Optimization design method and device for track floating slab ballast

Abstract

The present invention provides a method and device for optimizing the design of a track floating plate track bed. The method includes the steps of aligning the time domain signal data of multiple detection devices, performing spectrum analysis on the aligned track bed vibration acceleration signal data, and optimizing the design of the floating plate track bed according to the spectrum analysis results. Since the characteristic points in the time domain signal are matched with the event of a specific train structure passing through the detection device, and the data alignment is achieved in combination with the predetermined distance between each detection device, automatic data alignment can be achieved. Furthermore, the natural frequency of the floating plate track bed can be obtained according to the spectrum analysis results of the aligned track bed vibration acceleration signal data. After calculating the difference between the natural frequency and the ideal frequency, the mass of the floating plate track bed and / or the stiffness and geometric dimensions of the elastic unit of the vibration isolator therein can be optimized according to the difference, thereby achieving a more accurate and intelligent optimization design of the vibration reduction performance of the floating plate track bed.

Description

Technical Field

[0001] The invention belongs to the technical field of track structure design, and in particular relates to a method and a device for optimizing the design of a track floating plate ballast. Background Art

[0002] With the increase in the density of urban subway lines and the increase in vibration-sensitive points such as buildings, precision instruments and equipment on urban subway lines, the proportion of subway vibration-reducing tracks has also increased significantly. There are many types of vibration-reducing tracks, among which the most commonly used type is a floating plate track on a lower foundation with multiple vibration isolators. The vibration isolators are equipped with elastic units to absorb the impact energy generated by the train passing on the track through multiple elastic units to achieve a vibration reduction effect. In the actual track structure, due to installation errors, component wear after a period of use, and the restraint of the rails on the track, the actual vibration reduction performance of the floating plate track often deviates from the ideal performance (design performance). If the deviation can be corrected, it will have better vibration reduction performance and less impact on surrounding buildings.

[0003] With the development of track detection related technologies, a variety of sensors are currently being deployed on the track to collect multiple detection data during the actual operation of the track. Based on these detection data, the vibration reduction performance of the floating plate track bed should be optimized. However, there is still a lack of such an automated method. The multi-source detection data is mainly collected, processed and analyzed manually, and then the track designers make some optimization designs by comprehensively considering the functional requirements and mechanical performance requirements of the floating plate track bed. The efficiency is very low, and it is difficult to ensure that the optimized design can achieve the ideal vibration reduction performance. It is still necessary to use the limited downtime maintenance time for testing and verification, and then improve the optimization design. If the above detection data is to be used to realize the intelligent optimization of the vibration reduction performance of the floating plate track bed, there are still many difficulties: on the one hand, due to the differences in the installation positions of the sensors and the system time differences of different data acquisition instruments, the collected data has time deviations, which brings difficulties to the subsequent data processing and analysis. In addition, due to the fact that most sensors are passive acquisition mode sensors and the number of sensors is very large, some existing time synchronization methods are also not applicable. Therefore, there is no method that can automatically realize the time domain alignment of track detection data. On the other hand, when optimizing the design, it is necessary not only to consider the vibration reduction performance, but also to ensure other normal functions and mechanical properties of the floating slab track bed. Moreover, there are many factors that affect its vibration reduction performance, and it is difficult to obtain an optimized design by simply processing the corresponding sensor data. Summary of the invention

[0004] The present invention is made to solve the above problems, and aims to provide an optimization design method for a floating plate track bed that can realize automatic and intelligent optimization design according to track detection data, and a device using the method. The present invention adopts the following technical solutions:

[0005] The present invention provides a method for optimizing the design of a floating plate track bed, which is used for optimizing the design of a floating plate track bed having a plurality of vibration isolators, wherein the vibration isolators include elastic units. The method has the following technical features, and comprises the following steps: step S1, searching for predetermined feature points in the time domain signal data of a plurality of detection devices in the track and obtaining the time points thereof, and performing time domain alignment on the time domain signal data of the plurality of detection devices according to the correspondence between the feature points and the train structure and the predetermined distance between the plurality of detection devices, wherein the detection device comprises a vibration acceleration detection device, which is at least used for detecting the vibration acceleration of the floating plate track bed to obtain corresponding track bed vibration acceleration signal data; step S2, performing spectrum analysis on the aligned track bed vibration acceleration signal data, and calculating at least the free attenuation frequency and the natural frequency of the floating plate track bed according to the spectrum analysis result; and step S3, optimizing the stiffness of the elastic unit, the geometric dimensions of the elastic unit and / or the mass of the floating plate track bed according to the difference between the natural frequency of the floating plate track bed and the predetermined ideal natural frequency of the floating plate track bed.

[0006] The track floating plate track bed optimization design method provided by the present invention may also have such a technical feature, wherein step S2 includes the following sub-steps: step S2-1, performing fast Fourier transform analysis on the track bed vibration acceleration signal data, extracting the spectrum of the vibration signal, and identifying the main vibration frequency components; step S2-2, simplifying the floating plate track bed into a mass-spring-damping system, calculating the free decay frequency of the system according to the extracted frequency of the vibration signal and the main vibration frequency components, as the free decay frequency of the floating plate track bed; step S2-3, calculating the natural frequency of the floating plate track bed according to the free decay vibration frequency of the floating plate track bed.

[0007] The track floating plate ballast optimization design method provided by the present invention may also have such a technical feature, wherein the free vibration equation of the mass-spring-damper system is:

[0008]

[0009] In the formula, m is the equivalent mass of the floating slab ballast, c is the damping coefficient of the floating slab ballast, kis the equivalent stiffness of the floating slab ballast, and the stiffness of the elastic element is used to solve the free vibration equation to obtain the free attenuation frequency:

[0010]

[0011] The natural frequency is calculated according to the following formula:

[0012]

[0013] Where 𝜉 is the damping coefficient of the floating slab ballast.

[0014] The track floating plate ballast optimization design method provided by the present invention may also have such a technical feature, wherein step S3 includes the following sub-steps: step S3-1, calculating the difference between the natural frequency and the ideal natural frequency; step S3-2, judging in which of a plurality of predetermined threshold ranges the difference is; step S3-3, when it is judged in step S3-2 that it is less than a predetermined first threshold, calculating the quality optimization value of the floating plate ballast according to the difference and the current quality of the floating plate ballast; step S3-4, outputting the quality optimization value obtained in step S3-3; step S3-5, when it is judged in step S3-2 that the difference is between the first threshold and a predetermined second threshold, calculating the elastic modulus optimization value of the elastic unit according to the difference and the current elastic modulus of the elastic unit; step S3-6, according to the elastic modulus obtained in step S3-5 The step S3-7 outputs the information of the optimized rubber material obtained in step S3-6. The step S3-8 calculates the elastic modulus optimization value and the geometrical dimension optimization value of the elastic unit according to the difference, the current elastic modulus of the elastic unit, the current geometrical dimension of the elastic unit and the predetermined corresponding weight coefficient when it is judged in step S3-2 that the difference is between the second threshold value and the predetermined third threshold value. The step S3-9 obtains the information of the optimized rubber material according to the elastic modulus optimization value obtained in step S3-8 and the predetermined corresponding relationship between the elastic modulus and the rubber material. The step S3-10 outputs the information of the optimized rubber material obtained in step S3-9 and the geometrical dimension optimization value obtained in step S3-8.

[0015] The track floating plate ballast optimization design method provided by the present invention may also have such a technical feature, wherein step S3 also includes: step S3-11, when it is judged in step S3-2 that the difference is greater than the third threshold value, the elastic modulus optimization value, the geometric dimension optimization value, and the mass optimization value of the floating plate ballast of the elastic unit are calculated according to the difference, the current elastic modulus of the elastic unit, the current geometric dimension of the elastic unit, the current mass of the floating plate ballast and the predetermined corresponding weight coefficient; step S3-12, according to the elastic modulus optimization value obtained in step S3-11 and the predetermined correspondence between each elastic modulus and the rubber material, the information of the optimized rubber material is obtained; step S3-13, outputting the information of the optimized rubber material obtained in step S3-12, the geometric dimension optimization value of the elastic unit obtained in step S3-11, and the mass optimization value of the floating plate ballast.

