Method and device for optimizing the ranging error of a track detection system

Abstract

The application discloses a kind of track detection system ranging error optimization method and device, it is related to track detection technical field, wherein the method includes: determining the theoretical sampling pulse number of track detection system ranging;Determine two positive integers adjacent to theoretical sampling pulse number;According to the pre-established ping-pong algorithm, according to two positive integers and theoretical sampling pulse number, construct space sampling pulse dynamic comparison value array;Ping-pong algorithm is used for: construct space sampling pulse dynamic comparison value array;Each element in the array is two positive integers adjacent to theoretical sampling pulse number, the average value of each element in the array is approximated or equal to theoretical sampling pulse number, each element in the array is sorted according to cumulative error minimum, cumulative error indicates the difference between each element in the array and theoretical sampling pulse number Sum;Ranging error optimization is carried out using the array.The application can improve the ranging accuracy of track detection system.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of track detection, in particular to a track detection system ranging error optimization method and device. BACKGROUND

[0002] This section is intended to provide background or context to the embodiments of the application recited in the claims. The description herein does not constitute admission that the prior art is prior art nor does it constitute admission that anything in this section is "prior art".

[0003] High-speed railway track smoothness directly affects train operation safety. High-speed comprehensive detection train, high-speed railway comprehensive inspection vehicle, track inspection vehicle and other track mobile equipment are automatic equipment for dynamic detection of track smoothness. The track detection system installed on the track mobile equipment detects track diseases such as track gauge, track alignment, height, level (super-elevation), and triangular pit. The ranging accuracy of the track detection system directly determines the accuracy of the track disease location on the line. Accurate determination of the track disease location has guiding significance for railway maintenance personnel to timely and quickly manage track diseases, can shorten the time to find the track disease location, quickly respond to ensure train operation safety, and effectively reduce the cost of maintenance manpower and resources.

[0004] In the prior art, the most common track detection system ranging method is to rely on the encoder installed on the axle head of the track mobile equipment. The encoder generates N pulses (N is an integer) for each revolution of the wheel, corresponding to the wheel circumference. The distance can be calculated according to the wheel circumference and the number of pulses per revolution. However, in practice, the track detection system records the number of pulses generated by the encoder every distance Δx spatial sampling interval. Theoretically, the number of pulses generated by the encoder obtained every distance Δx is m (m = (Δx × N) / wheel circumference). Theoretically, m is a small number, but in practice, the number of pulses generated by the encoder obtained every distance Δx by the track mobile equipment is an integer. This results in a certain ranging error in the number of pulses obtained each time, which will increase as the distance traveled by the track mobile equipment increases. SUMMARY

[0005] The present application provides a track detection system ranging error optimization method to improve the ranging accuracy of the track detection system and solve the problem that the ranging error of the track detection system increases as the distance traveled by the track mobile equipment increases. The method comprises:

[0006] Determine the theoretical sampling pulse number of the track detection system ranging. The theoretical sampling pulse number represents the first distance pulse number value generated by the encoder when the track mobile equipment travels a spatial sampling interval. The theoretical sampling pulse number is a small number. The track detection system is used to dynamically detect track smoothness and is installed on the track mobile equipment.

[0007] determining two positive integers adjacent to the theoretical sampling pulse number according to the theoretical sampling pulse number;

[0008] constructing a space sampling pulse dynamic comparison value array according to the two positive integers and the theoretical sampling pulse number according to a pre-established ping-pong algorithm; the ping-pong algorithm is used for: determining a weight coefficient ratio value and a total number of elements in the space sampling pulse dynamic comparison value array according to the two positive integers and the theoretical sampling pulse number; constructing the space sampling pulse dynamic comparison value array by using the two positive integers, the weight coefficient ratio value and the total number of elements; each element in the space sampling pulse dynamic comparison value array is the two positive integers adjacent to the theoretical sampling pulse number, and a sum of each element in the space sampling pulse dynamic comparison value array is approximately equal to or equal to the theoretical sampling pulse number; each element in the space sampling pulse dynamic comparison value array is sorted according to a minimum cumulative error, and the cumulative error represents a sum of differences between each element in the space sampling pulse dynamic comparison value array and the theoretical sampling pulse number;

[0009] acquiring a plurality of second distance pulse numbers generated by an encoder when a plurality of actual track mobile equipment running sampling distance intervals;

[0010] sorting the plurality of second distance pulse numbers according to a track mobile equipment running route, and replacing each first number of second distance pulse numbers with an element in the space sampling pulse dynamic comparison value array in sequence to obtain updated plurality of second distance pulse numbers; the first number is equal to the total number of elements in the space sampling pulse dynamic comparison value array.

