CN112803369A - Intelligent operation method and device of efficient motor - Google Patents
Intelligent operation method and device of efficient motor Download PDFInfo
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- CN112803369A CN112803369A CN202011619503.9A CN202011619503A CN112803369A CN 112803369 A CN112803369 A CN 112803369A CN 202011619503 A CN202011619503 A CN 202011619503A CN 112803369 A CN112803369 A CN 112803369A
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02H—EMERGENCY PROTECTIVE CIRCUIT ARRANGEMENTS
- H02H7/00—Emergency protective circuit arrangements specially adapted for specific types of electric machines or apparatus or for sectionalised protection of cable or line systems, and effecting automatic switching in the event of an undesired change from normal working conditions
- H02H7/08—Emergency protective circuit arrangements specially adapted for specific types of electric machines or apparatus or for sectionalised protection of cable or line systems, and effecting automatic switching in the event of an undesired change from normal working conditions for dynamo-electric motors
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- 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
- G08B21/185—Electrical failure alarms
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- 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
- G08B21/24—Reminder alarms, e.g. anti-loss alarms
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Abstract
The invention discloses an intelligent operation method and an intelligent operation device for a high-efficiency motor, wherein the method comprises the following steps: obtaining a first amplitude of the first bearing; obtaining a second amplitude of the second bearing; obtaining an amplitude difference from the first amplitude and the second amplitude, wherein the first amplitude is greater than the second amplitude; determining whether the amplitude difference is within a predetermined amplitude threshold; obtaining a first position if the amplitude difference is not within the predetermined amplitude threshold, the first position being a position of a first bearing; inputting the amplitude difference and the first position into a neural network model to obtain first fault information; acquiring first reminding information according to the first fault information; and reminding the first motor of the fault according to the first reminding information. The technical problem that the motor is damaged more due to the fact that the motor fault is not found in time and the motor is overhauled in time is solved.
Description
Technical Field
The invention relates to the technical field of motor operation, in particular to an intelligent operation method and device of a high-efficiency motor.
Background
At present, electromechanical equipment and technologies of a power plant are not newly improved, in order to guarantee safe production and enhance management and maintenance of motor equipment in enterprises, every enterprise needs to make good, and maintenance and technology of electromechanical equipment need to be improved if feet are stable when the enterprise stands in a market with huge competitiveness.
However, in the process of implementing the technical solution of the invention in the embodiments of the present application, the inventors of the present application find that the above-mentioned technology has at least the following technical problems:
because in the working process of the motor, the motor fault is not found in time and the motor is overhauled in time, the motor is damaged more.
Disclosure of Invention
The embodiment of the application provides an intelligent operation method and device of a high-efficiency motor, solves the technical problem that the motor is damaged more because the motor fault is not found in time and is overhauled in time, and achieves the purpose of timely monitoring various working parameters and performances of the motor during working, so that the abnormal conditions of the motor during working are found in time, the fault finding and overhauling are facilitated, the motor is prevented from being damaged more, and the intelligent and stable operation technical effect of the motor is ensured.
The embodiment of the application provides an intelligent operation method of a high-efficiency motor, wherein the method is applied to an intelligent operation device of the high-efficiency motor, the device comprises an image acquisition device, and the method comprises the following steps: obtaining a first amplitude of the first bearing; obtaining a second amplitude of the second bearing; obtaining an amplitude difference from the first amplitude and the second amplitude, wherein the first amplitude is greater than the second amplitude; determining whether the amplitude difference is within a predetermined amplitude threshold; obtaining a first position if the amplitude difference is not within the predetermined amplitude threshold, the first position being a position of a first bearing; inputting the amplitude difference and the first position into a neural network model to obtain first fault information; acquiring first reminding information according to the first fault information; and reminding the first motor of the fault according to the first reminding information.
On the other hand, this application still provides an intelligent operation device of high-efficient motor, wherein, the device includes: a first obtaining unit: the first obtaining unit is used for obtaining a first amplitude of the first bearing; a second obtaining unit: the second obtaining unit is used for obtaining a second amplitude of the second bearing; a third obtaining unit: the third obtaining unit is configured to obtain an amplitude difference according to the first amplitude and the second amplitude, where the first amplitude is greater than the second amplitude; a first judgment unit: the first judging unit is used for judging whether the amplitude difference is within a preset amplitude threshold value; a fourth obtaining unit: the fourth obtaining unit is used for obtaining a first position if the amplitude difference is not within the preset amplitude threshold value, wherein the first position is the position of the first bearing; a first input unit: the first input unit is used for inputting the amplitude difference and the first position into a neural network model to obtain first fault information; a fifth obtaining unit: the fifth obtaining unit is used for obtaining first reminding information according to the first fault information; the first reminding unit: the first reminding unit is used for reminding the first motor of a fault according to the first reminding information.
