CN109543550B - Steel rail acceleration signal identification method and identification device - Google Patents
Steel rail acceleration signal identification method and identification device Download PDFInfo
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Abstract
The embodiment of the invention provides a method and a device for identifying a steel rail acceleration signal, wherein the method for identifying the steel rail acceleration signal comprises the following steps: acquiring an actually measured acceleration signal of a steel rail; carrying out wavelet packet decomposition on the acceleration measured signal to obtain a wavelet packet coefficient of each scale; processing the wavelet packet coefficient to obtain an axle characteristic coefficient; and determining a data pickup point sequence of the steel rail acceleration signal to be recognized corresponding to the actually measured acceleration signal according to the axle characteristic coefficient, and determining the steel rail acceleration signal to be recognized according to the data pickup point sequence. According to the embodiment of the invention, the acceleration of the steel rail is determined by performing wavelet packet decomposition on the acceleration signal of the steel rail to obtain the axle characteristic sequence, the resolution of high-frequency decomposition is improved, the characteristic of high-frequency vibration of the wheel rail is met, the acceleration signal does not need to be reconstructed, the uncertainty of a sampling value under the field complex excitation condition is eliminated, and the efficiency and the accuracy of integrally obtaining an effective signal are improved.
Description
Technical Field
The invention relates to railway engineering steel rail testing, in particular to a steel rail acceleration signal identification method and a steel rail acceleration signal identification device.
Background
The steel rail is a main part of the whole railway steel rail system, the steel rail is in direct contact with wheel pairs of a train, when the wheels are rolled, the acceleration of the steel rail generated by the action of the wheel pairs on the steel rail directly determines the contact mode of the wheel and the rail and transmits the response to a lower structure of the steel rail, and the acceleration of the steel rail directly influences the running safety and stability of the rolling stock. Therefore, in order to reveal the rail acceleration of the rail in service, the rail acceleration is usually measured directly by pasting an accelerometer on the rail.
However, in the steel rail serving as a structure in which the wheel sets are in direct contact, due to factors such as more wheel sets, frequent load, complex wheel-rail contact relationship and the like, in the service process, actually measured acceleration signals generally have multiple components, such as excitation of the wheel sets at the acceleration measurement points of the steel rail directly acting on the wheel sets, excitation of the wheel sets at the measurement points of the front carriage and the rear carriage, and the like.
Therefore, it is necessary to identify and acquire the rail acceleration signal generated by the action of the train direct acting wheel on the rail.
At present, for signal denoising, a lot of digital filters are generally used, such as butterworth filters, chebyshev filters and the like, and technologies such as median filtering and the like also exist, however, no better method for removing the vibration high-frequency interference signals of the wheel-track system exists.
Disclosure of Invention
The embodiment of the invention aims to provide a steel rail acceleration signal identification method and a steel rail acceleration signal identification device, and aims to solve the problem that the existing actually-measured acceleration signal has influence on the acceleration of a steel rail due to multiple factors.
In order to achieve the above object, an embodiment of the present invention provides a method for identifying a rail acceleration signal, where the method for identifying a rail acceleration signal includes: acquiring an actually measured acceleration signal of a steel rail; carrying out wavelet packet decomposition on the acceleration measured signal to obtain wavelet packet coefficients of all scales; processing the wavelet packet coefficients to obtain axle characteristic coefficients; and determining a data pickup point sequence of the acceleration signal of the steel rail to be identified, which corresponds to the actually measured acceleration signal, according to the axle characteristic coefficient, and determining the acceleration signal of the steel rail to be identified according to the data pickup point sequence.
Optionally, the method for identifying a steel rail acceleration signal is characterized in that the obtaining of an actual measurement signal of the steel rail acceleration includes: and acquiring the measured acceleration signal of the steel rail through an acceleration sensor arranged on the steel rail.
Optionally, the performing wavelet packet decomposition on the acceleration measured signal includes selecting a mother wavelet basis to perform decomposition on the acceleration measured signal for several times, where the mother wavelet basis is an asymmetric wavelet basis from top to bottom.
Optionally, the up-down asymmetric mother wavelet basis is a discrete Meyer wavelet.
