Railway vehicle snaking stability diagnosis identification and result level-to-level management method based on rolling vibration test bed

Abstract

The invention discloses a railway vehicle snaking stability diagnosis and identification method based on a rolling vibration test bed, and the method comprises the following steps: S1, when a railway vehicle is in snaking instability, wheel pairs present transverse oscillation behaviors along a track direction no matter whether a vehicle body snakes or a bogie snakes, and therefore, the wheel pairs are not in the transverse oscillation behaviors along the track direction; assuming that the maximum transverse movement amplitudes yw0 of the first-position wheel set and the second-position wheel set of the bogie are the same, the transverse movement of the bogie can be described as yw1 = yw0cos omega htyw2 = yw0cos (omega ht + theta), and wh instability angular frequency is the phase difference of the first-position wheel set and the second-position wheel set; s2, the elastic deformation of the primary suspension is not considered, and the motion posture of the framework can be described as follows: 10 is the axle distance of the bogie; and S3, through theoretical analysis, establishing a relationship between the transverse vibration acceleration of the framework and the transverse movement amount and the snaking frequency of the wheel set, and constructing a vehicle stability diagnosis identification evaluation index HC serving as an instability coefficient.

Description

Technical Field

[0001] The present invention belongs to the field of rail transportation technology, and in particular relates to a method for diagnosing and identifying the snaking stability of rail vehicles and managing the results in a graded manner based on a rolling vibration test bench. Background Art

[0002] Snake motion, a unique lateral oscillation phenomenon of rail vehicles, is primarily caused by the coupling of multiple factors, including the geometric relationship between the wheelset and track, vehicle structural parameters, and operating speed. Snake motion in rail vehicles primarily consists of two forms: body snake and bogie snake. Stable and rapidly convergent snake motion has minimal impact on vehicle dynamic performance. However, once it develops into an unstable state, it poses a significant threat to rail vehicle operational safety and performance. First, snake instability can trigger severe lateral impact between the wheel and rail, increasing wear on the wheel flange and rail head, significantly shortening component life. Second, frequent lateral oscillations reduce ride comfort, creating a noticeable sense of shaking and severely impacting the passenger experience. Third, in extreme cases, excessive wheelset displacement can lead to derailment, seriously threatening operational safety. Therefore, snake stability is not only a key indicator for measuring vehicle operational performance but also a core dynamic performance parameter directly related to operational safety. Scientific methods are urgently needed to accurately identify and effectively control it.

[0003] With the rapid development of high-speed railways and the continuous advancement of detection technology, research on detecting vehicle snaking instability is increasing. For new vehicles, their critical speed is often far higher than the maximum test speed of the line, making it difficult to conduct stability assessments directly on the line. However, the rolling vibration test bench for locomotives provides an effective means for studying snaking stability. The test bench is mainly composed of a mechanical system, a drive control system, a hydraulic control system, and a measurement system. The rollers of the simulated track are designed to resemble the shape of a rail head. Each roller has independent degrees of freedom and is independent of each other, allowing for simultaneous rolling, lateral, and vertical excitation. Based on this, the test bench can apply impact, swept frequency, and random excitation according to test requirements, and can accurately simulate the actual wheel-rail contact relationship. The critical speed and convergence speed, which are closely related to the stability of vehicle snaking motion, can be determined using the rolling vibration test bench's speed-up and speed-down method. The speed-up method is to keep the vehicle system in a pure rolling state under the condition of no track disturbance, and gradually increase the speed through the test bench drive control system until periodic snaking motion is observed for the first time. The speed at this time is the linear critical speed; the speed-down method is to use the test bench hydraulic control system to apply disturbance, and gradually increase the speed through the test bench drive control system to make the vehicle system unstable. The speed at this time is the nonlinear critical speed, which can also be called the actual instability speed or actual critical speed of the vehicle. Then, the disturbance is removed and the speed is slowly reduced through the drive control system. The convergence of the vehicle's snaking motion is observed with the help of the measurement system to determine the convergence speed, also known as the nonlinear stability speed.

