CN115112390A

CN115112390A - Vehicle abnormal vibration identification method and device

Info

Publication number: CN115112390A
Application number: CN202210727836.6A
Authority: CN
Inventors: 田朋溢; 石雯; 董孝卿; 朱韶光; 高攀; 刘鹏; 蒋成成
Original assignee: China Academy of Railway Sciences Corp Ltd CARS; Locomotive and Car Research Institute of CARS; Beijing Zongheng Electromechanical Technology Co Ltd
Current assignee: China Academy of Railway Sciences Corp Ltd CARS; Locomotive and Car Research Institute of CARS; Beijing Zongheng Electromechanical Technology Co Ltd
Priority date: 2022-06-24
Filing date: 2022-06-24
Publication date: 2022-09-27

Abstract

The invention provides a method and a device for identifying abnormal vibration of a vehicle. The vehicle abnormal vibration identification method includes: determining vehicle shaking characteristic parameters according to the vehicle shaking whole wave acceleration signal; determining a vehicle shaking characteristic parameter according to the vehicle shaking acceleration signal, the vehicle shaking window duration and the sampling frequency; determining a frequency characteristic parameter according to the frequency of the frequency acceleration signal and the vibration main frequency amplitude; and recognizing abnormal vibration of the vehicle according to the vehicle shaking characteristic parameters, the vehicle shaking characteristic parameters and the frequency characteristic parameters. The invention can accurately identify the abnormal vibration type and cause, thereby realizing the accurate guidance of the vehicle operation and maintenance.

Description

Vehicle abnormal vibration identification method and device

Technical Field

The invention relates to the field of vehicle monitoring, in particular to a method and a device for identifying abnormal vibration of a vehicle.

Background

With the rapid development of high-speed railways, the holding capacity of high-speed motor train units is gradually increased, and the problem of more and more abnormal vibration of vehicles is caused. The outstanding abnormal vibration problem that exists at present EMUs can be divided into two types of EMUs low frequency abnormal vibration and high frequency abnormal vibration according to its vibration frequency range. The low-frequency abnormal vibration of the motor train unit is low-frequency vibration within 40Hz, and mainly shows transverse snaking motion of a framework and transverse and vertical low-frequency abnormal vibration of a train body. According to the difference of the vibration position and the vibration frequency, the low-frequency abnormal vibration of the motor train unit can be mainly divided into two types of shaking and shaking. The shaking refers to shaking of a car body caused by transmission of snake-shaped instability of a bogie 6H z-9 Hz to the car body, mainly occurs at the later stage of turning of the wheel, and is represented as abnormal shaking of a car body seat, a luggage rack and the like. The shaking refers to the low-frequency shaking of the car body at 1 Hz-2 Hz, mainly occurs in the initial stage of the wheel turning, and is represented as rolling on the upper center or the lower center of the whole car body. The low-frequency abnormal vibration reduces riding comfort, can cause the deceleration running and even stopping of the motor train unit, increases the derailment risk of the motor train unit, and has great influence on the running sequence and safety of the motor train unit. The frequency of the high-frequency abnormal vibration of the motor train unit is usually more than 500Hz, and the main cause is that the high-frequency vibration of the wheel rail part is excited by the polygonal wheel and the rail corrugation. The problems belong to short-wavelength high-frequency disturbance, the influence on the stability and the comfort of the motor train unit is small in a short period, but the influence on the service life of wheel-rail parts is great, and great wheel-rail noise can be generated. In conclusion, the abnormal vibration conditions of the vehicles need to be monitored and analyzed in real time so as to intelligently guide the operation and maintenance of the motor train unit.

The existing high-speed motor train unit train is provided with a vehicle-mounted stability monitoring device, and the change of the vibration acceleration amplitude and stability index of the train can be monitored in real time through an acceleration sensor; however, in the actual operation process, the following situations may exist: when the vehicle stability monitoring device displays that the vehicle stability index is large, the vehicle and the line state are detected respectively, and the vehicle and the track state are found to be abnormal respectively. Through research and analysis, the reason for increasing the stability index of the vehicle is that the wheel-rail matching is poor, and the normal snake-shaped motion of the bogie is influenced, so that primary snake-shaped instability (shaking) and secondary snake-shaped instability (shaking) are caused. The stability index parameter monitored by the conventional vehicle-mounted stability monitoring device reflects the overall response result of the vehicle body, the cause of the abnormal vibration of the vehicle cannot be distinguished from primary snake-like instability, secondary snake-like instability or high-frequency vibration, and the main cause of the abnormal vibration cannot be distinguished, namely, the abnormal vibration is originated from the vehicle or the track or the wheel-track matching problem of both the abnormal vibration and the track. The defects seriously affect the quick identification of the abnormal vibration problem of the vehicle and the determination of the corresponding rectification scheme, so that the cycle of finding and solving the abnormal vibration problem of the vehicle is too long, the abnormal vibration problem of the vehicle cannot be finely guided to be applied and maintained, and the operation efficiency and the economical efficiency of the vehicle are affected.

