CN117592970A - Non-return device life cycle management method and device and non-return device - Google Patents
Non-return device life cycle management method and device and non-return device Download PDFInfo
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Abstract
The application discloses a method and a device for managing the life cycle of a backstop and the backstop. The backstop life cycle management method comprises the following steps: acquiring key information parameters of a backstop of the backstop at the current time; and acquiring the health condition of the backstop according to the key information parameters of the backstop. According to the method for managing the life cycle of the backstop, the health condition of the backstop can be known in real time through analysis of key information parameters of the backstop, so that the problem that the health condition of the backstop can be known only through a manual observation mode in the prior art is solved.
Description
Technical Field
The application relates to the technical field of a backstop, in particular to a backstop life cycle management method, a backstop life cycle management device and a backstop.
Background
The backstop is used on an upward-conveying belt conveyor having an inclination angle to prevent the apparatus from reversing. However, the conventional backstop is purely mechanical and does not have any monitoring. For maintenance of equipment, inspection can only be performed manually, sightseeing, hearing or disassembly and factory return detection can be performed. The health state of the backstop can not be judged through each parameter, and the life cycle of the backstop can not be predicted.
Disclosure of Invention
The present invention is directed to a method for managing a life cycle of a backstop, which solves at least one of the above-mentioned problems.
In one aspect of the present invention, there is provided a method of managing a life cycle of a backstop, the method comprising:
acquiring key information parameters of a backstop of the backstop at the current time;
and acquiring the health condition of the backstop according to the key information parameters of the backstop.
Optionally, the key information parameters of the backstop comprise vibration parameters, liquid level parameters, oil parameters, noise parameters, rotating speed parameters and temperature parameters.
Optionally, the acquiring the health condition of the backstop according to the key information parameter of the backstop includes:
obtaining a pre-stored classifier database, wherein the classifier database comprises at least two trained classifiers, and each classifier has different characteristic input requirements;
obtaining vibration characteristics according to the vibration parameters;
acquiring liquid level characteristics according to the liquid level parameters;
acquiring oil characteristics according to the oil parameters;
acquiring noise characteristics according to the noise parameters;
acquiring a rotating speed characteristic according to the rotating speed parameter;
acquiring temperature characteristics according to the temperature parameters;
pairing and fusing the obtained characteristics respectively to form a characteristic group, wherein one characteristic group comprises at least one characteristic of vibration characteristics, liquid level characteristics, oil product characteristics, noise characteristics, rotating speed characteristics and temperature characteristics;
acquiring a trained classifier corresponding to each group of feature groups according to the feature input requirements;
and inputting the feature group into a corresponding trained classifier, thereby obtaining a classification result of the feature group.
Optionally, the classifier includes:
a single temperature risk classifier whose required feature input requirement is a single temperature risk requirement;
the required characteristic input requirement of the combined temperature risk classifier is the combined temperature risk requirement;
a single vibration risk classifier whose required feature input requirement is a single vibration risk requirement;
the required characteristic input requirement of the combined vibration risk classifier is the combined vibration risk requirement;
the required characteristic input requirement of the single liquid level risk classifier is the single liquid level risk requirement;
the required characteristic input requirement of the combined liquid level risk classifier is the combined liquid level risk requirement;
the step of obtaining the trained classifier corresponding to each group of feature groups according to the feature input requirement comprises the following steps:
when the required characteristic input requirement is a single temperature risk requirement, the characteristic group comprises a temperature characteristic or a rotating speed characteristic;
when the required characteristic input requirement is a combined temperature risk requirement, the characteristic group comprises a temperature characteristic, a rotating speed characteristic and a vibration characteristic;
when the required characteristic input requirement is a single vibration risk requirement, the characteristic group comprises a vibration characteristic or a rotating speed characteristic;
when the required characteristic input requirement is a combined vibration risk requirement, the characteristic group comprises a rotating speed characteristic, a vibration characteristic, an oil product characteristic and a liquid level characteristic;
when the required feature input requirement is a single liquid level risk requirement, the feature set includes liquid level features;
when the desired characteristic input requirement is a combined level risk requirement, the set of characteristics includes a level characteristic and a vibration characteristic.
