CN110758456A - Wheel rail health state monitoring system and method - Google Patents

Abstract

The invention relates to a system and method for monitoring the health status of a wheel and rail, comprising: a plurality of sensors installed on the side of a steel rail, wherein each sensor is set to be able to collect the signal of the position; a plurality of signal processing units are set to be able to Process signals collected by multiple sensors, including program modules such as the monitoring method, signal preprocessing, signal denoising, damage detection, damage classification, damage location, damage severity assessment, and wheel-rail service life prediction, etc. A wheel-rail health state monitoring control center, including control, display and early warning units; and between multiple sensors and signal processing units, between multiple signal processing units, and between multiple signal processing units and Monitor data transfer between control centers. The invention is suitable for the whole-process monitoring of the wheel-rail health state under the conditions of different wheel-rail contact states, driving speeds, loads and the like.

Description

A system and method for monitoring the health status of wheels and rails

technical field

The invention relates to a wheel-rail health state monitoring system and a method for realizing wheel-rail health state monitoring in the system. The solution of the present invention is especially suitable for the whole-process monitoring of the wheel-rail health state under different wheel-rail contact states, driving speeds, loads and the like.

Background technique

Wheels and rails are the basic components of the railway system, and the assurance of their health is crucial to railway safety. At present, wheel and rail damage detection is carried out under non-operating conditions. Wheel damage detection mainly relies on factory quality inspection and regular return to the factory inspection, while rail damage detection is mainly based on rail flaw detection vehicles and hand-push flaw detectors. Therefore, the existing wheel and rail damage detection consumes a lot of manpower and material resources, and is slow and inefficient, and cannot reflect the evolution process and all information of the damage in real time. With the rapid development of high-speed railways, it is far from ensuring the safe operation of trains. The monitoring of the health status of the wheel and rail can not only improve the efficiency of flaw detection, but also facilitate the understanding of the damage generation mechanism and the whole process of development, which is convenient for the hierarchical diagnosis and timely treatment of the damage. Direction of development.

The occurrence of wheel-rail damage is accompanied by changes in stress, displacement, vibration, sound, etc. Therefore, the purpose of monitoring wheel-rail damage can be achieved by installing such sensors. The risk of installing sensors on high-speed wheels is high and the safety factor is low, but the stress, displacement, vibration, sound and other changes caused by damage can not only be transmitted in the wheel and rail, but also can pass through the wheel-rail contact. Therefore, the installation of sensors on the side of the rail has become the most reliable installation method at present, which can realize the health status monitoring of the wheel and the wheel-related, rail and the rail-related infrastructure at the same time. At this time, the collection of wheel and rail damage signals is carried out synchronously, and the sensor cannot distinguish whether the damage signal comes from the wheel or the rail. Therefore, when using the same system to monitor the health status of the wheel and rail, an appropriate monitoring method is required to distinguish the damage signals of the wheel and the rail, so that the two can be further processed in a targeted manner.

In addition, the installed sensor passively receives the damage signal generated when the wheel and rail damage occurs, so the monitoring of the health status of the wheel and rail has nothing to do with external conditions, but only related to internal factors such as the type, location, and severity of the damage. Therefore, installing sensors on the side of the rail is suitable for monitoring the health status of the wheel and rail under different wheel-rail contact states, driving speeds, and loads.

SUMMARY OF THE INVENTION

The purpose of the present invention is to provide a wheel-rail health state monitoring system and method, which can not only improve the detection efficiency of wheel-rail damage, but also monitor the wheel-rail health state under different wheel-rail contact states, driving speeds, loads, etc. The whole process is monitored to ultimately ensure the safety of the wheel-rail system.

The present invention will be described below with reference to the accompanying drawings. A first aspect of the present invention provides a wheel-rail health state monitoring system, the structure of which is shown in FIG. 1 , in which the wheel 102 is in rolling contact with the rail 101 . The system includes a plurality of sensors 103a-i mounted on the sides of the rail 101, wherein each sensor is arranged to acquire a signal of that position. The system also includes a plurality of signal processing units 104 configured to process signals acquired by a plurality of sensors. In particular, it is required that the number of multiple sensors associated with one signal processing unit is not less than 2, and the distance between the two farthest sensors is equivalent to the circumference of the wheel. The structure diagram of the signal processing unit is shown in FIG. 2, wherein one signal processing unit may include a processor 1041 and a memory 1042, which are respectively used for executing and saving signal preprocessing, signal denoising, damage detection, and damage classification , damage location, damage severity assessment and wheel-rail service life prediction and other program modules. The system also includes a wheel-rail health state monitoring control center 105, the structure of which is shown in Figure 3, including a control unit 1051, a display unit 1052 and an early warning unit 1053, which are used to issue instructions to the signal processing unit 104 and display the monitoring results. and warning of dangerous situations. The system also includes data transmission between the plurality of sensors 103a-i and the signal processing units 104a-c, between the plurality of signal processing units 104a-c and between the plurality of signal processing units 104a-c and the monitoring control center 105 , which can be wired or wireless. Through transmission, the signal collected by the sensor can be uploaded to its associated signal processing unit, data can be exchanged between adjacent signal processing units, and the result data processed by multiple signal processing units can be uploaded to the control center, and the control center can Issue instructions to multiple signal processing units.

