Wheel polygon roughness limit value measuring method based on vehicle dynamics

Abstract

The invention discloses a wheel polygon roughness level limit value measuring method based on vehicle dynamics, which comprises the following steps of: proposing a concept of a wheel-rail force level by analyzing wheel-rail force characteristics and rules under a wheel polygon fault, and constructing a response curved surface of the wheel-rail force level with respect to a vehicle speed, an order and a 0dB / 1 [mu] m roughness level by utilizing a KSM (Kernel-Square-Modulation); the relation between the wheel-rail force level and the roughness level is obtained, then the relation between the wheel-rail force amplitude and the wheel roughness level is analyzed, the limit value of the wheel-rail force amplitude is calculated through the limit value of the wheel load shedding rate, and then the limit value of the wheel-rail force amplitude is converted into the limit value of the roughness level.

Description

Technical Field

[0001] The invention relates to a fault diagnosis method, in particular to a wheel polygon roughness level limit value measurement method based on vehicle dynamics. Background Art

[0002] High-speed rail is an important part of the world's transportation field today. Its fast, efficient and safe characteristics make it attract much attention. With the continuous advancement of science and technology and people's pursuit of quality of life, high-speed rail has become a necessity. The safety of railway transportation is of vital importance, and high-speed rail, as a key component, will face new challenges in the future. On the one hand, the operating speed of domestic EMUs is generally between 200 and 350 km / h. However, with the development of technology, the number of EMUs with higher speed levels is increasing. The continuous improvement of vehicle operating speed brings convenience but also brings many thorny problems. On the other hand, with the rapid expansion of the scale of high-speed railways and the increase in the service time of high-speed railway equipment, the infrastructure has gradually entered the maintenance cycle, and the pressure on EMU maintenance has also increased. In many years of use, a series of problems such as high cost and over-maintenance have been found. The above factors have led to the increasing pressure on high-speed rail safety assurance and operation and maintenance, bringing more safety risks and operation and maintenance costs. Therefore, it is particularly important to study more reasonable and effective theories and methods for vehicle condition monitoring and fault diagnosis.

[0003] In recent years, wheel polygon problems have become more and more common, and trains of various models and lines have experienced wheel polygon phenomena. The wheels and rails are in rolling contact to transmit traction and braking force, and the wheel circumference is easily subjected to uneven loads. In addition, the material related to the friction properties of the wheel tread circumference is uneven, which causes uneven friction in the circumference, which will inevitably directly cause uneven sliding and wear characteristics, bringing inevitable wear of the wheels and rails. When wear causes the wheel circumference to be non-circular in a wavy shape, this is the wheel polygon phenomenon.

[0004] After the wheel polygon is generated, it will cause a main frequency related to the vehicle speed and the polygon order. When this frequency is close to a certain modal frequency of vehicle parts, resonance will occur, which will seriously affect the fatigue life of the parts, generate noise, and even affect the stability, comfort and safety. With the increase of train mileage, wheel polygon failures are inevitable. In addition, the characteristic frequency range of wheel polygons is increasing with the continuous increase of train speed. The vibration of parts caused by polygons may also bring serious safety hazards. Therefore, the wheel polygon problem cannot be ignored. However, the current online monitoring technology of wheel polygons is mostly "qualitative judgment", that is, judging whether the polygon occurs, and cannot quantitatively judge the severity of the wheel polygon. Therefore, the maintenance strategy is to regularly measure the wheel tread, judge whether it exceeds the limit according to the radial runout and roughness level, and repair the over-limit wheels, or repair them according to the mileage, which undoubtedly increases the operation and maintenance costs. Therefore, it is very necessary to realize online quantitative monitoring of wheel polygons in the condition monitoring and fault diagnosis system. Among them, formulating reasonable polygon limits is an indispensable link, which has practical engineering significance for improving the benefits of operation and maintenance. Summary of the invention

[0005] In view of the above-mentioned deficiencies in the prior art, the present invention provides a method for measuring the limit value of wheel polygon roughness level based on vehicle dynamics.

