CN116226958B - Maintenance strategy optimization method for longitudinal settling tank of rail transit tunnel - Google Patents
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Abstract
The invention relates to a maintenance strategy optimization method for a longitudinal sedimentation tank of a rail transit tunnel, which comprises the following steps: predicting the development trend of the non-uniform settlement of the tunnel under the non-maintenance condition, determining the settlement state at the end of the design service life based on the development trend, and if the settlement state at the end of the design service life exceeds the settlement state safety threshold, judging that: inputting the settlement state of the end of the designed service life into a constructed maintenance strategy model, solving the maintenance strategy model to obtain an optimal maintenance strategy, and maintaining the longitudinal settlement tank of the track traffic tunnel based on the optimal maintenance strategy. Compared with the prior art, the invention has the advantages of both operation safety and maintenance economy.
Description
Technical Field
The invention relates to the technical field of track traffic tunnel engineering, in particular to a maintenance strategy optimization method for a longitudinal settling tank of a track traffic tunnel.
Background
The track traffic tunnel in the soft soil area is easily subjected to uneven settlement in the long-term service process due to uneven distribution of the lower lying soil layer or the influence of peripheral construction load, and single or multiple settling tanks are longitudinally formed along the line. The uneven settlement of the tunnel can cause the defects of track deformation overrun, lining crack, track bed void, water seepage and mud leakage and the like, and the safety, durability and economy of the track traffic operation are affected. At present, the treatment of the longitudinal sedimentation tank of the rail transit tunnel mainly adopts passive maintenance, namely the structure is remedied after obvious uneven sedimentation occurs. This mode has the following drawbacks: firstly, lack of maintenance theoretical basis, and the existing maintenance strategy does not consider the long-term development rule of tunnel settlement; secondly, under maintenance or over maintenance is easy to occur, the concrete state of the structure is not clear by passive maintenance, and the maintenance degree is often not matched with the structure state, so that the maintenance efficiency is low and the resource is wasted; and thirdly, the maintenance cost is high, the maintenance period is long, and the normal operation of the rail transit is adversely affected. In view of the above problems with passive maintenance, the differential settlement management mode needs to be changed. However, at present, a method for deciding the maintenance of the settling tank by considering the long-term evolution process of the settling state of the tunnel is still lacking, and it is important to make an optimal maintenance strategy for the longitudinal settling tank capable of considering both operation safety and maintenance economy.
Disclosure of Invention
The invention aims to overcome the defects of the prior art, and provides a maintenance method for a longitudinal sedimentation tank of a rail transit tunnel, which has the advantages of operation safety and maintenance economy.
The aim of the invention can be achieved by the following technical scheme:
the maintenance strategy optimization method for the longitudinal settling tank of the track traffic tunnel comprises the following steps:
selecting a state evaluation index, predicting the development trend of the non-uniform settlement of the tunnel under the non-maintenance condition based on the state evaluation index, determining the final settlement state of the design service life based on the development trend, continuously monitoring the development trend of the non-uniform settlement of the tunnel if the final settlement state of the design service life is not beyond the settlement state safety threshold, and judging the final settlement state of the design service life to exceed the settlement state safety threshold if the final settlement state of the design service life is judged:
inputting the development trend of the non-uniform settlement of the tunnel under the non-maintenance condition into a constructed maintenance strategy model, solving the maintenance strategy model to obtain an optimal maintenance strategy, and maintaining the longitudinal settlement tank of the track traffic tunnel based on the optimal maintenance strategy, wherein the method adopted for solving the maintenance strategy model is a strategy iteration method, a neural network method, an ant colony method or a genetic algorithm, and the construction process of the maintenance strategy model comprises the following steps:
selecting a sampling period, maintenance time, maintenance times and maintenance places as strategy parameters to form a maintenance strategy, and generating a maintenance strategy library;
generating a maintenance effect prediction module based on the lifting amount and the sedimentation rate variation;
setting constraint conditions of a maintenance strategy model, wherein the constraint conditions comprise a settlement state safety threshold constraint condition and a cost constraint condition;
and (3) formulating a maintenance strategy objective function, wherein the maintenance strategy objective function is a function of the total maintenance cost about maintenance time, maintenance times and maintenance places.