Disclosure of Invention

The embodiment of the invention mainly aims to provide a method and a device for identifying abnormal vibration of a vehicle, so as to accurately identify the type and cause of the abnormal vibration, and thus, realize accurate guidance on the operation and maintenance of the vehicle.

In order to achieve the above object, an embodiment of the present invention provides a vehicle abnormal vibration identification method, including:

determining vehicle shaking characteristic parameters according to the vehicle shaking whole wave acceleration signal;

determining a vehicle shaking characteristic parameter according to the vehicle shaking acceleration signal, the vehicle shaking window duration and the sampling frequency;

determining a frequency characteristic parameter according to the frequency of the frequency acceleration signal and the vibration main frequency amplitude;

and recognizing abnormal vibration of the vehicle according to the vehicle shaking characteristic parameters, the vehicle shaking characteristic parameters and the frequency characteristic parameters.

In one embodiment, the method further comprises the following steps:

determining a shaking car whole wave acceleration signal according to the original acceleration signal and a shaking car filter transfer function;

determining a vehicle shaking acceleration signal according to the original acceleration signal and a transfer function of a vehicle shaking filter;

the frequency acceleration signal is determined from the raw acceleration signal and the frequency filter transfer function.

In one embodiment, the identifying the abnormal vibration of the vehicle according to the vehicle shaking characteristic parameter, the vehicle shaking characteristic parameter and the frequency characteristic parameter comprises:

determining a vibration acceleration characteristic parameter according to the shaking characteristic parameter, the shaking characteristic parameter and the frequency characteristic parameter;

and identifying abnormal vibration of the vehicle according to the vibration acceleration characteristic parameters.

In one embodiment, the vibration acceleration characteristic parameters comprise a current vehicle vibration acceleration characteristic parameter, a historical vehicle vibration acceleration characteristic parameter and a comparison vehicle vibration acceleration characteristic parameter;

the step of identifying the abnormal vibration of the vehicle according to the vibration acceleration characteristic parameters comprises the following steps:

determining a consistency factor according to the characteristic parameters of the vibration acceleration of the current vehicle and the characteristic parameters of the vibration acceleration of the historical vehicle;

determining an equivalent factor according to the characteristic parameters of the vibration acceleration of the current vehicle and the characteristic parameters of the vibration acceleration of the comparison vehicle;

and identifying abnormal vibration of the vehicle according to the consistency factor and the equivalent factor.

The embodiment of the present invention further provides a device for identifying abnormal vibration of a vehicle, including:

the vehicle shaking module is used for determining vehicle shaking characteristic parameters according to the vehicle shaking whole wave acceleration signal;

the vehicle shaking module is used for determining vehicle shaking characteristic parameters according to the vehicle shaking acceleration signal, the vehicle shaking window opening duration and the sampling frequency;

the frequency module is used for determining frequency characteristic parameters according to the frequency of the frequency acceleration signal and the vibration main frequency amplitude;

and the vehicle abnormal vibration identification module is used for identifying the vehicle abnormal vibration according to the vehicle shaking characteristic parameters, the vehicle shaking characteristic parameters and the frequency characteristic parameters.

In one embodiment, the method further comprises the following steps:

the vehicle shaking wave shaping acceleration module is used for determining a vehicle shaking wave shaping acceleration signal according to the original acceleration signal and a vehicle shaking filter transfer function;

the vehicle shaking acceleration module is used for determining a vehicle shaking acceleration signal according to the original acceleration signal and a transfer function of a vehicle shaking filter;

and the frequency acceleration module is used for determining a frequency acceleration signal according to the original acceleration signal and the transfer function of the frequency filter.

In one embodiment, the vehicle abnormal vibration identification module includes:

the acceleration vibration characteristic unit is used for determining vibration acceleration characteristic parameters according to the vehicle shaking characteristic parameters, the vehicle shaking characteristic parameters and the frequency characteristic parameters;

and the vehicle abnormal vibration identification unit is used for identifying the vehicle abnormal vibration according to the vibration acceleration characteristic parameters.

the vehicle abnormal vibration recognition unit includes:

the consistency factor subunit is used for determining a consistency factor according to the characteristic parameters of the current vehicle vibration acceleration and the characteristic parameters of the historical vehicle vibration acceleration;

the equivalent factor subunit is used for determining an equivalent factor according to the current vehicle vibration acceleration characteristic parameter and the comparison vehicle vibration acceleration characteristic parameter;

and the vehicle abnormal vibration identification subunit is used for identifying the vehicle abnormal vibration according to the consistency factor and the equivalent factor.

The embodiment of the invention also provides computer equipment which comprises a memory, a processor and a computer program stored on the memory and operated on the processor, wherein the steps of the vehicle abnormal vibration identification method are realized when the processor executes the computer program.

