CN115384580B - Steel rail online detection method and system - Google Patents
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- 229910000831 Steel Inorganic materials 0.000 title claims abstract description 107
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B61—RAILWAYS
- B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
- B61L23/00—Control, warning or like safety means along the route or between vehicles or trains
- B61L23/04—Control, warning or like safety means along the route or between vehicles or trains for monitoring the mechanical state of the route
- B61L23/042—Track changes detection
- B61L23/044—Broken rails
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- G01N29/00—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
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- G—PHYSICS
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- G01N29/44—Processing the detected response signal, e.g. electronic circuits specially adapted therefor
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- G—PHYSICS
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Abstract
The invention relates to a steel rail online detection method and a system, wherein the method comprises the following steps: collecting an original signal and filtering; performing Fourier transform on the filtered signals to obtain a module value; calculating an effective value of a frequency spectrum of the filtered signal after Fourier transformation according to the modulus; determining a peak factor according to the effective value; and detecting the health state of the steel rail according to the peak value factor. The system comprises: a sensor, a filter and a receiver. The steel rail online detection method and the system provided by the invention can monitor the damage of the steel rail in real time in different degrees (rail head fracture, rail web fracture, complete steel rail and all steel rail fracture), so that the damage degree of the steel rail can be reported before the steel rail is completely broken, and the driving safety is improved.
Description
Technical Field
The invention belongs to the technical field of railway track state detection, and particularly relates to a steel rail online detection method and system.
Background
The health state of the steel rail is directly related to the running safety of the train, and the steel rail in the turnout area is easy to break due to repeated moving to provide steering for the train, so that the running safety of the train and the life and property safety of people are seriously threatened. At present, the detection of the steel rail in the turnout area is mainly carried out by adopting an ultrasonic flaw detector or a hand-push type steel rail flaw detection vehicle and other manual modes at a skylight point of railway operation. This approach requires a large amount of human resources, is inefficient, requires a train line, and cannot be detected during the train operation. With the popularization of high-speed trains and the improvement of the line occupancy rate, the impact, extrusion force and frequency of the trains on the steel rail are larger and larger, so that the service life of the steel rail is reduced, the occurrence probability of rail breakage accidents is continuously improved, and serious threat is caused to the running safety of the trains. In order to change the direction of the train running, the rails in the turnout area need to be repeatedly moved, and rail breakage is very easy to occur. Therefore, it is necessary to research a real-time on-line monitoring technology for the health state of the steel rail in the fork area.
At present, rail health condition monitoring is mainly divided into on-line monitoring and off-line detection. The on-line monitoring mainly depends on a track circuit, and the method can realize the monitoring of the complete broken state of the steel rail. However, in the switch area, because the slide plate electrically connects the switch rails with the stock rails, when the rails are broken, the electric signals can still detour to the receiving end of the track circuit through the slide plate, and the rail break monitoring cannot be realized. The off-line detection is mainly carried out by a large-scale steel rail flaw detection vehicle and a small flaw detector, the mode can only be carried out at a skylight point of train shutdown, line resources are required to be occupied, and whether the steel rail is broken or not cannot be monitored in real time. In addition, this method is inefficient and requires a lot of human resources.
Some on-line monitoring systems for the health state of the rail in the bifurcation area mainly depend on the amplitude value of the signal of the receiving end, and one disadvantage of the method is that the fluctuation range of the signal amplitude value of the receiving end is larger, sometimes the amplitude value is equivalent to the amplitude value when the rail breaks, and the state of the rail cannot be effectively monitored. The problem is mainly that the transducer arranged on the steel rail is greatly influenced by temperature, and when the temperature changes, the density of the steel rail changes, so that acoustic impedance between the transducer and the steel rail is not matched; in addition, the coupling state between the transducer and the steel rail also changes greatly along with the temperature, and finally the energy of the acoustic signal coupled to the steel rail fluctuates and the frequency shifts.
Therefore, it is needed to provide a method and a system for detecting the rail on line, which can solve the problems of frequency deviation and large energy fluctuation of acoustic signals transmitted on the rail when the temperature changes, and can realize all-weather real-time on-line monitoring of the health condition of the rail in the fork area on the premise of not interfering with the safety environment of the existing rail.
Disclosure of Invention
Aiming at the problems, the invention provides a steel rail online detection method, which is used for carrying out online detection on cracks of different degrees of steel rails based on peak factors of single-frequency point signal spectrums.