One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:
whether the motor breaks down or not is judged according to the amplitude difference and the position of the amplitude difference according to the different amplitudes of each bearing of the motor, so that the motor can be subjected to emergency braking processing when the motor breaks down, the motor fault can be further judged according to the vibration amplitude difference and the bearing position of the bearing, the technical effects that the judgment result is more accurate, and the efficient and intelligent operation of the motor is ensured are achieved.
The foregoing description is only an overview of the technical solutions of the present application, and the present application can be implemented according to the content of the description in order to make the technical means of the present application more clearly understood, and the following detailed description of the present application is given in order to make the above and other objects, features, and advantages of the present application more clearly understandable.
Drawings
Fig. 1 is a schematic flowchart of an intelligent operation method of a high-efficiency motor according to an embodiment of the present application;
fig. 2 is a schematic structural diagram of an intelligent operating system of a high-efficiency motor according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of an exemplary electronic device according to an embodiment of the present application.
Description of reference numerals: the device comprises a first obtaining unit 11, a second obtaining unit 12, a third obtaining unit 13, a first judging unit 14, a fourth obtaining unit 15, a first input unit 16, a fifth obtaining unit 17, a first reminding unit 18, a bus 300, a receiver 301, a processor 302, a transmitter 303, a memory 304 and a bus interface 305.
Detailed Description
The embodiment of the application provides an intelligent operation method and device of a high-efficiency motor, solves the technical problem that the motor is damaged more because the motor fault is not found in time and is overhauled in time, and achieves the purpose of timely monitoring various working parameters and performances of the motor during working, so that the abnormal conditions of the motor during working are found in time, the fault finding and overhauling are facilitated, the motor is prevented from being damaged more, and the intelligent and stable operation technical effect of the motor is ensured.
Hereinafter, example embodiments according to the present application will be described in detail with reference to the accompanying drawings. It should be apparent that the described embodiments are merely some embodiments of the present application and not all embodiments of the present application, and it should be understood that the present application is not limited to the example embodiments described herein.
Summary of the application
At present, electromechanical equipment and technologies of a power plant are not newly improved, in order to guarantee safe production and enhance management and maintenance of motor equipment in enterprises, every enterprise needs to make good, and maintenance and technology of electromechanical equipment need to be improved if feet are stable when the enterprise stands in a market with huge competitiveness. Because in the working process of the motor, the motor fault is not found in time and the motor is overhauled in time, the motor is damaged more.
In view of the above technical problems, the technical solution provided by the present application has the following general idea:
the embodiment of the application provides an intelligent operation method of a high-efficiency motor, wherein the method is applied to an intelligent operation device of the high-efficiency motor, the device comprises an image acquisition device, and the method comprises the following steps: obtaining a first amplitude of the first bearing; obtaining a second amplitude of the second bearing; obtaining an amplitude difference from the first amplitude and the second amplitude, wherein the first amplitude is greater than the second amplitude; determining whether the amplitude difference is within a predetermined amplitude threshold; obtaining a first position if the amplitude difference is not within the predetermined amplitude threshold, the first position being a position of a first bearing; inputting the amplitude difference and the first position into a neural network model to obtain first fault information; acquiring first reminding information according to the first fault information; and reminding the first motor of the fault according to the first reminding information.
For better understanding of the above technical solutions, the following detailed descriptions will be provided in conjunction with the drawings and the detailed description of the embodiments.
Example one
As shown in fig. 1, an embodiment of the present application provides an intelligent operation method for a high-efficiency motor, where the method is applied to an intelligent operation device for a high-efficiency motor, the device includes an image capture device, and the method includes:
step S100: obtaining a first amplitude of the first bearing;
step S200: obtaining a second amplitude of the second bearing;
specifically, an Electric machine (commonly called "motor") refers to an electromagnetic device that converts or transmits Electric energy according to the law of electromagnetic induction, and its main function is to generate driving torque as a power source for electrical appliances or various machines. The motor consists of a stator, a rotor, a bearing and other accessories. Among them, the Bearing (Bearing) is an important part in the modern mechanical equipment, and its main function is to support the mechanical rotating body, reduce the friction coefficient in its motion process, and ensure its rotation precision. Because a general motor is provided with two bearings, the vibration amplitude of the bearings can be analyzed, and then the motor is subjected to state monitoring and fault diagnosis, so that a fault part can be judged more accurately. First amplitudes of the first bearings can be obtained respectively, the first amplitudes are vibration amplitudes of the first bearings, and similarly, second amplitudes of the second bearings are obtained.
