CN114548501A - Balance checking method, system and equipment - Google Patents
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Abstract
The invention provides a balance checking method, which comprises the following steps: determining the time entropy of each rail transit linear asset grid based on the decision variables, wherein the time entropy of each rail transit linear asset grid is the information entropy of unit time distribution of the inspection activities on the rail transit linear asset grid; determining the time entropy of the rail transit space-time grid according to the time entropy of each rail transit linear asset grid; determining a balance objective function according to the time entropy of the rail transit space-time grid; and determining an inspection plan of the rail transit linear assets according to the balance objective function. The invention provides a scientific and efficient inspection plan optimization determination method which can meet the balance requirement of an inspection plan.
Description
Technical Field
The invention belongs to the technical field of rail transit, and particularly relates to a method, a system and equipment for checking the balance.
Background
In the rail transit production practice, the rail transit linear asset inspection plan is generally manually compiled by a manager according to experience, and the balance of the inspection plan is difficult to ensure. The traditional network planning method or gantt chart method is not applicable to inspection activities of line-like assets. Currently, domestic and foreign experts and scholars have less direct research on optimization of time interval balance of adjacent inspection activities of rail transit linear asset inspection plans. At present, aiming at the problem of optimizing and compiling a traffic infrastructure inspection plan, relevant researches of experts and scholars at home and abroad mainly focus on the following two aspects.
The optimization selection of the traffic infrastructure inspection mode is based on the targets of safety, cost and the like. This type of research assumes that the traffic infrastructure takes a periodic inspection strategy, where each inspection can be performed in one of a number of different inspection modes, but not in multiple inspection modes simultaneously. The related research results can not be directly used for solving the optimization compilation problem of the inspection plan of the rail transit linear asset with fixed inspection tasks and inspection frequency in multiple inspection modes.
And secondly, with safety, cost and the like as optimization targets, the inspection times of the same inspection mode and the time interval between two adjacent inspections of the traffic infrastructure in a certain planning period are determined in an optimized mode. Such studies neglect the effect of other inspection modalities of the traffic infrastructure on the time interval between two adjacent inspections of the investigated inspection modality. The related research results of the category can not be directly used for optimizing and compiling the inspection plan of the rail transit linear asset in various inspection modes.
The direct research of experts and scholars at home and abroad on the inspection plan optimization compilation of various inspection modes of the traffic infrastructure with fixed inspection tasks and inspection frequency is less.
Due to the requirements of high reliability and high stability of rail transit infrastructure, in order to ensure that a manager can timely sense the quality state of a rail transit linear asset, according to relevant repair rules, the system should plan and periodically arrange the inspection activities of multiple inspection modes of equipment, such as rail inspection vehicle inspection, rail inspection instrument inspection and portable add-on instrument inspection, for investigating the smoothness of the geometry of a rail, and rail flaw detection vehicle inspection, rail flaw detector inspection and manual inspection are used for investigating the damage condition of the rail. This results in that the two adjacent inspection intervals of the different inspection methods are mutually influenced. How to scientifically compile an inspection plan of various inspection modes of linear assets of rail transit, reasonably distributing inspection resources and guaranteeing the balance of the inspection plan is a problem to be solved urgently in the technical field of rail transit.
Disclosure of Invention
In view of the above problem, the present invention provides a method for checking the equality, including:
determining the time entropy of each rail transit linear asset grid based on decision variables, wherein the time entropy of each rail transit linear asset grid is the information entropy of unit time distribution of the inspection activities on the rail transit linear asset grid;
determining the time entropy of the rail transit space-time grids according to the time entropy of each rail transit linear asset grid;
determining a balance objective function according to the time entropy of the rail transit space-time grid;
and determining an inspection plan for the rail transit linear asset according to the balance objective function.
Further, the air conditioner is provided with a fan,
taking the balance objective function as an objective function of a grid inspection plan optimization compilation model of the rail transit linear assets;
and determining an optimal inspection plan according to the rail transit linear asset gridding inspection plan optimization compilation model.
Further, the air conditioner is provided with a fan,
the rail transit space-time grid is determined by the following method:
and establishing a rail transit space-time grid based on the rail transit line space dimension and the time dimension of rail transit linear asset inspection.
Further, the air conditioner is characterized in that,
the equalization objective function is:
the ratio of the time entropy of the rail transit space-time grid to the ideal maximum time entropy of the rail transit linear asset grid is maximum;
the ideal maximum time entropy is the time entropy of the rail transit space-time grid when all the inspection activities on all the rail transit linear asset grids are distributed at equal intervals.
Further, the air conditioner is provided with a fan,
and determining the time entropy of the rail transit space-time grid according to the condition that the rail transit linear assets execute the inspection activities in each unit time.
Further, the air conditioner is provided with a fan,
determining the time entropy of each rail transit linear asset grid based on decision variables, and determining a balance objective function based on the time entropy of the rail transit linear asset grid, wherein the time entropy calculation mode of the rail transit linear asset grid is as follows:
wherein:
THilinear asset grid G for rail transitiThe temporal entropy of (a) is determined,
representing rail transit linear asset grid GiThe time interval between the (n + 1) th examination activity and the (n) th examination activity,
and
respectively representing linear asset grids G of rail transitiIn the first place
Is first and second
The checking activity is performed per unit time, and at this time,
Sifor rail transit linear asset grid GiThe total number of passes threshold for all modes of inspection,
is a set UiIs an element in (1), n belongs to [1, 2i-1]Decision variables
And E represents the total unit time in one planning period, and E represents the E unit time.
Further, the air conditioner is provided with a fan,
the equalization objective function is:
max THR (22), wherein,
the invention provides a balance checking system, comprising:
the time entropy determining unit is used for determining the time entropy of each rail transit linear asset grid based on the decision variables, and the time entropy of each rail transit linear asset grid is the information entropy of unit time distribution of the inspection activities on the rail transit linear asset grid; determining the time entropy of the rail transit space-time grids according to the time entropy of each rail transit linear asset grid;
the target function determining unit is used for determining a balance target function according to the time entropy of the rail transit space-time grid;
and the inspection plan determining unit is used for determining an inspection plan of the rail transit linear asset according to the balance objective function.
Further, the air conditioner is provided with a fan,
the inspection plan determining unit is further used for taking the balance objective function as an objective function of a grid inspection plan optimization compilation model of the rail transit linear assets; and determining an optimal inspection plan according to the rail transit linear asset gridding inspection plan optimization compilation model.
