CN114877803A - Pantograph slide plate abrasion state detection method based on laser displacement sensor - Google Patents
Pantograph slide plate abrasion state detection method based on laser displacement sensor Download PDFInfo
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Abstract
The invention discloses a pantograph slide plate abrasion state detection method based on a laser displacement sensor, which comprises the following steps: two groups of laser displacement sensors are installed in mirror symmetry about the central line of the steel rail, and slide plate data acquisition is carried out vertically downwards; analyzing the distribution rule of the number of data points output by the sensor, and screening effective data frames; converting effective data of the two sensors into the same coordinate system through data fusion; filtering interference points, and extracting a skateboard profile data point; carrying out inclination correction on the outline data of the sliding plate; smoothing the outline of the sliding plate by adopting a curve fitting algorithm to obtain the actual outline of the sliding plate; estimating the initial profile of the sliding plate, calculating the actual abrasion curve of the sliding plate by matching the actual profile of the sliding plate, and finally analyzing the abrasion state of the sliding plate. The invention not only reflects the abrasion degree of the sliding plate, but also analyzes the state of the sliding plate from the aspects of eccentric wear, groove abrasion and the like, and has the advantages of high detection speed, high precision, online non-contact measurement and the like.
Description
Technical Field
The invention belongs to the technical field of intelligent operation and maintenance of urban rail transit, and particularly relates to a pantograph slide plate wear state detection method based on a laser displacement sensor.
Background
With the rapid development of urban rail transit, the on-line operation safety problem of trains is increasingly prominent. The pantograph pan is an important electrical component of an urban rail train and is used for collecting current from a contact wire and providing power for the train. In the train operation process, slide and contact wire direct contact, the interact between the two will lead to the continuous wearing and tearing of slide, and the wearing and tearing state of slide has the great influence to the safe operation of train, consequently, in time monitors the pantograph slide state and is the important measure of guarantee train operation safety.
The detection of the state of the pantograph slide plate is an important index for daily detection of urban rail train vehicles. At present, the main detection method for the state of the pantograph sliding plate is still a manual detection method, but the method needs manual overhead detection for detecting the pantograph, the detection efficiency is low, the safety is poor, and the detection result is greatly influenced by human factors. With the rapid development of computer information technology, the automatic intelligent detection of key components of urban rail vehicles becomes a trend. According to the traditional pantograph slide plate automatic detection scheme, a 2D camera is adopted to collect a slide plate image, the residual abrasion of the slide plate is measured through image processing technologies such as edge detection, the influence of factors such as flash lamp polishing quality, a complex background environment of a pantograph, slide plate stains and the like is caused in practical application, and the detection precision of the scheme is low. Compared with a laser displacement sensor, the image method is inferior in detection precision, stability, anti-interference capability and the like.
Patent CN202010997861.7 discloses a pantograph pan wear detection method and system, in which a laser scanner is used to longitudinally emit pulsed laser to a pantograph pan, and the time difference between the emission of the pulsed laser and the reception of reflected light is determined; determining a distance value between the laser scanner and the corresponding reflection position based on the time difference; calculating a depression value of the real position on the pantograph slide plate according to the difference value between the distance value and the standard distance; and transforming the scanning angle of the laser scanner, determining the depression values of all real positions on the pantograph slide plate, and sequencing according to the real positions to generate a surface oscillogram of the pantograph slide plate so as to determine the abrasion degree of the pantograph slide plate. The method also needs to adjust the angle of the laser scanner, is complex to operate, is easy to introduce errors, has low detection precision, and only adopts the depression value to reflect the abrasion degree of the sliding plate.
Patent CN202011565715.3 discloses an online detection device and method for train pantograph slide plate abrasion based on laser projection, which comprises a pantograph-catenary system, a drive-in detection module, a data acquisition module and a data processing module which are connected in sequence; the pantograph-catenary system comprises a catenary and a pantograph, the train entrance signal is acquired by the entrance detection module when the train enters the detection area, and the train entrance signal is sent to the data acquisition module; the data acquisition module comprises a laser and a camera which are connected, the laser and the camera are arranged above and below the pantograph at the same side of the train, when a train driving signal is received, the laser is triggered to emit laser to the surface of the pantograph, and an image shot by the camera is sent to the data processing module to be processed to obtain the sliding plate abrasion data. The method needs combination of a plurality of components such as a camera, a laser and the like, is complex to install, and has poor stability and anti-interference capability.
Disclosure of Invention
The invention aims to provide a pantograph slide plate wear state detection method based on a laser displacement sensor.
The technical solution for realizing the purpose of the invention is as follows: a pantograph slide plate wear state detection method based on a laser displacement sensor is characterized by comprising the following steps:
s1: two groups of laser displacement sensors are installed in mirror symmetry about the central line of the steel rail, and slide plate data acquisition is carried out vertically downwards;
s2: analyzing the distribution rule of the number of data points output by the laser displacement sensor, and screening effective data frames;
s3: converting effective data of the two laser displacement sensors into the same coordinate system through data fusion;
s4: filtering interference points, and extracting a skateboard profile data point;
s5: carrying out inclination correction on the outline data of the sliding plate;
s6: smoothing the outline of the sliding plate by adopting a curve fitting algorithm to obtain the actual outline of the sliding plate;
s7: estimating the initial profile of the sliding plate, and calculating the actual wear curve of the sliding plate by matching the actual profile of the sliding plate;
s8: and analyzing the abrasion state of the sliding plate according to the actual abrasion curve of the sliding plate.
