CN114330429B - Rail scratch identification method, device, system, equipment and storage medium - Google Patents
Rail scratch identification method, device, system, equipment and storage medium Download PDFInfo
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Abstract
Provided herein are a rail scratch recognition method, device, system, apparatus, and storage medium, wherein the method comprises: performing energy conversion on the obtained vortex signals of the steel rail to obtain energy signals corresponding to the vortex signals; judging whether the amplitude of the energy signal is larger than an adaptive energy threshold corresponding to the energy signal; when the amplitude value is smaller than the self-adaptive energy threshold value, judging that the steel rail is not scratched; and when the amplitude value is greater than or equal to the self-adaptive energy threshold value, judging that the rail is scratched. The method can compare the energy signal obtained by converting the eddy current signal with the self-adaptive energy threshold value, can eliminate the influence of factors such as difference of conductivity and permeability of the steel rail caused by states such as rail corrugation and rust on the scratch judgment, realizes automatic identification of the rail scratch, improves the scratch identification efficiency, and greatly improves the accuracy of scratch identification.
Description
Technical Field
The invention relates to the technical field of nondestructive testing, in particular to a method, a device, a system, equipment and a storage medium for identifying rail scratch.
Background
The service state of the steel rail serving as an important part of the high-speed railway directly influences the transportation safety of the high-speed railway. The steel rail scratch is one of common rail diseases, high temperature is generated due to friction with a contact surface of a wheel rail, and meanwhile, high contact stress reduces the phase transition temperature of a material, so that the metal structure on the top surface of the rail head is subjected to phase transition, the pearlite structure is converted into a hard and brittle white layer, the white layer structure is easy to break and fracture under the action of external force, and finally cracks or falling blocks are formed. The abrasion of the high-speed railway rail can influence the smoothness of the rail, so that the impact force of the wheel rail is increased sharply, the rail structure is possibly damaged, and the rail is possibly broken and the running safety of the train is influenced when the abrasion is serious.
The existing method for identifying the rail scratch mainly depends on an ultrasonic flaw detection system and a visual inspection system which are carried on a rail flaw detection vehicle; ultrasonic flaw detection technology can only find scratches and cannot evaluate the area and depth of the scratches; the inspection system can evaluate the area of the scratch, but it is difficult to evaluate the depth of the scratch. Therefore, for the detected suspected scratch, the site check is also needed by combining with a manual work, and the scratch depth are determined by a method of a feeler gauge, but the feeler gauge mode is only suitable for the depth measurement of the scratch with the formed block, and the severity of the scratch with the formed white layer tissue without the block cannot be accurately estimated. That is, the existing scratch detection method has problems of low detection efficiency and inaccurate detection.
In view of the above, it is an object of the present invention to provide a method, apparatus, system, device and storage medium for identifying scratches on a rail, which can improve the efficiency and accuracy of identifying scratches.
Disclosure of Invention
In view of the foregoing problems of the prior art, it is an object herein to provide a method, apparatus, system, device and storage medium for identifying rail scratches, so as to solve the problems of low efficiency and inaccuracy in identifying rail scratches in the prior art.
In order to solve the technical problems, the specific technical scheme is as follows:
in a first aspect, provided herein is a rail scratch identification method comprising:
performing energy conversion on the obtained vortex signals of the steel rail to obtain energy signals corresponding to the vortex signals;
Judging whether the amplitude of the energy signal is larger than an adaptive energy threshold corresponding to the energy signal;
When the amplitude value is smaller than the self-adaptive energy threshold value, judging that the steel rail is not scratched;
and when the amplitude value is greater than or equal to the self-adaptive energy threshold value, judging that the steel rail is scratched.
Specifically, after judging that the steel rail has scratches, the method further comprises the following steps:
Determining parameters of the scratch based on the eddy current signal, the energy signal, and an array sensor for acquiring the eddy current signal, the parameters including a length, a width, and a depth of the scratch;
Determining the shape and type of the scratch according to the parameters; the shapes include elongated shapes and oval shapes, and the types of scratches include superficial white layer tissue, deep white layer combinations, and chipping.
Further, the determining the parameter of the scratch based on the eddy current signal, the energy signal, and an array sensor for acquiring the eddy current signal comprises:
acquiring a position interval corresponding to the amplitude of the energy signal meeting a preset condition as a first characteristic value;
acquiring the number of channels of the array sensor corresponding to the scratch as a second characteristic value;
calculating the difference value between the maximum value and the minimum value of the amplitude of the eddy current signal in the position interval as a third characteristic value;
And respectively determining the length, the width and the depth of the scratch according to the first characteristic value, the second characteristic value and the third characteristic value.
Further, determining the type of the scratch from the parameter includes:
Judging whether the third characteristic value is larger than a first depth threshold value and smaller than or equal to a second depth threshold value;
determining that the type of the scratch is deep white tissue when the third feature value is greater than the first depth threshold and less than or equal to the second depth threshold;
when the third characteristic value is smaller than or equal to the first depth threshold value, determining that the scratch type is superficial white tissue;
and when the third characteristic value is larger than the second depth threshold value, determining the scratch type as a block drop.