A second aspect of the present invention provides a method for monitoring the health status of wheels and rails, the flowchart of which is shown in FIG. 4 , which can be embedded into a signal preprocessing module or a signal denoising module in a signal processing unit as a program module, and is divided into three parts. The steps are described by taking the signal processing unit 104a and its associated multiple sensors 103a-c as an example in FIG. 1, and the specific steps are as follows:

Step 1: Determine if there is damage

The vehicle speed V, the wheel radius R, and the signal s _ac (t) collected by the sensors 103a-c are input, and the presence or absence of damage is determined from the s _ac (t). When the amplitude of the background noise in s _ac (t) is small, the existence of the damaged signal can be clearly seen. If the damaged signal exists, step 2 is performed. If the damaged signal does not exist, the process ends. The monitoring method can be embedded in The signal preprocessing module in the signal processing unit; when the amplitude of the background noise in _sac (t) is so large that the damaged signal is overwhelmed, the monitoring method can be used as a separate module after the signal denoising module, and the noise after denoising The amplitude is significantly reduced, and it can be judged whether the damaged signal exists from the signal amplitude. If the damaged signal exists, step 2 is performed, and if the damaged signal does not exist, the process ends;

Step 2: Calculate the period

When the wheel runs for one week, the ratio of the forward distance of the wheel to the vehicle speed is the running period, so the running period of the wheel can be calculated by the vehicle speed V and the wheel radius R

When the wheel is damaged, the damage will generate a damage signal when it is in pressure contact with the rail, and the damage signal of the sensors 103a-c in the adjacent period will show a periodicity consistent with the running cycle of the wheel; and when the rail is damaged , the damage signals of the sensors 103a-c in adjacent time periods will be independent of the operating period, so the signal period can be calculated from the damage signals s _ac (t) of the two adjacent time periods

为在t2时间段传感器103a-c中伤损信号最大幅值对应的时刻；Among them, A _a,t1 , A _b,t1 , and A _c,t1 are the amplitudes of the damage signals collected by the sensors 103a, 103b, and 103c in the time period t1, and A _a,t2 , A _b,t2 , and A _c,t2 are The amplitude of the damage signal collected by the sensors 103a, 103b, 103c in the time period t2, t2>t1, max{} is the maximum value, is the time corresponding to the maximum amplitude of the damage signal in the sensors 103a-c in the time period t1,

is the time corresponding to the maximum amplitude of the damage signal in the sensors 103a-c in the time period t2;

Step 3: Cycle Comparison

Comparing the size of the running period _Tw and the signal period T _s , if the signal period is approximately equal to the running period, the signal is a wheel damage signal, and if the difference between the two is large, the signal is a rail damage signal. Combined with the positions of the sensors 103a-c and the schematic diagrams of the wheel and rail damage signals collected by the sensors 103a-c in different time periods, the monitoring method is further explained as follows. Fig. 5 is a schematic diagram of a damaged wheel generating a damaged signal when passing through the sensors 103a-c, Fig. 6(a) is a schematic diagram of the wheel damage signal collected by the sensors 103a-c during the t1 period, and Fig. 6(b) is the t2 period. A schematic diagram of wheel damage signals collected by sensors 103a-c. Suppose the position where the wheel damage first comes into pressure contact with the rail is p1 (close to the sensor 103a), and the damage signal collected by the sensors 103a-c is intercepted as the signal segment t1; after the wheel rolls for a week, the second pressure occurs The contact position is p2 (close to the sensor 103c), and the damage signal collected by the intercepting sensors 103a-c at this time is the signal segment t2. Since the amplitude of the signal is attenuated when it propagates in the rail, and p1 is the closest to the sensor 103a, the amplitude of the signal collected by the sensor 103a during t1 is the largest; and because the signal propagates from left to right, the sensor 103a first receives the damage signal, Sensor 103c is the latest. Similarly, in the period t2, the sensor 103c that is closer to p2 receives the damage signal first and has the largest amplitude, and then the signal gradually propagates from right to left to the sensor 103b and the sensor 103a. From the periodicity of wheel rolling, it can be known that the difference between the maximum amplitude occurrence time of the sensor 103c in the t2 period and the maximum amplitude occurrence time of the sensor 103a in the t1 period should be approximately equal to the operation period. Fig. 7 is a schematic diagram of the damage signal generated by the damaged rails being collected by the sensors 103a-c, Fig. 8(a) is a schematic diagram of the rail damage signal collected by the sensors 103a-c during t1, Fig. 8(b) is t2 A schematic diagram of the rail damage signals collected by the time period sensors 103a-c. Suppose the position of the rail damage is p1 (close to the sensor 103a), and the damage signal collected by the intercepting sensors 103a-c is the signal segment t1; after a period of time, the damage at the position p1 is further expanded to generate a damage signal, At this time, the damage signal collected by the intercepting sensors 103a-c is the signal segment t2. Since p1 is the closest to the sensor 103a, the sensor 103a firstly collects the damage signal in both time periods t1 and t2, and the amplitude is the largest. The signals collected by the sensors 103a-c in the two time periods maintain the same pattern. However, the rail damage signal does not have the same periodicity as the operation period, so the difference between the maximum amplitude occurrence time of the sensor 103c in the t2 period and the maximum amplitude occurrence time of the sensor 103a in the t1 period is not equal to the operation period.