[0004] Currently, there are two main methods for studying snaking stability on rolling vibration test rigs. The first method, based on wheelset lateral displacement, is the most commonly used detection method. This method determines vehicle snaking stability by testing whether the lateral motion amplitude of the wheelset in a pure rolling state exceeds a threshold. A wheelset lateral displacement of 1mm is generally used as the instability limit. However, bogie snaking stability can have different instability mechanisms, such as supercritical and subcritical bifurcations. The characteristics of wheelset lateral displacement differ significantly under these two typical bifurcations. In supercritical bifurcations, wheelset lateral displacement exhibits a gradual increase with speed; in subcritical bifurcations, wheelset lateral displacement may experience a sudden increase. Therefore, using a uniform instability limit of 1mm for vehicles with different snaking instability types can easily lead to misjudgments. The second method is based on the lateral acceleration of the frame ends. The GB 5599-2019 standard specifies a threshold of 0.8g for vibrations after bandpass filtering between 0.5-10Hz. This method has a good diagnostic and identification effect on bogies under high-speed instability, but the identification effect is average under conditions where the bogie instability speed is low. In addition, this method has a poor detection effect on vehicle body snaking instability and is unable to identify the vehicle body snaking instability state.

[0005] A comprehensive analysis of the two existing detection methods shows that they can only perform binary diagnostic identification of stable and unstable snaking states, and cannot achieve hierarchical management of snaking stability. Hierarchical management is a key link in achieving real-time diagnostic identification and fault diagnosis of vehicle snaking stability, and is one of the key foundational links for achieving condition-based maintenance of rail vehicles. By conducting research on the state identification and hierarchical management of vehicle snaking stability, a more accurate basis for vehicle condition-based maintenance can be provided, making vehicle maintenance more scientific and reasonable, and avoiding excessive or insufficient maintenance. At the same time, it also lays the foundation for research on active control based on vehicle snaking stability, helps improve vehicle operational safety and dynamic performance, and has important practical significance for the development of the rail transit industry. Summary of the Invention

[0006] The purpose of the present invention is to solve the above problems and provide a method for diagnosing and identifying the hunting stability of railway vehicles and hierarchical management of the results based on a rolling vibration test bench, which can improve the recognition efficiency and accuracy and at the same time achieve a certain degree of prediction of the hunting instability behavior of railway vehicles.

[0007] To solve the above technical problems, the technical solution of the present invention is: a method for diagnosing and identifying the snaking stability of a rail vehicle based on a rolling vibration test bench, comprising the following steps:

[0008] S1. When a rail vehicle experiences snaking instability, regardless of whether the vehicle body or bogie is snaking, the wheelset exhibits lateral oscillation along the track direction. Therefore, it is assumed that the maximum lateral motion amplitude of the first and second wheelset of the bogie is yw0 are the same, then its lateral movement can be described as:

[0009] y w1 =y w0 cosω h t

[0010] y w2 =y w0 cos(ω h t+θ) (1)

[0011] Among them, w h The instability angular frequency is the phase difference between the first and second wheelsets;

[0012] S2. Without considering the elastic deformation of the primary suspension, the motion posture of the frame can be described as:

[0013]

[0014] Where l0 is the bogie wheelbase;

[0015] S3. Through theoretical analysis, the relationship between the frame lateral vibration acceleration and the wheelset lateral displacement and snaking frequency is established, and a vehicle stability diagnosis and identification evaluation index H is constructed as the instability coefficient. C .

[0016] Furthermore, the lateral motion speed and acceleration of the frame in S2 can be described as:

[0017]

[0018] Therefore, the lateral vibration acceleration of the frame end can be obtained as:

[0019]

[0020] Among them, the maximum lateral vibration acceleration amplitude of the frame end measurement point is:

[0021]

[0022] Further rewriting formula (5) can be obtained:

[0023]

[0024] Furthermore, in S3, a vehicle stability diagnosis and identification evaluation index called an instability coefficient is constructed, which is expressed as:

[0025]

[0026] The present invention also discloses a hierarchical management method for the diagnosis and identification results of the snaking stability of rail vehicles based on a rolling vibration test bench, including the following steps: C After the values ​​are determined, these data are managed in a graded manner; the graded management is specifically as follows: through a large amount of calculations and rolling vibration test data, the thresholds and methods of graded management are preliminarily formulated, and the limits can be further optimized based on a large number of subsequent tests; regardless of the type of rail vehicle or the complex and changeable vehicle service environment, the grade 1 grade division limit is less than 10, the grade 2 grade division limit is 10-20, and the grade 2 and grade 3 grade division limits are 20-40.