Specifically, the obtained vortex signal of the steel rail is calculated through the following formula to obtain the energy signal:
Wherein E (N) is an energy signal, the value range of N is 1-M+1-N, M is the sequence length of the eddy current signal, N is the width of a calculation window, and x (M) is the eddy current signal detected at M.
Further, the energy threshold is obtained by:
calculating the average energy of the energy signal to obtain an initial energy threshold, wherein the calculation formula of the average energy is as follows:
Where Th is the initial energy threshold and E (i) is the energy of the ith signal;
Correcting the initial energy threshold to obtain the self-adaptive energy threshold, wherein a correction formula is as follows:
THR＝a×Th+b；
where THR is the adaptive energy threshold, a is the amplification factor, and b is the bias factor.
Preferably, before calculating the acquired eddy current signal of the rail to obtain the energy signal, the method further comprises:
and filtering and denoising the eddy current signals.
Further, the filtering and denoising processing for the eddy current signal is further as follows:
Band-pass filtering the eddy current signal through finite impulse response of an equiripple method;
and carrying out wavelet denoising on the eddy current signal subjected to band-pass filtering treatment by using a db3 base-based minimum maximum criterion soft threshold method.
In a second aspect, provided herein is a rail abrasion identification apparatus comprising:
the conversion module is used for carrying out short-time energy conversion on the obtained vortex signals of the steel rail to obtain energy signals corresponding to the vortex signals;
The judging module is used for judging whether the amplitude of the energy signal is larger than an adaptive energy threshold value of the energy signal or not;
the first judging module is used for judging that the steel rail is not scratched when the amplitude value is smaller than the energy threshold value;
And the second judging module is used for judging that the steel rail is scratched when the amplitude value is larger than or equal to the energy threshold value.
In a third aspect, there is also provided herein a rail abrasion identification system comprising a probe, a probe support structure, a signal excitation unit, a signal acquisition processing unit, and a controller;
The probe supporting structure is connected with the probe and is used for fixing the probe so as to keep the distance between the probe and the surface of the steel rail to be detected stable;
An array sensor is arranged on one side of the probe, which is close to the steel rail, and is connected with the signal excitation unit and the signal acquisition processing unit and is used for generating an alternating magnetic field under the alternating excitation of the signal excitation unit and feeding back the detected eddy current signals generated by the steel rail under the alternating magnetic field to the signal acquisition processing unit;
The signal acquisition processing unit is connected with the signal excitation unit and the controller and is used for regulating and controlling the parameters of alternating current excitation of the signal excitation unit under the control of the controller and feeding back the acquired eddy current signals to the controller through conditioning and amplification;
the controller is configured to identify rail scratches based on the received conditioned amplified vortex signals.
In a fourth aspect, there is also provided a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the method provided by the above technical solution when executing the computer program.
In a fifth aspect, there is also provided herein a storage medium storing a computer program which, when executed by a processor, implements a method as provided in the above-mentioned technical solution.
By adopting the technical scheme, the method, the device, the system, the equipment and the storage medium for identifying the steel rail scratch can compare the energy signal obtained by converting the vortex signal with the self-adaptive energy threshold value, the self-adaptive energy threshold value corresponds to the energy signal one by one, the influence of factors such as the environment where different steel rails are located, the difference of conductivity and permeability of different steel rails on the scratch judgment can be eliminated, the automatic identification of the steel rail scratch is realized, the scratch identification efficiency is improved, and meanwhile, the accuracy of the scratch identification is greatly improved.
The foregoing and other objects, features and advantages will be apparent from the following more particular description of preferred embodiments, as illustrated in the accompanying drawings.
Drawings
In order to more clearly illustrate the embodiments herein or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described below, it being obvious that the drawings in the following description are only some embodiments herein and that other drawings may be obtained according to these drawings without inventive effort to a person skilled in the art.
Fig. 1 is a schematic step diagram of a rail scratch recognition method provided in an embodiment herein;
FIGS. 2 (a) to 2 (f) are schematic diagrams of several untreated vortex signals;
Fig. 3 (a) to 3 (f) are schematic diagrams of eddy current signals obtained by performing band-pass filtering and wavelet denoising on the eddy current signals shown in fig. 2 (a) to 2 (f);
FIG. 4 is a schematic diagram illustrating steps of another rail scratch identification method provided by embodiments herein;
FIG. 5 illustrates a flow chart of steps of a method of determining an scratch size parameter provided by embodiments herein;
FIG. 6 is a schematic diagram of acquiring a first characteristic value of an energy signal;
FIG. 7 is a schematic diagram of the principle of the array sensor for detecting scratches on a steel rail;
FIG. 8 is a schematic diagram of acquiring a third characteristic value of the eddy current signal corresponding to the energy signal of FIG. 6;
FIG. 9 illustrates a flow chart of steps of a method of determining a type of scratch provided by embodiments herein;
fig. 10 is a schematic structural view of a rail scratch recognition device according to an embodiment of the present disclosure;
FIG. 11 is a schematic diagram of a rail scratch identification system provided in embodiments herein;
Fig. 12 shows a schematic structural diagram of a computer device provided in an embodiment herein.