Further, the air conditioner is provided with a fan,
the balance check system further comprises:
and the rail transit space-time grid determining unit is used for establishing a rail transit space-time grid based on the rail transit line space dimension and the time dimension of the rail transit linear asset inspection.
The invention also provides a device for checking the equality, which comprises at least one processor and at least one memory;
the memory stores a computer program for performing the above method, and the processor calls the computer program in the memory to perform the above method.
The method and the system for checking the balance have important significance for timely mastering the health state of the linear assets of the rail transit and reasonably arranging maintenance and repair operation of the linear assets of the rail transit. The invention provides a track traffic linear asset inspection plan optimization compilation model, which subdivides track traffic linear asset inspection activities in time and space dimensions according to units with specified lengths, more finely defines various constraints and objective functions of different inspection activities of track traffic linear assets in time and space, and takes the balance of a track traffic linear asset inspection plan into consideration by the objective functions. Based on the maximum entropy criterion, the equilibrium of the distribution of the check plan in the time dimension is measured by using entropy.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.
FIG. 1 shows a flow diagram of a method of equality checking according to an embodiment of the invention;
FIG. 2 is a diagram illustrating inspection activity adjacency inspection time intervals for different inspection modes according to an embodiment of the invention;
FIG. 3 illustrates a schematic diagram of a railway spatiotemporal grid in accordance with an embodiment of the present invention;
FIG. 4(a) illustrates a spatiotemporal grid-based rail transit linear asset inspection activity diagram according to an embodiment of the present invention;
FIG. 4(b) is a diagram illustrating spatiotemporal constraints of two activities adjacent to a spatiotemporal grid-based linear asset of rail transit according to an embodiment of the present invention;
FIG. 5 illustrates decision variables in the model OISM-TG according to an embodiment of the present invention
A schematic diagram;
FIG. 6 illustrates a track traffic linear asset inspection activity time constraint diagram according to an embodiment of the invention;
FIG. 7 illustrates a track traffic linear asset inspection activity schedule constraint diagram according to an embodiment of the invention;
FIG. 8 illustrates a rail transit linear asset inspection activity space constraint diagram according to an embodiment of the invention;
FIG. 9 illustrates a track traffic linear asset inspection activity rate constraint diagram according to an embodiment of the invention;
FIG. 10 illustrates a track traffic linear asset inspection activity resource constraint schematic according to an embodiment of the present invention;
FIG. 11 illustrates a track traffic linear asset inspection activity inspection continuity constraint diagram in accordance with an embodiment of the present invention;
FIG. 12 is a diagram illustrating temporal constraints based on a rail transit spatiotemporal grid in accordance with an embodiment of the present invention;
FIG. 13 illustrates a schematic diagram of a track traffic spatiotemporal grid-based campaign constraint in accordance with an embodiment of the present invention;
FIG. 14 illustrates a spatial constraint diagram based on a rail transit spatiotemporal mesh, according to an embodiment of the present invention;
FIG. 15 is a diagram illustrating velocity constraints based on a rail transit spatiotemporal grid in accordance with an embodiment of the present invention;
FIG. 16 is a schematic diagram illustrating resource constraints based on a rail transit spatiotemporal grid in accordance with an embodiment of the present invention;
FIG. 17 is a diagram illustrating inspection continuity constraints based on a rail transit spatiotemporal grid in accordance with an embodiment of the present invention;
FIG. 18 shows a 2016 actual track inspection plan for a descent of a New line in a Lanzhou, railway bureau, Jiayuguan line shop, Lanzhou, 12 months, according to an embodiment of the invention;
FIG. 19 shows a plan view of a new down-track inspection line in the Caryugate line workshop, Lanzhou, Branch, at 2016, and compiled by model OISM-TG, according to an embodiment of the present invention;
FIG. 20 is a block diagram of an equalization check system according to an embodiment of the present invention;
fig. 21 is a schematic structural diagram showing an equalization checking apparatus according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention provides a method for checking the balance, as shown in figure 1, the method comprises the following steps: determining the time entropy of each rail transit linear asset grid based on decision variables, wherein the time entropy of each rail transit linear asset grid is the information entropy of unit time distribution of the inspection activities on the rail transit linear asset grid; determining the time entropy of the rail transit space-time grid according to the time entropy of each rail transit linear asset grid; determining a balance objective function according to the time entropy of the rail transit space-time grid; and determining an inspection plan of the rail transit linear assets according to the balance objective function.
Linear Assets (Linear Assets) are Assets that have a start point and an end point of measurement and can be maintained in segments. IBM corporation defines a line asset as a piece-wise maintained asset along which measurements may be made to specify work, monitoring, metering, mark location, etc. For a line asset, its length plays a critical role in maintenance. For example, the equipment such as rails, roadbeds, overhead lines, tunnels, bridges and the like in the rail transit infrastructure belong to linear assets, have the characteristics of linear, continuous, strip-shaped layout and the like in spatial distribution, are organized and arranged in a relatively narrow and strip-shaped space, and are easily influenced by various time factors and space factors.
The inspection task and the inspection frequency in the rail transit linear asset inspection plan are generally fixed, and the most important challenge in the compilation of the rail transit linear asset inspection plan is to realize the optimization of the balance of adjacent inspection activity time intervals in the inspection plan. The equality of time intervals of adjacent examination activities of an examination plan means that the time intervals of different examination activities should be as even as possible, as shown in fig. 2, Tj、Tj+1、Tj+2、Tj+3And Tj+4Equal as much as possible, so as to avoid that the linear rail transit assets are not inspected in a longer time span, but are inspected for multiple times in a shorter time span. In fig. 2 the abscissa indicates mileage, the ordinate indicates time, and the different shaped lines indicate different examination activities.
Although the track traffic linear asset inspection modes are various in types and different in inspection principle, the track traffic linear asset inspection activities have the following characteristics in general.
(1) The rail transit linear asset inspection activities have continuity in the horizontal direction; track traffic linear asset inspection activities typically extend from one end of a line segment to the other; the rail transit linear asset inspection activity is primarily composed of activities with repetitive features. If the locomotive inspection activities are continuously and repeatedly carried out in a plurality of line sections, the locomotive inspection activities continuously progress forward on mileage positions while consuming time.
(2) The inspection items of different inspection modes are overlapped, for example, the inspection items of rail inspection vehicle inspection and rail inspection instrument inspection all contain height, rail direction, rail distance, level and triangular pits, and the rail flaw detection vehicle, the rail flaw detector and manual inspection all inspect the rail flaw condition.
