CN114523996B - Early warning method and device for vehicle faults, computer equipment and readable storage medium - Google Patents
Early warning method and device for vehicle faults, computer equipment and readable storage medium Download PDFInfo
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- CN114523996B CN114523996B CN202210110170.XA CN202210110170A CN114523996B CN 114523996 B CN114523996 B CN 114523996B CN 202210110170 A CN202210110170 A CN 202210110170A CN 114523996 B CN114523996 B CN 114523996B
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B61—RAILWAYS
- B61K—AUXILIARY EQUIPMENT SPECIALLY ADAPTED FOR RAILWAYS, NOT OTHERWISE PROVIDED FOR
- B61K9/00—Railway vehicle profile gauges; Detecting or indicating overheating of components; Apparatus on locomotives or cars to indicate bad track sections; General design of track recording vehicles
- B61K9/12—Measuring or surveying wheel-rims
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60T—VEHICLE BRAKE CONTROL SYSTEMS OR PARTS THEREOF; BRAKE CONTROL SYSTEMS OR PARTS THEREOF, IN GENERAL; ARRANGEMENT OF BRAKING ELEMENTS ON VEHICLES IN GENERAL; PORTABLE DEVICES FOR PREVENTING UNWANTED MOVEMENT OF VEHICLES; VEHICLE MODIFICATIONS TO FACILITATE COOLING OF BRAKES
- B60T17/00—Component parts, details, or accessories of power brake systems not covered by groups B60T8/00, B60T13/00 or B60T15/00, or presenting other characteristic features
- B60T17/18—Safety devices; Monitoring
- B60T17/22—Devices for monitoring or checking brake systems; Signal devices
- B60T17/228—Devices for monitoring or checking brake systems; Signal devices for railway vehicles
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- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/10—Internal combustion engine [ICE] based vehicles
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Abstract
The application relates to a vehicle fault early warning method, a vehicle fault early warning device, computer equipment and a readable storage medium, wherein the method comprises the steps of obtaining the current temperature of each wheel and the current average temperature of the wheels; under the condition that the current temperature is larger than the current average temperature, acquiring the maximum temperature value in each current temperature; obtaining a temperature detection result according to the maximum temperature value and a preset value; acquiring audio data of each wheel and processing the audio data to obtain a sound detection result; according to the temperature detection result and the sound detection result, early warning information used for representing that the vehicle is in a fault state is output, the influence of environmental factors on the temperature is eliminated, the accuracy of fault judgment is improved, the temperature and the sound are comprehensively judged, the false alarm rate is reduced, and reliable early warning of the vehicle fault is realized.
Description
Technical Field
The present disclosure relates to the field of fault diagnosis technologies, and in particular, to a vehicle fault early warning method, device, computer device, and readable storage medium.
Background
The failure of the brake band-type brake is poor in braking relief caused by the reasons of brake failure, unreliability of a hand brake and the like, and the rail wagon operation failure that a brake shoe cannot be separated from a wheel tread is mainly harmful to the abrasion of the wheel tread, slag on the wheel tread, pile rolling and even the failure of a combustion shaft. In the prior art, the brake fault is judged by manually detecting whether sparks and slag exist at the wheels and whether peculiar smell is generated; or the infrared light sensor is used for collecting the abrasion data of the brake shoe on the vehicle, judging the working state of the brake shoe according to the abrasion value of the brake shoe, and judging whether the vehicle has a brake fault or not. However, on the one hand, the prior art is only suitable for band-type brake fault detection under the static or low-speed running state of the vehicle, when the vehicle is in the high-speed running state, the infrared light sensor or the human body cannot acquire real-time sampling data, and particularly under the night or severe weather environment, the failure to acquire effective detection data can cause low early warning accuracy and serious false alarm missing. On the other hand. When the vehicle normally brakes and adjusts speed, all brake shoes are adhered to the tread of the wheel, so that the temperature of the wheel is increased, and the prior art cannot distinguish whether the band-type brake is in an adjustable speed state or in a fault state.
Disclosure of Invention
In view of the foregoing, it is desirable to provide an early warning method, apparatus, computer device, and readable storage medium that can reliably early warn of a vehicle failure.
A vehicle fault early warning method comprises the following steps:
acquiring the current temperature of each wheel and the current average temperature of the wheels;
under the condition that the current temperature is larger than the current average temperature, acquiring the maximum temperature value in each current temperature;
obtaining a temperature detection result according to the maximum temperature value and a preset value;
acquiring audio data of each wheel and processing the audio data to obtain a sound detection result;
and outputting early warning information used for representing that the vehicle is in a fault state according to the temperature detection result and the sound detection result.