Step S300: obtaining an amplitude difference from the first amplitude and the second amplitude, wherein the first amplitude is greater than the second amplitude;
specifically, it is known to obtain the first amplitude and the second amplitude, and an amplitude difference may be obtained from the first amplitude and the second amplitude, wherein the first amplitude is larger than the second amplitude, and whether the motor has a failure may be monitored by obtaining the amplitude difference between the first amplitude and the second amplitude.
Step S400: determining whether the amplitude difference is within a predetermined amplitude threshold;
step S500: obtaining a first position if the amplitude difference is not within the predetermined amplitude threshold, the first position being a position of a first bearing;
specifically, it is known that the amplitude difference is obtained by determining whether the amplitude difference is within a predetermined amplitude threshold, where the predetermined amplitude threshold is a threshold range in which a preset allowable amplitude difference exists, if the amplitude difference exceeds the predetermined amplitude threshold, the motor is likely to malfunction, if the amplitude difference is not within the predetermined amplitude threshold, a first position is obtained, where the first position is a position of the first bearing, and a position of a malfunction point of the motor is determined by determining a position of the bearing in one step.
Step S600: inputting the amplitude difference and the first position into a neural network model to obtain first fault information;
specifically, knowing the amplitude difference and the first position, the amplitude difference and the first position can be input into a neural network model for training, the neural network model is a data training model, that is, input data is continuously trained, so that an output training result is more accurate, here, the amplitude difference and the first position are continuously trained, so that an output first fault phenomenon is more accurate, and the first fault information is fault information of the motor.
Step S700: acquiring first reminding information according to the first fault information;
step S800: and reminding the first motor of the fault according to the first reminding information.
Specifically, after the first fault information is obtained, first reminding information can be obtained, and the first reminding information is used for reminding relevant workers that the motor is in fault. The motor fault is accurately judged according to the amplitude difference and the bearing position of the bearing, so that the motor fault can be technically maintained, and the technical effect of avoiding greater damage to the motor is achieved.
Further, before obtaining the first amplitude of the first bearing, an embodiment of the present application further includes:
step S910: obtaining a first control instruction;
step S920: rotating a rotor of a first motor according to the first control instruction;
step S930: acquiring first video information according to the image acquisition device;
step S940: judging whether a rotor of the first motor starts to rotate or not according to the first video information;
step S950: after the rotor of the first motor starts to rotate, judging whether the rotor generates friction with the stator;
step S960: if the rotor and the stator do not generate friction, second reminding information is obtained;
step S970: and reminding the first motor of safe operation according to the second reminding information to obtain the first amplitude of the first bearing.
Specifically, before the first amplitude of the first bearing is obtained, whether the space between the stator and the rotor of the motor is normal or not may be determined. The stator is a static part of the motor and consists of a stator core, a stator winding and a machine base. The main function of the stator is to generate a rotating magnetic field, and the main function of the rotor is to be cut by magnetic lines of force in the rotating magnetic field to generate (output) current. The rotating body supported by the bearing is called a rotor, and the rotor is a main rotating part in power machines and working machines. Because there is no friction between the stator and the rotor of the motor, however, the old motor will rub due to the aging of the bearing, and this phenomenon is called the chamber sweeping. The friction can generate heat, so that the motor can be scrapped more quickly. Therefore, a first control instruction can be obtained first, the first control instruction is used for rotating the rotor of the first motor, and then according to the image acquisition device, first video information is obtained, the first video information is video information of the rotor of the first motor, whether the rotor of the first motor starts to rotate or not can be judged according to the first video information, after the rotor rotates, whether the rotor rubs with the stator or not can be judged, if the rotor rubs with the stator, the risk that the motor is scrapped is indicated, if the rotor does not rub with the stator, the motor works normally, second reminding information is obtained, the second reminding information is used for reminding relevant workers, the first motor can run safely, and then the first amplitude of the first bearing is obtained. Whether friction is generated between the stator and the rotor of the motor is monitored in real time according to the video information, and the technical effect of ensuring normal work of the motor is achieved.