(3) In order to ensure the operation safety of the upper-track personnel, the inspection activities of certain inspection modes need to be executed within the skylight time, such as rail inspection instrument inspection and rail flaw detector inspection; meanwhile, the condition that the inspection activities of some inspection modes do not need to be arranged in the skylight time, such as rail car inspection, dynamic inspection car inspection and rail flaw detection car inspection, also exists.
(4) The logical constraint of the sequence of the checking activities of different checking modes does not exist in the time dimension, namely the sequence of the checking activities of different checking modes in time does not influence the perception of the track state.
(5) At the same time and space mileage position, there are no multiple inspection activities, for example, when the rail flaw detector inspection activities are implemented, the rail flaw detector inspection activities cannot be arranged at the same position at the same time.
(6) The inspection activity is influenced by various time and space factors, and the frequency of the inspection activity is increased if the quality of equipment has a line section with higher risk hidden danger; the inspection rate is affected by various temporal and spatial factors, with uncertainty.
In the embodiment of the invention, the rail transit linear asset inspection refers to the sum of a series of actions performed by applying technical means to survey the state of the rail transit linear asset. The rail transit linear asset inspection has definite time span and mileage range information, and certain time and resources are consumed in the execution process of the rail transit linear asset inspection. An inspection activity refers to an inspection task that a workgroup is scheduled to perform over a span of time, a range of miles.
In the embodiment of the invention, a balance objective function is used as an objective function of a rail transit linear asset gridding inspection plan optimization compilation model; and determining an optimal inspection plan according to the rail transit linear asset gridding inspection plan optimization compilation model.
Wherein the decision variable is determined by: and determining whether to execute the inspection activity of the designated inspection mode in the designated unit time aiming at the designated track traffic linear asset grid based on the track traffic space-time grid.
The rail transit space-time grid is determined by the following method: and establishing a rail transit space-time grid based on the rail transit line space dimension and the time dimension of rail transit linear asset inspection. Specifically, on the spatial dimension, a rail transit line is divided into a plurality of rail transit linear asset grids; on the time dimension, dividing the whole inspection planning cycle process into a plurality of unit times; and forming a rail transit space-time grid according to the rail transit linear asset grid and the unit time.
The embodiment of the invention takes the space-Time grid of the rail transit linear asset Inspection as a basic unit, discretizes the rail transit linear asset Inspection activities in space and Time dimensions, provides an optimized compilation Model (Optimal Inspection Scheduling Model for Time-location Grids, OISM-TG) of the rail transit linear asset grid Inspection plan, more finely defines various constraints and objective functions of different Inspection activities of the rail transit linear asset in Time and space, optimizes the balance of the compiled rail transit linear asset Inspection plan and enhances the practicability of the rail transit linear asset Inspection plan.
The following describes in detail the construction of a rail transit linear asset gridding inspection plan optimization compilation model.
In the embodiment of the invention, the track traffic line in linear, continuous and strip-shaped layout is divided into a plurality of small sections according to a certain rule to form a track traffic grid. Without loss of generality, the line is divided into several small segments of adjacent equal length. The rail transit space-time grid refers to a plurality of small units formed by dividing the whole life cycle process of rail transit line facilities according to a certain rule based on two dimensions of time and space. As shown in FIG. 3, the abscissa represents mileage, the ordinate represents time, and each spatiotemporal grid is represented by GijAnd i represents the ith rail transit grid, and j represents the time period of the grid. The rail transit space-time grid is a basic unit based on time-space. Illustratively, the rail transit spatiotemporal meshing method is as follows.
(1) Time grid division: according to the actual working requirements of the rail transit infrastructure management, the whole life cycle process of the rail transit infrastructure can be divided according to minutes, hours, days, weeks, months and years in the time dimension. In different application scenarios, the manager can select the size of the time grid unit according to the actual scenario requirements.
(2) Spatial grid division: as a minimum unit for segmenting linear and continuous rail transit lines in spatial dimension, the division of spatial grids should fully consider the service characteristics of inspection activities and the field management requirements, the length of the rail transit grids is set to be 200 meters in the embodiment of the invention, and railway hectometer marks are selected as demarcation points for adjacent grids.
The rail transit linear asset inspection activity has definite time span and mileage range information, and consumes certain time and resources in the execution process. Based on the space-time grid, the rail transit linear asset inspection activities are divided according to smaller time units and space units, various constraints of the inspection activities on time and space can be defined more finely, the influence of various time factors and space factors on the inspection activities can be described more accurately, and a manager can manage the rail transit infrastructure inspection activities under higher time and space resolution, as shown in fig. 4(a) and 4 (b). The abscissa in the figure represents the route mileage, the ordinate represents the time of execution of the activity, and the broken line represents the inspection activity of the rail transit infrastructure. In fig. 4(b), the size of the angle between the broken line and the abscissa indicates the execution speed of the activity, and a smaller angle indicates a faster execution speed of the corresponding activity. The shaded part in fig. 4(b) represents the space-time constraint existing between any mile point at any time in the whole process of executing two adjacent activities.
The track traffic linear asset inspection activities may be delayed or temporarily cancelled due to various temporal and spatial factors (such as bad weather), and the track traffic linear asset inspection plan may be adjusted multiple times during actual execution. Therefore, the embodiment of the invention provides a concept of a track traffic linear asset inspection plan basic diagram in a summary manner, wherein the track traffic linear asset inspection plan basic diagram is a graphical representation of inspection activity time and space relation by using a coordinate principle and is used for describing information such as start time, end time, start mileage, end mileage, sequence of occupied intervals of different inspection activities, time length of the occupied intervals of the inspection activities and the like of track traffic linear assets.
In the actual execution process of the rail transit linear asset inspection plan, when the actual progress deviates from the plan, in order to prevent the whole inspection plan from being disordered, the basic diagram of the rail transit linear asset inspection plan is adjusted by taking the minimum plan change as an optimal target, and the inspection plan is ensured to be executed orderly.
In order to consider the influence of various factors, the embodiment of the invention subdivides rail transit linear asset Inspection activities in space and Time dimensions, provides an optimized compilation Model (Optimal Inspection Scheduling Model for Time-location Grids, OISM-TG) of rail transit linear asset grid Inspection plans by combining the characteristics of the rail transit linear asset Inspection activities, more finely defines various constraints and objective functions of different rail transit linear asset Inspection activities in Time and space, optimizes the balance of the compiled rail transit linear asset Inspection plans, and enhances the practicability of the rail transit linear asset Inspection plans. The OISM-TG contains at least an objective function and may also contain constraints. Wherein the objective function is the minimum of plan variation; the constraint system includes time constraints, time limit constraints, space constraints, rate constraints, resource constraints, check continuity constraints, and the like.