[0011] The embodiment of the present application also provides a track detection system ranging error optimization device for reducing the track detection system ranging error and improving the problem that the track detection system ranging error increases with the increase of the track mobile equipment running distance; the device comprises:

[0012] a theoretical sampling pulse number determination module configured to determine a theoretical sampling pulse number of track detection system ranging; the theoretical sampling pulse number represents a first distance pulse number value generated by an encoder when a track mobile equipment runs a space sampling interval in theory; the theoretical sampling pulse number is a decimal number; the track detection system is used for dynamically detecting track smoothness and is installed on the track mobile equipment;

[0013] The array establishing module is configured to determine two positive integers adjacent to the theoretical sampling pulse number according to the theoretical sampling pulse number, and construct a space sampling pulse dynamic comparison value array according to the two positive integers and the theoretical sampling pulse number according to a pre-established ping-pong algorithm.

[0014] The error optimization processing module is configured to obtain a second distance pulse number generated by an encoder when the plurality of actual track mobile equipment running sampling distance intervals, sort the plurality of second distance pulse numbers according to a track mobile equipment running route, and replace each first numerical second distance pulse number with an element in the space sampling pulse dynamic comparison value array in sequence to obtain updated plurality of second distance pulse numbers. The first numerical value is equal to the total number of elements in the space sampling pulse dynamic comparison value array.

[0015] The embodiment of the present application further provides a computer device, which comprises a memory, a processor and a computer program stored in the memory and capable of running on the processor, and the processor implements the above-mentioned track detection system ranging error optimization method when executing the computer program.

[0016] The embodiment of the present application further provides a computer readable storage medium, which stores a computer program, and the computer program implements the above-mentioned track detection system ranging error optimization method when executed by a processor.

[0017] The embodiment of the present application further provides a computer program product, which comprises a computer program, and the computer program implements the above-mentioned track detection system ranging error optimization method when executed by a processor.

[0018] In the embodiment of the present application, the ping-pong algorithm is established, and the ping-pong algorithm is used for track detection system ranging error optimization. The error can be completely eliminated after the distance pulse corresponding to an array ends, the accuracy of detecting the track disease mileage position of the track detection system is improved, the problem that the track detection system ranging error increases with the increase of the track mobile equipment running distance is improved, the track disease is effectively guided for the railway maintenance personnel to timely and quickly treat the track disease, the labor and material costs of maintenance are reduced, and the requirements of the modern railway safety guarantee system are further met. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. In the drawings:

[0020] Figure 1 This is a flowchart illustrating the distance measurement error optimization method for the track detection system in an embodiment of the present invention;

[0021] Figure 2 This is a specific embodiment of the distance measurement error optimization method for the track detection system in this invention;

[0022] Figure 3 This is a specific embodiment of the distance measurement error optimization method for the track detection system in this invention;

[0023] Figure 4 This is a schematic diagram of the ranging error optimization device for the track detection system in an embodiment of the present invention;

[0024] Figure 5 This is a schematic diagram of a computer device in an embodiment of the present invention. Detailed Implementation

[0025] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings. Here, the illustrative embodiments of the present invention and their descriptions are used to explain the present invention, but are not intended to limit the present invention.

[0026] In existing technologies, track detection systems rely on encoders installed on the axle ends of track-moving equipment to measure distances. The distance traveled by the vehicle can be calculated based on the wheel circumference and the number of encoder sampling pulses. Currently, the cumulative error of encoder ranging is mainly corrected automatically through satellite positioning or RFID tag positioning systems, or manually by observing the track mileage markers.

[0027] The automatic correction of the encoder ranging cumulative error by the satellite positioning or radio frequency tag positioning system has the following deficiencies: firstly, at the device level, satellite positioning or radio frequency tag positioning devices are added, which increases the overall cost of equipment and maintenance and repair costs, and the increase in equipment introduces more system failure points and increases the instability of the system, which accordingly increases the cost of manpower and resources. Secondly, at the application level, the satellite positioning system cannot receive satellite signals in the tunnel and is disabled; the radio frequency tag needs to be laid in advance on the track plate, and the long-distance line layout and regular maintenance of the radio frequency tag will increase the cost of manpower and resources, and the radio frequency tag is in an outdoor environment on the track plate for a long time, which will largely cause the failure of the radio frequency tag due to factors such as battery attenuation and abnormal excitation signals.

[0028] The manual correction of the encoder ranging cumulative error by manually observing the line mileage mark has the following deficiencies: firstly, for existing conventional speed lines, it is difficult to ensure the accuracy and timeliness of the mileage correction due to factors such as light, speed, meeting, attention, and reaction force, and there is often a large mileage error. Secondly, for high-speed railways, due to the high speed, manual observation of the mileage mark is impossible, and this method has completely failed.

[0029] It should be noted that the acquisition, storage, use, processing, etc. of data in the technical solution of the present application comply with the relevant provisions of national laws and regulations.

[0030] The present application aims at the problem that the encoder ranging cumulative error of the track detection system increases with the increase of the driving distance of the track detection system, designs a ping-pong algorithm, reduces the encoder ranging cumulative error from the algorithm level, and verifies the effectiveness of the algorithm through the track detection comprehensive test calibration platform.