Further, the specific steps for solving the maintenance strategy model based on the strategy iteration method are as follows:
under the same sampling period, selecting a maintenance strategy with the maintenance frequency of 1 from a maintenance strategy library, calculating the maintenance total cost of the maintenance strategy, obtaining the design service life end settlement state of the maintenance strategy based on the maintenance strategy and a maintenance effect estimation module, screening out all maintenance strategies with the maintenance frequency of 1 and meeting constraint conditions, further screening out a first maintenance strategy with the minimum maintenance strategy objective function, adding 1 to the maintenance frequency, repeating the steps, screening out a second maintenance strategy with the minimum maintenance strategy objective function from all the first maintenance strategies with different maintenance frequencies, updating the sampling period if all the maintenance strategies are not traversed, repeating the steps, updating the second maintenance strategy until all the maintenance strategies are traversed, and taking the second maintenance strategy obtained after traversing all the maintenance strategies as the optimal maintenance strategy.
Further, the maintenance policy objective function has the expression:
wherein Mt= { ta, W n (t), m, n } represents a maintenance strategy library, and includes a sampling period ta and a maintenance time W n (t), maintenance times m and maintenance site nth settling tank, C m The maintenance cost is single; c (C) c Punishment costs for failure risk required when the tunnel settlement state exceeds the settlement state safety threshold; k (K) n Overrun times for the sedimentation state of the nth sedimentation tank; d is the discount rate; n is the number of the longitudinal settling tanks; c (C) l Is of dimensionTotal cost of protection; t is the service life of the tunnel.
Further, for a single settling tank, the cost constraint condition is a total maintenance cost constraint in the design year, and for a multiple settling tank, the cost constraint condition is a total maintenance cost constraint in the design year and a total annual maintenance cost constraint.
Further, the total amount of maintenance cost in the design year is constrained to be not more than the upper limit of the total amount of maintenance cost in the design year.
Further, the total annual maintenance cost is constrained to a total annual maintenance cost not exceeding the annual planned investment in maintenance funds.
Further, the setting rule of the maintenance site is:
for a single settler, no maintenance site is provided, and for multiple settlers, the priority of the settler with poorer end-of-life settling condition is higher, with the sequencing according to the end-of-life settling condition of each settler.
Further, the development trend of the non-uniform settlement of the tunnel under the non-maintenance condition is predicted by numerical simulation analysis, empirical formula fitting, gray theoretical model or artificial intelligence prediction method.
Further, the empirical formula fitting includes fitting using a hyperbolic model, a logarithmic curve model, and an exponential curve model.
Further, the state evaluation index is an accumulated sedimentation amount, differential sedimentation or a longitudinal deformation curvature radius.
Compared with the prior art, the invention has the following beneficial effects:
(1) According to the method, on the basis of defining the long-term development rule of the non-uniform settlement state of the track traffic tunnel, the current and future settlement states of the tunnel are safely evaluated and reasonably predicted, a maintenance plan is formulated in advance according to the development trend of the settlement state of the tunnel, and the blindness of maintenance opportunity selection is reduced.
(2) The method focuses on the tunnel settlement state and the maintenance treatment cost simultaneously, obtains the optimal maintenance strategy considering both the tunnel operation safety and the maintenance economy through the comprehensive optimization process under the multi-constraint condition, improves the reliability of the tunnel structure, reduces the safety risk and simultaneously can reduce the tunnel settlement maintenance cost within the design period to the greatest extent.
(3) The method constructs a maintenance strategy library containing four strategy parameters, provides a maintenance strategy optimization method with high solving efficiency and low calculation cost, optimizes maintenance time, maintenance place, maintenance times and sampling period, and is convenient for making a long-term maintenance plan of the longitudinal sedimentation tank for the rail transit tunnel operation and maintenance department.