[0006] In order to achieve the above-mentioned object of the invention, the technical solution adopted by the present invention is:

[0007] A method for measuring wheel polygon roughness limit based on vehicle dynamics comprises the following steps:

[0008] S1. Establish the Kriging proxy model response surface of wheel-rail force level with respect to vehicle speed and order at 0dB / 1μm roughness level;

[0009] S2. Input any vehicle speed and order into the established Kriging proxy model response surface to obtain the wheel-rail force level corresponding to the vehicle speed and order at a roughness level of 0 dB / 1 μm, and obtain the wheel-rail force level at any roughness level based on the linear relationship between the roughness level and the wheel-rail force level;

[0010] S3, analyze the non-serious order components of the polygon based on the measured data and establish the relationship between the wheel-rail force amplitude and the roughness level;

[0011] S4. Calculate the wheel roughness level limit according to the wheel weight reduction rate limit based on the relationship between the wheel-rail force amplitude and the roughness level.

[0012] Furthermore, the wheel-rail force level in S1 is expressed as:

[0013]

[0014] in, is the wheel-rail force level, F k is the effective value of the wheel-rail force spectrum amplitude, F 0 is the amplitude reference value.

[0015] Furthermore, the specific method of analyzing the non-serious order components of the polygon in S3 is:

[0016] S31, selecting a plurality of wheels including first-order and multi-order protruding polygons from the train sample, and performing simulation with the selected wheels to analyze the non-serious order components of the polygons;

[0017] S32, removing abnormal values ​​from the statistically analyzed wheel roughness levels and calculating the average to obtain a roughness level average;

[0018] S33. Using the established KSM response surface and the calculated roughness level mean, the sum of the wheel-rail force spectrum amplitudes corresponding to the polygonal orders where the wheel is not obvious under multiple speed conditions is calculated respectively.

[0019] Furthermore, the limit value of the wheel-rail force level in S3 is expressed as:

[0020]

[0021] In the formula, is the limit value of wheel-rail force level, P 均 is the mean wheel-rail force, A sumlow is the sum of the wheel-rail force spectrum amplitudes corresponding to the inconspicuous polygonal orders, and n is the number of obvious polygonal orders

[0022] Furthermore, the wheel-rail force amplitude in S3 satisfies the following conditions:

[0023] nA highn +A sumlow ≤0.8P 均

[0024] Where n is the number of severe polygon orders, A highn is the magnitude of these severe polygonal orders when there are n severe polygonal orders, A sumlow is the sum of the wheel-rail force spectrum amplitudes corresponding to the inconspicuous polygon order, P 均 is the mean wheel-rail force.

[0025] Furthermore, the wheel roughness level limit value in S4 is calculated as follows:

[0026]

[0027] In the formula, is the roughness limit, is the limit value of the wheel-rail force level, is the wheel-rail force level when the roughness level is 0dB / 1μm, P 均 is the mean wheel-rail force, A sumlow is the sum of the wheel-rail force spectrum amplitudes corresponding to the inconspicuous polygonal orders, and n is the number of obvious polygonal orders

[0028] The present invention has the following beneficial effects:

[0029] The research method of wheel roughness level limit based on vehicle dynamics proposed in the present invention not only takes into account the vehicle speed and vehicle modal information, but also takes into account the number of obvious polygon orders. It can more accurately judge the degree of wheel polygon failure, reduce missed alarms and false alarms, and reduce operation and maintenance costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 The figure is a flow chart of the wheel polygon roughness level limit measurement method based on vehicle dynamics.

[0031] Figure 2 It is a schematic diagram of the KSM response surface corresponding to the wheel roughness level of 0dB / 1μm in an embodiment of the present invention.

[0032] FIG3 is a diagram showing the amplitude statistics of the wheel-rail force spectrum according to an embodiment of the present invention, wherein (a) is a diagram showing the amplitude statistics of the complete wheel-rail force spectrum, and (b) is a diagram showing the amplitude statistics of the local wheel-rail force spectrum.

[0033] FIG4 is a schematic diagram of the roughness level and tread polar coordinate information of a simulated wheel according to an embodiment of the present invention, wherein (a) is the roughness level and (b) is the wheel tread polar coordinate.

[0034] Fig. 5 is a schematic diagram of the calculation results of the maximum wheel-rail vertical force, derailment coefficient, and wheel weight reduction rate at different phases of an embodiment of the present invention, wherein (a) is the maximum wheel-rail vertical force of the left wheel, (b) is the maximum wheel-rail vertical force of the right wheel, (c) is the derailment coefficient, and (d) is the wheel weight reduction rate.

[0035] Figure 6 Schematic diagram of sample calculation results of an embodiment of the present invention.

[0036] Figure 7 Schematic diagram of the rough level mean result of an embodiment of the present invention.