[0016] The track floating plate track bed optimization design method provided by the present invention may also have such technical features, wherein step S2 also includes: step S2-4, obtaining the vibration attenuation rate of the floating plate track bed according to the frequency spectrum of the vibration signal, and the track floating plate track bed optimization design method also includes: step S4, optimizing the damping of the floating plate track bed according to the difference between the vibration attenuation rate of the floating plate track bed and the predetermined ideal vibration attenuation rate of the floating plate track bed.

[0017] The track floating plate ballast optimization design method provided by the present invention may also have such a technical feature, wherein the optimized value of the damping coefficient of the elastic unit is calculated based on the difference between the vibration attenuation rate and the ideal vibration attenuation rate and the current damping ratio of the floating plate ballast, and the information on optimizing the rubber material is obtained based on the corresponding relationship between each damping coefficient and the rubber material.

[0018] The track floating plate track bed optimization design method provided by the present invention may also have such a technical feature, wherein step S1 includes the following sub-steps: step S1-1, pre-processing the original signal data of multiple detection devices to obtain the corresponding time domain signal data; step S1-2, using one of the multiple detection devices as a reference detection device, and searching for predetermined feature points and their corresponding time points corresponding to the characteristic structure of the train in the time domain signal data of the reference detection device; step S1-3, calculating the time difference between two adjacent feature points to obtain a feature point time difference array; step S1-4, based on the feature point time difference array, calculating the cross-correlation coefficients between multiple groups of feature points through a cross-correlation algorithm to obtain a cross-correlation array; step S1-5, searching for the maximum value position in the cross-correlation array, and obtaining the time point corresponding to the maximum value position as as a reference time point to determine the best alignment point between the time domain signal data collected by different detection devices; step S1-6, calculating the train speed according to the size of the characteristic structure of the train and the time difference between the characteristic points generated by the characteristic structure passing through the reference detection device; step S1-7, calculating the passing time of the characteristic structure of the train through the predetermined distance between the reference detection device and the detection device to be aligned and the train speed; step S1-8, calculating the time shift of the time domain signal data of the detection device to be aligned relative to the time domain signal data of the reference detection device according to the passing time and the reference time point; and step S1-9, performing time domain shift on the time domain signal data of each detection device to be aligned according to the corresponding time shift, so as to obtain aligned data.

[0019] The track floating plate ballast optimization design method provided by the present invention may also have such technical features, wherein the multiple detection devices also include a load detection device, which is arranged under the steel rails of the track and is used to detect the load of the track, the reference detection device is the load detection device, and the vibration acceleration detection device includes a plurality of vibration acceleration sensors, wherein one or more of the vibration acceleration sensors are arranged in the middle of the upper surface of the floating plate ballast and are used to obtain the vibration acceleration signal data of the ballast.

[0020] The present invention provides a track floating plate ballast optimization design device, which is used for optimizing the design of a floating plate ballast with multiple vibration isolators, wherein the vibration isolators include elastic units. The device has the following technical features: a signal data acquisition unit, which is used to acquire time domain signal data collected by multiple detection devices in the track, wherein the detection devices include vibration acceleration detection devices, which are at least used to detect the vibration acceleration of the floating plate ballast to obtain corresponding ballast vibration acceleration signal data; a signal data alignment processing unit, which is used to find predetermined feature points in the time domain signal data of multiple detection devices and obtain their time points, And according to the correspondence between the characteristic points and the train structure and the predetermined distance between the multiple detection devices, the time domain signal data of the multiple detection devices are aligned in time domain; a vibration signal analysis unit is used to perform spectrum analysis on the aligned roadbed vibration acceleration signal data, and at least calculate the free attenuation frequency and natural frequency of the floating plate roadbed according to the spectrum analysis result; and a natural frequency optimization processing unit is used to optimize the stiffness of the elastic unit and / or the mass of the floating plate roadbed according to the difference between the natural frequency of the floating plate roadbed and the predetermined ideal natural frequency of the floating plate roadbed.

[0021] The invention has the following functions and effects.

[0022] According to the method and device for optimizing the design of the track floating plate track bed provided by the present invention, the method includes the steps of aligning the time domain signal data of multiple detection devices, performing spectrum analysis on the aligned track bed vibration acceleration signal data, and optimizing the design of the floating plate track bed according to the spectrum analysis results. Among them, since the characteristic points in the time domain signal are matched with the event that the specific structure of the train passes through the detection device, and the time domain signal alignment is achieved in combination with the predetermined distance between the detection devices, the automatic time domain alignment of the detection data can be achieved, and no manual operation is required to achieve the data time domain alignment, the alignment accuracy is higher, and a lot of manpower and time can be saved. Further, the natural frequency of the floating plate track bed can be obtained according to the spectrum analysis results of the aligned track bed vibration acceleration signal data. After calculating the difference between the natural frequency and the ideal frequency, the mass of the floating plate track bed and / or the stiffness and geometric dimensions (parameters related to the natural frequency) of the vibration isolator elastic unit can be optimized according to the difference, so that the vibration reduction performance optimization design of the floating plate track bed with higher accuracy and more intelligence can be achieved, and the burden of track designers can be greatly reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 is a flow chart of a method for optimizing the design of a track floating plate ballast in an embodiment of the present invention;

[0024] Figure 2is a top view of a track system in an embodiment of the present invention;

[0025] Figure 3 is a cross-sectional view of a track system in an embodiment of the present invention;

[0026] Figure 4 is a schematic diagram of the structure of a train in an embodiment of the present invention;

[0027] Figure 5 is a structural schematic diagram of a vibration isolator detection device in an embodiment of the present invention;

[0028] Figure 6 is a structural diagram of a fixed tooling and a distance measuring sensor in an embodiment of the present invention;

[0029] Figure 7 is an installation position diagram of a load detection device in an embodiment of the present invention;

[0030] Figure 8 is a structural exploded view of a load detection device in an embodiment of the present invention;

[0031] Fig. 9 is a flow chart of step S1 in an embodiment of the present invention;

[0032] Fig.10 is a flowchart of step S1-1 in an embodiment of the present invention;

[0033] Fig.11 is a flow chart of step S2 in an embodiment of the present invention;

[0034] Fig.12 is a flow chart of step S3 in an embodiment of the present invention;

[0035] Fig.13 It is a logic block diagram of a track floating plate ballast optimization design device in an embodiment of the present invention.

[0036] Reference numerals:

[0037] Track system 1000; vibration isolator detection device 100; fixing tool 10; base plate 11; flat plate portion 111; clearance notch 1112; fitting protrusion 112; fixing protrusion 113; first sensor bracket 121; first fixing plate portion 1211; first mounting plate portion 1212; second sensor bracket 122; second fixing plate portion 1221; second mounting plate portion 1222; positioning assembly 13; positioning member 131; mounting hole 1131; first distance measuring sensor 21; second distance measuring sensor 22; power supply unit 30; data acquisition instrument 40; load detection device 200; loading pad 211; sensor fixing plate 212; load sensor 213; cable 214; load transfer column 215; base plate 216; fixing hole 2161; spike mounting hole 2162; fixing plate fastening screw 217; base fixing screw 218; spike 22 1; vibration acceleration detection device 300; rail vibration acceleration sensor 310; ballast vibration acceleration sensor 320; foundation vibration acceleration sensor 330; rail displacement detection device 400; track floating plate ballast optimization design device 700; signal data acquisition unit 710; signal data alignment processing unit 720; vibration signal analysis unit 730; natural frequency optimization processing unit 740; vibration attenuation speed optimization processing unit 750; optimization device communication unit 760; device control unit 770; train 800; carriage 810; bogie 820; wheelset 822; wheel 8221; axle 8222; track 900; lower foundation 910; floating track plate 920; vibration isolator 930; sleeve 931; elastic element 932; unit support plate 933; short rail sleeper 940; rail 950; rail pad 960; track fastener 970. DETAILED DESCRIPTION

[0038] In order to make the technical means, creative features, objectives and effects achieved by the present invention easy to understand, the track floating plate track bed optimization design method and device of the present invention are specifically described below in combination with embodiments and drawings.