Description of the drawings:
10. a probe;
20. A probe support structure;
30. a signal excitation unit;
40. a signal acquisition processing unit;
50. a controller;
60. A steel rail;
101. A conversion module;
102. A judging module;
103. a first determination module;
104. A second determination module;
1202. a computer device;
1204. a processor;
1206. a memory;
1208. A driving mechanism;
1210. An input/output module;
1212. An input device;
1214. An output device;
1216. a presentation device;
1218. A graphical user interface;
1220. A network interface;
1222. a communication link;
1224. a communication bus.
Detailed Description
The following description of the embodiments of the present disclosure will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are only some, but not all embodiments of the disclosure. All other embodiments, based on the embodiments herein, which a person of ordinary skill in the art would obtain without undue burden, are within the scope of protection herein.
It should be noted that the terms "first," "second," and the like in the description and claims herein and in the foregoing figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments described herein may be capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, apparatus, article, or device that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed or inherent to such process, method, article, or device.
The existing method for identifying the rail scratch mainly depends on an ultrasonic flaw detection system and a visual inspection system which are carried on a rail flaw detection vehicle. However, ultrasonic flaw detection technology only can detect scratches and cannot evaluate the area and depth of the scratches; the inspection system can evaluate the area of the scratch, but it is difficult to evaluate the depth of the scratch. Therefore, on-site review is also required in combination with manual work, for example, the method of determining the scratch and the depth of the scratch by using a feeler gauge, but the feeler gauge mode is only suitable for the depth measurement of the scratch with the formed block, and the severity of the scratch with the formed white layer tissue without the block cannot be accurately estimated. Therefore, the existing detection method has the problems of low detection efficiency and low accuracy.
In order to solve the problems, embodiments herein provide a method, an apparatus, a system, a device and a storage medium for identifying scratches of a steel rail, which can improve the efficiency and accuracy of identifying scratches. Fig. 1 is a schematic step diagram of a rail scratch identification method provided in embodiments herein, the present disclosure provides method operational steps as described in the examples or flowcharts, but may include more or fewer operational steps based on conventional or non-inventive labor. The order of steps recited in the embodiments is merely one way of performing the order of steps and does not represent a unique order of execution. When a system or apparatus product in practice is executed, it may be executed sequentially or in parallel according to the method shown in the embodiments or the drawings. As shown in fig. 1, the method may include:
s110: and performing energy conversion on the obtained vortex signals of the steel rail to obtain energy signals corresponding to the vortex signals.
The eddy current signals in the embodiments of the present description are detected by an array sensor provided on the probe. For example, in the embodiment of the present disclosure, a1×4 array sensor is used, as shown in fig. 7, where 4 array sensors (channel numbers 1, 2, 3, and 4, respectively) disposed side by side are adapted to the width direction of the track, and together with the rail scratch recognition system, the rail surface is detected while moving along the length direction of the track (4 sets of eddy current signals are generated for each detection position).
The detection principle is as follows: the probe generates an alternating magnetic field, the steel rail is in the alternating magnetic field and generates vortex-like induction alternating current (namely vortex signals), and the distribution and the size of the vortex signals can be influenced by factors such as the conductivity, the magnetic permeability, the existing defects, the size and the shape of the defects of the steel rail. And obtaining the defect characteristics of the detected steel rail by analyzing the information such as distribution, size, phase and the like in the vortex signals. The eddy current detection adopted between the array sensor and the steel rail is a non-contact detection method, but the surface and near-surface structural state of the steel rail can be detected due to the influence of the skin effect.
S120: and judging whether the amplitude of the energy signal is larger than an energy threshold adaptive to the energy signal.
In the embodiment of the specification, each energy signal is compared with each energy threshold value, so that the influence of eddy current signals in different rail surface states on scratch judgment can be eliminated, and the accuracy of scratch identification is improved.
S130: when the amplitude is smaller than the energy threshold, judging that the steel rail is not scratched;
s140: and when the amplitude value is greater than or equal to the energy threshold value, judging that the steel rail is scratched.
According to the rail scratch identification method provided by the embodiment of the specification, the detected vortex signals of the rail are converted into the energy signals, and the energy signals are compared with the self-adaptive energy threshold value corresponding to the energy signals one by one, so that the automatic identification of whether the rail is scratched or not is realized, and compared with the existing mode of using the unified judgment threshold value, the influence of factors such as the environment where different rails are located, the conductivity permeability of the rail and the like on scratch judgment can be eliminated, and the accuracy of scratch identification is greatly improved.
In some possible embodiments, before the short-time energy conversion of the acquired eddy current signal of the rail in step S110, the method further includes:
and filtering and denoising the eddy current signals.
In some preferred embodiments, the eddy current signal is bandpass filtered by an Equiripple (FIR) finite impulse response (Finite Impulse Response;
And performing wavelet denoising on the eddy current signal subjected to band-pass filtering treatment by using a db3 base-based minimum maximum criterion soft threshold method.