[0031] Figure 1 The flowchart of the track detection system ranging error optimization method in the embodiment of the present application is shown in Figure 1 The method comprises the following steps:

[0032] Step 101, determining the theoretical sampling pulse number of the track detection system ranging;

[0033] Step 102, determining two positive integers adjacent to the theoretical sampling pulse number according to the theoretical sampling pulse number;

[0034] Step 103, constructing a space sampling pulse dynamic comparison value array according to the two positive integers and the theoretical sampling pulse number according to the pre-established ping-pong algorithm;

[0035] Step 104, acquiring the second distance pulse number generated by the encoder when a plurality of actual track mobile equipment driving sampling distance intervals;

[0036] Step 105: sorting the plurality of second distance pulse numbers according to the track moving equipment driving route, and replacing each first number of second distance pulse numbers in the array of space sampling pulse dynamic comparison values in sequence to obtain updated plurality of second distance pulse numbers; the first number is equal to the total number of elements in the array of space sampling pulse dynamic comparison values.

[0037] From Figure 1 As can be seen from the flowchart, in the embodiment of the present application, the ping-pong algorithm is established, and the ping-pong algorithm is used for distance error optimization of the track detection system, so that the error can be completely eliminated after the distance pulse corresponding to an array ends, the accuracy of detecting the track disease mileage position of the track detection system is improved, the problem that the distance error of the track detection system increases with the increase of the driving distance of the track moving equipment is improved, the track disease is effectively guided for the railway maintenance personnel to timely and quickly treat the track disease, the labor and material costs of maintenance are reduced, and the requirements of the modern railway safety guarantee system are further met.

[0038] The track detection system distance error optimization method in the embodiment of the present application will be explained in detail below.

[0039] Firstly, the theoretical analysis of the distance error accumulation of the encoder of the track detection system is performed.

[0040] The track detection system is used for dynamically detecting track smoothness, mainly including a computer, a software program, various sensors (an encoder, a sensor for detecting track parameters, etc.), a circuit board, a circuit, various devices, etc., and is mainly installed on track moving equipment, wherein the encoder is installed at the train shaft end of the track moving equipment, and a protective cover is additionally packaged, the encoder generates N distance pulses when rotating one circle, and the corresponding vehicle driving distance is the wheel circumference πD, and the driving distance l corresponding to each distance pulse is:

[0041]

[0042] In the formula, D is the wheel diameter.

[0043] The track detection system is sampled at a fixed interval (space sampling interval) Δx, and the theoretical sampling pulse number represents the first distance pulse number generated by the encoder when the track moving equipment drives the space sampling interval in theory, and the theoretical sampling pulse number m is:

[0044]

[0045] As can be seen, the theoretical sampling pulse number m is a small number.

[0046] A sampling pulse number fixed threshold value M is set, that is, when the accumulated distance pulse number of the system reaches M, a sampling pulse is generated and sampling is implemented, and then the distance pulse number is re-accumulated.

[0047] M = trunc(m + 0.5) (3)

[0048] In the formula, trunc represents a truncation process.

[0049] The error generated by actually rounding m is

[0050] 0 <= |M - m| <= 0.5 (4)

[0051] Then the error ε of each spatial sampling interval is:

[0052]

[0053] The ε is deformed as follows:

[0054]

[0055] When the track moving equipment travels a distance L, the maximum ranging error δ generated is:

[0056]

[0057] As can be seen from formula (7), the ranging accumulation error of the track detection system encoder increases with the increase of the travel distance of the track moving equipment. From the perspective of the encoder body, the ranging accumulation error can be reduced by increasing the value of N to improve the distance measurement accuracy. However, on the one hand, the increase of the value of N of the encoder is limited by technology and other factors, and cannot be infinite, and the accumulation error cannot be reduced from the root; on the other hand, the increase of the value of N means the increase of the resolution of the encoder, and the increase of the resolution means the increase of the cost of the encoder, in addition, the value of N of the current general specification encoder is generally small, and the interchangeability and universality of the high-resolution encoder with a large value of N will also be greatly reduced.

[0058] Based on the theoretical analysis of the ranging accumulation error of the track detection system encoder, a ping-pong algorithm is proposed in the embodiment of the application.

[0059] The ping-pong algorithm in the embodiment of the application is used for:

[0060] According to two positive integers and the theoretical sampling pulse number, the weight coefficient ratio and the total number of elements in the spatial sampling pulse dynamic comparison value array are determined; the two positive integers are two positive integers adjacent to the theoretical sampling pulse number.

[0061] The space sampling pulse dynamic comparison value array is constructed by using two positive integers, a weight coefficient ratio, and a total number of array elements.

[0062] Each element in the space sampling pulse dynamic comparison value array is two positive integers adjacent to the theoretical sampling pulse number, the sum of each element in the space sampling pulse dynamic comparison value array is approximately equal to the theoretical sampling pulse number, and each element in the space sampling pulse dynamic comparison value array is sorted according to the minimum cumulative error, which represents the difference between the theoretical sampling pulse number and the theoretical sampling pulse number.

