CN110471376A - A kind of industry spot fault detection method and equipment - Google Patents
A kind of industry spot fault detection method and equipment Download PDFInfo
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- CN110471376A CN110471376A CN201910620847.2A CN201910620847A CN110471376A CN 110471376 A CN110471376 A CN 110471376A CN 201910620847 A CN201910620847 A CN 201910620847A CN 110471376 A CN110471376 A CN 110471376A
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Abstract
The present invention is suitable for field of computer technology, provides a kind of industry spot fault detection method and equipment, comprising: obtain the scene information of object to be detected；Wherein, the scene information is used to judge the fault message of the object to be detected；The scene information includes environmental information and location information；The scene information is input to preparatory trained Fault Model to handle, obtains the fault identification result of the object to be detected.The above method, the comprehensive fault message that object to be detected is judged with reference to environmental information and location information, by the way that scene information is input in Fault Model, identify the fault identification result of object to be detected, the type being out of order and location of fault can be accurately identified, manpower has been saved, the efficiency of inspection is improved.
Description
Technical field
The invention belongs to field of computer technology more particularly to a kind of industry spot fault detection method and equipment.
Background technique
The safe Daily Round Check of industry spot makes the emphasis of management of safe operation, and existing industry inspection field scene is complicated,
And it is excessive dependent on artificial and all kinds of tools during carrying out fault detection, for example, existing tool has temperature
The temperature measurement tools such as test paper, thermal infrared imager, infrared point temperature instrument, while there are also vibration-detecting instrument, voice detector and detection rulers
Very little various measuring tools.
But excessive dependence tool and artificial when detecting failure, the scene at inspection scene is many and diverse, and every kind of tool
A kind of corresponding reference factor can only be obtained, leads to not accurately identify the type being out of order and location of fault in this way, wave
A large amount of manpower is taken, routing inspection efficiency is extremely low.
Summary of the invention
In view of this, the embodiment of the invention provides a kind of industry spot fault detection method and equipment, it is existing to solve
The type being out of order and location of fault can not be accurately identified in technology, wastes a large amount of manpower, and routing inspection efficiency is extremely low
Problem.
The first aspect of the embodiment of the present invention provides a kind of industry spot fault detection method, comprising:
Obtain the scene information of object to be detected；Wherein, the scene information is used to judge the event of the object to be detected
Hinder information；The scene information includes environmental information and location information；
The scene information is input to preparatory trained Fault Model to handle, it is described to be detected right to obtain
The fault identification result of elephant；Wherein, the fault identification result includes fault type and fault location information；In training process
In, the input of the Fault Model is the sample scene information and the corresponding fault message of the sample scene of sample object
Label, the output of the Fault Model are the fault identification result of the sample object.
The second aspect of the embodiment of the present invention provides a kind of industry spot fault detection means, comprising:
Acquiring unit, for obtaining the scene information of object to be detected；Wherein, the scene information for judge it is described to
The fault message of test object；The scene information includes environmental information and location information；
Processing unit is handled for the scene information to be input to preparatory trained Fault Model, is obtained
To the fault identification result of the object to be detected；Wherein, the fault identification result includes fault type and fault bit confidence
Breath；In the training process, sample scene information and the sample scene of the input of the Fault Model for sample object
Corresponding fault message label, the output of the Fault Model are the fault identification result of the sample object.
The third aspect of the embodiment of the present invention provides a kind of industry spot fault test set, including memory, processing
Device and storage in the memory and the computer program that can run on the processor, described in the processor execution
The step of industry spot fault detection method as described in above-mentioned first aspect is realized when computer program.
The fourth aspect of the embodiment of the present invention provides a kind of computer readable storage medium, the computer-readable storage
Media storage has computer program, and the industry as described in above-mentioned first aspect is realized when the computer program is executed by processor
The step of field failure detection method.
In the embodiment of the present invention, the scene information of object to be detected is obtained；Wherein, the scene information is described for judging
The fault message of object to be detected；The scene information includes environmental information and location information；The scene information is input to
Preparatory trained Fault Model is handled, and the fault identification result of the object to be detected is obtained.The above method, it is comprehensive
The fault message that object to be detected is judged with reference to environmental information and location information closed, by the way that scene information to be input to
In Fault Model, the fault identification of object to be detected is identified as a result, it is possible to accurately identify the type being out of order and event
The position of barrier, has saved manpower, improves the efficiency of inspection.