Further, the inputting the amplitude difference and the first position into a neural network model to obtain first fault information, and the step S600 further includes:
step S610: inputting the amplitude difference and the first position into a neural network model, wherein the neural network model is obtained by training a plurality of sets of training data, and each set of the plurality of sets of training data comprises: the amplitude difference, the first location, and identification information identifying a first fault;
step S620: obtaining a first output result of the neural network model, the first output result including the first fault information.
Specifically, in order to obtain more accurate first fault information, the amplitude difference and the first position are input into the neural network model to be continuously trained, so that the output training result can be more accurate. The Neural network model is a data training model in machine learning, and Neural Networks (NN) are complex Neural network systems formed by widely interconnecting a large number of simple processing units (called neurons), reflect many basic features of human brain functions, and are highly complex nonlinear dynamical learning systems. Neural network models are described based on mathematical models of neurons. Artificial Neural Networks (Artificial Neural Networks) are a description of the first-order properties of the human brain system. Briefly, it is a mathematical model. In the embodiment of the application, the amplitude difference and the first position are input into a neural network model for continuous training, and the neural network model is trained by using the identified first fault information.
Further, the process of training the neural network model is substantially a process of supervised learning. The plurality of groups of training data are specifically: the amplitude difference, the first location, and identification information identifying a first fault. By inputting the amplitude difference and the first position, the neural network model outputs a first training result, the first training result is first fault information, the output information and the first fault information with the identification function are verified, if the output information is consistent with the first fault information with the identification function, the data supervised learning is finished, and then the next group of data supervised learning is carried out; and if the output information is inconsistent with the first fault information requirement playing the role of identification, the neural network learning model adjusts itself until the output result of the neural network learning model is consistent with the first fault information requirement playing the role of identification, and then the supervised learning of the next group of data is carried out. The neural network learning model is continuously corrected and optimized through training data, the accuracy of the neural network learning model in processing the information is improved through the process of supervised learning, and the technical effect that the first fault information is more accurate is achieved.
Further, the embodiment of the application further comprises:
step S1010: obtaining the overall vibration amplitude of the first motor;
step S1020: obtaining a predetermined vibration amplitude threshold value;
step S1030: and when the overall vibration amplitude exceeds the preset vibration amplitude threshold value, obtaining first recording information, wherein the first recording information is used for recording the overall vibration amplitude exceeding the preset vibration amplitude threshold value.
Specifically, in order to ensure that the motor works normally, the overall vibration amplitude of the first motor, that is, the overall amplitude of the motor during working, is obtained, and a predetermined vibration amplitude threshold is obtained at the same time, where the predetermined vibration amplitude threshold is a preset vibration amplitude of the motor during normal working, and the existing qualified standard of the motor vibration value is as follows: the rated rotation speed is less than 750r/min, and the vibration value of the bearing is not more than 0.12 mm; the bearing vibration value of the rotary machine with the rated rotating speed of 1000r/min is not more than 0.10 mm; the vibration value of the bearing does not exceed 0.085mm when the rotary machine is rotated at the rated rotating speed of 1500 r/min; the vibration value of the bearing does not exceed 0.05mm when the rotary machine is rotated at a rated rotating speed of 3000 r/min. The integral vibration amplitude of the first motor can be monitored in real time, and when the integral vibration amplitude exceeds the preset vibration amplitude threshold, first recorded information is obtained and used for recording the integral vibration amplitude exceeding the preset vibration amplitude threshold. By obtaining the integral vibration amplitude of the motor and comparing the integral vibration amplitude with a preset vibration amplitude threshold value, the technical effect of judging whether the motor works normally is achieved.
Further, after the obtaining the first record information, the embodiment of the present application further includes:
step S1040: obtaining the number of the first record information;
step S1050: obtaining a predetermined number threshold;
step S1060: when the number of the first record information exceeds the preset number threshold, obtaining third reminding information;
step S1070: and reminding the first motor of the fault according to the third reminding information.
Specifically, given the first recorded information, in order to accurately evaluate the determination result, the number of the first recorded information may also be obtained, that is, the number of times that the overall vibration amplitude exceeds the predetermined vibration amplitude threshold value, and meanwhile, a predetermined number threshold value is obtained, where the predetermined number threshold value is the maximum number of times that the overall vibration amplitude is allowed to exceed the predetermined vibration amplitude threshold value on the premise that the motor is ensured to normally operate, and if the overall vibration amplitude exceeds the predetermined vibration amplitude threshold value only in an emergency, the overall vibration amplitude is negligible, but if the overall vibration amplitude exceeds the predetermined vibration amplitude threshold value, the overall vibration amplitude exceeds the predetermined vibration amplitude threshold value once and once or once, the number of the first recorded information exceeds the predetermined number threshold value, that is, the first motor is likely to fail, and third reminding information is obtained, which is used for reminding relevant staff that the first motor fails, so.
