Heavy haul railway sleeper supporting state vehicle-mounted detection method based on variational mode decomposition

Abstract

The invention discloses a heavy haul railway sleeper supporting state vehicle-mounted detection method based on variational mode decomposition, and the method comprises the operation steps: collecting a vertical acceleration signal of a vehicle body under a set sampling frequency, and then taking a theoretical sleeper excitation frequency as an initial parameter; according to the method, the sleeper excitation component in the vertical acceleration of the vehicle body is extracted through the driving variational mode decomposition method, then the sleeper supporting state index SSI is calculated through the excitation component, finally, the sleeper supporting state evaluation rule based on the sleeper excitation component is constructed, graded evaluation of the heavy haul railway sleeper supporting state can be achieved, and the method has the advantages of being accurate, efficient, stable, reliable and the like.

Description

Technical Field

[0001] The invention belongs to the technical field of railway line service status monitoring and operation maintenance, and in particular relates to a vehicle-mounted detection method for heavy-load railway sleeper support status based on variational mode decomposition. Background Art

[0002] As an important part of the ballasted track structure, the sleeper not only bears the violent interaction caused by the dynamic contact between the wheel and the rail, but also transmits the dynamic force evenly to the ballast bed, while also effectively maintaining the gauge, direction and position of the rail. However, under the long-term action of the severe cyclic load of heavy-load trains, the track structure will inevitably suffer from problems such as ballast bed crushing and roadbed settlement, leading to failure of sleeper support. At the same time, the failure of sleeper support will further aggravate the wheel-rail interaction, reduce the service life of the vehicle and track structure, and even threaten driving safety. Therefore, it is necessary to accurately detect the support status of the sleeper in order to effectively guide track maintenance and ensure the safe and stable operation of heavy-load railways.

[0003] Existing methods for detecting the support status of sleepers mainly include manual on-track detection (i.e. static detection) and track inspection vehicles. The former is simple and easy to perform, but it is highly subjective, inefficient and has safety hazards. The latter can achieve dynamic detection, but the detection cycle is relatively fixed, and there are obvious differences between the track inspection vehicle and the actual operating vehicle, making it difficult to reflect the support status of the sleepers in the actual operating environment. Since the vibration response sensors (car body acceleration sensors) of operating vehicles are easy to install and maintain, and do not interfere with the normal operation of the railway, the track status detection technology based on the vibration response of operating vehicles has gradually received widespread attention in recent years. However, since the correlation between the support status of sleepers and the vibration signals of heavy-loaded vehicles has not yet been clarified, and the vehicle vibration response components caused by disturbances such as wheel polygons and track unevenness may overwhelm the support status characteristics of sleepers, there is still a lack of effective on-board detection methods for the support status of sleepers on heavy-load railways. Summary of the invention

[0004] In order to overcome the above-mentioned shortcomings, an on-board detection method for the support status of heavy-duty railway sleepers based on variational mode decomposition is proposed. The present invention uses the theoretical sleeper excitation frequency as the initial parameter, drives the variational mode decomposition method to extract the vertical acceleration of the vehicle body, and can successfully separate the sleeper excitation component. The excitation component is then used to calculate the sleeper support state index SS, and the sleeper support state evaluation index and rules are designed based on the sleeper excitation component. This can realize the graded evaluation of the support state of heavy-duty railway sleepers, and has the characteristics of accuracy, efficiency, stability and reliability. To achieve the above-mentioned purpose, the technical solution adopted by the present invention is to provide an on-board detection method for the support status of heavy-duty railway sleepers based on variational mode decomposition. The steps include:

[0005] S1, collecting the vertical acceleration signal of the vehicle body at a set sampling frequency;

[0006] S2, using variational mode decomposition method to extract the sleeper excitation component from the vehicle body vertical acceleration signal;

[0007] S3, calculate the sleeper support status index SSI, based on which the sleeper support status is evaluated, and the degree of support failure is graded and the location is accurately identified;

[0008] S3.1, calculate the envelope signal of the sleeper excitation component using Hilbert transform;

[0009] S3.2, determine the sliding window length using the sleeper spacing and sampling frequency;

[0010] S3.3, intercepting the envelope signal of the sleeper excitation component according to the sliding window length, and calculating the sleeper support state index SSI.

