CN117030259A - Monitoring and early warning method, system, device and medium for vibration of rolling bearing - Google Patents

Monitoring and early warning method, system, device and medium for vibration of rolling bearing Download PDF

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Publication number
CN117030259A
CN117030259A CN202310848794.6A CN202310848794A CN117030259A CN 117030259 A CN117030259 A CN 117030259A CN 202310848794 A CN202310848794 A CN 202310848794A CN 117030259 A CN117030259 A CN 117030259A
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data
early warning
vibration
rolling bearing
monitoring
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马金
蔡泽校
鲁鑫钰
蒋易佐
李晨斯
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Guangzhou Hongke Electronic Technology Co ltd
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Guangzhou Hongke Electronic Technology Co ltd
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
    • G01M13/00—Testing of machine parts
    • G01M13/04—Bearings
    • G01M13/045—Acoustic or vibration analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/10—Pre-processing; Data cleansing
    • G06F18/15—Statistical pre-processing, e.g. techniques for normalisation or restoring missing data
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/22—Matching criteria, e.g. proximity measures
    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
    • G08B21/18—Status alarms
    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
    • G08B21/18—Status alarms
    • G08B21/182—Level alarms, e.g. alarms responsive to variables exceeding a threshold

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  • General Physics & Mathematics (AREA)
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  • Data Mining & Analysis (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Artificial Intelligence (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Life Sciences & Earth Sciences (AREA)
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  • General Engineering & Computer Science (AREA)
  • Business, Economics & Management (AREA)
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  • Acoustics & Sound (AREA)
  • Probability & Statistics with Applications (AREA)
  • Testing Of Devices, Machine Parts, Or Other Structures Thereof (AREA)

Abstract

The application discloses a monitoring and early warning method, a system, a device and a medium for vibration of a rolling bearing, wherein the monitoring and early warning method comprises the following steps: acquiring first data of the rolling bearing, wherein the first data comprises vibration data and scalar data; preprocessing the first data to obtain second data, and extracting salient feature data of the second data; determining a diagnosis result according to the significant feature data and the prediction model, and sending the diagnosis result and the scalar data to an early warning module so that the early warning module displays the diagnosis result and the scalar data and sends out a corresponding early warning notice; the diagnostic result includes a number of fault levels. The embodiment of the application realizes intelligent fault diagnosis of the rolling bearing, gives early warning aiming at different fault diversification, and jointly visualizes the diagnosis result and scalar data, improves the efficiency of equipment monitoring and fault maintenance, and can be widely applied to the field of equipment monitoring.