Optionally, before acquiring the pre-stored classifier database, the acquiring the health status of the backstop according to the key information parameter of the backstop further includes:
acquiring a classifier selection strategy database, wherein the classifier selection strategy database comprises at least one selection strategy, and each selection strategy comprises a preset classifier and a preset parameter set range;
judging whether the acquired key information parameters of the backstop accord with any one of the preset parameter group ranges in the classifier selection strategy database, if so, then
And obtaining a preset classifier corresponding to the preset parameter set range.
Optionally, when judging whether the acquired key information parameters of the backstop meet the number of any preset parameter group range in the classifier selection strategy database or not, respectively acquiring preset classifier use corresponding to each preset parameter group range.
Optionally, the backstop life cycle management method further comprises:
acquiring time information of the health condition of the backstop acquired each time;
and generating a curve segment of the running state of the backstop according to the time information of the health condition of the backstop.
Optionally, acquiring a historical backstop operation state curve database, wherein the backstop operation state curve database comprises a plurality of preset backstop operation state curves;
acquiring the total running time of the curve segment of the running state of the backstop;
the following operations are respectively carried out for each preset backstop running state curve:
taking the origin of a preset backstop running state curve as the initial time, and acquiring a curve segment with the same total running time as the preset backstop running state curve to be fitted from the preset backstop running state curve;
obtaining fitting degrees of the curve sections of the running state of the backstop and each preset curve section to be fitted of the running state of the backstop respectively, judging whether at least one fitting degree exceeds a preset threshold value, if so, then
And acquiring a preset backstop running state curve corresponding to a to-be-fitted section of the preset backstop running state curve with the highest fitting degree exceeding a preset threshold value as a future estimated running state curve.
The application also provides a backstop life cycle management device, backstop life cycle management device includes:
the backstop key information parameter acquisition module is used for acquiring backstop key information parameters of the backstop at the current time;
the health condition evaluation module is used for acquiring the health condition of the backstop according to the key information parameters of the backstop.
Advantageous effects
According to the method for managing the life cycle of the backstop, the health condition of the backstop can be known in real time through analysis of key information parameters of the backstop, so that the problem that the health condition of the backstop can be known only through a manual observation mode in the prior art is solved.
Drawings
FIG. 1 is a flow chart of a method for managing a life cycle of a backstop according to an embodiment of the present application.
Fig. 2 is a schematic diagram of an electronic device for implementing the method of managing the life cycle of the backstop shown in fig. 1.
Detailed Description
In order to make the purposes, technical solutions and advantages of the implementation of the present application more clear, the technical solutions in the embodiments of the present application will be described in more detail below with reference to the accompanying drawings in the embodiments of the present application. In the drawings, the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The described embodiments are some, but not all, of the embodiments of the present application. The embodiments described below by referring to the drawings are exemplary and intended for the purpose of explaining the present application and are not to be construed as limiting the present application. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, are intended to be within the scope of the present application. Embodiments of the present application are described in detail below with reference to the accompanying drawings.
FIG. 1 is a flow chart of a method for managing a life cycle of a backstop according to an embodiment of the present application.
The backstop life cycle management method shown in fig. 1 comprises the following steps:
acquiring key information parameters of a backstop of the backstop at the current time;
and acquiring the health condition of the backstop according to the key information parameters of the backstop.
According to the method for managing the life cycle of the backstop, the health condition of the backstop can be known in real time through analysis of key information parameters of the backstop, so that the problem that the health condition of the backstop can be known only through a manual observation mode in the prior art is solved.
