CN114475716A

CN114475716A - Method, device, equipment and storage medium for detecting turnout working state

Info

Publication number: CN114475716A
Application number: CN202210078400.9A
Authority: CN
Inventors: 秦航远; 许庆阳; 杨飞; 孟景辉; 刘金朝; 罗泽霖
Original assignee: China Academy of Railway Sciences Corp Ltd CARS; China State Railway Group Co Ltd; Infrastructure Inspection Institute of CARS; Beijing IMAP Technology Co Ltd
Current assignee: China Academy of Railway Sciences Corp Ltd CARS; China State Railway Group Co Ltd; Infrastructure Inspection Institute of CARS; Beijing IMAP Technology Co Ltd
Priority date: 2022-01-24
Filing date: 2022-01-24
Publication date: 2022-05-13

Abstract

The method comprises the steps of acquiring transverse acceleration data of a vehicle body, vertical acceleration data of the vehicle body, transverse movement data of a framework, wheel rail force detection data and action power data; calculating to obtain a vehicle shaking index, a shock index and a conversion index; constructing a pair comparison matrix based on the vehicle shaking index, the impact index and the conversion index; according to the paired comparison matrix, calculating to obtain weighting coefficients corresponding to the vehicle shaking index, the impact index and the conversion index one by one; calculating to obtain the comprehensive score of the turnout to be detected according to the car shaking index, the impact index, the conversion index and the respective weighting coefficients; and judging the working state of the turnout to be detected according to the comprehensive score. The method provided by the invention can eliminate the problem of nonuniform dimensions among different detection data so as to perform fusion analysis on the engineering performance and the electric performance of the turnout, thereby comprehensively judging the working state of the turnout and realizing accurate identification of turnout diseases.

Description

Method, device, equipment and storage medium for detecting turnout working state

Technical Field

The present invention relates to the technical field of railway engineering and electric service, in particular to a method, a device, equipment and a storage medium for detecting the working state of a switch.

Background

The turnout mainly comprises a turnout and a turnout conversion part, is complex in structure, is easily influenced by severe weather such as sand blown by the wind, rain, snow and the like, and is one of the important devices concerned by the railway system power and electricity combination part. The maintenance and repair of the turnout equipment mainly relates to two major fields of engineering and electric affairs, wherein the electric affair major field is mainly responsible for maintenance and repair of turnout conversion equipment and related components, close contact inspection of switch rails and the like; the major responsibility of the business profession is the maintenance and inspection of the basic state of the switch rails, stock rails and track beds within the switch section. According to on-site investigation, the maintenance workload of turnout equipment accounts for more than 1/3 of the maintenance workload of engineering and electrical equipment every year, and the high failure rate is a main problem facing the maintenance of turnout equipment.

The existing detection and fault diagnosis about turnout equipment mostly adopt the following steps that turnout state analysis is divided into two parts of work and electric affairs to be respectively carried out: the detection is mainly performed by the engineering, and the turnout is inspected mainly by adopting a dynamic and static combination mode, wherein the inspection comprises track geometric parameters, vehicle dynamic response parameters and the like; the electric affairs are mainly monitored, the turnout states are mainly monitored by adopting power characteristics and the like, and in addition, the displacement, the temperature and the damage of the steel rail in the turnout area can be monitored. However, as a typical power and electricity joint in a track structure, the problems of the power and electricity professions in the turnout part are often in a cause-and-effect relationship with each other, and the two are inseparable, so that the cause of the problem is difficult to be accurately identified only from one direction. However, when the engineering and electric affairs are subjected to fusion analysis, different inspection and monitoring data used in different analysis directions have the characteristics of non-uniform units, large data magnitude difference and the like, and direct fusion analysis of the data is not facilitated.

In view of this, the present disclosure aims to provide a method, an apparatus, a device and a storage medium for detecting a switch operating state, which can eliminate the problem of non-uniform dimensions between different detection data, so as to perform fusion analysis on the engineering performance and the electrical performance of a switch, thereby performing comprehensive evaluation on the operating state of the switch and realizing effective and accurate identification of a switch fault.

Disclosure of Invention

In view of the above problems in the prior art, an object of the present disclosure is to provide a method, an apparatus, a device, and a storage medium for detecting a switch operating state, so as to solve the problem that the switch operating state cannot be accurately judged due to the fact that the switch operating performance and the switch electrical performance cannot be subjected to fusion analysis in the prior art.

In order to solve the technical problems, the specific technical scheme is as follows:

in a first aspect, a method for detecting a switch operating state is provided, including:

acquiring transverse acceleration data, vertical acceleration data and transverse movement data of a frame of a high-speed comprehensive detection train passing through a turnout to be detected, and acquiring wheel-rail force detection data and action power data of the turnout to be detected;

calculating to obtain a vehicle shaking index according to the vehicle transverse acceleration data, the vehicle vertical acceleration data and the framework transverse movement data, calculating to obtain an impact index according to the wheel-rail force detection data, and calculating to obtain a conversion index according to the action power data;

constructing a pair comparison matrix based on the vehicle shaking index, the impact index and the conversion index;

calculating to obtain weighting coefficients corresponding to the vehicle shaking index, the impact index and the conversion index one by one according to the paired comparison matrix;

calculating to obtain a comprehensive score of the turnout to be detected according to the vehicle shaking index, the impact index, the conversion index and respective weighting coefficients;

and judging the working state of the turnout to be detected according to the comprehensive score.

Specifically, calculating a weighting coefficient corresponding to the vehicle shaking index, the impact index and the conversion index one to one according to the pair comparison matrix includes:

calculating feature roots and feature vectors of the pair-wise comparison matrix;

selecting a feature vector corresponding to the maximum feature root, and carrying out normalization processing on the feature vector to obtain a normalized feature vector;

and obtaining respective weighting coefficients of the vehicle shaking index, the impact index and the conversion index according to the normalized feature vector.