[0027] Furthermore, the H C When ≤10, the vehicle is not unstable. At this time, the vehicle remains stable regardless of whether the excitation is loaded or removed.

[0028] Furthermore, the H C At 10<H C When ≤20, although the snaking stability state is stable, there are signs of instability. The vehicle is unstable under excitation, but it recovers to stability after the excitation is removed. Therefore, it is necessary to perform status detection on the problem wheelset.

[0029] Furthermore, the H C When the vehicle is unstable, whether it is loaded or removed, it is in an unstable state and requires subsequent inspection and maintenance. C The value can also be used to predict the vehicle's snake instability.

[0030] The beneficial effects of the present invention are:

[0031] 1. The present invention provides a method for diagnosing and identifying hunting stability of rail vehicles and managing the hierarchical results based on a rolling vibration test bench. Compared with the existing technology, the present invention proposes a method for diagnosing hunting instability of rail vehicles based on the hunting coefficient. By introducing the hunting coefficient as an innovative performance indicator, it constructs a new vehicle instability diagnosis system.

[0032] 2. The two current mainstream diagnostic technologies based on rolling vibration test benches have significant limitations. While the wheelset lateral displacement-based identification method can capture bogie snaking characteristics, the fixed instability limit of 1mm cannot adapt to the nonlinear dynamic characteristics of supercritical bifurcation bogies, such as those found on European EMUs, leading to the risk of misjudgment. The frame end lateral acceleration-based method, while highly capable of identifying bogie snaking at a threshold of 0.8g, is not suitable for determining vehicle body snaking, even if the vehicle clearly exhibits snaking motion but the detection value remains within the specified range.

[0033] 3. The instability coefficient proposed in the present invention performs well in identifying two types of snaking motions. More importantly, the instability coefficient can be managed in a graded manner according to the vehicle status and is applicable to any type of vehicle and any complex service environment. In this patent, the instability coefficient is divided into three levels. Level 1 indicates that the vehicle's snaking motion is stable and the vehicle's dynamic performance is in a safe range; Level 2 represents a critical warning state, where the system has shown an instability trend and requires enhanced monitoring; Level 3 is defined as an unstable state, triggering a maintenance warning. In addition, the instability coefficient can also predict body snaking and bogie snaking to a certain extent. If some points exceed the limit of Level 3, it proves that the vehicle has already experienced instability and requires subsequent maintenance. Achieving early warning management of maintenance is an important step in the maintenance of rail vehicles. This grading mechanism can not only adapt to the dynamic differences of different models (including Japanese and European EMUs, etc.), but also be compatible with changes in working conditions in complex service environments. Through dynamic threshold adjustment, it achieves a transition from qualitative judgment to quantitative evaluation, providing a refined decision-making basis for vehicle health management.

[0034] 4. Validated through extensive rolling vibration testing and actual line data, the instability coefficient-based diagnostic and identification method demonstrates excellent stability and robustness under varying vehicle speeds and load conditions. This method is not only applicable to bench testing on rolling vibration test rigs but can also be seamlessly migrated to online monitoring systems on operating lines, providing the rail transit industry with a solution that combines theoretical innovation with engineering value. Subsequently, based on continuously accumulated big data, adaptive optimization of the classification thresholds will be conducted to further enhance diagnostic accuracy and reliability. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 This is a comparison chart of three stability identification methods under the vehicle body snaking condition of the present invention;

[0036] Figure 2 1 is a comparison chart of three stability identification methods under bogie snaking conditions according to the present invention;

[0037] Figure 3 1 is a graph showing the limit cycle test results of different types of vehicles under snaking instability according to the present invention;

[0038] Figure 4 1 is a relationship diagram between typical instability modes and instability coefficients of rail vehicles according to the present invention;

[0039] Figure 5 It is a schematic diagram of the hierarchical management method of rail vehicle stability test results based on the instability coefficient of the present invention. DETAILED DESCRIPTION

[0040] The present invention will be further described below with reference to the accompanying drawings and specific embodiments:

[0041] like Figure 1 As shown, the present invention provides a method for diagnosing and identifying the snaking stability of a rail vehicle based on a rolling vibration test bench, comprising the following steps:

[0042] S1. When a rail vehicle experiences snaking instability, regardless of whether the vehicle body or bogie is snaking, the wheelset exhibits lateral oscillation along the track direction. Therefore, it is assumed that the maximum lateral motion amplitude of the first and second wheelset of the bogie is y w0 are the same, then its lateral movement can be described as:

[0043] y w1 =y w0 cosω h t

[0044] y w2 =y w0 cos(ω h t+θ) (1)

[0045] Among them, t refers to time, w h The instability angular frequency, θ is the phase difference between the first and second wheelsets.