[0063] In the embodiment of the application, first, the theoretical sampling pulse number of the track detection system is determined according to the actual situation according to formula (2). Then, two positive integers adjacent to the theoretical sampling pulse number are determined according to the theoretical sampling pulse number. Then, according to the pre-established ping-pong algorithm, the space sampling pulse dynamic comparison value array M[i] is constructed according to the two positive integers and the theoretical sampling pulse number.

[0064] In one embodiment, determining two positive integers adjacent to the theoretical sampling pulse number according to the theoretical sampling pulse number can include:

[0065] According to formula (1) and the following formula (8) and (9), two positive integers a and b adjacent to the theoretical sampling pulse number are determined according to the theoretical sampling pulse number.

[0066]

[0067]

[0068] In the formula, trunc represents truncation processing, Δx is the sampling distance interval, D is the wheel diameter of the track moving equipment, and N is the number of distance pulses generated by the encoder when the wheel diameter of the track moving equipment rotates one revolution.

[0069] That is, the value of each element in the space sampling pulse dynamic comparison value array M[i] can only be two integers a or b adjacent to m, that is, the result of rounding up or rounding down m.

[0070] For example, when the wheel diameter is 920 mm, the wheel rotates one revolution with a distance of 920π, the track detection system generates a sampling pulse every 250 mm, and the corresponding encoder generates 5000 pulses per revolution, the theoretical calculation sampling pulse number is m=5000*250 / 920π≈432.7, where π is rounded to 2 decimal places, and the values of a and b are 432 and 433.

[0071] To establish the space sampling pulse dynamic comparison value array M[i], only the values of the elements in the array are determined, and the values of the elements are also determined.

[0072] Figure 2 For a specific embodiment of the orbit detection system ranging error optimization method in the embodiment of the application, the weight coefficient ratio is determined according to two positive integers and a theoretical sampling pulse number, and the total number of elements in the space sampling pulse dynamic comparison value array M[i] can include:

[0073] Step 201, establishing a target optimization function y:

[0074] y=a×p+b×q (10)

[0075] In the formula, p and q are weight coefficients.

[0076] Step 202, determining the weight coefficient ratio p / q when y converges to or equals the theoretical sampling pulse number by a mathematical statistical method.

[0077] Step 203, determining the total number of elements in the space sampling pulse dynamic comparison value array M[i] according to the weight coefficient ratio p / q.

[0078] For example, the target optimization function y is established as y=432×p+233×q, and reasonable weight coefficients p and q are designed to make y approach 432.7. If p=q=0.5, y=432.5, and there is still a gap from the optimal target. If p=0.7 and q=0.3, y=432.7, and the optimal target is reached. At this time, p and q are the optimal weight coefficients.

[0079] In order to simplify the algorithm and improve the calculation efficiency, in an embodiment, the weight coefficient ratio is determined according to two positive integers and a theoretical sampling pulse number, and the total number of elements in the space sampling pulse dynamic comparison value array can include:

[0080] According to the following formula, the weight coefficient ratio p / q is determined according to two positive integers and a theoretical sampling pulse number:

[0081]

[0082] In the formula, m is the theoretical sampling pulse number.

[0083] For example, the weight coefficient ratio p / q= (432.7-432) / (433-432.7)=7 / 3. When the weight coefficient ratio is determined to be 7 / 3, the total number of elements in the space sampling pulse dynamic comparison value array M[i] can be determined to be 10, that is, p+q, and p and q are positive integers.

[0084] Figure 3 For a specific embodiment of the orbit detection system ranging error optimization method in the embodiment of the application, after determining the number and value of elements in the array, the space sampling pulse dynamic comparison value array is constructed using two positive integers, the weight coefficient ratio, and the total number of array elements.

[0085] Step 301, respectively calculate the absolute value of the difference between two positive integers a, b and the theoretical sampling pulse number |m-a|, |m-b|, determine the positive integer corresponding to the smaller difference as the first element in the spatial sampling pulse dynamic comparison value array; update the difference m-a between the first element and the theoretical sampling pulse number as the cumulative error SUME;

[0086] Step 302, loop process as follows until the last element in the spatial sampling pulse dynamic comparison value array is determined:

[0087] Step 3021, respectively calculate the difference m-a, m-b between two positive integers a, b and the theoretical sampling pulse number;

[0088] Step 3022, respectively calculate the absolute value of the difference |SUME+m-a|, |SUME+m-b| between the cumulative error SUME and the difference m-a, m-b;

[0089] Step 3023, determine the positive integer corresponding to the smaller difference in the absolute value |SUME+m-a|, |SUME+m-b| as the second element in the spatial sampling pulse dynamic comparison value array, and assign the absolute value |SUME+m-a| to the cumulative error SUME.