Further, before calculating respective weighting coefficients of the vehicle shaking indicator, the impact indicator and the conversion indicator according to the pair comparison matrix, the method further includes:

calculating a consistency check index of the pair comparison matrix according to the maximum feature root, wherein the consistency check index is as follows:

wherein λ is_maxIs the maximum eigenvalue of the pair of comparison matrices, n is the order of the pair of comparison matrices;

comparing the consistency check index with a preset consistency judgment threshold;

and when the consistency check index is larger than a preset consistency judgment threshold value, adjusting each element in the paired comparison matrixes.

Specifically, the constructing a pair comparison matrix based on the car shaking index, the impact index and the conversion index includes:

determining importance scale values for comparing two indexes in the car shaking index, the impact index and the conversion index according to historical turnout working state data;

and constructing the pair comparison matrix according to the importance scale value to obtain:

wherein, a_ijIs the importance scale value of index i compared with index j, and n is the order number of the pair comparison matrix.

Further, before constructing a pair-wise comparison matrix based on the sway indicator, the impact indicator, and the conversion indicator, the method further comprises:

using formulas

Calculating normalized car shaking index, impact index and conversion index, wherein s is_iThe normalized index i; x is the number of_iThe initial value of the index i is not normalized; a is_iAnd b_iA parameter adjusted in dependence on the index i, a_iAnd b_iIs a constant.

Specifically, the calculating of the vehicle shaking index according to the vehicle transverse acceleration data, the vehicle vertical acceleration data and the framework transverse movement data comprises the following steps:

respectively acquiring peak values and peak values of the transverse acceleration data of the vehicle body, the vertical acceleration data of the vehicle body and the transverse moving data of the framework;

calculating to obtain a transverse acceleration index of the vehicle body according to the peak value and the peak-to-peak value of the transverse acceleration data of the vehicle body, calculating to obtain a vertical acceleration index of the vehicle body according to the peak value and the peak-to-peak value of the vertical acceleration data of the vehicle body, and calculating to obtain a framework transverse moving index according to the peak value and the peak-to-peak value of the transverse moving data of the framework;

normalizing the vehicle body transverse acceleration index, the vehicle body vertical acceleration index and the framework sideslip index;

constructing a first comparison matrix based on the normalized vehicle body transverse acceleration index, the normalized vehicle body vertical acceleration index and the framework transverse moving index;

calculating to obtain weighting coefficients corresponding to the transverse acceleration index of the vehicle body, the vertical acceleration index of the vehicle body and the transverse movement index of the framework one by one according to the first comparison matrix;

and obtaining the vehicle shaking index according to the normalized vehicle transverse acceleration index, the normalized vehicle vertical acceleration index, the normalized framework transverse moving index and respective weighting coefficients.

Specifically, the calculating the impact index according to the wheel-rail force detection data includes:

carrying out filtering and denoising processing on the wheel-rail force detection data;

calculating the peak value and the peak value of the wheel-rail force detection data after filtering and denoising;

calculating to obtain a wheel-rail force index according to the peak value and the peak value of the wheel-rail force detection data;

and carrying out normalization processing on the wheel-rail force index to obtain the impact index.

Specifically, the calculating a conversion index according to the action power data includes:

dividing the action power data into an unlocking stage, a conversion stage and a locking stage;

respectively calculating the unlocking stage, the conversion stage and the locking stage to obtain an unlocking stage score, a conversion stage score and a locking stage score;

carrying out normalization processing on the unlocking stage score, the conversion stage score and the locking stage score;

constructing a second contrast matrix based on the unlocking stage score, the conversion stage score and the locking stage score after normalization processing;

calculating to obtain weighting coefficients corresponding to the unlocking stage score, the conversion stage score and the locking stage score one by one according to the second contrast matrix;

and obtaining the conversion index according to the unlocking stage score, the conversion stage score, the locking stage score and respective weighting coefficients after normalization processing.

Further, the judging the working state of the turnout to be detected according to the comprehensive score comprises the following steps:

comparing the comprehensive score with a preset first threshold value;

and when the comprehensive score is larger than a preset first threshold value, judging that the turnout to be detected breaks down.

Further, the method further comprises:

and judging the working state of the turnout to be detected according to the comprehensive score, the car shaking index, the impact index and the conversion index.

In a second aspect, the present disclosure also provides a device for detecting an operating condition of a railway switch, including:

the system comprises an acquisition module, a detection module and a control module, wherein the acquisition module is used for acquiring transverse acceleration of a train body, vertical acceleration of the train body and transverse movement data of a framework when a high-speed comprehensive detection train passes through a turnout to be detected, and acquiring wheel-rail force detection data and action power data of the turnout to be detected;

the index calculation module is used for calculating to obtain a vehicle shaking index according to the transverse acceleration of the vehicle body, the vertical acceleration of the vehicle body and the transverse movement data of the framework, calculating to obtain an impact index according to the wheel-rail force detection data, and calculating to obtain a conversion index according to the action power data;

the matrix construction module is used for constructing a pair comparison matrix based on the vehicle shaking index, the impact index and the conversion index;

the weighting coefficient calculation module is used for calculating weighting coefficients corresponding to the vehicle shaking index, the impact index and the conversion index one by one according to the paired comparison matrix;

the comprehensive score calculation module is used for calculating to obtain a comprehensive score of the turnout to be detected according to the vehicle shaking index, the impact index, the conversion index and respective weighting coefficients;

and the judging module is used for judging the working state of the turnout to be detected according to the comprehensive score.

In a third aspect, this document also provides a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor executes the computer program to implement the method according to the above technical solution.

In a fourth aspect, this document also provides a computer-readable storage medium, in which a computer program is stored, which computer program, when being executed by a processor, is adapted to carry out the method according to the above-mentioned technical solution.