[0046] S2. Without considering the elastic deformation of the primary suspension, the motion posture of the frame can be described as:

[0047]

[0048] Among them, y f is the lateral vibration displacement of the frame, is the frame pitch angle, and l0 is the bogie wheelbase.

[0049] The lateral motion speed and acceleration of the frame in S2 can be described as:

[0050]

[0051] Based on the lateral displacement of the YF frame, the lateral relative velocity and lateral acceleration are calculated, so the lateral vibration acceleration of the frame end can be obtained as:

[0052]

[0053] Among them, the maximum lateral vibration acceleration amplitude of the frame end measurement point is:

[0054]

[0055] Further rewriting formula (5) can be obtained:

[0056]

[0057] S3. Through theoretical analysis, the relationship between the frame lateral vibration acceleration and the wheelset lateral displacement and snaking frequency is established, and a vehicle stability diagnosis and identification evaluation index H is constructed as the instability coefficient. C .

[0058] In step S3, a vehicle stability diagnosis and identification evaluation index called the instability coefficient is constructed, which is expressed as:

[0059]

[0060] The present invention also discloses a hierarchical management method for the diagnosis and identification results of the snaking stability of rail vehicles based on a rolling vibration test bench, including the following steps: C After determining the values, these data are managed in a tiered manner. Specifically, through extensive calculations and rolling vibration test data, thresholds and methods for tiered management are initially formulated. Based on subsequent extensive testing, these limits can be further optimized. Regardless of the type of rail vehicle or the complex and changing vehicle service environment, the tiered classification limit for Level 1 is less than 10, the tiered classification limit for Level 2 is between 10 and 20, and the tiered classification limits for Levels 2 and 3 are between 20 and 40.

[0061] Table 1 Hierarchical management methods

[0062]

[0063] When H C When ≤10, the vehicle is not unstable. At this time, whether it is loaded or removed, the vehicle remains stable. C At 10<H C When ≤20, the snaking stability state is stable, but there are signs of instability. The vehicle is unstable under excitation, but it recovers after the excitation is removed. Therefore, it is necessary to perform status detection on the problem wheelset. C When the vehicle is unstable, whether it is loaded or removed, it is in an unstable state and requires subsequent inspection and maintenance. C The value can also be used to predict the vehicle's snake instability.