The FIR filter has accurate linear phase and the system is stable; the equal ripple method is based on a maximum error minimization criterion, so that the maximum error between the frequency domain characteristics of the FIR filter and the frequency domain characteristics of the ideal filter is minimum, the amplitude has equal fluctuation in the stop band and the pass band, and the error is uniformly distributed in the whole frequency band.
The upper and lower cut-off frequencies of the filter can be set and adjusted according to the detection frequency, the scratch signal frequency obtained according to the historical data, the impurity signal frequency and the like, so that influences of irrelevant clutter signals are filtered to the greatest extent, and more accurate scratch signals are extracted.
DbN wavelets have better regularities, so that the signal reconstruction process is smoother. N represents the vanishing moment of the wavelet, the larger the number of the vanishing moment is, the smoother the wavelet is, and the better the frequency band dividing effect is; however, the time domain tight support property is weakened, the calculated amount is greatly increased, and the real-time property is deteriorated. Thus, the dB3 wavelet is selected in the embodiment of the present specification taking into account the amount of computation and the localization capability of the frequency domain. Of course, in practical use, the inspector can select other filtering methods and other dbN wavelets according to practical needs.
As shown in fig. 2 (a) to 2 (f), there are several untreated eddy current signals, i.e. eddy current signals detected at different rail surface positions; as shown in fig. 3 (a) to 3 (f), the signals shown in fig. 2 (a) to 2 (f) are eddy current signals obtained by sequentially performing bandpass filtering processing and wavelet denoising processing.
Referring to fig. 2 (a) and fig. 3 (a), it can be seen that the signal amplitude fluctuation is very small, and after filtering and denoising, the signal becomes smooth overall, and it can be inferred that the rail surface of the detection position corresponding to the signal is smooth; referring to fig. 2 (b) and fig. 3 (b), the amplitude of the processed signal is smaller but the amplitude of the processed signal is not large, and the signal morphology is basically better preserved, so that it can be inferred that the eddy current signal has scratches on the rail surface at the detection position of 1000mm to 1200 mm; comparing fig. 2 (c) with fig. 3 (c), it can be known that the eddy current signal has a portion with a few sections of fluctuation, the fluctuation amplitude of the fluctuation portion is not large, the signal is smoother as a whole than before processing, it can be inferred that the rail surface at the detection position corresponding to the signal has a rust phenomenon, the magnetic permeability of the rail at the rust position is different from the magnetic permeability of the rail at the non-rust position, and the rust thickness of the rail surface at different positions is different, so that the eddy current signal has fluctuation of different degrees; comparing fig. 2 (d) with fig. 3 (d), the condition of the eddy current signals before and after treatment is similar to that of the eddy current signals before and after treatment shown in fig. 2 (c) and fig. 3 (c), the track surface at the detection position corresponding to the signals also has a corrosion problem, and the corrosion degree is more serious than that of the track surface corresponding to fig. 2 (c) and fig. 3 (c); comparing FIG. 2 (e) with FIG. 3 (e), it can be seen that the amplitude of the eddy current signal before processing periodically fluctuates, the fluctuation amplitude is larger, the amplitude after processing fluctuates up and down at the 0mV datum line, which indicates that the low frequency part of the eddy current signal is filtered, and the rail surface of the detection position corresponding to the signal is presumed to have the wave grinding phenomenon; compared with the signal waveforms in fig. 2 (f) and fig. 3 (f), the signal waveforms before and after the processing have small amplitude change, but the signal morphology remains relatively intact, and it is known that the rail surface at the detection position corresponding to the signal has a wave abrasion phenomenon and scratches around 1100mm-1200 mm.
In combination with the above example, in the embodiment of the present disclosure, band-pass filtering is performed on the eddy current signal by using an isopulse method to limit impulse response, and wavelet denoising is performed by using a db 3-based minimum maximum criterion soft threshold method, so that impurity signals can be filtered, interference of different states of the rail surface on the eddy current signal can be eliminated, and signal extraction accuracy can be improved. After the filtering and denoising processes, there are interference signals such as rust and wave grinding which need to be filtered out in the eddy current signals, and these are not signal objects which need to be identified by the rail scratch identification method provided in the embodiment of the present specification. Thus, in the present description embodiments, adaptive energy thresholds are provided for filtering out these interfering signals.
Specifically, in step S110, the energy conversion is performed on the eddy current signal, and the energy signal may be obtained by the following formula:
Wherein E (N) is an energy signal, the value range of N is 1-M+1-N, N is the width of a calculation window, M is the sequence length of the eddy current signal, and x (M) is the eddy current signal detected at the detection point M.
For example, in the embodiment of the present disclosure, the detection frequency of the eddy current signal is 1 (1/mm), and the number of the ripple points of the scratch signal is about 4 to 10 according to the history data experience, and the value of the calculated window width N may be set to 10, which is as follows:
……
therefore, each energy signal in the embodiment of the specification corresponds to the average value of the absolute values of the amplitude values of the eddy current signals measured by the N test points at the corresponding detection positions, has a noise reduction effect, and can avoid the reduction of the follow-up scratch recognition accuracy caused by the abnormality of the signal of the single detection point.