In this embodiment, the key information parameters of the backstop include vibration parameters, liquid level parameters, oil parameters, noise parameters, rotation speed parameters and temperature parameters.
In this embodiment, the obtaining the health status of the backstop according to the key information parameter of the backstop includes:
obtaining a pre-stored classifier database, wherein the classifier database comprises at least two trained classifiers, and each classifier has different characteristic input requirements;
obtaining vibration characteristics according to the vibration parameters;
acquiring liquid level characteristics according to the liquid level parameters;
acquiring oil characteristics according to the oil parameters;
acquiring noise characteristics according to the noise parameters;
acquiring a rotating speed characteristic according to the rotating speed parameter;
acquiring temperature characteristics according to the temperature parameters;
pairing and fusing the obtained characteristics respectively to form a characteristic group, wherein one characteristic group comprises at least one characteristic of vibration characteristics, liquid level characteristics, oil product characteristics, noise characteristics, rotating speed characteristics and temperature characteristics;
acquiring a trained classifier corresponding to each group of feature groups according to the feature input requirements;
and inputting the feature group into a corresponding trained classifier, thereby obtaining a classification result of the feature group.
In this embodiment, the classifier includes:
a single temperature risk classifier whose required feature input requirement is a single temperature risk requirement;
the required characteristic input requirement of the combined temperature risk classifier is the combined temperature risk requirement;
a single vibration risk classifier whose required feature input requirement is a single vibration risk requirement;
the required characteristic input requirement of the combined vibration risk classifier is the combined vibration risk requirement;
the required characteristic input requirement of the single liquid level risk classifier is the single liquid level risk requirement;
the required characteristic input requirement of the combined liquid level risk classifier is the combined liquid level risk requirement;
the step of obtaining the trained classifier corresponding to each group of feature groups according to the feature input requirement comprises the following steps:
when the required characteristic input requirement is a single temperature risk requirement, the characteristic group comprises a temperature characteristic or a rotating speed characteristic;
when the required characteristic input requirement is a combined temperature risk requirement, the characteristic group comprises a temperature characteristic, a rotating speed characteristic and a vibration characteristic;
when the required characteristic input requirement is a single vibration risk requirement, the characteristic group comprises a vibration characteristic or a rotating speed characteristic;
when the required characteristic input requirement is a combined vibration risk requirement, the characteristic group comprises a rotating speed characteristic, a vibration characteristic, an oil product characteristic and a liquid level characteristic;
when the required feature input requirement is a single liquid level risk requirement, the feature set includes liquid level features;
when the desired characteristic input requirement is a combined level risk requirement, the set of characteristics includes a level characteristic and a vibration characteristic.
In this application, this application has designed a plurality of classifiers, and every classifier has different input characteristics, like this when in actual use, can select different classifiers according to actual conditions, and this kind of mode considers different parameters and probably needs the combination to reflect the state of backstop, and wherein certain parameter can be the main cause, and other parameters then probably play the condition of supplementary reference, for example, the backstop normal operating time, and the temperature rise can not surpass ambient temperature 30, if the backstop is during actual operation, temperature exceeds ambient temperature 30 degrees, then need send the warning, carries out manual intervention. When the backstop is operated, the temperature rise exceeding 30 degrees may have the following problems: excessive vibration of the equipment results in direct sunlight, and conduction of other equipment.
In this case, if only the temperature parameter is used to input into the classifier, then we can classify only an over-temperature alarm or a normothermic one.
However, if we input the temperature characteristics, vibration characteristics, noise characteristics into the classifier, we may get more classification results, for example, the temperature is too high due to simple solar irradiation, the temperature is too high due to vibration caused by equipment failure, etc.
Other fusion characteristics can reflect different conditions, for example, the combined vibration risk may be vibration caused by less lubricating oil, mechanical fault vibration caused by normal oil product characteristics and liquid level characteristics, simple rotation speed characteristics and abnormal vibration characteristics, and the like.