[0039] Figure 1 It is a flow chart of the track floating plate ballast optimization design method in this embodiment.

[0040] like Figure 1 As shown, the method comprises the following steps:

[0041] Step S1, searching for predetermined feature points in the time domain signal data of multiple detection devices and obtaining their time points, and performing time domain alignment on the time domain signal data of the multiple detection devices according to the corresponding relationship between the feature points and the train structure and the predetermined distance between the multiple detection devices, wherein the detection device includes a vibration acceleration detection device, which is at least used to detect the vibration acceleration of the roadbed to obtain corresponding roadbed vibration acceleration signal data.

[0042] Step S2, performing spectrum analysis on the aligned ballast vibration acceleration signal data, and calculating the free attenuation frequency, natural frequency and vibration attenuation speed of the floating slab ballast according to the spectrum analysis results.

[0043] Step S3, optimizing the stiffness, geometric dimensions and / or mass of the elastic unit of the vibration isolator according to the difference between the natural frequency of the floating slab track bed and the predetermined ideal natural frequency of the floating slab track bed.

[0044] Step S4, optimizing the damping of the elastic unit of the vibration isolator according to the difference between the vibration attenuation speed of the floating slab ballast and the predetermined ideal vibration attenuation speed of the floating slab ballast.

[0045] In order to better illustrate the present method, the algorithm flow of the present method will be specifically described below by way of example in combination with an actual track structure.

[0046] Figure 2 is a top view of the track system in this embodiment, Figure 3 is a cross-sectional view of the track system in this embodiment.

[0047] like Figure 2 and Figure 3 As shown, taking a track arranged in a circular tunnel as an example, the track system 1000 includes a track 900, a vibration isolator detection device 100, a load detection device 200, a vibration acceleration detection device 300, and a rail displacement detection device 400.

[0048] The track 900 includes a lower foundation 910 , a plurality of floating track plates 920 , a plurality of vibration isolators 930 , a plurality of short sleepers 940 , and two steel rails 950 .

[0049] The lower foundation 910 is arranged at the bottom of the circular tunnel, and its upper surface is roughly flat. The floating track plate 920 is roughly in the shape of a rectangular plate as a whole, and is a precast concrete plate. Multiple floating track plates 920 are connected end to end and arranged in sequence along the tunnel. The short sleepers 940 are concrete short sleepers, which are arranged on the upper surface of the floating track plate 920 to form two rows, and the multiple short sleepers 940 in each row are arranged at roughly equal intervals. The rails 950 are I-shaped rails, and the two rails 950 are respectively placed on the two rows of short sleepers 940 and fixed by rail fasteners arranged on the rectangular sleepers 940.

[0050] A plurality of vibration isolators 930 are embedded in the floating track plate 920 to form a floating track bed. The vibration isolator 930 includes a sleeve 931, an elastic element 932 and other mounting components pre-buried in the floating track plate 920. The elastic element 932 is arranged at the bottom of the sleeve 931, and the lower end of the elastic element 932 extends out of the sleeve 931 and abuts against the lower foundation 910. The vibration isolators 930 are distributed on both sides of the width direction of the floating track plate 920 to form two rows, and each vibration isolator 930 is located between two adjacent short sleepers 940 and is closer to one side edge of the floating track plate 920 in the width direction relative to the short sleepers 940. The floating track plate 920 is arranged on the lower foundation 910 through a plurality of vibration isolators 930, and there is a certain gap between the bottom surface of the floating track plate 920 and the upper surface of the lower foundation 910.

[0051] Optionally, an elastic pad for vibration isolation may be provided between the rail 950 and the short sleeper 940 .

[0052] In this embodiment, the size of the floating track plate 920 is 4710×2600×320mm (length×width×thickness). There are eight short sleepers 940 in a row on each floating track plate 920, and the distance between two adjacent short sleepers 940 is 595mm, which is the distance between two adjacent sets of track fasteners. There are four vibration isolators 930 in a row on each floating track plate 920, two of which are respectively arranged near the two side plate ends (two ends in the length direction) of the floating track plate 920, and the distance between two adjacent vibration isolators 930 is 1190mm. The elastic element 932 in the vibration isolator 930 is a rubber spring or includes a rubber spring.

[0053] Figure 4 is a schematic diagram of the structure of the train in this embodiment. In addition, Figure 3 The structure diagram of the train is also shown in FIG.

[0054] like Figure 3 and Figure 4 As shown, the train 800 includes multiple carriages 810 and multiple bogies 820. Multiple bogies 820 are arranged at the bottom of each carriage 810, and the bogies 820 include a support frame, a wheel pair 822, a spring device and a shock absorber, etc. The wheel pair 822 includes a wheel 8221 and an axle 8222.

[0055] In this embodiment, the train 800 has six carriages 810, and each carriage 810 has two bogies 820 at the bottom. The total length of the train is 118.8m, the vehicle fixed distance (the distance between two bogies at the bottom of a carriage) is 12.6m, and the wheelbase (the distance between two wheel pairs in a bogie, also called fixed wheelbase) is 2300mm.

[0056] Figure 5 is a schematic diagram of the structure of the vibration isolator detection device in this embodiment, Figure 6 is a structural diagram of the fixed tooling and the distance measuring sensor in this embodiment.

[0057] like Figure 5 As shown, the vibration isolator 930 also includes a unit support plate 933, which is a metal flat plate, embedded in the sleeve 931 and abutted against a circle of steps near the bottom of the sleeve 931, and the upper end of the elastic unit 932 abuts against the unit support plate 933. The edge of the unit support plate 933 has a plurality of arc-shaped notches. The diameter of the elastic element 932 is smaller than the inner diameter of the sleeve 931, and is arranged approximately coaxially with the sleeve 931.

[0058] The elastic element 932 may be a rubber spring, or a unit including a rubber spring, for example, an upper shell and a lower shell that fit together and can move relative to each other, and the rubber spring is accommodated in a cavity formed by the fitting of the upper shell and the lower shell, and its two ends are respectively in contact with the upper and lower shells. The elastic element 932 may further include a fixing component for fixing the two ends of the rubber spring, a spring limiting component, etc., and may specifically adopt an elastic element structure in the prior art.

[0059] The vibration isolator detection device 100 is disposed in the vibration isolator 930 and is used to detect the dynamic deformation of the elastic element 932 (rubber spring). Figure 5 and Figure 6 As shown, the vibration isolator detection device 100 includes a fixing device 10 , a plurality of first distance measuring sensors 21 , a plurality of second distance measuring sensors 22 , corresponding power supply units 30 and a data acquisition device 40 .

[0060] The fixing tool 10 includes a base plate 11 , a plurality of first sensor brackets 121 , a plurality of second sensor brackets 122 , and a positioning assembly 13 .

[0061] The base plate 11 includes a disc-shaped flat plate portion 111, a plurality of engaging protrusions 112 formed on the edge of the flat plate portion 111, and a plurality of fixing protrusions 113, wherein the fixing protrusions 113 have mounting holes 1131. The edge of the flat plate portion 111 also has a plurality of clearance notches 1112.

[0062] The first sensor bracket 121 is L-shaped as a whole, and has a first fixing plate portion 1211 and a first mounting plate portion 1212 which are perpendicular to each other. The first fixing plate portion 1211 is fixedly mounted on the base plate 11, and the first mounting plate portion 1212 is vertically located above the base plate 11 and next to a clearance notch 1112. The first distance measuring sensor 21 is mounted on the outer end of the first mounting plate portion 1212, with its detection end facing downward, and can detect the distance from the sensor to the unit support plate 933 through the clearance notch 1112.

[0063] The structure of the second sensor bracket 122 is substantially the same as that of the first sensor bracket 121, and it has a second fixing plate portion 1221 and a second mounting plate portion 1222 which are perpendicular to each other. The second fixing plate portion 1221 is fixedly mounted on the base plate 11, and the second mounting plate portion 1222 vertically extends from the outside of the base plate 11 to the bottom of the base plate 11. The second distance measuring sensor 22 is mounted on the outer end of the second mounting plate portion 1222, with its detection end facing downward, and can detect the distance from the sensor to the lower foundation through the corresponding arc-shaped notch on the unit support plate 933.