By adopting the technical scheme, the turnout working state detection method, the turnout working state detection device, the turnout working state detection equipment and the turnout working state detection storage medium can fuse and analyze a plurality of indexes reflecting turnout engineering performance and electric performance to obtain comprehensive scores of turnouts, are beneficial to realizing prejudgment and early warning of possible faults of turnouts, are beneficial to effectively preventing and maintaining fault problems, and are further beneficial to reducing the cost of turnout maintenance and repair and improving the safety and comfort of track operation.

In order to make the aforementioned and other objects, features and advantages of the present invention comprehensible, preferred embodiments accompanied with figures are described in detail below.

Drawings

In order to more clearly illustrate the embodiments or 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 only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.

Fig. 1 is a schematic diagram illustrating steps of a railway switch operating state detection method provided in an embodiment of the present disclosure;

FIG. 2 is a schematic diagram illustrating the steps of calculating the sloshing index in the embodiments herein;

FIG. 3 shows a schematic representation of the steps in calculating the impact indicator in an embodiment herein;

FIG. 4 is a schematic diagram illustrating the steps of calculating the transformation index in an embodiment herein;

fig. 5 shows a schematic diagram of an architecture for calculating a composite score of a switch to be detected, which is established in the embodiment of the present disclosure;

FIG. 6 shows the scoring of points to be detected at various stages of the conversion process;

FIG. 7 shows a graph of the action power of the switch;

fig. 8 is a schematic structural diagram illustrating a railway switch operating condition detecting device provided by an embodiment of the present disclosure;

fig. 9 shows a schematic structural diagram of a computer device provided in an embodiment herein.

Description of the symbols of the drawings:

81. an acquisition module;

82. an index calculation module;

83. a matrix construction module;

84. a weighting coefficient calculation module;

85. a comprehensive score calculation module;

86. a judgment module;

902. a computer device;

904. a processor;

906. a memory;

908. a drive mechanism;

910. an input/output module;

912. an input device;

914. an output device;

916. a presentation device;

918. a graphical user interface;

920. a network interface;

922. a communication link;

924. a communication bus.

Detailed Description

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 only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments herein without making any creative effort, shall fall within the scope of protection.

It should be noted that the terms "first," "second," and the like in the description and claims herein and in the above-described drawings are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments herein described are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, apparatus, article, or device that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or device.

At present, the detection and fault diagnosis of turnout equipment are mostly carried out by dividing the turnout state analysis into two parts of engineering and electric affairs: the detection is mainly performed by the engineering, and the turnout is inspected mainly by adopting a dynamic and static combination mode, wherein the inspection comprises track geometric parameters, vehicle dynamic response parameters and the like; the electric affairs are mainly monitored, the turnout states are mainly monitored by adopting power characteristics and the like, and in addition, the displacement, the temperature and the damage of the steel rail in the turnout area can be monitored. However, as a typical work and electricity joint part in a track structure, work and electricity professional faults of a turnout are often in a cause-and-effect relationship with each other, the two are inseparable, and the cause of the fault is difficult to be accurately identified only from one direction. However, when the engineering and electric affairs are subjected to fusion analysis, different inspection and monitoring data used in different analysis directions have the characteristics of non-uniform units, large data magnitude difference and the like, and direct fusion analysis of the data is not facilitated.

In order to solve the above problems, embodiments herein provide a method for detecting a turnout operating state, which can overcome the problem of non-uniform dimensions among different detection data, and implement fusion analysis of the engineering performance and the electrical performance of a turnout, thereby performing comprehensive evaluation on the operating state of the turnout and implementing effective and accurate identification of a turnout disease. Fig. 1 is a schematic diagram of steps of a method for detecting a switch operating state provided in an embodiment of the present disclosure, and the present disclosure provides the method operation steps as described in the embodiment or the flowchart, but more or less operation steps may be included based on conventional or non-inventive labor. The order of steps recited in the embodiments is merely one manner of performing the steps in a multitude of orders and does not represent the only order of execution. When an actual system or apparatus product executes, it can execute sequentially or in parallel according to the method shown in the embodiment or the figures. Specifically, as shown in fig. 1, the method may include:

s110: the method comprises the steps of obtaining transverse acceleration of a train body, vertical acceleration of the train body and transverse movement data of a framework when a high-speed comprehensive detection train passes through a turnout to be detected, and obtaining wheel-rail force detection data and action power data of the turnout to be detected.

The transverse acceleration and the vertical acceleration of the train body can be respectively measured by a transverse acceleration sensor and a vertical acceleration sensor which are arranged on the high-speed comprehensive detection train; the frame is connected with train wheels and a train body structure and is also called a bogie, the frame transverse moving data can be used for representing the swinging condition of the frame relative to a steel rail when the frame passes through a turnout to be measured, and the frame transverse moving data can be obtained according to a detector arranged at the frame; the wheel-rail force can be used for reflecting strain generated by interaction force of train wheels and rails, and wheel-rail force detection data can be obtained by detecting a special force measuring wheel; the action power data is the power value when the switch machine switches the turnout from one lane to another lane.

S120: calculating to obtain a shaking indicator according to the transverse acceleration of the vehicle body, the vertical acceleration of the vehicle body and the transverse movement data of the framework, calculating to obtain an impact indicator according to the wheel-rail force detection data, and calculating to obtain a conversion indicator according to the action power data.

The car shaking index and the impact index can be used for reflecting the engineering performance of the turnout, the conversion index can be used for reflecting the electric performance of the turnout, and by combining the car shaking index, the impact index and the conversion index, the integration analysis of the engineering performance and the electric performance of the turnout can be realized, and the comprehensive judgment of the working state of the turnout can be realized.

S130: and constructing a pair comparison matrix based on the vehicle shaking index, the impact index and the conversion index.

S140: and calculating to obtain weighting coefficients corresponding to the vehicle shaking index, the impact index and the conversion index one by one according to the paired comparison matrix.

S150: and calculating to obtain the comprehensive score of the turnout to be detected according to the car shaking index, the impact index, the conversion index and the respective weighting coefficients.

S160: and judging the working state of the turnout to be detected according to the comprehensive score.