The following exemplarily describes the construction of the OISM-TG model, and the specific implementation process of the embodiments of the aspects of the present equality check method can be known from the construction process of the OISM-TG model.
The model OISM-TG involves the following constants:
SD represents the starting mileage of the inspection plan;
ED represents the end-point mileage of the inspection plan;
DR represents the mileage length of the examination activity, which is calculated in equation (1);
DR＝ED-SD (1)
LE represents the length of the rail transit linear asset grid, typically 200 meters;
the rail transit spatiotemporal grid and the inspection activities are represented in the following ways (the representation symbols are not limited by the embodiment of the invention, and other variables or symbols can be replaced by the embodiment of the invention):
n represents the total number of grids divided by the linear asset line of the rail transit, and the calculation is shown in formula (2);
Gi(i∈[1，2，...，N]) Representing the ith rail transit linear asset grid; i represents the serial number of the linear asset grid of the rail transit;
m represents the total category number of the linear asset inspection modes of the rail transit;
Cj(j∈[1，2，...，M]) The j-th type checking mode is shown; j represents a serial number of a rail transit linear asset inspection mode;
Cij(i∈[1，2，...，N]，j∈[1，2，...，M]) Representing rail transit linear asset grid GiThe jth type inspection mode of (1);
e represents the total unit time in a planning period, and E represents the E-th unit time; e represents the serial number of the unit time in the planning period;
Sijshowing the rail transit linear asset grid G in one planning cycleiInspection method CjThe inspection pass threshold value of (2) is influenced by various time and space factors, so that the inspection frequency of the same inspection mode of different rail transit linear asset grids can be different;
Sishowing the rail transit linear asset grid G in one planning cycleiThe total inspection pass threshold of all inspection modes is calculated according to the formula:
min Tijshowing the rail transit linear asset grid G in one planning cycleiInspection method CjMinimum inspection ofAn interval threshold;
max Tijshowing the rail transit linear asset grid G in one planning cycleiInspection mode CjA maximum check interval threshold of;
indicates the inspection mode C per unit timejA maximum check grid number threshold of (a);
min Ljindicates the inspection mode C per unit timejA minimum check grid number threshold of;
RCjdenotes the execution of the inspection mode as CjChecking the number of active work groups;
RC represents the total number of work groups performing the checking activity.
The OISM-TG model relates to decision variables, and in the embodiment of the invention, the decision variables are variables for determining whether to execute the inspection activities of a designated inspection mode in a designated unit time aiming at the designated rail transit linear asset grid based on the rail transit spatiotemporal grid.
The decision variable of the model OISM-TG is
The variable represents a rail transit linear asset grid GiWhether the check is performed at the e-th unit time is CjThe examination activities of (1) are performed,
see equation (4).
Representing rail transit linear asset grid GiThe mode of executing the check in the e unit time is CjThe examination activities of (1) are performed,
representing rail transit linear asset grid GiThe mode of not executing the check in the e unit time is CjThe checking activity of (2).
For inspection mode CjThe optimization problem has N × E boolean decision variables to be considered, as shown in fig. 5. The whole model checking mode has M types, so that the model OISM-TG has M multiplied by N multiplied by E Boolean decision variables to be considered. The embodiment of the invention adopts the Boolean numerical value as the decision variable value, the operation speed is high, and the value is not easy to make mistakes. However, the embodiment of the present invention does not limit the manner of taking the decision variable, and in another embodiment, types such as integers may be used, so that the value is not limited to 0 and 1, as long as the value can be used for calculating the change of the inspection plan.
And determining a decision expression according to the decision variables, wherein the decision expression related to the model OISM-TG is as follows. Decision expressions can be used to construct constraints.
ZijShowing grid G during an inspection planning cycleiInspection method CjThe history of activity execution time of (c) is examined to form a set. Set ZijThe number of middle elements is equal to grid GiInspection method CjIs checked by the number of passes threshold Sij. Set ZijWherein the element is ZijDenotes that n ∈ [1, 2.,. S ]ij]，
Representation grid GiIn the first place
The checking mode executed per unit time is CjThe checking activity of (1).
And
(e∈[1，2，...，E]) The functional relationship of (c) is shown in equation (5).
Show grid GiThe checking mode is executed in the e unit time as CjThe examination activity of (a), at this time,
UiShowing grid G during an inspection planning cycleiThe execution time of all the checking modes in the past checking activity is formed into a set. Set UiThe number of middle elements is equal to grid GiTotal number of passes threshold S for all inspection modesi. Set UiThe elements in (1) are used
Denotes that n ∈ [1, 2.,. S ]i]，
Representation grid GiIn the first place
The checking activity is performed per unit time.
And
the functional relationship of (c) is shown in equation (6).
Show grid GiThe checking mode is executed in the e unit time as CjThe examination activity of (a), at this time,
Qijrepresentation grid GiThe inspection is performed in a manner of CjThe number of check activities is calculated in equation (7).
And determining an objective function based on a space-time grid, wherein the objective function of the OISM-TG model comprises an equilibrium objective function in the embodiment of the invention.
Equality objective function
In the embodiment of the invention, the OISM-TG model utilizes an entropy theory to construct an index for measuring the balance of the rail transit linear asset inspection plan in a time dimension, and the index is called as time entropy. A larger temporal entropy indicates a more uniform examination plan in the temporal dimension.
"Information Entropy" (Information Entropy) or so-called "Shannon Entropy" (Shannon Entropy) was first proposed by Claude Elwood Shannon in 1948 to measure the uncertainty of Information. When the states or results of the events are all known, the information entropy H is equal to 0; the greater its uncertainty, the greater H, the more possible states or outcomes of an event. The information entropy H is mathematically abstracted that there are n possible results X for a certain eventi(i∈[1，2，...，n]) The probability of each occurrence is PiThe information entropy H for measuring the uncertainty of the event is calculated in formula (10).
pi≥0，i∈[1，2，...，n] (12)
Based on the maximum entropy criterion, when piWhen (i ═ 1, 2, 3., n) satisfies the condition of the following formula (13), H in the formula (10) has a maximum value. The degree to which the set of data deviates from the mean value is greater when the entropy is smaller; when the entropy is larger, the data is more concentrated near the mean value, and the data distribution is more balanced; when a set of data is completely equal, the value of entropy reaches a maximum.