In one embodiment, the step of obtaining the temperature detection result according to the maximum temperature value and the preset value includes:
under the condition that the maximum temperature value is smaller than or equal to a preset value, determining that the temperature detection result is normal;
and under the condition that the maximum temperature value is larger than a preset value, determining that the temperature detection result is abnormal.
In one embodiment, the method for early warning of a vehicle fault further includes the steps of:
and under the condition that each current temperature is smaller than or equal to the current average temperature, determining that the temperature detection result is normal.
In one embodiment, the step of outputting the warning information for representing that the vehicle is in the fault state according to the temperature detection result and the sound detection result includes:
outputting early warning information of a second preset level for representing that the vehicle is in a fault state under the condition that the temperature detection result is normal and the sound detection result is abnormal;
outputting early warning information of a second preset level under the condition that the temperature detection result is abnormal and the sound detection result is normal;
outputting early warning information of a first preset level for representing that the vehicle is in a fault state under the condition that the temperature detection result is abnormal and the sound detection result is abnormal; the first preset level is greater than the second preset level.
In one embodiment, the method for early warning of a vehicle fault further includes the steps of:
and under the condition that the temperature detection result is normal and the sound detection result is also normal, outputting normal information used for representing that the vehicle is in a normal state.
In one embodiment, the steps of acquiring audio data of each wheel and processing the audio data to obtain a sound detection result include:
sampling the audio data to obtain standardized audio data;
processing the standardized audio data to obtain a spectrogram;
acquiring a neural network model;
training the neural network model to obtain a voice recognition model;
and identifying the spectrogram by adopting a voice identification model to obtain a voice detection result.
In one embodiment, the step of obtaining the current temperature of each wheel, and the current average temperature of the wheels, comprises:
acquiring the total number of all wheels;
summing the current temperatures of all the wheels to obtain a total temperature;
the quotient of the total temperature and the total number of all wheels is determined as the current average temperature of the wheels.
An early warning device for a vehicle failure, comprising:
the temperature acquisition module is used for acquiring the current temperature of each wheel and the current average temperature of the wheels;
the maximum temperature value acquisition module is used for acquiring the maximum temperature value in each current temperature under the condition that the current temperature is larger than the current average temperature;
the temperature detection module is used for obtaining a temperature detection result according to the maximum temperature value and a preset value;
the sound detection module is used for acquiring the audio data of each wheel and processing the audio data to obtain a sound detection result;
and the early warning information output module is used for outputting early warning information used for representing that the vehicle is in a fault state according to the temperature detection result and the sound detection result.
A computer device comprising a memory storing a computer program and a processor implementing the steps of the above method when the processor executes the computer program.
A computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of the above method.
According to the vehicle fault early warning method, the current temperature of each wheel and the current average temperature of the wheels are obtained; under the condition that the current temperature is larger than the current average temperature, acquiring the maximum temperature value in each current temperature; obtaining a temperature detection result according to the maximum temperature value and a preset value; acquiring audio data of each wheel and processing the audio data to obtain a sound detection result; according to the temperature detection result and the sound detection result, early warning information used for representing that the vehicle is in a fault state is output, the influence of environmental factors on the temperature is eliminated, the accuracy of fault judgment is improved, the temperature and the sound are comprehensively judged, the false alarm rate is reduced, and reliable early warning of the vehicle fault is realized.
Drawings
In order to more clearly illustrate the technical solutions of embodiments or conventional techniques of the present application, the drawings required for the descriptions of the embodiments or conventional techniques will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present application, and other drawings may be obtained according to these drawings without inventive effort for a person of ordinary skill in the art.
FIG. 1 is a first schematic flow diagram of a method of warning of a vehicle fault in one embodiment;
FIG. 2 is a second schematic flow diagram of a method of warning of a vehicle fault in one embodiment;
FIG. 3 is a flowchart illustrating steps for outputting warning information indicating that a vehicle is in a fault state according to a temperature detection result and a sound detection result in one embodiment;
FIG. 4 is a flowchart illustrating steps for acquiring audio data of each wheel and processing the audio data to obtain a sound detection result according to an embodiment;
FIG. 5 is a flow chart of the steps for obtaining the current temperature of each wheel, and the current average temperature of the wheels, in one embodiment.
Detailed Description
In order to facilitate an understanding of the present application, a more complete description of the present application will now be provided with reference to the relevant figures. Examples of the present application are given in the accompanying drawings. This application may, however, be embodied in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein in the description of the application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application.