Compared with the prior art, the invention has the following remarkable advantages: (1) the abrasion curve of the sliding plate is calculated by adopting a laser ranging technology, so that the abrasion detection precision of the sliding plate is effectively improved; (2) the analysis of the state of the sliding plate is more systematic, the maximum abrasion loss is adopted to reflect the abrasion degree of the sliding plate, and the state of the sliding plate is analyzed from the aspects of eccentric wear, groove abrasion and the like; (3) the system has simple structural design, and can realize the acquisition of the outline of the pantograph slide plate only by two groups of laser displacement sensors.
Drawings
Fig. 1 is a flowchart of a pantograph slide wear state detection method according to the present invention.
Fig. 2 is a schematic view of the sensor installation for detecting the wear state of the pantograph pan according to the present invention.
FIG. 3 is a diagram of a pantograph slide wear condition detection slide according to the present invention.
Fig. 4 is a diagram of raw data of a pantograph pan acquired by a laser displacement sensor according to the present invention.
Fig. 5 is a matching diagram of the pantograph pan profile of the present invention.
Fig. 6 is a graph of the wear of the pantograph slide plate according to the invention.
FIG. 7 is a graph showing the amount of wear change in the pantograph pan of the present invention.
Detailed Description
The invention discloses a pantograph slide plate abrasion state detection method based on a laser displacement sensor, which comprises the following steps of:
s1: two groups of laser displacement sensors are installed in mirror symmetry about the central line of the steel rail, and slide plate data acquisition is carried out vertically downwards;
s2: analyzing the distribution rule of the number of data points output by the laser displacement sensor, and screening effective data frames;
s3: converting effective data of the two laser displacement sensors into the same coordinate system through data fusion;
s4: filtering interference points, and extracting a skateboard profile data point;
s5: carrying out inclination correction on the outline data of the sliding plate;
s6: smoothing the outline of the sliding plate by adopting a curve fitting algorithm to obtain the actual outline of the sliding plate;
s7: estimating the initial profile of the sliding plate, and calculating the actual wear curve of the sliding plate by matching the actual profile of the sliding plate;
s8: and analyzing the abrasion state of the sliding plate according to the actual abrasion curve of the sliding plate.
Further, step S1 includes:
s11: the laser displacement sensor adopts a 2D laser displacement sensor;
s12: the two groups of laser displacement sensors are arranged above the contact line and are in mirror symmetry with respect to the central line of the track, and the horizontal distance between the laser source points of the two groups of laser displacement sensors is 500-700 mm;
s13: the laser displacement sensor is vertically installed downwards to collect the sliding plate data, and the vertical upper detection range is 900-1300 mm.
Further, the valid data frame filtering process in step S2 is as follows:
s21: in the running process of the train, when the sliding plate enters and leaves the detection area, the output points of the laser displacement sensor obviously rise and fall according to the N i ＞N set The criteria of (1) screening the valid data frames, where N i Number of data points acquired for the ith time of the laser displacement sensor, N set Screening a threshold value for valid data;
s22: and according to the index of the effective data frame, carrying out segmentation processing on the effective data frame to obtain the number of the sliding plates and the laser displacement sensor data corresponding to each sliding plate.
Further, the data fusion process in step S3 is as follows:
s31: the self coordinate system of the laser displacement sensor is defined as that the emitting direction of the laser is used as the y axis, the direction perpendicular to the emitting direction of the laser is used as the x axis, the laser source is used as the origin of coordinates, the two groups of laser displacement sensors are respectively marked as LS1 and LS2, and the self coordinate system is respectively marked as x (1) o (1) y (1) 、x (2) o (2) y (2) ；
S32: taking a laser displacement sensor LS2 coordinate system as a target coordinate system, rotationally translating a laser displacement sensor LS1 coordinate system to a laser displacement sensor LS2 coordinate system, wherein data fusion parameters are x respectively (1) Axis and x (2) The included angle alpha between the axes and the spatial distances DX and DY of the origin of the coordinate system are calculated by adopting a data fusion parameter calculation method based on a calibration block;
s33: after data fusion parameters are acquired, the LS1 coordinate system of the laser displacement sensor is rotationally translated into the LS2 coordinate system of the laser displacement sensor, and the specific conversion formula is as follows:
in the formula (x) n (1) ,y n (1) )、(x n (2) ,y n (2) ) Are respectively a seatSystem of symbols x (1) o (1) y (1) 、x (2) o (2) y (2) Point (c) above.
Further, in step S32, the specific process of the data fusion parameter calculation method based on the calibration block is as follows:
s321: a finely-machined cuboid calibration block is adopted, the width of the calibration block is L, two laser displacement sensors need to be irradiated on the same straight line in the calibration process, and the average value of multiple times of calibration is taken as the final calibration result;
s322: the rotation angle alpha is obtained, the data collected by the two sensors are subjected to linear fitting, and the straight lines of the data fitting detected by the two sensors are respectively l in the ith calibration process i1 、l i2 The slope is respectively k i1 、k i2 The angles of inclination are each theta i1 、θ i2 The rotation angle alpha in the ith calibration process i The calculation is as follows:
s323: the calculation of the translation parameters DX and DY is that the laser displacement sensor LS1 and the laser displacement sensor LS2 respectively detect a boundary point of the calibration block, and the coordinates of the boundary point in the sensor coordinate systems are respectively (x) 1 ,y 1 )、(x 2 ,y 2 ) The sensor LS1 coordinate system is rotated by an angle alpha, point (x) 1 ,y 1 ) The rotated coordinate is (x' 1 ,y′ 1 ) The conversion formula is as follows:
according to the fixed length characteristic of the calibration block, the translation distance DX of the coordinate origin in the x-axis direction and the translation distance DY of the coordinate origin in the y-axis direction are calculated, and the calculation formula is as follows:
in the formula k 2 Is the slope, theta, of the straight line on the upper surface of the calibration block in the LS2 coordinate system of the sensor 2 Is k 2 The corresponding tilt angle.