[0037] Figure 8 It is a schematic diagram of the next-order obvious polygonal roughness level limit curve at each speed level in an embodiment of the present invention.

[0038] Figure 9 is a schematic diagram of multi-order obvious polygonal roughness level limit curves at various speed levels of an embodiment of the present invention, where (a) is a vehicle speed of 250 km / h, (b) is a vehicle speed of 300 km / h, (c) is a vehicle speed of 350 km / h, and (d) is a vehicle speed of 400 km / h. DETAILED DESCRIPTION

[0039] The specific implementation modes of the present invention are described below so that those skilled in the art can understand the present invention. However, it should be clear that the present invention is not limited to the scope of the specific implementation modes. For those of ordinary skill in the art, as long as various changes are within the spirit and scope of the present invention as defined and determined by the attached claims, these changes are obvious, and all inventions and creations utilizing the concept of the present invention are protected.

[0040] A method for measuring wheel polygon roughness limit based on vehicle dynamics comprises the following steps:

[0041] S1. Establish the Kriging proxy model response surface of wheel-rail force level with respect to vehicle speed and order at 0dB / 1μm roughness level;

[0042] If the Kriging proxy model method is used to obtain the transfer relationship between the wheel-rail vertical force and the order, vehicle speed, and roughness level, the three variables will lead to too many simulation conditions. Therefore, the concept of wheel-rail force level is defined, and the linear relationship between the wheel-rail force level and the roughness level is obtained, which simplifies the problem to obtain the transfer relationship between the wheel-rail force level and the order and vehicle speed, greatly reducing the amount of calculation. The wheel-rail force level is defined according to the following formula (1), and then the transfer relationship between the wheel-rail force level and the order, vehicle speed, and roughness level is studied.

[0043] The wheel-rail force level is defined as follows:

[0044]

[0045] In the formula, is the wheel-rail force level (dB / 1kN), F k is the effective value of the wheel-rail force spectrum amplitude (kN), F 0 is the amplitude reference value, which is taken as 1kN.

[0046] In this embodiment, there is a linear relationship between the roughness level and the wheel-rail force level. Therefore, the mapping relationship between the roughness level and the wheel-rail force level can be obtained by using KSM to establish a relationship surface between the wheel-rail force level, the polygon order and the vehicle speed under a certain wheel roughness level. In KSM modeling, the order and the vehicle speed are regarded as input variables, and the wheel-rail force level is regarded as the output response. The following working conditions are adopted, that is, in the case of straight line and no track excitation, the wheel roughness level is 0dB / 1μm, and dynamic simulation calculations are performed on the working conditions of 31 vehicle speeds (25, 37.5, ..., 400km / h) and 40 different orders (1, 2, ..., 40th order) combinations.

[0047] Figure 2 is the KSM response surface corresponding to the wheel roughness level of 0dB / 1μm. Figure 2It can be seen that when the order is constant, the wheel-rail force level and the vehicle speed present a complex nonlinear relationship. When the vehicle speed is constant, the wheel-rail force level and the order also present a complex nonlinear relationship. Generally speaking, the vibration level increases with the increase of order and vehicle speed, but at certain orders and vehicle speeds, the KSM response surface will show a ring-shaped "bulge", that is, the vibration level will produce an obvious peak, which ultimately causes the KSM response surface to present a "step-like" shape.

[0048] As for the accuracy of KSM, the accuracy of the KSM response surface of 0dB / 1μm roughness level is first verified. The sample points are selected from working conditions other than the samples used to establish the KSM response surface. Three vehicle speeds are randomly selected within the sample space, namely 110, 210, and 310km / h, and then 5 orders are selected, namely 11, 15, 19, 23, and 27, with a total of 15 samples. The simulation calculation results are compared with the KSM response surface estimation results. The comparison results are shown in Table 1. As can be seen from the table, the wheel-rail force level obtained by simulation is almost consistent with the KSM response surface estimation value, and the minimum absolute error between the two is 0.01dB / 1kN, and the maximum absolute error is 0.85dB / 1kN, indicating that the KSM accuracy established in this embodiment can meet the research needs and can replace the original dynamic simulation model to obtain the wheel-rail force level under various vehicle speeds, polygon orders, and roughness levels.