[0011] According to the on-board detection method of the support status of heavy-load railway sleepers based on variational mode decomposition of the present invention, a further preferred technical solution is: in step S1, the vehicle body vertical acceleration signal is obtained using a vehicle body acceleration sensor installed just above the center of the two wheelsets of the heavy-load truck.

[0012] According to the on-board detection method for the support status of heavy-duty railway sleepers based on variational mode decomposition of the present invention, a further preferred technical solution is: in step S1, the sampling frequency of the vehicle body acceleration is 200Hz to 300Hz.

[0013] According to the on-board detection method for heavy-duty railway sleeper support status based on variational mode decomposition of the present invention, a further preferred technical solution is: Step S2 specifically comprises:

[0014] S2.1, obtain the theoretical sleeper excitation frequency f according to the vehicle running speed and sleeper spacing se :

[0015]

[0016] Among them, ν is the vehicle running speed, in km / h; L is the sleeper spacing, in m, which needs to be set according to the actual line;

[0017] S2.2, using f se The initial center frequency drives the variational mode decomposition method, accelerating vertically from the vehicle body

[0018] Extract the sleeper excitation component m(t) from the signal:

[0019] m(t)=VMD[s(t),f se ]

[0020] Here, s(t) represents the measured vehicle acceleration and VMD[·] represents the variational mode decomposition method.

[0021] According to the on-board detection method for heavy-duty railway sleeper support status based on variational mode decomposition of the present invention, a further preferred technical solution is: Step S3 specifically comprises:

[0022] S3.1, use Hilbert transform to calculate the envelope signal a(t) of the sleeper excitation component:

[0023] a(t)=|H[m(t)]|

[0024] Where H[·] represents Hilbert transform, |·| represents absolute value operation;

[0025] S3.2, according to the sleeper spacing L and sampling frequency f s Determine the sliding window length Ls:

[0026]

[0027] S3.3, intercept the envelope signal of the sleeper excitation component according to the window length Ls, and calculate the sleeper support state index SSI:

[0028]

[0029] Where SSI is essentially the inverse of the sleeper excitation component; N represents the number of data intercepted by the sliding window with a length of Ls; a i (t) represents the i-th envelope value; μ is a constant coefficient, which is 10 -4 ;

[0030] S3.4, assess the sleeper support status by graded evaluation rules, and accurately identify the degree and location of sleeper support failure.

[0031] According to the on-board detection method for the support status of heavy-duty railway sleepers based on variational mode decomposition described in the present invention, a further preferred technical solution is: in step S2.2, the variational mode decomposition method is used as an optimal bandpass filter to extract only one sleeper excitation component.

[0032] According to the on-board detection method for heavy-duty railway sleeper support status based on variational mode decomposition of the present invention, a further preferred technical solution is: in step S3.4, the middle sleeper support status evaluation

[0033] The rules for evaluating the sleeper support status are shown in the following table:

[0034]

[0035] Compared with the prior art, the technical solution of the present invention has the following advantages / benefits:

[0036] 1. The present invention uses the vertical acceleration of the vehicle body as the monitoring signal, and can utilize the primary and secondary suspension systems to effectively eliminate high-frequency interference components caused by disturbances such as wheel polygons and short-wave unevenness of tracks, thereby making the results more accurate.

[0037] 2. The present invention uses the theoretical sleeper excitation frequency as the initial parameter, drives the variational mode decomposition method to extract the sleeper excitation component in the vehicle body vertical acceleration, and then uses the excitation component to calculate the sleeper support state index SSI. Finally, a sleeper support state evaluation rule based on the sleeper excitation component is constructed, which can realize the graded evaluation of the support state of heavy-duty railway sleepers, and has the characteristics of accuracy, efficiency, stability and reliability. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0039] Figure 1 It is a flow chart of the detection of the support state of heavy-duty railway sleepers of the present invention;

[0040] Figure 2 It is a schematic diagram of the installation position of the vehicle acceleration sensor of the present invention;

[0041] Figure 3 It is a schematic diagram of the time domain waveform of the simulated vehicle acceleration;

[0042] Figure 4 The sleeper excitation component is extracted from the simulated vehicle body acceleration by the variational mode decomposition method of the present invention;