Drawings
FIG. 1 is a flow chart of the present invention;
FIG. 2 is a schematic diagram of the maximum cumulative sedimentation trend of a single sedimentation tank without maintenance and with an optimal maintenance strategy according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a solution flow of a single settler maintenance strategy model in accordance with an embodiment of the invention;
FIG. 4 is a schematic diagram of a multi-settler maintenance strategy model solving process in accordance with an embodiment of the invention.
Detailed Description
The invention will now be described in detail with reference to the drawings and specific examples. The present embodiment is implemented on the premise of the technical scheme of the present invention, and a detailed implementation manner and a specific operation process are given, but the protection scope of the present invention is not limited to the following examples.
Example 1:
the invention provides a maintenance strategy optimization method for a longitudinal settlement tank of a track traffic tunnel, and a flow chart of the method is shown in figure 1. The method comprises the following steps:
predicting the development trend of the non-uniform settlement of the tunnel under the non-maintenance condition, determining the settlement state at the end of the design service life based on the development trend, and if the settlement state at the end of the design service life exceeds the settlement state safety threshold, judging that:
inputting the development trend of the non-uniform settlement of the tunnel under the non-maintenance condition into a constructed maintenance strategy model, solving the maintenance strategy model to obtain an optimal maintenance strategy, and maintaining the longitudinal settlement tank of the track traffic tunnel based on the optimal maintenance strategy.
The construction process of the maintenance strategy model comprises the following steps:
selecting a sampling period, maintenance time, maintenance times and maintenance places as strategy parameters to form a maintenance strategy, and generating a maintenance strategy library; generating a maintenance effect prediction module based on the lifting amount and the sedimentation rate variation; setting constraint conditions of a maintenance strategy model, wherein the constraint conditions comprise a settlement state safety threshold constraint condition and a cost constraint condition; and (3) formulating a maintenance strategy objective function, wherein the maintenance strategy objective function is a function of the total maintenance cost about maintenance time, maintenance times and maintenance places.
The method adopted for solving the maintenance strategy model is a strategy iteration method, a neural network method, an ant colony method or a genetic algorithm.
If the settlement state does not exceed the settlement state safety threshold value at the end of the design service life, continuing to monitor the development trend of the uneven settlement of the tunnel.
The tunnel differential settlement development trend, settlement state safety threshold and settlement state at the end of the designed service life under the non-maintenance condition are set as follows:
1. development trend of non-uniform settlement of tunnel under non-maintenance condition
In the field, numerical simulation analysis and empirical formula fitting are often adopted, such as a hyperbolic model, a logarithmic curve model, an exponential curve model and the like, a gray theoretical model and an artificial intelligent prediction method, such as a neural network model, an ant colony algorithm, a support vector machine model and the like, are adopted to predict the long-term development trend of the non-uniform settlement of the tunnel under the condition of no maintenance, and the specific prediction method is determined according to the actual condition of engineering.
2. Safety threshold for sedimentation state
The safety of the tunnel structure is described by indexes such as the inter-annular staggered bench quantity, the annular seam opening quantity and the bolt stress, the mapping relation between the settlement state evaluation index and the structural safety index is established by methods such as engineering analogy, theoretical analysis or numerical simulation, and the safety threshold value [ I ] of the tunnel settlement state is determined. The technical personnel can reasonably select the tunnel settlement state evaluation index and the evaluation method according to the actual condition of the engineering to formulate a tunnel settlement state safety threshold value [ I ] suitable for the actual engineering.
3. Design of the end of life sedimentation State
And (3) evaluating the settlement state of the tunnel by adopting indexes such as accumulated settlement amount, differential settlement or longitudinal deformation curvature radius, and judging the settlement state of the tunnel according to the development trend of the uneven settlement of the tunnel under the non-maintenance condition to obtain the settlement state at the end of the design service life.
If the settlement state exceeds the settlement state safety threshold value at the end of the design service life, the maintenance decision analysis of the tunnel longitudinal settlement tank is required.