A third aspect of the present invention provides a computer program comprising software instructions that, when executed by a computer, implement the monitoring method, signal preprocessing, signal denoising, damage detection, damage classification, damage localization , damage severity assessment and wheel/rail service life prediction and other program modules.

Compared with the prior art, the present invention not only improves the wheel-rail damage detection efficiency, but also has the following advantages:

1) Applicable to wheel and wheel-related, rail and rail-related infrastructure health status monitoring;

2) It is suitable for wheel-rail health status monitoring under different wheel-rail contact status, driving speed, load, etc.;

3) It is suitable for monitoring the whole process of the evolution of the wheel-rail health state.

Description of drawings

Figure 1 is a structural diagram of a wheel-rail health state monitoring system;

FIG. 2 is a structural diagram of the signal processing unit 104;

FIG. 3 is a structural diagram of the wheel-rail health state monitoring and control center 105;

FIG. 4 is a flowchart of a method for monitoring the health status of wheels and rails;

5 is a schematic diagram of a damaged wheel generating a damaged signal when passing through the sensors 103a-c;

Fig. 6 is a schematic diagram of wheel damage signals collected by sensors 103a-c (a) during t1 period (b) during t2 period;

FIG. 7 is a schematic diagram when the damage signal generated by the damaged rail is collected by the sensors 103a-c;

Fig. 8 is a schematic diagram of the rail damage signals collected by the sensors 103a-c (a) during the t1 period (b) during the t2 period;

Fig. 9 shows the signals collected by the three sensors 103a-c in two time periods during driving;

Figure 10 shows the signals collected by the three sensors 103a-c over two time periods without a car.

Detailed ways

Hereinafter, taking the monitoring of the health status of the wheel and rail based on the acoustic emission sensor as an example, the specific implementation of the present invention will be described with reference to the accompanying drawings: three acoustic emission sensors 103a-c are installed on the side of the rail in the manner of FIG. 1, and all the sensors are It is connected with a signal processing unit 104 including a processor and a memory. The signal processing unit is connected with a computer 105 as a monitoring control center to form a monitoring system. The monitoring method is stored and executed by the signal processing unit 104 as a program module. The horizontal distance between adjacent acoustic emission sensors is 1m, that is, x _b =1m and x _c =2m in FIG. 5 and FIG. 7 . The wheel radius R=0.45m, and the following processing is performed on the signals measured in the two cases of the driving speed V=10m/s and no vehicle.

Step 1: Determine whether the damage exists.

When the wheel 102 rolls stably on the rail 101 at a speed of 10m/s, the signals collected by the three sensors 103a-c in two time periods are shown in FIG. 9, wherein the time period t1 corresponds to 0 to 1ms, and the time period t2 corresponds to 282.86ms to 283.86ms. The background noise in the driving process in Figure 9 cannot be ignored, but its amplitude is relatively small, and the damage signal is clearly visible, so it is judged that the damage exists. During the period t1, the acoustic emission sensor 103a firstly measures the damage signal and has the largest amplitude, while the acoustic emission sensor 103c measures the damage signal last and has the smallest amplitude, indicating that the damage occurrence position p1 is the closest to the acoustic emission sensor 103a and farther away from the acoustic emission sensor 103a. The acoustic emission sensor 103c is the farthest; the acoustic emission sensor 103c measures the damage signal first and has the largest amplitude during t2, indicating that the damage occurrence position p2 is the closest to the acoustic emission sensor 103c and the farthest to the acoustic emission sensor 103a.

