On-vehicle Detection Method for the Support State of Overloaded Railway Sleepers Based on Variational Mode Decomposition

Abstract

The present invention discloses a vehicle-mounted detection method for the support state of heavy-haul railway sleepers based on variational mode decomposition. The operation steps are as follows: collect the vertical acceleration signal of the vehicle body at a set sampling frequency, then use the theoretical sleeper excitation frequency as the initial parameter to drive the variational mode decomposition method to extract the sleeper excitation component in the vertical acceleration of the vehicle body, and then calculate the sleeper support state index SSI using the excitation component. Finally, construct an evaluation rule for the sleeper support state based on the sleeper excitation component, which can realize the hierarchical evaluation of the support state of heavy-haul railway sleepers, and has the characteristics of accuracy, high efficiency, stability and reliability.

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. Extract the sleeper excitation component from the vertical acceleration signal of the car body using the variational mode decomposition method;

[0007] S3. Calculate the sleeper support state index SSI, and based on this, evaluate the sleeper support state to achieve the classification and grading of the support failure degree and the accurate identification of the location;

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

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

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

[0011] According to the on-vehicle detection method for the sleeper support state of heavy-haul railways based on variational mode decomposition of the present invention, a further preferred technical solution is: in step S1, the vertical acceleration signal of the car body is obtained by using a car body acceleration sensor installed directly above the center of the second axle of the heavy-haul freight car.

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

[0013] According to the on-vehicle detection method for the sleeper support state of heavy-haul railways based on variational mode decomposition of the present invention, a further preferred technical solution is: the specific steps of step S2 are as follows:

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

[0015]

[0016] where ν is the vehicle running speed, with the unit of km / h; L is the sleeper spacing, with the unit of m, which needs to be set according to the actual line;

[0017] S2.2. Use f se as the initial center frequency to drive the variational mode decomposition method to extract the sleeper excitation component m(t) from the vertical acceleration

[0018] signal of the car body:

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

[0020] Among them, s(t) represents the measured car body acceleration, and VMD[·] represents the variational mode decomposition method.

[0021] For the on-vehicle detection method of the sleeper support state of heavy-haul railways based on variational mode decomposition according to the present invention, a further preferred technical solution is: The specific steps of step S3 are as follows:

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

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

[0024] Among them, H[·] represents the Hilbert transform, and |·| represents the absolute value operation;

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

[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] Among them, SSI is essentially the reciprocal 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 among them; μ is a constant coefficient, taking 10 -4 ;

[0030] S3.4, grade and evaluate the sleeper support state through the sleeper support state evaluation rule, and accurately identify the degree and position of sleeper support failure.

[0031] For the on-vehicle detection method of the sleeper support state of heavy-haul railways based on variational mode decomposition according to the present invention, a further preferred technical solution is: In step S2.2, the variational mode decomposition method is used as the optimal band-pass filter to extract only 1 sleeper excitation component.

[0032] For the on-vehicle detection method of the sleeper support state of heavy-haul railways based on variational mode decomposition according to the present invention, a further preferred technical solution is: In step S3.4, the evaluation of the middle sleeper support state

[0033] The rule is as shown in the following table of the sleeper support state grade evaluation rule:

[0034]

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

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

[0037] 2. The present invention takes the theoretical sleeper excitation frequency as the initial parameter, drives the variational mode decomposition method to extract the sleeper excitation component in the vertical acceleration of the vehicle body, then calculates the sleeper support state index SSI using the excitation component, and finally constructs a sleeper support state evaluation rule based on the sleeper excitation component, which can realize the hierarchical evaluation of the sleeper support state of heavy-haul railways, and has the characteristics of accuracy, high 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 following will briefly introduce the drawings required for the embodiments. It should be understood that the following drawings only show some embodiments of the present invention, and therefore should not be regarded as limiting the scope. For those of ordinary skill in the art, other related drawings can be obtained based on these drawings without creative efforts.

[0039] Figure 1 is the flow chart of the sleeper support state detection of the heavy-haul railway of the present invention;

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

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

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

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

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

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

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

[0047] To make the objectives, technical solutions, and advantages of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without making creative efforts belong to 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 present invention, but merely represents selected embodiments of the present invention.

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

[0049] Example:

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

[0051] Step S1: Obtain the vertical acceleration signal of the vehicle body using a vehicle body acceleration sensor installed directly above the center of the second axle of the heavy-haul freight car, with a sampling frequency of f s , and the installation position is as Figure 2 shown. The obtained simulated vehicle body acceleration (referring to the vertical acceleration of the vehicle body) signal is as Figure 3 shown;

[0052] Step S2: Extract the sleeper excitation component from the simulated vehicle body acceleration signal using the variational mode decomposition method, as Figure 4 shown;

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

[0054]

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

[0056] Step S2.2: Use f se as the initial center frequency to drive the variational mode decomposition method to extract the sleeper excitation component m(t) from the vertical acceleration signal of the vehicle body:

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

[0058] Among them, s(t) represents the measured car body acceleration, and VMD[·] represents the variational mode decomposition method; the variational mode decomposition method is equivalent to an optimal band-pass filter, which only extracts one sleeper excitation component.