Description

Monitoring and early warning method, system, device and medium for vibration of rolling bearing
Technical Field
The application relates to the field of equipment monitoring, in particular to a method, a system, a device and a medium for monitoring and early warning vibration of a rolling bearing.
Background
The rolling bearing is used as a key component of the rotary equipment, and the load operation of the equipment mainly depends on the action of the rolling bearing, so that the vibration of the machine mainly occurs from the bearing, and the abnormal vibration directly affects the operation state of the whole equipment.
Vibration sensors are typically installed at bearings to monitor equipment failure conditions, such as bearing failure, loss of lubrication, shaft misalignment, imbalance, etc. However, the occurrence time and the severity of the fault can correspond to different priorities, the existing bearing vibration monitoring system adopts a fixed early warning mode, the alarm triggering mode is single, the alarm can not be sent as required, and the user can not be reminded according to the priority of the fault, so that the reliability in the aspect of timely processing the fault is insufficient; in addition, the function of commonly managing the device data and status and the fault diagnosis result is not provided.
Disclosure of Invention
In view of the above, an object of the embodiments of the present application is to provide a method, a system, a device, and a medium for monitoring and early warning of rolling bearing vibration, which implement a function of reminding a user according to a fault level and sending an alarm as required, and implement common visualization of field data, a device state, and a fault diagnosis result of a device.
In a first aspect, an embodiment of the present application provides a method for monitoring and early warning vibration of a rolling bearing, including the following steps:
acquiring first data of the rolling bearing, wherein the first data comprises vibration data and scalar data;
preprocessing the first data to obtain second data, and extracting salient feature data of the second data;
determining a diagnosis result according to the significant characteristic data and the prediction model, and sending the diagnosis result and scalar data to the early warning module so that the early warning module displays the diagnosis result and scalar data and sends out corresponding early warning notification; the diagnostic result includes several fault levels.
Optionally, preprocessing the first data to obtain second data, which specifically includes:
and performing data cleaning and data screening on the first data to obtain second data.
Optionally, extracting salient feature data of the second data specifically includes:
extracting salient feature data of the second data by performing spectrum screening on the second data; the salient feature data includes vibration feature data of the rolling bearing.
Optionally, determining the diagnosis result according to the salient feature data and the prediction model specifically includes:
matching the significant feature data with feature data in the prediction model to obtain a fault type;
determining a corresponding fault level according to the fault type to determine a diagnosis result; the failure level includes any one of extreme, severe, moderate, mild or good.
Optionally, the corresponding pre-warning notification is sent out by the following steps:
according to different fault grades, different modes are set to send out early warning notices;
and/or determining different modes to send out early warning notification according to scalar data and a preset trigger threshold; the preset trigger threshold comprises a warning value and a critical value;
and/or, determining different modes according to preset parameters to send out early warning notification; the preset parameters comprise a time table and a notification receiving object;
the mode of sending out the early warning notification comprises any one of a short message, an email, a VoIP voice, a VoIP text message, a fax or a desktop sound alarm.
Optionally, the early warning module displays the diagnosis result and scalar data, specifically including:
simultaneously displaying the diagnosis result and scalar data on the same interface; the interface also comprises a structural relation diagram of each device in the monitoring and early warning system, and the diagnosis results and the display areas of the scalar data are respectively arranged at the corresponding positions of the corresponding devices.
In a second aspect, an embodiment of the present application provides a monitoring and early warning system for vibration of a rolling bearing, including:
a first module for acquiring first data of the rolling bearing, the first data including vibration data and scalar data;
the second module is used for preprocessing the first data to obtain second data and extracting the salient feature data of the second data;
the third module is used for determining a diagnosis result according to the significant feature data and the prediction model, and sending the diagnosis result and scalar data to the early warning module so that the early warning module displays the diagnosis result and scalar data and sends out corresponding early warning notification; the diagnostic result includes several fault levels.
In a third aspect, an embodiment of the present application provides a monitoring and early warning device for rolling bearing vibration, including:
at least one processor;
at least one memory for storing at least one program;
the at least one program, when executed by the at least one processor, causes the at least one processor to implement the method as described above.
In a fourth aspect, embodiments of the present application provide a computer readable storage medium in which a processor executable program is stored, characterized in that the processor executable program is for performing the method as described above when being executed by a processor.