[0064] In this embodiment, the first distance measuring sensor 21 and the second distance measuring sensor 22 are both laser distance measuring sensors.

[0065] The positioning assembly 13 includes a plurality of thin rod-shaped positioning members 131, which are respectively inserted into a plurality of corresponding mounting holes on the base plate 11, and the mounting positions of the positioning members 131 in the corresponding mounting holes are adjustable. When installing the base plate 11, the plurality of positioning members 131 can be used to keep the surface direction of the base plate 11 perpendicular to the axial direction of the sleeve, and the leveling of the base plate 11 can be further achieved by adjusting the positioning members 131.

[0066] like Figure 2 As shown, in this embodiment, the eight vibration isolators 930 in a floating track bed slab 920 are all provided with vibration isolator detection devices 100. Optionally, the two vibration isolators 930 at the plate ends of an adjacent floating track bed slab 920 are also provided with vibration isolator detection devices 100.

[0067] Figure 7 2 is an installation position diagram of the load detection device in this embodiment.

[0068] like Figure 7 As shown, the overall shape of the load detection device 200 is consistent with the track iron pad, and it is installed in the track structure instead of the track iron pad, specifically between the short sleeper 940 and the rail 950. When the rail pad 960 is provided, it is located between the short sleeper 940 and the rail pad 960. The rail fastener 970 is fixed on the load detection device 200.

[0069] Figure 8 It is a structural exploded view of the load detection device in this embodiment.

[0070] like Figure 8 As shown, the load detection device 200 includes a loading pad 211, a sensor fixing plate 212, a plurality of load sensors 213 and their cables 214, a plurality of load transfer columns 215, a base plate 216, a plurality of fixing plate fastening screws 217, a plurality of base fixing screws 218, and also includes a corresponding data acquisition instrument (not shown in the figure).

[0071] Among them, the lower surface of the loading pad 211 and the upper surface of the sensor fixing plate 212 have correspondingly arranged multiple sensor fixing grooves and wiring grooves. After being assembled, corresponding accommodating cavities and wiring channels are formed. Multiple load sensors 213 are respectively embedded in each accommodating cavity, and a load transfer column 215 is arranged at the bottom. Its cables 214 are gathered together through the wiring channel and led out from one side of the entire device. According to the distribution of the accommodating cavities, multiple load sensors 213 form two rows, which are respectively located below the two sides of the rail 950.

[0072] The base plate 216 has a plurality of fixing holes 2161 and a pair of spike mounting holes 2162 . The loading pad 211 , the sensor fixing plate 212 , and the base plate 216 are stacked and assembled and fixed on the short rail sleeper 940 through a plurality of spikes 221 .

[0073] The load sensor 213 may be a pressure sensor or a piezoelectric sensor. In this embodiment, it is a pressure sensor. There are six load sensors 213 in one device, forming two rows, with three in each row.

[0074] like Figure 2 As shown, in this embodiment, a load detection device 200 is provided at each short sleeper 940 on a floating track plate 920 .

[0075] like Figure 2 and Figure 3 As shown, there are two vibration acceleration detection devices 300, which are respectively arranged in the plate (middle in the length direction) of the floating track plate 920, and are respectively located on both sides (both sides in the width direction) of the floating track plate 920. The vibration acceleration detection device 300 includes a rail vibration acceleration sensor 310, a roadbed vibration acceleration sensor 320, and a foundation (tunnel wall) vibration acceleration sensor 330, which are respectively used to collect vibration acceleration data at predetermined positions above the rail 950, the floating track plate 920, and the lower foundation 910, and also includes a corresponding data acquisition instrument (not shown in the figure).

[0076] The rail vibration acceleration sensor 310 is installed at the outer rail web of the rail 950 or on the outer rail bottom.

[0077] The track bed vibration acceleration sensor 320 is installed on the upper surface of the floating track plate 920 and is located at the edge in the width direction thereof.

[0078] The foundation vibration acceleration sensor 330 is installed on the tunnel wall above the lower foundation 910.

[0079] like Figure 2 and Figure 3As shown, there are two rail displacement detection devices 400, which are also respectively arranged in the middle of the floating track plate 920 and are relatively close to both sides of the floating track plate 920. The rail displacement detection device 400 includes a rail displacement ranging sensor and a corresponding data acquisition instrument. The rail displacement ranging sensor is arranged on the upper surface of the floating track plate 920 and is located directly below the rail 950. Its detection end faces upward to the bottom surface of the rail 950, and is used to detect the displacement of the rail in the middle of the plate.

[0080] The method of the present invention will be described in detail below in conjunction with the above-mentioned track system 1000.

[0081] Step S1, searching for predetermined feature points in the time domain signal data of multiple detection devices and obtaining their time points, and performing time domain alignment on the time domain signal data of multiple detection devices according to the correspondence between the feature points and the train structure and the predetermined distance between the multiple detection devices.

[0082] The plurality of detection devices at least include a vibration acceleration detection device, which is at least used to detect the vibration acceleration of the floating plate track bed to obtain corresponding track bed vibration acceleration signal data. Optionally, the detection device may further include the other detection devices mentioned above.

[0083] Fig. 9 is a flow chart of step S1 in this embodiment.

[0084] like Fig. 9 As shown, step S1 specifically includes the following sub-steps:

[0085] Step S1 - 1 , performing corresponding preprocessing on the original signal data collected by multiple detection devices to obtain corresponding time domain signal data.

[0086] Fig.10 is a flowchart of step S1-1 in this embodiment.

[0087] like Fig.10 As shown, for the load signal data of the track collected by the load detection device 200, step S1-1 includes the following sub-steps.

[0088] Step SA1, downloading load signal data from a data acquisition instrument corresponding to the load detection device.

[0089] Step SA2: preview the load signal data.

[0090] Step SA3, smoothing the load signal data, wherein a low-pass filter or a moving average smoothing algorithm may be used to smooth the data to reduce noise.

[0091] Step SA4, performing data cleaning on the smoothed load signal data, including removing abnormal values ​​therein.

[0092] Step SA5, reset the cleaned load signal data to zero, wherein the load signal data is a time domain signal (time history curve), whose two axes are time and load value, respectively. By translating the time history curve as a whole along the axis of the load value, the load value of the time history curve is made to be 0 when the train does not pass through the load detection device, thereby eliminating the influence of the train passing on the installation status of the load detection device.

[0093] For the elastic element distance signal data collected by the vibration isolator detection device 100 , step S1 includes the following sub-steps.

[0094] Step SB1, downloading elastic element distance signal data, which is electrical signal data, from a data acquisition instrument corresponding to the vibration isolator detection device.

[0095] Step SB2, performing conversion calculation on the elastic element distance signal data of the electrical signal data to convert it into digital signal data.

[0096] Step SB3, previewing the elastic element distance signal data of the digital signal data.

[0097] Step SB4, smoothing the elastic element distance signal data.

[0098] Step SB5, cleaning the smoothed elastic element distance signal data, including removing abnormal values ​​therein.

[0099] Step SB6, returning the distance signal data of the cleaned elastic element to zero.

[0100] The specific operations of step SB3 to step SB6 are substantially the same as those of the above-mentioned step SA2 to step SA5, and thus will not be described again. The corresponding steps of the following other detection devices are also the same.

[0101] For the rail displacement distance signal data collected by the rail displacement detection device 400, step S1 includes the following sub-steps.

[0102] Step SC1, downloading rail displacement distance signal data, which is electrical signal data, from a data acquisition instrument corresponding to the rail displacement detection device.

[0103] Step SC2, converting and calculating the rail displacement distance signal data of the electrical signal data to convert it into digital signal data.

[0104] Step SC3: previewing the rail displacement distance signal data of the digital signal data.

[0105] Step SC4, smoothing the rail displacement distance signal data.

[0106] Step SC5, cleaning the smoothed rail displacement distance signal data, including removing abnormal values ​​therein.

[0107] Step SC6, returning the displacement distance signal data of the cleaned rail to zero.

[0108] For the vibration acceleration signal data collected by the vibration acceleration detection device 300, step S1 includes the following sub-steps.