An on-line rail detection method, comprising:
collecting an original signal and filtering;
performing Fourier transform on the filtered signals to obtain a module value;
calculating an effective value of a frequency spectrum of the filtered signal after Fourier transformation according to the modulus;
determining a peak factor according to the effective value;
and detecting the health state of the steel rail according to the peak value factor.
Further, when the peak factor is larger than the first threshold value and not larger than the second threshold value, judging that the steel rail is completely broken; or,
when the peak factor is larger than the second threshold value and not larger than the third threshold value, judging that the steel rail is broken to the rail web; or,
when the peak factor is larger than the third threshold value and not larger than the fourth threshold value, judging that the steel rail is broken to the rail head; or,
and when the peak factor is larger than a fourth threshold value, judging that the steel rail is good.
Further, the specific calculation method for obtaining the modulus value by carrying out fourier transform on the filtered signal comprises the following steps:
for the filtered signal x filtered (n) fourier transforming to obtain X (k);
wherein k=0, 1,..n-1; n=0, 1, …, N-1, N being a predetermined value, X (k) being the kth value of the discrete spectrum;
calculating a module value X of the filtered signal after Fourier transformation abs (k)：
Where a (k) is the real part of X (k) and b (k) is the imaginary part of X (k).
Further, the specific calculation method for calculating the effective value of the frequency spectrum of the filtered signal after fourier transformation according to the modulus value is as follows:
wherein X is rms K is the total length of the spectrum, k=1, 2.
Further, the specific calculation method for determining the peak factor according to the effective value is as follows:
wherein C is a peak factor, X max Is the maximum value of the frequency spectrum of the filtered signal after Fourier transformation, X min Is the filtered signalThe minimum of the frequency spectrum after fourier transform.
The invention also provides a steel rail online detection system, which comprises:
the system includes a sensor, a filter, and a receiver;
the sensor is used for acquiring an original signal;
the filter is used for filtering the original signal;
the receiver is used for carrying out Fourier transform on the filtered signals to obtain a module value;
the receiver is further configured to calculate an effective value of a frequency spectrum of the filtered signal after fourier transform according to the modulus value;
the receiver is further configured to determine a crest factor based on the effective value;
the receiver is also used for detecting the health state of the steel rail according to the magnitude of the peak factor.
Further, the receiver is used for judging that the steel rail is completely broken when the peak factor is larger than a first threshold value and not larger than a second threshold value; or,
when the peak factor is larger than the second threshold value and not larger than the third threshold value, judging that the steel rail is broken to the rail web; or,
when the peak factor is larger than the third threshold value and not larger than the fourth threshold value, judging that the steel rail is broken to the rail head; or,
and when the peak factor is larger than a fourth threshold value, judging that the steel rail is good.
Further, the specific calculation for obtaining the modulus value by performing fourier transform on the filtered signal by the receiver includes:
for the filtered signal x filtered (n) fourier transforming to obtain X (k);
wherein k=0, 1, …, N-1; n=0, 1, …, N-1, N being a predetermined value, X (k) being the kth value of the discrete spectrum;
calculating a module value X of the filtered signal after Fourier transformation abs (k)：
Where a (k) is the real part of X (k) and b (k) is the imaginary part of X (k).
Further, the receiver is configured to calculate, according to the modulus value, a specific calculation of an effective value of a frequency spectrum of the filtered signal after fourier transform, where the specific calculation is:
wherein X is rms K is the total length of the spectrum, k=1, 2.
Further, the specific calculation of the receiver for determining the peak factor according to the effective value is as follows:
wherein C is a peak factor, X max Is the maximum value of the frequency spectrum of the filtered signal after Fourier transformation, X min Is the minimum value of the frequency spectrum of the filtered signal after Fourier transformation.