It will be understood that the terms "a," "an," and "the" as used herein also include plural forms, unless the context clearly dictates otherwise. It will be further understood that the terms "comprises" and/or "comprising," and/or the like, specify the presence of stated features, integers, steps, operations, elements, components, or groups thereof, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, or groups thereof.
When the freight train operates, a set of devices for generating braking are arranged on the locomotive and the vehicle in order to adjust the running speed of the train and stop the train at a specified place and ensure the normal point and safe running of the train. The braking device uses lever principle to expand the thrust of the piston of the braking cylinder of the air braking part or the pulling force generated by manual braking machine, and then to transmit the expanding force to each brake shoe evenly to stop the rotation of the wheel. The failure of the brake band-type brake is poor in braking relief caused by the reasons of brake failure, unreliability of a hand brake and the like, and the rail wagon operation failure that a brake shoe cannot be separated from a wheel tread is mainly harmful to the abrasion of the wheel tread, slag on the wheel tread, pile rolling and even the failure of a combustion shaft. Band-type brake failure of a vehicle can be divided into the following cases:
1. when the vehicle brake is in a release position, the piston rod of the brake cylinder is still in an extension state, namely the brake cylinder is not released, so that all brake shoes of the vehicle are clung to the wheel tread, slag and rolling piles are generated due to abrasion of the wheel tread, and high temperature is associated.
2. When the vehicle brake is in a release position, the piston rod of the brake cylinder is retracted, but the hand brake device is still in a braking position, namely, a brake chain of the hand brake is not released, and the front brake lever is still pulled, so that the basic brake device is still in a braking state, all brake shoes of the vehicle are clung to the wheel tread, slag is generated when the wheel tread is scratched, the wheel tread is rolled, and high temperature is associated.
3. In the running process of railway trucks, particularly when passing through a station, a brake speed regulation phenomenon often occurs, and a brake shoe is instantly abutted against a wheel tread to leave due to air braking of small decompression amount, but because of the difference of the brake sensitivity, brake adjuster flexibility and brake shoe thickness of each vehicle, certain brake shoes of certain vehicles can be relatively delayed to generate sparks when leaving the wheel tread, the phenomenon cannot be simply considered as a brake band-type brake, and the front station can be notified to focus on observation and then judgment.
In the prior art, the brake fault is judged by manually detecting whether sparks and slag exist at the wheels and whether peculiar smell is generated; or the infrared light sensor is used for collecting the abrasion data of the brake shoe on the vehicle, judging the working state of the brake shoe according to the abrasion value of the brake shoe, and judging whether the vehicle has a brake fault or not. However, on the one hand, the prior art is only suitable for band-type brake fault detection under the static or low-speed running state of the vehicle, when the vehicle is in the high-speed running state, the infrared light sensor or the human body cannot acquire real-time sampling data, and particularly under the night or severe weather environment, the failure to acquire effective detection data can cause low early warning accuracy and serious false alarm missing. On the other hand. When the vehicle normally brakes and adjusts speed, all brake shoes are adhered to the tread of the wheel, so that the temperature of the wheel is increased, and the prior art cannot distinguish whether the band-type brake is in an adjustable speed state or in a fault state.
In view of the above, the invention provides an early warning method, an early warning device, computer equipment and a readable storage medium, which can reliably early warn a vehicle fault.
In one embodiment, as shown in fig. 1, there is provided a vehicle fault early warning method, including the steps of:
s110, acquiring the current temperature of each wheel and the current average temperature of the wheels;
specifically, magnetic steel is arranged on a rail running on a train, and the magnetic steel has the functions of judging the coming train, measuring the speed, monitoring the sectional situation and judging the running-off of the train. And the thermal imagers are arranged on two sides of the train steel rail, and the installation height is flush with the train wheels, so that the wheels completely appear in the visual field of the thermal imagers. When a train passes through, the magnetic steel is started, the thermal imager starts to work, the current temperature of each wheel is collected, the current temperature is used for representing the average temperature of each wheel and is not the temperature of a certain point of the wheel, and the inaccuracy of collected data caused by the fact that the temperature of the certain point of the wheel is too high or too low is avoided. The current average temperature of the wheels is an average value of the current temperatures of all the wheels, and can be obtained by calculation.