The turnout working state detection method provided by the embodiment of the specification utilizes a hierarchical analysis method to perform fusion analysis on a plurality of indexes reflecting turnout engineering performance and electric performance to obtain comprehensive score of the turnout, is favorable for realizing pre-judgment and early warning of possible faults of the turnout, and is favorable for effectively preventing, treating and maintaining fault problems, thereby being favorable for reducing the cost of turnout maintenance and repair and improving the safety and comfort of track operation.

Specifically, in the embodiment of the present specification, at step S130: before constructing a pair of comparison matrices based on the sway indicator, the impact indicator, and the transformation indicator, the method further comprises:

using formulas

Calculating normalized vehicle shaking index, impact index and conversion index, wherein s is_iThe normalized index i; x is the number of_iThe initial value of the index i is not normalized; a is_iAnd b_iA parameter adjusted in dependence on the index i, a_iAnd b_iIs a constant.

Exemplary, for non-normalized vehicle shaking indicator x₁Its corresponding normalized sloshing index s₁Comprises the following steps:

wherein, a₁And b₁Can be calculated by the following formula:

μ₁the average value of the car shaking indexes of all turnouts to be detected is obtained; v is₁The score is 95% of the car shaking indexes of all turnouts to be detected, namely the value of the car shaking indexes ranked at 95% after the car shaking indexes of all turnouts to be detected are sorted from small to large. Of course, v in the above simultaneous formula₁Other values may be chosen, and the right side of the equation may be other than 0.95. Similarly, for the initial impact index x₂And the non-normalized conversion index x₃Normalization processing is carried out to obtain the impact index s after normalization₂And normalized conversion index s₃。

Specifically, in the embodiment of the present specification, step S130: based on the car shaking index, the impact index and the conversion index, a pairwise comparison matrix is constructed, which includes:

and determining importance scale values for comparing two indexes in the car shaking index, the impact index and the conversion index according to historical turnout working state data.

wherein, a_ijIs the importance scale value of index i compared with index j, and n is the order number of the pair comparison matrix. a is_ijHas a value of 1 to 9 and satisfies

Specifically, the importance scale value may be assigned with reference to table 1 below:

TABLE 1

In some feasible embodiments, according to some existing turnout data, including normally-operating turnout data and faulted turnout data, and according to the fault type, the fault severity and the like, which data are more strongly correlated with the fault are considered, so that the importance scale value of pairwise comparison among the vehicle shaking index, the impact index and the conversion index is determined.

Illustratively, the impact indicator is somewhat important compared to the sloshing indicator, namely a₂₁The value of (d) is taken as 3; the conversion index is of intermediate and extreme importance compared to the sloshing index, i.e. a₃₁The value of (2) is taken as 8; and the transformation index is slightly more important than the impact index, i.e. a₃₂Taking the value of 3, the following pairwise comparison matrix can be established:

the values of the elements in the pair-wise comparison matrix, that is, the relative importance scale values among the indexes are exemplary, and the importance scale values among the indexes need to be set according to the actual application scene.

Further, in the embodiment of the present specification, in step S140: before calculating weighting coefficients corresponding to the vehicle shaking index, the impact index and the conversion index one by one according to the paired comparison matrix, the method further comprises:

calculating a consistency check index of the paired comparison matrixes according to the maximum characteristic root of the paired comparison matrixes, wherein the consistency check index is as follows:

comparing the consistency check index with a preset consistency judgment threshold; in the embodiment of the present specification, the preset consistency determination threshold may be set to 0.1 or another constant close to 0.

Exemplarily, the feature roots and the feature vectors corresponding to the feature roots one by one are solved for the pairwise comparison matrix constructed based on the vehicle shaking index, the impact index and the conversion index, wherein the feature root with the largest value is the largest feature root, and λ is obtained through calculation_maxIs 3.002 (the largest feature root corresponds to the matrix, when matrix A is used₀When the middle element changes, the maximum feature root changes accordingly).

If the consistency verification index CI is 0.001; if the value is less than the preset consistency judgment threshold value, the pair comparison constructed in the above way is indicatedMatrix A₀The consistency requirement is met, and the method can be used for calculating the weighting coefficient of each index. The larger the CI value of the consistency verification index is, the more serious the inconsistency of the pair comparison matrix is, and at this time, if the calculation result of the weight vector is taken as a decision basis, the problem of deviation from the actual situation will occur.

Since the deviation of the consistency of the pair of comparison matrices may also be caused by random reasons, in some preferred embodiments, the relative consistency index of the pair of comparison matrices may be further calculated, where the relative consistency index is denoted as CR, then:

wherein, RI is a random consistency index; the random consistency index can be obtained by RI according to the rank table of the matrix. For example, when the order is 3, the random consistency index may be RI 0.58.

Comparing the relative consistency index with a preset relative consistency judgment threshold; for example, the preset relative consistency determination threshold may be set to 0.1, but may be set to other values.

Then calculating to obtain random consistency index

Then the comparison matrix a is paired₀And the consistency requirement is met.

In the embodiment of the present specification, after verifying that the constructed pair of comparison matrices meet the consistency condition, step S140 is performed: calculating weighting coefficients corresponding to the vehicle shaking index, the impact index and the conversion index one to one according to the pair comparison matrix, and the calculating may include:

calculating a feature root and a feature vector of the pair-wise comparison matrix;

Illustratively, the pair-wise comparison matrix A is computed₀Maximum characteristic root λ of_maxIs 3.002, and the corresponding feature vector is

That is, the sway indicator, the impact indicator, and the conversion indicator weighting coefficients are 0.082, 0.244, and 0.674, respectively.

And recording the comprehensive score of the turnout to be detected as S, and then:

S＝0.082s₁+0.244s₂+0.674s₃。

and then, judging the working state of the turnout to be detected according to the comprehensive score obtained by calculation.