The invention has the following beneficial effects:
(1) When the rail in the fork area is broken, the alarm can be accurately and timely given, the broken rail can be conveniently and rapidly checked and replaced by the work, the real-time performance and the accuracy of rail inspection are improved, and the labor cost can be reduced;
(2) The method can monitor the damage of the steel rail in real time in different degrees (rail head fracture, rail web fracture, intact steel rail and all steel rail fracture) so as to report the damage degree of the steel rail before the steel rail is completely broken and improve the driving safety;
(3) The problem of signal fluctuation of the receiving end of the steel rail caused by environmental factors such as external temperature and the like is effectively avoided, and the problem of unstable energy of the receiving end calculated only by Fourier transform is solved;
(4) The method can realize all-weather real-time on-line monitoring of the health condition of the steel rail in the turnout area on the premise of not interfering the safety environment of the existing track.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention may be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 shows a schematic structural diagram of a rail on-line detection system according to an embodiment of the present invention;
FIG. 2 shows a flow chart of a rail on-line detection method according to an embodiment of the invention;
FIG. 3 shows a schematic diagram of an on-line detection of an original acoustic signal for a rail in accordance with an embodiment of the present invention;
FIG. 4 shows a graph of a high pass filter amplitude versus frequency characteristic in accordance with an embodiment of the present invention;
FIG. 5 shows a schematic diagram of an acoustic signal after filtering by a high pass filter according to an embodiment of the present invention;
FIG. 6 shows a spectrum diagram of a rail after on-line detection Fourier transform according to an embodiment of the present invention;
fig. 7 shows a graph of the peak factor for 4 different degrees of damage to a rail according to an embodiment of the invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The invention provides a steel rail on-line detection method and a system, which are used for detecting the health state of a steel rail by calculating the peak factor of a frequency spectrum after Fourier transformation of an acquired signal. The embodiment of the invention is exemplified by the detection of the health state of the steel rail in the fork area, but is not limited to the detection of the health state of the steel rail in the fork area, and the detection of the health state of the steel rail in any section can be applied to the invention.
In the detection of the health state of the rail in the fork area, numerous devices are included, such as transmitters, transducers, sensors, filters, receivers, data transmission modules, power supply modules, display terminals, etc. In order to realize the detection of the health state of the steel rail in the fork area, different devices have an interaction relationship.
The detection of the health state of the rail in the turnout region is illustrated by using several common devices, the connection relation between the related devices according to the detection of the health state of the rail in the turnout region is shown in fig. 1, fig. 1 shows a schematic diagram of the rail on-line detection system according to the embodiment of the invention, and it can be seen from fig. 1 that a transmitter and a transducer are connected with each other, a transducer and a sensor are connected with each other, and a sensor and a receiver are connected with each other in an outdoor rail side cabinet. The electrical signal is sent out by the transmitter and converted into an acoustic signal by the transducer, and the acoustic signal is transmitted to the receiver by the sensor. The acoustic signal is converted into a peak factor at a receiver, the receiver is connected with a data transmission module, the receiver transmits the peak factor value to the data transmission module, and the data transmission module transmits the received peak factor value to a display terminal positioned outdoors. The power supply module is connected with the receiver, the transmitter and the data transmission module and is used for supplying power to the receiver, the transmitter and the data transmission module. It should be noted that the embodiments of the present invention are only exemplified by the above-described apparatus, but are not limited to the above-described apparatus.
As shown in fig. 2, fig. 2 shows a flowchart of a rail online detection method according to an embodiment of the present invention, where the detection method includes: collecting an original signal and filtering; performing Fourier transform on the filtered signals to obtain a module value; calculating the effective value of the frequency spectrum of the filtered signal after Fourier transformation according to the modulus; determining a peak factor according to the effective value; and detecting the health state of the steel rail according to the peak value factor.
Specifically, the original signal (the original signal in this embodiment is an electrical signal) is generated by sending an electrical signal with the frequency of 10kHz through a transmitter, the electrical signal is converted into an acoustic signal through a transducer installed at the rail web at the root end of the fork area rail and coupled to the rail, the acoustic signal of the rail web at the tip end of the fork area rail is collected through a sensor, and the sensor is installed on the rail web at the tip end of the fork area rail. It should be noted that, in the embodiment of the present invention, the acoustic signal is a single-frequency point sinusoidal signal.
In the sampling and determining, the sampling rate must be more than 2 times of the highest frequency, theoretically, the higher the sampling rate, the better, and the equipment hardware cost is larger when the sampling rate is too high, so the sampling frequency of the system is set to 100kHz, the signal length is n=4096 points, and the original acoustic signal x (N) is obtained, where n=0, 1, …, N-1, x (N) represents the nth value of the time domain sampling. The original acoustic signal is shown in fig. 3, fig. 3 shows a schematic diagram of the on-line detection of the original acoustic signal by the steel rail, the horizontal axis represents time, and the vertical axis represents amplitude.