[0109] Step SD1, downloading vibration acceleration signal data from a data acquisition instrument corresponding to the vibration acceleration detection device.

[0110] Step SD2, previewing the vibration acceleration signal data.

[0111] Step S1-2, using one of the multiple detection devices as a reference detection device, searching for predetermined feature points corresponding to the characteristic structure of the train and their corresponding time points in the time domain signal data corresponding to the reference detection device.

[0112] In this embodiment, the load detection device 200 located in the middle of the floating track plate 920 (the middle in the length direction) is selected as the reference detection device, and its time domain signal data is also the load time history curve, and the peak and the corresponding coordinate (time point) are found in the curve.

[0113] In the middle of the floating plate, the load detection device 200 (pad device) is surrounded by other pad devices to bear the load together, so the middle of the plate is relatively stable. The load detection device 200 in the middle of the plate detects that there is little noise in the load signal data generated by the train passing through the track, and a group of peaks generated by the train passing through the load detection device 200 is very clear. At the end of the plate, the load detection device 200 only has other pad devices to bear the load on one side close to the middle of the plate, but not on the other side. Moreover, when the train passes through the end of the plate, the plate end will be warped under the force, that is, the position close to the middle of the plate sinks and the end of the plate is lifted. Therefore, there will be abnormal peaks in the collected data, and the overall waveform is also quite different from the waveform in the middle of the plate. Therefore, in order to conveniently and more accurately find the wave peak corresponding to the train bogie, and thus more accurately correspond the data points and time points in the collected signal data to the event of the train bogie passing through a specific detection device, the load detection device 200 in the middle of the plate is selected as the reference detection device in this embodiment. For the sake of ease of description, other detection devices are recorded as detection devices to be aligned.

[0114] Step S1-3, based on the found feature points, calculate the time difference between two adjacent feature points to obtain a feature point time difference array.

[0115] In this embodiment, based on the time point of the peak found, the time difference between two adjacent peaks is calculated to obtain the peak time difference array of each group of peaks. Peak time difference array = [peak 2 coordinate - peak 1 coordinate, peak 3 coordinate - peak 2 coordinate, peak 4 coordinate - peak 3 coordinate, ...].

[0116] Step S1-4, based on the feature point time difference array, calculate the cross-correlation coefficients between multiple groups of feature points through a cross-correlation algorithm to obtain a cross-correlation array.

[0117] Among them, firstly, a cross-correlation array is created to store the cross-correlation calculation results, and then the cross-correlation coefficients between multiple groups of peaks are calculated, wherein, for each possible lag value (the time lag of each group of peaks relative to the first group of peaks), the product sum of the overlapping parts of the group of peaks and the first group of peaks is calculated as the lag value, and the result of the lag value is stored in the cross-correlation array as the corresponding cross-correlation coefficient.

[0118] Step S1-5, searching for the maximum value position in the cross-correlation array, and obtaining the time point corresponding to the maximum value position as the reference time point, so as to determine the best alignment point between the signal data collected by different detection devices.

[0119] Step S1-6, calculating the train speed of the train according to the size of the characteristic structure of the train and the characteristic point time difference (peak time difference) between a group of characteristic points (peaks) generated by the characteristic structure of the train passing through the reference detection device.

[0120] The train speed is calculated based on the peak time difference between a group of wave peaks generated when the first bogie of the train passes through the reference detection device and the wheelbase of the train.

[0121] Step S1-7, calculating the time it takes for the characteristic structure (bogie) of the train to pass the predetermined distance according to the predetermined distance between the reference detection device and the detection device to be aligned and the train speed.

[0122] Step S1-8, calculate the time shift of the time domain signal data of the detection device to be aligned relative to the time domain signal data of the reference detection device based on the elapsed time and the reference time point, wherein the time shift = the distance between the detection device to be aligned and the reference detection device / train speed + the offset value of the reference time point relative to the coordinate origin.

[0123] Step S1-9, performing time domain shift on the time domain signal data of each detection device to be aligned according to the corresponding time shift amount, so as to obtain multi-source detection data after time domain alignment.

[0124] Step S2, performing spectrum analysis on the vibration acceleration signal data of the ballast bed, and calculating the free attenuation frequency, natural frequency and vibration attenuation speed of the floating plate ballast bed according to the spectrum analysis result.

[0125] Fig.11 is a flow chart of step S2 in this embodiment.

[0126] like Fig.11 As shown, step S2 specifically includes the following sub-steps:

[0127] Step S2-1, performing fast Fourier transform (FFT) analysis on the vibration acceleration signal data (time history curve) of the ballast bed, extracting the frequency spectrum of the vibration signal, and identifying the main vibration frequency components.

[0128] Step S2-2, simplifying the floating slab ballast into a mass-spring-damper system, and calculating the free decay frequency of the system according to the frequency of the extracted vibration signal and the main vibration frequency components as the free decay frequency of the floating slab ballast.

[0129] Among them, the free vibration equation of the mass-spring-damper system is:

[0130]

[0131] In the formula, m is the equivalent mass of the floating slab ballast, using the theoretical mass (design mass) of the floating slab ballast; c is the damping coefficient of the floating slab ballast; k The equivalent stiffness of the floating slab track bed is the stiffness of the elastic element (rubber spring).

[0132] By solving the above second-order ordinary differential equation, the free decay frequency of the mass-spring-damper system with relatively small damping can be obtained:

[0133]

[0134] Step S2-3, calculating the natural frequency of the floating slab ballast according to the free attenuation vibration frequency of the floating slab ballast.

[0135] The mass-spring-damper system is a single-degree-of-freedom vibration system. According to the theory of single-degree-of-freedom vibration system, for a small damping system, the free attenuation frequency is f d With natural frequency f n There is an approximate relationship between them, and the natural frequency of the floating slab track bed can be calculated according to the following formula:

[0136]

[0137] Where 𝜉 is the predetermined damping coefficient.

[0138] After testing multiple actual floating slab ballasts, through the above steps, the free attenuation frequency of the floating slab ballast within the vibration frequency range of 20Hz~30Hz is calculated to be 22.0Hz~26.8Hz based on the aligned multiple test data. Then, through the above steps, the first-order natural frequency of the floating slab ballast is calculated to be within the range of 10Hz~20Hz based on the stiffness of the rubber spring of its vibration isolator and the theoretical mass of the floating slab ballast.

[0139] Since the floating slab roadbed is actually subject to certain constraints from the rails, the natural frequency of the floating slab roadbed calculated based on the test data deviates to a certain extent from the ideal natural frequency of the floating slab roadbed under ideal conditions (about 12 Hz).

[0140] Step S2-4, the vibration attenuation rate of the floating plate track bed is obtained according to the frequency spectrum of the vibration signal. For example, the corresponding data points can be found in the vibration signal data according to the predetermined corresponding vibration amplitude threshold and their coordinates (time points) can be obtained, and then the vibration attenuation rate can be calculated according to the time difference.

[0141] Step S3, optimizing the stiffness, geometric dimensions and / or mass of the elastic unit of the vibration isolator according to the difference between the natural frequency of the floating slab track bed and the predetermined ideal natural frequency of the floating slab track bed.

[0142] Fig.12 is a flow chart of step S3 in this embodiment.

[0143] like Fig.12 As shown, when the difference is small, only the material of the rubber spring is optimized; when the difference is larger, the material and geometric dimensions of the rubber spring are optimized at the same time; when the difference is large, the material and geometric dimensions of the rubber spring, as well as the mass of the isolator (that is, the mass of the floating slab track bed) are optimized at the same time. Specifically, step S3 specifically includes the following sub-steps.

[0144] Step S3-1, calculating the difference between the natural frequency of the floating slab track bed and the predetermined ideal natural frequency △ f = f n - f i In the formula, f n is the natural frequency of the floating slab track bed, f i is the predetermined ideal natural frequency.

[0145] Step S3-2, determining whether the difference between the natural frequency of the floating slab track bed and the ideal natural frequency is within a plurality of predetermined threshold ranges.