Detailed description of the invention
It to describe the technical solutions in the embodiments of the present invention more clearly, below will be to embodiment or description of the prior art
Needed in attached drawing be briefly described, it should be apparent that, the accompanying drawings in the following description is only of the invention some
Embodiment for those of ordinary skill in the art without any creative labor, can also be according to these
Attached drawing obtains other attached drawings.
Fig. 1 is a kind of schematic flow diagram of industry spot fault detection method provided in an embodiment of the present invention；
Fig. 2 is the exemplary flow that S102 is refined in a kind of industry spot fault detection method provided in an embodiment of the present invention
Figure；
Fig. 3 be another embodiment of the present invention provides another industry spot fault detection method schematic flow diagram；
Fig. 4 be another embodiment of the present invention provides another industry spot fault detection method in S202 refinement signal
Flow chart；
Fig. 5 is a kind of schematic flow diagram for industry spot fault detection method that yet another embodiment of the invention provides；
Fig. 6 is a kind of the application schematic diagram of industry spot fault detection means provided in an embodiment of the present invention；
Fig. 7 is the schematic diagram for the industry spot fault test set that one embodiment of the invention provides.
Specific embodiment
In being described below, for illustration and not for limitation, the tool of such as particular system structure, technology etc is proposed
Body details, to understand thoroughly the embodiment of the present invention.However, it will be clear to one skilled in the art that there is no these specific
The present invention also may be implemented in the other embodiments of details.In other situations, it omits to well-known system, device, electricity
The detailed description of road and method, in case unnecessary details interferes description of the invention.
In order to illustrate technical solutions according to the invention, the following is a description of specific embodiments.
Referring to Figure 1, Fig. 1 is a kind of exemplary flow of industry spot fault detection method provided in an embodiment of the present invention
Figure.In the present embodiment the executing subject of industry spot fault detection method be industry spot fault test set, equipment include but
It is not limited to smart phone, tablet computer, wearable device, mobile terminal etc..Industry spot fault detection method as shown in Figure 1
Can include:
S101: the scene information of object to be detected is obtained；Wherein, the scene information is for judging the object to be detected
Fault message；The scene information includes environmental information and location information.
During industry spot inspection, on-the-spot meeting includes multiple objects to be detected, and industry spot fault detection is set
The standby scene information for obtaining object to be detected.Wherein, scene information is used to judge the fault message of object to be detected, fault message
It may include fault type, the fault condition information etc. of object to be detected.Scene information can be obtained by the sensor at scene
It takes, scene information includes environmental information and location information.
Environmental information is the relevant information of object local environment to be detected, may include the ambient image letter of object to be detected
Breath, also may include the parameter of the environmental correclation of object to be detected, such as the operating temperature of object to be detected, object to be detected
Working environment humidity etc..
Location information includes object to be detected in the location of inspection scene information and object internal structure to be detected
In each position location information.Wherein, object to be detected inspection scene the location of information can by obtain to
The object identity of test object determines object to be detected based on the corresponding relationship of default object identity and preset position information
In the location of inspection scene information；It can also be obtained by positioning device, such as use electronic gyroscope/GPS/4G/5G/
The positioning devices such as WIFI.The location information at each position can be based on the object of object to be detected in object internal structure to be detected
Mark obtains the location information at each position in the corresponding internal structure of the object to be detected, can also be to be detected right by obtaining
The image information of elephant constructs the internal structure of object to be detected based on preset parameter, so that it is determined that object to be detected is corresponding
The location information at each position in internal structure.
S102: being input to preparatory trained Fault Model for the scene information and handle, obtain it is described to
The fault identification result of test object；Wherein, the fault identification result includes fault type and fault location information；In training
In the process, the input of the Fault Model is the sample scene information and the corresponding failure of the sample scene of sample object
Information labels, the output of the Fault Model are the fault identification result of the sample object.
Trained Fault Model is pre-set in equipment, preparatory trained Fault Model may include
Input layer, hidden layer, output layer (loss function layer).Input layer includes an input layer, for receiving input from outside
Scene information.Hidden layer is for handling scene information.Output layer is used to export the fault identification knot of object to be detected
Fruit.In the present embodiment, in the training process, the input of Fault Model is sample pair to preparatory trained Fault Model
The corresponding fault message label of sample scene information and sample scene of elephant, the output of Fault Model are the event of sample object
Hinder recognition result.Scene information is input to preparatory trained Fault Model to handle, obtains object to be detected
Fault identification is as a result, fault identification result includes fault type and fault location information.
Further, in order to more accurately identify the fault identification of object to be detected as a result, S102 may include S1021
~S1022, as shown in Fig. 2, S1021~S1022 is specific as follows:
S1021: between identification information based on the object to be detected, default identification information and preset failure detection model
Corresponding relationship, determine the corresponding target faults detection model of the object to be detected.
