CN114216704A - Track vibration damping pad parameter detection method - Google Patents
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Abstract
The utility model discloses a track vibration damping pad parameter detection method, which aims to solve the problem that the detection of the numerical value change of various sensors in the running process of a train cannot be realized, and comprises the following steps: s1: arranging a detection unit on the vibration damping pad, and acquiring key parameter data; s2: carrying out qualitative analysis on the acquired key parameter data to obtain effective data; s3: fitting and twice integrating the effective data to obtain track rigidity irregularity information; s4: calculating the upper and lower offsets of the track according to the effective data, and detecting whether the track meets the standard; s5: and judging whether the damping pad achieves the corresponding setting effect according to the results of the step S3 and the step S4. The utility model has the beneficial effects that: can detect each item sensor numerical value change among the train driving process through implanted sensor structure to judge whether track damping pad reaches corresponding settlement effect, be convenient for carry out real-time supervision to the damping pad, and judge whether report to the police according to the monitoring result.
Description
Technical Field
The utility model relates to the field of damping pads, in particular to a track damping pad parameter detection method.
Background
The utility model detects the value change of each sensor in the running process of a train by using an implanted sensor structure of pressure, displacement, acceleration, vibration and the like, thereby judging whether the track vibration damping pad achieves the corresponding set effect, being convenient for monitoring the vibration damping pad in real time and judging whether to give an alarm according to the monitoring result.
An improved track damping base plate disclosed in Chinese patent literature, which is disclosed under the publication number CN211689686U, comprises a base plate body, wherein the base plate body is made of rubber and is of a rectangular solid flat plate structure with a certain thickness, the lower surface of the base plate body is a plane, the upper surface of the base plate body is provided with a plurality of damping bosses arranged in an array shape, the damping bosses are of a truncated cone structure, a cylindrical structure or a ridge structure, each damping boss comprises a first damping boss and a second damping boss, and the height of the first damping boss is lower than that of the second damping boss; therefore, the elastic lug boss is arranged between the steel rail and the fastener or between the fastener and the sleeper, can better buffer high-speed vibration and impact generated when vehicles pass through the rail, effectively protects the roadbed and the sleeper, better reduces noise, provides superposition of different rigidity through combination of the elastic lug bosses with various specifications and sizes, increases the rigidity of the base plate and improves the vibration reduction effect. The disadvantages are as follows: the detection of the numerical value change of each sensor in the running process of the train cannot be realized.
Disclosure of Invention
The utility model mainly aims to solve the problem that the detection of the numerical value change of each sensor in the running process of a train cannot be realized, and provides a track vibration damping pad parameter detection method which can realize the detection of the numerical value change of each sensor in the running process of the train.
In order to achieve the purpose, the utility model adopts the following technical scheme:
a method for detecting parameters of a track damping pad comprises the following steps:
s1: arranging a detection unit on the vibration damping pad, and acquiring key parameter data;
s2: carrying out qualitative analysis on the acquired key parameter data to obtain effective data;
s3: fitting and twice integrating the effective data to obtain track rigidity irregularity information;
s4: calculating the upper and lower offsets of the track according to the effective data, and detecting whether the track meets the standard;
s5: and judging whether the damping pad achieves the corresponding setting effect according to the results of the step S3 and the step S4.
In step S1, the vibration damping pad is provided with a detection unit, and the implanted sensor structure is used to detect the changes in the values of various sensors during the running of the train, so as to determine whether the rail vibration damping pad has a corresponding setting effect, and determine whether to alarm according to the result.
In the step S2, the effective data is obtained by performing qualitative analysis on the key parameter data and performing denoising processing, where the effective data includes effective acceleration data.
In the step S3, after the effective acceleration data is calculated and analyzed, information about whether the rigidity of the left and right rails is smooth can be obtained, which is convenient for detecting the condition that the rigidity of the left and right rails is smooth.
In step S4, the vertical offset of the left and right rails during the running of the train is calculated from the effective acceleration data, so as to realize real-time detection of the rails, automatically determine whether the rails meet the standards, and indirectly monitor the damping pads.