Further, the sliding plate contour data point extraction process in step S4 is as follows:
let the coordinate of the ith point of a frame of valid data be (x) i (2) ,y i (2) ) I is 1,2, …, h, h is the number of points of the frame data;
from the starting point (x) 1 (2) ,y 1 (2) ) Starting to search in sequence, and calculating two adjacent points { (x) n (2) ,y n (2) ),(x n+1 (2) ,y n+1 (2) ) The Euclidean distance d of the (d) is compared with a threshold value delta d, if d is satisfied<Δ d, then the subsequent point (x) n+1 (2) ,y n+1 (2) ) Adding to the same point set R c ＝{(x 1 (2) ,y 1 (2) ),…,(x n (2) ,y n (2) ),(x n+1 (2) ,y n+1 (2) ) In the symbol, if d.gtoreq.Δ d, then at a point (x) n (2) ,y n (2) ) As a division point, the next set of points R c+1 From (x) n+1 (2) ,y n+1 (2) ) Continuing searching for a starting point;
and after data point retrieval is finished, counting the number of data points of each point set, and extracting the point set data with the most data points as the outline data points of the sliding plate.
Further, the slide profile data correction process described in step S5 is as follows:
s51: according to the outline data points of the sliding plate obtained in the step S4, extracting the data points of the left and right slope areas of the sliding plate to calculate the inclination angle beta of the sliding plate, wherein the calculation formula is as follows:
β＝π-δ 1 -δ 2
in the formula, delta 1 、δ 2 Respectively carrying out first-order linear fitting on data points of a left slope area and a right slope area of the sliding plate and then carrying out inclination angles of the sliding plate in the horizontal direction;
s52: after the slide angle of inclination is acquireed, carry out inclination correction to slide profile data, the correction formula is as follows:
in the formula (x) n (2) ,y n (2) ) As fused data points, (u) n ,v n ) Are corrected data points.
Further, the curve fitting process in step S6 is as follows:
s61: based on the least square principle and a preset error tolerance e, automatically determining the length of each section by adopting a third-order polynomial fitting equation, and recording initial segmentation points and fitting coefficients;
s62: dividing each initial segmentation interval into an overlapping area and a non-overlapping area according to the overlapping proportion eta, wherein a fitting equation of data in the non-overlapping area is an initial fitting equation;
s63: performing least square fitting on data points in the overlapping area under the condition that two end points in the overlapping area meet the first-order continuous constraint to obtain a data fitting equation of the overlapping area;
s64: and obtaining regression coefficients and segmentation points of the polynomial equation of the intersection area and the non-intersection area, and realizing the fitting of the whole slide plate outline data points.
Further, when least square fitting is carried out on data points of the overlapping area, if the number of the data points of the overlapping area is less than 4, first-order linear fitting is adopted, otherwise, third-order polynomial fitting is adopted, two endpoints of the overlapping area meet first-order linear constraint, and the constraint conditions are as follows:
in the formula (p) 1 ,q 1 )、(p 2 ,q 2 ) Respectively representing two endpoints of an overlap region, the polynomial fitting equation of the overlap region is
The polynomial fitting equations of the front and back adjacent non-overlapping regions are respectively
k is the polynomial degree of the curve.
Further, the actual wear curve of the slider in step S7 is obtained as follows:
s71: estimating the profile of the sliding plate when the sliding plate is not worn based on the unworn area of the upper surface of the sliding plate, and taking the curve as the initial profile of the sliding plate;
s72: and (3) performing curve matching on the actual profile of the sliding plate and the initial profile, performing equidistant point taking, and performing subtraction operation on the actual profile and the initial profile to obtain an actual wear curve of the sliding plate.
Further, the estimation process of the initial contour of the skateboard in step S71 is as follows:
s711: the sliding plate is divided into a left slope area, a horizontal area and a right slope area, wherein the left slope area and the right slope area are not in contact with a contact line, and the outlines acquired by the left slope area sensor and the right slope area sensor are initial outlines;
s712: estimating the initial contour of the horizontal area of the sliding plate according to unworn areas of two side parts of the horizontal area of the sliding plate, wherein the specific process is as follows:
if the number of data points of the whole sliding plate is q, extracting data points in [1, q/3], [2q/3, q ], detecting the minimum distance values by the laser displacement sensor to be vl _ min and vr _ min respectively, taking the data points positioned in [ vl _ min-0.2, vl _ min ], [ vr _ min-0.2, vr _ min ] as partial data of a horizontal unworn area of the sliding plate, and taking corresponding average values to be vl _ ave and vr _ ave respectively;
simulating the initial machining state of the sliding plate by using a random error with the amplitude of 2 × abs (vl _ ave-vr _ ave)/3 and adopting adaptive piecewise curve fitting to realize the estimation of the horizontal initial contour of the sliding plate by taking (vl _ ave + vr _ ave)/2 as a reference value;
s713: and splicing the outlines of the left slope area and the right slope area of the sliding plate with the horizontal initial outline of the sliding plate to obtain the initial outline of the complete sliding plate.