In industry spot fault test set, multiple Fault Models, each preset failure detection model are preset
Correspondence can identify the fault identification result of different objects.Preset failure detection model may include input layer, hidden layer, defeated
Layer (loss function layer) out.Input layer includes an input layer, for receiving the scene information inputted from external.Hidden layer
For handling scene information.Output layer is used to export the fault identification result of object to be detected.In the present embodiment, preset
In the training process, the input of Fault Model is the sample scene information and sample scene of sample object to Fault Model
Corresponding fault message label, the output of Fault Model are the fault identification result of sample object.Scene information is inputted
It is handled to preparatory trained Fault Model, obtains the fault identification of object to be detected as a result, fault identification result
Including fault type and fault location information.
Corresponding pass between default identification information and preset failure detection model is set in industry spot fault test set
System, identification information, default identification information based on object to be detected and the corresponding relationship between preset failure detection model, determine
The corresponding target faults detection model of object to be detected.
S1022: the scene information is input to the target faults detection model and is handled, is obtained described to be detected
The fault identification result of object.
Scene information is input to target faults detection model and handled by industry spot fault test set, i.e., will be to be checked
The scene information for surveying object is input to the corresponding Fault Model of the object and is handled, and the failure for obtaining object to be detected is known
Other result.Different objects is identified, classification processing, realize intelligent classification, intelligent measurement improves fault detection
Efficiency also improves the accuracy of fault detection.
In the embodiment of the present invention, the scene information of object to be detected is obtained；Wherein, the scene information is described for judging
The fault message of object to be detected；The scene information includes environmental information and location information；The scene information is input to
Preparatory trained Fault Model is handled, and the fault identification result of the object to be detected is obtained.The above method, it is comprehensive
The fault message that object to be detected is judged with reference to environmental information and location information closed, by the way that scene information to be input to
In Fault Model, the fault identification of object to be detected is identified as a result, it is possible to accurately identify the type being out of order and event
The position of barrier, has saved manpower, improves the efficiency of inspection.
Refer to Fig. 3, Fig. 3 be another embodiment of the present invention provides another industry spot fault detection method signal
Flow chart.The executing subject of industry spot fault detection method is industry spot fault test set, equipment packet in the present embodiment
Include but be not limited to smart phone, tablet computer, wearable device, mobile terminal etc..For more comprehensive test object for the treatment of
Failure is identified, more detailed scene information is obtained in the present embodiment, and the difference of the present embodiment and first embodiment is
S201~S203, S204 is identical as the S102 in first embodiment in the present embodiment, and S201~S203 is in first embodiment
The further refinement of S101, S201, S202, S203 execution have no sequencing, also may be performed simultaneously, as shown in figure 3, S201
~S203 is specific as follows:
S201: obtaining the radio signal at scene to be detected, based on radio signal identification object to be detected and its
Identification information.
Industry spot fault test set obtains the radio signal at scene to be detected, using radio frequency in the present embodiment
Identification technology (Radio Frequency Identification, RFID), is arranged RFID electronic label on object to be detected.
RFID is a kind of wireless communication technique, and specific objective can be identified by radio signals and reads and writes related data.Radio
Signal is the electromagnetic field by being tuned into radio frequency, data is sent out from the label being attached on article, with automatic
Identification and the tracking article.Certain labels can be obtained by energy from the electromagnetic field that identifier issues in identification, and be not required to
Want battery；Also there is label itself to possess power supply, and can actively issue radio wave (electromagnetic field for being tuned into radio frequency).Mark
Label contain the information of Electronic saving, can identify within several meters.Unlike bar code, RF tag does not need to be in
Within identifier sight, it can also be embedded in and be tracked within object.That is, each object to be detected have one it is unique
Identification information therefore by the available identification information to object to be detected of radio signal, be then based on default mark
The corresponding relationship of information and default object determines object to be detected.Wherein, the identification information of object to be detected can be unique
Electronic code.
In addition it is also possible to obtain the other information, such as location information etc. of object to be detected.
S202: the environmental information of the object to be detected is obtained.
S202 is identical as the associated description in S101, specifically can be refering to S101, and details are not described herein again.
Further, it in order to which the more comprehensive failure for treating test object is identified, is obtained in the present embodiment more in detail
Thin scene information, environmental information include sound frequency information, intensity of sound information, electromechanical amount vibrational waveform information and work temperature
Information is spent, S202 may include S2021~S2022, as shown in figure 4, S2021~S2022 is specific as follows:
S2021: sound frequency information, the intensity of sound information, vibrational waveform letter when the object to be detected work are obtained
Breath.