In this embodiment, before obtaining the pre-stored classifier database, the obtaining the health status of the backstop according to the key information parameter of the backstop further includes:
acquiring a classifier selection strategy database, wherein the classifier selection strategy database comprises at least one selection strategy, and each selection strategy comprises a preset classifier and a preset parameter set range;
judging whether the acquired key information parameters of the backstop accord with any one of the preset parameter group ranges in the classifier selection strategy database, if so, then
And obtaining a preset classifier corresponding to the preset parameter set range.
For example, each selection policy is determined according to a preset parameter set range, for example, if the vibration parameter value is a, the rotation speed parameter is B, and the temperature parameter is C, and in one preset parameter set range, the vibration parameter value includes a, the rotation speed parameter is B, and the temperature parameter is C, and then the classifier corresponding to the preset parameter set range is selected for use. If none of the preset parameter sets includes A, B, C, but one of the preset parameter sets includes a, and one of the preset parameter sets includes B, the corresponding classifiers are also selected for use.
In this embodiment, when it is determined whether the acquired key information parameters of the backstop conform to the number of any one of the preset parameter set ranges in the classifier selection policy database, the preset classifier corresponding to each set of preset parameter set ranges is acquired for use.
In this embodiment, the method for managing the life cycle of the backstop further includes:
acquiring time information of the health condition of the backstop acquired each time;
and generating a curve segment of the running state of the backstop according to the time information of the health condition of the backstop.
In this way, the user can obtain the specific operating condition of the backstop from working to present by observing the curve segment of the operating condition of the backstop.
The method comprises the steps that a backstop running state curve section obtains a historical backstop running state curve database, and the backstop running state curve database comprises a plurality of preset backstop running state curves;
acquiring the total running time of the curve segment of the running state of the backstop;
the following operations are respectively carried out for each preset backstop running state curve:
taking the origin of a preset backstop running state curve as the initial time, and acquiring a curve segment with the same total running time as the preset backstop running state curve to be fitted from the preset backstop running state curve;
obtaining fitting degrees of the curve sections of the running state of the backstop and each preset curve section to be fitted of the running state of the backstop respectively, judging whether at least one fitting degree exceeds a preset threshold value, if so, then
And acquiring a preset backstop running state curve corresponding to a to-be-fitted section of the preset backstop running state curve with the highest fitting degree exceeding a preset threshold value as a future estimated running state curve.
In this way, once the fitting degree exceeds the preset threshold value, it is indicated that the running state curve of a certain backstop in the history after the running state curve section of the backstop is likely to be the same, and the possible future situation is also about the same, so that the preset running state curve of the backstop in the history can be called as the future estimated running state curve, and a user can know the future running condition and the possible residual life cycle of the backstop by referring to the future estimated running state curve.
It can be appreciated that the training of the classifier can be performed by generating a data set through actual operation data, or by artificially generating data.
It will be appreciated that the historical inverter operating condition curve database may be a preset inverter operating condition curve generated by the actual condition of the inverter used each time before.
The application also provides a backstop life cycle management device, which comprises a backstop key information parameter acquisition module and a health condition evaluation module, wherein the backstop key information parameter acquisition module is used for acquiring backstop key information parameters of the backstop at the current time; the health condition evaluation module is used for acquiring the health condition of the backstop according to the key information parameters of the backstop.
The application also provides a non-return device, which comprises a vibration sensor, a liquid level sensor, an oil product sensor, a sound sensor, a rotating speed sensor, a temperature sensor and a master controller, wherein,
the vibration sensor is arranged on the backstop and used for acquiring vibration parameters of the backstop;
the liquid level sensor is arranged on the backstop and used for acquiring the liquid level parameter of the lubricating oil in the backstop;
the oil sensor is arranged on the backstop and used for acquiring oil parameters of lubricating oil in the backstop;
the sound sensor is arranged on the backstop and used for acquiring noise parameters of the backstop in the running process;
the rotation speed sensor is arranged on the backstop and used for acquiring rotation speed parameters of the backstop;
the temperature sensor is arranged on the backstop and used for acquiring the temperature parameter of the backstop;
the master controller comprises the backstop life cycle management device, and the master controller is respectively connected with each sensor and is used for enabling the backstop life cycle management device to acquire the health condition of the backstop according to the acquired information of each sensor.