Further, the curve matching process in step S72 is as follows:
after the initial contour is obtained, the actual contour and the initial contour are registered according to the unworn characteristics of the left slope area and the right slope area of the sliding plate, and if the initial contour data point set is { (u 1) 1 ,v1 1 ),…,(u1 n1 ,v1 n1 ) The point set of the actual contour is { (u 2) 1 ,v2 1 ),…,(u2 n2 ,v2 n2 )}；
Extracting left and right slope region data points of the initial contour and the actual contour respectively, performing third-order polynomial curve fitting, and performing deviation model establishment on the fitted data, wherein curve matching deviation z is as follows:
wherein (u1_ l) i1 ,v1_l i1 )、(u1_r i1 ,v1_r i1 ) For the left and right slope data points of the initial contour, (u2_ l) i2 ,v2_l i2 )、(u2_r i2 ,v2_r i2 ) The data points are left slope data points and right slope data points of the actual contour, m1 and m2 are data points for matching the left slope and the right slope respectively, and delta u and delta v are translation parameters of the actual contour of the sliding plate;
and (4) carrying out constrained nonlinear optimal value calculation on the deviation model, wherein the parameters delta u and delta v corresponding to the minimum value of the deviation z are final matching parameters.
Further, the analysis process of the wear state of the slide plate in step S8 is as follows:
after obtaining the actual wear curve of the sliding plate, adopting the maximum wear loss W M Wear variation W V And eccentric wear amount W P These 3 variablesThe state of the skateboard is analyzed and the variables are defined as follows:
W M ＝max(W(x)),x∈[0,L s ]
wherein W (x) represents a sliding plate wear value at position x, L s Indicating the length of the worn area of the slide, W ave Is the average wear value of the skateboard; i represents a position number, n represents the total number of positions;
based on the maximum wear loss W M Wear variation W V And eccentric wear amount W P Analyzing the abrasion state of the sliding plate, wherein the specific judgment rule is as follows:
(1) when the maximum abrasion loss W of the slide plate M Greater than wear threshold G WM When the sliding plate is in an over-abrasion state;
(2) when the slide plate is eccentrically worn W P Greater than the partial wear threshold G WP When the sliding plate is worn, the sliding plate is asymmetric in wear, and eccentric wear occurs;
(3) when wear changes amount abs (W) V ) Greater than a threshold value G WV When the sliding plate is worn, the sliding plate wearing curve is raised or lowered; if the wear variation is first greater than the threshold G WV Then less than G within a set width distance WV There is a groove type wear.
The invention is described in further detail below with reference to the figures and the embodiments.
Examples
With reference to fig. 1, the method for detecting the wear state of a pantograph slide plate based on a laser displacement sensor comprises the following steps:
s1: two sets of laser displacement sensors are installed in mirror symmetry about the central line of a steel rail, and slide data acquisition is vertically performed downwards, wherein the installation schematic of the sensors is shown in figure 2, and the test slide is shown in figure 3, and the specific process is as follows:
s11: the laser displacement sensor adopts a high-precision large-range 2D laser displacement sensor, and selects a Ginzhi LJ-X8900 sensor;
s12: the two groups of laser displacement sensors are arranged above the contact line and are in mirror symmetry with respect to the central line of the track, and the horizontal distance between the laser source points of the two groups of laser displacement sensors is 550 mm;
s13: the laser displacement sensor is vertically installed downwards to collect the data of the pantograph slide plate, and the detection distance in the vertical direction is 980 mm; the raw data of the pantograph pan collected by the laser displacement sensor is shown in fig. 4.
S2: analyzing the distribution rule of the number of the data points output by the sensor, and screening effective data frames, wherein the specific process comprises the following steps:
s21: during the running of the train, when the sliding plate enters and leaves the detection area, the output points of the sensor obviously rise and fall according to the N i ＞N set The criteria of (1) screening the valid data frames, where N i Number of data points acquired for sensor i set Screening a threshold value for valid data, and setting the threshold value to be 1500;
s22: and carrying out segmentation processing on the effective data frames according to the indexes of the effective data frames to obtain the number of the sliding plates and the sensor data corresponding to each sliding plate.
S3: the data of the two sensors are converted into the same coordinate system through data fusion, and the specific process is as follows:
s31: the self coordinate system of the sensor is defined as that the laser emission direction is used as a y axis, the direction vertical to the laser emission direction is used as an x axis, the laser source is used as a coordinate origin, the two groups of laser displacement sensors are respectively marked as LS1 and LS2, and the self coordinate systems are respectively marked as x (1) o (1) y (1) 、x (2) o (2) y (2) As shown in fig. 2;
s32: taking a sensor LS2 coordinate system as a target coordinate system, rotationally translating a sensor LS1 coordinate system to a sensor LS2 coordinate system, wherein data fusion parameters are x respectively (1) Axis and x (2) Angle alpha between the axes, coordinate systemThe spatial distances DX and DY of the origin are calculated by adopting a data fusion parameter calculation method based on a calibration block, wherein the calculation process comprises the following steps:
a finely-machined cuboid calibration block is adopted, the width of the calibration block is equal to 90mm, two laser displacement sensors need to be irradiated on the same straight line in the calibration process, and two groups of sensors respectively detect a boundary point;
calculating the rotation angle alpha of the coordinate system according to the characteristics of the same straight line irradiated by the two laser lines on the calibration block, linearly fitting the data acquired by the two groups of sensors, wherein the straight lines fitted by the data detected by the two groups of sensors are respectively l in the ith calibration process i1 、l i2 The slope is respectively k i1 、k i2 The angle of inclination is theta i1 、θ i2 Angle of rotation alpha i The calculation is as follows:
the sensors LS1 and LS2 each detect a boundary point of the calibration block, the coordinates of which in the respective sensor coordinate system are (x) 1 ,y 1 )、(x 2 ,y 2 ) The sensor LS1 coordinate system is rotated by an angle alpha, point (x) 1 ,y 1 ) The rotated coordinate is (x' 1 ,y′ 1 ) The conversion formula is as follows:
according to the fixed length characteristic of the calibration block, the translation distance DX of the coordinate origin in the x-axis direction and the translation distance DY of the coordinate origin in the y-axis direction are calculated, and the calculation formula is as follows:
in the formula, k 2 Is the slope, theta, of the straight line on the upper surface of the calibration block in the LS2 coordinate system of the sensor 2 Is its corresponding tilt angle;
setting the calibration times to be 3 by taking the average value of multiple times of calibration as a final calibration result, wherein the calibration results are respectively alpha-0.0365 degrees, DX-416.3652 mm and DY-2.5924 mm;
s33: after data fusion parameters are acquired, the sensor LS1 coordinate system is rotationally translated into the sensor LS2 coordinate system, and the specific conversion formula is as follows:
in the formula (x) n (1) ,y n (1) )、(x n (2) ,y n (2) ) Are respectively a coordinate system x (1) o (1) y (1) 、x (2) o (2) y (2) Point (c) above.