In the embodiment of the invention, the method for determining the equilibrium objective function of the model OISM-TG based on the rail transit space-time grid and the decision variables comprises the following steps: determining the time entropy of each rail transit linear asset grid based on the decision variables, wherein the time entropy of each rail transit linear asset grid is the information entropy of unit time distribution of the inspection activities on the rail transit linear asset grid; determining the time entropy of the rail transit space-time grid according to the time entropy of each rail transit linear asset grid; and determining a balance objective function according to the time entropy of the rail transit space-time grid. The target function is that the ratio of the time entropy of the rail transit space-time grid to the time entropy of the ideal maximum value of the rail transit linear asset grid is maximum. The ideal maximum time entropy is the time entropy of the rail transit space-time grid when all the inspection activities on all the rail transit linear asset grids are distributed at equal intervals.
In particular, the model OISM-TG employs a time interval of two consecutive checking activities
Event outcome probability defined as the ratio of the sum of interval units of time over the planning period
Substitution of variable p in equation (10)iThe entropy is redefined. In the embodiment of the present invention, the sum of the interval unit times is set to E-1. This entropy is called the grid GiTemporal entropy of (TH)iAs a metric grid GiThe balance index of the activity time interval is checked in two adjacent times in a planning cycle, see equation (14). Temporal entropy THiThe larger the value, the more balanced the time interval between two adjacent examination activities in the examination plan is.
Representation grid GiThe time interval between the (n + 1) th examination activity and the (n) th examination activity, see equation (15), n and n +1 representing the grid GiThe next two checks of the activity sequence number.
To represent
The ratio to the total number of unit times E-1 in the planning period is shown in equation (16). Wherein i belongs to [1, 2]，n∈[1，2，...，Si-1]. By definition of E-1
The reason for (a) is that the grid GiAll S' S in the planning cyclei-1 time interval
The sum of the two is less than or equal to E-1.
From the maximum entropy criterion, grid GiTemporal entropy of (TH)iWhen the maximum value is taken out of the range,
equal two by two. I.e. time entropy TH within a planning periodiThe larger the value of (A), the grid GiThe closer the time intervals of two adjacent examination activities are, the closer the grid G is constructediThe higher the balance of the inspection plan.
The time entropy of the rail transit linear asset space-time grid is denoted by TH, and is used for measuring the rail transit linear asset space-time grid, namely all grids check the equilibrium of the plan in one planning period, and the calculation is shown as formula (18).
When the time entropy TH of the whole rail transit linear asset is maximum, the grid Gi(i∈[1，2，...，N]) Temporal entropy of (TH)iThe method reaches the maximum value, and the balance degree of the inspection plan of each grid in the whole rail transit linear asset is the highest.
According to the maximum entropy criterion, under the condition of not considering task constraint conditions, the grid GiTemporal entropy of (TH)iIdeal maximum value TH ofi，maxAs shown in equation (19). The ideal maximum is reached when the time intervals between all activities are equal.
Correspondingly, the ideal maximum value TH of the time entropy TH of all grids of the linear asset in the rail transitmaxAs shown in equation (20).
Time entropy TH of all grids of linear asset in rail transit and ideal maximum value TH thereofmaxThe ratio of (d) is represented by THR, as shown in equation (21).
The equilibrium objective function of the model OISM-TG is shown in equation (22).
max THR (22)
In the embodiment of the invention, the balance objective function is defined by the ratio, and the ideal maximum value is 1, so that the difference between the ideal maximum value and the most balanced state can be clearly seen according to the calculation result and is used as an index of a measurement plan.
In combination with analysis of rail transit linear asset inspection activity characteristics, the embodiment of the invention also considers the constraints among rail transit linear asset inspection activities to be divided into time constraints, construction period constraints, space constraints, rate constraints, resource constraints, inspection continuity constraints and the like.
(1) Time constraints
As shown in FIG. 6, the time interval T of two adjacent inspections of the same inspection mode of the same rail transit linear assetjShould satisfy the minimum time constraint, the maximum time constraint, Tj≥min Tj，Tj≤max Tj，max TjRepresents the maximum time constraint threshold, min TjRepresents a minimum time constraint threshold, the size of which is determined by the frequency of checks of the different modes of check specified in the repair rules. In the figure, the abscissa represents the route mileage, the ordinate represents the time, and the lines of different shapes represent the examination activities in different examination modes.
Violating the maximum time constraint will result in that the manager cannot find the quality problem of the rail transit linear asset in time, and violating the minimum time constraint will result in the waste of the inspection resource.
(2) Construction period constraint
The rail transit linear asset inspection activity needs to be performed within a specified time period according to the relevant repair rules. When a manager prepares an inspection plan, due to interference of various random factors, some rail transit linear assets may not be organized and arranged with corresponding inspection activities, namely, missed inspection, within a specified time period. As shown in fig. 7, mileage di> 0, mileage di+1> 0, violating the project time constraint. The length of the construction period is determined by the inspection frequency of different inspection modes, for example, the frequency of the on-line inspection of the general speed railway track inspection instrument is 1 time/month, and the corresponding construction period is 1 month. The abscissa of the graph represents the route mileage, the ordinate represents the time, and the broken line represents the expiration date of the examination plan.
Violating the construction period constraint, the rail transit linear assets which are not at risk originally are likely to develop risk hidden danger, and the original low risk is likely to develop into high risk.
(3) Space constraint
Minimum distance constraint and minimum time constraint exist between every two different examination activities. Checking that the time of the activity satisfies Tj≥min Tj，Tj+1≥min Tj+1(ii) a Checking that the distance of the movement satisfies di≥min di，di+1≥min di+1As shown in fig. 8. min di、min di+1Represents the minimum distance constraint threshold, min Tj、min Tj+1A minimum time constraint threshold is indicated, which is set to ensure that different inspection activities do not interfere or conflict with each other during execution. In the figure, the abscissa represents the route mileage, the ordinate represents the time, and different shapes of examination activities represent different examination modes.
If the above constraints are violated, a space-time conflict is generated between the checking activities, and the efficiency and safety of the checking activities are affected.