The construction process of the maintenance strategy model comprises the following steps:
1. constructing a maintenance policy repository
The maintenance strategy library Mt comprises a sampling period ta and a maintenance time W n (t), number of maintenance times m and maintenance location n, i.e. Mt= { ta, W n (t), m, n), wherein the sampling period ta is the time interval of two times of tunnel settlement observation before and after, the calculation cost is increased due to the fact that the ta value is too small, and the settlement prediction accuracy is reduced due to the fact that the ta value is too large, so that the calculation economy and the prediction accuracy are comprehensively balanced when the ta value range is determined, and the operability of settlement observation in actual engineering is considered; maintenance opportunity W n The determination of (t) is the key to maintenance decision, and in order to reduce the difficulty of maintenance opportunity selection, it is considered that the maintenance opportunity is set only at the sampling time point.
The maintenance site n is set up as follows: when the decision object is a single sedimentation tank, no maintenance site policy parameter is required to be set; when the decision object is a plurality of settling tanks, sequencing the settling tanks according to the settling states of the settling tanks in the tunnel at the end of the design service life, wherein the worse the settling states of the tunnels, the more forward the sequencing, namely the higher the maintenance priority.
2. Generating maintenance effect prediction module
And generating a maintenance effect prediction module based on the lifting amount and the sedimentation rate variation, wherein the sedimentation rate variation is described by adopting a reduction coefficient k (t). The expression of the reduction coefficient is:
v′(t)＝k(t)v(t)
in the above expression, v' (t) and v (t) represent the sedimentation rate values after and before maintenance at time t, respectively.
When the tunnel lifting quantity A and the reduction coefficient k (t) are determined, factors such as a maintenance mode, process parameters, engineering geological conditions, a tunnel settlement state before maintenance and the like are considered, and the factors can be obtained by a person skilled in the art through engineering analogy, indoor test or theoretical analysis and the like.
Before the maintenance effect is obtained, the settlement state of the tunnel at the maintenance time point under the non-maintenance condition needs to be predicted and estimated. Based on the sedimentation state, the lifting amount and the sedimentation rate change amount of the tunnel at the time point of maintenance under the condition of no maintenance, the maintenance effect prediction module can obtain the designed service life end sedimentation state when one maintenance strategy is adopted.
3. Setting constraint conditions of maintenance strategy model
The constraint includes a settlement state safety threshold constraint L 1 And cost constraint L 2 And L 3 。L 2 To maintain total cost constraint in design year, L 3 Capital constraints are maintained for annual plan investment.
(1) Constraint L 1 : the settlement state I of the tunnel does not exceed the settlement state safety threshold value [ I ]]I is less than or equal to [ I ]](2) constraint L 2 : total maintenance cost C within design year l Not exceeding its upper limit C lmax C, i.e l ≤C lmax (3) constraint L 3 : total annual maintenance cost C y No more than annual planned investment in maintenance funds C ymax C, i.e y ≤C ymax 。
The constraint condition setting principle is as follows: for a single settling tank, only the tunnel settlement state constraint L needs to be satisfied 1 And total maintenance cost L within design years 2 The method comprises the steps of carrying out a first treatment on the surface of the For multiple settling tanks, the requirements are simultaneously satisfiedTunnel settlement state constraint L 1 Total maintenance cost constraint L 2 Annual planned investment maintenance fund constraint L 3 。
To plan to invest maintenance funds C each year ymax When the distribution is carried out, the maintenance funds required by the settling tanks with higher maintenance priorities are satisfied.
4. Formulating maintenance policy objective functions
On the premise of ensuring the safety of the tunnel, determining the maintenance time W of the longitudinal sedimentation tank n (T), maintenance times m and maintenance places n such that the total cost of maintenance C within the tunnel design period T l Minimum.
Total maintenance cost C within tunnel design period T l Calculated as follows:
in the above formula, mt= { ta, W n (t), m, n } represents a maintenance strategy library, and includes a sampling period ta and a maintenance time W n (t), maintenance times m and maintenance sites n, wherein W n (t) is a variable of 0-1, 0 is taken to indicate that the nth settling tank is not maintained at the sampling time point t, and 1 is taken to indicate that maintenance is performed; c (C) m The maintenance cost is single; c (C) c Punishment costs for failure risk required when the tunnel settlement state exceeds the settlement state safety threshold; k (K) n Overrun times for the sedimentation state of the nth sedimentation tank; d is the discount rate; n is the number of longitudinal settling tanks.