In step S5, whether the vibration damping pad has a corresponding setting effect is determined by analyzing and processing the track vertical offset and track stiffness irregularity information, so as to implement real-time monitoring of the vibration damping pad and determine whether to alarm according to the monitoring result.
Preferably, the detecting unit in step S1 includes an acceleration detecting unit and a displacement detecting unit; the key parameter data in step S1 includes acceleration data and displacement data.
The acceleration detection unit is used for detecting the acceleration data; the displacement detection unit includes a path displacement sensor for detecting a displacement in an acceleration direction.
Preferably, step S2 includes the steps of:
s21: qualitatively analyzing the acquired key parameter data, and screening the key parameter data to be processed;
s22: filtering the screened key parameter data to filter out low-frequency components;
s23: and obtaining effective data after filtering.
In step S21, the collected key parameter data is qualitatively analyzed, and effective data and useless signals in the key parameter data can be obtained through a qualitative analysis formula, so as to screen out the key parameter data that needs to be processed.
In step S22, the noise signal is removed by filtering processing, so as to obtain valid data, which is convenient for improving reliability and accuracy of the key parameter data.
Preferably, the formula for qualitatively analyzing the collected key parameter data in step S21 is as follows:
wherein μ is the mean value, AjIs the amplitude of order j, p is the total component, ω0Is the fundamental frequency of the radio signal and,
is the initial phase angle and σ (t) is the noise signal.
When the track state is researched, the qualitative analysis is carried out on the key parameter data to be collected. The resulting data contains two major components: one is the collected valid data and the other is the unwanted signal (noise signal). The noise signal is mainly from the accuracy error of the instrument itself and the assembly error when fitting other systems.
The formula of the signal output by the detection unit is as follows:
y(t)＝f(t)+σ(t)
where f (t) is the desired signal and σ (t) is the noise signal.
Analyzing the collected effective data, wherein the formula of a useful signal f (t) is as follows:
to the output signal formula
y(t)＝f(t)+σ(t)
And carrying out integral transformation to obtain the formula for qualitatively analyzing the acquired key parameter data.
The integrated formula is analyzed, and the amplitude of the useful signal is
As j tends to be infinitely small, the magnitude tends to be infinite. The weight of the noise signal is small and can be ignored. Therefore, the low-frequency component has a large influence on the acceleration, and the acquired acceleration signal needs to be filtered to filter out the low-frequency component.
Preferably, the formula for filtering the filtered key parameter data in step S22 is as follows:
Y(ejω)＝X(ejω)×H(ejω)
in the formula, X (ej ω) is an excitation response amplitude angle, and H (ej ω) is a unit sampling response amplitude angle.
The digital filter is widely applied, and the finite unit impulse response filter can ensure any amplitude-frequency characteristic and simultaneously has strict linear phase-frequency characteristic, and the unit sampling response is finite. The acceleration signal is mixed with low-frequency components, so that a low-frequency cut-off filter and a high-frequency pass filter are required. The time domain analysis formula of the high-pass filtering is as follows:
y(n)＝x(n)×h(n)
where x (n) is the excitation response and h (n) is the unit sample response. x (n) passes through h (n) in a certain step length, a response value y (n) is obtained when the user walks each step, and high-frequency passing and low-frequency cut-off can be realized by weighting the window h (n). And converting the time domain into a frequency domain analysis formula to obtain the formula for filtering the screened key parameter data.
In the formula for filtering the screened key parameter data, the excitation response argument and the unit sampling response argument have large influence on the high-frequency response weight and small influence on the low-frequency response weight, so that the effect of filtering the low-frequency component can be achieved.
Preferably, step S3 includes the steps of:
s31: fitting the effective data by adopting a least square method, and performing secondary integration on the fitted data to obtain track transverse rigidity irregularity information;
s32: obtaining the irregularity information of the longitudinal rigidity of the track according to the irregularity information of the transverse rigidity of the track;
s33: obtaining information of the effective data in three directions of XYZ axes through the effective data;
s34: and fitting and twice integrating the effective data information on the Z axis to obtain the rigidity irregularity information of the left and right tracks.