Embodiments of the present invention further provide a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the steps of the method for identifying abnormal vibration of a vehicle.

The method and the device for identifying the abnormal vibration of the vehicle, provided by the embodiment of the invention, firstly determine the characteristic parameters of the vehicle shaking according to the whole wave acceleration signal of the vehicle shaking, determine the characteristic parameters of the vehicle shaking according to the data of the vehicle shaking, determine the characteristic parameters of the frequency according to the frequency data, and then identify the abnormal vibration of the vehicle according to the characteristic parameters of the vehicle shaking, the characteristic parameters of the vehicle shaking and the characteristic parameters of the frequency, so that the type and the cause of the abnormal vibration can be accurately identified, and the accurate guidance of the application and the maintenance of the vehicle is realized.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the description below are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained based on these drawings without creative efforts.

FIG. 1 is a flowchart of a vehicle abnormal vibration identification method in an embodiment of the present invention;

FIG. 2 is a flowchart of a vehicle abnormal vibration identification method according to another embodiment of the present invention;

FIG. 3 is a flowchart of S104 in an embodiment of the present invention;

FIG. 4 is a flowchart of S202 in an embodiment of the present invention;

FIG. 5 is a schematic diagram of vibration acceleration raw data of a motor train unit at a certain day in the first embodiment;

FIG. 6 is a schematic illustration of a filtered vehicle shaking acceleration signal;

FIG. 7 is an enlarged comparison schematic diagram of vibration acceleration raw data and a filtered vehicle shaking acceleration signal;

FIG. 8 is a schematic view of a vehicle shaking characteristic parameter;

FIG. 9 is a schematic diagram of vibration acceleration raw data of a motor train unit at a certain day in the second embodiment;

FIG. 10 is a schematic illustration of a filtered vehicle shake acceleration signal;

FIG. 11 is a schematic view of a vehicle shake feature parameter;

FIG. 12 is a schematic diagram of comparison between the daily filtered vibration acceleration raw data and the filtered vibration acceleration raw data of the motor train unit in the third embodiment;

FIG. 13 is a schematic illustration of a frequency characteristic parameter;

FIG. 14 is a schematic of the mean and variance of a historical frequency characteristic parameter;

FIG. 15 is a schematic of a consistency factor;

FIG. 16 is a schematic illustration of the mean and variance of historical vehicle shaking characteristic parameters;

FIG. 17 is a schematic of an equivalence factor;

FIG. 18 is a block diagram showing the construction of an abnormal vibration recognizing apparatus for a vehicle in the embodiment of the invention;

fig. 19 is a block diagram showing the structure of a computer device in the embodiment of the present invention.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

As will be appreciated by one skilled in the art, embodiments of the present invention may be embodied as a system, apparatus, device, method, or computer program product. Accordingly, the present disclosure may be embodied in the form of: entirely hardware, entirely software (including firmware, resident software, micro-code, etc.), or a combination of hardware and software.

In view of the problems of abnormal vibration of vehicles in the prior art that the period from discovery to solution is too long, the operation and maintenance cannot be guided in a refined manner, and the operation efficiency and the economy of the vehicles are affected, the embodiment of the invention provides a method and a device for identifying the abnormal vibration of the vehicles, which can accurately identify the type and the cause of the abnormal vibration, thereby realizing the accurate guidance of the operation and maintenance of the vehicles.

Characteristic parameter a of acceleration _λ,v Including a characteristic parameter a of the vehicle shaking _λ,v,H Characteristic parameter a of vehicle shaking _λ,v,D And a characteristic parameter a of frequency (high frequency vibration, i.e. abnormal vibration in the range of 500Hz-1000 Hz) _λ,v,P The calculation needs to jointly determine different processing methods for the vibration acceleration based on vehicle parameters (including main parameters such as vehicle types, advanced post-repair travel mileage, post-turning-repair travel mileage and the like), line parameters (namely line conditions, such as whether parameters are parameters of special sections such as turnouts, bridges and the like) and characteristic value type parameters (namely shaking, shaking and high-frequency vibration), the main idea is to select different frequency bands according to vehicle and line states to filter the vibration acceleration, and then adopt different calculation methods to extract shaking, shaking and high-frequency vibration characteristic values:

a _λ,v ＝f(a,V,L,v,T)＝f(a,t _V ,m_ar _V ,m_ahr _V ,t _L ,x _L ,v,T)；

wherein a is vibration acceleration and a characteristic parameter of shaking car _λ,v,H The corresponding vibration acceleration is transverse vibration acceleration, and a vehicle shaking characteristic parameter a _λ,v,D The corresponding vibration acceleration is transverse vibration acceleration, vertical vibration acceleration and frequency (high-frequency vibration) characteristic parameter a _λ,v,P The corresponding vibration acceleration is vertical vibration acceleration; v is vehicle parameter including vehicle type parameter t _V And the running mileage m _ ar after the vehicle is turned for repair _V And advanced repair running mileage m _ ahr _V (ii) a L is a line parameter including a line condition t _L And the position x of the vehicle on the road _L (ii) a v is the vehicle operating speed; t is a eigenvalue type parameter. Frequencies mentioned in the present invention

Fig. 1 is a flowchart of a vehicle abnormal vibration recognition method in an embodiment of the present invention. Fig. 2 is a flowchart of a vehicle abnormal vibration recognition method according to another embodiment of the present invention. As shown in fig. 1 to 2, the vehicle abnormal vibration recognition method includes:

s101: and determining vehicle shaking characteristic parameters according to the vehicle shaking whole wave acceleration signal.