It should be noted that, in the actual scratch detection scene, the energy signal may also be obtained by converting in other manners, for example, the energy signal of each detection point is obtained by taking the absolute value of the amplitude of the eddy current signal corresponding to the detection point; or the absolute values of the amplitude values of the eddy current signals are taken from N detection points near the detection point, and then weighting calculation is carried out to obtain the method.
In some possible embodiments, the energy threshold value that is adaptive to the energy signal may be obtained by:
calculating the average energy of the energy signal to obtain an initial energy threshold, wherein the calculation formula of the average energy is as follows:
Where Th is the initial energy threshold and E (i) is the energy of the ith signal;
Correcting the initial energy threshold to obtain the self-adaptive energy threshold, wherein a correction formula is as follows:
THR＝a×Th+b；
Where THR is the adaptive energy threshold, a is the amplification factor, and b is the bias factor. The coefficients a and b may be determined in training based on the actual scratch signal. For example, the value of a may be 7, and the value of b may be 0.3, although other data may be set according to the actual scratch recognition requirement. By amplifying and biasing the initial energy threshold, the initial energy threshold is corrected, and the energy signal is compared with the self-adaptive energy threshold obtained by correction to carry out scratch identification, so that the influence of interference noise such as rust and wave mill in the eddy current signal on scratch identification can be eliminated, and the accuracy of scratch identification is improved.
Further, as shown in fig. 4, in the embodiment of the present specification, in step S140: when the amplitude is greater than or equal to the adaptive energy threshold, after determining that the rail is scratched, the method further comprises:
s410: based on the eddy current signal, the energy signal, and an array sensor for acquiring the eddy current signal, parameters of the scratch are determined, including a length, a width, and a depth of the scratch.
The length refers to the size of the scratch in the length direction along the track, the width refers to the size of the scratch in the width direction along the track, and the depth refers to the size of the scratch in the vertical direction along the track. Therefore, the rail scratch recognition method provided by the embodiment of the specification not only can accurately recognize and judge whether the rail is scratched or not; compared with the prior art that the scratch area and the scratch depth cannot be estimated and manual review is needed, the identification method provided by the embodiment of the specification can greatly reduce the workload of detection personnel, improve the detection efficiency and avoid errors caused by human factors in the detection process.
S420: determining the shape and type of the scratch according to the parameters; the shapes include elongated shapes and oval shapes, and the types of scratches include shallow white tissue, deep white tissue, and flaking.
The type of scratch can be used to analyze the severity of the scratch; the scratch shape may be used to analyze the cause of the scratch where, for example, an elongated scratch may be caused by a train wheel locking and an oval scratch may be caused by a wheel spinning. Of course, the above few are merely illustrative, and in practice, track scratches are mostly caused by a combination of factors. Subsequent rail repair and repair can be facilitated by analysis of the scratch shape and type.
The steel rail scratch recognition method provided by the embodiment of the specification can also recognize the shape and the type of scratches, is favorable for analyzing the formation reason of the scratches and evaluating the severity of the scratches, so that the efficiency and the accuracy of scratch recognition can be improved, and the comprehensive scratch recognition can be realized.
As shown in fig. 5, in some specific embodiments, step S410: based on the eddy current signal, the energy signal, and an array sensor for acquiring the eddy current signal, determining a dimensional parameter of the scratch may be:
S510: acquiring a position interval corresponding to the amplitude of the energy signal meeting a preset condition as a first characteristic value; the first characteristic value is noted as PP.
Specifically, fig. 6 is a schematic diagram of acquiring a first characteristic value of an energy signal. For example, if the first preset condition is that the amplitude is greater than or equal to 0.2mV and the duration is 10mm, the first characteristic value PP of the energy signal shown in fig. 6 is [990, 1100]. Of course, other setting manners of the preset condition are also possible.
Note that, the dashed line in fig. 6 indicates an adaptive energy threshold corresponding to the energy signal one-to-one, and it can be seen that the energy signal amplitude is greater than or equal to the adaptive energy threshold in the vicinity of the [1020, 1080] position interval, that is, the energy signal has scratches, so as to determine the scratch parameter and identify the shape and type of the scratches.
S520: acquiring the number of channels of the array sensor corresponding to the scratch as a second characteristic value; the first eigenvalue is noted NN.