Further, the embodiment of the application further comprises:
step S1110: judging whether the first bearing is a sliding bearing or not;
step S1120: obtaining a first predetermined temperature threshold if the first bearing is the plain bearing;
step S1130: obtaining a first temperature control instruction according to the first preset temperature threshold;
step S1140: and controlling the temperature of the first bearing not to exceed the first preset temperature threshold according to the first temperature control instruction.
Specifically, the normal operation of the motor can be ensured by controlling the working temperature, and the bearings can be divided into rolling (friction) bearings and sliding (friction) bearings according to different friction properties, obviously, the rolling bearing has smaller friction resistance, faster starting and higher efficiency than the sliding bearing, which is the advantage of the rolling bearing, and compared with the sliding bearing, the rolling bearing has larger radial dimension, poorer vibration damping capability, lower service life at high speed and larger sound, which is the defect of the rolling bearing, and the working temperatures of the rolling bearing and the sliding bearing are different. Whether the first bearing is a sliding bearing can be judged firstly, if so, a first preset temperature threshold value is obtained, the first preset temperature threshold value is a preset highest acceptable temperature value of the sliding bearing and generally does not exceed 80 ℃, and then a first temperature control instruction is obtained according to the first preset temperature threshold value, the first temperature control instruction is used for controlling the temperature of the first bearing not to exceed the first preset temperature threshold value 80 ℃, and the technical effect of ensuring the normal work of the motor is achieved by controlling the temperature of the sliding bearing to be within a normal working temperature.
Further, after judging whether the first bearing is a sliding bearing, the embodiment of the present application further includes:
step S1150: if the first bearing is a rolling bearing, obtaining a second predetermined temperature threshold;
step S1160: obtaining a second temperature control instruction according to the second preset temperature threshold;
step S1170: and controlling the temperature of the first bearing not to exceed the second preset temperature threshold according to the second temperature control instruction, wherein the maximum value of the first preset temperature threshold is smaller than the maximum value of the second preset temperature threshold.
Specifically, whether the first bearing is a sliding bearing is judged, if not, the first bearing is a rolling bearing, a second preset temperature threshold value is obtained, the second preset temperature threshold value is a preset highest acceptable temperature value of the rolling bearing and generally does not exceed 100 ℃, a second temperature control instruction is obtained according to the second preset temperature threshold value, the second temperature control instruction is used for controlling the temperature of the first bearing not to exceed the second preset temperature threshold value by 100 ℃, wherein the maximum value of the first preset temperature threshold value is smaller than the maximum value of the second preset temperature threshold value, namely the highest acceptable temperature value of 80 ℃ is lower than the highest acceptable temperature value of 100 ℃ of the rolling bearing, and the technical effect of ensuring the normal operation of the motor is achieved by controlling the temperature of the rolling bearing within a normal working temperature.
In order to ensure that the fault information of the first motor is safely recorded and stored, and the fault information can be encrypted based on a block chain, the embodiment of the present application further includes:
step 1210: generating a first verification code according to first fault information of the first motor, wherein the first verification code corresponds to the first fault information of the first motor one by one;
step S1220: generating a second verification code according to second fault information of the first motor, wherein the second verification code corresponds to the second fault information of the first motor one to one, and in the same way, generating an nth verification code according to the nth fault information of the first motor and an nth-1 verification code, wherein N is a natural number greater than 1;
step S1230: and respectively copying and storing all fault information and verification codes of the first motor on M devices, wherein M is a natural number greater than 1.
Specifically, in order to ensure that the failure information of the first motor is safely recorded and stored and is not tampered, an encryption operation based on a block chain can be performed. The block chain technology is a universal underlying technical framework, and can generate and synchronize data on distributed nodes through a consensus mechanism, and realize automatic execution and data operation of contract terms by means of programmable scripts. A block chain is defined as a data structure that organizes data blocks in time sequence, with chain-like connections being formed in order between different blocks, by means of which a digital ledger is built.