S120, under the condition that the current temperature is larger than the current average temperature, acquiring the maximum temperature value in each current temperature;
specifically, the current temperature of each wheel is compared with the current average temperature, and if the current temperature of the wheel is larger than the current average temperature, the maximum temperature value in the current temperature of each wheel is obtained. Specifically, the current temperature of each wheel is compared with the current average temperature, so that the influence of environmental factors on a temperature acquisition result can be eliminated, for example, the current temperature of each wheel is generally higher in daytime and the current temperature of each wheel is generally lower at night, and therefore, under the condition that a train is longer, the influence of environmental factors can be eliminated and the accuracy of a detection result can be improved by comparing the current temperature of each wheel with the current average temperature.
S130, obtaining a temperature detection result according to the maximum temperature value and a preset value;
specifically, the temperature detection result includes normal and abnormal; the preset value is an empirical value and is set according to the ambient temperature, for example, the daytime temperature is higher, and the preset value is correspondingly larger; the night temperature is lower and the preset value is correspondingly smaller. In a specific embodiment, in the case that the maximum temperature value is greater than the preset value, determining the temperature detection result as abnormal; and determining the temperature detection result as normal when the maximum temperature is smaller than the preset value. In another specific embodiment, if the maximum temperature value is less than or equal to the current average temperature, the temperature detection result is directly confirmed to be normal.
S140, acquiring audio data of each wheel and processing the audio data to obtain a sound detection result;
in particular, the audio data is generated when the wheel is in contact with the rail. Specifically, the magnetic steel on the steel rail judges the coming train, tests the speed, determines the sectional situation and judges the running off of the train, and meanwhile, the pickup on the steel rail collects the sound generated when the wheels collide with the steel rail, when the train passes by, the magnetic steel is started, the pickup enters the working state, and the audio data of each wheel are collected.
S150, outputting early warning information used for representing that the vehicle is in a fault state according to the temperature detection result and the sound detection result.
Specifically, the early warning information comprises early warning information of a first preset level and early warning information of a second preset level; wherein the first preset level is higher than the second preset level. Specifically, under the condition that the temperature detection result and the sound detection result are abnormal, outputting early warning information of a first preset level; and outputting early warning information of a second preset level under the condition that the temperature detection result is normal and the sound detection result is abnormal or under the condition that the temperature detection result is abnormal and the sound detection result is normal. In another specific embodiment, the temperature detection result and the sound detection result are multiplied by the corresponding weight coefficients and then added and summed to obtain the early warning information that the vehicle is in a fault state. Judging whether the brake shoe is faulty or not from two dimensions of temperature and sound. When the band-type brake fault occurs, the temperature of the wheels is increased, and meanwhile, because the wheels are limited to rotate, sliding friction occurs between the wheels and the rail surface, and the audio signal generated by rolling friction in a normal state is different from the audio signal generated by rolling friction. And judging the two dimensions respectively, and then integrating the two results to finally give an early warning result.
According to the vehicle fault early warning method, the current temperature of each wheel and the current average temperature of the wheels are obtained; under the condition that the current temperature is larger than the current average temperature, acquiring the maximum temperature value in each current temperature; obtaining a temperature detection result according to the maximum temperature value and a preset value; acquiring audio data of each wheel and processing the audio data to obtain a sound detection result; according to the temperature detection result and the sound detection result, early warning information used for representing that the vehicle is in a fault state is output, the influence of environmental factors on the temperature is eliminated, the accuracy of fault judgment is improved, the temperature and the sound are comprehensively judged, the false alarm rate is reduced, and reliable early warning of the vehicle fault is realized.
In one embodiment, as shown in fig. 2, the step of obtaining the temperature detection result according to the maximum temperature value and the preset value includes:
s160, determining that the temperature detection result is normal under the condition that the maximum temperature value is smaller than or equal to a preset value;
s170, determining that the temperature detection result is abnormal when the maximum temperature value is larger than a preset value.
Specifically, the preset value is an empirical value, and is set according to the ambient temperature, for example, the daytime temperature is higher, and the preset value is correspondingly higher; the night temperature is lower and the preset value is correspondingly smaller. Specifically, in the case where the maximum temperature value is greater than the preset value, the temperature detection result is determined to be abnormal; and determining the temperature detection result as normal when the maximum temperature is smaller than the preset value.
In one embodiment, the method for early warning of a vehicle fault further comprises the steps of:
s180, determining that the temperature detection result is normal under the condition that each current temperature is smaller than or equal to the current average temperature.
Specifically, if the maximum temperature value is less than or equal to the current average temperature, the temperature detection result is directly confirmed to be normal, and the detection efficiency is improved.