[0059] Step S3, evaluate the sleeper support state through a sleeper support state index SSI to achieve hierarchical assessment of the support failure degree and precise identification of the location, as Figure 5 shown;

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

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

[0062] Among them, H[·] represents the Hilbert transform, and |·| represents the absolute value operation;

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

[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] Among them, SSI is essentially the reciprocal 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 among them; μ is a constant coefficient, taking 10 -4 ;

[0068] Step S3.4, grade and evaluate the sleeper support state through the sleeper support state evaluation rule, and accurately identify the sleeper support failure degree and location. The support state refers to the data corresponding to the running distance of SSI. Therefore, the position where SSI exceeds the threshold is the failure position;

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

[0070] The sleeper support state evaluation rule in step S3 is as shown in the following table of the sleeper support state level evaluation rule:

[0071] Sleeper Support State Level Evaluation Table

[0072] Sleeper support status level Support status evaluation index Evaluation Level 1 SSI ≤ 1 Excellent Level 2 1 < SSI ≤ 2 Good Level 3 2 ≤ SSI < 3 Qualified Level 4 SSI ≥ 3 Poor

[0073] The method provided by the present invention is used for detecting the support state of sleepers on heavy-haul railways through actual measurement. Figure 6 It is a schematic diagram of the time-domain waveform of the measured vehicle body acceleration. Figure 7 It is the sleeper excitation component obtained by variational mode decomposition. Figure 8 It is a schematic diagram of the detection result of the sleeper support state. The results show that the method provided by the present invention can realize the decomposition and 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 orientation or positional relationship indicated by terms such as "center", "longitudinal", "transverse", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", etc. is based on the orientation or positional relationship shown in the drawings. It is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation to the present invention.

[0075] In the present invention, unless otherwise clearly defined and limited, terms such as "installation", "connection", "connection", "fixation", etc. should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or integrated; it can be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium, and it can be the communication inside two elements or the interaction relationship between two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0076] The above is only the preferred embodiment of the present invention. It should be noted that the above preferred embodiment should not be regarded as a limitation to the present invention. The protection scope of the present invention should be subject to the scope defined by the claims. For those of ordinary skill in the technical field, without departing from the spirit and scope of the present invention, several improvements and refinements can also be made, and these improvements and refinements should also be regarded as the protection scope of the present invention.

Claims

1. A vehicle-mounted detection method for the support state of heavy-haul railway sleepers based on variational mode decomposition, characterized in that, The steps include: S1. Collect the vertical acceleration signal of the car body at a set sampling frequency; S2. Extract the sleeper excitation component from the vertical acceleration signal of the car body by using the variational mode decomposition method. The specific steps are as follows: Specifically: S2.

1. Obtain the theoretical sleeper excitation frequency f based on the vehicle running speed and sleeper spacing se : where 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 As the initial center frequency drives the variational mode decomposition method, extract the sleeper excitation component m(t) from the vertical acceleration signal of the car body: m(t) = VMD[s(t), f se ​ where s(t) represents the measured car body acceleration, and VMD[·] represents the variational mode decomposition method; S3. Evaluate the sleeper support state by using the sleeper support state index SSI. The specific steps are as follows: S3.

1. Calculate the envelope signal a(t) of the sleeper excitation component by using the Hilbert transform: a(t) = |H[m(t)]| where H[·] represents the Hilbert transform, and |·| represents the absolute value operation; S3.2, determine the sliding window length Ls according to the sleeper spacing L and the sampling frequency f s : 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 the reciprocal of the sleeper excitation component; N represents the number of data intercepted by a sliding window with a length of Ls; a i (t) represents the i-th envelope value among them; μ is a constant coefficient, taking 10 -4 ; S3.

4. Classify and evaluate the sleeper support state according to the sleeper support state evaluation rules, and accurately identify the failure degree and location of the sleeper support.

2. The on-vehicle detection method for the support state of heavy-haul railway sleepers based on variational mode decomposition according to claim 1, wherein In step S1, the vertical acceleration signal of the car body is obtained by using a car body acceleration sensor installed directly above the center of the 2nd wheel pair of the heavy-duty truck.

3. The on-vehicle detection method for the support state of heavy-haul railway sleepers based on variational mode decomposition according to claim 1, characterized in that In step S1, the sampling frequency of the car body acceleration is set to 200 Hz to 300 Hz.

4. The on-vehicle detection method for the support state of heavy-haul railway sleepers based on variational mode decomposition according to claim 1, wherein In step S2.2, the variational mode decomposition method is used as an optimal band-pass filter to extract only 1 sleeper excitation component.

5. The vehicle-mounted detection method for the support state of heavy-haul railway sleepers based on variational mode decomposition according to claim 1, wherein In step S3.4, the sleeper support state level evaluation rules are shown in the following table:

Images