Optionally, the obtaining the axle characteristic coefficient includes: and processing the wavelet packet coefficients, and determining the axle characteristic coefficients according to a graph change rule of the wavelet packet coefficients, wherein the graph change rule is that the wavelet packet coefficients form a plurality of groups of curves which take a preset number of obvious peaks as a group and have the same change trend.
Optionally, the determining the data pick-up point sequence includes: determining the point at which the distinct peak is located as the data pick-up point.
Optionally, the determining the rail acceleration signal includes: the data pickup point sequence corresponds to the actually measured acceleration signal, wherein the steel rail acceleration signal to be identified is the acceleration signal of the data pickup point and the actually measured acceleration signal corresponding point; and acquiring the acceleration amplitude of the corresponding point to determine the acceleration of the steel rail.
According to another aspect of the embodiments of the present invention, there is also provided a rail acceleration recognition apparatus including: the sampling module is used for acquiring an actually measured signal of the acceleration of the steel rail; the analysis module is used for carrying out wavelet packet decomposition on the acceleration measured signal to obtain a wavelet packet coefficient of each scale; analyzing the wavelet packet coefficient to obtain an axle characteristic coefficient; and determining a data pickup point sequence of the steel rail acceleration signal corresponding to the acceleration measured signal according to the axle characteristic coefficient, and determining the steel rail acceleration signal according to the data pickup point sequence.
Optionally, the performing, by the analysis module, wavelet packet decomposition on the acceleration measured signal includes: and selecting a mother wavelet basis to decompose the acceleration measured signal for a plurality of times, wherein the mother wavelet basis is an upper and lower asymmetrical wavelet basis.
According to a third aspect of the present invention, there is provided a machine-readable storage medium having stored thereon instructions for causing a machine to perform any one of the methods of rail acceleration signal identification described above in this application.
According to the embodiment of the invention, the acceleration of the steel rail is determined by performing wavelet packet decomposition on the acceleration signal of the steel rail to obtain the axle characteristic sequence, the resolution of high-frequency decomposition is improved, the characteristic of high-frequency vibration of the wheel rail is met, the acceleration signal does not need to be reconstructed, the uncertainty of a sampling value under the field complex excitation condition is eliminated, and the efficiency and the accuracy of integrally obtaining an effective signal are improved.
Additional features and advantages of embodiments of the invention will be set forth in the detailed description which follows.
Drawings
The accompanying drawings, which are included to provide a further understanding of the embodiments of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the embodiments of the invention without limiting the embodiments of the invention. In the drawings:
FIG. 1 is a flow chart of rail acceleration signal identification provided by an embodiment of the present invention;
FIG. 2 is a graph of measured rail acceleration signals provided by an embodiment of the present invention;
FIGS. 3 and 4 are schematic diagrams of phi (x) and psi (x) in a mother wavelet based Meyer wavelet provided by an embodiment of the present invention, respectively;
FIG. 5 is an enlarged view of a portion of signals in a measured rail acceleration signal provided in an embodiment of the present invention;
FIG. 6 is a graph of axle characteristic coefficients provided by an embodiment of the present invention;
FIG. 7 is a schematic diagram of characteristic coefficients of axles when a train passes through according to an embodiment of the present invention;
FIG. 8 is a schematic diagram of a data pick-up point pick-up result provided by an embodiment of the present invention;
fig. 9 is a schematic diagram of a pick-up point sequence corresponding to an original signal sequence according to an embodiment of the present invention; and
fig. 10 is a block diagram of a rail acceleration signal recognition apparatus according to an embodiment of the present invention.
Description of the reference numerals
10 sampling module 20 analysis module
Detailed Description
The following detailed description of embodiments of the invention refers to the accompanying drawings. It should be understood that the detailed description and specific examples, while indicating embodiments of the invention, are given by way of illustration and explanation only, not limitation.
In the embodiment of the present invention, without being particularly described, the rail acceleration refers to a rail vibration acceleration generated by an action of a train load on a rail when an axle rolls the rail; the wheel set refers to the position of the train in direct contact with the steel rail; excitation refers to the influence of various factors on the acceleration of the steel rail, for example, excitation of a wheel pair directly acting at an acceleration measurement point refers to the vibration acceleration generated by the action of the train wheel pair on the steel rail at the acceleration measurement point.