In one embodiment, as shown in fig. 3, the step of outputting the warning information for representing that the vehicle is in the fault state according to the temperature detection result and the sound detection result includes:
s190, outputting early warning information of a second preset level for representing that the vehicle is in a fault state under the condition that the temperature detection result is normal and the sound detection result is abnormal;
s200, outputting early warning information of a second preset level under the condition that the temperature detection result is abnormal and the sound detection result is normal;
s210, outputting early warning information of a first preset level for representing that the vehicle is in a fault state under the condition that the temperature detection result is abnormal and the sound detection result is abnormal; the first preset level is greater than the second preset level.
Specifically, the first preset level is greater than the second preset level. Specifically, when the temperature detection result and the sound detection result are abnormal, outputting early warning information of a first preset level; and outputting early warning information of a second preset level when the temperature detection result is abnormal and the sound detection result is normal or when the temperature detection result is normal and the sound detection result is abnormal. When the staff receives the early warning information of the first preset level, the staff is highly armed and comprehensively checked; and when the worker receives the early warning information of the second preset level, repeatedly checking the result to confirm whether the fault occurs. And the two dimensions of sound and dimension are respectively judged, and then the two results are combined, so that an early warning result is finally given, and the early warning accuracy is improved. Meanwhile, the early warning is carried out according to two early warning levels, so that the experience of the system in use is improved, and the labor cost is reduced.
In one embodiment, the method for early warning of a vehicle fault further comprises the steps of:
and under the condition that the temperature detection result is normal and the sound detection result is also normal, outputting normal information used for representing that the vehicle is in a normal state.
Specifically, when the temperature detection result and the sound detection result are both normal, normal information is output so that the working personnel can record the train running condition.
In one embodiment, as shown in fig. 4, the steps of acquiring audio data of each wheel and processing the audio data to obtain a sound detection result include:
s230, sampling the audio data to obtain standardized audio data;
sampling refers to the process of discretizing a time-continuous analog signal on the time axis. The sampling period, that is, the time interval between two adjacent sampling points, the sampling frequency is the inverse of the sampling period, and theoretically, the higher the sampling frequency is, the higher the degree of restoration of the sound is, and the more realistic the sound is. In order to be undistorted, the sampling frequency needs to be greater than twice the highest frequency of the sound. Sampling here refers to measuring the analog sound signal at certain specific moments in time to obtain discrete sound signals.
Specifically, the audio data is an analog signal, the amplitude value of the audio data is intercepted according to a fixed time interval, the amplitude value of the positive phase and the negative phase is obtained by intercepting the amplitude value twice in each waveform period, and the amplitude value is represented by a plurality of binary digits, so that the analog sound signal is changed into a digital audio signal, namely, the standardized audio data.
S240, processing the standardized audio data to obtain a spectrogram;
specifically, the spectrogram may be acquired using any one of the methods, and alternatively, the spectrogram may be acquired using a short-time fourier transform method.
S250, acquiring a neural network model;
s260, training the neural network model to obtain a voice recognition model;
specifically, a convolutional neural network model is established, sample data of a train passing through a rail in a normal state is collected, and features in the sample data are extracted through the convolutional neural network model to form a voice recognition model. The voice recognition model is used for recognizing and classifying the audio data.
S270, recognizing the spectrogram by adopting a voice recognition model to obtain a voice detection result.
Specifically, the spectrogram is input into a voice recognition model, the voice recognition model extracts the characteristics in the spectrogram, the characteristics in the spectrogram are compared with the characteristics in the sample data, if the characteristics are consistent, the voice detection result is determined to be normal, and if the characteristics are inconsistent, the voice detection result is determined to be abnormal.
In one embodiment, as shown in fig. 5, the step of obtaining the current temperature of each wheel, and the current average temperature of the wheels, includes:
s280, obtaining the total number of all wheels;
s290, summing the current temperatures of the wheels to obtain a total temperature;
and S300, determining the quotient of the total temperature and the total number of all the wheels as the current average temperature of the wheels.
Specifically, when a train passes through, the magnetic steel is started, the thermal imager starts working, and the current temperature of each wheel is collected; the current average temperature of the wheels is an average value of the current temperatures of all the wheels, and can be obtained by calculation. Specifically, the total number of all wheels is obtained, and the current temperature of each wheel is summed to obtain the total temperature of all the wheels; the quotient of the total temperature and the total number of wheels is determined as the current average temperature of the wheels. By setting the current average temperature, the influence of environmental factors on the temperature detection result can be avoided.