(4) Rate constraints
The speed of the linear asset inspection activity of the rail transit is uncertain due to the influence of various time and space factors, but the minimum speed constraint, the maximum speed constraint and the min v are metj≤vj≤max vj，min vj+1≤vj+1≤max vj+1As shown in fig. 9. min vj、min vj+1The representation represents the activity minimum rate constraint threshold, max vj、max vj+1Representing a maximum rate constraint threshold min vjAnd max vjFor indicating the range of rate variation in the case of start time determination, min vj+1And max vj+1This is used to indicate the rate fluctuation range in the case of end time determination. The threshold value is generally determined by technical parameters of a detection instrument or device, for example, the track detection instrument usually has a traveling speed of 3-4 km/h, and the fastest speed should not be greater than 8 km/h. The abscissa of the graph represents the route mileage, the ordinate represents the time, and the broken line represents the expiration date of the examination plan.
The maximum rate constraint is met, the inspection quality is guaranteed, and false detection and missing detection are prevented; a minimum rate constraint is satisfied for ensuring efficiency of the inspection activity.
(5) Resource constraints
The resource usage amount that can be occupied during the track traffic linear asset inspection process is often limited, and in order to ensure the smooth proceeding of the inspection activities, the number of the inspection activities organized and arranged at the same time should be less than or equal to the number of the working groups (i.e. the resource usage amount), as shown in fig. 10. The workgroup is a basic unit for checking activities, which is composed of mechanical equipment, personnel and related auxiliary production data, represents a certain resource allocation and corresponds to a certain checking efficiency. In the figure, the abscissa represents time, the ordinate represents the number of work groups, the broken line represents the threshold of the resource usage, and the size of the threshold is represented by RC.
Meeting the resource constraints is a basic guarantee of the feasibility of the inspection plan, which directly results in the inability to organize and schedule the inspection activities if the amount of resources used by the inspection activities exceeds the amount of available resources.
(6) Checking continuity constraints
The linear asset inspection activity of rail transit has the characteristics of linearity, continuity, repetition and the like, and is organized and arranged as a complete whole in a unit time WT, and the continuous and uninterrupted execution of the linear asset inspection activity is ensuredj＝0，d i0, as shown in fig. 11. In the figure, the abscissa represents the route mileage, the ordinate represents the time, and two horizontal broken lines represent the start time and the end time of a unit time, respectively.
If the above constraints are violated, the checking activity is discontinuous or discontinuous, which causes waste of resources and loss of checking efficiency, and increases management cost.
The constraint conditions of the rail transit linear asset grid based on the embodiment of the invention are as follows.
Time constraints
As shown in fig. 12, the time constraints for the rail transit linear asset inspection activity are as follows: firstly, in a planning period, grid GiInspection method CjShould be greater than or equal to the minimum inspection interval threshold min TijSee equation (28); ② in a planning periodInner and outer grids GiInspection mode CjShould be less than or equal to a maximum check interval threshold max TijSee formula (29). If the number of inspections specified by a certain inspection method is 1 in one inspection planning cycle, the time constraint of the inspection activity corresponding to the inspection method is not considered. In fig. 12, the abscissa indicates the route mileage, the ordinate indicates the time, and the broken lines of different shapes indicate the inspection activities of different inspection modes. The abscissa is divided by the length of the grid, and the ordinate is divided by the time granularity required by management to form a rail transit linear asset space-time grid.
Violating the maximum time constraint will result in that the manager cannot find the quality problem of the rail transit linear asset in time, and violating the minimum time constraint will result in the waste of the inspection resource.
Construction period constraint
The construction period constraint of the rail transit linear asset inspection activity comprises two aspects: firstly, in a planning period, each type of inspection mode needs to complete the specified inspection times; and secondly, in each inspection activity of each type of inspection mode, all rail transit linear asset grids need to be inspected in each inspection, so that the inspection omission is avoided. Therefore, in one planning cycle, grid GiThe inspection is performed in a manner of CjNumber of examination activities QijShould be equal to the threshold S of the number of passes of the checkijSee formula (30) and fig. 13. In fig. 13, the abscissa represents the route mileage, the ordinate represents the time, the abscissa is divided by the grid length, and the ordinate is divided by the time granularity required for management, so as to form the rail transit linear asset space-time grid. The dotted line indicates the expiration date of the examination plan. Due to the presence of d in the figurei> 0, resulting in a dashed box region Qij＜SijAnd the construction period constraint is not met.
Violating the construction period constraint, the rail transit linear assets which are not at risk originally are likely to develop risk hidden danger, and the original low risk is likely to develop into high risk.
Space constraint
The space constraint of the track traffic linear asset inspection activities means that only one inspection activity can occur at most in any track traffic linear asset space-time grid. I.e. grid GiAt most one inspection activity can occur per unit time, see equation (31) and fig. 14. In fig. 14, the abscissa indicates the route mileage, the ordinate indicates the time, and the lines of different shapes indicate the examination activities of different examination modes. Abscissa in grid lengthAnd dividing scales and the vertical coordinate to manage the required time granularity to form the rail transit linear asset space-time grid.
If the above constraints are violated, a space-time conflict is generated between the checking activities, and the efficiency and safety of the checking activities are affected.
Rate constraints
The model OAMIS-TG defines the inspection rate by the number of the grids of the linear assets of the rail transit inspected in unit time by the inspection activities of each type of inspection mode. As shown in fig. 15, the rate constraints for the rail transit linear asset inspection activity are as follows: checking in a mode CjThe number of grids checked per unit time by the checking activity
Should be less than or equal to the maximum rate threshold max LjSee equation (32); checking mode is CjThe number of grids checked per unit time by the checking activity
Should be greater than or equal to the minimum rate threshold min LjSee formula (33). In fig. 15, the abscissa represents the route mileage, the ordinate represents the time, the abscissa is divided by the grid length, and the ordinate is divided by the time granularity required for management, forming the rail transit linear asset space-time grid.
The maximum rate constraint is met, the inspection quality is guaranteed, and false detection and missing detection are prevented; a minimum rate constraint is satisfied for ensuring efficiency of the inspection activity.
Resource constraints
The resource constraint of the rail transit linear asset inspection activity means that the inspection mode in unit time is CjNumber of examination activities
Less than or equal to the corresponding number of working groups RCjSee equation (34) and fig. 16. In fig. 16, the abscissa represents time, and the ordinate represents the number of work groups. The dotted line represents the threshold value RC of the resource usagej。
Meeting the resource constraints is a basic guarantee of the feasibility of the inspection plan, which directly results in the inability to organize and schedule the inspection activities if the amount of resources used by the inspection activities exceeds the amount of available resources.