Fig. 7 is a schematic diagram of the principle of the array sensor for detecting the scratch of the steel rail. As shown in FIG. 7, the array sensor used in the embodiment of the specification has 4 channels, and each channel is placed on the surface of the tread of the steel rail side by side during flaw detection, wherein the 1 st channel is close to the vicinity of the light band of the steel rail, and the 4 th channel is close to the vicinity of the rail angle. For example, when the eddy current signals detected by the 1 st channel and the 2 nd channel are analyzed at a certain detection position of the steel rail to obtain that the corresponding rail surfaces are scratched, and the rail surfaces corresponding to the eddy current signals detected by the 3 rd channel and the 4 th channel are not scratched, the second characteristic value NN is 2, and the width of the scratch is the detection width of the 1 st channel and the 2 nd channel of the array sensor at the detection position of the steel rail. It should be noted that the second eigenvalue should be the number of channels of the adjacent array sensor: when the 1 st and 4 th channels detect scratches and the 2 nd and 3 rd channels do not detect scratches, the parameter analysis should be performed as two scratches, and the second characteristic value corresponding to the two scratches is 1.
S530: calculating the difference value between the maximum value and the minimum value of the amplitude of the eddy current signal in the position interval as a third characteristic value; the first characteristic value is noted as MM.
FIG. 8 is a schematic diagram of acquiring a third characteristic value of the eddy current signal corresponding to the energy signal of FIG. 6. As shown in fig. 8, in the position interval [990, 1100] indicated by PP, the difference between the maximum value and the minimum value of the obtained eddy current signal amplitude is MM, that is, the deepest depth of the scratch in the position interval is obtained. In the embodiment of the present disclosure, the eigenvalues MM and PP are the maximum values detected by the 4 channel array sensors.
S540: and respectively determining the length, the width and the depth of the scratch according to the first characteristic value, the second characteristic value and the third characteristic value. Namely, the length of the scratch is determined according to the first characteristic value, the width of the scratch is determined according to the second characteristic value and the depth of the scratch is determined according to the third characteristic value, so that the scratch size parameter is determined, and the gap of the scratch size identification in the prior art is filled.
In some possible embodiments, S420: determining the shape and type of the scratch according to the parameters; the shapes include elongated shapes and oval shapes, and the types of scratches include shallow white tissue, deep white combinations and chipping, which may be:
and determining the shape of the scratch according to the first characteristic value and the second characteristic value.
Specifically, the length of the location interval determined by the first characteristic value may be calculated in combination with table 1, and the shape of the scratch may be determined in combination with the length and the second characteristic value.
TABLE 1
The division of the length of the location interval calculated according to the first characteristic value and the association relation between the division of the location interval and the number of the second characteristic values in table 1 are all exemplary, and a person skilled in the art can adapt according to the actual scratch recognition requirement.
And determining the type of the scratch according to the third characteristic value.
Specifically, as shown in fig. 9, the type of scratch may be determined as follows:
s910: judging whether the third characteristic value is larger than a first depth threshold value and smaller than or equal to a second depth threshold value;
For example, the first depth threshold is an equivalent amplitude of 50mV, the second depth threshold is 100mV, and of course, the first depth threshold and the second depth threshold may be set as other data parameters.
S920: determining that the type of the scratch is deep white tissue when the third feature value is greater than the first depth threshold and less than or equal to the second depth threshold;
s930: when the third characteristic value is smaller than or equal to the first depth threshold value, determining that the scratch type is superficial white tissue;
s940: and when the third characteristic value is larger than the second depth threshold value, determining the scratch type as a block drop.
By the rail scratch recognition method provided by the specification, not only can scratches be detected and recognized, but also the shape and the type of the scratches can be determined, and the method has positive effects on subsequent rail maintenance.
Besides the processing method, the three-dimensional image of the scratch can be drawn based on the third characteristic value of the vortex signal obtained by detecting each detection point of each channel of the array sensor, so as to assist in identifying the shape and the severity of the scratch, thereby analyzing the formation cause of the scratch more accurately, selecting more effective rail maintenance measures and improving the safety of the rail driving and the travelling comfort of passengers.
As shown in fig. 10, the embodiment of the present disclosure further provides a rail scratch recognition device, including:
the conversion module 101 is used for performing short-time energy conversion on the obtained vortex signals of the steel rail to obtain energy signals corresponding to the vortex signals;
a determining module 102, configured to determine whether the amplitude of the energy signal is greater than an adaptive energy threshold for the energy signal;
a first determining module 103, configured to determine that the rail is not scratched when the amplitude is less than the energy threshold;
And the second judging module 104 is used for judging that the steel rail is scratched when the amplitude value is greater than or equal to the energy threshold value.
The beneficial effects obtained by the device provided by the embodiment of the present disclosure are consistent with those obtained by the above method, and will not be described herein.
As shown in fig. 11, the embodiment of the present disclosure further provides a rail abrasion identification system, including a probe 10, a probe support structure 20, a signal excitation unit 30, a signal acquisition processing unit 40, and a controller 50;
the probe support structure 20 is connected with the probe 10 and is used for fixing the probe 10 so as to keep the surface distance between the probe 10 and the steel rail 60 to be detected stable;
An array sensor is arranged on one side of the probe 10, which is close to the steel rail 60, and is connected with the signal excitation unit 30 and the signal acquisition processing unit 40, and is used for generating an alternating magnetic field under the alternating excitation of the signal excitation unit 30 and feeding back the detected eddy current signals generated by the steel rail 60 under the alternating magnetic field to the signal acquisition processing unit 40;
the signal acquisition processing unit 40 is connected with the signal excitation unit 30 and the controller 50, and is used for regulating and controlling parameters of alternating current excitation of the signal excitation unit 30 under the control of the controller 50, and conditioning, amplifying and feeding back the acquired eddy current signals to the controller 50;
The controller 50 is configured to identify rail scratches based on the received conditioned amplified vortex signals.