It should be understood that, although the steps in the flowcharts of fig. 1-5 are shown in order as indicated by the arrows, these steps are not necessarily performed in order as indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least a portion of the steps of fig. 1-5 may include multiple steps or stages that are not necessarily performed at the same time, but may be performed at different times, nor does the order in which the steps or stages are performed necessarily occur sequentially, but may be performed alternately or alternately with at least a portion of the steps or stages in other steps or other steps.
In one embodiment, there is provided a vehicle fault early warning apparatus including:
the temperature acquisition module is used for acquiring the current temperature of each wheel and the current average temperature of the wheels;
the maximum temperature value acquisition module is used for acquiring the maximum temperature value in each current temperature under the condition that the current temperature is larger than the current average temperature;
the temperature detection module is used for obtaining a temperature detection result according to the maximum temperature value and a preset value;
the sound detection module is used for acquiring the audio data of each wheel and processing the audio data to obtain a sound detection result;
and the early warning information output module is used for outputting early warning information used for representing that the vehicle is in a fault state according to the temperature detection result and the sound detection result.
In one embodiment, the temperature detection module includes:
the first normal temperature detection result confirming module is used for confirming that the temperature detection result is normal under the condition that the maximum temperature value is smaller than or equal to a preset value;
and the abnormal temperature detection result confirming module is used for determining that the temperature detection result is abnormal under the condition that the maximum temperature value is larger than a preset value.
In one embodiment, the early warning device for a vehicle fault further includes:
and the second normal temperature detection result confirming module is used for determining that the temperature detection result is normal under the condition that each current temperature is smaller than or equal to the current average temperature.
In one embodiment, the early warning information output module includes:
the first second preset level early warning information output module is used for outputting the second preset level early warning information used for representing that the vehicle is in a fault state under the condition that the temperature detection result is normal and the sound detection result is abnormal;
the early warning information output module is used for outputting early warning information of a second preset level under the condition that the temperature detection result is abnormal and the sound detection result is normal;
the early warning information output module is used for outputting early warning information of the first preset level for representing that the vehicle is in a fault state under the condition that the temperature detection result is abnormal and the sound detection result is abnormal; the first preset level is greater than the second preset level.
In one embodiment, the early warning device for a vehicle fault further includes:
and the normal state information output module is used for outputting normal information used for representing that the vehicle is in a normal state under the condition that the temperature detection result is normal and the sound detection result is also normal.
In one embodiment, the sound detection module includes:
the standardized module is used for sampling the audio data to obtain standardized audio data;
the spectrogram acquisition module is used for processing the standardized audio data to obtain a spectrogram;
the neural network model acquisition module is used for acquiring a neural network model;
the voice recognition model acquisition module is used for training the neural network model to obtain a voice recognition model;
and the sound detection result acquisition module is used for identifying the spectrogram by adopting the sound identification model to obtain a sound detection result.
In one embodiment, the temperature acquisition module includes:
the number acquisition module of the train theory is used for acquiring the total number of all wheels;
the total temperature acquisition module is used for carrying out summation treatment on the current temperature of each wheel to obtain the total temperature;
and the average temperature acquisition module is used for determining the quotient of the total temperature and the total number of all the wheels as the current average temperature of the wheels.
For specific limitations of the vehicle fault warning device, reference may be made to the above limitation of the vehicle fault warning method, and the description thereof will not be repeated here. The modules in the vehicle fault early warning device can be realized in whole or in part through software, hardware and a combination thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules. It should be noted that, in the embodiment of the present application, the division of the modules is schematic, which is merely a logic function division, and other division manners may be implemented in actual implementation.
In one embodiment, a computer device is provided comprising a memory storing a computer program and a processor that when executing the computer program performs the steps of:
acquiring the current temperature of each wheel and the current average temperature of the wheels;
under the condition that the current temperature is larger than the current average temperature, acquiring the maximum temperature value in each current temperature;
obtaining a temperature detection result according to the maximum temperature value and a preset value;
acquiring audio data of each wheel and processing the audio data to obtain a sound detection result;
and outputting early warning information used for representing that the vehicle is in a fault state according to the temperature detection result and the sound detection result.
In one embodiment, the processor when executing the computer program further performs the steps of:
under the condition that the maximum temperature value is smaller than or equal to a preset value, determining that the temperature detection result is normal;
and under the condition that the maximum temperature value is larger than a preset value, determining that the temperature detection result is abnormal.
In one embodiment, the processor when executing the computer program further performs the steps of:
and under the condition that each current temperature is smaller than or equal to the current average temperature, determining that the temperature detection result is normal.