[0146] In this embodiment, there are four threshold ranges: less than the first threshold, between the first threshold and the second threshold, between the second threshold and the third threshold, and greater than the third threshold. From the first threshold to the third threshold, the value gradually increases. The first threshold to the third threshold can be set according to the optional range of parameters such as the elastic modulus of the rubber spring, the geometric dimensions of the rubber spring, and the design quality of the floating plate track bed. The optional range means that when the parameter selects any value within the range, the floating plate track bed can maintain its normal function and other mechanical properties are also within an acceptable range.

[0147] Step S3-3, when it is determined in step S3-2 that the difference is less than the first threshold, the optimal value of the mass of the floating slab track bed is calculated according to the difference and the design mass of the floating slab track bed.

[0148] Step S3-4, outputting the optimized value of the quality of the floating slab track bed.

[0149] Optionally, after step S3-3, the number of counterweights and the mass of each counterweight set in each vibration isolator can be calculated based on the difference between the design mass of the floating slab track bed and the optimization value and the number of vibration isolators in the floating slab track bed. In step S3-4, the number and mass of the counterweights are also outputted at the same time.

[0150] Step S3-5, when it is determined in step S3-2 that the difference is between the first threshold and the second threshold, the optimized value of the elastic modulus of the elastic unit is calculated according to the difference and the current elastic modulus of the elastic unit.

[0151] Step S3-6, obtaining a rubber material satisfying the optimized value of the elastic modulus as the optimized rubber material according to the optimized value of the elastic modulus and the predetermined correspondence between each elastic modulus and the rubber material (eg, a correspondence table of the optimized value of the elastic modulus and rubber material information).

[0152] Step S3-7, outputting the information of the optimized rubber material, such as the model, elastic modulus and other information of the rubber material.

[0153] Step S3-8, when it is determined in step S3-2 that the difference is between the second threshold and the third threshold, the optimized value of the elastic modulus and the optimized value of the geometric dimension of the elastic unit are calculated based on the difference, the current elastic modulus (design value) of the elastic unit, the current geometric dimension (design value) of the elastic unit and the predetermined weight coefficient.

[0154] The geometric dimensions may include the diameter and overall thickness of the rubber spring, etc. For example, the difference may be further reduced by reducing the diameter of the rubber spring.

[0155] In an alternative solution, the elastic unit may also be a steel spring, and its geometric dimensions may include the diameter, wire diameter, overall height, number of effective turns, etc. of the steel spring.

[0156] Step S3-9, obtaining a rubber material satisfying the optimized value of the elastic modulus as an optimized rubber material according to the optimized value of the elastic modulus and the predetermined corresponding relationship between each elastic modulus and the rubber material.

[0157] Step S3-10, outputting the information of the optimized rubber material and the optimized value of the geometrical dimension of the elastic unit.

[0158] That is, when the difference is relatively large and it is difficult to adjust the natural frequency to the ideal value by optimizing the elastic modulus of the elastic unit alone, the elastic modulus and geometric dimensions of the elastic unit are optimized at the same time. According to the setting of the weight coefficient, for example, the elastic modulus can be adjusted mainly or the geometric dimensions can be adjusted mainly.

[0159] Step S3-11, when it is determined in step S3-2 that the difference is greater than the third threshold, the optimized value of the elastic modulus of the elastic unit, the optimized value of its geometric dimensions, and the optimized value of the mass of the floating slab track bed are calculated based on the difference, the current elastic modulus of the elastic unit, the current geometric dimensions of the elastic unit, the current mass of the floating slab track bed, and a predetermined weight coefficient.

[0160] Step S3-12, obtaining a rubber material satisfying the optimized value of the elastic modulus as an optimized rubber material according to the optimized value of the elastic modulus and the predetermined corresponding relationship between each elastic modulus and the rubber material.

[0161] Step S3-13, outputting the information of the optimized rubber material, the optimized value of the geometrical dimension of the elastic unit, and the optimized value of the mass of the floating slab track bed.

[0162] That is, when the difference is relatively large and it is difficult to adjust the natural frequency to the ideal value by optimizing only the stiffness of the elastic unit, the stiffness of the elastic unit and the mass of the roadbed are optimized at the same time. According to the setting of the weight coefficient, for example, the elastic modulus of the elastic unit can be adjusted mainly, or its geometric dimensions can be adjusted mainly, or the mass of the roadbed can be adjusted mainly.

[0163] Similarly, after step S3-11, a step of calculating the number and mass of the counterweight blocks may be included, and in step S-13, the number and mass of the counterweight blocks may be output simultaneously.

[0164] In practical applications, it is usually necessary to reduce the natural frequency of the floating slab track bed. If the current natural frequency of the floating slab track bed is higher than the ideal natural frequency, and the difference is f Relatively large, such as f >5Hz, consider reducing the stiffness of the rubber spring, that is, the first threshold can be set to 5Hz or ±5Hz. Since according to the natural frequency formula, the stiffness is proportional to the square of the natural frequency, reducing the stiffness can effectively reduce the natural frequency.

[0165] Step S4, optimizing the damping of the floating slab ballast according to the difference between the vibration attenuation speed of the floating slab ballast and the predetermined ideal vibration attenuation speed of the floating slab ballast.

[0166] Among them, when the calculated vibration attenuation rate is significantly greater or less than the ideal vibration attenuation rate, that is, the vibration attenuation rate of the floating slab track bed is too slow or too fast, it is caused by its inappropriate damping, so it is possible to consider adjusting its damping. Appropriate damping can improve the vibration attenuation characteristics of the floating slab track bed and enable it to reach a balanced state faster during the vibration process.

[0167] For example, the adjustment amount of the damping ratio can be calculated based on the difference between the vibration attenuation speed and the ideal vibration attenuation speed and the current damping ratio (design value) of the floating plate track bed, and then the rubber material of the rubber spring with the corresponding damping coefficient is selected as the optimized rubber material according to the adjustment amount of the damping ratio, that is, the optimal value of the damping coefficient of the rubber spring is calculated, and the optimized rubber material that meets the optimal value of the damping coefficient is obtained according to the corresponding relationship between each damping coefficient and the rubber material, and the information of the rubber material is output. The rubber material itself has certain damping characteristics, so the vibration attenuation characteristics can be improved by replacing rubber springs with different damping coefficients.

[0168] The damping ratio of the floating slab ballast can be calculated according to the following damping ratio formula.

[0169]

[0170] Alternatively, the number of dampers of a predetermined type to be installed and the parameters of the dampers may be calculated and outputted based on the adjustment amount of the damping ratio and a predetermined parameter range of the dampers.

[0171] Through the above steps, multi-source detection data can be automatically processed, and the optimization values ​​related to the vibration reduction performance of the floating slab track bed can be intelligently and automatically output based on the detection data, which can be used as a reference for track designers to better and more conveniently optimize the design of the floating slab track bed.

[0172] Fig.13 It is a logic block diagram of the track floating plate ballast optimization design device in this embodiment.

[0173] like Fig.13 As shown, a device corresponding to the above method can be formed, and the track floating plate track bed optimization design device 700 includes a signal data acquisition unit 710, a signal data alignment processing unit 720, a vibration signal analysis unit 730, a natural frequency optimization processing unit 740, a vibration attenuation speed optimization processing unit 750, an optimization device communication unit 760, and an optimization device control unit 770.

[0174] The signal data acquisition unit 710 is used to acquire corresponding signal data collected by each detection device from each data acquisition instrument, wherein it at least acquires load signal data and track bed vibration acceleration signal data.

[0175] The signal data alignment processing unit 720 adopts the method of step S1 above to pre-process the signal data acquired from the multiple detection devices and perform data time domain alignment.

[0176] The vibration signal analysis unit 730 uses the method in step S2 to perform spectrum analysis on the vibration acceleration signal of the aligned track bed.

[0177] The natural frequency optimization processing unit 740 optimizes the stiffness of the elastic unit and / or the mass of the floating slab track bed according to the spectrum analysis result using the method of step S3 above, so as to optimize the natural frequency of the floating slab track bed, and outputs the corresponding elastic unit information and / or optimization value.

[0178] The vibration attenuation speed optimization processing unit 750 optimizes the damping design of the floating slab track bed according to the spectrum analysis result using the method of step S4 to improve its vibration attenuation characteristics, and outputs corresponding elastic unit information and / or optimization value.

