CN113159338A - Method, apparatus, device and medium for determining maintenance time of device component - Google Patents
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- 238000012423 maintenance Methods 0.000 title claims abstract description 47
- 238000000034 method Methods 0.000 title claims abstract description 38
- 230000008439 repair process Effects 0.000 claims abstract description 39
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- XEEYBQQBJWHFJM-UHFFFAOYSA-N Iron Chemical compound [Fe] XEEYBQQBJWHFJM-UHFFFAOYSA-N 0.000 description 2
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Abstract
The disclosed embodiments of the invention disclose methods, apparatuses, devices and media for determining equipment component repair time. The method comprises the following steps: acquiring parameters of a target equipment component based on a joint learning architecture; calculating a fouling threshold of the target equipment component according to the parameter; predicting a repair time for the target equipment component using the fouling threshold; transmitting the maintenance time to a target display device, and controlling the target display device to display the maintenance time. According to the embodiment, the maintenance work is carried out by determining the maintenance time, so that the time for checking the equipment components by personnel is saved, and the efficiency of the maintenance work is improved.
Description
Technical Field
The embodiment of the invention relates to the technical field of computers, in particular to a method, a device, equipment and a medium for determining equipment component maintenance time.
Background
In large system installations, the metal components in the system are susceptible to external factors that can cause fouling of the components. Thus, maintenance of parts is required to maintain the operation of large-scale system equipment according to the fouling situation.
Disclosure of Invention
This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the detailed description. This summary of the disclosure is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter.
Embodiments of the present disclosure provide methods, apparatuses, devices, and media for determining repair time of equipment components to solve the technical problems mentioned in the background section above.
In a first aspect, an embodiment of the disclosure provides a method for determining a repair time of an equipment component, the method including: acquiring parameters of a target equipment component based on a joint learning architecture; calculating a fouling threshold of the target equipment component according to the parameter; predicting a repair time for the target equipment component using the fouling threshold; transmitting the maintenance time to a target display device, and controlling the target display device to display the maintenance time.
In a second aspect, an embodiment of the disclosure provides an apparatus for determining a repair time of a device component, the apparatus including: an acquisition unit configured to acquire parameters of a target device component based on a joint learning architecture; a calculation unit configured to calculate a fouling threshold of the target equipment component from the parameter; a prediction unit configured to predict a repair time of the target equipment component using the fouling threshold; a display unit configured to transmit the repair time to a target display apparatus, and control the target display apparatus to display the repair time.
In a third aspect, an embodiment of the present disclosure provides an electronic device, including: one or more processors; a storage device having one or more programs stored thereon which, when executed by one or more processors, cause the one or more processors to implement the method as described in the first aspect.
In a fourth aspect, embodiments of the present disclosure provide a computer readable medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the method as described in the first aspect.
One of the above embodiments disclosed by the invention has the following beneficial effects: first, a fouling threshold is determined based on parameters of the target equipment component. Then, the maintenance time of the target equipment component is determined according to the scaling threshold value, and convenience is provided for component maintenance work. And finally, controlling the target display equipment to display the maintenance time so as to prompt a worker to maintain the target equipment component. Maintenance work is carried out by determining maintenance time, so that the time for personnel to check equipment components is saved, and the efficiency of the maintenance work is improved.
Drawings
The above and other features, advantages and aspects of the disclosed embodiments will become more apparent from the following detailed description when taken in conjunction with the accompanying drawings. Throughout the drawings, the same or similar reference numbers refer to the same or similar elements. It should be understood that the drawings are schematic and that elements and elements are not necessarily drawn to scale.
FIG. 1 is a schematic illustration of an application scenario of a method of determining equipment component repair time according to a disclosed embodiment of the invention;
FIG. 2 is a flow chart of an embodiment of a method of determining equipment component repair time according to the present disclosure;
FIG. 3 is a schematic structural diagram of an embodiment of an apparatus for determining repair time of equipment components according to the present disclosure;
FIG. 4 is a schematic block diagram of an electronic device suitable for use in implementing the disclosed embodiments of the invention.
Detailed Description
Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present disclosure are shown in the drawings, it is to be understood that the present disclosure may be embodied in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided for a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and examples are for illustrative purposes only and are not intended to limit the scope of the present disclosure.
It should be noted that, for convenience of description, only the portions related to the related invention are shown in the drawings. The embodiments and features of the embodiments disclosed in the present invention may be combined with each other without conflict.
It should be noted that the terms "first", "second", and the like in the present disclosure are only used for distinguishing different devices, modules, or units, and are not used for limiting the order or interdependence of the functions performed by the devices, modules, or units.
It is noted that references to "a", "an", and "the" modifications in the disclosure are exemplary rather than limiting, and that those skilled in the art will understand that "one or more" unless the context clearly dictates otherwise.
The names of messages or information exchanged between devices in the disclosed embodiments are for illustrative purposes only and are not intended to limit the scope of such messages or information.
The present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
FIG. 1 is a schematic diagram of an application scenario of a method of determining equipment component repair time according to some embodiments of the present disclosure.