The development trend of the tunnel differential settlement under the non-maintenance condition is input into a constructed maintenance strategy model, and the maintenance strategy model can be solved by adopting a strategy iteration method, a neural network method, an ant colony method or a genetic algorithm and other common optimization algorithms.
The specific steps of solving based on the strategy iteration method are as follows: under the same sampling period, selecting a maintenance strategy with the maintenance frequency of 1 from a maintenance strategy library, calculating the maintenance total cost of the maintenance strategy, obtaining the design service life end settlement state of the maintenance strategy based on the maintenance strategy and a maintenance effect estimation module, screening out all maintenance strategies with the maintenance frequency of 1 and meeting constraint conditions, further screening out a first maintenance strategy with the minimum maintenance strategy objective function, adding 1 to the maintenance frequency, repeating the steps, screening out a second maintenance strategy with the minimum maintenance strategy objective function from all the first maintenance strategies with different maintenance frequencies, updating the sampling period if all the maintenance strategies are not traversed, repeating the steps, updating the second maintenance strategy until all the maintenance strategies are traversed, and taking the second maintenance strategy obtained after traversing all the maintenance strategies as the optimal maintenance strategy.
If the maintenance times m are determined, searching for the optimal maintenance strategy under the single maintenance condition (i.e. m=1) preferentially, and if all the single maintenance strategies cannot meet the tunnel settlement state requirement, gradually increasing the maintenance times (i.e. m=m+1) again to search for the optimal solution under the maintenance timesOptimal solution in obtaining maintenance number m ∈ ->After that, the maintenance times are increased again and the solving process is repeated to obtain +.>If->Continuing to increase the maintenance times and repeating the solving process, if +.> The maintenance number m is the optimal maintenance number in the current sampling period.
The following are 2 specific examples:
example 1:
the parameters were set as follows: sampling period ta= [0.25,5 ]](Unit: year), cost of maintenance per time C m =17500 (unit:/m), failure risk penalty cost C c The discount rate d=8%, the service life T=100 years of the tunnel design, the single maintenance lifting amount A=1 mm, and the sedimentation rate discount coefficient after maintenance is a random variable k= [0.4,0.6 ]]. There is only a single settling tank.
The tunnel differential settlement curve function S (x) is in cosine distribution, and the following formula is shown:
in the above formula, L is the width of the settling tank, L=120m in this embodiment, Z is the cumulative settlement of the bottom of the settling tank, i.e. the maximum cumulative settlement, x i For measuring point mileage of tunnel, i.e. x i ∈[0,120](unit: m).
The sedimentation rate value before maintenance was calculated as follows:
V(t)＝α·e -βr
in the above formula, α and β are regression coefficients of a sedimentation rate development curve, in this embodiment, α=21.4 and β=0.08 are taken, t is tunnel operation time, and the cumulative sedimentation development trend of the tunnel within the service life can be predicted by the formula.
The maintenance method for the longitudinal sedimentation tank of the rail transit tunnel comprises the following specific steps:
SA1, adopting a longitudinal deformation curvature radius R as an evaluation index of the non-uniform settlement state of the tunnel, and determining a safety threshold value of the settlement state of the tunnel to be [ I ] = [ R ] = 2940m through theoretical analysis based on the relation between the longitudinal deformation curvature radius and the dislocation of the pipe piece, the opening amount of the circular seam and the stress state of the bolt. Predicting the development trend of the non-uniform settlement of the tunnel under the non-maintenance condition, determining the settlement state at the end of the design service life based on the development trend, and judging that the settlement state at the end of the design service life exceeds the settlement state safety threshold, namely R= 2728.07m < [ R ], as shown in figure 2. Therefore, a tunnel settlement maintenance decision analysis needs to be performed, and SA2 is performed.