Before executing S101, the method further includes: and determining the shaking vehicle whole wave acceleration signal according to the original acceleration signal and the transfer function of the shaking vehicle filter. Wherein, the transfer function H of the shaking filter can be determined according to parameters such as the model of the target motor train unit, the running speed of the motor train unit, the line parameters, the running mileage after turning and the running mileage after advanced repair of the motor train unit and the like _H . Carrying out band-pass filtering processing on the vibration acceleration original data a with a certain specific duration to obtain a filtered vehicle shaking acceleration signal

Then processed according to the zero crossing point principle

To obtain

Whole wave acceleration signal A passing through zero point _i 。

In specific implementation, the vehicle shaking characteristic parameters are determined by the following formula:

wherein, a _λ,v,H As a characteristic parameter of the vehicle shaking, A _i For shaking vehicle whole wave acceleration signal

A whole wave acceleration signal passing through zero),

is a filtered shaking vehicle acceleration signal H _H A is the (lateral) vibration acceleration raw data for the filter transfer function of the vehicle shaking.

The embodiment of the vehicle shaking characteristic parameters is as follows:

FIG. 5 is a schematic diagram of vibration acceleration raw data of a motor train unit at a certain day in the first embodiment. Fig. 6 is a schematic diagram of a filtered vehicle shaking acceleration signal. Fig. 7 is an enlarged comparison diagram of vibration acceleration raw data and a filtered vehicle shaking acceleration signal. Fig. 8 is a schematic view of a vehicle shaking characteristic parameter. As shown in fig. 5-8, when the characteristic parameter of the electric motor train unit is determined according to the target electric motor train unit type, the vehicle running speed, the line parameter, the running mileage after the vehicle is turned and the running mileage after the advanced repair, etc., the electric motor train unit is subjected to the band-pass filtering of 0.2 Hz-3 Hz, so as to determine the electric motor train unit transfer function H of the electric motor train unit _H The following were used:

wherein n is an order number, the general value range is 2-5, the higher the numerical value is, the higher the filter precision is, and k is the count from 1 to n. According to

A filtered vehicle shaking acceleration signal as shown in fig. 6 is obtained.

As shown in fig. 7, the local pairs of the filtered forward and backward acceleration signals show that the vibration acceleration signals are filtered to reduce the dc component. According to the zero crossing point principle, for

The signal judges the number of the whole waves existing, and utilizes

The vehicle shaking characteristic parameters were obtained, and the results are shown in fig. 8. In the vicinity of 12:08:38, the characteristic parameter a of the vehicle shaking _λ,v,H Significant increase, indicating vehicleA car sway condition caused by one-time snake-like instability of the bogie occurs.

S102: and determining the vehicle shaking characteristic parameters according to the vehicle shaking acceleration signal, the vehicle shaking window duration and the sampling frequency.

Before executing S102, the method further includes: and determining the shaking car acceleration signal according to the original acceleration signal and the transfer function of the shaking car filter. Wherein, the transfer function H of the shaking filter can be determined according to parameters such as the model of the target motor train unit, the running speed of the motor train unit, the line parameters, the running mileage after turning and the running mileage after advanced repair of the motor train unit and the like _D . Carrying out band-pass filtering processing on vibration acceleration original data a with a certain specific duration to obtain a filtered vehicle shaking acceleration signal

When the method is specifically implemented, the vehicle shaking characteristic parameters are determined through the following formula:

wherein, a _λ,v,D Is the characteristic parameter of the vehicle shaking,

is the m-th filtered vehicle shaking acceleration signal, Delta T _D Window duration of vehicle shaking characteristic parameter, S _f For sampling frequency, a is the raw data of (lateral and vertical) vibration acceleration, H _D Is the jitter filter transfer function.

Examples of the vehicle shaking characteristic parameters are as follows:

FIG. 9 is a diagram of vibration acceleration raw data of a motor train unit at a certain day in the second embodiment. FIG. 10 is a schematic diagram of a filtered vehicle shake acceleration signal. Fig. 11 is a schematic diagram of a vehicle shaking characteristic parameter. As shown in fig. 9-11, when determining the calculated jitter characteristic parameters according to the target motor train unit model, the vehicle running speed, the line parameters, the after-turning running mileage and the after-advanced running mileage of the vehicle, the band-pass filtering of 6 Hz-10 Hz is required,from which the jitter filter transfer function H is determined _D The following were used:

according to

A filtered shake acceleration signal as shown in fig. 10 is obtained.