[0090] In implementation, the following algorithm logic can be used:

[0091] ……………………… Algorithm logic ………………………

[0092] if(|m-a|≤|m-b|)

[0093] M[1]=a

[0094] SUME[1]=m-a

[0095] else

[0096] M[1]=b

[0097] SUME[1]=m-b

[0098] for(i=1,i++,i<k)

[0099] {

[0100] if(|SUME[i]+m-a|≤|SUME[i]+m-b|)

[0101] M[i+1]=a

[0102] SUME[i+1]=SUME[i]+m-a

[0103] else

[0104] M[i+1] = b

[0105] SUME[i+1] = SUME[i] + m - b

[0106] }

[0107] ……………………………………………………………

[0108] After the space sampling pulse dynamic comparison value array is determined, each time when the multiple actual track moving equipment running sampling distance intervals are obtained, the number of second distance pulses generated by the encoder is obtained, the multiple second distance pulse numbers are sorted according to the track moving equipment running route, and each first number of second distance pulse numbers is replaced according to the elements in the space sampling pulse dynamic comparison value array in sequence to obtain updated multiple second distance pulse numbers; the first number is equal to the total number of elements in the space sampling pulse dynamic comparison value array.

[0109] In implementation, the number of the space sampling pulse dynamic comparison value array is compared as a group, one comparison period is completed, the cumulative error of the encoder is zero or approximately zero, and then the next comparison period is entered, M[i] elements are used as comparison numbers again, and so on, and the cumulative error can be neutralized at the end of the period.

[0110] In order to verify the reliability of the track detection system ranging error optimization method in the embodiment of the application, the following test is performed.

[0111] Test 1: The theoretical sampling pulse number is 432.7, the nominal running distance is 1km, the actual sampling pulse numbers are 432, 433 respectively, and the difference of the influence of the space sampling pulse dynamic comparison value array M[i] in the embodiment of the application on the cumulative error is compared, as shown in Table 1 and Table 2.

[0112] Table 1 is a cumulative error diagram of the space sampling pulse dynamic comparison value array constructed by using the ping-pong algorithm. In implementation, the actual sampling pulse number is compared with the elements in the space sampling pulse dynamic comparison value array every 10 groups, the same is retained and the different is replaced, and it can be seen that the cumulative error of the space sampling pulse dynamic comparison value array constructed by using the ping-pong algorithm becomes 0 after 10 sampling pulses.

[0113] Table 1 is a cumulative error diagram of the space sampling pulse dynamic comparison value array constructed by using the ping-pong algorithm.

[0114] i M[i] SUME[i] 1 433 0.3 2 432 -0.4 3 433 -0.1 4 433 0.2 5 433 0.5 6 432 -0.2 7 433 0.1 8 433 0.4 9 432 -0.3 10 433 0

[0115] Table 2 is a cumulative error diagram of the existing method and the method in the embodiment of the application, the existing method is all fixed 432 or 433, and the method in the embodiment of the application is dynamically adjusted to reduce the cumulative error to 0.

[0116] Table 2 is a cumulative error diagram of the existing method and the method in the embodiment of the application

[0117]

[0118] Test 2: The cumulative error difference of the space sampling pulse dynamic comparison value array M[i] in a single cycle is compared. Table 3 is a cumulative error difference diagram of the space sampling pulse dynamic comparison value array in a single cycle, wherein the nominal distance represents the distance traveled by the track moving equipment, and it can be seen from Table 3 that the maximum cumulative error of the ping-pong algorithm in the space sampling pulse dynamic threshold comparison value array in a single cycle is 0.3 mm. If the maximum cumulative error is sorted according to a single cycle, the maximum cumulative error is 1.2 mm.

[0119] Table 3 is a cumulative error difference diagram of the space sampling pulse dynamic comparison value array in a single cycle

[0120] i Nominal distance M[i] accumulated error (m) 1 1 km + 0.25 m 0.0002 2 1 km + 0.5 m -0.0002 3 1 km + 0.75 m -0.0001 4 1 km + 1 m 0.0001 5 1 km + 1.25 m 0.0003 6 1 km + 1.5 m -0.0001 7 1 km + 1.75 m 0.0001 8 1 km + 2 m 0.0002 9 1 km + 2.25 m -0.0002 10 1 km + 2.5 m 0.0000

[0121] Test 3: The influence difference of the encoder N value of 5000 and 2000 on the ping-pong algorithm result is compared. According to the ping-pong algorithm, when the encoder N value is 5000, the number of elements 432 in the array M[i] takes a weight of 3, the number of elements 433 takes a weight of 7, and the cumulative error is 0 m. When the encoder N value is 2000, the number of elements 173 in the array M[i] takes a weight of 9, the number of elements 174 takes a weight of 1, and the cumulative error is 0 m. Table 4 is a diagram of the influence difference of the encoder on the ping-pong algorithm result, and it can be seen from Table 4 that the ping-pong algorithm can reduce the resolution of the encoder and improve the universality of the encoder under the condition that the error is unchanged.

[0122] Table 4 is a diagram of the influence difference of the encoder on the ping-pong algorithm result

[0123]

[0124] In summary, the embodiment of the application has the following technical effects:

[0125] 1) Improve the ranging accuracy, and the error influence can be completely overcome when a single cycle of the space sampling pulse dynamic comparison value array is ended. Compared with the method in which the sampling pulse number is a fixed value, the encoder ranging cumulative error of the track detection system can be effectively reduced.