In one embodiment, the processor when executing the computer program further performs the steps of:
outputting early warning information of a second preset level for representing that the vehicle is in a fault state under the condition that the temperature detection result is normal and the sound detection result is abnormal;
outputting early warning information of a second preset level under the condition that the temperature detection result is abnormal and the sound detection result is normal;
outputting early warning information of a first preset level for representing that the vehicle is in a fault state under the condition that the temperature detection result is abnormal and the sound detection result is abnormal; the first preset level is greater than the second preset level.
In one embodiment, the processor when executing the computer program further performs the steps of:
and under the condition that the temperature detection result is normal and the sound detection result is also normal, outputting normal information used for representing that the vehicle is in a normal state.
In one embodiment, the processor when executing the computer program further performs the steps of:
sampling the audio data to obtain standardized audio data;
processing the standardized audio data to obtain a spectrogram;
acquiring a neural network model;
training the neural network model to obtain a voice recognition model;
and identifying the spectrogram by adopting a voice identification model to obtain a voice detection result.
In one embodiment, the processor when executing the computer program further performs the steps of:
acquiring the total number of all wheels;
summing the current temperatures of all the wheels to obtain a total temperature;
the quotient of the total temperature and the total number of all wheels is determined as the current average temperature of the wheels.
In one embodiment, a computer readable storage medium is provided having a computer program stored thereon, which when executed by a processor, performs the steps of:
acquiring the current temperature of each wheel and the current average temperature of the wheels;
under the condition that the current temperature is larger than the current average temperature, acquiring the maximum temperature value in each current temperature;
obtaining a temperature detection result according to the maximum temperature value and a preset value;
acquiring audio data of each wheel and processing the audio data to obtain a sound detection result;
and outputting early warning information used for representing that the vehicle is in a fault state according to the temperature detection result and the sound detection result.
In one embodiment, the computer program when executed by the processor further performs the steps of:
under the condition that the maximum temperature value is smaller than or equal to a preset value, determining that the temperature detection result is normal;
and under the condition that the maximum temperature value is larger than a preset value, determining that the temperature detection result is abnormal.
In one embodiment, the computer program when executed by the processor further performs the steps of:
and under the condition that each current temperature is smaller than or equal to the current average temperature, determining that the temperature detection result is normal.
In one embodiment, the computer program when executed by the processor further performs the steps of:
outputting early warning information of a second preset level for representing that the vehicle is in a fault state under the condition that the temperature detection result is normal and the sound detection result is abnormal;
outputting early warning information of a second preset level under the condition that the temperature detection result is abnormal and the sound detection result is normal;
outputting early warning information of a first preset level for representing that the vehicle is in a fault state under the condition that the temperature detection result is abnormal and the sound detection result is abnormal; the first preset level is greater than the second preset level.
In one embodiment, the computer program when executed by the processor further performs the steps of:
and under the condition that the temperature detection result is normal and the sound detection result is also normal, outputting normal information used for representing that the vehicle is in a normal state.
In one embodiment, the computer program when executed by the processor further performs the steps of:
sampling the audio data to obtain standardized audio data;
processing the standardized audio data to obtain a spectrogram;
acquiring a neural network model;
training the neural network model to obtain a voice recognition model;
and identifying the spectrogram by adopting a voice identification model to obtain a voice detection result.
In one embodiment, the computer program when executed by the processor further performs the steps of:
acquiring the total number of all wheels;
summing the current temperatures of all the wheels to obtain a total temperature;
the quotient of the total temperature and the total number of all wheels is determined as the current average temperature of the wheels.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, or the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory. By way of illustration, and not limitation, RAM can be in the form of a variety of forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), and the like.
In the description of the present specification, reference to the terms "some embodiments," "other embodiments," "desired embodiments," and the like, means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, schematic descriptions of the above terms do not necessarily refer to the same embodiment or example.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples merely represent a few embodiments of the present application, which are described in more detail and are not to be construed as limiting the scope of the invention. It should be noted that it would be apparent to those skilled in the art that various modifications and improvements could be made without departing from the spirit of the present application, which would be within the scope of the present application. Accordingly, the scope of protection of the present application is to be determined by the claims appended hereto.