The collected rail web sound signal at the tip of the steel rail in the bifurcation area is filtered by a high-pass filter, and the high-pass filter can be a chebyshev high-pass filter, as shown in fig. 4, fig. 4 shows a graph of amplitude-frequency characteristics of the high-pass filter according to an embodiment of the invention, wherein the horizontal axis represents frequency, and the vertical axis represents amplitude.
In order to filter out low-frequency noise and interference generated by passing vehicles, the passband frequency of the filter is set to be 2kHz-100kHz, as shown in fig. 5, fig. 5 shows a schematic diagram of an acoustic signal after being filtered by the high-pass filter according to an embodiment of the invention, the horizontal axis represents time, and the vertical axis represents amplitude.
Further, fourier transforming the filtered signal to obtain a modulus value, which is specifically calculated by: for the filtered signal x filtered (n) fourier transforming to obtain X (k);
wherein k=0, 1, …, N-1; n=0, 1, …, N-1, N being a predetermined value, X (k) being the kth value of the discrete spectrum;
calculating a module value X of the filtered signal after Fourier transformation abs (k)：
Where a (k) is the real part of X (k) and b (k) is the imaginary part of X (k).
The fourier transformed result of the filtered signal is shown in fig. 6, fig. 6 shows a spectrogram of the rail on-line detection fourier transformed result according to an embodiment of the present invention, the horizontal axis represents frequency, and the vertical axis represents amplitude;
further, the specific calculation method for calculating the effective value of the frequency spectrum of the filtered signal after Fourier transformation according to the modulus value comprises the following steps:
wherein X is rms K is the total length of the spectrum, k=1, 2.
Further, the specific calculation method for determining the peak factor according to the effective value comprises the following steps:
wherein C is a peak factor, X max Is the maximum value of the frequency spectrum of the filtered signal after Fourier transformation, X min Is the minimum value of the frequency spectrum of the filtered signal after Fourier transformation.
The peak factor in the embodiments of the present invention refers to the ratio of the signal spectrum peak to the spectrum effective value (RMS), which represents the extreme extent of the peak in the waveform. The traditional calculation of the signal peak factor is to detect whether a pulse exists in a signal aiming at a time domain signal. The invention takes the frequency spectrum of the single-frequency point sine signal after Fourier transformation as the calculation object of the peak factor. For single frequency point sinusoidal signals, when the steel rail is intact, the frequency spectrum of the signal received by the receiving end should be a spectral line with concentrated energy. When the steel rail has cracks, sound waves can be reflected at the cracks, and the energy value of a signal received by a steel rail tip sensor can be reduced; and as the crack depth increases, the reflected wave energy increases and the direct wave energy decreases, resulting in a decrease in the maximum of the spectral energy and thus a decrease in the peak factor of the signal spectrum.
Further, detecting the health state of the steel rail according to the magnitude of the peak factor specifically includes:
when the peak factor is larger than the first threshold value and not larger than the second threshold value, judging that the steel rail is completely broken; or when the peak factor is larger than the second threshold value and is not larger than the third threshold value, judging that the steel rail is broken to the rail web; or when the peak factor is larger than the third threshold value and not larger than the fourth threshold value, judging that the steel rail is broken to the rail head; or when the peak factor is larger than a fourth threshold value, judging that the steel rail is good.
The embodiment of the invention collects multiple test data under 4 different damage degrees of the steel rail, wherein the test data comprises four states of complete steel rail, broken steel rail to rail head, broken steel rail to rail web and broken steel rail. And according to the algorithm steps of the invention, the peak factor of the acquired acoustic signals is calculated, the result is shown in fig. 6, and fig. 6 shows a graph of peak factors according to 4 different damage degrees of the steel rail, wherein the abscissa is the number of samples, and the ordinate is the peak factor. When the steel rail is in good condition, the peak factor value of the steel rail fluctuates around 25; when the rail breaks to the rail head, the peak factor value fluctuates around 18; when the steel rail breaks to the rail web, the peak factor value of the steel rail fluctuates around 9; when the rail breaks completely, its peak factor value fluctuates around 5. It can be seen that the deeper the rail is damaged, the smaller the peak factor value. The magnitude of this peak factor can therefore be used to describe the extent of rail damage. In addition, according to the experimental result, the embodiment of the invention sets the first threshold value as 0, the second threshold value as 8, the third threshold value as 14, the fourth threshold value as 22, and specifically detects different damage degrees of the steel rail as follows:
when the peak factor is more than 0 and less than or equal to 8, judging that the steel rail is completely broken; or when the peak factor is more than 8 and less than or equal to 14, judging that the steel rail is broken to the rail web; or when the peak factor is greater than 14 and less than or equal to 22, judging that the steel rail is broken to the rail head; or when the peak factor is greater than 22, judging that the steel rail is good.