[0064] like Figure 1 The figure shows the comparison of the identification results of three stability diagnosis methods under the vehicle body hunting instability condition. Figure 1Figure (a) is a schematic diagram of the method for identifying vehicle snaking stability based on wheelset lateral displacement. The results show that at 80 km / h, after a period of excitation and then the removal of the excitation, the wheelset lateral motion returns to an equilibrium position, indicating that the vehicle snaking is stable. At 120 km / h, after a period of excitation and then the removal of the excitation, the wheelset lateral motion diverges, with the wheelset lateral displacement reaching approximately 9 mm. This indicates that the vehicle is unstable based on the wheelset lateral displacement method, and the wheelset lateral motion confirms this state. The critical speed is 120 km / h. Subsequently, the vehicle speed begins to decrease, and when it drops to 82 km / h, the wheelset lateral motion returns from a divergent state to an equilibrium position. The wheelset lateral displacement returns to 0 mm, and the speed of 82 km / h represents the vehicle's convergence rate under this operating condition. Figure 1 (b) is a schematic diagram of the vehicle snaking stability identification method based on the lateral vibration acceleration of the frame end. It can be observed that at 80 km / h, the vehicle is in the excitation process, the frame lateral vibration acceleration is very small, and the maximum peak is about 0.08g, which is significantly less than the limit of 0.8g. The vehicle is in a stable state; when the speed increases to 120 km / h, the maximum peak of the frame lateral vibration acceleration is about 0.12g, which is still less than the limit of 0.8g. Based on the identification method of the frame lateral vibration acceleration, the vehicle is still in a stable state at this time. However, in fact, the vehicle is already in an obvious unstable state, and the wheelset is in a large oscillation behavior in the lateral direction. This shows that the method based on the frame lateral vibration acceleration is inaccurate for the identification of vehicle body snaking motion, and therefore it is impossible to perform vehicle body stability identification based on the frame vibration acceleration. Figure 1 (c) is a schematic diagram of the vehicle snaking stability identification method based on the instability coefficient proposed in this patent. When the vehicle speed is 80km / h, during the excitation process, most of the results of the instability coefficient are within 10, and some points are in the numerical range of 10 to 20, and after the excitation is removed, the instability coefficient gradually decreases to close to 0, indicating that at this speed, the vehicle is generally in a stable state; when the speed is increased to 120km / h, in the early excitation process, the value of the instability coefficient is larger than that at 80km / h, and after the vehicle becomes unstable, the value of the instability coefficient rapidly increases to about 25, and after the excitation is removed, the instability coefficient remains stable at about 25, indicating that the vehicle has become snaking unstable at this time; when the vehicle speed starts to drop from 120km / h, it can be found that the instability coefficient gradually decreases, and at 440s, that is, when the vehicle speed is 81km / h, the instability coefficient decreases to close to 0, and the vehicle returns to a stable state, that is, the vehicle snaking motion converges. This result is consistent with Figure 1The results shown in (a) are completely consistent, indicating that it is feasible to judge the vehicle's snake-like stability based on the instability coefficient, and both the instability speed and the convergence speed are reflected more accurately. Figure 1 From the three vehicle hunting instability diagnosis and identification methods shown, the two vehicle hunting instability diagnosis and identification methods based on wheelset lateral displacement and instability coefficient are both feasible, and the vehicle hunting instability diagnosis method based on frame lateral vibration acceleration cannot accurately identify vehicle hunting motion.

[0065] like Figure 2 The figure shows the comparison of the diagnostic results of three stability identification methods under the bogie hunting instability condition. Figure 2 Figure (a) shows a schematic diagram of the bogie snaking stability identification method based on wheelset lateral displacement. The results show that as the vehicle speed increases from 120 km / h to 380 km / h, after a period of excitation at each speed level and then the excitation is removed, the wheelset lateral motion returns to equilibrium, indicating that the vehicle maintains snaking stability up to 380 km / h. However, when the vehicle speed increases to 420 km / h, the wheelset exhibits lateral oscillation during track excitation, demonstrating typical vehicle instability. At this point, the wheelset lateral displacement reaches approximately 8 mm, and even after the excitation is removed, the wheelset maintains lateral oscillation, with an amplitude of approximately 8 mm. This indicates that the vehicle is already unstable at this point, as determined by the wheelset lateral displacement method. This also confirms the vehicle's instability from the wheelset lateral motion, thus establishing the critical speed of 420 km / h. Then the vehicle speed began to slowly decrease. When the vehicle speed dropped to 249 km / h, the lateral movement of the wheelset returned to the equilibrium position, and the value of the wheelset lateral displacement returned to 0 mm. At this time, the vehicle's snaking instability disappeared. Therefore, it can be judged that 249 km / h is the convergence speed of the vehicle under this working condition. Figure 2 (b) is a schematic diagram of the bogie snaking stability identification method based on the lateral vibration acceleration of the frame end. In the process of the vehicle speed gradually increasing from 120km / h to 380km / h, when each speed level is under excitation, there is no harmonic vibration in the lateral vibration of the frame, and the acceleration amplitude is lower than the limit of 0.8g, with the maximum peak value of about 0.5g. Therefore, the vehicle is in a stable state at these speed levels. When the vehicle speed increases to 420km / h, the maximum peak value of the lateral vibration acceleration of the frame suddenly increases, and the amplitude is close to 2g, which obviously exceeds the limit of 0.8g, indicating that the vehicle is already in an unstable state at this time; then the vehicle speed is slowly reduced. When the speed is reduced to 249km / h, the amplitude of the lateral vibration acceleration of the frame is reduced to about 0g, indicating that the convergence speed of the vehicle under this working condition is 249km / h. This result is consistent with Figure 2 The results are consistent with those shown in (a). Figure 2Middle (c) is a schematic diagram of the vehicle snaking stability identification method based on the instability coefficient proposed in this patent. In the process of the vehicle speed gradually increasing from 120km / h to 380km / h, at each speed level under excitation, the instability coefficient results are all within 10, indicating that the vehicle is in a stable state at these speed levels. When the vehicle speed is increased to 420km / h, the vehicle's instability coefficient increases sharply during the excitation process, and the maximum instability coefficient reaches about 175. After the excitation is removed, the instability coefficient decreases slightly but remains at a high level, and the value is basically maintained in the range of 130-150, indicating that the vehicle has already experienced snaking instability. After the vehicle speed begins to slowly decrease, the instability coefficient also gradually decreases. When the time is close to 1700s, that is, when the vehicle speed decreases to 247km / h, the instability coefficient also decreases to close to 0, and the vehicle returns to a stable state. At this moment, the vehicle's running speed is the vehicle's snaking motion convergence speed. This result is consistent with Figure 2 The results of Figure (a) and Figure (b) are consistent, indicating that it is also feasible to judge the bogie hunting stability based on the instability coefficient, and the instability speed and convergence speed are reflected more accurately. Figure 2 From the three bogie hunting instability diagnosis and identification methods shown, the three vehicle hunting instability diagnosis and identification methods based on wheelset lateral displacement, frame lateral vibration acceleration and instability coefficient are all feasible.