When object to be detected works, certain sound can be generated, the sound that generates when based on work, it can be determined that operation is
It is no it is normal, whether working condition stable.So obtaining sound frequency information when object to be detected work, intensity of sound information
With vibrational waveform information can also it is more acurrate, more fully judge failure.It is to be detected right that industry spot fault test set obtains
Sound frequency information, intensity of sound information when as work, can by the voice collection devices such as the microphone acquisition at scene to
Sound when test object works, obtains sound frequency information and intensity of sound information after processing.Obtaining object to be detected
It after sound, needs to remove extra noise, only there are the noise waves of object to be detected.
When measurement equipment to be checked works normally, machinery rotation has the regular waveform of comparison, and vibration is fixed on a certain wave
Section, when occurring abnormal, waveform will appear mutation, and the failure of target can be judged according to this mutation.Industry spot fault detection
Equipment obtains vibrational waveform information when object to be detected work, can be turned by the mechanical quantity that electric measuring type vibrating sensor will acquire
Charge transport is turned to, is shown waveform according to electricity.Acquisition, vibration wave analysis and processing including vibration wave, pass through biography
The vibration wave of sensor acquisition is the signal of simulation, and waveform variation is small, and display vibration wave need to be exported after amplification or filtration treatment
Shape.Vibrational waveform is mainly reflected in frequency and amplitude when target operation, complements each other with sound frequency information.It is understood that
It is that, when environmental information includes sound frequency information, intensity of sound information and vibrational waveform information, corresponding model is in training
When, also want collecting sample sound frequency information and sample audio intensity and sample vibrational waveform information.
S2022: obtaining the thermal infrared imagery of the object to be detected, based on the thermal infrared imagery determine described in
The operational temperature information of test object.
Due to the operating temperature under industry spot, each object work Shi Douyou normal operating conditions to be detected, once
When failure, may result in operating temperature and change, thus we using the operational temperature information of object to be detected as
Judge a reference factor of failure.
Industry spot fault test set obtains the thermal infrared imagery of object to be detected, and thermal infrared imagery is referred to as infrared
Image, also known as thermal imagery are by thermal infrared scanner reception and to record the infrared radiant energy that object emits and the image formed.Heat
Infrared image is heat radiation imaging, it is the appearance with infrared imagery technique and is born.Infrared imagery technique is a kind of heat
Radiation information Detection Techniques, it is imaged according to the infra-red radiation difference of object, and infra-red thermal imaging system can be object table
Naturally the infrared radiation distribution emitted in face is changed into visual picture.Since the different parts of different objects or same object are usual
With different thermal radiation properties, such as the temperature difference, emissivity, after carrying out thermal infrared imaging, object in thermal infrared images because
For its heat radiation difference and be distinguished.So being the work temperature that can determine object to be detected based on thermal infrared imagery
Spend information.
Wherein, in industry spot, the thermal infrared images of object to be detected can be got by infrared sensor.Industry is existing
Field fault test set always obtains the thermal infrared imagery of object to be detected from infrared sensor, is determined based on thermal infrared imagery
The operational temperature information of object to be detected.
S203: the location information of the object to be detected is obtained.
S203 is identical as the associated description in S101, specifically can be refering to S101, and details are not described herein again.
Further, it in order to which the more comprehensive failure for treating test object is identified, is obtained in the present embodiment more in detail
Thin scene information, scene information further include the three-dimensional model information of object to be detected, and three-dimensional model information includes to be detected right
The three-dimensional structure image of elephant, before S204, can also include: obtain the object to be detected two-dimensional image information and
Spatial parameter information determines the three-dimensional mould of the object to be detected based on the two-dimensional image information and the spatial parameter information
Type information.
Scene information further includes the three-dimensional model information of object to be detected, and three-dimensional model information includes the three of object to be detected
Stereochemical structure image is tieed up, the three-dimensional structure image of object to be detected is passed through, it can be determined that whether object to be detected has scarce out
The case where part or deformation, thus we using the three-dimensional model information of object to be detected as judge one of failure refer to because
Element.
Industry spot fault test set obtains the two-dimensional image information and spatial parameter information of object to be detected, wherein
Spatial parameter information is that two dimensional image is converted into parameter information required when three-dimensional image, can be obtained by distance measuring sensor
The range information of distance measuring sensor and object to be detected is taken to determine spatial parameter information.Joined based on two-dimensional image information and space
Number information determines the three-dimensional model information of object to be detected.