In a fifth aspect, an embodiment of the present application provides a system for monitoring and early warning vibration of a rolling bearing, which is characterized by comprising a vibration sensing module, a data gateway, a diagnostic platform and an early warning platform, wherein,
the vibration sensing module is used for collecting first data of the rolling bearing and transmitting the first data to the diagnosis platform through the data gateway; the first data includes vibration data and scalar data;
the diagnostic platform comprises:
at least one processor;
at least one memory for storing at least one program;
when the at least one program is executed by the at least one processor, the at least one processor is caused to implement the method as described above;
and the early warning platform is used for displaying the diagnosis result and scalar data and sending out corresponding early warning notification.
The embodiment of the application has the following beneficial effects: in the monitoring and early warning method provided by the embodiment, the rolling bearing is diagnosed according to the significant characteristic data and the prediction model, the diagnosis result is determined, the diagnosis result comprises a plurality of fault levels, and intelligent fault diagnosis of the rolling bearing is realized; the diagnosis result is sent to the early warning module so that the early warning module sends an early warning notice, the early warning mode can be selected according to the fault grade or the requirement, timely and effective early warning is realized, and the timeliness of equipment fault maintenance is improved; and enabling a common visualization of the diagnostic result and the scalar data.
Drawings
Fig. 1 is a schematic step flow diagram of a method for monitoring and early warning vibration of a rolling bearing according to an embodiment of the present application;
FIG. 2 is a schematic flow chart of steps of a fault diagnosis method for vibration of a rolling bearing according to an embodiment of the present application;
fig. 3 is an interface schematic diagram of different early warning notification modes in a rolling bearing vibration monitoring and early warning system provided by the embodiment of the application;
FIG. 4 is a schematic diagram of a setting interface for setting an early warning notification mode according to a schedule according to an embodiment of the present application;
fig. 5 is a schematic diagram of a display screen of an early warning platform in a rolling bearing vibration monitoring and early warning system according to an embodiment of the present application;
fig. 6 is a schematic structural diagram of a monitoring and early warning system for vibration of a rolling bearing according to an embodiment of the present application;
fig. 7 is a schematic structural diagram of a device for monitoring and early warning vibration of a rolling bearing according to an embodiment of the present application;
fig. 8 is a schematic structural diagram of another monitoring and early warning system for vibration of a rolling bearing according to an embodiment of the present application.
Detailed Description
The application will now be described in further detail with reference to the drawings and to specific examples. The step numbers in the following embodiments are set for convenience of illustration only, and the order between the steps is not limited in any way, and the execution order of the steps in the embodiments may be adaptively adjusted according to the understanding of those skilled in the art.
In the following description, reference is made to "some embodiments" which describe a subset of all possible embodiments, but it is to be understood that "some embodiments" can be the same subset or different subsets of all possible embodiments and can be combined with one another without conflict.
In the following description, the terms "first", "second", "third" and the like are merely used to distinguish similar objects and do not represent a specific ordering of the objects, it being understood that the "first", "second", "third" may be interchanged with a specific order or sequence, as permitted, to enable embodiments of the application described herein to be practiced otherwise than as illustrated or described herein.
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 in the embodiments of the application is for the purpose of describing embodiments of the application only and is not intended to be limiting of the application.
Before describing embodiments of the present application in further detail, the terms and terminology involved in the embodiments of the present application will be described, and the terms and terminology involved in the embodiments of the present application will be used in the following explanation.
As shown in fig. 1, the embodiment of the application provides a method for monitoring and early warning vibration of a rolling bearing, which comprises the following steps:
s100, acquiring first data of the rolling bearing, wherein the first data comprises vibration data and scalar data.
In particular, the vibration data includes vibration information of the axial, radial and tangential directions of the rolling bearing. Scalar data includes, but is not limited to, any one or more of temperature, speed, or acceleration of the rolling bearing. The scalar data acquisition mode is determined according to practical situations, and the embodiment of the application is not limited and only specific embodiments are provided for reference. For example, scalar data may be acquired by the sensing device once an hour.
S200, preprocessing the first data to obtain second data, and extracting salient feature data of the second data.