Generating a first verification code according to first fault information of the first motor, wherein the first verification code corresponds to the first fault information of the first motor one by one; generating a second verification code according to second fault information of the first motor, wherein the second verification code corresponds to the second fault information of the first motor one to one, and in the same way, generating an nth verification code according to the nth fault information of the first motor and an nth-1 verification code, wherein N is a natural number greater than 1; and respectively copying and storing all fault information and verification codes of the first motor on M devices, wherein M is a natural number greater than 1. And all fault information of the first motor is encrypted and stored, wherein each device corresponds to one node, all the nodes are combined to form a block chain, and the block chain forms a total account book which is convenient to verify (the Hash value of the last block is verified to be equivalent to the whole version), and cannot be changed (the Hash value of all the following blocks can be changed by changing any transaction information, so that the transaction information cannot pass the verification).
The block chain system adopts a distributed data form, each participating node can obtain a complete database backup, and unless 51% of nodes in the whole system can be controlled simultaneously, modification of the database by a single node is invalid, and data contents on other nodes cannot be influenced. Therefore, the more nodes participating in the system, the more powerful the computation, and the higher the data security in the system. The personal information of the first user is encrypted based on the block chain, so that the storage safety of the personal information of the first user is effectively ensured, and the technical effect of safely recording and storing the personal information of the first user is achieved.
To sum up, the intelligent operation method and device for the efficient motor provided by the embodiment of the application have the following technical effects:
1. whether the motor breaks down or not is judged according to the amplitude difference and the position of the amplitude difference according to the different amplitudes of each bearing of the motor, so that the motor can be subjected to emergency braking processing when the motor breaks down, the motor fault can be further judged according to the vibration amplitude difference and the bearing position of the bearing, the technical effects that the judgment result is more accurate, and the efficient and intelligent operation of the motor is ensured are achieved.
2. The technical effects of ensuring normal work of the motor and further improving the intelligent operation efficiency of the motor are achieved by ensuring that the rotor and the stator of the motor do not generate friction, the whole amplitude of the motor is in a normal amplitude interval value, and the sliding bearing and the rolling bearing of the motor are respectively in a normal working temperature.
Example two
Based on the same inventive concept as the intelligent operation method of the high-efficiency motor in the foregoing embodiment, the present invention further provides an intelligent operation device of the high-efficiency motor, as shown in fig. 2, the device includes:
the first obtaining unit 11: the first obtaining unit 11 is configured to obtain a first amplitude of the first bearing;
the second obtaining unit 12: the second obtaining unit 12 is configured to obtain a second amplitude of the second bearing;
the third obtaining unit 13: the third obtaining unit 13 is configured to obtain an amplitude difference according to the first amplitude and the second amplitude, where the first amplitude is greater than the second amplitude;
the first judgment unit 14: the first judging unit 14 is configured to judge whether the amplitude difference is within a predetermined amplitude threshold;
the fourth obtaining unit 15: the fourth obtaining unit 15 is configured to obtain a first position if the amplitude difference is not within the predetermined amplitude threshold, where the first position is a position of the first bearing;
the first input unit 16: the first input unit 16 is configured to input the amplitude difference and the first position into a neural network model, so as to obtain first fault information;
the fifth obtaining unit 17: the fifth obtaining unit 17 is configured to obtain first prompting information according to the first fault information;
the first reminder unit 18: the first reminding unit 18 is configured to remind the first motor of a fault according to the first reminding information.
Further, the system further comprises:
a sixth obtaining unit: the sixth obtaining unit is used for obtaining a first control instruction;
a first rotation unit: the first rotating unit is used for rotating a rotor of a first motor according to the first control instruction;
a seventh obtaining unit: the seventh obtaining unit is used for obtaining first video information according to the image acquisition device;
a second judgment unit: the second judging unit is used for judging whether the rotor of the first motor starts to rotate or not according to the first video information;
a third judging unit: the third judging unit is used for judging whether the rotor of the first motor generates friction with the stator after the rotor of the first motor starts to rotate;
an eighth obtaining unit: the eighth obtaining unit is used for obtaining second reminding information if the rotor and the stator do not generate friction;
the second reminding unit: the second reminding unit is used for reminding the first motor of running safely according to the second reminding information to obtain the first amplitude of the first bearing.
Further, the system further comprises:
a second input unit: the second input unit is configured to input the amplitude difference and the first position into a neural network model, where the neural network model is obtained by training multiple sets of training data, and each of the multiple sets of training data includes: the amplitude difference, the first location, and identification information identifying a first fault;
a ninth obtaining unit: the ninth obtaining unit is configured to obtain a first output result of the neural network model, where the first output result includes the first fault information.