It should be noted that the foregoing explanation of the method embodiment is also applicable to the apparatus of this embodiment, and will not be repeated here.
The application also provides an electronic device comprising a memory, a processor and a computer program stored in the memory and capable of running on the processor, the processor implementing the in vivo detection method as above when executing the computer program.
The present application also provides a computer-readable storage medium storing a computer program which, when executed by a processor, is capable of implementing the living body detection method as above.
FIG. 2 is an exemplary block diagram of an electronic device capable of implementing the method of backstop lifecycle management provided in accordance with an embodiment of the present application.
As shown in fig. 2, the electronic device includes an input device 501, an input interface 502, a central processor 503, a memory 504, an output interface 505, and an output device 506. The input interface 502, the central processing unit 503, the memory 504, and the output interface 505 are connected to each other through a bus 507, and the input device 501 and the output device 506 are connected to the bus 507 through the input interface 502 and the output interface 505, respectively, and further connected to other components of the electronic device. Specifically, the input device 504 receives input information from the outside, and transmits the input information to the central processor 503 through the input interface 502; the central processor 503 processes the input information based on computer executable instructions stored in the memory 504 to generate output information, temporarily or permanently stores the output information in the memory 504, and then transmits the output information to the output device 506 through the output interface 505; the output device 506 outputs the output information to the outside of the electronic device for use by the user.
That is, the electronic device shown in fig. 2 may also be implemented to include: a memory storing computer-executable instructions; and one or more processors that, when executing the computer-executable instructions, implement the backstop lifecycle management method described in connection with fig. 1.
In one embodiment, the electronic device shown in FIG. 2 may be implemented to include: a memory 504 configured to store executable program code; one or more processors 503 configured to execute the executable program code stored in the memory 504 to perform the method of backstop lifecycle management in the above embodiments.
In one typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include volatile memory in a computer-readable medium, random Access Memory (RAM) and/or nonvolatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of computer-readable media.
Computer-readable media include both permanent and non-permanent, removable and non-removable media, and the media may be implemented in any method or technology for storage of information. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media for a computer include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computing device.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application 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.
Furthermore, it is evident that the word "comprising" does not exclude other elements or steps. A plurality of units, modules or means recited in the apparatus claims can also be implemented by means of software or hardware by means of one unit or total means.
The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The processor referred to in this embodiment may be a central processing unit (Central Processing Unit, CPU), or other general purpose processor, digital signal processor (Digital Signal Processor, DSP), application specific integrated circuit (Application Specific Integrated Circuit, ASIC), off-the-shelf programmable gate array (Field-Programmable Gate Array, FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory may be used to store computer programs and/or modules, and the processor may perform various functions of the apparatus/terminal device by executing or executing the computer programs and/or modules stored in the memory, and invoking data stored in the memory. The memory may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program (such as a sound playing function, an image playing function, etc.) required for at least one function, and the like; the storage data area may store data (such as audio data, phonebook, etc.) created according to the use of the handset, etc. In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as a hard disk, memory, plug-in hard disk, smart Media Card (SMC), secure Digital (SD) Card, flash Card (Flash Card), at least one disk storage device, flash memory device, or other volatile solid-state storage device.