The beneficial effects obtained by the system provided by the embodiments of the present disclosure are consistent with those obtained by the above method, and will not be described herein.
As shown in fig. 12, for a computer device provided by embodiments herein, the computer device 1202 may include one or more processors 1204, such as one or more Central Processing Units (CPUs), each of which may implement one or more hardware threads. Computer device 1202 may also include any memory 1206 for storing any kind of information, such as code, settings, data, etc. For example, and without limitation, memory 1206 may include any one or more of the following combinations: any type of RAM, any type of ROM, flash memory devices, hard disks, optical disks, etc. More generally, any memory may store information using any technique. Further, any memory may provide volatile or non-volatile retention of information. Further, any memory may represent fixed or removable components of computer device 1202. In one case, when the processor 1204 executes associated instructions stored in any memory or combination of memories, the computer device 1202 can perform any of the operations of the associated instructions. The computer device 1202 also includes one or more drive mechanisms 1208 for interacting with any memory, such as a hard disk drive mechanism, optical disk drive mechanism, and the like.
The computer device 1202 may also include an input/output module 1210 (I/O) for receiving various inputs (via an input device 1212) and for providing various outputs (via an output device 1214). One particular output mechanism may include a presentation device 1216 and an associated Graphical User Interface (GUI) 1218. In other embodiments, input/output module 1210 (I/O), input device 1212, and output device 1214 may not be included as only one computer device in a network. Computer device 1202 may also include one or more network interfaces 1220 for exchanging data with other devices via one or more communication links 1222. One or more communication buses 1224 couple the above-described components together.
The communication link 1222 may be implemented in any manner, for example, through a local area network, a wide area network (e.g., the internet), a point-to-point connection, etc., or any combination thereof. The communication link 1222 may include any combination of hardwired links, wireless links, routers, gateway functions, name servers, etc., governed by any protocol or combination of protocols.
Corresponding to the method in fig. 1, 4 to 5 and 9, embodiments herein also provide a computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the above method.
Embodiments herein also provide a computer readable instruction wherein the program therein causes the processor to perform the method as shown in fig. 1, 4-5 and 9 when the processor executes the instruction.
It should be understood that, in the various embodiments herein, the sequence number of each process described above does not mean the sequence of execution, and the execution sequence of each process should be determined by its functions and internal logic, and should not constitute any limitation on the implementation process of the embodiments herein.
It should also be understood that in embodiments herein, the term "and/or" is merely one relationship that describes an associated object, meaning that three relationships may exist. For example, a and/or B may represent: a exists alone, A and B exist together, and B exists alone. In addition, the character "/" herein generally indicates that the front and rear associated objects are an "or" relationship.
Those of ordinary skill in the art will appreciate that the elements and algorithm steps described in connection with the embodiments disclosed herein may be embodied in electronic hardware, in computer software, or in a combination of the two, and that the elements and steps of the examples have been generally described in terms of function in the foregoing description to clearly illustrate the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present disclosure.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, and are not repeated herein.
In the several embodiments provided herein, it should be understood that the disclosed systems, devices, and methods may be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of the units is merely a logical function division, and there may be additional divisions when actually implemented, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted or not performed. In addition, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices, or elements, or may be an electrical, mechanical, or other form of connection.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the elements may be selected according to actual needs to achieve the objectives of the embodiments herein.
In addition, each functional unit in the embodiments herein may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solutions herein are essentially or portions contributing to the prior art, or all or portions of the technical solutions may be embodied in the form of a software product stored in a storage medium, including several instructions to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the embodiments herein. And the aforementioned storage medium includes: a usb disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
Specific examples are set forth herein to illustrate the principles and embodiments herein and are merely illustrative of the methods herein and their core ideas; also, as will be apparent to those of ordinary skill in the art in light of the teachings herein, many variations are possible in the specific embodiments and in the scope of use, and nothing in this specification should be construed as a limitation on the invention.
Claims (11)
1. A method of identifying rail scratches comprising:
performing energy conversion on the obtained vortex signals of the steel rail to obtain energy signals corresponding to the vortex signals;
Judging whether the amplitude of the energy signal is larger than an adaptive energy threshold corresponding to the energy signal, wherein the energy threshold is obtained through the following steps:
calculating the average energy of the energy signal to obtain an initial energy threshold, wherein the calculation formula of the average energy is as follows:
Wherein Th is an initial energy threshold, E (i) is the energy of the ith signal, M is the sequence length of the eddy current signal, and N is the calculated window width;
Correcting the initial energy threshold to obtain the self-adaptive energy threshold, wherein a correction formula is as follows:
THR＝a×Th+b；
wherein THR is an adaptive energy threshold, a is an amplification coefficient, and b is a bias coefficient;
When the amplitude value is smaller than the self-adaptive energy threshold value, judging that the steel rail is not scratched;
and when the amplitude value is greater than or equal to the self-adaptive energy threshold value, judging that the steel rail is scratched.