It should be noted that, after the weighting coefficients of the vehicle shaking indicator, the impact indicator, and the conversion indicator are obtained through calculation, whether a logical error exists in the construction of the pair of comparison matrices may also be verified according to the relative magnitude relationship of the values of the weighting coefficients: that is, it is determined whether the magnitude relationship of the weighting coefficients of the respective indexes is consistent with the importance scale relationship when the pair comparison matrix is constructed, for example, if the impact index is slightly more important than the vehicle shaking index, the weighting coefficient of the impact index should be larger than the weighting coefficient of the vehicle shaking index, otherwise, a logical error is stored.

As shown in fig. 2, in the embodiment of the present specification, the vehicle shaking indicator (non-normalized vehicle shaking indicator x)₁) The method can be obtained by calculation according to the transverse acceleration of the vehicle body, the vertical acceleration of the vehicle body and the transverse movement data of the framework, and specifically comprises the following steps:

s210: and respectively acquiring peak values and peak values of the transverse acceleration data of the vehicle body, the vertical acceleration data of the vehicle body and the transverse moving data of the framework.

S220: calculating to obtain a transverse acceleration index of the vehicle body according to the peak value and the peak-to-peak value of the transverse acceleration data of the vehicle body, calculating to obtain a vertical acceleration index of the vehicle body according to the peak value and the peak-to-peak value of the vertical acceleration data of the vehicle body, and calculating to obtain a framework transverse moving index according to the peak value and the peak-to-peak value of the transverse moving data of the framework.

S230: normalizing the vehicle body transverse acceleration index, the vehicle body vertical acceleration index and the framework sideslip index;

s240: constructing a first comparison matrix based on the normalized vehicle body transverse acceleration index, the normalized vehicle body vertical acceleration index and the framework transverse moving index;

s250: calculating to obtain weighting coefficients corresponding to the transverse acceleration index of the vehicle body, the vertical acceleration index of the vehicle body and the transverse movement index of the framework one by one according to the first comparison matrix;

s260: and obtaining the vehicle shaking index according to the normalized vehicle transverse acceleration index, the normalized vehicle vertical acceleration index, the normalized framework transverse moving index and respective weighting coefficients.

How to obtain the vehicle shaking index is described below by taking the lateral acceleration data of the vehicle body as an example:

a group of transverse acceleration data cl of the train body is obtained by walking the high-speed comprehensive detection train along the turnout to be detected_iAnd i is 1, 2, … N, and N is the number of detected transverse acceleration data of the train body (related to the sampling frequency and the traveling speed of the high-speed comprehensive detection train).

The peak value PV of the lateral acceleration data of the vehicle body_clComprises the following steps:

PV_cl＝max(abs(cl_i))；

where max (. cndot.) is the maximum value and abs (. cndot.) is the absolute value.

The peak-to-peak value PPV of the lateral acceleration data of the vehicle body_clComprises the following steps:

PPV_cl＝max(abs(P_max-P_min))；

wherein, P_maxAnd P_minRespectively the lateral acceleration of the vehicle bodyData for adjacent peaks and valleys.

And calculating all extreme points (including a maximum value and a minimum value) of the transverse acceleration data of the vehicle body, calculating a difference value of an amplitude value for each group of adjacent wave peak values and wave trough values, and selecting the maximum difference value as a peak-peak value.

In the embodiment of the specification, the peak-to-peak value is not simply calculated by using the maximum value and the minimum value of the whole group of data, but calculated by using the adjacent extreme values, so that the detection sensitivity can be improved, the omission of characteristic data is avoided, the method is more suitable for the instantaneous characteristic of the vehicle shaking index, and the accuracy of the vehicle shaking index calculation is improved; the method is also suitable for the transverse acceleration data with zero drift, and is beneficial to improving the applicability of the peak-to-peak value calculation method.

Calculating to obtain the transverse acceleration index of the vehicle body according to the peak value and the peak value of the transverse acceleration data of the vehicle body, and recording that the transverse acceleration index of the vehicle body is WCI_clThen, there are:

WCI_cl＝η_cl1PV_cl+η_cl2PPV_cl；

wherein eta is_cl1And η_cl2Peak PV of the vehicle body lateral acceleration data respectively_clSum peak PPV_clCoefficient of (1), in the examples of the present specification,. eta_cl1And η_cl2Can be derived from historical empirical data, exemplary, η_cl1And η_cl2Can be respectively

And

then

Similarly, the vehicle body vertical acceleration data bl is calculated_iPeak value PV of_blSum peak PPV_bl(ii) a And frame traverse data cv_iPeak of (2)Value PV_cvSum peak PPV_cv。

And then calculating to obtain the WCI as the vertical acceleration index of the vehicle body_bl＝η_bl1PV_bl+η_bl2PPV_bl；

And architecture sideslip indicator WCI_cv＝η_cv1PV_cv+η_cv2PPV_cv。

Wherein eta is_bl1And η_bl2Peak PV of vertical acceleration data of vehicle body_blSum peak PPV_blCoefficient of (eta)_cv1And η_cv2Peak PV of architectural traversing data, respectively_cvSum peak PPV_cvAnd in the examples of this specification, there are

Namely:

for the car body lateral acceleration index WCI_clThe vertical acceleration index WCI of the car body_blAnd the architecture sideslip indicator WCI_cvNormalizing the above-mentioned indexes by using Sigmoid function (the normalization method can refer to the above-mentioned text, and is not described here again), and recording that the normalized transverse acceleration index of the vehicle body, the normalized vertical acceleration index of the vehicle body and the normalized frame transverse movement index are respectively S_cl、S_blAnd S_cv。

Based on the vehicle body lateral acceleration index S after normalization processing_clThe vertical acceleration index S of the vehicle body_blAnd the frame traversing index S_cvConstructing a first contrast matrix, denoted A₁。

Judging the first contrast matrix A₁Whether a consistency condition is satisfied; when the first contrast matrix A₁When the consistency condition is met, calculating to obtain the first contrast matrix A₁And the maximum feature root ofThe characteristic vector corresponding to the maximum feature root is recorded as

Normalizing the feature vector corresponding to the maximum feature root to obtain a normalized feature vector; and obtaining respective weighting coefficients of the transverse acceleration index of the vehicle body, the vertical acceleration index of the vehicle body and the transverse movement index of the framework by using the normalized feature vector.