By using

The vehicle shaking characteristic parameters were obtained, and the results are shown in fig. 11. It can be seen that the vehicle shaking characteristic parameter a is in the time period from 9:47:31 to 9:48:40 _λ,v,D The increase is remarkable, which indicates that the vehicle has the vehicle shaking condition caused by the secondary snake-shaped instability of the bogie.

S103: and determining a frequency characteristic parameter according to the frequency of the frequency acceleration signal and the vibration main frequency amplitude.

Before executing S103, the method further includes: and determining a frequency acceleration signal (a high-frequency abnormal vibration acceleration signal, namely an abnormal vibration acceleration signal in a 500Hz-1000Hz section) according to the original acceleration signal and the transfer function of the frequency filter. The frequency filter transfer function H can be determined according to parameters such as target motor train unit type, vehicle running speed, line parameters, running mileage after turning and running mileage after advanced repair _P . Carrying out band-pass filtering processing on vibration acceleration original data a with a certain specific duration to obtain a filtered frequency acceleration signal

In specific implementation, the frequency characteristic parameter is determined by the following formula:

wherein, a _λ,v,P In order to be a characteristic parameter of the frequency,

for filtered frequency acceleration signals, Δ T ₀ Is the window duration of the frequency characteristic parameter,

as frequency acceleration signals

The frequency of (a) of (b) is,

is the amplitude of vibration main frequency, a is the (vertical) vibration acceleration raw data, H _P Is the frequency filter transfer function.

Examples of frequency characteristic parameters are as follows:

FIG. 12 is a schematic diagram of comparison between the daily filtered vibration acceleration raw data and the filtered vibration acceleration raw data of the motor train unit in the third embodiment. Fig. 13 is a schematic diagram of a frequency characteristic parameter. As shown in FIGS. 12-13, when determining the characteristic parameters of the calculated frequency (high-frequency vibration) according to the parameters of the target motor train unit model, the vehicle running speed, the line parameters, the vehicle turning mileage, the advanced driving mileage and the like, the characteristic parameters of the calculated frequency (high-frequency vibration) need to be subjected to band-pass filtering of 500Hz-1000Hz, and thus the frequency filter transfer function H is determined _P The following were used:

according to

A filtered frequency acceleration signal is obtained as shown in fig. 12.

By using

Obtaining a frequency characteristic parameter, wherein

At 592Hz, the frequency characteristic is shown in fig. 13. It can be seen that the frequency characteristic parameter of the vehicle body is always at a high level, which indicates that abnormal high-frequency vibration occurs in the vehicle.

S104: and recognizing abnormal vibration of the vehicle according to the vehicle shaking characteristic parameters, the vehicle shaking characteristic parameters and the frequency characteristic parameters.

Fig. 3 is a flowchart of S104 in the embodiment of the present invention, and as shown in fig. 3, S104 includes:

s201: and determining the vibration acceleration characteristic parameters according to the shaking characteristic parameters, the shaking characteristic parameters and the frequency characteristic parameters.

The vibration acceleration characteristic parameters comprise current vehicle vibration acceleration characteristic parameters, historical vehicle vibration acceleration characteristic parameters and comparison vehicle vibration acceleration characteristic parameters.

S202: and identifying abnormal vibration of the vehicle according to the vibration acceleration characteristic parameters.

Fig. 4 is a flowchart of S202 in the embodiment of the present invention. As shown in fig. 4, S202 includes:

s301: and determining a consistency factor according to the characteristic parameters of the vibration acceleration of the current vehicle and the characteristic parameters of the vibration acceleration of the historical vehicle.

In particular implementation, the consistency factor may be determined by the following formula:

wherein CF is a consistency factor, a _λ,v,t For the current vehicle vibration acceleration characteristic parameter (a) _λ,v,t May be a current shake characteristic parameter, a current shake characteristic parameter or a current frequency characteristic parameter),

is the average value of the characteristic parameters of the vibration acceleration of the (same-vehicle type) historical vehicle,

the variance of the characteristic parameters of the vibration acceleration of the (same-vehicle type) historical vehicle is shown, and N is a variance multiple.

When a is _λ,v,t When the current characteristic parameter of the vehicle shaking is obtained,

the characteristic parameters of the historical vehicle shaking are obtained; when a is _λ,v,t When the current characteristic parameter of the vehicle shaking is obtained,

the characteristic parameters of the historical vehicle shaking are obtained; when a is _λ,v,t In the case of the current frequency characteristic parameter,

is a historical frequency characteristic parameter. The mean value and the variance are numerical values counted under the condition that main parameters of the same vehicle type, the same after-advanced-repair traveling mileage interval, the same after-turning traveling mileage interval and the like are the same.