Claims (9)
1. The early warning method for the vehicle fault is characterized by comprising the following steps:
acquiring the current temperature of each wheel and the current average temperature of the wheels;
acquiring the maximum temperature value in each current temperature under the condition that the current temperature is larger than the current average temperature;
obtaining a temperature detection result according to the maximum temperature value and a preset value;
acquiring audio data of each wheel and processing the audio data to obtain a sound detection result;
outputting early warning information used for representing that the vehicle is in a fault state according to the temperature detection result and the sound detection result;
the step of outputting early warning information for representing that the vehicle is in a fault state according to the temperature detection result and the sound detection result comprises the following steps:
outputting early warning information of a second preset level for representing that the vehicle is in a fault state under the condition that the temperature detection result is normal and the sound detection result is abnormal;
outputting early warning information of the second preset level under the condition that the temperature detection result is abnormal and the sound detection result is normal;
outputting early warning information of a first preset level for representing that the vehicle is in a fault state under the condition that the temperature detection result is abnormal and the sound detection result is abnormal; the first preset level is greater than the second preset level.
2. The method for early warning of a vehicle fault according to claim 1, wherein the step of obtaining a temperature detection result according to the maximum temperature value and a preset value includes:
under the condition that the maximum temperature value is smaller than or equal to the preset value, determining that the temperature detection result is normal;
and under the condition that the maximum temperature value is larger than the preset value, determining that the temperature detection result is abnormal.
3. The vehicle failure warning method according to claim 1, characterized by further comprising the step of:
and under the condition that each current temperature is smaller than or equal to the current average temperature, determining that the temperature detection result is normal.
4. The vehicle failure warning method according to claim 1, characterized by further comprising the step of:
and outputting normal information used for representing that the vehicle is in a normal state under the condition that the temperature detection result is normal and the sound detection result is also normal.
5. The vehicle malfunction alerting method according to claim 1, wherein the steps of acquiring audio data of each of the wheels and processing the audio data to obtain a sound detection result, include:
sampling the audio data to obtain standardized audio data;
processing the standardized audio data to obtain a spectrogram;
acquiring a neural network model;
training the neural network model to obtain a voice recognition model;
and recognizing the spectrogram by adopting the voice recognition model to obtain the voice detection result.
6. The vehicle failure warning method according to claim 1, characterized in that the step of acquiring the current temperature of each wheel, and the current average temperature of the wheels, includes:
acquiring the total number of all wheels;
summing the current temperatures of the wheels to obtain a total temperature;
the quotient of the total temperature and the total number of all wheels is determined as the current average temperature of the wheels.
7. An early warning device for a vehicle failure, comprising:
the temperature acquisition module is used for acquiring the current temperature of each wheel and the current average temperature of the wheels;
the maximum temperature value acquisition module is used for acquiring the maximum temperature value in each current temperature under the condition that the current temperature is larger than the current average temperature;
the temperature detection module is used for obtaining a temperature detection result according to the maximum temperature value and a preset value;
the sound detection module is used for acquiring the audio data of each wheel and processing the audio data to obtain a sound detection result;
the early warning information output module is used for outputting early warning information used for representing that the vehicle is in a fault state according to the temperature detection result and the sound detection result;
wherein, early warning information output module includes:
the first and second preset level early warning information output module is used for outputting the second preset level early warning information used for representing that the vehicle is in a fault state under the condition that the temperature detection result is normal and the sound detection result is abnormal;
the second pre-warning information output module is used for outputting pre-warning information of a second pre-set level under the condition that the temperature detection result is abnormal and the sound detection result is normal;
the early warning information output module is used for outputting early warning information of a first preset level, which is used for representing that the vehicle is in a fault state, under the condition that the temperature detection result is abnormal and the sound detection result is abnormal; the first preset level is greater than the second preset level.
8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1 to 6 when the computer program is executed.
9. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method according to any one of claims 1 to 6.
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| CN107554558A (en) * | 2017-08-31 | 2018-01-09 | 哈尔滨威克科技有限公司 | Running mechanism of train portion safety detection prewarning apparatus |
| CN108928366A (en) * | 2018-06-22 | 2018-12-04 | 北京康拓红外技术股份有限公司 | A kind of 5T comprehensive detection system and detection method |
| CN112418604A (en) * | 2020-10-16 | 2021-02-26 | 宝山钢铁股份有限公司 | Intelligent monitoring method for large-scale travelling crane wheel |
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| CN107554558A (en) * | 2017-08-31 | 2018-01-09 | 哈尔滨威克科技有限公司 | Running mechanism of train portion safety detection prewarning apparatus |
| CN108928366A (en) * | 2018-06-22 | 2018-12-04 | 北京康拓红外技术股份有限公司 | A kind of 5T comprehensive detection system and detection method |
| CN112418604A (en) * | 2020-10-16 | 2021-02-26 | 宝山钢铁股份有限公司 | Intelligent monitoring method for large-scale travelling crane wheel |
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