Whereby the vehicle shaking index x₁Comprises the following steps:

that is to say, the application not only obtains the comprehensive score of the turnout to be detected based on the hierarchical analysis method for the vehicle shaking index, the impact index and the conversion index, but also obtains the vehicle shaking index by calculating according to the data of three dimensions, namely the transverse acceleration data of the vehicle body, the vertical acceleration data of the vehicle body and the transverse movement data of the framework, can comprehensively consider the influence of various factors on the working state of the turnout, and improves the accurate judgment on the working state of the turnout.

As shown in FIG. 3, in the examples of the present specification, the impact index x₂The method can be obtained by calculation according to the wheel-rail force detection data, and specifically comprises the following steps:

s310: and carrying out filtering and denoising processing on the wheel-rail force detection data.

For the turnout to be detected, the wheel-rail force detection data is f (i), i is 1, 2, … N, N is the number of data, and the low-frequency part is removed by carrying out band-pass filtering processing on the turnout to obtain f_h(i) So as to improve the accuracy of the subsequent impact index calculation.

S320: and calculating the peak value and the peak value of the wheel-rail force detection data after filtering and denoising.

Recording the peak value and the peak value of the wheel-rail force detection data as PV respectively_fAnd PPV_f(ii) a Please refer to the foregoing discussion for the peak value and the method for calculating the peak value, which are not further described herein。

S330: and calculating to obtain the wheel-rail force index according to the peak value and the peak value of the wheel-rail force detection data.

Recording the wheel-rail force index as WCI_fThen, there are:

WCI_f＝η_f1PV_f+η_f2PPV_f；

wherein eta is_f1And η_f2Peak values PV of the wheel-rail force detection data, respectively_fSum peak PPV_fAnd eta is obtained from historical empirical data_f1And η_f2Can be respectively

And

then

S340: and carrying out normalization processing on the wheel-rail force index to obtain the impact index.

Please refer to the foregoing for the method for normalizing the wheel-rail force index, which is not described herein again, and the normalized wheel-rail force index is denoted by S_fBecause the impact index is calculated from data of only one dimension (i.e., wheel-rail force detection data), the construction of a pair comparison matrix and the calculation of a weighting coefficient are not required after the wheel-rail force index is normalized, that is, the normalized wheel-rail force index is S_fNamely the impact index x₂，x₂＝S_f。

As shown in FIG. 4, in the embodiment of the present specification, the index x is converted₃The method can be obtained by calculation according to the action power data, and specifically comprises the following steps:

s410: and dividing the action power data into an unlocking phase, a conversion phase and a locking phase.

Fig. 7 is a graph plotted according to the operation power data of the switch to be detected.

Since the switch machine usually has a relatively fixed working power and working period when switching the switch from one lane to another lane, in the embodiment of the present specification, the action power data may be divided into an unlocking phase, a switching phase and a locking phase according to time, for example, 0 second to 0.5 second may be divided into the unlocking phase, 0.5 second to 5.5 second may be divided into the switching phase, and a part after 5.5 seconds may be divided into the locking phase. It should be noted that the time nodes that are divided for each phase are only exemplary, and besides the above-mentioned dividing of each phase according to time, there may be other dividing manners, such as dividing according to the magnitude of power, and the like.

S420: and respectively calculating the unlocking stage, the conversion stage and the locking stage to obtain an unlocking stage score, a conversion stage score and a locking stage score.

The score of the unlocking stage, the score of the conversion stage and the score of the locking stage are respectively T_op、T_drAnd T_lk。

S430: and carrying out normalization processing on the unlocking stage score, the conversion stage score and the locking stage score.

Scoring the unlock phase by T_opConversion stage score T_drAnd locking phase score T_lkPlease refer to the foregoing for the normalization method, which is not repeated herein, and the normalized unlocking stage score, conversion stage score and locking stage score are respectively denoted as S_op、S_drAnd S_lk。

S440: and constructing a second contrast matrix based on the unlocking stage score, the conversion stage score and the locking stage score after normalization processing.

Unlocking stage score S based on normalization_opConversion stage scoring S_drAnd locking stage score S_lkMethod for constructing the second contrast matrix please refer to the above text, note the second contrast matrix as A₂。

S450: and calculating to obtain weighting coefficients corresponding to the unlocking stage score, the conversion stage score and the locking stage score one by one according to the second comparison matrix.

Namely, the maximum characteristic root of the second contrast matrix and the characteristic vector corresponding to the maximum characteristic root are obtained by calculation and are recorded as

The normalized feature vector is:

the weighting coefficients of the unlocking stage score, the conversion stage score and the locking stage score are respectively

And

s460: and obtaining the conversion index according to the unlocking stage score, the conversion stage score, the locking stage score and respective weighting coefficients after normalization processing.

The conversion index is:

preferably, in step S450: before calculating, according to the second comparison matrix, weighting coefficients corresponding to the unlocking stage score, the conversion stage score and the locking stage score one to one, the method further includes:

judging the second contrast matrix A₂Whether a consistency condition is satisfied; specifically, according to the second contrast matrix A₂Calculating a consistency check indicator of the second contrast matrix according to the maximum feature root, and calculating a consistency check indicator of the second contrast matrix according to oneCalculating a relative consistency check index of the second contrast matrix according to the consistency check index and the random consistency index; comparing the second contrast matrix A₂Comparing the consistency check index with a preset consistency judgment threshold value, and comparing the relative consistency index with a preset relative consistency judgment threshold value; and when the consistency check index of the second comparison matrix is smaller than a preset consistency judgment threshold value, or the relative consistency index is smaller than a preset relative consistency judgment threshold value, the second comparison matrix meets the consistency condition.

If yes, executing step S450;

and if not, adjusting each element in the second contrast matrix.