S302: and determining the equivalent factor according to the current vehicle vibration acceleration characteristic parameter and the comparison vehicle vibration acceleration characteristic parameter.

In particular, the equivalence factor EF can be determined by the following equation:

wherein EF is an equivalent factor,

to compare the average values of the characteristic parameters of the vibration acceleration of the vehicle,

the variance or variance multiple of the vehicle vibration acceleration characteristic parameter is compared. The characteristic parameter of the vibration acceleration of the vehicle is the characteristic parameter of the vibration acceleration of the vehicle of other vehicles under the same line condition in the past time of the day.

S303: and identifying the abnormal vibration of the vehicle according to the consistency factor and the equivalent factor.

Whether the abnormal vibration is caused by the vehicle side reason can be identified according to the section where the consistency factor CF is located.

And when the CF is less than or equal to 1, indicating that the vehicle shaking characteristic parameter, the vehicle shaking characteristic parameter or the frequency characteristic parameter at the current moment is in a normal fluctuation range, and the vehicle is normal.

When in use

And then, the state of the motor train unit is checked or historical data is reviewed again when the current vehicle shaking characteristic parameter, the current vehicle shaking characteristic parameter or the current frequency characteristic parameter fluctuates at a higher position and is in the state for a longer time, and the vehicle may be in a corresponding vehicle shaking state, a vehicle shaking state or a high-frequency vibration state.

When the temperature is higher than the set temperature

And when the vehicle is in the corresponding vehicle shaking state, the vehicle shaking state or the high-frequency vibration state, the vehicle is required to be checked, and the vehicle is indicated that the vehicle shaking characteristic parameter, the vehicle shaking characteristic parameter or the frequency characteristic parameter at the current moment exceeds the corresponding historical normal high position.

Wherein,

is the value of 99.5 th percentile in the characteristic parameter of the vibration acceleration of the historical vehicle.

Examples of the consistency factor CF are as follows:

the calculation implementation process of the consistency factor CF is explained by taking a vehicle frequency characteristic parameter as an example. Fig. 14 is a schematic diagram of the mean and variance of the historical frequency characteristic parameter. FIG. 15 is a schematic of a consistency factor. As shown in FIGS. 14-15, the average values of the frequency characteristic parameters of the same model, the same after-turning travel mileage interval and the same travel kilometer post are determined according to the historical data of the same line

Sum variance

In this embodiment, N is 2, and the obtained consistency factor CF is shown in fig. 15.

As shown by the broken line in fig. 15, the solid line in fig. 15 is 1. Therefore, in fig. 15, the lower part of the solid line is the normal fluctuation range of the vibration acceleration characteristic parameter, the part between the broken line and the solid line is the critical normal fluctuation range, and the upper part of the broken line is the abnormal range. It can be seen that the consistency factor CF in the present embodiment is far beyond the critical normal fluctuation range as a whole, which indicates that abnormal high-frequency vibration occurs, and the vehicle should have a problem and needs to be checked.

Whether the abnormal vibration is caused by the vehicle-side cause or not can be identified according to the section where the equivalent factor EF is located.

And when the EF is less than or equal to 1, the vehicle shaking characteristic parameter or the frequency characteristic parameter at the current moment is in a normal fluctuation range, and the vehicle is normal.

When in use

And then, the vehicle shaking characteristic parameter or the frequency characteristic parameter at the current moment is shown to be in a higher position (critical normal fluctuation range) fluctuation, the vehicle may be in a corresponding vehicle shaking state, vehicle shaking state or high-frequency vibration state, and the historical data of the line needs to be reviewed or updated when the vehicle is in the state for a long time.

When in use

When the vehicle is in the corresponding vehicle shaking state, the vehicle shaking state or the high-frequency vibration state, the current vehicle shaking characteristic parameter, the vehicle shaking characteristic parameter or the frequency characteristic parameter is required to be in the corresponding historical normal high position at the current momentThe line at the time is checked.

Wherein,

the value of the 99.5 th percentile in the characteristic parameter of the vibration acceleration of the vehicle is compared.

Examples of equivalent factors EF are as follows:

the calculation implementation process of the equivalent factor EF is explained by taking the vehicle shaking characteristic parameter as an example. Fig. 16 is a schematic diagram of the mean and variance of the historical vehicle-shaking characteristic parameters. FIG. 17 is a schematic of the equivalence factor. As shown in fig. 16 to 17, the average value of the sway characteristic parameters of the other vehicle types under the same route condition and in the same speed section is determined

Sum variance

In this embodiment, N is 3, and the obtained equivalent factor EF is shown in fig. 17.

As shown by the broken line in fig. 17, the solid line in fig. 17 is 1. Therefore, in fig. 17, the lower part of the solid line is the normal fluctuation range of the train shaking characteristic parameter, the part between the dotted line and the solid line is the critical normal fluctuation range, and the upper part of the dotted line is the abnormal range, so that the line section where the train is located at the current time needs to be checked.