In this embodiment, the modules/units of the apparatus/terminal device integration may be stored in a computer readable storage medium if implemented in the form of software functional units and sold or used as a separate product. Based on such understanding, the present invention may implement all or part of the flow of the method of the above embodiment, or may be implemented by a computer program to instruct related hardware, and the computer program may be stored in a computer readable storage medium, where the computer program, when executed by a processor, may implement the steps of each of the method embodiments described above. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, executable files or in some intermediate form, etc. The computer readable medium may include: any entity or device capable of carrying computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), an electrical carrier signal, a telecommunications signal, a software distribution medium, and so forth. It should be noted that the content of the computer readable medium can be appropriately increased or decreased according to the requirements of the legislation and the practice of the patent in the jurisdiction. While the preferred embodiments have been described, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the invention, and it is intended that the scope of the invention shall be limited only by the claims appended hereto.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application 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.
Furthermore, it is evident that the word "comprising" does not exclude other elements or steps. A plurality of units, modules or means recited in the apparatus claims can also be implemented by means of software or hardware by means of one unit or total means.
While the invention has been described in detail in the foregoing general description and with reference to specific embodiments thereof, it will be apparent to one skilled in the art that modifications and improvements can be made thereto. Accordingly, such modifications or improvements may be made without departing from the spirit of the invention and are intended to be within the scope of the invention as claimed.
While the invention has been described in detail in the foregoing general description and with reference to specific embodiments thereof, it will be apparent to one skilled in the art that modifications and improvements can be made thereto. Accordingly, such modifications or improvements may be made without departing from the spirit of the invention and are intended to be within the scope of the invention as claimed.
Claims (10)
1. A method for managing the life cycle of a backstop, the method comprising:
acquiring key information parameters of a backstop of the backstop at the current time;
and acquiring the health condition of the backstop according to the key information parameters of the backstop.
2. The method of claim 1, wherein the key information parameters of the non-return device include vibration parameters, liquid level parameters, oil parameters, noise parameters, rotational speed parameters, and temperature parameters.
3. The method of claim 2, wherein said obtaining the health of the backstop based on the key information parameters of the backstop comprises:
obtaining a pre-stored classifier database, wherein the classifier database comprises at least two trained classifiers, and each classifier has different characteristic input requirements;
obtaining vibration characteristics according to the vibration parameters;
acquiring liquid level characteristics according to the liquid level parameters;
acquiring oil characteristics according to the oil parameters;
acquiring noise characteristics according to the noise parameters;
acquiring a rotating speed characteristic according to the rotating speed parameter;
acquiring temperature characteristics according to the temperature parameters;
pairing and fusing the obtained characteristics respectively to form a characteristic group, wherein one characteristic group comprises at least one characteristic of vibration characteristics, liquid level characteristics, oil product characteristics, noise characteristics, rotating speed characteristics and temperature characteristics;
acquiring a trained classifier corresponding to each group of feature groups according to the feature input requirements;
and inputting the feature group into a corresponding trained classifier, thereby obtaining a classification result of the feature group.
4. A method of backstop lifecycle management as recited in claim 3, wherein the classifier comprises:
a single temperature risk classifier whose required feature input requirement is a single temperature risk requirement;
the required characteristic input requirement of the combined temperature risk classifier is the combined temperature risk requirement;
a single vibration risk classifier whose required feature input requirement is a single vibration risk requirement;
the required characteristic input requirement of the combined vibration risk classifier is the combined vibration risk requirement;
the required characteristic input requirement of the single liquid level risk classifier is the single liquid level risk requirement;
the required characteristic input requirement of the combined liquid level risk classifier is the combined liquid level risk requirement;
the step of obtaining the trained classifier corresponding to each group of feature groups according to the feature input requirement comprises the following steps:
when the required characteristic input requirement is a single temperature risk requirement, the characteristic group comprises a temperature characteristic or a rotating speed characteristic;
when the required characteristic input requirement is a combined temperature risk requirement, the characteristic group comprises a temperature characteristic, a rotating speed characteristic and a vibration characteristic;
when the required characteristic input requirement is a single vibration risk requirement, the characteristic group comprises a vibration characteristic or a rotating speed characteristic;
when the required characteristic input requirement is a combined vibration risk requirement, the characteristic group comprises a rotating speed characteristic, a vibration characteristic, an oil product characteristic and a liquid level characteristic;
when the required feature input requirement is a single liquid level risk requirement, the feature set includes liquid level features;
when the desired characteristic input requirement is a combined level risk requirement, the set of characteristics includes a level characteristic and a vibration characteristic.