2. The method of claim 1, wherein after determining that the rail is scratched, the method further comprises:
Determining parameters of the scratch based on the eddy current signal, the energy signal, and an array sensor for acquiring the eddy current signal, the parameters including a length, a width, and a depth of the scratch;
Determining the shape and type of the scratch according to the parameters; the shapes include elongated shapes and oval shapes, and the types of scratches include superficial white layer tissue, deep white layer combinations, and chipping.
3. The method of claim 2, wherein the determining the parameters of the scratch based on the eddy current signal, the energy signal, and an array sensor for acquiring the eddy current signal comprises:
acquiring a position interval corresponding to the amplitude of the energy signal meeting a preset condition as a first characteristic value;
acquiring the number of channels of the array sensor corresponding to the scratch as a second characteristic value;
calculating the difference value between the maximum value and the minimum value of the amplitude of the eddy current signal in the position interval as a third characteristic value;
And respectively determining the length, the width and the depth of the scratch according to the first characteristic value, the second characteristic value and the third characteristic value.
4. The method of claim 3, wherein determining the type of scratch from the parameter further comprises:
Judging whether the third characteristic value is larger than a first depth threshold value and smaller than or equal to a second depth threshold value;
Determining that the type of the scratch is deep white tissue when the third feature value is greater than the first depth threshold and less than or equal to the second depth threshold;
when the third characteristic value is smaller than or equal to the first depth threshold value, determining that the scratch type is superficial white tissue;
and when the third characteristic value is larger than the second depth threshold value, determining the scratch type as a block drop.
5. The method of claim 1, wherein the energy signal is obtained by calculating the acquired eddy current signal of the rail by the following formula:
Wherein E (N) is an energy signal, the value range of N is 1-M+1-N, M is the sequence length of the eddy current signal, N is the width of a calculation window, and x (M) is the eddy current signal detected at M.
6. The method of claim 1, wherein prior to calculating the acquired eddy current signal of the rail to obtain the energy signal, the method further comprises:
and filtering and denoising the eddy current signals.
7. The method of claim 6, wherein said filtering and denoising said eddy current signal further comprises:
Band-pass filtering the eddy current signal through finite impulse response of an equiripple method;
and carrying out wavelet denoising on the eddy current signal subjected to band-pass filtering treatment by using a db3 base-based minimum maximum criterion soft threshold method.
8. A rail scratch recognition device, comprising:
the conversion module is used for carrying out short-time energy conversion on the obtained vortex signals of the steel rail to obtain energy signals corresponding to the vortex signals;
The judging module is used for judging whether the amplitude of the energy signal is larger than an adaptive energy threshold value of the energy signal, and the energy threshold value is obtained through the following steps:
calculating the average energy of the energy signal to obtain an initial energy threshold, wherein the calculation formula of the average energy is as follows:
Wherein Th is an initial energy threshold, E (i) is the energy of the ith signal, M is the sequence length of the eddy current signal, and N is the calculated window width;
Correcting the initial energy threshold to obtain the self-adaptive energy threshold, wherein a correction formula is as follows:
THR＝a×Th+b；
wherein THR is an adaptive energy threshold, a is an amplification coefficient, and b is a bias coefficient;
the first judging module is used for judging that the steel rail is not scratched when the amplitude value is smaller than the energy threshold value;
And the second judging module is used for judging that the steel rail is scratched when the amplitude value is larger than or equal to the energy threshold value.
9. The rail scratch recognition system is characterized by comprising a probe, a probe supporting structure, a signal excitation unit, a signal acquisition processing unit and a controller;
The probe supporting structure is connected with the probe and is used for fixing the probe so as to keep the distance between the probe and the surface of the steel rail to be detected stable;
An array sensor is arranged on one side of the probe, which is close to the steel rail, and is connected with the signal excitation unit and the signal acquisition processing unit and is used for generating an alternating magnetic field under the alternating excitation of the signal excitation unit and feeding back the detected eddy current signals generated by the steel rail under the alternating magnetic field to the signal acquisition processing unit;
The signal acquisition processing unit is connected with the signal excitation unit and the controller and is used for regulating and controlling the parameters of alternating current excitation of the signal excitation unit under the control of the controller and feeding back the acquired eddy current signals to the controller through conditioning and amplification;
the controller is configured to identify rail scratches based on the received conditioned amplified vortex signal and the rail scratch identification method of any of claims 1 to 7.
10. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method of any one of claims 1 to 7 when the computer program is executed.
11. A computer readable storage medium, characterized in that the computer readable storage medium stores a computer program which, when executed by a processor, implements the method according to any one of claims 1 to 7.
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| CN116039713B (en) * | 2022-12-30 | 2023-08-01 | 合肥德泰科通测控技术有限公司 | Intelligent damage identification management system for steel rail |
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