[0049] Next, the accuracy of wheel-rail force level estimation under different roughness levels is verified. The order is selected as 24, and two vehicle speeds are selected, namely 175 and 275 km / h. Then 8 roughness levels are selected in arithmetic progression, namely -4, 0, ..., 24 dB / 1 μm, for a total of 16 samples. As can be seen from the previous analysis, the roughness level and the wheel-rail force level are linearly related and the slope is 1. Therefore, this embodiment takes the point on the KSM response surface of the roughness level of 0 dB / 1 μm as the reference, and adds the difference between the roughness level and 0 dB / 1 μm on the basis of this wheel-rail force level as the estimated value of the wheel-rail force level. The simulation calculation results are compared with the estimated results. The comparison results are shown in Table 2. As can be seen from the table, the wheel-rail force level obtained by simulation is almost consistent with the estimated value, and the absolute error is less than 0.1 dB / 1 kN, indicating that the roughness level and the wheel-rail force level have a good linear relationship. Therefore, the method of estimating the wheel-rail force level by the KSM response surface established by this embodiment can meet the research requirements.

[0050] Table 1 KSM accuracy verification

[0051]

[0052] Table 2 KSM accuracy verification

[0053]

[0054] S2. Input any vehicle speed and order into the established Kriging proxy model response surface to obtain the wheel-rail force level corresponding to the vehicle speed and order at a roughness level of 0 dB / 1 μm, and obtain the wheel-rail force level at any roughness level based on the linear relationship between the roughness level and the wheel-rail force level;

[0055] The specific method to obtain the wheel-rail force level under any roughness level is:

[0056]

[0057] is the wheel-rail force level (dB / 1kN), where For the rough level, The wheel-rail force level corresponding to the measured order and speed on the KSM response surface when the roughness level is 0dB / 1μm.

[0058] S3, analyze the non-serious order components of the polygon based on the measured data and establish the relationship between the wheel-rail force amplitude and the roughness level;

[0059] In this embodiment, the following steps are specifically included:

[0060] S31, selecting a plurality of wheels including first-order and multi-order protruding polygons from the train sample, and performing simulation with the selected wheels to analyze the non-serious order components of the polygons;

[0061] In this embodiment, 82 wheels with one or more protruding polygons are selected from the train sample, and these wheels with different roughness levels are used for simulation to observe the wheel-rail force spectrum amplitude of the polygon order that is not serious. Figures 3(a) and 3(b) show the wheel-rail force spectrum amplitude corresponding to each order under 82 different wheel out-of-round excitations, and box-whisker plots are used for statistics. It can be seen from the figure that among the wheels with more serious wheel polygons on this train, there are generally more serious 19th and 20th order wheel polygons, while the wheel-rail force amplitude corresponding to the less serious polygon order is about 2kN or less.

[0062] Since there are many non-serious polygon orders and the corresponding wheel-rail force spectrum amplitudes are small, the situation will be too complicated if they are considered one by one. The above statistical values ​​are now integrated into a constant term to represent the non-serious polygon frequency components in the wheel-rail force with a constant value.

[0063] Let the wheel-rail force amplitude be A and the maximum wheel-rail force be P max , the minimum value is P min The mean wheel-rail force is P 均 The wheel-rail force spectrum amplitude corresponding to the most prominent polygon order is A max The wheel-rail force spectrum amplitude corresponding to the i-th order is A i(i=1, 2, ..., 40). Calculate the 82 sample results and sum the wheel-rail force spectrum amplitudes corresponding to the polygonal frequencies of each order less than 2 kN, and let it be A sumlow In order to more accurately reflect the influence of the superposition of non-serious orders on the wheel-rail force amplitude, it is necessary to exclude the influence of serious orders as much as possible. Therefore, from these 82 samples, only samples with one order amplitude exceeding 2kN are selected, and their wheel-rail force amplitude A is calculated, and the amplitude A corresponding to the order exceeding 2kN is subtracted. max , A sumlow With AA max Comparative analysis is performed and the calculation results are as follows Figure 6 As shown, the selected sample A sumlow The maximum value is 30.16kN, the minimum value is 6.64kN, the average value is 18.40kN, and AA max The maximum value is 10.00kN, the minimum value is 5.06kN, and the average value is 6.88kN. Obviously, the sum of the amplitudes of each order less than 2kN has a large interval span, so all samples A sumlow The mean of A sumlow The value of is more appropriate. In addition, A sumlow With AA max There is a certain gap between the mean values, but this gap can be retained to offset the impact of track unevenness and model errors, but specific adjustments are still needed when the limit is finally formulated. The above statistical values ​​are all calculated at a speed of 300km / h. However, the amplitudes of each order calculated at different speeds are different, and the resulting A sumlow The mean is also different, but the roughness level of the sample wheels is unchanged, so the roughness level of the wheels of each sample is statistically analyzed next.