In step S31, performing least square fitting and quadratic integration on the effective acceleration data to obtain displacement data, where the displacement data is track transverse stiffness irregularity information data.
In step S32, the track transverse stiffness irregularity information may be twice integrated to obtain track longitudinal stiffness irregularity information, i.e., track stiffness irregularity information in the longitudinal direction.
In step S33, the acceleration data is transmitted to the terminal through the detection unit, and after the effective acceleration data is obtained through analysis, the information of the effective acceleration data in the three directions of the XYZ axes is output, which is convenient for the subsequent calculation of the left and right track stiffness irregularity information.
Preferably, step S4 includes the steps of:
s41: calculating vibration displacement data through the effective data;
s42: judging whether the vibration displacement data meet the standard, and jumping to the step S43 if the vibration displacement data meet the standard; if the standard is not met, sending alarm information;
s43: calculating the upper and lower offset of the track according to the vibration displacement data;
s44: and detecting whether the damping pad meets the standard or not through the calculated upper and lower offset of the track.
In step S41, the vibration displacement data is calculated from the effective acceleration data, and the calculation method is the calculation of the existing formula. First, a theoretical value of the vibration intensity is calculated by calculation or by multiplying the acceleration measured by an acceleration sensor by the displacement in the acceleration direction, and then the vibration amplitude (i.e., vibration displacement data) is calculated from the vibration intensity.
And step S42, detecting whether the vibration amplitude meets the requirement according to the vibration standard of the vibration damping pad, conveniently monitoring the vibration damping pad in real time, and judging whether to give an alarm according to the monitoring result.
In the step S43, the upper and lower offset of the track is calculated through the vibration amplitude, so that the numerical range of the upper and lower offset of the track is obtained, and whether the track meets the standard or not is conveniently detected in the step S44, so that the condition of the vibration damping pad is indirectly monitored in real time.
Preferably, step S5 includes the steps of:
s51: judging whether the track has unsmooth rigidity according to the track rigidity unsmooth information obtained in the step S3, and if so, sending alarm information; if not, continuously acquiring key parameter data;
s52: judging whether the track meets the standard or not according to the upper and lower offset of the track obtained in the step S4, and if so, continuing to acquire key parameter data; if not, alarm information is sent out.
And (4) detecting and judging the track in real time through the track rigidity irregularity information in the step S51 and the track up-and-down offset in the step S52, so as to judge whether the track damping pad achieves a corresponding set effect, facilitate real-time monitoring of the damping pad, and judge whether to give an alarm according to a monitoring result.
Preferably, the detection unit is arranged in a vibration damping pad of the two side rails.
The track information on the two sides can be respectively collected by the arrangement mode, so that the data collection is more direct and comprehensive.
The detection units are connected and transmit data to the terminal in a wireless or wired mode, so that the terminal can analyze the data in real time conveniently, and whether the track vibration damping pad achieves a corresponding set effect or not is judged in real time.
The utility model has the beneficial effects that:
(1) according to the utility model, the detection unit is arranged on the vibration damping pad, and the numerical value change of each sensor in the running process of the train is detected through the implanted sensor structure, so that whether the track vibration damping pad achieves the corresponding set effect or not is judged, the vibration damping pad is conveniently monitored in real time, and whether an alarm is given or not is judged according to the monitoring result.
(2) Step S2 may perform qualitative analysis on the collected key parameter data to obtain valid data and useless signals in the key parameter data, thereby screening out the key parameter data that needs to be processed.
(3) In step S2, the noise signal may be removed through filtering processing, so as to obtain valid data, which is convenient for improving reliability and accuracy of the key parameter data.
(4) Step S3 can obtain the unsmooth information of the rigidity of the left track and the right track in the mode of least square fitting and quadratic integration, and is convenient for detecting the real-time state of the damping pad.
(5) Through the setting mode of detecting element setting in the orbital damping pad of both sides, can realize gathering respectively of both sides track information, make data acquisition more direct and comprehensive.