5. The method of claim 4, wherein said obtaining the health of the backstop based on the key information parameters of the backstop further comprises, prior to obtaining a pre-stored classifier database:
acquiring a classifier selection strategy database, wherein the classifier selection strategy database comprises at least one selection strategy, and each selection strategy comprises a preset classifier and a preset parameter set range;
judging whether the acquired key information parameters of the backstop accord with any one of the preset parameter group ranges in the classifier selection strategy database, if so, then
And obtaining a preset classifier corresponding to the preset parameter set range.
6. The method according to claim 5, wherein when it is determined whether the acquired key information parameters of the inverter conform to any one of the preset parameter set ranges in the classifier selection policy database, the preset classifier corresponding to each preset parameter set range is acquired for use.
7. The method of backstop lifecycle management of claim 6, further comprising:
acquiring time information of the health condition of the backstop acquired each time;
and generating a curve segment of the running state of the backstop according to the time information of the health condition of the backstop.
8. The method of claim 7, wherein a historical inverter operating state curve database is obtained, the inverter operating state curve database comprising a plurality of preset inverter operating state curves;
acquiring the total running time of the curve segment of the running state of the backstop;
the following operations are respectively carried out for each preset backstop running state curve:
taking the origin of a preset backstop running state curve as the initial time, and acquiring a curve segment with the same total running time as the preset backstop running state curve to be fitted from the preset backstop running state curve;
obtaining fitting degrees of the curve sections of the running state of the backstop and each preset curve section to be fitted of the running state of the backstop respectively, judging whether at least one fitting degree exceeds a preset threshold value, if so, then
And acquiring a preset backstop running state curve corresponding to a to-be-fitted section of the preset backstop running state curve with the highest fitting degree exceeding a preset threshold value as a future estimated running state curve.
9. A backstop life cycle management device, characterized in that the backstop life cycle management device comprises:
the backstop key information parameter acquisition module is used for acquiring backstop key information parameters of the backstop at the current time;
the health condition evaluation module is used for acquiring the health condition of the backstop according to the key information parameters of the backstop.
10. A backstop, characterized in that it comprises:
the vibration sensor is arranged on the backstop and used for acquiring vibration parameters of the backstop;
the liquid level sensor is arranged on the backstop and is used for acquiring liquid level parameters of lubricating oil in the backstop;
the oil product sensor is arranged on the backstop and is used for acquiring oil product parameters of lubricating oil in the backstop;
the sound sensor is used for being arranged on the backstop and used for acquiring noise parameters of the backstop in the running process;
the rotating speed sensor is used for being arranged on the backstop and obtaining rotating speed parameters of the backstop;
the temperature sensor is arranged on the backstop and used for acquiring temperature parameters of the backstop;
a master controller comprising the backstop life cycle management device of claim 9, wherein the master controller is respectively connected with each sensor and is used for enabling the backstop life cycle management device to acquire the health condition of the backstop according to the acquired information of each sensor.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311665092.0A CN117592970A (en) | 2023-12-06 | 2023-12-06 | Non-return device life cycle management method and device and non-return device |
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311665092.0A CN117592970A (en) | 2023-12-06 | 2023-12-06 | Non-return device life cycle management method and device and non-return device |
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| CN117592970A true CN117592970A (en) | 2024-02-23 |
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| CN202311665092.0A Pending CN117592970A (en) | 2023-12-06 | 2023-12-06 | Non-return device life cycle management method and device and non-return device |
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| CN (1) | CN117592970A (en) |
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