Re-timing, it is measured that the signals collected by the three sensors 103a-c in two time periods in the absence of a car are shown in Figure 10, wherein the t1 period corresponds to 96.22ms to 97.0392ms, and the t2 period corresponds to 99.01ms to 99.8292ms. In Figure 10, the amplitude of the background noise is very small, the damage signal is clearly visible, and it is judged that the damage exists. In the two periods of t1 and t2, the signals collected by the sensors 103a-c have the same pattern, and the acoustic emission sensor 103a firstly measures the damage signal and the amplitude is the largest, indicating that the two damages occurred at positions relative to the three sensors. Remaining unchanged, they are both closest to the acoustic emission sensor 103a and farthest away from the acoustic emission sensor 103c.

Perform step 2: Calculate the period.

When the wheel runs for one week, the ratio of the forward distance of the wheel to the speed of the vehicle is the running cycle. When the vehicle speed is V=10m/s and the wheel radius R=0.45m, the running cycle of the wheel is calculated

Tw = _282.7ms is obtained. When the wheel is damaged, the damage will generate a damage signal when it is in pressure contact with the rail, and the damage signal of the sensors 103a-c in the adjacent period will show a periodicity consistent with the running cycle of the wheel; and when the rail is damaged When damaged, the damage signals of the sensors 103a-c in adjacent time periods will be independent of the operation period, so the signal period can be calculated from the damage signals s _ac (t) of the two adjacent time periods

Wherein A _a,t1 , _Ab,t1 , A _c,t1 are the amplitudes of the damage signals of the sensors 103a, 103b, 103c in the time period t1, A _a,t2 , _Ab,t2 , A _c,t2 are the sensors The amplitudes of the damage signals of 103a, 103b, and 103c in the time period t2, t2>t1, max{} is the maximum value, is the time corresponding to the maximum amplitude of the damage signal in the acoustic emission sensors 103a-c in the time period t1, is the time corresponding to the maximum amplitude of the damage signal in the acoustic emission sensors 103a-c in the time period t2. Calculate the damage signal period T _sw in the driving process and the damage signal period T _sr when there is no vehicle, respectively, and obtain

T _sw =283.09-0.2308=282.8592(ms),

T _sr =99.07-96.277=2.793(ms).

Perform step 3: cycle comparison.

Comparing the damage signal period T _sw , T _sr with the running period _Tw , we get

T _{sw ≈Tw} ,

T _sr ≠ _Tw ,

It shows that the damage signal measured during driving is generated by wheel damage, while the damage signal measured without a car is a rail damage signal, which may be generated by the further expansion of the rail damage at the same position. After the source of the damage signal is determined, the signal processing unit can enter the next step of processing, and finally realize the monitoring of the health status of the wheel and rail.

In addition, the wheel-rail health state monitoring system and method according to the present invention can be based not only on acoustic emission sensors, but also on stress sensors, displacement sensors, vibration sensors, acceleration sensors, ultrasonic sensors, and the like.

It should be appreciated that embodiments of the present invention may also be implemented or implemented by computer hardware, a combination of hardware and software, or by computer instructions stored in non-transitory computer readable memory. The method can be implemented in a computer program using standard programming techniques - including a non-transitory computer-readable storage medium configured with a computer program, wherein the storage medium so configured causes the computer to operate in a specific and predefined manner - according to the specific implementation. The methods and figures described in the examples. Each program may be implemented in a high-level procedural or object-oriented programming language to communicate with a computer system. However, if desired, the program can be implemented in assembly or machine language. In any case, the language can be a compiled or interpreted language. Furthermore, the program can be run on a programmed application specific integrated circuit for this purpose.

Further, the methods may be implemented in any type of computing platform operably connected to a suitable, including but not limited to personal computer, minicomputer, mainframe, workstation, network or distributed computing environment, stand-alone or integrated computer platform, or communicate with charged particle tools or other imaging devices, etc. Aspects of the invention may be implemented in machine-readable code stored on a non-transitory storage medium or device, whether removable or integrated into a computing platform, such as a hard disk, an optically read and/or written storage medium, RAM, ROM, etc., such that it can be read by a programmable computer, when a storage medium or device is read by a computer, it can be used to configure and operate the computer to perform the processes described herein. Furthermore, the machine-readable code, or portions thereof, may be transmitted over wired or wireless networks. The invention described herein includes these and other various types of non-transitory computer-readable storage media when such media includes instructions or programs that implement the steps described above in conjunction with a microprocessor or other data processor. The invention also includes the computer itself when programmed according to the methods and techniques described herein.