In the application scenario of fig. 1, first, the computing device 101 may obtain parameters 102 of a target device component based on a joint learning architecture. The computing device 101 may then calculate a fouling threshold 103 for the target equipment component based on the parameters 102. Thereafter, the computing device 101 may predict a repair time 104 for the target equipment component using the fouling threshold 103 for the target equipment component. Finally, the computing device 101 may transmit the repair time 104 to the target display device 105 and control the target display device 105 to display the repair time 104.
The computing device 101 may be hardware or software. When the computing device is hardware, it may be implemented as a distributed cluster composed of multiple servers or terminal devices, or may be implemented as a single server or a single terminal device. When the computing device is embodied as software, it may be installed in the hardware devices enumerated above. It may be implemented, for example, as multiple software or software modules to provide distributed services, or as a single software or software module. And is not particularly limited herein.
It should be understood that the number of computing devices in FIG. 1 is merely illustrative. There may be any number of computing devices, as implementation needs dictate.
With continued reference to FIG. 2, a flow 200 of an embodiment of a method of determining equipment component repair time is shown in accordance with the present disclosure. The method may be performed by the computing device 101 of fig. 1. The method for determining the maintenance time of the equipment component comprises the following steps:
In an embodiment, an executing entity (e.g., the computing device 101 shown in fig. 1) of the method for determining the repair time of the device component may obtain the parameter of the target device component through a wired connection manner or a wireless connection manner based on a joint learning architecture. Here, the target equipment component may be a critical, fouling prone component of the equipment. The parameters of the target device component may include, but are not limited to, at least one of: the parameter used for representing the solution environment state, the protective layer thickness parameter and the scaling rate corresponding to the current environment state.
It should be noted that the wireless connection means may include, but is not limited to, a 3G/4G connection, a WiFi connection, a bluetooth connection, a WiMAX connection, a Zigbee connection, a uwb (ultra wideband) connection, and other wireless connection means now known or developed in the future.
In an embodiment, the execution subject may calculate the fouling threshold of the target equipment component by: first, the execution body may obtain a metal type (e.g., steel, iron) of the target device component; a second step in which the execution body fits a fouling distribution of the target equipment member based on the metal species and the parameter; third, the execution subject may determine a fouling threshold of the target equipment component based on the fouling distribution.
By way of example, the fouling process (where fouling and wear are both reducing the thickness of the equipment parts) can be expressed as follows:
m ═ 1, 2, 3; three solution environment modes are represented. (e.g., neutral, weak acid, weak base three environmental states.1, 2, 3 are assigned, respectively).
Wherein m istIs the solution environment at time t, dtIs the thickness of the scale formation in the plant part at time t, γtIs the increased thickness of the protective layer at time t, ptIs the fouling rate in the current solution environment at time t,
representing a positive real number set.
Wherein eta is1＝30000(η1Representing the time constant in hours).
The starting time is from 0 and is defined as
X0＝(1，0，γ0，ρ0)，
Wherein gamma is0Conforming to a weibull distribution. Gamma ray0Uniform distribution is met at 1, 3 and exponential distribution is met at 2.
Thus, changes in the environment can be recorded over time from 0-T1, T1-T2, … Tn-1-Tn, but as the environment changes, changes in other parameters will conform to the corresponding probability distributions. And receiving a scaling threshold set by a user based on the probability distribution.
And 203, predicting the maintenance time of the target equipment component by using the scaling threshold.
In an embodiment, the execution body may predict the repair time of the target device component by: first, the executive may determine an upper bound for the target cost equation based on the fouling threshold and the target cost equation. Then, the execution subject may determine a time corresponding to the upper bound as a maintenance time of the target device component.
As an example, it can be expressed as follows:
where upsilon (z) represents the reward value, z represents the initial point, g represents the cost equation, E represents the expectation, τ represents the time at which the device stopped, X represents the time at which the device stoppedτIndicating wear at the time of equipment stop and N indicating the number of times the environmental pattern is changed. The execution body may determine a time corresponding to when the prize value is maximized, and then determine the corresponding time as the maintenance time.
And step 204, transmitting the maintenance time to target display equipment, and controlling the target display equipment to display the maintenance time.
In an embodiment, the execution subject may generate prompt information for characterizing prompt maintenance based on the maintenance time. As an example, the reminder information used to characterize the reminder for repair may be "the target device component is repaired! ". Then, the execution body may transmit the prompt message to the target display device, and control the target display device to display the prompt message.
In an optional implementation manner of the embodiment, the executing agent may input parameters of the target device component to a pre-trained device maintenance time determination model, and output the maintenance time. The equipment maintenance time determination model is obtained through joint learning training, and the equipment maintenance time determination model adopts a segmented determination Markov process (PDMP). The environmental states are divided into 3, the initial state x in environment m, over time, transitions from the initial time to the next random environment (the transition is many times, but eventually reaches the fouling threshold stop), or reaches the specified fouling threshold stop. Each stochastic process is the process of moving the components from one environment/state to another, which constitutes a markov process.