Fig. 1 is a flowchart of rail acceleration signal identification provided in an embodiment of the present invention, and as shown in fig. 1, a method for identifying rail acceleration provided in an embodiment of the present invention includes the following steps:
s101, acquiring an actually measured acceleration signal of a steel rail
And according to the field conditions, carrying out arrangement and actual measurement on field acceleration measurement points to obtain a field steel rail acceleration actual measurement signal.
In order to obtain the on-site rail acceleration, the arrangement scheme and the selection of measuring equipment are considered, so that the on-site signal noise interference is reduced, and the signal to noise ratio is improved. The factors mainly considered for the arrangement of the acceleration or other testing equipment according to the actual situation on site include: 1. whether a placing space of the data acquisition equipment exists on site or not is judged; 2. whether there is power supply, etc. An on-site actual measurement acceleration signal diagram obtained through on-site actual measurement in the embodiment of the invention is shown in fig. 2.
S102, obtaining wavelet packet coefficients of all scales
And carrying out multi-scale wavelet packet decomposition on the field acceleration response signal to obtain the wavelet packet coefficient of each scale. In this embodiment, the mother wavelet is exemplarily calculated using a discrete Meyer wavelet, with the order of calculation being 8.
Wherein the wavelet packet decomposition is defined as:
in multi-scale wavelet packet analysis, a scale subspace V is defined j Sum wavelet subspace W j Where j is a scale factor (j ∈ Z), then the orthogonal decomposition of Hilbert space V j+1 ＝V j ∪W j . Scale functions are respectively
And psi (x), the scale equation is
Wherein h is k And g k A low-pass filter and a high-pass filter respectively, k is a translation factor, k belongs to Z and represents k is an integer,
and ψ (x) is the mother wavelet base, based, </or > selected for embodiments of the present invention>
For the scale function, ψ (x) is a wavelet function.
FIG. 3 and FIG. 4 are diagrams illustrating a Meyer wavelet based mother wavelet according to an embodiment of the present invention
And psi (x), for the vertical acceleration of the heavy haul railway steel rail, the actually measured acceleration signal is a symmetrical graph along a time axis, which is not beneficial to obtaining the axle information. For symmetric signals, upper and lower asymmetric wavelet bases are used, and the obtained wavelet coefficients are upper and lower asymmetric values. Therefore, the embodiment of the invention pertinently selects the mother wavelet base with upper and lower asymmetry: the Meyer wavelet.
Introduction of new expressions
u 1 = ψ (x), then = shall be satisfied +>
Wherein u 0 (x)，u 1 (x) Respectively represent pair
And a function, h, obtained by further decomposition of ψ (x) k And g k A low pass filter and a high pass filter, respectively, k being a translation factor and k being an integer.
Through u 0 (x)，u 1 (x)，h k ，g k A set of wavelet packet functions u may be defined at a fixed scale n (n =0,1,2, …), and thus the wavelet packet decomposition formula can be expressed as:
wherein u is n Representing a wavelet packet, n =2l or n =2l +1, l =0,1,2, ….
Therefore, compared with wavelet decomposition, wavelet packet decomposition further divides and resolves the spectrum window which is widened along with the increase of the scale.
Fig. 5 is an enlarged view of a part of signals in an actually measured steel rail acceleration signal provided in an embodiment of the present invention, as shown in fig. 5, when the actually measured steel rail acceleration signal is used as a first-layer structure in which wheel rails are in direct contact with each other, due to factors such as a large number of wheel sets, frequent loads, complex wheel-rail contact relationships, and the like, the actually measured acceleration signal generally has a plurality of components, such as excitation of a wheel set directly acting at an acceleration measurement point, excitation of front and rear wheel pairs at measurement points, and the like, so that excitation of each wheel set in the actually measured acceleration signal is not well known, and it is difficult to identify an axle position in the figure, and thus reading accuracy is limited.
In order to extract the excitation components of the corresponding wheel pairs of the train to the steel rails, decomposition is carried out in a wavelet packet analysis mode, and the actually measured acceleration signals are processed.
S103, obtaining characteristic coefficients of the axle
And processing the wavelet packet coefficient to obtain an axle characteristic coefficient, wherein the processed wavelet packet coefficient is different from an original signal, and each vehicle, each bogie and even each wheel pair can be accurately described.