Further, during inspection, industry spot fault test set can obtain inspection by positioning device
Path, to obtain the track of inspection.The track of inspection is recorded, can prevent from missing object to be detected.
It further, can also include blending image in scene information, industry spot fault test set can will be to be checked
The thermal infrared images and two-dimensional image information for surveying object are merged, and obtain blending image, and will obtain by various sensors
The every reference factor and its parameter tags got are in blending image.That is much information fusion is formed under blending image, i.e.,
Each object to be detected has object oriented, temperature information, sound frequency information, intensity of sound information, location information etc., removes
Except this, the vibration information of target, the identification information of RFID label tag and 3D Model Matching synchronizing information are shown, that is, show infrared figure
As under the blending image of visible images.Industry spot fault test set can transmit blending image and scene information
It is shown on to other equipment, the form of display can switch over according to the demand of user, for example, display sound waveform is simultaneously
And carry other information or show vibrational waveform and carry other information or display three-dimensional structure image and
Other information is carried, herein with no restrictions.
Fig. 5 is referred to, Fig. 5 is a kind of signal stream for industry spot fault detection method that yet another embodiment of the invention provides
Cheng Tu.The executing subject of industry spot fault detection method is industry spot fault test set in the present embodiment, and equipment includes
But be not limited to smart phone, tablet computer, wearable device, mobile terminal etc..In order to obtain the higher fault identification of accuracy rate
Model, the training method for fault identification model limited in the present embodiment, the difference of the present embodiment and first embodiment exist
S303~S304 is identical as S101~S102 in first embodiment in S301~S302, the present embodiment, and S301~S302 exists
It is executed before S303~S304, as shown in figure 5, S301~S302 is specific as follows:
S301: sample training collection is obtained；The sample training collection includes the sample scene information and the sample of sample object
The corresponding fault message label of this object.
Industry spot fault test set obtains sample training collection, and sample training collection includes the sample scene letter of sample object
Cease fault message label corresponding with sample object.It is understood that the sample size that sample training is concentrated is more, train
Model it is more accurate when being identified.When in sample scene information including the image information of sample object, this can be acquired
The image of object different angle, different distance, the comprehensive image information for obtaining the sample object, for carrying out the instruction of model
Practice.
S302: being trained the sample training collection, obtains for exporting the corresponding fault identification of the sample object
As a result fault identification model.
Industry spot fault test set is trained sample training collection, obtains for exporting the corresponding event of sample object
Hinder the fault identification model of recognition result.It further, can also be to sample training collection according to different samples in trained process
This object is classified, and is trained respectively to inhomogeneous sample training collection, is obtained the corresponding failure of different sample objects and is known
Other model.
Two steps of S301~S302 in the present embodiment can also execute before S201~S204, form another reality
Example is applied, specifically can be refering to associated description, details are not described herein again.
It should be understood that the size of the serial number of each step is not meant that the order of the execution order in above-described embodiment, each process
Execution sequence should be determined by its function and internal logic, the implementation process without coping with the embodiment of the present invention constitutes any limit
It is fixed.
It is a kind of the application signal of industry spot fault detection means provided in an embodiment of the present invention referring to Fig. 6, Fig. 6
Figure.Industry spot fault detection means 6 can be industry spot fault test set, equipment include but is not limited to smart phone,
Tablet computer, wearable device, mobile terminal etc..Originally each unit for including is for executing in the corresponding embodiment of FIG. 1 to FIG. 5
Each step, referring specifically to the associated description in the corresponding embodiment of FIG. 1 to FIG. 5.For ease of description, illustrate only with
The relevant part of the present embodiment.The industry spot fault detection means 6 of the present embodiment includes:
Acquiring unit 610, for obtaining the scene information of object to be detected；Wherein, the scene information is for judging institute
State the fault message of object to be detected；The scene information includes environmental information and location information；
Processing unit 620 is handled for the scene information to be input to preparatory trained Fault Model,
Obtain the fault identification result of the object to be detected；Wherein, the fault identification result includes fault type and abort situation
Information；In the training process, sample scene information and the sample field of the input of the Fault Model for sample object
The corresponding fault message label of scape, the output of the Fault Model are the fault identification result of the sample object.
Further, acquiring unit 610, comprising:
First acquisition unit, for obtaining the radio signal at scene to be detected, based on radio signal identification to
Test object and its identification information；
Second acquisition unit, for obtaining the environmental information of the object to be detected；
Third acquiring unit, for obtaining the location information of the object to be detected.