Specifically, the first data further comprises noise and interference factors, the first data is preprocessed to remove the noise and interference factors, and the data processing amount is reduced, so that the salient feature data of the second data are better extracted, and the accuracy of fault diagnosis is improved.
S300, determining a diagnosis result according to the significant feature data and the prediction model, and sending the diagnosis result and scalar data to an early warning module so that the early warning module displays the diagnosis result and scalar data and sends out a corresponding early warning notice; the diagnostic result includes several fault levels.
Specifically, the prediction model includes a plurality of fault types of the rolling bearing, and the fault types are used for matching with the salient feature data, so that the fault types are obtained and are classified into a plurality of fault levels according to severity and emergency degree.
Specifically, the early warning module may include a SCADA (Supervisory Control And Data Acquisition) platform; the early warning module may send early warning notifications in several different ways and visualize the diagnostic results and scalar data. Specifically, trigger thresholds of scalar data corresponding to different devices can be preset according to the different devices; and comparing the scalar data obtained each time with a trigger threshold, and when the scalar data exceeds the trigger threshold, triggering the early warning module to send out a corresponding early warning notice.
Specifically, the method for monitoring and early warning the vibration of the rolling bearing in the embodiment of the application can be realized through an artificial intelligent algorithm or a machine learning method.
Optionally, preprocessing the first data to obtain second data, which specifically includes:
and S210, performing data cleaning and data screening on the first data to obtain second data.
Specifically, performing data cleansing and data screening on the first data includes: any one of filtering, trending, noise reduction, and the like is performed on the first data.
Optionally, extracting salient feature data of the second data specifically includes:
s220, extracting salient feature data of the second data by performing spectrum screening on the second data; the salient feature data includes vibration feature data of the rolling bearing.
In particular, spectrum screening may be performed by a spectrum screening module; the extracted salient feature data of the second data may be used to evaluate the equipment condition.
Optionally, determining the diagnosis result according to the salient feature data and the prediction model specifically includes:
s310, matching the significant feature data with feature data in a prediction model to obtain a fault type;
s320, determining a corresponding fault level according to the fault type so as to determine a diagnosis result; the failure level includes any one of extreme, severe, moderate, mild or good.
Specifically, the salient feature data are matched with feature data in the prediction model according to a preset diagnosis rule, and a diagnosis result is determined.
Specifically, the prediction model includes a fault type library, where the fault type library includes more than 1200 fault types, and the fault types include, but are not limited to, any one of bearing wear, shaft misalignment, shaft imbalance, bearing looseness, and the like, and each fault type has respective corresponding feature data.
Specifically, the salient feature data is matched with the feature data in the prediction model, and when the value of the salient feature data reaches the value of the feature data corresponding to the fault type, the corresponding fault type is obtained.
In particular, the diagnostic process also includes determining a fault type in combination with the device type and a particular fault type for the particular device type.
Specifically, different fault types correspond to different fault levels, and the monitoring and early warning system in the embodiment of the application automatically identifies the corresponding fault levels according to the fault types.
In particular, the diagnosed fault level may be modified manually.
As shown in fig. 2, an embodiment of the present application provides a fault diagnosis method for vibration of a rolling bearing, which specifically includes:
collecting vibration signals of the rolling bearing;
preprocessing the obtained data, wherein the preprocessing comprises any one of filtering, trending or noise reduction;
performing spectrum analysis on the preprocessed data; performing feature extraction on the preprocessed data through spectrum analysis;
and inputting the extracted features into a diagnosis rule base for evaluation to obtain a diagnosis result.
Optionally, the corresponding pre-warning notification is sent out by the following steps:
s330, setting different modes to send out early warning notification according to different fault grades.
As shown in fig. 3, the mode of sending out the early warning notification includes any one of a short message, an email, a VoIP voice, a VoIP text message, a fax or a desktop sound alarm.
Specifically, according to different fault levels, different modes are set to send out early warning notification, including:
the fault with the extreme fault grade adopts a VoIP voice telephone mode to send out an early warning notice;
the fault grade is that serious faults send out early warning notice by adopting a mode of sending short messages;
faults with a mild, slight or good fault level can be sent out to give out early warning notification by adopting any mode of sending email, voIP text message, fax or desktop sound alarm respectively.
S340, and/or determining different modes to send out early warning notification according to scalar data and a preset trigger threshold; the preset trigger threshold includes a warning value and a critical value.
Specifically, different modes are determined according to scalar data and a preset trigger threshold to send out early warning notification; the preset trigger threshold includes a warning value and a critical value, including:
setting a trigger threshold of scalar data, wherein the trigger threshold comprises a warning value and a critical value;
comparing the obtained scalar data with a trigger threshold value, and sending an early warning notice in a mode of sending a text message notice when the trigger threshold value reaches a warning value, wherein the text message notice comprises any one of a short message, an electronic mail, a VoIP text message or a fax; when the trigger threshold reaches a critical value, a telephone or voice mode is adopted to send out an early warning notice, and the telephone or voice comprises any one of VoIP voice and desktop sound alarm.
S350, and/or sending out early warning notices according to different modes determined by preset parameters; the preset parameters include a schedule and a notification reception object.
Specifically, as shown in fig. 4, determining different modes according to a preset schedule to send out early warning notification includes: different time periods are selected to send out the early warning notification in different manners, and the embodiment of the present application is not limited, and only specific embodiments are provided for reference, for example:
for daytime of working days, sending out an early warning notice in a VoIP voice mode;
and/or, for the evening of the working day, sending out an early warning notice in a mode of sending VoIP text information;
and/or, for holidays, sending out early warning notification by adopting a mode of sending short messages or emails;
and/or sending out early warning notification according to different modes of calendar setting.
Specifically, the early warning notification is sent out according to different modes determined by a preset notification receiving object, wherein the notification receiving object comprises any one of management personnel, engineers or operators; for selecting different manners for sending out the early warning notification according to different notification receiving objects, the embodiment of the present application is not limited, and only specific embodiments are provided for reference, for example:
for an operator, sending out an early warning notice in a VoIP voice or desktop sound alarm mode;
for engineers, sending out early warning notification by adopting a mode of sending short messages;
for the manager, an early warning notice is sent by adopting a mail generation mode.
Optionally, the early warning module displays the diagnosis result and scalar data, specifically including:
simultaneously displaying the diagnosis result and scalar data on the same interface; the interface also comprises a structural relation diagram of each device in the monitoring and early warning system, and the diagnosis results and the display areas of the scalar data are respectively arranged at the corresponding positions of the corresponding devices.
Specifically, the diagnosis results also include vibration monitoring results, and the interface may display detailed data of vibration.
Specifically, as shown in fig. 5, the structural relationship diagram of each device in the monitoring and early warning system can be understood as a field working condition picture, where the field working condition picture includes a schematic diagram of each device in the monitoring and early warning system, a connection structure between the schematic diagrams and an operation state of the field device.
Specifically, the display areas of the diagnosis result and the scalar data are respectively provided at the corresponding positions of the corresponding devices, and may include: and setting a corresponding display device nearby the device to display the diagnosis result and scalar data corresponding to the device.
The embodiment of the application has the following beneficial effects: in the monitoring and early warning method provided by the embodiment, the sensing equipment and the data gateway are respectively provided with the respective specific serial numbers, so that the reliability and high safety of data transmission are ensured; according to the significant characteristic data and the prediction model, the rolling bearing is diagnosed, a diagnosis result is determined, the diagnosis result comprises a plurality of fault levels, and intelligent fault diagnosis of the rolling bearing is realized; the fault level can be modified manually, so that an analyst can judge the fault by combining own expertise and experience, and the accuracy and flexibility of fault diagnosis are improved; sending the diagnosis result to an early warning module so as to send an early warning notice, wherein the early warning mode can be selected according to the degree of urgency of the fault level; or, setting different early warning modes according to a preset time table; or, different early warning modes are set according to the preset notification receiving object, so that timely and effective early warning is realized, the timeliness of equipment fault maintenance and the flexibility of sending early warning notification are improved, the fault risk is reduced, and the time for equipment shutdown and damage is reduced; the diagnosis result and scalar data are displayed in the same interface, so that a user can conveniently and intuitively check and compare the data, and the efficiency of monitoring and maintaining faults of the equipment is improved.
As shown in fig. 6, an embodiment of the present application provides a monitoring and early warning system for vibration of a rolling bearing, including:
a first module for acquiring first data of the rolling bearing, the first data including vibration data and scalar data;
the second module is used for preprocessing the first data to obtain second data and extracting the salient feature data of the second data;