Further, the system further comprises:
a tenth obtaining unit: the tenth obtaining unit is used for obtaining the overall vibration amplitude of the first motor;
an eleventh obtaining unit: the eleventh obtaining unit is configured to obtain a predetermined vibration amplitude threshold value;
a twelfth obtaining unit: the twelfth obtaining unit is configured to obtain first recording information when the overall vibration amplitude exceeds the predetermined vibration amplitude threshold, where the first recording information is used to record the overall vibration amplitude exceeding the predetermined vibration amplitude threshold.
Further, the system further comprises:
a thirteenth obtaining unit: the thirteenth obtaining unit is configured to obtain the number of the first recording information;
a fourteenth obtaining unit: the fourteenth obtaining unit is configured to obtain a predetermined number of thresholds;
a fifteenth obtaining unit: the fifteenth obtaining unit is configured to obtain third reminding information when the number of the first recorded information exceeds the predetermined number threshold;
a third reminding unit: and the third reminding unit is used for reminding the first motor of a fault according to the third reminding information.
Further, the system further comprises:
a fourth judging unit: the fourth judging unit is used for judging whether the first bearing is a sliding bearing;
a sixteenth obtaining unit: the sixteenth obtaining unit is configured to obtain a first predetermined temperature threshold if the first bearing is the sliding bearing;
a seventeenth obtaining unit: the seventeenth obtaining unit is used for obtaining a first temperature control instruction according to the first preset temperature threshold;
a first control unit: the first control unit is used for controlling the temperature of the first bearing not to exceed the first preset temperature threshold according to the first temperature control instruction.
Further, the system further comprises:
an eighteenth obtaining unit: the eighteenth obtaining unit is configured to obtain a second predetermined temperature threshold if the first bearing is a rolling bearing;
a nineteenth obtaining unit: the nineteenth obtaining unit is used for obtaining a second temperature control instruction according to the second preset temperature threshold;
a second control unit: the second control unit is used for controlling the temperature of the first bearing not to exceed the second preset temperature threshold according to the second temperature control instruction, wherein the maximum value of the first preset temperature threshold is smaller than the maximum value of the second preset temperature threshold.
Various changes and specific examples of the intelligent operation method of the high-efficiency motor in the first embodiment of fig. 1 are also applicable to the intelligent operation device of the high-efficiency motor in this embodiment, and through the foregoing detailed description of the intelligent operation method of the high-efficiency motor, those skilled in the art can clearly know the implementation method of the intelligent operation device of the high-efficiency motor in this embodiment, so for the sake of brevity of the description, detailed description is not repeated again.
EXAMPLE III
The electronic device of the embodiment of the present application is described below with reference to fig. 3.
Fig. 3 illustrates a schematic structural diagram of an electronic device according to an embodiment of the present application.
Based on the inventive concept of the intelligent operation method of the high-efficiency motor in the foregoing embodiment, the present invention further provides an intelligent operation device of the high-efficiency motor, which has a computer program stored thereon, and when the program is executed by a processor, the steps of any one of the foregoing intelligent operation methods of the high-efficiency motor are implemented.
Where in fig. 3 a bus architecture (represented by bus 300), bus 300 may include any number of interconnected buses and bridges, bus 300 linking together various circuits including one or more processors, represented by processor 302, and memory, represented by memory 304. The bus 300 may also link together various other circuits such as peripherals, voltage regulators, power management circuits, and the like, which are well known in the art, and therefore, will not be described any further herein. A bus interface 305 provides an interface between the bus 300 and the receiver 301 and transmitter 303. The receiver 301 and the transmitter 303 may be the same element, i.e., a transceiver, providing a means for communicating with various other apparatus over a transmission medium. The processor 302 is responsible for managing the bus 300 and general processing, and the memory 304 may be used for storing data used by the processor 302 in performing operations.