Further, the environmental information includes sound frequency information, intensity of sound information, vibrational waveform information and work
Temperature information, second acquisition unit are specifically used for:
Obtain sound frequency information, intensity of sound information and the vibrational waveform information when object to be detected work；
The thermal infrared imagery for obtaining the object to be detected, it is described to be detected right to be determined based on the thermal infrared imagery
The operational temperature information of elephant.
Further, the scene information further includes the three-dimensional model information of the object to be detected, the three-dimensional model
Information includes the three-dimensional structure image of the object to be detected, acquiring unit 610, further includes:
4th acquiring unit is based on for obtaining the two-dimensional image information and spatial parameter information of the object to be detected
The two-dimensional image information and the spatial parameter information determine the three-dimensional model information of the object to be detected.
Further, the scene information further includes the vibration band information of the object to be detected, acquiring unit 610,
Further include:
5th acquiring unit, for obtaining the vibration band information of the object to be detected.
Further, processing unit 620 are specifically used for:
It is corresponding between identification information based on the object to be detected, default identification information and preset failure detection model
Relationship determines the corresponding target faults detection model of the object to be detected；
The scene information is input to the target faults detection model to handle, obtains the object to be detected
Fault identification result.
Further, industry spot fault test set 6, further includes:
6th acquiring unit, for obtaining sample training collection；The sample training collection includes the sample scene of sample object
Information and the corresponding fault message label of the sample object；
Training unit obtains corresponding for exporting the sample object for being trained to the sample training collection
The fault identification model of fault identification result.
Fig. 7 is the schematic diagram for the industry spot fault test set that one embodiment of the invention provides.As shown in fig. 7, the reality
The industry spot fault test set 7 for applying example includes: processor 70, memory 71 and is stored in the memory 71 and can
The computer program 72 run on the processor 70, such as industry spot fault detection program.The processor 70 executes
The step in above-mentioned each industry spot fault detection method embodiment is realized when the computer program 72, such as shown in Fig. 1
Step 101 to 102.Alternatively, the processor 70 is realized when executing the computer program 72 in above-mentioned each Installation practice
The function of each module/unit, such as the function of module 610 to 620 shown in Fig. 6.
Illustratively, the computer program 72 can be divided into one or more module/units, it is one or
Multiple module/units are stored in the memory 71, and are executed by the processor 70, to complete the present invention.Described one
A or multiple module/units can be the series of computation machine program instruction section that can complete specific function, which is used for
Implementation procedure of the computer program 72 in the industry spot fault test set 7 is described.For example, the computer journey
Sequence 72 can be divided into acquiring unit, processing unit, and each unit concrete function is as follows:
Acquiring unit, for obtaining the scene information of object to be detected；Wherein, the scene information for judge it is described to
The fault message of test object；The scene information includes environmental information and location information；
Processing unit is handled for the scene information to be input to preparatory trained Fault Model, is obtained
To the fault identification result of the object to be detected；Wherein, the fault identification result includes fault type and fault bit confidence
Breath；In the training process, sample scene information and the sample scene of the input of the Fault Model for sample object
Corresponding fault message label, the output of the Fault Model are the fault identification result of the sample object.
The industry spot fault test set may include, but be not limited only to, processor 60, memory 61.This field skill
Art personnel are appreciated that Fig. 7 is only the example of industry spot fault test set 6, do not constitute and examine to industry spot failure
The restriction of measurement equipment 7 may include perhaps combining certain components or different components than illustrating more or fewer components,
Such as the industry spot fault test set can also include input-output equipment, network access equipment, bus etc..
Alleged processor 70 can be central processing unit (Central Processing Unit, CPU), can also be
Other general processors, digital signal processor (Digital Signal Processor, DSP), specific integrated circuit
(Application Specific Integrated Circuit, ASIC), ready-made programmable gate array (Field-
Programmable Gate Array, FPGA) either other programmable logic device, discrete gate or transistor logic,
Discrete hardware components etc..General processor can be microprocessor or the processor is also possible to any conventional processor
Deng.
The memory 71 can be the internal storage unit of the industry spot fault test set 7, such as industry is now
The hard disk or memory of field fault test set 7.The memory 71 is also possible to the outer of the industry spot fault test set 7
The plug-in type hard disk being equipped in portion's storage equipment, such as the industry spot fault test set 7, intelligent memory card (Smart
Media Card, SMC), secure digital (Secure Digital, SD) card, flash card (Flash Card) etc..Further,
The memory 71 can also both including the industry spot fault test set 7 internal storage unit and also including external storage
Equipment.The memory 71 is for storing needed for the computer program and the industry spot fault test set other
Program and data.The memory 71 can be also used for temporarily storing the data that has exported or will export.