The steel rail online detection method has obvious crack distinction of different damage degrees, and the accuracy of detection is greatly improved compared with the original algorithm. The detection accuracy calculation results are shown in table 1 below.
TABLE 1 crack detection accuracy for different degrees of damage
As can be seen from the table 1, the steel rail online detection method provided by the invention has high accuracy in detecting the damage degree of the steel rail. Specifically, the accuracy of detection of the intact rail and the broken rail to the rail head is up to 100%, and the accuracy of detection of the broken rail to the rail web and the complete broken rail is up to 99.83%.
The invention also provides a steel rail online detection system, as shown in fig. 1, fig. 1 shows a schematic structural diagram of the steel rail online detection system, and the system comprises:
a sensor, a filter (not shown in the figure, the filter being in the receiver) and a receiver;
the sensor is used for acquiring an original signal; the filter is used for filtering the original signal;
the receiver is used for carrying out Fourier transform on the filtered signals to obtain a module value; calculating the effective value of the frequency spectrum of the filtered signal after Fourier transformation according to the modulus; determining a peak factor according to the effective value; and detecting the health state of the steel rail according to the peak value factor.
Further, the receiver is used for judging that the steel rail is completely broken when the peak factor is larger than the first threshold value and not larger than the second threshold value; or when the peak factor is larger than the second threshold value and is not larger than the third threshold value, judging that the steel rail is broken to the rail web; or when the peak factor is larger than the third threshold value and not larger than the fourth threshold value, judging that the steel rail is broken to the rail head; or when the peak factor is larger than a fourth threshold value, judging that the steel rail is good.
Specifically, the specific calculation of the module value obtained by the receiver through fourier transformation of the filtered signal includes:
for the filtered signal x filtered (n) fourier transforming to obtain X (k);
wherein k=0, 1, …, N-1; n=0, 1, …, N-1, N being a predetermined value, X (k) being the kth value of the discrete spectrum;
calculating a module value X of the filtered signal after Fourier transformation abs (k)：
Where a (k) is the real part of X (k) and b (k) is the imaginary part of X (k).
The receiver is used for calculating the effective value of the frequency spectrum of the filtered signal after Fourier transformation according to the modulus value, and the specific calculation is as follows:
wherein X is rms K is the total length of the spectrum, k=1, 2.
The specific calculation of the receiver for determining the peak factor from the effective value is:
wherein C is a peak factor, X max Is the maximum value of the frequency spectrum of the filtered signal after Fourier transformation, X min Is the minimum value of the frequency spectrum of the filtered signal after Fourier transformation.
Further, the system further comprises: the device comprises a transmitter, a transducer, a data transmission module, a display terminal and a power supply module;
the original signal is generated by an electric signal sent by a transmitter; the transducer is used for converting an original signal sent by the transmitter into an acoustic signal and is coupled to the fork area steel rail;
and a data transmission module: the peak value factor is used for transmitting the peak value factor calculated in the receiver to the display terminal; the data transmission module in the invention can also adopt cable communication, and can also adopt NB-IoT (narrowband internet of things, narrow Band Internet of Things, NB-IoT) communication and PLC (programmable logic controller ) communication modes.
And (3) a display terminal: displaying peak factor data in the data transmission module, and judging the health state of the steel rail according to the peak factor;
and a power supply module: for powering receivers, transmitters, transducers, filters, sensors, data transmission modules and display terminals in the system.
The method comprises the steps that a transmitter is used for transmitting an original electric signal, converting the original electric signal into an acoustic signal through a transducer and coupling the acoustic signal to a fork area steel rail, the acoustic signal is received by a sensor arranged at the tip of the fork area steel rail after being transmitted in the steel rail, further the acoustic signal is subjected to high-pass filtering through a chebyshev filter, the filtered signal is subjected to Fourier transform in a receiver, a module value after the Fourier transform is calculated, the effective value of a frequency spectrum of the filtered signal after the Fourier transform is calculated according to the module value, further a peak factor is determined according to the effective value, and finally the health state of the steel rail is detected according to the size of the peak factor.