Drawings
FIG. 1 is a schematic flow diagram of the present invention.
Detailed Description
The utility model is further described with reference to the following figures and detailed description.
As shown in fig. 1, a method for detecting parameters of a track damping pad includes the following steps:
s1: arranging a detection unit on the vibration damping pad, and acquiring key parameter data;
s2: carrying out qualitative analysis on the acquired key parameter data to obtain effective data;
s3: fitting and twice integrating the effective data to obtain track rigidity irregularity information;
s4: calculating the upper and lower offsets of the track according to the effective data, and detecting whether the track meets the standard;
s5: and judging whether the damping pad achieves the corresponding setting effect according to the results of the step S3 and the step S4.
In step S1, the vibration damping pad is provided with a detection unit, and the implanted sensor structure is used to detect the changes in the values of various sensors during the running of the train, so as to determine whether the rail vibration damping pad has a corresponding setting effect, and determine whether to alarm according to the result.
In the step S2, the effective data is obtained by performing qualitative analysis on the key parameter data and performing denoising processing, and the effective data includes effective acceleration data.
In the step S3, after the effective acceleration data is calculated and analyzed, information about whether the rigidity of the left and right rails is smooth can be obtained, which is convenient for detecting the condition that the rigidity of the left and right rails is smooth.
In step S4, the vertical offset of the left and right rails during the running of the train is calculated from the effective acceleration data, so as to realize real-time detection of the rails, automatically determine whether the rails meet the standards, and indirectly monitor the damping pads.
In step S5, whether the vibration damping pad has a corresponding setting effect is determined by analyzing and processing the track vertical offset and track stiffness irregularity information, so as to implement real-time monitoring of the vibration damping pad and determine whether to alarm according to the monitoring result.
The detection unit in the step S1 includes an acceleration detection unit and a displacement detection unit; the key parameter data in step S1 includes acceleration data and displacement data.
The acceleration detection unit is used for detecting acceleration data; the displacement detection unit includes a course displacement sensor for detecting displacement in the acceleration direction.
Step S2 includes the following steps:
s21: qualitatively analyzing the acquired key parameter data, and screening the key parameter data to be processed;
s22: filtering the screened key parameter data to filter out low-frequency components;
s23: and obtaining effective data after filtering.
In step S21, the collected key parameter data is qualitatively analyzed, and effective data and useless signals in the key parameter data can be obtained through a qualitative analysis formula, so as to screen out the key parameter data that needs to be processed.
In step S22, the noise signal is removed by filtering processing, so as to obtain valid data, which is convenient for improving reliability and accuracy of the key parameter data.
In step S21, the formula for performing qualitative analysis on the collected key parameter data is:
wherein μ is the mean value, AjIs the amplitude of order j, p is the total component, ω0Is the fundamental frequency of the radio signal and,
is the initial phase angle and σ (t) is the noise signal.
When the track state is researched, the qualitative analysis is carried out on the key parameter data to be collected. The resulting data contains two major components: one is the collected valid data and the other is the unwanted signal (noise signal). The noise signal is mainly from the accuracy error of the instrument itself and the assembly error when fitting other systems.
The formula of the signal output by the detection unit is as follows:
y(t)＝f(t)+σ(t)
where f (t) is the desired signal and σ (t) is the noise signal.
Analyzing the collected effective data, wherein the formula of a useful signal f (t) is as follows:
to the output signal formula
y(t)＝f(t)+σ(t)
And carrying out integral transformation to obtain a formula for qualitatively analyzing the acquired key parameter data.
The integrated formula is analyzed, and the amplitude of the useful signal is
As j tends to be infinitely small, the magnitude tends to be infinite. The weight of the noise signal is small and can be ignored. Therefore, the low-frequency component has a large influence on the acceleration, and the acquired acceleration signal needs to be filtered to filter out the low-frequency component.
The formula for filtering the screened key parameter data in step S22 is as follows:
Y(ejω)＝X(ejω)×H(ejω)
in the formula, X (ej ω) is an excitation response amplitude angle, and H (ej ω) is a unit sampling response amplitude angle.