The above descriptions are only preferred embodiments of the present invention, and the present invention is not limited to the above-mentioned embodiments, as long as the technical effects of the present invention are achieved by the same means, they should all belong to the protection scope of the present invention. Various modifications and changes can be made to its technical solutions and/or implementations within the protection scope of the present invention.

Claims (3)

1. a wheel-rail health state monitoring system, its structure diagram as shown in Figure 1, is characterized in that: a plurality of sensors 103a-i mounted on the sides of the rail 101, wherein each sensor is configured to acquire a signal of that position; A plurality of signal processing units 104 are configured to process signals collected by a plurality of sensors. In particular, it is required that the number of multiple sensors associated with one signal processing unit is not less than 2, and the distance between the two farthest sensors is equivalent to the circumference of the wheel; The structure diagram of the signal processing unit is shown in Figure 2. One of the signal processing units may include a processor 1041 and a memory 1042, which are respectively used to execute and save signal preprocessing, signal denoising, damage detection, damage classification, damage Program modules such as damage location, damage severity assessment and wheel/rail service life prediction; A wheel-rail health state monitoring control center 105, the structure of which is shown in Figure 3, includes a control unit 1051, a display unit 1052 and an early warning unit 1053, which are used to issue instructions to the signal processing unit 104, display the monitoring results, and give dangerous conditions. give an early warning; The data transmission between the plurality of sensors 103a-i and the signal processing units 104a-c, between the plurality of signal processing units 104a-c and between the plurality of signal processing units 104a-c and the monitoring control center 105 can be wired transmission It can also be wireless transmission. Through transmission, the signal collected by the sensor can be uploaded to the signal processing unit associated with it, data exchange can be performed between adjacent signal processing units, and the result data processed by multiple signal processing units can be uploaded to the control unit. center, and the control center can issue instructions to a plurality of signal processing units. 2. A method for monitoring the health status of wheels and rails, the flowchart of which is shown in FIG. 4 , characterized in that, when the signal processing unit 104a and its associated multiple sensors 103a-c in FIG. 1 are taken as an example, the method Include the following steps: Step 1: Determine if there is damage The vehicle speed V, the wheel radius R, and the signal s _ac (t) collected by the sensors 103a-c are input, and the presence or absence of damage is determined from the s _ac (t). When the amplitude of the background noise in s _ac (t) is small, the existence of the damaged signal can be clearly seen. If the damaged signal exists, step 2 is performed. If the damaged signal does not exist, the process ends. The monitoring method can be embedded in The signal preprocessing module in the signal processing unit; when the amplitude of the background noise in _sac (t) is so large that the damaged signal is overwhelmed, the monitoring method can be used as a separate module after the signal denoising module, and the noise after denoising The amplitude is significantly reduced, and it can be judged whether the damaged signal exists from the signal amplitude. If the damaged signal exists, step 2 is performed, and if the damaged signal does not exist, the process ends; Step 2: Calculate the period When the wheel runs for one week, the ratio of the forward distance of the wheel to the vehicle speed is the running period, so the running period of the wheel can be calculated by the vehicle speed V and the wheel radius R

When the wheel is damaged, the damage will generate a damage signal when it is in pressure contact with the rail, and the damage signal of the sensors 103a-c in the adjacent period will show a periodicity consistent with the running cycle of the wheel; and when the rail is damaged , the damage signals of the sensors 103a-c in adjacent time periods will be independent of the operating period, so the signal period can be calculated from the damage signals s _ac (t) of the two adjacent time periods

Among them, A _a,t1 , A _b,t1 , and A _c,t1 are the amplitudes of the damage signals collected by the sensors 103a, 103b, and 103c in the time period t1, and A _a,t2 , A _b,t2 , and A _c,t2 are The amplitude of the damage signal collected by the sensors 103a, 103b, 103c in the time period t2, t2>t1, max{} is the maximum value, is the time corresponding to the maximum amplitude of the damage signal in the sensors 103a-c in the time period t1,

is the time corresponding to the maximum amplitude of the damage signal in the sensors 103a-c in the time period t2; Step 3: Cycle Comparison Comparing the size of the running period _Tw and the signal period T _s , if the signal period is approximately equal to the running period, the signal is a wheel damage signal, and if the difference between the two is large, the signal is a rail damage signal. 3. A computer program comprising software instructions which, when executed by a computer, implement the method of any of claims 1-2.

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