Fig. 6 is a characteristic coefficient diagram of the axle according to the embodiment of the present invention, as shown in fig. 6, the abscissa is a point sequence, the ordinate is a corresponding wavelet coefficient value, and is a dimensionless value, and it can be seen from the diagram that a peak occurs which takes 4 distinct peaks as a group and conforms to the acceleration response law when the vehicle passes through the rail. As can be seen from fig. 6, the purpose of separating the axle position information from the acceleration signal is achieved by using the wavelet packet decomposition method.
Fig. 7 is a schematic diagram of axle characteristic coefficients when a train passes through according to an embodiment of the present invention, as shown in fig. 7, a lower curve in fig. 7 is an enlarged view of a curve in fig. 6, and it can be seen from the diagram that each train axle has a better correspondence with a signal peak value, which indicates a correspondence relationship between the axle characteristic coefficients and an actual train passing process. Because the graphs are clear, a plurality of simple methods can be used for selecting the characteristic points, and sequences of all wheel sets of the whole train passing by are extracted, such as: and (4) a peak value extraction method.
S104, determining a data pick-up point
And determining a data pick-up point sequence of the acceleration signal of the steel rail to be identified, which corresponds to the actually measured acceleration signal, according to the axle characteristic coefficient.
Fig. 8 is a schematic diagram of the data pick-up point pick-up result provided by the embodiment of the invention, as shown in fig. 8, in which a dotted line is an axle characteristic coefficient, and a solid point is a pick-up point, i.e., a corresponding excitation point when an axle is rolled.
S105, determining the acceleration signal of the steel rail to be identified
And determining the steel rail acceleration signal to be identified according to the data pickup point sequence.
Through the steps S101-S104, the signal sequence of the excitation of each axle to the steel rail when the rolling stock passes is obtained, the data pickup point sequence corresponds to the actually measured acceleration signal, the acceleration amplitude at the corresponding point is collected, and the acquisition of the acceleration response under the excitation of the corresponding wheel pair can be completed. Fig. 9 is a schematic diagram of a pick-up point sequence corresponding to an original signal sequence provided in an embodiment of the present invention, as shown in fig. 9, a thin solid line in the diagram is an actually measured acceleration signal, a thick dotted line is a wavelet coefficient diagram, and a solid point on the actually measured signal is a rail acceleration signal identified through the above process.
According to another aspect of the embodiments of the present invention, there is also provided a rail acceleration recognition apparatus, and fig. 10 is a block diagram of the rail acceleration signal recognition apparatus provided in the embodiments of the present invention, and as shown in fig. 10, the rail acceleration recognition apparatus includes: the sampling module 10 is used for acquiring an actually measured signal of the acceleration of the steel rail; the analysis module 20 is configured to perform wavelet packet decomposition on the acceleration measured signal to obtain a wavelet packet coefficient of each scale; analyzing the wavelet packet coefficient to obtain an axle characteristic coefficient; and determining a data pickup point sequence of the steel rail acceleration signal corresponding to the acceleration measured signal according to the axle characteristic coefficient, and determining the steel rail acceleration signal according to the data pickup point sequence.
Preferably, the wavelet packet decomposition of the acceleration measured signal by the analysis module includes: and selecting a mother wavelet basis to decompose the acceleration measured signal for a plurality of times, wherein the mother wavelet basis is an upper and lower asymmetrical wavelet basis.
Other implementation details of the rail acceleration recognition device are the same as those of the rail acceleration recognition method, and are not described herein again.
According to the embodiment of the invention, the acceleration of the steel rail is determined by performing wavelet packet decomposition on the acceleration signal of the steel rail to obtain the axle characteristic sequence, so that the resolution of high-frequency decomposition is improved, and the characteristic of high-frequency vibration of the wheel rail is met. And the rail acceleration signal is decomposed by adopting the upper and lower asymmetric mother wavelet bases to obtain a peak which accords with the acceleration response rule when the vehicle passes through the rail, and each train axle has better correspondence with the signal peak value, thereby achieving the purpose of separating the axle position information from the acceleration signal. Acceleration signals do not need to be reconstructed, uncertainty of sampling values under the complex excitation condition on site is eliminated, and efficiency and accuracy of obtaining effective signals integrally are improved.