the third module is used for determining a diagnosis result according to the significant feature data and the prediction model, and sending the diagnosis result and scalar data to the early warning module so that the early warning module displays the diagnosis result and scalar data and sends out corresponding early warning notification; the diagnostic result includes several fault levels.
It can be seen that the content in the above method embodiment is applicable to the system embodiment, and the functions specifically implemented by the system embodiment are the same as those of the method embodiment, and the beneficial effects achieved by the method embodiment are the same as those achieved by the method embodiment.
As shown in fig. 7, an embodiment of the present application provides a monitoring and early warning device for rolling bearing vibration, including:
at least one processor;
at least one memory for storing at least one program;
the at least one program, when executed by the at least one processor, causes the at least one processor to implement the method as described above.
Wherein the memory is operable as a non-transitory computer readable storage medium storing a non-transitory software program and a non-transitory computer executable program. The memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, the memory optionally includes remote memory provided remotely from the processor, the remote memory being connectable to the processor through a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
It can be seen that the content in the above method embodiment is applicable to the embodiment of the present device, and the functions specifically implemented by the embodiment of the present device are the same as those of the embodiment of the above method, and the beneficial effects achieved by the embodiment of the above method are the same as those achieved by the embodiment of the above method.
An embodiment of the present application provides a computer-readable storage medium in which a processor-executable program is stored, characterized in that the processor-executable program is for performing the method as described above when being executed by a processor.
It is to be understood that all or some of the steps, systems, and methods disclosed above may be implemented in software, firmware, hardware, and suitable combinations thereof. Some or all of the physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on computer readable media, which may include computer storage media (or non-transitory media) and communication media (or transitory media). The term computer storage media includes both volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data, as known to those skilled in the art. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by a computer. Furthermore, as is well known to those of ordinary skill in the art, communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media.
As shown in fig. 8, the embodiment of the application provides a monitoring and early warning system for vibration of a rolling bearing, which is characterized by comprising a vibration sensing module, a data gateway, a diagnosis platform and an early warning platform, wherein,
the vibration sensing module is used for collecting first data of the rolling bearing and transmitting the first data to the diagnosis platform through the data gateway; the first data includes vibration data and scalar data;
the diagnostic platform comprises:
at least one processor;
at least one memory for storing at least one program;
when the at least one program is executed by the at least one processor, the at least one processor is caused to implement the method as described above;
and the early warning platform is used for displaying the diagnosis result and scalar data and sending out corresponding early warning notification.
Specifically, the vibration sensing module includes a sensing device, and the specific sensing device is determined according to actual situations, which is not limited in the embodiments of the present application, and only specific embodiments are provided for reference. For example, the vibration sensing module includes a wireless three-axis temperature vibration sensor that may be disposed at a rolling bearing of the apparatus, monitor vibration data of the rolling bearing in axial, radial and tangential directions, and surface temperature of the apparatus.
Specifically, after the wireless three-axis temperature vibration sensor is started, any gateway nearby can be automatically identified and connected with the wireless three-axis temperature vibration sensor; the wireless three-axis temperature vibration sensor can transmit first data to the data gateway in a wireless mesh ad hoc network mode.
Specifically, the data gateway transmits the first data to a network where the diagnostic platform relies primarily on the equipment site; the networks in the field include WIFI, ethernet and carrier networks.
Specifically, the sensing device and the data gateway are respectively provided with respective specific serial numbers.
Specifically, the early warning platform may include a SCADA platform, and the diagnostic platform transmits data to the SCADA platform through a API (Application Programming Interface) interface.
It can be seen that the content in the above method embodiment is applicable to the system embodiment, and the functions specifically implemented by the system embodiment are the same as those of the method embodiment, and the beneficial effects achieved by the method embodiment are the same as those achieved by the method embodiment.
While the preferred embodiment of the present application has been described in detail, the application is not limited to the embodiment, and various equivalent modifications and substitutions can be made by those skilled in the art without departing from the spirit of the application, and these equivalent modifications and substitutions are intended to be included in the scope of the present application as defined in the appended claims.