Although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (4)
1. An online steel rail detection method is characterized by comprising the following steps:
collecting an original signal and filtering; setting the sampling frequency to 100kHz, and obtaining an original acoustic signal x (N) with a signal length of n=4096 points, wherein n=0, 1, …, N-1, x (N) represents an nth value of time domain sampling;
performing Fourier transform on the filtered signals to obtain a module value; the specific calculation method comprises the following steps:
for the filtered signal x filtered (n) fourier transforming to obtain X (k);
wherein k=0, 1, …, N-1; n=0, 1, …, N-1, N being a predetermined value, X (k) being the kth value of the discrete spectrum;
calculating a module value X of the filtered signal after Fourier transformation abs (k)：
Wherein a (k) is the real part of X (k), and b (k) is the imaginary part of X (k);
calculating an effective value of a frequency spectrum of the filtered signal after Fourier transformation according to the modulus; the specific calculation method comprises the following steps:
wherein X is rms K is the total length of the spectrum, k=1, 2 …, K, which is the effective value of the spectrum after fourier transformation of the filtered signal;
determining a peak factor according to the effective value, wherein the peak factor is the ratio between a spectrum peak value and the effective value of the spectrum, and the peak factor is adopted to represent the extreme degree in the waveform; the specific calculation method of the peak factor comprises the following steps:
wherein C is a peak factor, X max Is the maximum value of the frequency spectrum of the filtered signal after Fourier transformation, X min The minimum value of the frequency spectrum of the filtered signal after Fourier transformation;
and detecting the health state of the steel rail according to the peak value factor.
2. The steel rail on-line detecting method according to claim 1, wherein,
when the peak factor is larger than the first threshold value and not larger than the second threshold value, judging that the steel rail is completely broken; or,
when the peak factor is larger than the second threshold value and not larger than the third threshold value, judging that the steel rail is broken to the rail web; or,
when the peak factor is larger than the third threshold value and not larger than the fourth threshold value, judging that the steel rail is broken to the rail head; or,
and when the peak factor is larger than a fourth threshold value, judging that the steel rail is good.
3. An on-line rail detection system, the system comprising:
a sensor, a filter, and a receiver;
the sensor is used for acquiring an original signal;
the filter is used for filtering the original signal;
the receiver is used for carrying out Fourier transform on the filtered signals to obtain a module value; the specific calculation comprises the following steps:
for the filtered signal x filtered (n) fourier transforming to obtain X (k);
wherein k=0, 1, …, N-1; n=0, 1, …, N-1, N being a predetermined value, X (k) being the kth value of the discrete spectrum;
calculating a module value X of the filtered signal after Fourier transformation abs (k)：
Wherein a (k) is the real part of X (k), and b (k) is the imaginary part of X (k);
the receiver is further configured to calculate an effective value of a frequency spectrum of the filtered signal after fourier transform according to the modulus value; the specific calculation is as follows:
wherein X is rms K is the total length of the spectrum, k=1, 2 …, K, which is the effective value of the spectrum after fourier transformation of the filtered signal;
the receiver is further configured to determine a peak factor according to the effective value, where the peak factor is a ratio between a spectrum peak value and the effective value of the spectrum, and the peak factor is used to represent an extreme degree in the waveform; the peak factor is specifically calculated as:
wherein C is a peak factor, X max Is the maximum value of the frequency spectrum of the filtered signal after Fourier transformation, X min The minimum value of the frequency spectrum of the filtered signal after Fourier transformation;
the receiver is also used for detecting the health state of the steel rail according to the magnitude of the peak factor.
4. A steel rail on-line detection system according to claim 3, wherein,
the receiver is used for judging that the steel rail is completely broken when the peak factor is larger than a first threshold value and not larger than a second threshold value; or,
when the peak factor is larger than the second threshold value and not larger than the third threshold value, judging that the steel rail is broken to the rail web; or,
when the peak factor is larger than the third threshold value and not larger than the fourth threshold value, judging that the steel rail is broken to the rail head; or,
and when the peak factor is larger than a fourth threshold value, judging that the steel rail is good.
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