Trondheim imperfect maintenance effects. IEEE Access 6:62174–62183 20. Zhao HS, Zhang LP (2014) Preventive opportunistic maintenance 7. Chen YX, Gong WJ, Xu D et al (2018) Imperfect maintenance strategy for wind turbines based on reliability. Proc Chin Soc policy considering positive and negative effects for deteriorating Elect Eng 34(22):3777–3783 systems with variation of operating conditions. IEEE Trans 21. Li L, Cheng HB, Song ZC (2012) Study of health management Autom Sci Eng 15(2):872–878 and condition based maintenance for traction power supply sys- 8. Chen ZX, He YH, Zhao YX et al (2019) Mission reliability- tem of high-speed railway. In: 3rd International symposium on oriented selective maintenance optimization for intelligent mul- innovation & sustainability of modern railway (ISMR), tistate manufacturing systems with uncertain maintenance qual- pp 388–393 ity. IEEE Access 7:109804–109816 22. Tang ZY, Zhou WJ, Zhao JK et al (2015) Comparison of the 9. Afzali P, Keynia F (2017) Lifetime efficiency index model for weibull and the crow-AMSAA model in prediction of early cable optimal maintenance of power substation equipment based on joint failures. IEEE Trans Power Del 30(6):2410–2418 cuckoo optimisation algorithm. IET Generat Transmiss Distrib 23. Dong M, Nassif AB (2019) Combining modified Weibull distri- 11(11):2787–2795 bution models for power system reliability forecast. IEEE Trans 10. Nicolai RP, Dekker R (2007) A review of multi-component Power Syst 34(2):1610–1619 maintenance models. Eur Safety Rel Conf (ESREL) 3:289–296. 24. Chen ZM (2000) A new two-parameter lifetime distribution with https://www.researchgate.net/publication/287486197 bathtub shape or increasing failure rate function. Statist Probab 11. Cheng ZJ, Yang Z, Guo B (2012) Opportunistic maintenance Lett 49(2):155–161 optimization of a two-unit system with different unit failure 25. Hirose H (1999) Bias correction for the maximum likelihood patterns. In: International conference on quality, reliability, risk, estimates in the two-parameter weibull distribution. IEEE Trans maintenance, and safety engineering (QR2MSE), 15–18 June Dielectr Electr Insul 6(1):66–68 2012, Chengdu, China, pp 409–413 26. Cheng HB, Wang X, Sun NN et al (2019) Research on catenary 12. Hou WR, Jiang ZH (2013) An opportunistic maintenance policy preventive opportunistic maintenance method based on interval of multi-unit series production system with consideration of mathematics. J East Chin Jiaotong Univ 36(4):124–130 imperfect maintenance. Appl Math Inf Sci 7:283–290 27. Feng D, Lin S, He ZY et al (2018) Failure risk interval estimation 13. Abdollahzadeh H, Atashgar K, Abbasi M (2016) Multi-objective of traction power supply equipment considering the impact of opportunistic maintenance optimization of a wind farm consid- multiple factors. IEEE Trans Transp Electrific 4(2):389–398 ering limited number of maintenance groups. Renew Energy 28. Rudsari FN, Razi-Kazemi AA, Shoorehdeli MA (2019) Fault 88:247–261 analysis of high-voltage circuit breakers based on coil current and 14. Zhang C, Gao W, Guo S et al (2017) Opportunistic maintenance contact travel waveforms through modified SVM classifier. IEEE for wind turbines considering imperfect reliability-based main- Trans Power Del 34(4):1608–1618 tenance. Renew Energy 103:606–612 Rail. Eng. Science (2020) 28(2):199–211
Railway Engineering Science – Springer Journals
Published: Jun 3, 2020
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