[0126] 2) Reduce the requirement for the encoder accuracy, and a low-precision encoder with higher interchangeability and universality can be used, so that the cost is greatly reduced and the universality of the encoder is improved.

[0127] The application also provides a device for optimizing the ranging error of a track detection system, as described in the following embodiments. Since the device solves the problem by the same principle as the method for optimizing the ranging error of a track detection system, the implementation of the device can be referred to the implementation of the method for optimizing the ranging error of a track detection system, and the repeated parts will not be described again.

[0128] Figure 4 FIG. 1 shows a schematic diagram of the device for optimizing the ranging error of a track detection system according to an embodiment of the application, which comprises: Figure 4

[0129] a theoretical sampling pulse number determination module 401 configured to determine a theoretical sampling pulse number of the track detection system; the theoretical sampling pulse number represents a first distance pulse number value generated by an encoder when a track moving equipment travels a theoretical sampling interval in space; the theoretical sampling pulse number is a decimal number; the track detection system is an automated equipment for dynamically detecting track smoothness, and is installed on the track moving equipment;

[0130] an array establishment module 402 configured to determine two positive integers adjacent to the theoretical sampling pulse number according to the theoretical sampling pulse number; and construct a space sampling pulse dynamic comparison value array according to the two positive integers and the theoretical sampling pulse number according to a pre-established ping-pong algorithm; the ping-pong algorithm is configured to determine a weight coefficient ratio and a total number of elements in the space sampling pulse dynamic comparison value array according to the two positive integers and the theoretical sampling pulse number; and construct the space sampling pulse dynamic comparison value array by using the two positive integers, the weight coefficient ratio and the total number of elements; each element in the space sampling pulse dynamic comparison value array is the two positive integers adjacent to the theoretical sampling pulse number, the sum of each element in the space sampling pulse dynamic comparison value array is approximately equal to or equal to the theoretical sampling pulse number, and each element in the space sampling pulse dynamic comparison value array is sorted according to the minimum cumulative error, wherein the cumulative error represents the sum of the differences between each element in the space sampling pulse dynamic comparison value array and the theoretical sampling pulse number;

[0131] an error optimization processing module 403 configured to obtain a second distance pulse number generated by the encoder when a plurality of actual track moving equipment travels a sampling distance interval; sort the plurality of second distance pulse numbers according to the track moving equipment travel route, and replace each first number of second distance pulse numbers in the space sampling pulse dynamic comparison value array in sequence to obtain updated second distance pulse numbers; the first number is equal to the total number of elements in the space sampling pulse dynamic comparison value array.

[0132] In one embodiment, the array establishment module 402 is specifically configured to:

[0133] determine the two positive integers a and b adjacent to the theoretical sampling pulse number according to the theoretical sampling pulse number by the following formula:​

[0134]

[0135]

[0136]

[0137] wherein trunc represents a truncation process, Δx is a sampling distance interval, D is a track mobile equipment wheel diameter, and N is a number of distance pulses generated by an encoder in one revolution of the track mobile equipment wheel diameter.

[0138] In one embodiment, the array establishing module 402 is specifically configured to:

[0139] establish a target optimization function y:

[0140] y = a x p + b x q

[0141] wherein p and q are weight coefficients;

[0142] determine the weight coefficient ratio p / q when y converges to the theoretical sampling pulse number by means of mathematical statistics;

[0143] determine the total number of elements in the spatial sampling pulse dynamic comparison value array according to the weight coefficient ratio p / q.

[0144] In one embodiment, the array establishing module 402 is specifically configured to:

[0145] determine the weight coefficient ratio p / q according to the two positive integers and the theoretical sampling pulse number by the following formula:

[0146]

[0147] wherein m is the theoretical sampling pulse number.

[0148] In one embodiment, the array establishing module 402 is specifically configured to:

[0149] respectively calculate the absolute values of the difference |m-a| and |m-b| of the two positive integers a and b and the theoretical sampling pulse number, determine the positive integer a corresponding to the smaller difference value as the first element in the spatial sampling pulse dynamic comparison value array, and update the difference m-a of the first element and the theoretical sampling pulse number as the cumulative error SUME;

[0150] perform the following loop processing until the last element in the spatial sampling pulse dynamic comparison value array is determined:

[0151] respectively calculate the difference values m-a and m-b of the two positive integers a and b and the theoretical sampling pulse number;

[0152] Calculate the absolute value of the difference between the accumulated error SUME and the difference m-a, m-b, |SUME+m-a|, |SUME+m-b| respectively;

[0153] Determine the positive integer corresponding to the smaller difference in the absolute value of the difference |SUME+m-a|, |SUME+m-b| as the second element in the array of dynamic comparison values of the spatial sampling pulse, and assign the absolute value of the difference |SUME+m-a| to the accumulated error SUME.