It is apparent to those skilled in the art that for convenience of description and succinctly, only with above-mentioned each function
Can unit, module division progress for example, in practical application, can according to need and by above-mentioned function distribution by different
Functional unit, module are completed, i.e., the internal structure of described device is divided into different functional unit or module, more than completing
The all or part of function of description.Each functional unit in embodiment, module can integrate in one processing unit, can also
To be that each unit physically exists alone, can also be integrated in one unit with two or more units, it is above-mentioned integrated
Unit both can take the form of hardware realization, can also realize in the form of software functional units.In addition, each function list
Member, the specific name of module are also only for convenience of distinguishing each other, the protection scope being not intended to limit this application.Above system
The specific work process of middle unit, module, can refer to corresponding processes in the foregoing method embodiment, and details are not described herein.
In the above-described embodiments, it all emphasizes particularly on different fields to the description of each embodiment, is not described in detail or remembers in some embodiment
The part of load may refer to the associated description of other embodiments.
Those of ordinary skill in the art may be aware that list described in conjunction with the examples disclosed in the embodiments of the present disclosure
Member and algorithm steps can be realized with the combination of electronic hardware or computer software and electronic hardware.These functions are actually
It is implemented in hardware or software, the specific application and design constraint depending on technical solution.Professional technician
Each specific application can be used different methods to achieve the described function, but this realization is it is not considered that exceed
The scope of the present invention.
In embodiment provided by the present invention, it should be understood that disclosed device/terminal device and method, it can be with
It realizes by another way.For example, device described above/terminal device embodiment is only schematical, for example, institute
The division of module or unit is stated, only a kind of logical function partition, there may be another division manner in actual implementation, such as
Multiple units or components can be combined or can be integrated into another system, or some features can be ignored or not executed.Separately
A bit, shown or discussed mutual coupling or direct-coupling or communication connection can be through some interfaces, device
Or the INDIRECT COUPLING or communication connection of unit, it can be electrical property, mechanical or other forms.
The unit as illustrated by the separation member may or may not be physically separated, aobvious as unit
The component shown may or may not be physical unit, it can and it is in one place, or may be distributed over multiple
In network unit.It can select some or all of unit therein according to the actual needs to realize the mesh of this embodiment scheme
's.
It, can also be in addition, the functional units in various embodiments of the present invention may be integrated into one processing unit
It is that each unit physically exists alone, can also be integrated in one unit with two or more units.Above-mentioned integrated list
Member both can take the form of hardware realization, can also realize in the form of software functional units.
If the integrated module/unit be realized in the form of SFU software functional unit and as independent product sale or
In use, can store in a computer readable storage medium.Based on this understanding, the present invention realizes above-mentioned implementation
All or part of the process in example method, can also instruct relevant hardware to complete, the meter by computer program
Calculation machine program can be stored in a computer readable storage medium, the computer program when being executed by processor, it can be achieved that on
The step of stating each embodiment of the method.Wherein, the computer program includes computer program code, the computer program
Code can be source code form, object identification code form, executable file or certain intermediate forms etc..Computer-readable Jie
Matter may include: can carry the computer program code any entity or device, recording medium, USB flash disk, mobile hard disk,
Magnetic disk, CD, computer storage, read-only memory (ROM, Read-Only Memory), random access memory (RAM,
Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium etc..It should be noted that described
The content that computer-readable medium includes can carry out increasing appropriate according to the requirement made laws in jurisdiction with patent practice
Subtract, such as does not include electric carrier signal and electricity according to legislation and patent practice, computer-readable medium in certain jurisdictions
Believe signal.
Embodiment described above is merely illustrative of the technical solution of the present invention, rather than its limitations；Although referring to aforementioned reality
Applying example, invention is explained in detail, those skilled in the art should understand that: it still can be to aforementioned each
Technical solution documented by embodiment is modified or equivalent replacement of some of the technical features；And these are modified
Or replacement, the spirit and scope for technical solution of various embodiments of the present invention that it does not separate the essence of the corresponding technical solution should all
It is included within protection scope of the present invention.
Claims (10)
1. a kind of industry spot fault detection method characterized by comprising
Obtain the scene information of object to be detected；Wherein, the scene information is used to judge the failure letter of the object to be detected
Breath；The scene information includes environmental information and location information；
The scene information is input to preparatory trained Fault Model to handle, obtains the object to be detected
Fault identification result；Wherein, the fault identification result includes fault type and fault location information；In the training process, institute
The input for stating Fault Model is the sample scene information and the corresponding fault message label of the sample scene of sample object,
The output of the Fault Model is the fault identification result of the sample object.