[0179] The optimization device communication unit 760 is used to communicate with other devices, for example, the optimized elastic unit information and optimized value can be sent to other computing and analysis devices, so that track designers can use this information more conveniently. Optionally, the track floating plate track bed optimization design device 700 has an input display unit, which can directly display the optimized elastic unit information and optimized value. Optionally, the track floating plate track bed optimization design device 700 does not directly connect with each data acquisition instrument and obtain the corresponding signal data collected by it, but receives the signal data collected by each detection device from other devices through the optimization device communication unit 760.

[0180] The optimization device control unit 770 is used to control the operation of the above-mentioned functional units.

[0181] In this embodiment, the track floating plate ballast optimization design device 700 is a laptop computer equipped with a corresponding computer program.

[0182] This embodiment has the following functions and effects.

[0183] According to the method and device for optimizing the design of the floating plate track bed provided in this embodiment, the method includes the steps of aligning the time domain signal data of multiple detection devices, performing spectrum analysis on the aligned track bed vibration acceleration signal data, and optimizing the design of the floating plate track bed according to the spectrum analysis results. Among them, since the characteristic points in the time domain signal correspond to the event that the specific structure of the train passes through the detection device, and the time domain signal alignment is achieved in combination with the predetermined distance between the detection devices, the automatic time domain alignment of the detection data can be achieved, and no manual operation is required to achieve the data time domain alignment, the alignment accuracy is higher, and a lot of manpower and time can be saved. Further, the natural frequency of the floating plate track bed can be obtained according to the spectrum analysis results of the aligned track bed vibration acceleration signal data. After calculating the difference between the natural frequency and the ideal frequency, the mass of the floating plate track bed and / or the stiffness and geometric dimensions (parameters related to the natural frequency) of the elastic unit of the vibration isolator can be optimized according to the difference, so that the vibration reduction performance optimization design of the floating plate track bed with higher accuracy and more intelligence can be achieved, and the burden of track designers can be greatly reduced.

[0184] In the embodiment, different preprocessing is performed on the raw data collected by various detection devices, including data smoothing, elimination of abnormal data, and data zeroing. After preprocessing, the noise in the raw data can be reduced, and the impact of passing trains on the installation status of each detection device can be eliminated, which is conducive to obtaining more accurate alignment results later.

[0185] Furthermore, in the data time domain alignment, the load detection device installed in the middle of the floating track plate is used as a reference detection device. Since there are multiple pad devices in the middle of the track plate that bear the load together and are relatively stable, there are basically no abnormal peaks in the time history curve collected by the load detection device in the middle of the plate, and there are very few other abnormal values. The correspondence between multiple peaks and the train bogie is clear and definite. Therefore, it is used as the reference detection device, and the search for characteristic points (peaks) is more convenient and accurate. Correspondingly, the subsequently calculated train speed and time shift are also more accurate, and the multi-source detection data can be more accurately aligned in the time domain.

[0186] Furthermore, the maximum correlation algorithm can effectively determine the optimal alignment point between signals. Due to the structural characteristics of the floating track plate, the time history curves collected by the load detection device in the middle of the plate and the load detection device at the end of the plate are very different. It is impossible to use the data in the middle of the plate to assist the correspondence and confirmation of the wheel position in the data at the end of the plate through algorithms such as peak matching. However, by using the characteristic that the bogie will produce two peaks with equal time intervals when passing through the load detection device, the maximum correlation algorithm can well determine the optimal alignment point between the very different signals, and then calculate the vehicle speed and other data through the peak data in the middle of the plate, which can assist in confirming the wheel position in the data at the end of the plate.

[0187] Furthermore, since the various detection devices are fixedly installed in the track structure, the known device spacing, the calculated train speed, and the reference time point when the train passes the reference detection device can be used to obtain accurate time shifts with very little calculation complexity. This can be used to automatically align large-scale multi-source detection data in the time domain, thus facilitating big data analysis.

[0188] Furthermore, in the optimization design, different optimization design strategies are adopted according to the predetermined multiple threshold ranges. When the difference between the natural frequency and the ideal frequency is small, only the quality of the floating plate track bed is optimized; when the difference is relatively large, the stiffness of the elastic unit is adjusted. Since the stiffness is proportional to the square of the natural frequency, the natural frequency can be effectively adjusted; when the difference is larger, the stiffness and geometric dimensions of the elastic unit are adjusted at the same time; further, when the difference is larger, the stiffness and geometric dimensions of the elastic unit and the quality of the floating plate track bed are optimized at the same time, and the threshold range and the adjustment range of each parameter can ensure the normal function and other mechanical properties of the floating plate track bed after optimization. Therefore, based on the detection data collected during the actual track operation process, a very intelligent optimization of the vibration reduction characteristics of the floating plate track bed is realized. The output optimized rubber material information and the optimized values ​​of each parameter can provide track designers with very valuable references, which can help them optimize the design of floating plate track beds more quickly and better.

[0189] Furthermore, for the optimization of the quality of the floating slab track bed, the quality of the track bed is adjusted by designing a matching block installed in the vibration isolator. For the optimization of the elastic unit, the elastic unit is an independent component arranged in a sleeve on the floating slab track bed. The stiffness and geometric dimensions of the elastic unit can be adjusted by replacing the elastic unit. Therefore, the optimized design scheme is easy to deploy in the actual track and does not require a long period of construction to achieve.

[0190] Furthermore, the vibration attenuation rate of the floating slab track bed is calculated based on the detection data. In the optimization design, the material of the elastic unit is optimized based on the vibration attenuation rate and the corresponding ideal vibration attenuation rate, or the number and parameters of the corresponding dampers can be automatically designed. Therefore, not only the natural frequency of the floating slab track bed can be improved, but also its vibration attenuation characteristics can be improved, so that the floating slab track bed can reach a balanced state faster during the vibration process, which is beneficial to improving the riding experience of train passengers and also beneficial to increasing the service life of related track components.

[0191] The above embodiments are only used to illustrate the specific implementation of the present invention, and the present invention is not limited to the description scope of the above embodiments. Those skilled in the art should understand that the present invention is not limited by the above embodiments. The above embodiments and descriptions are only to illustrate the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, and these changes and improvements fall within the scope of the present invention to be protected. The scope of protection of the present invention is defined by the attached claims and their equivalents.

[0192] For example, in the above embodiment, the detection device includes a vibration isolator detection device, a load detection device, a vibration acceleration detection device, and a rail displacement detection device. In an alternative solution, the detection device may also only include a load detection device and a vibration acceleration detection device. In the embodiment, the vibration acceleration detection device includes a rail vibration acceleration sensor, a ballast vibration acceleration sensor, and a tunnel wall vibration acceleration sensor. In an alternative solution, it may also only include a ballast vibration acceleration sensor.

[0193] In the above embodiment, the load detection device in the middle of the plate is used as the reference detection device, and the wave peaks corresponding to the wheels are found from its time domain signal as the feature points for time domain alignment. In alternative schemes, other detection devices can also be used as reference detection devices, as long as their time domain signals have waveform features that are relatively easy to identify and can clearly correspond to specific structures on the train.

[0194] In the above embodiment, a floating slab ballast using a plurality of rubber spring isolators is used as an example for specific description. In an alternative solution, the method can also be similarly applied to a floating slab ballast using other types of elastic isolators, such as a floating slab ballast using steel springs.

[0195] In the above embodiment, the track floating plate ballast optimization design device is a laptop computer. In an alternative solution, it may also be other computing and analysis equipment, and may also be a remote device.

Claims

1. A method for optimizing the design of a floating plate track bed, for optimizing the design of a floating plate track bed having a plurality of vibration isolators, wherein the vibration isolators include elastic units, characterized in that: The following steps are involved: Step S1, searching for predetermined feature points in the time domain signal data of multiple detection devices in the track and obtaining the time points thereof, and performing time domain alignment on the time domain signal data of the multiple detection devices according to the correspondence between the feature points and the train structure and the predetermined distances between the multiple detection devices, wherein the detection device includes a vibration acceleration detection device, which is at least used to detect the vibration acceleration of the floating plate track bed to obtain corresponding track bed vibration acceleration signal data; Step S2, performing spectrum analysis on the aligned ballast vibration acceleration signal data, and calculating at least the free attenuation frequency and the natural frequency of the floating plate ballast according to the spectrum analysis result; and Step S3, optimizing the stiffness of the elastic unit, the geometric dimensions of the elastic unit and / or the mass of the floating slab ballast according to the difference between the natural frequency of the floating slab ballast and the predetermined ideal natural frequency of the floating slab ballast, Wherein, the characteristic point is the wave crest corresponding to the bogie of the train.