Although the embodiments of the present invention have been described in detail with reference to the accompanying drawings, the embodiments of the present invention are not limited to the details of the above embodiments, and various simple modifications can be made to the technical solutions of the embodiments of the present invention within the technical idea of the embodiments of the present invention, and the simple modifications all belong to the protection scope of the embodiments of the present invention.
It should be noted that the various features described in the above embodiments may be combined in any suitable manner without departing from the scope of the invention. In order to avoid unnecessary repetition, the embodiments of the present invention do not describe every possible combination.
Those skilled in the art will understand that all or part of the steps in the method according to the above embodiments may be implemented by a program, which is stored in a storage medium and includes several instructions to enable a single chip, a chip, or a processor (processor) to execute all or part of the steps in the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
In addition, any combination of various different implementation manners of the embodiments of the present invention is also possible, and the embodiments of the present invention should be considered as disclosed in the embodiments of the present invention as long as the combination does not depart from the spirit of the embodiments of the present invention.
Claims (8)
1. A rail acceleration signal identification method is characterized by comprising the following steps:
acquiring an actually measured acceleration signal of a steel rail;
carrying out wavelet packet decomposition on the acceleration measured signal to obtain a wavelet packet coefficient of each scale;
processing the wavelet packet coefficients to obtain axle characteristic coefficients; and
determining a data pickup point sequence of the steel rail acceleration signal to be recognized corresponding to the actually measured acceleration signal according to the axle characteristic coefficient, and determining the steel rail acceleration signal to be recognized according to the data pickup point sequence;
the obtaining of the axle characteristic coefficient includes: processing the wavelet packet coefficients, and determining the axle characteristic coefficients according to a graph change rule of the wavelet packet coefficients, wherein the graph change rule is that the wavelet packet coefficients form a plurality of groups of curves with the same change trend, and the groups of curves are one group of preset number of obvious peak values;
the determining the sequence of data pickup points comprises: determining the point at which the distinct peak is located as the data pick-up point.
2. The method for identifying a rail acceleration signal according to claim 1, wherein the acquiring a measured rail acceleration signal includes: and acquiring the measured acceleration signal of the steel rail through an acceleration sensor arranged on the steel rail.
3. The method for identifying a rail acceleration signal according to claim 1, wherein the wavelet packet decomposition of the acceleration measured signal comprises:
selecting mother wavelet basis to decompose the acceleration measured signal for a plurality of times,
wherein, the mother wavelet base is asymmetric up and down.
4. The rail acceleration signal identification method according to claim 3, wherein the mother wavelet basis with the upper and lower asymmetry is a discrete Meyer wavelet.
5. The rail acceleration signal identification method of claim 1, wherein the determining the rail acceleration signal comprises:
the data pickup point sequence corresponds to the actually measured acceleration signal, wherein the steel rail acceleration signal to be identified is the acceleration signal of the data pickup point and the actually measured acceleration signal corresponding point; and acquiring the acceleration amplitude at the corresponding point to determine the acceleration of the steel rail.
6. A rail acceleration recognition apparatus for performing the rail acceleration signal recognition method according to any one of claims 1 to 5, wherein the rail acceleration recognition apparatus includes:
the sampling module is used for acquiring an actually measured signal of the acceleration of the steel rail;
the analysis module is used for carrying out wavelet packet decomposition on the acceleration measured signal to obtain a wavelet packet coefficient of each scale; analyzing the wavelet packet coefficient to obtain an axle characteristic coefficient; and determining a data pickup point sequence of the steel rail acceleration signal corresponding to the acceleration measured signal according to the axle characteristic coefficient, and determining the steel rail acceleration signal according to the data pickup point sequence.
7. The rail acceleration recognition device of claim 6, wherein the analysis module performing wavelet packet decomposition on the acceleration measured signal comprises: and selecting a mother wavelet basis to decompose the acceleration measured signal for a plurality of times, wherein the mother wavelet basis is an asymmetric mother wavelet basis from top to bottom.
8. A machine-readable storage medium having instructions stored thereon for causing a machine to perform the method of identifying a rail acceleration signal of any one of claims 1 to 5.
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