Checking continuity constraints
The track traffic linear asset inspection continuity constraint means that each working group executes an inspection mode CjShould be continuous and uninterrupted per unit time, see equation (35) and fig. 17. In fig. 17, the abscissa represents the route mileage, the ordinate represents the time, the abscissa is divided by the grid length, and the ordinate is divided by the time granularity required for management, so as to form the rail transit linear asset space-time grid. The dotted line indicates the start time and the end time of the e-th unit time. Due to the presence of d in the figurei> 0, the check continuity constraint is not satisfied.
Where p represents the mileage position where the e-th unit time starts to be executed, then
Indicating the mileage position where the e-th unit time ends execution. If it is not goodAgainst the above constraints, the examination activities are discontinuous or discontinuous, which results in resource waste and loss of examination efficiency, and increases the management cost. Illustratively, for the same type of inspection activity, if a two kilometer mile line needs to be inspected while being performed on a certain day, the two kilometers must be continuous and cannot skip one kilometer in the middle, in accordance with the inspection continuity constraint. Otherwise, the intermediate skipped mileage needs to be checked separately again, which increases the cost of manpower and mechanical transportation and wastes resources.
The model can be used for generating an optimization scheme and screening or evaluating an existing inspection plan. When the optimization scheme is generated, the objective function and the constraint condition of the model can be applied to solving software, and the optimization scheme is automatically calculated through the solving software. Illustratively, the solving software has a global optimization algorithm, and the embodiment of the present invention does not limit the selection of the solving software. There is no limitation on how one or more inspection plans may be derived, for example, a new inspection plan may be derived by manual planning or an inspection plan may be derived by automatic computer calculation, or a combination of both. According to the OISM-TG model provided by the embodiment of the invention, optimal screening and feasibility screening can be carried out on a plurality of inspection plans to obtain a final optimized inspection plan. The embodiment of the invention carries out detailed and comprehensive management on the inspection activities in the whole inspection period based on the subdivided space-time grids and the variables for executing the inspection activities, provides scientific optimization basis, can carry out objective function calculation based on the decision variables of the embodiment of the invention, and can conveniently apply computer programs to realize automatic, efficient and accurate inspection plan evaluation and optimization. Furthermore, multiple alternative schemes can be generated by the random combination of the computers for the generation of the inspection plan, and the automatic screening is performed by adopting the model, so that the problems of low manual compilation efficiency, strong subjectivity and incapability of achieving the optimal or better result are solved.
The balance checking method of the embodiment of the invention achieves good technical effect in practical application. The effectiveness of the OISM-TG model provided by the embodiment of the invention is verified by taking an orbit inspection plan of K721+ 000-K765 +000 descending of the new line of 12-month orchid in 2016 as an example.
Railway track is a typical rail transit line asset. The length DR of a line section in the range of K721+ 000-K765 +000 of the upstream and downstream of the Lanxin line is 44km, and a Gayuguan line workshop of the Lanzhou office group of China (called Lanzhou office for short) undertakes daily inspection and maintenance tasks of industrial equipment. The length LE of the track grid is 200 m, so the number N of the track grids descending the new line is 220.
The total number of days E in the planning cycle of this example was 31, and the 4 types of inspection methods were rail inspection instrument inspection, rail flaw detection inspection, manual inspection, and rail inspection vehicle inspection, respectively. Table 1 shows the amount of track inspection tasks downstream of the lanxin line in the 12-month lanzhou jiayuguan line shop in 12 months. The track quality state of the descending K731+ 000-K736 +000 line of the Lanxin line is poor, so that the manual checking frequency of the track grids in the mileage range is once more than that of other track grids. The rail inspection vehicle inspection is arranged in advance at 8 days and 21 days, and the 1 st inspection and the 2 nd inspection are respectively carried out on the descending track line of the Lanxin line.
Table 12016 years 12 Yu Lanzhou Jiangyguan line workshop Lanxin down-line track line inspection task volume
The example relates to 4 working groups, namely a jiayuguan inspection and monitoring working area, a jiayuguan line maintenance working area, a jiayuguan steel rail flaw detection working area and a rail inspection working group. In order to observe the distribution of the whole data set, identify possible abnormal values in the data set, analyze the historical inspection rate data of 581 pieces in 3 years during 2015 year 1-2017 year 12 months of these working groups, and select the first quartile and the third quartile in the historical inspection rate data as the upper threshold and the lower threshold of the inspection rate, wherein the inspection rate is defined by the length of the line inspected in unit skylight time.
TABLE 2 inspection Rate constraints for different inspection modes of the New line
Analysis of model results
As can be seen from the analysis of the comparative contents in table 2,
(1) constraint conditions are as follows: the actual inspection plan in the case does not satisfy the duration, space, and rate constraints. This is because the planning of the railway on-site inspection plan is mainly based on the management experience of the on-site engineer, and it is difficult to comprehensively and systematically consider the inspection activity constraint system established by the embodiment of the present invention.
(2) An objective function: compared with the actual inspection plan of a railway field, the inspection plan compiled by the model OISM-TG has the advantage that the balance target is improved by 22.5%.
In conclusion, the results are shown in combination with the visualizations in fig. 18 and 19, and the railway track inspection plan compiled by the model OISM-TG is superior to the actual inspection plan compiled by the field engineer in the case, and has better balance.
TABLE 3 comparison of examination plans compiled by the model OISM-TG with actual examination plans in situ
Establishing a rail transit time-space grid based on the rail transit line space dimension and the time dimension of rail transit linear asset inspection;
the method for determining the rail transit linear asset gridding inspection plan evaluation model based on the rail transit space-time grid comprises the following steps:
determining a decision variable based on the rail transit spatiotemporal grid, wherein the decision variable is used for representing the execution condition of a specified checking activity in the spatiotemporal grid;
determining constraint conditions based on the rail transit space-time grid and decision variables;
and determining an inspection plan according to the rail transit linear asset gridding inspection plan evaluation model.
By the method for evaluating the inspection plan of the rail transit linear asset, the scientificity and efficiency of plan evaluation can be improved by screening and evaluating the reasonability of the inspection plan through the evaluation model with constraint conditions when the inspection plan is formulated or the inspection plan is adjusted and optimized.
Further, the constraints include at least one of the following constraints: time constraints, time of day constraints, space constraints, rate constraints, resource constraints, inspection continuity constraints. Some or all of the constraints may be selected as desired to build the evaluation model.
The specific expression mode of the process and the constraint of the model construction based on the space-time grid and the decision variables can be obtained from the embodiment related to the rail transit linear asset gridding inspection plan optimization adjustment model, and is not repeated.