2. The track floating plate ballast optimization design method according to claim 1, Features: Wherein, step S2 includes the following sub-steps: Step S2-1, performing fast Fourier transform analysis on the vibration acceleration signal data of the ballast bed, extracting the frequency spectrum of the vibration signal, and identifying the main vibration frequency components; Step S2-2, simplifying the floating plate ballast into a mass-spring-damper system, and calculating the free decay frequency of the system according to the extracted frequency of the vibration signal and the main vibration frequency component as the free decay frequency of the floating plate ballast; Step S2-3, calculating the natural frequency of the floating slab ballast according to the free decay frequency of the floating slab ballast.

3. The method for optimizing the design of floating slab track bed according to claim 2 is characterized in that: in, The free vibration equation of the mass-spring-damper system is: Wherein, m is the equivalent mass of the floating slab ballast, c is the damping coefficient of the floating slab ballast, k is the equivalent stiffness of the floating slab ballast, and the stiffness of the elastic unit is adopted. The free vibration equation is solved to obtain the free attenuation frequency: The natural frequency is calculated according to the following formula: Wherein, ξ is the damping coefficient of the floating slab ballast.

4. The method for optimizing the design of floating slab track bed according to claim 2, characterized in that: in, Step S3 includes the following sub-steps: Step S3-1, calculating the difference between the natural frequency and the ideal natural frequency; Step S3-2, determining which of a plurality of predetermined threshold ranges the difference falls within; Step S3-3, when it is determined in step S3-2 that the mass is less than a predetermined first threshold, calculating the mass optimization value of the floating slab ballast according to the difference and the current mass of the floating slab ballast; Step S3-4, outputting the quality optimization value obtained in step S3-3; Step S3-5, when it is determined in step S3-2 that the difference is between the first threshold and a predetermined second threshold, calculating an optimized elastic modulus value of the elastic unit according to the difference and a current elastic modulus of the elastic unit; Step S3-6, obtaining information on optimizing the rubber material according to the elastic modulus optimization value obtained in step S3-5 and the predetermined correspondence between each elastic modulus and the rubber material; Step S3-7, outputting the information of the optimized rubber material obtained in step S3-6; Step S3-8, when it is determined in step S3-2 that the difference is between the second threshold and the predetermined third threshold, the elastic modulus optimization value and the geometric dimension optimization value of the elastic unit are calculated according to the difference, the current elastic modulus of the elastic unit, the current geometric dimension of the elastic unit and the predetermined corresponding weight coefficient; Step S3-9, obtaining information on optimizing the rubber material according to the elastic modulus optimization value obtained in step S3-8 and the correspondence between the predetermined elastic moduli and the rubber material; Step S3-10, outputting the information of the optimized rubber material obtained in step S3-9 and the optimized value of the geometric dimension obtained in step S3-8.

5. The method for optimizing the design of floating slab track bed according to claim 4 is characterized in that: in, Step S3 also includes: Step S3-11, when it is determined in step S3-2 that the difference is greater than the third threshold, the elastic modulus optimization value, the geometrical dimension optimization value, and the mass optimization value of the floating slab ballast of the elastic unit are calculated according to the difference, the current elastic modulus of the elastic unit, the current geometrical dimension of the elastic unit, the current mass of the floating slab ballast, and the predetermined corresponding weight coefficients; Step S3-12, obtaining information on optimizing the rubber material according to the elastic modulus optimization value obtained in step S3-11 and the correspondence between the predetermined elastic moduli and the rubber material; Step S3-13, outputting the information of the optimized rubber material obtained in step S3-12, the geometrical dimension optimization value of the elastic unit obtained in step S3-11, and the mass optimization value of the floating plate track bed.

6. The method for optimizing the design of floating slab track bed according to claim 2, characterized in that: in, Step S2 also includes: Step S2-4, obtaining the vibration attenuation speed of the floating plate track bed according to the frequency spectrum of the vibration signal, The track floating plate ballast optimization design method further includes: Step S4, optimizing the damping of the floating slab ballast according to the difference between the vibration attenuation speed of the floating slab ballast and a predetermined ideal vibration attenuation speed of the floating slab ballast.

7. The method for optimizing the design of floating slab track bed according to claim 6, characterized in that: in, The optimized value of the damping coefficient of the elastic unit is calculated according to the difference between the vibration attenuation speed and the ideal vibration attenuation speed and the current damping ratio of the floating plate ballast, and the information of optimizing the rubber material is obtained according to the corresponding relationship between each damping coefficient and the rubber material.

8. The track floating plate ballast optimization design method according to claim 1, Features: Wherein, step S1 includes the following sub-steps: Step S1-1, preprocessing the original signal data of the plurality of detection devices to obtain the corresponding time domain signal data; Step S1-2, using one of the plurality of detection devices as a reference detection device, searching for predetermined feature points corresponding to the characteristic structure of the train and their corresponding time points in the time domain signal data of the reference detection device; Step S1-3, calculating the time difference between two adjacent feature points to obtain a feature point time difference array; Step S1-4, based on the feature point time difference array, calculating the cross-correlation coefficients between multiple groups of feature points by a cross-correlation algorithm to obtain a cross-correlation array; Step S1-5, searching for the maximum value position in the cross-correlation array, and obtaining the time point corresponding to the maximum value position as the reference time point, so as to determine the best alignment point between the time domain signal data collected by different detection devices; Step S1-6, calculating the train speed according to the size of the characteristic structure of the train and the characteristic point time difference between a group of characteristic points generated by the characteristic structure passing through the reference detection device; Step S1-7, calculating the time it takes for the characteristic structure of the train to pass the predetermined distance according to the predetermined distance between the reference detection device and the detection device to be aligned and the speed of the train; Step S1-8, calculating the time shift of the time domain signal data of the detection device to be aligned relative to the time domain signal data of the reference detection device according to the elapsed time and the reference time point; and Step S1-9, performing time domain shift on the time domain signal data of each detection device to be aligned according to the corresponding time shift amount, so as to obtain aligned data.

9. The method for optimizing the design of floating slab track bed according to claim 8, characterized in that: in, The plurality of detection devices also include a load detection device, which is arranged below the rail of the track and is used to detect the load of the track. The reference detection device is the load detection device, The vibration acceleration detection device includes a plurality of vibration acceleration sensors, wherein one or more of the vibration acceleration sensors are arranged in the middle of the upper surface of the floating plate track bed, and are used to obtain vibration acceleration signal data of the track bed.

10. A track floating plate ballast optimization design device, used for optimizing the design of a floating plate ballast with multiple vibration isolators, wherein the vibration isolators include elastic units, characterized in that: include: A signal data acquisition unit, used to acquire time domain signal data collected by a plurality of detection devices in the track, wherein the detection device includes a vibration acceleration detection device, which is at least used to detect the vibration acceleration of the floating plate track bed to obtain corresponding track bed vibration acceleration signal data; A signal data alignment processing unit, used to search for predetermined feature points in the time domain signal data of the plurality of detection devices and obtain their time points, and perform time domain alignment on the time domain signal data of the plurality of detection devices according to the correspondence between the feature points and the train structure and the predetermined distances between the plurality of detection devices; a vibration signal analysis unit, configured to perform spectrum analysis on the vibration acceleration signal data of the aligned ballast bed, and calculate at least the free attenuation frequency and the natural frequency of the floating plate ballast bed according to the spectrum analysis result; and The natural frequency optimization processing unit is used to optimize the stiffness of the elastic unit and / or the mass of the floating slab ballast according to the difference between the natural frequency of the floating slab ballast and the predetermined ideal natural frequency of the floating slab ballast. Wherein, the characteristic point is the wave crest corresponding to the bogie of the train.

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