S4: filtering interference points, and extracting a skateboard profile data point, wherein the specific process is as follows:
let the coordinate of the ith point of a frame of valid data be (x) i (2) ,y i (2) ) I is 1,2, …, h, h is the point number of the frame data;
from the starting point (x) 1 (2) ,y 1 (2) ) Starting to search in sequence, and calculating two adjacent points { (x) n (2) ,y n (2) ),(x n+1 (2) ,y n+1 (2) ) The euclidean distance d of (d) is compared with a threshold value Δ d of 2mm, if d is satisfied<Δ d, then the subsequent point (x) n+1 (2) ,y n+1 (2) ) Adding to the same point set R c ＝{(x 1 (2) ,y 1 (2) ),…,(x n (2) ,y n (2) ),(x n+1 (2) ,y n+1 (2) ) In the preceding, if d.gtoreq.Δ d, thenWith a point (x) n (2) ,y n (2) ) As a division point, the next set of points R c+1 From (x) n+1 (2) ,y n+1 (2) ) Continuing searching for a starting point;
and after data point retrieval is finished, counting the number of data points of each point set, and extracting the point set data with the most data points as the outline data points of the sliding plate.
S5: and (3) carrying out inclination correction on the sliding plate profile data, wherein the specific process is as follows:
s51: extracting data points of the left slope area and the right slope area of the sliding plate according to the data points of the profile of the sliding plate obtained in the step S4 to calculate the inclination angle of the sliding plate, wherein the inclination angle beta is-0.1602 degrees;
s52: after the slide angle of inclination is acquireed, carry out inclination correction to slide profile data, the correction formula is as follows:
in the formula (x) n (2) ,y n (2) ) As fused data points, (u) n ,v n ) Are corrected data points.
S6: adopting a curve fitting algorithm to carry out smoothing treatment on the outline of the sliding plate to obtain the actual outline of the sliding plate, and the method comprises the following specific processes:
s61: based on the least square principle and the preset error margin e is 0.4mm, automatically determining the length of each section by adopting a 3-order polynomial fitting equation, and recording initial segmentation points and fitting coefficients;
s62: dividing each initial segmentation interval into an overlapping area and a non-overlapping area according to the overlapping proportion eta of 0.3, wherein a fitting equation of data in the non-overlapping area is an initial fitting equation;
s63: performing least square fitting on data points in the overlapping area under the condition that two end points in the overlapping area meet the first-order continuous constraint to obtain a data fitting equation of the overlapping area;
s64: and obtaining regression coefficients and segmentation points of the polynomial equation of the intersection area and the non-intersection area, and realizing the fitting of the whole slide plate outline data points.
Step S63, performing curve fitting on the overlapping area, wherein if the number of data points in the overlapping area is less than 4, performing first-order linear fitting, otherwise, performing third-order polynomial fitting, wherein two endpoints in the overlapping area satisfy first-order linear constraint, and the constraint conditions are as follows:
in the formula (p) 1 ,q 1 )、(p 2 ,q 2 ) Respectively representing two endpoints of an overlap region, the polynomial fitting equation of the overlap region is
The polynomial fitting equations of the front and back adjacent non-overlapping regions are respectively
k is the polynomial degree of the curve, taken as 3.
S7: estimating the initial profile of the sliding plate, and calculating the actual wear curve of the sliding plate by matching the actual profile of the sliding plate, wherein the specific process is as follows:
s71: estimating the profile of the sliding plate when the sliding plate is not worn based on the unworn area of the upper surface of the sliding plate, and taking the curve as the initial profile of the sliding plate;
s72: and (3) performing curve matching on the actual profile of the sliding plate and the initial profile, performing equidistant point taking, and performing subtraction operation on the actual profile and the initial profile to obtain an actual wear curve of the sliding plate, wherein the wear curve is shown in fig. 6.
The estimation process of the initial contour of the skateboard in step S71 is as follows:
s711: the sliding plate is divided into a left slope area, a horizontal area and a right slope area, wherein the left slope area and the right slope area are not in contact with a contact line, and the outlines acquired by the left slope area sensor and the right slope area sensor are initial outlines;
s712: estimating the initial contour of the horizontal area of the sliding plate according to unworn areas of two side parts of the horizontal area of the sliding plate, wherein the specific process is as follows:
the data point number of the whole sliding plate is 4057, data points in [1,1200], [2860,4057] are extracted, the sensor detection minimum distance values are vl _ min 973.3223mm and vr _ min 973.4681mm respectively, the data points located in [ vl _ min-0.2, vl _ min ], [ vr _ min-0.2 and vr _ min ] are used as partial data of a horizontal unworn area of the sliding plate, and the average values are vl _ ave 973.4037mm and vr _ ave 973.5516mm respectively;
simulating the initial machining state of the sliding plate by applying a random error with the amplitude of 2 × abs (vl _ ave-vr _ ave)/3 by taking 973.4777mm as a reference value, and realizing the estimation of the horizontal initial profile of the sliding plate by adopting adaptive piecewise curve fitting;
s713: and splicing the outlines of the left and right slope areas of the sliding plate with the horizontal initial outline of the sliding plate to obtain the initial outline of the complete sliding plate, as shown by a red curve in fig. 5.