In this embodiment, the unlocking stage score T in step S420_opCan be obtained by calculation according to the following method:

respectively calculating the values of the statistical characteristics shown in the table 2 according to the action power data in the unlocking stage;

TABLE 2

In table 2, i (j) is the value of the jth sampling point in the motion power data, and c is the number of sampling points in the motion power data.

Namely, calculating to obtain the statistical characteristics of 20 dimensions;

normalizing the statistical characteristics of the 20 dimensions; further constructing to obtain a third contrast matrix, marked as A₃(ii) a Judging the third contrast matrix A₃Whether the consistency condition is met or not is judged, if yes, the third comparison matrix A is obtained through calculation₃And a feature vector corresponding to the maximum feature value; the unlocking stage score can be obtained based on the feature vector as follows:

k is the kth statistical characteristic, w_kWeighting coefficient, s, for the kth statistical feature_kThe k-th statistical characteristic after normalization processing is obtained.

Similarly, the transition stage score T can be calculated_drAnd said locking phase score T_lk。

Since the score T is calculated during the unlocking stage_opSaid transition stage score T_drAnd said locking phase score T_lkIn the process, the order number of the paired comparison matrix is larger, the calculation amount is larger, the calculation difficulty is higher, and according to historical empirical data, the score T of the unlocking stage and the statistical characteristics of the 20 dimensions can be known_opThe four statistical characteristics of peak time, peak state coefficient, peak factor and kurtosis are more closely related, so that the construction of a paired comparison matrix can be carried out based on the four statistical characteristics, the order of the paired comparison matrix is 4, the calculation difficulty can be greatly reduced, and the calculation response efficiency is improved. Similarly, the transition phase score T_drThe more closely related statistical characteristics are the conversion time, the root mean square, the wavelet energy, the maximum minimum difference and the quartering difference; and said locking phase score T_lkMore closely related are the four statistical characteristics of the import-export difference, the skewness coefficient, the wavelet energy and the average value. That is to say, in the embodiment of the present specification, a framework as shown in fig. 5 may be established, a triple-level analysis method is performed, and finally, a comprehensive score of the switch to be detected is obtained through calculation.

Further, in the embodiment of the present specification, step S160: judging the working state of the turnout to be detected according to the comprehensive score can include:

comparing the comprehensive score with a preset first threshold value;

For example, the first threshold may be set to 200; and when the comprehensive score is larger than 200, judging that the turnout to be detected breaks down, and sending early warning to prevent, control and maintain the turnout.

In some preferred embodiments, the working state, the fault type and the fault severity of the turnout to be detected can be comprehensively judged according to the comprehensive score, the vehicle shaking index, the impact index and the conversion index. Exemplarily, whether the vehicle shaking index is larger than a second threshold, whether the impact index is larger than a third threshold, and whether the conversion index is larger than a fourth threshold are judged; if the three judgment conditions are all met, the fault severity is high, if any two judgment conditions are met, the fault severity is medium, if one judgment condition is met, the fault severity is low, and turnout maintenance and first-aid repair work can be carried out in a targeted mode according to the severity of different turnout faults.

When the vehicle shaking index is larger than the second threshold value, the fact that the turnout track part possibly has a problem can be judged, and the track needs to be adjusted; when the impact index is larger than a third threshold value, judging that the track defect possibly exists, and polishing the track defect; and when the conversion index is larger than the fourth threshold value, judging that the electric service problem possibly exists. In conclusion, the turnout which is possibly in fault can be preliminarily screened through comprehensive grading, the cause of the fault and the severity of the fault are analyzed by utilizing the vehicle shaking index, the impact index and the conversion index, the working state of the turnout can be more accurately judged, and an accurate renovation plan can be provided for the turnout fault.

For the conversion index, the scores of each conversion stage, namely the score T of the unlocking stage, are calculated_opThe conversion phase score T_drAnd said locking phase score T_lkTherefore, further, the case that the conversion index is larger than the fourth threshold value can be further analyzed:

as shown in fig. 6, the scores of 30 groups of switches to be detected (numbered 0 to 29) at each stage of the conversion process are obtained, and (a) in fig. 6 is the score of the unlocking stage of each of the 30 groups of switches to be detected; fig. 6 (b) shows the respective transition stage scores of 30 sets of switches to be detected; and (c) of fig. 6, the locking stage scores of each of the 30 switches to be detected are given.

As shown in fig. 7, the graph of the operating power of the switch is shown, in which fig. 7 (a) shows the operating power curve of the switch numbered 15, and fig. 7 (b) shows the operating power curve of the switch numbered 25. It can be seen that the action power curve of the turnout numbered 15 is kept in a fixed range in a longer period of time, the turnout is finally not locked, the score of the turnout in the unlocking stage is lower, the score of the turnout in the conversion stage and the final locking stage is higher, and the turnout numbered 15 can be comprehensively judged to have a fault problem that the turnout is clamped by a foreign object. In the locking process of the turnout with the number of 25, the action power curve is not decreased or increased, the score of the locking stage of the turnout is higher, and the two-phase verification can judge that the possible fault problems of the turnout with the number of 25 are that the turnout is adjusted too tightly, the rack block is lack of oil and the like, so that the two faulty turnouts are maintained.

The method has the advantages that the normalization function is adopted to normalize the multi-source inspection monitoring data, and then data fusion analysis is carried out according to a hierarchical analysis method, so that the industrial and electric fusion data analysis method is adopted, the industrial and electric service inspection monitoring data are integrated, the integrated industrial and electric data are accurately identified and integrated, the industrial and electric professional maintenance and repair work of the turnout is scientifically guided, the early warning is carried out in advance and the possible fault type is pre-judged under the condition that the comprehensive score of the scientific and engineering significance is greater than the first threshold value, and the scientific guidance is provided for the maintenance or replacement of the turnout.