The embodiment of the application provides an intelligent operation method of a high-efficiency motor, wherein the method is applied to an intelligent operation device of the high-efficiency motor, the device comprises an image acquisition device, and the method comprises the following steps: obtaining a first amplitude of the first bearing; obtaining a second amplitude of the second bearing; obtaining an amplitude difference from the first amplitude and the second amplitude, wherein the first amplitude is greater than the second amplitude; determining whether the amplitude difference is within a predetermined amplitude threshold; obtaining a first position if the amplitude difference is not within the predetermined amplitude threshold, the first position being a position of a first bearing; inputting the amplitude difference and the first position into a neural network model to obtain first fault information; acquiring first reminding information according to the first fault information; and reminding the first motor of the fault according to the first reminding information.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (9)
1. An intelligent operation method of a high-efficiency motor, wherein the method is applied to an intelligent operation device of the high-efficiency motor, the device comprises an image acquisition device, and the method comprises the following steps:
obtaining a first amplitude of the first bearing;
obtaining a second amplitude of the second bearing;
obtaining an amplitude difference from the first amplitude and the second amplitude, wherein the first amplitude is greater than the second amplitude;
determining whether the amplitude difference is within a predetermined amplitude threshold;
obtaining a first position if the amplitude difference is not within the predetermined amplitude threshold, the first position being a position of a first bearing;
inputting the amplitude difference and the first position into a neural network model to obtain first fault information;
acquiring first reminding information according to the first fault information;
and reminding the first motor of the fault according to the first reminding information.
2. The method of claim 1, wherein obtaining the first amplitude of the first bearing comprises, prior to:
obtaining a first control instruction;
rotating a rotor of a first motor according to the first control instruction;
acquiring first video information according to the image acquisition device;
judging whether a rotor of the first motor starts to rotate or not according to the first video information;
after the rotor of the first motor starts to rotate, judging whether the rotor generates friction with the stator;
if the rotor and the stator do not generate friction, second reminding information is obtained;
and reminding the first motor of safe operation according to the second reminding information to obtain the first amplitude of the first bearing.
3. The method of claim 1, wherein said inputting the amplitude difference and the first location into a neural network model to obtain first fault information comprises:
inputting the amplitude difference and the first position into a neural network model, wherein the neural network model is obtained by training a plurality of sets of training data, and each set of the plurality of sets of training data comprises: the amplitude difference, the first location, and identification information identifying a first fault;
obtaining a first output result of the neural network model, the first output result including the first fault information.
4. The method of claim 1, wherein the method comprises:
obtaining the overall vibration amplitude of the first motor;
obtaining a predetermined vibration amplitude threshold value;
and when the overall vibration amplitude exceeds the preset vibration amplitude threshold value, obtaining first recording information, wherein the first recording information is used for recording the overall vibration amplitude exceeding the preset vibration amplitude threshold value.
5. The method of claim 4, wherein obtaining the first recording information comprises:
obtaining the number of the first record information;
obtaining a predetermined number threshold;
when the number of the first record information exceeds the preset number threshold, obtaining third reminding information;
and reminding the first motor of the fault according to the third reminding information.
6. The method of claim 1, wherein the method comprises:
judging whether the first bearing is a sliding bearing or not;
obtaining a first predetermined temperature threshold if the first bearing is the plain bearing;
obtaining a first temperature control instruction according to the first preset temperature threshold;
and controlling the temperature of the first bearing not to exceed the first preset temperature threshold according to the first temperature control instruction.
7. The method of claim 6, wherein said determining whether the first bearing is a plain bearing comprises:
if the first bearing is a rolling bearing, obtaining a second predetermined temperature threshold;
obtaining a second temperature control instruction according to the second preset temperature threshold;
and controlling the temperature of the first bearing not to exceed the second preset temperature threshold according to the second temperature control instruction, wherein the maximum value of the first preset temperature threshold is smaller than the maximum value of the second preset temperature threshold.
8. An intelligent operation device of a high-efficiency motor, wherein the device comprises:
a first obtaining unit: the first obtaining unit is used for obtaining a first amplitude of the first bearing;
a second obtaining unit: the second obtaining unit is used for obtaining a second amplitude of the second bearing;
a third obtaining unit: the third obtaining unit is configured to obtain an amplitude difference according to the first amplitude and the second amplitude, where the first amplitude is greater than the second amplitude;
a first judgment unit: the first judging unit is used for judging whether the amplitude difference is within a preset amplitude threshold value;
a fourth obtaining unit: the fourth obtaining unit is used for obtaining a first position if the amplitude difference is not within the preset amplitude threshold value, wherein the first position is the position of the first bearing;
a first input unit: the first input unit is used for inputting the amplitude difference and the first position into a neural network model to obtain first fault information;
a fifth obtaining unit: the fifth obtaining unit is used for obtaining first reminding information according to the first fault information;
the first reminding unit: the first reminding unit is used for reminding the first motor of a fault according to the first reminding information.
9. An intelligent operation device of a high-efficiency motor, comprising a memory, a processor and a computer program stored on the memory and operable on the processor, wherein the processor executes the program to implement the steps of the method according to any one of claims 1 to 7.
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