The execution subject of the vehicle abnormal vibration recognition method shown in fig. 1 may be a computer. As can be seen from the process shown in fig. 1, the method for identifying abnormal vehicle vibration according to the embodiment of the present invention determines a vehicle shaking characteristic parameter according to a vehicle shaking integral wave acceleration signal, determines a vehicle shaking characteristic parameter according to vehicle shaking data, determines a frequency characteristic parameter according to frequency data, and identifies abnormal vehicle vibration according to the vehicle shaking characteristic parameter, and the frequency characteristic parameter, so that the type and cause of the abnormal vehicle vibration can be accurately identified, thereby implementing accurate guidance on vehicle maintenance.

In summary, the method for identifying abnormal vibration of a vehicle provided by the embodiment of the invention has the following beneficial effects:

(1) judging whether the abnormal vibration cause of the vehicle is shaking caused by primary snake-shaped instability, shaking caused by secondary snake-shaped instability or high-frequency vibration caused by polygonal wheels or unsmooth tracks according to the amplitude of the vibration acceleration signal of the vehicle at a specific frequency;

(2) the consistency factor and the equivalent factor can be calculated to judge whether the abnormal vibration source of the vehicle is caused by the vehicle or the rail or caused by poor wheel-rail matching of the vehicle and the rail, so that the accurate guidance of the vehicle operation and maintenance is realized.

Based on the same inventive concept, the embodiment of the invention also provides a vehicle abnormal vibration identification device, and as the principle of solving the problems of the device is similar to the vehicle abnormal vibration identification method, the implementation of the device can refer to the implementation of the method, and repeated parts are not repeated.

Fig. 18 is a block diagram showing the structure of the vehicle abnormal vibration recognition apparatus in the embodiment of the present invention. As shown in fig. 18, the vehicle abnormal vibration recognition device includes:

In one embodiment, the method further comprises the following steps:

In one embodiment, the vehicle abnormal vibration recognition module includes:

the vehicle abnormal vibration recognition unit includes:

In summary, the vehicle abnormal vibration identification device in the embodiment of the present invention determines the shaking characteristic parameters according to the shaking whole wave acceleration signal, determines the shaking characteristic parameters according to the shaking data, determines the frequency characteristic parameters according to the frequency data, and identifies the vehicle abnormal vibration according to the shaking characteristic parameters, and the frequency characteristic parameters, so that the type and cause of the abnormal vibration can be accurately identified, thereby realizing accurate guidance for the vehicle maintenance.

The embodiment of the invention also provides a specific implementation manner of computer equipment capable of realizing all steps in the vehicle abnormal vibration identification method in the embodiment. Fig. 19 is a block diagram of a computer device in an embodiment of the present invention, and referring to fig. 19, the computer device specifically includes the following contents:

a processor (processor)1901 and a memory (memory) 1902.

The processor 1901 is configured to call a computer program in the memory 1902, and when executing the computer program, the processor implements all the steps in the vehicle abnormal vibration identification method in the above-described embodiment, for example, when executing the computer program, the processor implements the following steps:

To sum up, the computer device of the embodiment of the invention determines the shaking car characteristic parameters according to the shaking car whole wave acceleration signals, determines the shaking car characteristic parameters according to the shaking car data, determines the frequency characteristic parameters according to the frequency data, and identifies the abnormal vibration of the vehicle according to the shaking car characteristic parameters, the shaking car characteristic parameters and the frequency characteristic parameters, so that the type and cause of the abnormal vibration can be accurately identified, and the accurate guidance of the vehicle application and maintenance is realized.

An embodiment of the present invention further provides a computer-readable storage medium capable of implementing all the steps in the vehicle abnormal vibration identification method in the above-mentioned embodiment, where the computer-readable storage medium stores thereon a computer program, and the computer program, when executed by a processor, implements all the steps in the vehicle abnormal vibration identification method in the above-mentioned embodiment, for example, the processor implements the following steps when executing the computer program:

In summary, the computer-readable storage medium according to the embodiment of the present invention determines a shaking characteristic parameter according to the shaking whole wave acceleration signal, determines a shaking characteristic parameter according to the shaking data, determines a frequency characteristic parameter according to the frequency data, and identifies abnormal vibration of the vehicle according to the shaking characteristic parameter, and the frequency characteristic parameter, so as to accurately identify the type and cause of the abnormal vibration, thereby implementing accurate guidance on the operation and maintenance of the vehicle.

The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are only exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.

Those of skill in the art will further appreciate that the various illustrative logical blocks, units, and steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both. To clearly illustrate the interchangeability of hardware and software, various illustrative components, elements, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends upon the particular application and design requirements of the overall system. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present embodiments.