[0066] like Figure 3 The figure shows the limit cycle test results for different types of vehicles. The curve with the tail in the middle represents the supercritical bifurcation, which is represented by CRH2 and its extended series (Japanese). The curve with the tail at the highest point represents the subcritical bifurcation, which is mainly represented by CRH3 and its extended series (European). The dotted line represents the limit of the wheelset lateral displacement of 1mm. Figure 3As can be observed, as speed increases beyond 200 km / h, the wheelset lateral displacement of the supercritical bifurcation bogie gradually increases after track excitation is removed at each speed level. However, the increase is relatively slow and remains low. From 200 km / h to 325 km / h, the wheelset lateral displacement increases by only approximately 0.83 mm. As speed continues to increase, the wheelset lateral displacement reaches 1.17 mm at 350 km / h, exceeding the conventional threshold of 1 mm. At 440 km / h, the magnitude slowly increases to 1.95 mm. However, the subcritical bifurcation bogie exhibits a different trend. From 60 km / h to 350 km / h, the wheelset lateral displacement remains at 0 mm. However, at 420 km / h, the wheelset lateral displacement increases sharply, reaching approximately 6.2 mm, quickly exceeding the 1 mm limit. Therefore, it can be concluded that the characteristics of wheelset lateral displacement under the two types of bifurcation are different. Vehicle stability identification methods based on wheelset lateral displacement often use a threshold of 1mm, which is a relatively effective threshold for vehicles with subcritical bifurcations. However, for supercritical bifurcations, even at higher speeds, the wheelset lateral displacement exceeds the 1mm limit, and even after exceeding 200 km / h, a small-amplitude limit cycle appears. However, the wheelset lateral displacement increases slowly with increasing speed, and the amplitude does not suddenly change. From the definition of stability, this situation indicates that the vehicle is slightly unstable, but not truly unstable, and does not cause severe lateral vibration or pose a safety hazard. Therefore, for vehicle instability diagnosis and identification methods based on wheelset lateral displacement, the commonly used 1mm limit is not applicable to all types of rail vehicles. Furthermore, the main limitation of vehicle stability diagnosis methods based on wheelset lateral displacement is the lack of the necessary hierarchical management to achieve stability identification for vehicles with different instability types.