The digital filter is widely applied, and the finite unit impulse response filter can ensure any amplitude-frequency characteristic and simultaneously has strict linear phase-frequency characteristic, and the unit sampling response is finite. The acceleration signal is mixed with low-frequency components, so that a low-frequency cut-off filter and a high-frequency pass filter are required. The time domain analysis formula of the high-pass filtering is as follows:
y(n)＝x(n)×h(n)
where x (n) is the excitation response and h (n) is the unit sample response. x (n) passes through h (n) in a certain step length, a response value y (n) is obtained when the user walks each step, and high-frequency passing and low-frequency cut-off can be realized by weighting the window h (n). And converting the time domain into a frequency domain analysis formula to obtain a formula for filtering the screened key parameter data.
In the formula for filtering the screened key parameter data, the excitation response amplitude and the unit sampling response amplitude have large influence on the high-frequency response weight and small influence on the low-frequency response weight, so that the effect of filtering the low-frequency component can be achieved.
Step S3 includes the following steps:
s31: fitting the effective data by adopting a least square method, and performing secondary integration on the fitted data to obtain track transverse rigidity irregularity information;
s32: obtaining the irregularity information of the longitudinal rigidity of the track according to the irregularity information of the transverse rigidity of the track;
s33: obtaining information of the effective data in three directions of XYZ axes through the effective data;
s34: and fitting and twice integrating the effective data information on the Z axis to obtain the rigidity irregularity information of the left and right tracks.
In step S31, the effective acceleration data is subjected to least square fitting and twice integration to obtain displacement data, which is the track transverse stiffness irregularity information data.
In step S32, the track transverse stiffness irregularity information may be twice integrated to obtain track longitudinal stiffness irregularity information, i.e., track stiffness irregularity information in the longitudinal direction.
In step S33, the acceleration data is transmitted to the terminal through the detection unit, and after the effective acceleration data is obtained through analysis, information of the effective acceleration data in three directions of XYZ axes is output, which facilitates subsequent calculation of the left and right track stiffness irregularity information.
Step S4 includes the following steps:
s41: calculating vibration displacement data through the effective data;
s42: judging whether the vibration displacement data meet the standard, and jumping to the step S43 if the vibration displacement data meet the standard; if the standard is not met, sending alarm information;
s43: calculating the upper and lower offset of the track according to the vibration displacement data;
s44: and detecting whether the damping pad meets the standard or not through the calculated upper and lower offset of the track.
In step S41, the vibration displacement data is calculated from the effective acceleration data, and the calculation method is the calculation of the existing formula. First, a theoretical value of the vibration intensity is calculated by calculation or by multiplying the acceleration measured by an acceleration sensor by the displacement in the acceleration direction, and then the vibration amplitude (i.e., vibration displacement data) is calculated from the vibration intensity.
And step S42, detecting whether the vibration amplitude meets the requirement according to the vibration standard of the vibration damping pad, conveniently monitoring the vibration damping pad in real time, and judging whether to give an alarm according to the monitoring result.
In the step S43, the upper and lower offset of the track is calculated through the vibration amplitude, so that the numerical range of the upper and lower offset of the track is obtained, and whether the track meets the standard or not is conveniently detected in the step S44, thereby indirectly monitoring the condition of the vibration damping pad in real time.
Step S5 includes the following steps:
s51: judging whether the track has unsmooth rigidity according to the track rigidity unsmooth information obtained in the step S3, and if so, sending alarm information; if not, continuously acquiring key parameter data;
s52: judging whether the track meets the standard or not according to the upper and lower offset of the track obtained in the step S4, and if so, continuing to acquire key parameter data; if not, alarm information is sent out.
And (4) detecting and judging the track in real time through the track rigidity irregularity information in the step S51 and the track up-and-down offset in the step S52, so as to judge whether the track damping pad achieves the corresponding set effect, facilitate the real-time monitoring of the damping pad, and judge whether to give an alarm according to the monitoring result.