As shown in fig. 8, the present specification further provides a railway switch operating condition detecting device, including:

the acquisition module 81 is used for acquiring transverse acceleration of a train body, vertical acceleration of the train body and transverse movement data of a framework when the high-speed comprehensive detection train passes through a turnout to be detected, and acquiring wheel-rail force detection data and action power data of the turnout to be detected;

the index calculation module 82 is used for calculating a vehicle shaking index according to the transverse acceleration of the vehicle body, the vertical acceleration of the vehicle body and the transverse movement data of the framework, calculating an impact index according to the wheel-rail force detection data, and calculating a conversion index according to the action power data;

a matrix construction module 83, configured to construct a pair comparison matrix based on the vehicle shaking index, the impact index, and the conversion index;

a weighting coefficient calculation module 84, configured to calculate, according to the paired comparison matrix, weighting coefficients corresponding to the vehicle shaking indicator, the impact indicator, and the conversion indicator one to one;

the comprehensive score calculation module 85 is used for calculating and obtaining a comprehensive score of the turnout to be detected according to the vehicle shaking index, the impact index, the conversion index and respective weighting coefficients;

and the judging module 86 is used for judging the working state of the turnout to be detected according to the comprehensive score.

The advantages achieved by the device provided by the embodiment of the specification are consistent with those achieved by the method, and are not described in detail herein.

As shown in fig. 9, for a computer device provided for embodiments herein, the computer device 902 may include one or more processors 904, such as one or more Central Processing Units (CPUs), each of which may implement one or more hardware threads. The computer device 902 may also include any memory 906 for storing any kind of information, such as code, settings, data, etc. For example, and without limitation, memory 906 may include any one or more of the following in combination: any type of RAM, any type of ROM, flash memory devices, hard disks, optical disks, etc. More generally, any memory may use any technology to store information. Further, any memory may provide volatile or non-volatile retention of information. Further, any memory may represent fixed or removable components of computer device 902. In one case, when the processor 904 executes the associated instructions, which are stored in any memory or combination of memories, the computer device 902 can perform any of the operations of the associated instructions. The computer device 902 also includes one or more drive mechanisms 908, such as a hard disk drive mechanism, an optical disk drive mechanism, etc., for interacting with any memory.

Computer device 902 may also include an input/output module 910(I/O) for receiving various inputs (via input device 912) and for providing various outputs (via output device 914). One particular output mechanism may include a presentation device 916 and an associated Graphical User Interface (GUI) 918. In other embodiments, input/output module 910(I/O), input device 912, and output device 914 may also be excluded, acting as only one computer device in a network. Computer device 902 may also include one or more network interfaces 920 for exchanging data with other devices via one or more communication links 922. One or more communication buses 924 couple the above-described components together.

Communication link 922 may be implemented in any manner, such as over a local area network, a wide area network (e.g., the Internet), a point-to-point connection, etc., or any combination thereof. Communication link 922 may include any combination of hardwired links, wireless links, routers, gateway functions, name servers, etc., governed by any protocol or combination of protocols.

Corresponding to the methods in fig. 1 to 4, the embodiments herein also provide a computer-readable storage medium having stored thereon a computer program, which, when executed by a processor, performs the steps of the above-described method.

Embodiments herein also provide computer readable instructions, wherein when executed by a processor, a program thereof causes the processor to perform the method as shown in fig. 1-4.

It should be understood that, in various embodiments herein, the sequence numbers of the above-mentioned processes do not mean the execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments herein.

It should also be understood that, in the embodiments herein, the term "and/or" is only one kind of association relation describing an associated object, meaning that three kinds of relations may exist. For example, a and/or B, may represent: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter related objects are in an "or" relationship.

Those of ordinary skill in the art will appreciate that the elements and algorithm steps of the examples described in connection with the embodiments disclosed herein may be embodied in electronic hardware, computer software, or combinations of both, and that the components and steps of the examples have been described in a functional general in the foregoing description for the purpose of illustrating clearly the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present disclosure.

It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.

In the several embodiments provided herein, it should be understood that the disclosed system, apparatus, and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may also be an electric, mechanical or other form of connection.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purposes of the embodiments herein.

In addition, functional units in the embodiments herein may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.

The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present invention may be implemented in a form of a software product, which is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the methods described in the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.

The principles and embodiments of this document are explained herein using specific examples, which are presented only to aid in understanding the methods and their core concepts; meanwhile, for the general technical personnel in the field, according to the idea of this document, there may be changes in the concrete implementation and the application scope, in summary, this description should not be understood as the limitation of this document.

Claims

1. A method for detecting the working state of a switch is characterized by comprising the following steps:

2. The method of claim 1, wherein calculating weighting coefficients corresponding to the sway indicator, the impact indicator, and the conversion indicator one-to-one according to the pair-wise comparison matrix comprises:

3. The method of claim 2, wherein before calculating the weighting coefficients of the sway indicator, the impact indicator, and the conversion indicator according to the pair-wise comparison matrix, the method further comprises:

4. The method of claim 1, wherein constructing a pair of comparison matrices based on the sway indicator, the impact indicator, and the conversion indicator comprises:

5. The method of claim 4, wherein prior to constructing a pair of comparison matrices based on the sway indicator, the impact indicator, and the conversion indicator, the method further comprises:

using formulas

6. The method of claim 1, wherein calculating a sway indicator based on the lateral vehicle body acceleration data, the vertical vehicle body acceleration data, and the frame lateral movement data comprises:

7. The method of claim 1, wherein calculating an impact indicator from the wheel-rail force detection data comprises:

8. The method of claim 1, wherein calculating a transition indicator from the motion power data comprises:

9. The method according to claim 1, wherein the judging the operating state of the switch to be detected according to the composite score comprises:

comparing the comprehensive score with a preset first threshold value;

10. The method of claim 9, further comprising:

11. A railway switch operating condition detection device is characterized by comprising:

12. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the method according to any of claims 1 to 10 when executing the computer program.

13. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program which, when executed by a processor, implements the method of any one of claims 1 to 10.