[0067] like Figure 4 The figure shows the relationship between the typical instability type and instability coefficient of rail vehicles. Figure 1 、 Figure 2 The relationship between time and instability coefficient under the two types of serpentine motion is demonstrated. Since speed is related to time, the relationship between speed and instability coefficient under the two types of serpentine motion can be derived. Figure 4Figure (a) shows the diagnostic results of speed and instability coefficient under the vehicle snaking condition. The results show that at a speed of 80 km / h, the instability coefficient increases slightly during the excitation process, with most results below 10, and a few points falling within the 10-20 range. After the excitation is removed, the instability coefficient gradually decreases to near 0, indicating that the vehicle snaking is stable. At a speed of 120 km / h, the instability coefficient rapidly increases to around 25 during the initial excitation process and remains around 25 after the excitation is removed, indicating that the vehicle snaking is unstable. The vehicle speed is then slowly reduced, and when it drops to 107 km / h, the instability coefficient decreases to around 20. When it drops to 88 km / h, the instability coefficient decreases to around 10. Finally, when it drops to 81 km / h, the instability coefficient decreases to near 0, and the vehicle returns to a stable state. The vehicle's operating speed at this point represents the convergence rate of the vehicle snaking under this condition. Figure 4 Middle (b) is a schematic diagram of the diagnostic results of speed and instability coefficient under the bogie snaking condition. In the process of the vehicle speed gradually increasing from 120km / h to 380km / h, at each speed level under excitation, the instability coefficient results only slightly increased to about 2.5, indicating that at these speed levels, the vehicle is in a stable state. When the speed is increased to 420km / h, the instability coefficient of the vehicle increases sharply during the excitation process, and the maximum instability coefficient reaches about 175. After the excitation is removed, the instability coefficient decreases slightly but is still in the high range of 130-150, indicating that the vehicle has already experienced snaking instability. Then the speed is slowly reduced, and the instability coefficient gradually decreases. When the speed is reduced to 247km / h, the instability coefficient gradually returns to near 0. At this time, the vehicle returns to a stable state. The running speed of the vehicle at this moment is the convergence speed of the vehicle snaking motion under this condition. From Figure 4 From the two serpentine stability diagnosis methods based on the instability coefficient shown, the diagnostic results fully demonstrate that the instability coefficient is suitable for the stability identification of both body serpentine motions and bogie serpentine motions, and the relationship between vehicle speed and instability coefficient can be very conveniently obtained through the intermediate quantity of time, which makes it more convenient to diagnose and identify the vehicle's serpentine stability.

[0068] Figure 5 The figure shows a schematic diagram of the vehicle stability test result classification management method based on the instability coefficient. Figure 5 In the upper figure, the left axis is the wheelset lateral displacement, the right axis is the instability coefficient, and the right second axis is the test speed; Figure 5The figure below shows the preliminary levels based on the instability coefficient. At vehicle speeds of 80 km / h and 100 km / h, after a period of excitation, the wheelset's lateral displacement changes slightly, and the corresponding instability coefficient also increases slightly, but the results remain within 10, or level 1. After the excitation is removed, the wheelset's lateral movement stabilizes, and the instability coefficient also returns to near 0, indicating that the vehicle is stable. When the vehicle speed is at 120km / h and 140km / h, after a period of excitation, the wheelset lateral displacement is significantly larger than the previous two speed levels. In particular, when the vehicle speed is 140km / h, the amplitude of the wheelset lateral displacement is close to 5mm, and the corresponding instability coefficient also increases more. At this time, only a small number of points are in the value range of 10 to 20, and the values ​​of most points have exceeded 20, reaching the level of Level 3. However, after the excitation is removed, the lateral movement of the wheelset returns to stability, the value of the wheelset lateral displacement also returns to 0mm, and the corresponding instability coefficient also decreases to close to 0, indicating that although the vehicle is snaking stably at this time, there are signs of instability. When the vehicle speed is 160km / h, during the excitation process, the wheelset exhibits lateral oscillation behavior, and the vehicle shows typical instability. At this time, the wheelset lateral displacement reaches about 5mm, and after the excitation is removed, the wheelset still maintains lateral oscillation behavior, and the amplitude of the wheelset lateral displacement is about 5mm. The corresponding instability coefficient also increases significantly, and the values ​​of most points exceed 20, reaching the level of Level 3. After the excitation is removed, the vehicle's serpentine motion diverges, and the value of the instability coefficient remains at about 28, which is at the level of Level 3. The critical speed of the vehicle under this working condition is 160km / h. Subsequently, when the vehicle speed is gradually reduced to 132km / h, the wheelset lateral motion returns to stability, the vehicle returns to a stable state, the wheelset lateral displacement also returns to 0mm, and the instability coefficient also decreases to close to 0, indicating that the convergence speed of the vehicle under this working condition is 132km / h. Figure 5 Judging from the results of vehicle stability grading management based on the instability coefficient shown, compared with the traditional method, the instability coefficient proposed in the present invention can perform graded management of vehicle operating status, can better evaluate the vehicle status and guide subsequent inspection and maintenance of vehicles with potential hidden dangers.