[0064] S32, removing abnormal values ​​from the statistically analyzed wheel roughness levels and calculating the average to obtain a roughness level average;

[0065] In this embodiment, the wheel roughness levels of 82 samples are counted, and the average of the roughness level samples of each order after removing the abnormal values ​​is calculated, and the following is obtained: Figure 7 The mean value of the roughness level is shown in the figure. It can be seen from the figure that the 19th and 20th order roughness levels are higher and have obviously exceeded the ISO 3095 limit. The 18th order roughness level is also close to the limit. sumlow The amplitudes of these three orders need to be eliminated.

[0066] S33. Using the established KSM response surface and the calculated roughness level mean, the sum of the wheel-rail force spectrum amplitudes corresponding to the polygonal orders where the wheel is not obvious under multiple speed conditions is calculated respectively.

[0067] The established wheel-rail force level KSM response surface and the calculated roughness level mean are used to calculate the A values ​​for speed levels of 250, 300, 350, and 400 km / h.sumlow The calculation results are shown in Table 3.

[0068] Table 3 The sum of the amplitudes of the non-serious polygonal orders at each speed level A sumlow

[0069]

[0070]

[0071] When analyzing the wheel-rail force components, the wheel-rail force amplitude can be divided into severe polygonal order frequency components and non-severe polygonal order frequency components. The amplitude of the severe polygonal order frequency component is considered as the maximum amplitude, that is, the amplitudes of the more severe polygonal orders are directly added, while the non-severe polygonal order frequency components are calculated by averaging the roughness levels of the non-severe orders in 82 wheel samples, and combining the wheel-rail force level KSM response surface to calculate the sum of the amplitudes of the non-severe polygonal orders, which is considered as a constant, which has different values ​​at different speeds. Finally, the wheel-rail force amplitude is divided into two parts, and both can be obtained by calculation. The severe polygonal order part can be calculated by the roughness level of the order through the wheel-rail force level KSM response surface, while the non-severe polygonal order component has been obtained based on the statistical roughness level. So far, the relationship between the wheel-rail force amplitude and the roughness level has been established.

[0072] S4. Calculate the wheel roughness level limit according to the wheel weight reduction rate limit based on the relationship between the wheel-rail force amplitude and the roughness level.

[0073] When a wheel has a polygonal fault and runs on the track, it will move up and down, causing the wheel-rail force to increase or decrease, affecting the safety of vehicle operation. The derailment coefficient and wheel weight reduction rate under different wheel polygon excitations are analyzed below. However, the derailment coefficient and wheel weight reduction rate are both related to the difference in vertical force between the left and right wheels of the same axis. When the left and right wheels move up and down at the same time, these two indicators are often very small, but in this case the wheel-rail vertical force will be very large. Therefore, it is necessary to comprehensively consider the three indicators of derailment coefficient, wheel weight reduction rate, and wheel-rail vertical force. This leads to thinking that when the excitation other than the wheel polygon is not considered, the rotation phase difference between the left and right wheels of the same axis will affect the vertical movement relationship between the left and right wheels, resulting in changes in the derailment coefficient, wheel weight reduction rate, and wheel-rail force. Therefore, the influence of different rotation phases of the left and right wheels of the same axis on these three indicators is analyzed below.

[0074] Figure 4 shows the roughness level and tread polar coordinate information of the two simulated wheels, where the 18th and 22nd order roughness levels of wheel 1 are 15dB / 1μm, and the 18th order roughness level of wheel 2 is 15dB / 1μm. The remaining order roughness levels of the two wheels are low and basically the same. This design is to make the polygonal excitation of the two wheels interfere. The excitation of wheel 1 is input to the right wheel of axle 1, and the excitation of wheel 2 is input to the left wheel of axle 1. The phase of wheel 1 is changed to observe the changes in the wheel-rail vertical force, derailment coefficient and wheel weight reduction rate under different phases of the left and right wheels.