[0043] Figure 5 It is a schematic diagram of the sleeper support state detection result obtained by the present invention according to the simulated vehicle body acceleration;

[0044] Figure 6 It is a schematic diagram of the time domain waveform of the measured vehicle acceleration;

[0045] Figure 7 The sleeper excitation component is extracted from the measured vehicle body acceleration by the variational mode decomposition method of the present invention;

[0046] Figure 8 It is a schematic diagram of the sleeper support state detection result obtained according to the actual measured vehicle body acceleration of the present invention. DETAILED DESCRIPTION

[0047] In order to make the purpose, technical solutions and advantages of the present invention clearer, the technical solutions in the embodiments of the present invention are clearly and completely described below. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present invention. Therefore, the detailed description of the embodiments of the present invention provided below is not intended to limit the scope of the claimed invention, but merely represents the selected embodiments of the present invention.

[0048] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and thus, once an item is defined in one drawing, it may not be further defined or explained in the subsequent drawings.

[0049] Example:

[0050] like Figure 1 As shown, a vehicle-mounted detection method for the support state of heavy-duty railway sleepers based on variational mode decomposition comprises the following steps:

[0051] Step S1, using a body acceleration sensor installed just above the center of the two wheel sets of the heavy-duty truck to obtain the body vertical acceleration signal, the sampling frequency is f s , installation location: Figure 2 As shown in the figure, the obtained simulated vehicle acceleration (referring to the vertical acceleration of the vehicle) signal is as follows Figure 3 As shown;

[0052] Step S2, using the variational mode decomposition method to extract the sleeper excitation component from the simulated vehicle acceleration signal, such as Figure 4 As shown;

[0053] Step S2.1, obtain the theoretical sleeper excitation frequency f according to the vehicle running speed and the sleeper spacing se :

[0054]

[0055] Among them, ν is the vehicle running speed, in km / h, obtained by the vehicle-mounted GPS; L is the sleeper spacing, in m, which needs to be set according to the actual line;

[0056] Step S2.2, using f se The initial center frequency driven variational mode decomposition method is used to extract the sleeper excitation component m(t) from the vehicle body vertical acceleration signal:

[0057] m(t)=VMD[s(t),f se ]

[0058] Where s(t) represents the measured vehicle acceleration and VMD[·] represents the variational mode decomposition method, which is equivalent to an optimal bandpass filter and only extracts one sleeper excitation component.

[0059] Step S3, evaluating the sleeper support status through a sleeper support status index SSI, achieving graded assessment of the support failure degree and accurate identification of the location, such as Figure 5 As shown;

[0060] Step S3.1, using Hilbert transform to calculate the envelope signal a(t) of the sleeper excitation component:

[0061] a(t)=|H[m(t)]|

[0062] Where H[·] represents Hilbert transform, |·| represents absolute value operation;

[0063] Step S3.2, according to the sleeper spacing L and sampling frequency f s Determine the sliding window length Ls:

[0064]

[0065] Step S3.3, intercept the envelope signal of the sleeper excitation component according to the window length Ls, and calculate the sleeper support state index SSI:

[0066]

[0067] Where SSI is essentially the inverse of the sleeper excitation component; N represents the number of data intercepted by the sliding window with a length of Ls; a i (t) represents the i-th envelope value; μ is a constant coefficient, which is 10 -4 ;

[0068] Step S3.4, the sleeper support state is graded and evaluated by the sleeper support state evaluation rule, and the failure degree and position of the sleeper support are accurately identified. The support state refers to the SSI, which is data corresponding to the running distance. Therefore, the position where the SSI exceeds the threshold is the failure position;

[0069] In step S1, in order to ensure sufficient sampling, the sampling frequency of the vehicle acceleration should not be less than 200 Hz, and can be 200 Hz to 300 Hz;

[0070] The sleeper support status evaluation rules in step S3 are as shown in the following table:

[0071] Sleeper support status evaluation table

[0072] Sleeper support status grade Support status evaluation index evaluate Level 1 SSI≤1 excellent Level 2 1<SSI≤2 good Level 3 2≤SSI<3 qualified Level 4 SSI ≥ 3 Difference

[0073] The method provided by the present invention is used to detect the support status of heavy-load railway sleepers. Figure 6 This is a schematic diagram of the measured vehicle acceleration time domain waveform. Figure 7 is the sleeper excitation component obtained by variational mode decomposition, Figure 8 The results show that the method provided by the present invention can realize the decomposition evaluation of the actual sleeper support state and accurately identify the degree and location of sleeper support failure.