[0069] The hunting instability characteristics of a vehicle can be characterized by the lateral motion displacement of the wheelset and the lateral vibration acceleration of the frame. By applying various excitations to the vehicle, various real service environments can be simulated. The rolling vibration test bench can obtain a large amount of real test data, which can be used to determine the hunting instability of different vehicles in different service environments.

[0070] 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 it should be understood that the scope of protection of the present invention is not limited to such specific descriptions and embodiments. Those skilled in the art can make various other specific variations and combinations based on the technical teachings disclosed in the present invention without departing from the essence of the present invention, and such variations and combinations are still within the scope of protection of the present invention.

Claims

1. A method for diagnosing and identifying the snaking stability of railway vehicles based on a rolling vibration test bench, characterized in that: The following steps are involved: S1. When a rail vehicle experiences snaking instability, regardless of whether the vehicle body or bogie is snaking, the wheelset exhibits lateral oscillation along the track direction. Therefore, it is assumed that the maximum lateral motion amplitude of the first and second wheelset of the bogie is y w0 are the same, then its lateral movement can be described as: y w1 =y w0 cosω h t y w2 =y w0 cos(ω h t+θ) (1) Among them, w h The instability angular frequency is the phase difference between the first and second wheelsets; S2. Without considering the elastic deformation of the primary suspension, the motion posture of the frame can be described as: Where l0 is the bogie wheelbase; S3. Through theoretical analysis, the relationship between the frame lateral vibration acceleration and the wheelset lateral displacement and snaking frequency is established, and a vehicle stability diagnosis and identification evaluation index H is constructed as the instability coefficient. C .

2. The method for diagnosing and identifying the meandering stability of a railway vehicle based on a rolling vibration test bench according to claim 1, characterized in that: The lateral motion speed and acceleration of the frame in S2 can be described as: Therefore, the lateral vibration acceleration of the frame end can be obtained as: Among them, the maximum lateral vibration acceleration amplitude of the frame end measurement point is: Further rewriting formula (5) can be obtained:

3. The method for diagnosing and identifying the meandering stability of a railway vehicle based on a rolling vibration test bench according to claim 1, characterized in that: In S3, a vehicle stability diagnosis and identification evaluation index called the instability coefficient is constructed, which is expressed as:

4. A method for hierarchical management of rail vehicle hunting stability diagnosis and identification results based on a rolling vibration test bench according to any one of claims 1 to 3, characterized in that: Included in the calculation of the instability coefficient H C After the values ​​are determined, these data are managed in a graded manner; the graded management is specifically as follows: through a large amount of calculations and rolling vibration test data, the thresholds and methods of graded management are preliminarily formulated, and the limits can be further optimized based on a large number of subsequent tests; regardless of the type of rail vehicle or the complex and changeable vehicle service environment, the grade 1 grade division limit is less than 10, the grade 2 grade division limit is 10-20, and the grade 2 and grade 3 grade division limits are 20-40.

5. The method for hierarchical management of rail vehicle hunting stability diagnosis and identification results based on a rolling vibration test bench according to claim 4, characterized in that: The H C When ≤10, the vehicle is not unstable. At this time, the vehicle remains stable regardless of whether the excitation is loaded or removed.

6. The method for hierarchical management of rail vehicle hunting stability diagnosis and identification results based on a rolling vibration test bench according to claim 1, characterized in that: The H C At 10<H C When ≤20, although the snaking stability state is stable, there are signs of instability. The vehicle is unstable under excitation, but it recovers to stability after the excitation is removed. Therefore, it is necessary to perform status detection on the problem wheelset.

7. The method for hierarchical management of rail vehicle hunting stability diagnosis and identification results based on a rolling vibration test bench according to claim 1, characterized in that: The H C When the vehicle is unstable, whether it is loaded or removed, it is in an unstable state and requires subsequent inspection and maintenance. C The value can also be used to predict the vehicle's snake instability.

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