SA2, determining a maintenance strategy model of the single sedimentation tank according to the model parameters. Considering the non-uniform settlement of tunnels in practiceIs relatively abundant in maintenance funds, and the total maintenance cost C is not set in the embodiment lmax Constraint. Because the single settling tank does not need to optimize the maintenance site, the optimization objective formula is degenerated into:
SA3, adopting a maintenance strategy model solved by a strategy iterative algorithm, wherein the specific flow is shown in figure 3. The optimal maintenance strategy of the single settling tank is determined based on the lowest maintenance cost, namely: maintenance was performed in 25.25 and 54.00 years, corresponding to a total maintenance cost of C in design years l ＝33.371×10 4 The maximum accumulated settlement development curve of the tunnel under the condition of the optimal maintenance strategy is shown in fig. 2, and it can be seen that the settlement state of the tunnel in the designed service life does not exceed the settlement state safety threshold.
Example 2:
the parameters were set as follows: the number of longitudinal settling tanks N=5 (serial numbers A to E), the settlement development parameter design of each settling tank is shown in table 1, and the upper limit of maintenance funds planned to be put in each year is C ymax =1000000, the remaining model parameters are the same as in example 1.
TABLE 1 Settlement development parameters of each settler
| Number of settling tank | L i (m) | Regression coefficient alpha i | Regression coefficient beta i |
| A | 110 | 22.50 | 0.10 |
| B | 120 | 22.50 | 0.09 |
| C | 120 | 26.60 | 0.09 |
| D | 130 | 24.80 | 0.08 |
| E | 140 | 28.00 | 0.08 |
The maintenance method for the longitudinal sedimentation tank of the rail transit tunnel comprises the following specific steps:
sb1 tunnel differential settlement state classification standard is the same as example 1, and tunnel settlement state safety threshold is [ I ] = [ R ] = 2940m. According to the maximum accumulated sedimentation development trend of each sedimentation tank within the service life of the tunnel design, the corresponding longitudinal deformation curvature radiuses of the sedimentation tanks A-E are calculated to be 2725.02m, 2918.52m, 2468.57m, 2762.75m and 2837.97m respectively, and the sedimentation states of the sedimentation tanks are judged to exceed the sedimentation state safety threshold, so that tunnel sedimentation maintenance decision analysis is needed to be carried out, and SB2 is executed.
And SB2, determining a maintenance strategy model of the multiple settling tanks according to the parameters. Based on the design of each settling tank at the end of the service lifeRe-sequencing the settling tanks A-E, wherein the smaller the longitudinal deformation curvature radius of the tunnel is, the higher the sequencing is, the higher the maintenance priority is, namely, the maintenance plans of all the settling tanks are sequentially formulated according to the sequencing, and finally all constraint conditions are met. The maintenance cost total amount C is not set in this example lmax Constraint.
SB3, the solving flow of the maintenance strategy model is shown in figure 4, the optimal maintenance strategy of the multiple settling tanks is determined based on the lowest maintenance cost, as shown in table 2, and the total maintenance cost in the corresponding design period is C l ＝178.317×10 4 。
TABLE 2 optimal maintenance strategy for multiple settling tanks
The foregoing describes in detail preferred embodiments of the present invention. It should be understood that numerous modifications and variations can be made in accordance with the concepts of the invention by one of ordinary skill in the art without undue burden. Therefore, all technical solutions which can be obtained by logic analysis, reasoning or limited experiments based on the prior art by the person skilled in the art according to the inventive concept shall be within the scope of protection defined by the claims.