[0075] From the periodicity of polygonal excitation, it can be seen that if the polygonal excitation contains only one severe polygonal order, the phase change interval can select the period of the order that needs to be concerned, such as the period of the 18th order is 20°, and the period of the 22nd order is about 16.36°. If it contains multiple severe polygonal orders, the common multiples of the corresponding periods of multiple severe orders should be selected. For example, the period of the 18th order and the 22nd order combined should be the common multiple of the periods of the two, that is, 180°. However, since the periods of the two are relatively close, taking a larger value can observe the general rules, so observe the results at the phase interval of 2° from 0 to 20°. Figure 5 (a)-(d) shows the calculation results of the maximum wheel-rail vertical force, derailment coefficient, and wheel load reduction rate at different phases. As can be seen from the figure, under different phases, the maximum change of the vertical force of the 1L wheel and the 1R wheel is 0.2469kN, and the maximum change of the vertical force of the 1R wheel is 0.5402kN, and the maximum change of the wheel-rail force is not large; the derailment coefficient is generally very low, about 0.027, and the difference between the maximum and minimum values ​​is only 0.0006; the maximum value of the wheel weight reduction rate is 0.17, and the minimum value is 0.07, with a difference of 0.1. The wheel weight reduction rate changes significantly, and the maximum value is nearly 2.43 times the minimum value, and the phase difference between the maximum and minimum values ​​is only 10°. Theoretically speaking, the higher the polygon order, the smaller the corresponding period of the order, which means that at the same time, the crest of one wheel meets the trough of the other wheel, and the more likely it is to produce left and right overturning motion, resulting in an increase in the wheel weight reduction rate. In addition, 10° is exactly half of the 18th-order polygon period, which means that at the same moment, when the coaxial left and right wheels are in contact with the rail, one wheel is at the trough of the 18th-order waveform, and the other is at the peak. It is assumed that the wheel weight reduction rate is the largest when the vertical distance between the coaxial left and right wheels is the largest at the same moment. In summary, from the perspective of safety, wheel polygon failures, especially high-order polygon failures, are prone to cause a large wheel weight reduction rate, and the wheel weight reduction rate often reaches a maximum value when the coaxial left and right wheels are at the vertical extreme position. Therefore, this embodiment studies the wheel polygon limit from the perspective of wheel weight reduction rate and wheel-rail force.

[0076] The wheel weight reduction rate is analyzed. The wheel weight reduction rate is the ratio of the wheel weight reduction of one side of the wheelset to the average wheel weight of the vehicle. The calculation formula of the wheel weight reduction rate is as follows:

[0077]

[0078] Where ΔP is the wheel load reduction, P is the average wheel-rail vertical force of the left and right wheels, and P 1 , P 2 are the vertical forces of the left and right wheels and rails respectively.

[0079] The "High-speed EMU Vehicle Test Specification" GB5599-2019 stipulates that when the vehicle speed is greater than 160km / h, the limit of the wheel weight reduction rate is 0.8, that is:

[0080]

[0081] Since the wheel roughness limit should be applicable to each wheel, it is assumed that the left and right wheels are exactly the same, but there is a certain phase difference between the left and right wheels, that is, the wheel-rail force amplitudes of the left and right wheels are the same, but the wheel-rail force values ​​of the left and right wheels at the same time are not necessarily equal. It is assumed that the wheel-rail force of the left wheel is smaller than that of the right wheel at the same time, and the following is made:

[0082] P 2 =P 1 +P Δ (5)

[0083] Where P Δ is the difference between the left and right wheel-rail forces.

[0084] Substituting formula (5) into formula (4) yields:

[0085]

[0086] Simplified

[0087]

[0088] Right now

[0089]

[0090] Right now

[0091]

[0092] From the above analysis, we can see that the upper and lower limits of the wheel-rail force are approximately equal to the mean value of the wheel-rail force plus or minus the wheel-rail force amplitude, so

[0093] (P 1 ) min =P 均 -A (10)

[0094] (P Δ ) max =2A (11)

[0095] Where A is the amplitude of the wheel-rail force.

[0096] Substituting equation (10) and equation (11) into equation (9), we can obtain

[0097] A≤0.8P 均 (12)

[0098] From equations (9) to (12), it can be seen that in order to meet the wheel-weight reduction rate limit requirements, the wheel-rail force amplitude must be less than or equal to 0.8 times the wheel-rail force average, and when the wheel-rail vertical force difference between the left and right wheels on the same axis is the largest at the same time, the wheel-weight reduction rate reaches the maximum value, which is consistent with the previous conjecture. So far, through analysis and calculation, the wheel-weight reduction rate limit is converted into the wheel-rail vertical force amplitude limit. The relationship between the wheel-rail vertical force amplitude and the wheel-rail force level is studied below.