[0074] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the referred device or element must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present invention.

[0075] In the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0076] The above are only preferred embodiments of the present invention. It should be noted that the above preferred embodiments should not be regarded as limiting the present invention, and the protection scope of the present invention should be based on the scope defined by the claims. For ordinary technicians in this technical field, several improvements and modifications can be made without departing from the spirit and scope of the present invention, and these improvements and modifications should also be regarded as the protection scope of the present invention.

Claims

1. A vehicle-mounted detection method for the support status of heavy-duty railway sleepers based on variational mode decomposition, characterized in that: The steps include: S1, collecting the vertical acceleration signal of the vehicle body at a set sampling frequency; S2, using variational mode decomposition method to extract the sleeper excitation component from the vehicle body vertical acceleration signal; S3, use the sleeper support index SSI to evaluate the sleeper support condition: S3.1, calculate the envelope signal of the sleeper excitation component using Hilbert transform; S3.2, determine the sliding window length using the sleeper spacing and sampling frequency; S3.3, intercepting the envelope signal of the sleeper excitation component according to the sliding window length, and calculating the sleeper support state index SSI; S3.4, use the sleeper support condition index (SSI) to assess the sleeper support condition and identify the extent and location of sleeper support failure.

2. The vehicle-mounted detection method for heavy-duty railway sleeper support status based on variational mode decomposition according to claim 1 is characterized in that: In step S1, the vehicle body vertical acceleration signal is obtained by using a vehicle body acceleration sensor installed just above the center of two wheel sets of the heavy-duty truck.

3. The vehicle-mounted detection method for heavy-duty railway sleeper support status based on variational mode decomposition according to claim 1 is characterized in that: In step S1, the sampling frequency of the vehicle acceleration is 200 Hz to 300 Hz.

4. The vehicle-mounted detection method for heavy-duty railway sleeper support status based on variational mode decomposition according to claim 1 is characterized in that: The specific steps of step S2 are: S2.1, obtain the theoretical sleeper excitation frequency f according to the vehicle running speed and sleeper spacing se : Among them, ν is the vehicle running speed, in km / h; L is the sleeper spacing, in m, which needs to be set according to the actual line; S2.2, using f se The initial center frequency is used to drive the variational mode decomposition method, and the vertical Extract the sleeper excitation component m(t) from the velocity signal: m(t)=VMD[s(t),f se ] Where s(t) represents the measured vehicle acceleration and VMD[g] represents the variational mode decomposition method.

5. The vehicle-mounted detection method for heavy-duty railway sleeper support status based on variational mode decomposition according to claim 4 is characterized in that: The specific steps of step S3 are: S3.1, use Hilbert transform to calculate the envelope signal a(t) of the sleeper excitation component: a(t)=|H[m(t)]| Where H[g] represents Hilbert transform, |g| represents absolute value operation; S3.2, according to the sleeper spacing L and sampling frequency f s Determine the sliding window length Ls: S3.3, intercept the envelope signal of the sleeper excitation component according to the window length Ls, and calculate the sleeper support state index SSI: Where SSI is essentially the inverse of the sleeper excitation component; N represents the number of data intercepted by the sliding window with a length of Ls; a i (t) represents the i-th envelope value; μ is a constant coefficient, which is 10 -4 ; S3.4, assess the sleeper support status by graded evaluation rules, and accurately identify the degree and location of sleeper support failure.

6. The vehicle-mounted detection method for heavy-duty railway sleeper support status based on variational mode decomposition according to claim 4 is characterized in that: In step S2.2, the variational mode decomposition method is used as an optimal bandpass filter to extract only one sleeper excitation component.

7. The vehicle-mounted detection method for heavy-duty railway sleeper support status based on variational mode decomposition according to claim 4 is characterized in that: In step S3.4, the sleeper support status evaluation rules are shown in the following table:

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