Claims (8)
1. The maintenance strategy optimization method for the longitudinal settling tank of the track traffic tunnel is characterized by comprising the following steps of:
selecting a state evaluation index, predicting the development trend of the non-uniform settlement of the tunnel under the non-maintenance condition based on the state evaluation index, determining the final settlement state of the design service life based on the development trend, continuously monitoring the development trend of the non-uniform settlement of the tunnel if the final settlement state of the design service life is not beyond the settlement state safety threshold, and judging the final settlement state of the design service life to exceed the settlement state safety threshold if the final settlement state of the design service life is judged:
inputting the development trend of the non-uniform settlement of the tunnel under the non-maintenance condition into a constructed maintenance strategy model, solving the maintenance strategy model to obtain an optimal maintenance strategy, and maintaining the longitudinal settlement tank of the track traffic tunnel based on the optimal maintenance strategy, wherein the method adopted for solving the maintenance strategy model is a strategy iteration method, a neural network method, an ant colony method or a genetic algorithm, and the construction process of the maintenance strategy model comprises the following steps:
selecting a sampling period, maintenance time, maintenance times and maintenance places as strategy parameters to form a maintenance strategy, and generating a maintenance strategy library;
generating a maintenance effect prediction module based on the lifting amount and the sedimentation rate variation;
setting constraint conditions of a maintenance strategy model, wherein the constraint conditions comprise a settlement state safety threshold constraint condition and a cost constraint condition;
formulating a maintenance strategy objective function, wherein the maintenance strategy objective function is a function of the total maintenance cost about maintenance time, maintenance times and maintenance places;
the specific steps for solving the maintenance strategy model based on the strategy iteration method are as follows:
under the same sampling period, selecting a maintenance strategy with the maintenance frequency of 1 from a maintenance strategy library, calculating the maintenance total cost of the maintenance strategy, obtaining the design service life end settlement state of the maintenance strategy based on the maintenance strategy and a maintenance effect estimation module, screening out all maintenance strategies with the maintenance frequency of 1 and meeting constraint conditions, further screening out a first maintenance strategy with the minimum maintenance strategy objective function, adding 1 to the maintenance frequency, repeating the steps, screening out a second maintenance strategy with the minimum maintenance strategy objective function from all the first maintenance strategies with different maintenance frequencies, if all the maintenance strategies are not traversed, updating the sampling period, repeating the steps, updating the second maintenance strategy until all the maintenance strategies are traversed, and taking the second maintenance strategy obtained after traversing all the maintenance strategies as the optimal maintenance strategy;
the maintenance policy objective function has the expression:
wherein Mt= { ta, W n (t), m, n } represents a maintenance strategy library, and includes a sampling period ta and a maintenance time W n (t), maintenance times m and an nth settling tank at a maintenance site; c (C) m The maintenance cost is single; c (C) c Punishment costs for failure risk required when the tunnel settlement state exceeds the settlement state safety threshold; k (K) n Overrun times for the sedimentation state of the nth sedimentation tank; d is the discount rate; n is the number of the longitudinal settling tanks; c (C) l To maintain the total cost; t is the service life of the tunnel.
2. The method for optimizing maintenance strategy of longitudinal settling tanks of rail transit tunnel according to claim 1, wherein for single settling tank, the cost constraint condition is total maintenance cost constraint in design year, and for multiple settling tanks, the cost constraint condition is total maintenance cost constraint in design year and total annual maintenance cost constraint.
3. The method for optimizing maintenance strategies of the longitudinal settlement tanks of the track traffic tunnel according to claim 2, wherein the total maintenance cost in the design year is constrained to be not more than the upper limit of the total maintenance cost in the design year.
4. A method of optimizing maintenance strategy for a longitudinal settler of a rail transit tunnel according to claim 2, characterized in that said total annual maintenance cost is constrained to not exceed the total annual maintenance cost by the annual planned investment of maintenance funds.
5. The method for optimizing the maintenance strategy of the longitudinal settlement tank of the track traffic tunnel according to claim 1, wherein the setting rule of the maintenance site is as follows:
for a single settler, no maintenance site is provided, and for multiple settlers, the priority of the settler with poorer end-of-life settling condition is higher, with the sequencing according to the end-of-life settling condition of each settler.
6. The optimization method of the maintenance strategy of the longitudinal settlement tank of the track traffic tunnel according to claim 1, wherein the development trend of the non-uniform settlement of the tunnel under the non-maintenance condition is predicted by numerical simulation analysis, empirical formula fitting, gray theoretical model or artificial intelligent prediction method.
7. The method of optimizing maintenance strategy for longitudinal settling tanks of a rail transit tunnel according to claim 6, wherein the fitting of the empirical formula comprises fitting with hyperbolic model, logarithmic curve model and exponential curve model.
8. The method for optimizing maintenance strategies for longitudinal settlement tanks of rail transit tunnels according to claim 1, wherein the state evaluation index is an accumulated settlement amount, differential settlement or a longitudinal deformation curvature radius.
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