[0099] The wheel load reduction rate limit can be converted into the wheel-rail force amplitude limit, and the wheel-rail force amplitude is divided into a severe polygonal order part and a non-serious polygonal order. Then formula (12) can be converted into:

[0100] A sumhigh +A sumlow ≤0.8P 均 (13)

[0101] In the formula, A sumhigh is the sum of the amplitudes corresponding to the frequencies of the severe polygonal orders, which is considered to be the case with the largest amplitude, and the amplitudes of each severe polygonal order are equal, then it can be transformed into:

[0102] nA highn +A sumlow ≤0.8P 均 (14)

[0103] Where n is the number of severe polygon orders, A highn is the magnitude of these severe polygonal orders when there are n severe polygonal orders, then its limit is:

[0104]

[0105] Substituting the wheel-rail force level formula (1) into the above formula, the limit value of the wheel-rail force level is obtained:

[0106]

[0107] The limit value of the roughness level can be obtained from the linear relationship between the wheel-rail force level and the wheel roughness level:

[0108]

[0109] In the formula, is the roughness limit, It is the wheel-rail force level when the roughness level is 0dB / 1μm, which can be obtained from the wheel-rail force level KSM response surface.

[0110] The 0dB / 1μm KSM response surface of each order has different values ​​at different speeds. Therefore, different roughness level limits should be used at different speeds. The typical speed levels of high-speed trains are 250, 300, 350, and 400 km / h. The roughness level limits of each order are calculated by formula (17), as follows: Figure 8 As shown in the figure. It can be seen that at the same speed, the limit value generally decreases with the increase of the order, but the limit values ​​of some orders and nearby orders increase slightly. This is a limit value for a single order, that is, when one order of wheel roughness reaches this limit value, it is necessary to repair it immediately. The measured wheel may have more than one order of severe polygons, so it is possible to consider setting multiple order limits. For example, when the n-order roughness exceeds the n-order limit, maintenance is also required.

[0111] The roughness levels of 82 groups of wheels with obvious polygons were counted. As shown in Figure 9, there are still 3 orders of wheel roughness with larger roughness levels after averaging, so the limit is considered according to the 3 severe polygon orders. The roughness level limits when there are 1, 2, and 3 severe polygon orders at different speed levels are calculated, as shown in Figure 9. As can be seen from the figure, the multi-order roughness level limit is the 1st order limit shifted downward, and the judgment rule is as follows: when 1 order exceeds the 1st order limit, or when 2 orders exceed the 2nd order limit, or when 3 orders exceed the 3rd order limit, it is judged that the wheel needs to be repaired.

[0112] This embodiment uses multi-order roughness level limits to verify 120 sets of simulation data, including 40 sets of data at speed levels 250, 300, 350, and 400 km / h. Each set of data is run under uniform straight-line conditions. In terms of polygonal excitation settings, 100 wheel tread data with obvious polygonal faults are selected, and only two randomly selected measured wheel treads are input as wheel polygonal excitations on the left and right wheels of the 1st axle, mainly to verify whether there will be omissions and false alarms under the above upper limit standards. Omissions refer to the situation where the wheel weight reduction rate of the 1st axle is greater than 0.8 or the wheel-rail force amplitude exceeds 0.8 times the wheel-rail force mean, but the polygonal roughness level limit determines that the left and right wheels of the 1st axle are not over the limit, which is not allowed. A false alarm means that although the left or right wheel of axle 1 is judged to be over the limit, the wheel weight reduction rate is not greater than 0.8 or the wheel-rail force amplitude is not greater than 0.8 times the wheel-rail force average. This is because the most serious situation is considered when formulating the rough level limit, so a small number of false alarms is acceptable. The verification results are shown in Table 4. As can be seen from the table, among the 160 samples, the number of missed alarms is 0, the number of false alarms is 4, the missed alarm rate is 0%, and the false alarm rate is 3.33%. Among them, the specific situation of 4 groups of false alarm data is shown in Table 5. The wheel weight reduction rate or wheel-rail force amplitude is close to the limit, indicating that the limit standard has a high reliability of the alarm rate for polygonal faults.