The curve matching process described in step S72 is as follows:
after the initial contour is obtained, the actual contour and the initial contour are registered according to the unworn characteristics of the left slope region and the right slope region of the sliding plate, and if the initial contour data point set is { (u 1) 1 ,v1 1 ),…,(u1 n1 ,v1 n1 ) The point set of the actual contour is { (u 2) 1 ,v2 1 ),…,(u2 n2 ,v2 n2 )}；
Extracting left and right slope region data points of the initial contour and the actual contour respectively, performing 3-order polynomial curve fitting, and performing deviation model establishment on the fitted data, wherein curve matching deviation z is as follows:
wherein (u1_ l) i1 ,v1_l i1 )、(u1_r i1 ,v1_r i1 ) For the left and right slope data points of the initial contour, (u2_ l) i2 ,v2_l i2 )、(u2_r i2 ,v2_r i2 ) The data points are left slope data points and right slope data points of the actual contour, m1 and m2 are data points for matching the left slope and the right slope respectively, and delta u and delta v are translation parameters of the actual contour of the sliding plate;
the deviation model is subjected to constrained nonlinear optimal value calculation, parameters corresponding to the minimum value of the deviation z are respectively 1.5001mm and 0.1806mm, and the curve matching effect is shown in fig. 5.
S8: according to the sliding plate wear curve, the wear state of the sliding plate is analyzed, and the specific process is as follows:
after obtaining the slide plate abrasion curve, adopting the maximum abrasion loss W M Wear variation W V And eccentric wear amount W P These 3 variables were used to analyze the state of the slide plate, the maximum wear W of the slide plate M 11.78mm, eccentric wear amount W V 0.92mm, wear change as shown in fig. 7;
based on the maximum wear loss W M Wear variation W V And eccentric wear amount W P Analyzing the wear state of the sliding plate:
(1) setting a wear threshold G WM ＝10mm，W M >G WM The sliding plate has over-abrasion faults;
(2) setting an eccentric wear threshold G WP ＝2mm，W P <G WP The sliding plate has no eccentric wear fault;
(3) setting a threshold G WV The groove width is less than 200 data points at 0.5mm, and as can be seen from fig. 7, the slider has a groove-type wear.
Other structures of the pantograph slide plate abrasion state detection method based on the laser displacement sensor are referred to in the prior art and are not described herein again.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the present invention in any way, so that any modification, equivalent change and modification made to the above embodiment according to the technical spirit of the present invention are within the scope of the technical solution of the present invention.
Claims (10)
1. A pantograph slide plate wear state detection method based on a laser displacement sensor is characterized by comprising the following steps:
s1: two groups of laser displacement sensors are installed in mirror symmetry about the central line of the steel rail, and slide plate data acquisition is carried out vertically downwards;
s2: analyzing the distribution rule of the number of data points output by the laser displacement sensor, and screening effective data frames;
s3: converting effective data of the two laser displacement sensors into the same coordinate system through data fusion;
s4: filtering interference points, and extracting a skateboard profile data point;
s5: carrying out inclination correction on the outline data of the sliding plate;
s6: smoothing the outline of the sliding plate by adopting a curve fitting algorithm to obtain the actual outline of the sliding plate;
s7: estimating the initial profile of the sliding plate, and calculating the actual wear curve of the sliding plate by matching the actual profile of the sliding plate;
s8: and analyzing the abrasion state of the sliding plate according to the actual abrasion curve of the sliding plate.
2. The method for detecting the wear state of the pantograph slide plate based on the laser displacement sensor according to claim 1, wherein the step S1 includes:
s11: the laser displacement sensor adopts a 2D laser displacement sensor;
s12: the two groups of laser displacement sensors are arranged above the contact line and are in mirror symmetry with respect to the central line of the track, and the horizontal distance between the laser source points of the two groups of laser displacement sensors is 500-700 mm;
s13: the laser displacement sensor is vertically installed downwards to collect the sliding plate data, and the vertical upper detection range is 900-1300 mm.
3. The method for detecting the wear state of the pantograph slide plate based on the laser displacement sensor according to claim 1, wherein the screening process of the valid data frames in step S2 is as follows:
s21: column(s) ofDuring the running process of the vehicle, when the sliding plate enters and leaves the detection area, the output points of the laser displacement sensor obviously rise and fall according to the N i ＞N set The criteria of (1) screening the valid data frames, where N i Number of data points acquired for the ith time of the laser displacement sensor, N set Screening a threshold value for valid data;
s22: and according to the index of the effective data frame, carrying out segmentation processing on the effective data frame to obtain the number of the sliding plates and the laser displacement sensor data corresponding to each sliding plate.