Claims (10)

1. The monitoring and early warning method for the vibration of the rolling bearing is characterized by comprising the following steps of:
acquiring first data of the rolling bearing, wherein the first data comprises vibration data and scalar data;
preprocessing the first data to obtain second data, and extracting salient feature data of the second data;
determining a diagnosis result according to the significant feature data and the prediction model, and sending the diagnosis result and the scalar data to an early warning module so that the early warning module displays the diagnosis result and the scalar data and sends out a corresponding early warning notice; the diagnostic result includes a number of fault levels.
2. The method for monitoring and pre-warning vibration of a rolling bearing according to claim 1, wherein the preprocessing the first data to obtain second data specifically comprises:
and carrying out data cleaning and data screening on the first data to obtain second data.
3. The method for monitoring and pre-warning vibration of a rolling bearing according to claim 1, wherein the extracting the salient feature data of the second data specifically comprises:
extracting salient feature data of the second data by performing spectrum screening on the second data; the salient feature data includes vibration feature data of the rolling bearing.
4. The method for monitoring and early warning vibration of a rolling bearing according to claim 1, wherein the determining a diagnosis result according to the salient feature data and the predictive model specifically comprises:
matching the significant feature data with feature data in the prediction model to obtain a fault type;
determining a corresponding fault level according to the fault type to determine a diagnosis result; the failure level includes any one of extreme, severe, mild, slight, or good.
5. The method for monitoring and warning vibration of a rolling bearing according to claim 1, characterized in that the corresponding warning notification is issued by:
according to different fault grades, different modes are set to send out early warning notices;
and/or determining different modes to send out early warning notification according to the scalar data and a preset trigger threshold; the preset trigger threshold comprises a warning value and a critical value;
and/or, determining different modes according to preset parameters to send out early warning notification; the preset parameters comprise a time table and a notification receiving object;
the mode of sending out the early warning notification comprises any one of a short message, an email, a VoIP voice, a VoIP text message, a fax or a desktop sound alarm.
6. The method for monitoring and pre-warning vibration of a rolling bearing according to claim 1, wherein the pre-warning module displays the diagnosis result and the scalar data, and specifically comprises:
simultaneously displaying the diagnostic result and the scalar data on the same interface; the interface also comprises a structural relation diagram of each device in the monitoring and early warning system, and the diagnosis result and the display area of the scalar data are respectively arranged at the corresponding positions of the corresponding devices.
7. A monitoring and early warning system for vibration of a rolling bearing is characterized by comprising:
a first module for acquiring first data of the rolling bearing, the first data including vibration data and scalar data;
the second module is used for preprocessing the first data to obtain second data and extracting salient feature data of the second data;
the third module is used for determining a diagnosis result according to the significant feature data and the prediction model, and sending the diagnosis result and the scalar data to the early warning module so that the early warning module displays the diagnosis result and the scalar data and sends out a corresponding early warning notice; the diagnostic result includes a number of fault levels.
8. The utility model provides a antifriction bearing vibration's monitoring early warning device which characterized in that includes:
at least one processor;
at least one memory for storing at least one program;
the at least one program, when executed by the at least one processor, causes the at least one processor to implement the method of any of claims 1-6.
9. A computer readable storage medium, in which a processor executable program is stored, characterized in that the processor executable program is for performing the method according to any of claims 1-6 when being executed by a processor.
10. A monitoring and early warning system for vibration of a rolling bearing is characterized by comprising a vibration sensing module, a data gateway, a diagnosis platform and an early warning platform, wherein,
the vibration sensing module is used for collecting first data of the rolling bearing and transmitting the first data to the diagnosis platform through the data gateway; the first data includes vibration data and scalar data;
the diagnostic platform comprises:
at least one processor;
at least one memory for storing at least one program;
when the at least one program is executed by the at least one processor, the at least one processor is caused to implement the method of any one of claims 1-6;
the early warning platform is used for displaying the diagnosis result and the scalar data and sending out corresponding early warning notification.
CN202310848794.6A 2023-07-11 2023-07-11 Monitoring and early warning method, system, device and medium for vibration of rolling bearing Pending CN117030259A (en)

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CN202310848794.6A CN117030259A (en) 2023-07-11 2023-07-11 Monitoring and early warning method, system, device and medium for vibration of rolling bearing

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CN202310848794.6A CN117030259A (en) 2023-07-11 2023-07-11 Monitoring and early warning method, system, device and medium for vibration of rolling bearing

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CN117030259A true CN117030259A (en) 2023-11-10

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