[0113] Table 4 Verification results of roughness level limit without track irregularity

[0114]

[0115] Table 5 Details of misreported data

[0116]

[0117] Next, the reliability of the limit value under track irregularity excitation is verified. The polygonal excitation is still set in the above method, with 20 samples for each of the four speed levels, a total of 80 samples, and the verification results are shown in Table 6. Track irregularity was not considered when the roughness level limit value was formulated above. Although the sum of the calculated not serious polygon order amplitudes has a certain margin for track irregularity excitation, underreporting still occurs at the speed level of 250km / h, so the limit value needs to be adjusted and appropriately lowered.

[0118] Table 6 Verification results of roughness level limit under track irregularity

[0119]

[0120] After adjusting the limit down by 1dB / 1μm, the data with track unevenness excitation were re-verified, and the number of missed data was successfully reduced to 0.

[0121] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0122] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0123] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0124] The present invention uses specific embodiments to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

[0125] Those skilled in the art will appreciate that the embodiments described herein are intended to help readers understand the principles of the present invention, and should be understood that the protection scope of the present invention is not limited to such specific statements and embodiments. Those skilled in the art can make various other specific variations and combinations that do not deviate from the essence of the present invention based on the technical revelations disclosed by the present invention, and these variations and combinations are still within the protection scope of the present invention.

Claims

1. A wheel polygon roughness level limit measurement method based on vehicle dynamics, characterized in that: The steps include: S1. Establish the Kriging proxy model response surface of wheel-rail force level with respect to vehicle speed and order at 0dB / 1μm roughness level; S2. Input any vehicle speed and order into the established Kriging proxy model response surface to obtain the wheel-rail force level corresponding to the vehicle speed and order at a roughness level of 0 dB / 1 μm, and obtain the wheel-rail force level at any roughness level based on the linear relationship between the roughness level and the wheel-rail force level; S3, analyze the non-serious order components of the polygon based on the measured data and establish the relationship between the wheel-rail force amplitude and the roughness level; S4. Calculate the wheel roughness level limit according to the wheel weight reduction rate limit based on the relationship between the wheel-rail force amplitude and the roughness level.

2. The wheel polygon roughness level limit measurement method based on vehicle dynamics according to claim 1, characterized in that: The wheel-rail force level in S1 is expressed as: in, is the wheel-rail force level, F k is the effective value of the wheel-rail force spectrum amplitude, and F0 is the amplitude reference value.

3. The wheel polygon roughness level limit measurement method based on vehicle dynamics according to claim 1, characterized in that: The specific method of analyzing the non-serious order components of polygons in S3 is: S31, selecting a plurality of wheels including first-order and multi-order protruding polygons from the train sample, and performing simulation with the selected wheels to analyze the non-serious order components of the polygons; S32, removing abnormal values ​​from the statistically analyzed wheel roughness levels and calculating the average to obtain a roughness level average; S33. Using the established Kriging proxy model response surface and the calculated roughness level mean, the sum of the wheel-rail force spectrum amplitudes corresponding to the polygonal orders where the wheel is not obvious under multiple speed conditions is calculated respectively.

4. The wheel polygon roughness level limit measurement method based on vehicle dynamics according to claim 1, characterized in that: The limit value of the wheel-rail force level in S3 is expressed as: In the formula, is the limit value of wheel-rail force level, P 均 is the mean wheel-rail force, A sumlow is the sum of the wheel-rail force spectrum amplitudes corresponding to the inconspicuous polygon orders, and n is the number of obvious polygon orders.

5. The wheel polygon roughness level limit measurement method based on vehicle dynamics according to claim 1, characterized in that: The wheel-rail force amplitude in S3 satisfies the following conditions: nA highn +A sumlow ≤0.8P 均 Where n is the number of severe polygon orders, A highn is the magnitude of these severe polygonal orders when there are n severe polygonal orders, A sumlow is the sum of the wheel-rail force spectrum amplitudes corresponding to the inconspicuous polygon order, P 均 is the mean wheel-rail force.

6. The wheel polygon roughness level limit measurement method based on vehicle dynamics according to claim 1, characterized in that: The calculation method of the wheel roughness level limit in S4 is: In the formula, is the roughness limit, is the limit value of the wheel-rail force level, is the wheel-rail force level when the roughness level is 0dB / 1μm, P 均 is the mean wheel-rail force, A sumlow is the sum of the wheel-rail force spectrum amplitudes corresponding to the inconspicuous polygon orders, and n is the number of obvious polygon orders.

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