4. The method for detecting the wear state of the pantograph slide plate based on the laser displacement sensor according to claim 1, wherein the data fusion process in the step S3 is as follows:
s31: the self coordinate system of the laser displacement sensor is defined as that the emitting direction of the laser is used as the y axis, the direction perpendicular to the emitting direction of the laser is used as the x axis, the laser source is used as the origin of coordinates, the two groups of laser displacement sensors are respectively marked as LS1 and LS2, and the self coordinate system is respectively marked as x (1) o (1) y (1) 、x (2) o (2) y (2) ；
S32: taking a laser displacement sensor LS2 coordinate system as a target coordinate system, rotationally translating a laser displacement sensor LS1 coordinate system to a laser displacement sensor LS2 coordinate system, wherein data fusion parameters are x respectively (1) Axis and x (2) The included angle alpha between the axes and the spatial distances DX and DY of the origin of the coordinate system are calculated by adopting a data fusion parameter calculation method based on a calibration block;
s33: after data fusion parameters are acquired, the LS1 coordinate system of the laser displacement sensor is rotationally translated into the LS2 coordinate system of the laser displacement sensor, and the specific conversion formula is as follows:
in the formula (x) n (1) ,y n (1) )、(x n (2) ,y n (2) ) Are respectively a coordinate system x (1) o (1) y (1) 、x (2) o (2) y (2) Point (c) above.
5. The method for detecting the wear state of the pantograph slide plate based on the laser displacement sensor according to claim 4, wherein the data fusion parameter calculation method based on the calibration block in the step S32 includes the following steps:
s321: a finely-machined cuboid calibration block is adopted, the width of the calibration block is L, two laser displacement sensors need to be irradiated on the same straight line in the calibration process, and the average value of multiple times of calibration is taken as the final calibration result;
s322: the rotation angle alpha is obtained, the data collected by the two sensors are subjected to linear fitting, and the straight lines of the data fitting detected by the two sensors are respectively l in the ith calibration process i1 、l i2 The slope is respectively k i1 、k i2 The angle of inclination is theta i1 、θ i2 The rotation angle alpha in the ith calibration process i The calculation is as follows:
s323: the calculation of the translation parameters DX and DY is that the laser displacement sensor LS1 and the laser displacement sensor LS2 respectively detect a boundary point of the calibration block, and the coordinates of the boundary point in the sensor coordinate systems are respectively (x) 1 ,y 1 )、(x 2 ,y 2 ) The sensor LS1 coordinate system is rotated by an angle alpha, point (x) 1 ,y 1 ) The rotated coordinate is (x' 1 ,y′ 1 ) The conversion formula is as follows:
according to the fixed length characteristic of the calibration block, the translation distance DX of the coordinate origin in the x-axis direction and the translation distance DY of the coordinate origin in the y-axis direction are calculated, and the calculation formula is as follows:
in the formula k 2 Is the slope, theta, of the straight line on the upper surface of the calibration block in the LS2 coordinate system of the sensor 2 Is k 2 The corresponding tilt angle.
6. The method for detecting the wear state of a pantograph slide plate based on a laser displacement sensor according to claim 1, wherein the slide plate contour data point extraction process in step S4 is as follows:
let the coordinate of the ith point of a frame of valid data be (x) i (2) ,y i (2) ) I is 1,2, …, h, h is the number of points of the frame data;
from the starting point (x) 1 (2) ,y 1 (2) ) Starting to search in sequence, and calculating two adjacent points { (x) n (2) ,y n (2) ),(x n+1 (2) ,y n+1 (2) ) Comparing the Euclidean distance d of the d with a threshold value delta d, and if d is satisfied<Δ d, then the subsequent point (x) n+1 (2) ,y n+1 (2) ) Adding to the same point set R c ＝{(x 1 (2) ,y 1 (2) ),…,(x n (2) ,y n (2) ),(x n+1 (2) ,y n+1 (2) ) In the symbol, if d.gtoreq.Δ d, then at a point (x) n (2) ,y n (2) ) As a division point, the next set of points R c+1 From (x) n+1 (2) ,y n+1 (2) ) Continuing searching for a starting point;
and after data point retrieval is finished, counting the number of data points of each point set, and extracting the point set data with the most data points as the outline data points of the sliding plate.
7. The method for detecting the wear state of a pantograph pan based on a laser displacement sensor according to claim 1, wherein the tilt correction process of the pan profile data in step S5 is as follows:
s51: according to the outline data points of the sliding plate obtained in the step S4, extracting the data points of the left and right slope areas of the sliding plate to calculate the inclination angle beta of the sliding plate, wherein the calculation formula is as follows:
β＝π-δ 1 -δ 2
in the formula, delta 1 、δ 2 Respectively carrying out first-order linear fitting on data points of a left slope area and a right slope area of the sliding plate and then carrying out inclination angles of the sliding plate in the horizontal direction;
s52: after the slide angle of inclination is acquireed, carry out inclination correction to slide profile data, the correction formula is as follows:
in the formula (x) n (2) ,y n (2) ) As fused data points, (u) n ,v n ) Are corrected data points.
8. The method for detecting the wear state of the pantograph slide plate based on the laser displacement sensor according to claim 1, wherein the curve fitting process in the step S6 is as follows:
s61: based on the least square principle and a preset error tolerance e, automatically determining the length of each section by adopting a third-order polynomial fitting equation, and recording initial segmentation points and fitting coefficients;
s62: dividing each initial segmentation interval into an overlapping area and a non-overlapping area according to the overlapping proportion eta, wherein a fitting equation of data in the non-overlapping area is an initial fitting equation;
s63: performing least square fitting on data points in the overlapping area under the condition that two end points in the overlapping area meet the first-order continuous constraint to obtain a data fitting equation of the overlapping area;
when least square fitting is carried out on data points of the overlapped area, if the number of the data points of the overlapped area is less than 4, first-order linear fitting is adopted, otherwise, third-order polynomial fitting is adopted, two end points of the overlapped area meet first-order linear constraint, and the constraint condition is as follows:
in the formula (p) 1 ,q 1 )、(p 2 ,q 2 ) Respectively representing two endpoints of an overlap region, the polynomial fitting equation of the overlap region is
The polynomial fitting equations of the front and back adjacent non-overlapping regions are respectively
k is the polynomial degree of the curve;
s64: and obtaining regression coefficients and segmentation points of the polynomial equation of the intersection area and the non-intersection area, and realizing the fitting of the whole slide plate outline data points.