2. industry spot fault detection method as described in claim 1, which is characterized in that the field for obtaining object to be detected
Scape information, comprising:
The radio signal at scene to be detected is obtained, object and its identification information to be detected are identified based on the radio signal；
Obtain the environmental information of the object to be detected；
Obtain the location information of the object to be detected.
3. industry spot fault detection method as claimed in claim 2, which is characterized in that the environmental information includes sound audio
Rate information, intensity of sound information, vibrational waveform information and operational temperature information；
The environmental information for obtaining the object to be detected, comprising:
Obtain sound frequency information, intensity of sound information and the vibrational waveform information when object to be detected work；
The thermal infrared imagery for obtaining the object to be detected determines the object to be detected based on the thermal infrared imagery
Operational temperature information.
4. industry spot fault detection method as claimed in claim 2, which is characterized in that the scene information further includes described
The three-dimensional model information of object to be detected, the three-dimensional model information include the three-dimensional structure figure of the object to be detected
Picture, the industry spot fault detection method, further includes:
The two-dimensional image information and spatial parameter information of the object to be detected are obtained, based on the two-dimensional image information and described
Spatial parameter information determines the three-dimensional model information of the object to be detected.
5. industry spot fault detection method as described in claim 1, which is characterized in that described to input the scene information
It is handled to preparatory trained Fault Model, obtains the fault identification result of the object to be detected, comprising:
Identification information, default identification information based on the object to be detected and the corresponding pass between preset failure detection model
System, determines the corresponding target faults detection model of the object to be detected；
The scene information is input to the target faults detection model to handle, obtains the failure of the object to be detected
Recognition result.
6. industry spot fault detection method as described in any one in claim 1-5, which is characterized in that described by the field
Scape information input to preparatory trained Fault Model is handled, and the fault identification result of the object to be detected is obtained
Before, further includes:
Obtain sample training collection；The sample training collection includes that the sample scene information of sample object and the sample object correspond to
Fault message label；
The sample training collection is trained, the failure for exporting the corresponding fault identification result of the sample object is obtained
Identification model.
7. a kind of industry spot fault detection means characterized by comprising
Acquiring unit, for obtaining the scene information of object to be detected；Wherein, the scene information is described to be detected for judging
The fault message of object；The scene information includes environmental information and location information；
Processing unit handles for the scene information to be input to preparatory trained Fault Model, obtains institute
State the fault identification result of object to be detected；Wherein, the fault identification result includes fault type and fault location information；In
In training process, the input of the Fault Model is corresponding for the sample scene information of sample object and the sample scene
Fault message label, the output of the Fault Model are the fault identification result of the sample object.
8. industry spot fault detection means as claimed in claim 7, the acquiring unit, comprising:
First acquisition unit is identified to be detected for obtaining the radio signal at scene to be detected based on the radio signal
Object and its identification information；
Second acquisition unit, for obtaining the environmental information of the object to be detected；
Third acquiring unit, for obtaining the location information of the object to be detected.
9. a kind of industry spot fault test set, including memory, processor and storage are in the memory and can be
The computer program run on the processor, which is characterized in that the processor is realized such as when executing the computer program
The step of any one of claim 1 to 6 the method.
10. a kind of computer readable storage medium, the computer-readable recording medium storage has computer program, and feature exists
In when the computer program is executed by processor the step of any one of such as claim 1 to 7 of realization the method.
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| CN111144325A (en) * | 2019-12-28 | 2020-05-12 | 广东电网有限责任公司 | Fault identification and positioning method, device and equipment for power equipment of transformer substation |
| CN112001700A (en) * | 2020-08-21 | 2020-11-27 | 金钱猫科技股份有限公司 | Engineering inspection method based on big data automatic comparison and server |
| CN112204547A (en) * | 2020-05-26 | 2021-01-08 | 深圳市智物联网络有限公司 | Data processing method, device and equipment based on industrial object model |
| CN112714284A (en) * | 2020-12-22 | 2021-04-27 | 全球能源互联网研究院有限公司 | Power equipment detection method and device and mobile terminal |
| CN112907114A (en) * | 2021-03-18 | 2021-06-04 | 三一重工股份有限公司 | Oil leakage fault detection method and device, electronic equipment and storage medium |
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Application publication date: 20191119 |