Based on the same inventive concept, an embodiment of the present invention further provides a system for checking equality, as shown in fig. 20, the system includes:
the time entropy determining unit is used for determining the time entropy of each rail transit linear asset grid based on the decision variables, and the time entropy of each rail transit linear asset grid is the information entropy of unit time distribution of the inspection activities on the rail transit linear asset grid; determining the time entropy of the rail transit space-time grids according to the time entropy of each rail transit linear asset grid;
the target function determining unit is used for determining a balance target function according to the time entropy of the rail transit space-time grid;
and the inspection plan determining unit is used for determining an inspection plan of the rail transit linear asset according to the balance objective function.
The inspection plan determining unit is further used for taking the balance objective function as an objective function of a rail transit linear asset gridding inspection plan optimization compilation model; and determining an optimal inspection plan according to the rail transit linear asset gridding inspection plan optimization compilation model.
Further, the equilibrium inspection system further comprises a rail transit space-time grid determination unit, which is used for establishing the rail transit space-time grid based on the rail transit line space dimension and the time dimension of the rail transit linear asset inspection.
The specific implementation of the balance check system according to the embodiment of the present invention can be obtained according to the method according to any embodiment of the present invention, and is not described in detail.
The method of the invention can be realized by a computer or an embedded program controlled system. Accordingly, in another embodiment of the present invention, there is provided another equality check apparatus, as shown in fig. 21, the apparatus includes at least one processor and at least one memory; the memory stores a computer program for performing any of the above methods of embodiments of the invention, and the processor calls the computer program in the memory to perform any of the methods of embodiments of the invention.
Further, the memory may be communicatively coupled to the one or more processors and have stored therein instructions executable by the one or more processors to cause the one or more processors to implement the method of the present invention.
Although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (11)
1. A method for checking equality, comprising:
determining the time entropy of each rail transit linear asset grid based on decision variables, wherein the time entropy of each rail transit linear asset grid is the information entropy of unit time distribution of the inspection activities on the rail transit linear asset grid;
determining the time entropy of the rail transit space-time grid according to the time entropy of each rail transit linear asset grid;
determining a balance objective function according to the time entropy of the rail transit space-time grid;
and determining an inspection plan of the rail transit linear assets according to the balance objective function.
2. The equality check method of claim 1,
taking the balance objective function as an objective function of a grid inspection plan optimization compilation model of the rail transit linear assets;
and determining an optimal inspection plan according to the rail transit linear asset gridding inspection plan optimization compilation model.
3. The equality check method according to claim 1, wherein the rail transit spatiotemporal grid is determined by:
and establishing a rail transit space-time grid based on the rail transit line space dimension and the time dimension of rail transit linear asset inspection.
4. The equality check method of claim 1, wherein said equality objective function is:
the ratio of the time entropy of the rail transit space-time grid to the ideal maximum time entropy of the rail transit linear asset grid is maximum;
the ideal maximum time entropy is the time entropy of the rail transit space-time grid when all the inspection activities on all the rail transit linear asset grids are distributed at equal intervals.
5. The equality check method of claim 4,
and determining the time entropy of the rail transit space-time grid according to the condition that the rail transit linear asset executes the inspection activities in each unit time.
6. The equality check method of claim 5, wherein,
determining the time entropy of each rail transit linear asset grid based on decision variables, and determining a balance objective function based on the time entropy of the rail transit linear asset grid, wherein the time entropy calculation mode of the rail transit linear asset grid is as follows:
wherein:
THifor rail transit linear asset grid GiThe temporal entropy of (a) is determined,
representing rail transit linear asset grid GiThe time interval between the (n + 1) th examination activity and the (n) th examination activity,
and
respectively representing linear asset grids G of rail transitiIn the first place
Is first and second
The checking activity is performed per unit time, and at this time,
Sifor rail transit linear asset grid GiThe total number of passes threshold for all modes of inspection,
is a set UiIs an element in (1, 2), n belongs to [1, 2i-1]Decision variables
And E represents the total unit time in one planning period, and E represents the E unit time.
7. The equality check method of claim 6, wherein the equality objective function is:
max THR (22), wherein,
8. an equalization check system, comprising:
the time entropy determining unit is used for determining the time entropy of each rail transit linear asset grid based on the decision variables, and the time entropy of each rail transit linear asset grid is the information entropy of unit time distribution of the inspection activities on the rail transit linear asset grid; determining the time entropy of the rail transit space-time grids according to the time entropy of each rail transit linear asset grid;
the target function determining unit is used for determining a balance target function according to the time entropy of the rail transit space-time grid;
and the inspection plan determining unit is used for determining an inspection plan of the rail transit linear asset according to the balance objective function.
9. The equality check system of claim 8, wherein,
the inspection plan determining unit is further used for taking the balance objective function as an objective function of a grid inspection plan optimization compilation model of the rail transit linear assets; and determining an optimal inspection plan according to the rail transit linear asset gridding inspection plan optimization compilation model.
10. The balance check system of claim 8, further comprising:
and the rail transit space-time grid determining unit is used for establishing the rail transit space-time grid based on the rail transit line space dimension and the time dimension of the rail transit linear asset inspection.
11. An equality check device, wherein said device comprises at least one processor and at least one memory;
the memory stores a computer program for performing the method of any of claims 1-7, and the processor calls the computer program in the memory to perform the method of any of claims 1-7.
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| CN202210044961.7A CN114548501B (en) | 2022-01-14 | 2022-01-14 | Balancing checking method, system and equipment |
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| US20130174200A1 (en) * | 2011-12-29 | 2013-07-04 | United Video Properties, Inc. | Systems and methods for presenting multiple assets in an interactive media guidance application |
| CN107408384A (en) * | 2015-11-25 | 2017-11-28 | 百度（美国）有限责任公司 | The end-to-end speech recognition of deployment |
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| CN109063052A (en) * | 2018-07-19 | 2018-12-21 | 北京物资学院 | A kind of personalized recommendation method and device based on time entropy |
| US20190096099A1 (en) * | 2017-09-27 | 2019-03-28 | International Business Machines Corporation | Visualizing linear assets using client-side processing |
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| US20130174200A1 (en) * | 2011-12-29 | 2013-07-04 | United Video Properties, Inc. | Systems and methods for presenting multiple assets in an interactive media guidance application |
| CN107408384A (en) * | 2015-11-25 | 2017-11-28 | 百度（美国）有限责任公司 | The end-to-end speech recognition of deployment |
| US20190096099A1 (en) * | 2017-09-27 | 2019-03-28 | International Business Machines Corporation | Visualizing linear assets using client-side processing |
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