9. The method for detecting the wear state of the pantograph slide plate based on the laser displacement sensor according to claim 1, wherein the actual slide plate wear curve obtaining process in step S7 is as follows:
s71: estimating the profile of the sliding plate when the sliding plate is not worn based on the unworn area of the upper surface of the sliding plate, and taking the estimated curve as the initial profile of the sliding plate, wherein the process is as follows:
s711: the sliding plate is divided into a left slope area, a horizontal area and a right slope area, wherein the left slope area and the right slope area are not in contact with a contact line, and the outlines acquired by the left slope area sensor and the right slope area sensor are initial outlines;
s712: estimating the initial contour of the horizontal area of the sliding plate according to unworn areas of two side parts of the horizontal area of the sliding plate, wherein the specific process is as follows:
if the number of data points of the whole sliding plate is q, extracting data points in [1, q/3], [2q/3, q ], detecting the minimum distance values by the laser displacement sensor to be vl _ min and vr _ min respectively, taking the data points positioned in [ vl _ min-0.2, vl _ min ], [ vr _ min-0.2, vr _ min ] as partial data of a horizontal unworn area of the sliding plate, and taking corresponding average values to be vl _ ave and vr _ ave respectively;
simulating the initial machining state of the sliding plate by using a random error with the amplitude of 2 × abs (vl _ ave-vr _ ave)/3 and adopting adaptive piecewise curve fitting to realize the estimation of the horizontal initial contour of the sliding plate by taking (vl _ ave + vr _ ave)/2 as a reference value;
s713: splicing the outlines of the left slope area and the right slope area of the sliding plate with the horizontal initial outline of the sliding plate to obtain the initial outline of the complete sliding plate;
s72: curve matching is carried out on the actual outline and the initial outline of the sliding plate, points are taken at equal intervals, and the actual outline and the initial outline are subjected to subtraction operation to obtain an actual abrasion curve of the sliding plate; the curve matching process is as follows:
after the initial contour is obtained, the actual contour and the initial contour are registered according to the unworn characteristics of the left slope area and the right slope area of the sliding plate, and if the initial contour data point set is { (u 1) 1 ,v1 1 ),…,(u1 n1 ,v1 n1 ) The point set of the actual contour is { (u 2) 1 ,v2 1 ),…,(u2 n2 ,v2 n2 )}；
Extracting left and right slope region data points of the initial contour and the actual contour respectively, performing third-order polynomial curve fitting, and performing deviation model establishment on the fitted data, wherein curve matching deviation z is as follows:
wherein (u1_ l) i1 ,v1_l i1 )、(u1_r i1 ,v1_r i1 ) For the left and right slope data points of the initial contour, (u2_ l) i2 ,v2_l i2 )、(u2_r i2 ,v2_r i2 ) The data points are left slope data points and right slope data points of the actual contour, m1 and m2 are data points for matching the left slope and the right slope respectively, and delta u and delta v are translation parameters of the actual contour of the sliding plate;
and (4) carrying out constrained nonlinear optimal value calculation on the deviation model, wherein the parameters delta u and delta v corresponding to the minimum value of the deviation z are final matching parameters.
10. The method for detecting the wear state of the pantograph slide plate based on the laser displacement sensor according to claim 1, wherein the analysis process of the wear state of the slide plate in the step S8 is as follows:
after obtaining the actual wear curve of the sliding plate, adopting the maximum wear loss W M Wear variation W V And eccentric wear amount W P The 3 variables were analyzed for the state of the skateboard, and were defined as follows:
W M ＝max(W(x)),x∈[0,L s ]
wherein W (x) represents a sliding plate wear value at position x, L s Indicating the length of the worn area of the slide, W ave Is the average wear value of the skateboard; i represents a position number, n represents the total number of positions;
based on the maximum wear loss W M Wear variation W V And eccentric wear amount W P Analyzing the abrasion state of the sliding plate, wherein the specific judgment rule is as follows:
(1) when the maximum abrasion loss W of the slide plate M Greater than wear threshold G WM When the sliding plate is in an over-abrasion state;
(2) when the slide plate is eccentrically worn W P Greater than the partial wear threshold G WP When the sliding plate is worn, the sliding plate is asymmetric in wear, and eccentric wear occurs;
(3) when wear changes amount abs (W) V ) Greater than a threshold value G WV When the sliding plate is worn, the sliding plate wearing curve is raised or lowered; if the wear variation is first greater than the threshold G WV Then less than G within a set width distance WV There is a groove type wear.
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| WO2021043388A1 (en) * | 2019-09-03 | 2021-03-11 | Schweizerische Bundesbahnen Sbb | Device and method for detecting wear and/or damage on a pantograph |
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| CN107478176A (en) * | 2017-08-14 | 2017-12-15 | 广东工业大学 | A kind of pantograph loss detection method and system |
| CN108801134A (en) * | 2018-05-07 | 2018-11-13 | 南京理工大学 | A kind of abrasion of pantograph pan monitoring device and method based on sub-pixel edge detection |
| CN108981565A (en) * | 2018-05-07 | 2018-12-11 | 南京理工大学 | A kind of municipal rail train pantograph disalignment monitoring device and method |
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