The detection unit is arranged in the vibration damping pads of the two side rails.
The track information on the two sides can be respectively collected by the arrangement mode, so that the data collection is more direct and comprehensive.
The detection units in the utility model are connected and transmit data to the terminal in a wireless or wired mode, so that the terminal can conveniently analyze the data in real time, and whether the track vibration damping pad achieves the corresponding set effect or not can be judged in real time.
It should be understood that this example is only for illustrating the present invention and is not intended to limit the scope of the present invention. Further, it should be understood that various changes or modifications of the present invention may be made by those skilled in the art after reading the teaching of the present invention, and such equivalents may fall within the scope of the present invention as defined in the appended claims.
Claims (9)
1. A method for detecting parameters of a track damping pad is characterized by comprising the following steps:
s1: arranging a detection unit on the vibration damping pad, and acquiring key parameter data;
s2: carrying out qualitative analysis on the acquired key parameter data to obtain effective data;
s3: fitting and twice integrating the effective data to obtain track rigidity irregularity information;
s4: calculating the upper and lower offsets of the track according to the effective data, and detecting whether the track meets the standard;
s5: and judging whether the damping pad achieves the corresponding setting effect according to the results of the step S3 and the step S4.
2. The method as claimed in claim 1, wherein the detecting unit in step S1 comprises an acceleration detecting unit and a displacement detecting unit; the key parameter data in step S1 includes acceleration data and displacement data.
3. The method for detecting the parameters of the track damping pad according to the claim 1 or 2, wherein the step S2 comprises the following steps:
s21: qualitatively analyzing the acquired key parameter data, and screening the key parameter data to be processed;
s22: filtering the screened key parameter data to filter out low-frequency components;
s23: and obtaining effective data after filtering.
4. The method as claimed in claim 3, wherein the qualitative analysis of the collected key parameter data in step S21 is represented by the following formula:
wherein μ is the mean value, AjIs the amplitude of order j, p is the total component, ωoIs the fundamental frequency of the radio signal and,
is the initial phase angle, σ (t) is the noise signal。
5. The method as claimed in claim 3, wherein the formula for filtering the screened key parameter data in step S22 is as follows:
Y(ejω)＝X(ejω)×H(ejω)
in the formula, X (ej ω) is an excitation response amplitude angle, and H (ej ω) is a unit sampling response amplitude angle.
6. The method for detecting the parameters of the track damping pad according to claim 1, wherein the step S3 comprises the following steps:
s31: fitting the effective data by adopting a least square method, and performing secondary integration on the fitted data to obtain track transverse rigidity irregularity information;
s32: obtaining the irregularity information of the longitudinal rigidity of the track according to the irregularity information of the transverse rigidity of the track;
s33: obtaining information of the effective data in three directions of XYZ axes through the effective data;
s34: and fitting and twice integrating the effective data information on the Z axis to obtain the rigidity irregularity information of the left and right tracks.
7. The method for detecting the parameters of the track damping pad according to claim 2, wherein the step S4 comprises the following steps:
s41: calculating displacement data of up-and-down vibration of the track through the effective data;
s42: judging whether the vibration displacement data meet the standard, and jumping to the step S43 if the vibration displacement data meet the standard; if the standard is not met, sending alarm information;
s43: calculating the upper and lower offset of the track according to the vibration displacement data;
s44: and detecting whether the damping pad meets the standard or not through the calculated upper and lower offset of the track.
8. The method for detecting the parameters of the track damping pad according to claim 1, wherein the step S5 comprises the following steps:
s51: judging whether the track has unsmooth rigidity according to the track rigidity unsmooth information obtained in the step S3, and if so, sending alarm information; if not, continuously acquiring key parameter data;
s52: judging whether the track meets the standard or not according to the upper and lower offset of the track obtained in the step S4, and if so, continuing to acquire key parameter data; if not, alarm information is sent out.
9. The method for detecting the parameters of the track damping pads according to the claim 1 or 2, characterized in that the detection unit is arranged in the damping pads of the two-side track.
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