The various illustrative logical blocks, or units, or devices described in connection with the embodiments disclosed herein may be implemented or performed with a general purpose processor, a digital signal processor, an Application Specific Integrated Circuit (ASIC), a field programmable gate array or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general-purpose processor may be a microprocessor, but, in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices, e.g., a digital signal processor and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a digital signal processor core, or any other similar configuration.

The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may be stored in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. For example, a storage medium may be coupled to the processor such the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium may be integral to the processor. The processor and the storage medium may reside in an ASIC, which may be located in a user terminal. In the alternative, the processor and the storage medium may reside in different components in a user terminal.

In one or more exemplary designs, the functions described above in connection with the embodiments of the invention may be implemented in hardware, software, firmware, or any combination of the three. If implemented in software, the functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Computer-readable media includes both computer storage media and communication media that facilitate transfer of a computer program from one place to another. Storage media may be any available media that can be accessed by a general purpose or special purpose computer. For example, such computer-readable media can include, but is not limited to, RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to carry or store program code in the form of instructions or data structures and which can be read by a general-purpose or special-purpose computer, or a general-purpose or special-purpose processor. Additionally, any connection is properly termed a computer-readable medium, and, thus, is included if the software is transmitted from a website, server, or other remote source via a coaxial cable, fiber optic cable, twisted pair, Digital Subscriber Line (DSL), or wirelessly, e.g., infrared, radio, and microwave. Such discs (disk) and disks (disc) include compact disks, laser disks, optical disks, DVDs, floppy disks and blu-ray disks where disks usually reproduce data magnetically, while disks usually reproduce data optically with lasers. Combinations of the above may also be included in the computer-readable medium.

Claims

1. A vehicle abnormal vibration recognition method characterized by comprising:

and recognizing abnormal vibration of the vehicle according to the shaking characteristic parameters, the shaking characteristic parameters and the frequency characteristic parameters.

2. The vehicle abnormal vibration identification method according to claim 1, characterized by further comprising:

determining the shaking car whole wave acceleration signal according to the original acceleration signal and a shaking car filter transfer function;

determining the shaking car acceleration signal according to the original acceleration signal and a transfer function of a shaking car filter;

and determining the frequency acceleration signal according to the original acceleration signal and a frequency filter transfer function.

3. The vehicle abnormal vibration recognition method according to claim 2, wherein recognizing the vehicle abnormal vibration according to the vehicle shaking characteristic parameter, and the frequency characteristic parameter includes:

4. The vehicle abnormal vibration identification method according to claim 3, wherein the vibration acceleration characteristic parameters include a current vehicle vibration acceleration characteristic parameter, a historical vehicle vibration acceleration characteristic parameter, and a comparison vehicle vibration acceleration characteristic parameter;

the identifying of the abnormal vibration of the vehicle according to the vibration acceleration characteristic parameters comprises the following steps:

determining a consistency factor according to the characteristic parameters of the current vehicle vibration acceleration and the characteristic parameters of the historical vehicle vibration acceleration;

determining an equivalent factor according to the characteristic parameter of the current vehicle vibration acceleration and the characteristic parameter of the comparison vehicle vibration acceleration;

5. An abnormal vibration recognition device for a vehicle, comprising:

6. The vehicle abnormal vibration recognition device according to claim 5, further comprising:

the vehicle shaking wave shaping acceleration module is used for determining a vehicle shaking wave shaping acceleration signal according to an original acceleration signal and a vehicle shaking filter transfer function;

the vehicle shaking acceleration module is used for determining the vehicle shaking acceleration signal according to the original acceleration signal and a vehicle shaking filter transfer function;

and the frequency acceleration module is used for determining the frequency acceleration signal according to the original acceleration signal and a frequency filter transfer function.

7. The vehicle abnormal vibration recognition device according to claim 6, wherein the vehicle abnormal vibration recognition module includes:

the acceleration vibration characteristic unit is used for determining a vibration acceleration characteristic parameter according to the shaking vehicle characteristic parameter, the shaking vehicle characteristic parameter and the frequency characteristic parameter;

8. The vehicle abnormal vibration identifying device according to claim 7, wherein the vibration acceleration characteristic parameters include a current vehicle vibration acceleration characteristic parameter, a historical vehicle vibration acceleration characteristic parameter, and a comparison vehicle vibration acceleration characteristic parameter;

the vehicle abnormal vibration recognition unit includes:

the consistency factor subunit is used for determining a consistency factor according to the characteristic parameter of the current vehicle vibration acceleration and the characteristic parameter of the historical vehicle vibration acceleration;

the equivalent factor subunit is used for determining an equivalent factor according to the characteristic parameter of the current vehicle vibration acceleration and the characteristic parameter of the comparison vehicle vibration acceleration;

9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the vehicle abnormal vibration identification method according to any one of claims 1 to 4 when executing the computer program.

10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the vehicle abnormal vibration identification method according to any one of claims 1 to 4.