[0154] Figure 5 A schematic diagram of the computer device in the embodiment of the present application is shown in Figure 5 The embodiment of the present application also provides a computer device 500, which comprises a processor 501, a memory 502, and a computer program 503 stored in the memory 502 and capable of running on the processor 501, and the processor 501 implements the above-mentioned track detection system ranging error optimization method when executing the computer program 503.

[0155] The embodiment of the present application also provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the above-mentioned track detection system ranging error optimization method.

[0156] The embodiment of the present application also provides a computer program product, which comprises a computer program, and the computer program is executed by a processor to implement the above-mentioned track detection system ranging error optimization method.

[0157] In the embodiment of the present application, the ping-pong algorithm is established, and the ping-pong algorithm is used for track detection system ranging error optimization, which can completely eliminate the error after the distance pulse corresponding to an array ends, improves the accuracy of the track detection system in detecting the track disease mileage position, improves the problem that the track detection system ranging error increases with the increase of the track moving equipment driving distance, effectively guides the railway maintenance personnel to timely and quickly treat the track disease, reduces the labor and material cost of maintenance, and further meets the requirements of the modern railway safety guarantee system.

[0158] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can adopt a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer usable program code.

[0159] The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 one or more flow or blocks Figure 1 one or more flow or blocks

[0160] These computer program instructions can also be stored in a computer readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer readable memory produce an article of manufacture including instructions which implement the function specified in the flowchart block or blocks. Figure 1 one or more flow or blocks Figure 1 one or more flow or blocks

[0161] The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 one or more flow or blocks Figure 1 one or more flow or blocks

[0162] The above-described specific embodiments are merely intended to further describe and explain the purpose, technical solutions and beneficial effects of the present application, and should be understood that the above-described specific embodiments are merely specific embodiments of the present application, and are not used to limit the protection scope of the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for optimizing ranging error of a track detection system, characterized in that, The method comprises the following steps: determining a theoretical sampling pulse number of a track detection system ranging; The theoretical sampling pulse number represents a first distance pulse number value generated by an encoder when a track moving equipment theoretically travels a space sampling interval, and the theoretical sampling pulse number is a decimal number; the track detection system is used for dynamically detecting track smoothness and is installed on the track moving equipment; determining two positive integers adjacent to the theoretical sampling pulse number according to the theoretical sampling pulse number; constructing a space sampling pulse dynamic comparison value array according to the two positive integers and the theoretical sampling pulse number according to a pre-established ping-pong algorithm; the ping-pong algorithm is used for: determining a weight coefficient ratio value and a total number of elements in the space sampling pulse dynamic comparison value array according to the two positive integers and the theoretical sampling pulse number; constructing the space sampling pulse dynamic comparison value array by using the two positive integers, the weight coefficient ratio value and the total number of elements; each element in the space sampling pulse dynamic comparison value array is the two positive integers adjacent to the theoretical sampling pulse number, a sum of each element in the space sampling pulse dynamic comparison value array is approximately equal to or equal to the theoretical sampling pulse number, and each element in the space sampling pulse dynamic comparison value array is sorted according to a minimum cumulative error; the cumulative error represents a sum of differences between each element in the space sampling pulse dynamic comparison value array and the theoretical sampling pulse number; obtaining a second distance pulse number generated by the encoder when a plurality of actual track moving equipment travels a sampling distance interval; sequentially replacing each first number of second distance pulse numbers by elements in the space sampling pulse dynamic comparison value array to obtain updated second distance pulse numbers; the first number is equal to the total number of elements in the space sampling pulse dynamic comparison value array; wherein the two positive integers adjacent to the theoretical sampling pulse number are determined according to the theoretical sampling pulse number, comprising: According to the theoretical sampling pulse number, two positive integers adjacent to the theoretical sampling pulse number are determined according to the following formula a , b : wherein trunc represents a truncation process, Δ x is a sampling distance interval, D is a track mobile equipment wheel diameter, N is a number of distance pulses generated by an encoder during one revolution of the track mobile equipment wheel diameter.

2. The method of claim 1, wherein, determining the weight coefficient ratio value and the total number of elements in the space sampling pulse dynamic comparison value array according to the two positive integers and the theoretical sampling pulse number, comprising: establishing a target optimization function y: y = x + p a x + q b x + q In the formula p, q are weight coefficients; By mathematical statistics method, the weight coefficient ratio value when y converges to the theoretical sampling pulse number is determined p / q ; According to the weight coefficient ratio p / q The total number of elements in the spatial sampling pulse dynamic comparison value array is determined.

3. The method of claim 1, wherein, determining the weight coefficient ratio value and the total number of elements in the space sampling pulse dynamic comparison value array according to the two positive integers and the theoretical sampling pulse number, comprising: The weight coefficient ratio is determined according to the two positive integers and the theoretical sampling pulse number according to the following formula p / q : In the formula, m is the number of theoretical sampling pulses.

4. The method of claim 1, wherein, constructing the space sampling pulse dynamic comparison value array by using the two positive integers, the weight coefficient ratio value and the total number of elements, comprising: Calculate the two positive integers respectively a , b The absolute value of the difference between the theoretical number of sampling pulses and the actual number of sampling pulses. m - a |、| m - b | The positive integer corresponding to the smaller difference a The first element is determined as the first element in the array of dynamic comparison values ​​of spatial sampling pulses; the difference between the first element and the theoretical number of sampling pulses is... m - a Updated to cumulative error SUME; m is the theoretical number of sampling pulses; cyclically processing in the following manner until a last element in the space sampling pulse dynamic comparison value array is determined: calculating the difference between the two positive integers a , b and the theoretical number of sampling pulses m - a , m - b ; Calculate the cumulative error SUME and the difference value m - a 、 m - b the absolute value of the difference |SUME+ m - a |, |SUME+ m - b |; The absolute value of the difference |SUME+ m - a |、|SUME+ m - b The positive integer corresponding to the smaller difference is determined as the second element in the spatial sampling pulse dynamic comparison value array, and the absolute value of the difference is |SUME+ m - a | Assign the cumulative error SUME.

5. A track detection system range error optimization device, characterized in that, comprising: a theoretical sampling pulse number determination module, configured to determine a theoretical sampling pulse number of a track detection system ranging; The theoretical sampling pulse number represents a first distance pulse number value generated by an encoder when a track moving equipment theoretically travels a space sampling interval, and the theoretical sampling pulse number is a decimal number; the track detection system is used for dynamically detecting track smoothness and is installed on the track moving equipment; The array establishing module is configured to determine two positive integers adjacent to the theoretical sampling pulse number according to the theoretical sampling pulse number, and construct a space sampling pulse dynamic comparison value array according to the two positive integers and the theoretical sampling pulse number according to a pre-established ping-pong algorithm; the ping-pong algorithm is configured to determine a weight coefficient ratio and a total number of elements of the space sampling pulse dynamic comparison value array according to the two positive integers and the theoretical sampling pulse number, and construct the space sampling pulse dynamic comparison value array by using the two positive integers, the weight coefficient ratio and the total number of elements; each element in the space sampling pulse dynamic comparison value array is the two positive integers adjacent to the theoretical sampling pulse number, a sum of each element in the space sampling pulse dynamic comparison value array approximates or equals the theoretical sampling pulse number, each element in the space sampling pulse dynamic comparison value array is sorted according to a minimum cumulative error, and the cumulative error represents a sum of differences between each element in the space sampling pulse dynamic comparison value array and the theoretical sampling pulse number; The error optimization processing module is configured to acquire a second distance pulse number generated by an encoder when a plurality of actual track moving equipment running sampling distance intervals; The plurality of second distance pulse numbers are sorted according to a track moving equipment running route, and each first number of second distance pulse numbers are replaced by elements in the space sampling pulse dynamic comparison value array in sequence to obtain updated plurality of second distance pulse numbers; the first number is equal to the total number of elements in the space sampling pulse dynamic comparison value array; The array establishing module is configured to: According to the theoretical sampling pulse number, two positive integers adjacent to the theoretical sampling pulse number are determined according to the following formula a , b : wherein trunc represents a truncation process, Δ x is a sampling distance interval, D is a track mobile equipment wheel diameter, N is a number of distance pulses generated by an encoder during one revolution of the track mobile equipment wheel diameter.

6. The apparatus of claim 5, wherein, The array establishing module is configured to: Establish a target optimization function y: y = x + p a x + q b x - q In the formula p, q are weight coefficients; By mathematical statistics method, the weight coefficient ratio value when y converges to the theoretical sampling pulse number is determined p / q ; According to the weight coefficient ratio p / q The total number of elements in the spatial sampling pulse dynamic comparison value array is determined.

7. The apparatus of claim 5, wherein, The array establishing module is configured to: The weight coefficient ratio is determined according to the two positive integers and the theoretical sampling pulse number according to the following formula p / q : In the formula, m is the number of theoretical sampling pulses.

8. The apparatus of claim 5, wherein, The array establishing module is configured to: Calculate the absolute value of the difference between two positive integers a , b and the theoretical sampling pulse number m - a |、| m - b |, the smaller difference corresponds to the first element in the space sampling pulse dynamic comparison value array; the difference a between the first element and the theoretical sampling pulse number m - a is updated to the cumulative error SUME; m is the theoretical sampling pulse number; The last element in the space sampling pulse dynamic comparison value array is determined by the following loop processing: calculating the difference between the two positive integers a , b the difference between the theoretical number of sampling pulses m - a , m - b ;​​ Calculate the cumulative error SUME and the difference value m - a 、 m - b the absolute value of the difference |SUME+ m - a |SUME+ m - b |; the absolute value of the difference |SUME m - a the absolute value of the difference |SUME m - b the absolute value of the difference |SUME m - a the absolute value of the difference |SUME 9. 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 executes the computer program to implement the method of any one of claims 1 to 4.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, and the computer program is executed by the processor to implement the method of any one of claims 1 to 4.

11. A computer program product, characterised in that, The computer program product includes a computer program, and the computer program is executed by the processor to implement the method of any one of claims 1 to 4.

Images