In an alternative implementation manner of the embodiment, the joint learning training process is as follows: first, at least one participant downloads a device leakage maintenance time determination model from a target server. The respective participants are then controlled to begin training using the local data. And then, uploading the gradient to a target server after encrypting the gradient. The target server may then aggregate the gradient update model parameters. And then, the target server returns the updated model to the at least one participant. And finally, the at least one participant updates a local equipment leakage maintenance time determination model to complete the joint learning.
In an alternative implementation of the embodiment, in conventional machine learning modeling, it is common to assemble the data required for model training into a data center and then train the model, followed by prediction. In the horizontal federal learning, the distributed model training based on samples can be regarded as the distributed model training, all data are distributed to different machines, each machine downloads the model from the server, then the model is trained by using local data, and then the parameters which need to be updated are returned to the server; the server aggregates the returned parameters on each machine, updates the model, and feeds back the latest model to each machine. One of the above embodiments disclosed by the invention has the following beneficial effects: first, a fouling threshold is determined based on parameters of the target equipment component. Then, the maintenance time of the target equipment component is determined according to the scaling threshold value, and convenience is provided for component maintenance work. And finally, controlling the target display equipment to display the maintenance time so as to prompt a worker to maintain the target equipment component. Maintenance work is carried out by determining maintenance time, so that the time for personnel to check equipment components is saved, and the efficiency of the maintenance work is improved.
With further reference to fig. 3, as an implementation of the above method for the above figures, the present disclosure provides some embodiments of an apparatus for determining a repair time of a device component, which correspond to the above method embodiments of fig. 2, and which may be applied to various electronic devices.
As shown in fig. 3, an apparatus 300 for determining a repair time of a device component according to an embodiment includes: an acquisition unit 301, a calculation unit 302, a prediction unit 303, and a display unit 304. Wherein the obtaining unit 301 is configured to obtain parameters of the target device component based on a joint learning architecture; a calculation unit 302 configured to calculate a fouling threshold of the target equipment component from the parameter; a prediction unit 303 configured to predict a repair time of the target equipment component using the fouling threshold; a display unit 304 configured to transmit the repair time to a target display apparatus and control the target display apparatus to display the repair time.
In an optional implementation manner of the embodiment, the parameters of the target device component include: the parameter used for representing the solution environment state, the protective layer thickness parameter and the scaling rate corresponding to the current environment state.
In an alternative implementation of the embodiment, the calculation unit 302 of the apparatus 300 for determining a repair time for a component of a device is further configured to: a fitting subunit configured to fit a fouling profile of the target equipment component based on the parameters; a first determining subunit configured to determine a fouling threshold of the target equipment component based on the fouling distribution.
In an alternative implementation of the embodiment, the prediction unit 303 of the apparatus 300 for determining a repair time of a device component is further configured to: determining an upper bound for a target cost equation based on the fouling threshold and the target cost equation; and determining the time corresponding to the upper bound as the maintenance time of the target equipment component.
In an alternative implementation of the embodiment, the display unit 304 of the apparatus 300 for determining a repair time of a device component is further configured to: generating prompt information for representing prompt maintenance based on the maintenance time; transmitting the prompt information to the target display equipment, and controlling the target display equipment to display the prompt information.
It will be understood that the units described in the apparatus 300 correspond to the various steps in the method described with reference to fig. 2. Thus, the operations, features and resulting advantages described above with respect to the method are also applicable to the apparatus 300 and the units included therein, and are not described herein again.
Referring now to FIG. 4, a block diagram of an electronic device (e.g., computing device 101 of FIG. 1)400 suitable for use in implementing some embodiments of the present disclosure is shown. The server illustrated in fig. 4 is only an example and should not bring any limitations to the function and scope of use of the disclosed embodiments of the present invention.
As shown in fig. 4, electronic device 400 may include a processing device (e.g., central processing unit, graphics processor, etc.) 401 that may perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM)402 or a program loaded from a storage device 408 into a Random Access Memory (RAM) 403. In the RAM 403, various programs and data necessary for the operation of the electronic apparatus 400 are also stored. The processing device 401, the ROM 402, and the RAM 403 are connected to each other via a bus 404. An input/output (I/O) interface 405 is also connected to bus 404.
Generally, the following devices may be connected to the I/O interface 405: input devices 406 including, for example, a touch screen, touch pad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc.; an output device 407 including, for example, a Liquid Crystal Display (LCD), a speaker, a vibrator, and the like; storage 408 including, for example, tape, hard disk, etc.; and a communication device 409. The communication means 409 may allow the electronic device 400 to communicate wirelessly or by wire with other devices to exchange data. While fig. 4 illustrates an electronic device 400 having various means, it is to be understood that not all illustrated means are required to be implemented or provided. More or fewer devices may alternatively be implemented or provided. Each block shown in fig. 4 may represent one device or may represent multiple devices as desired.
In particular, according to some embodiments of the present disclosure, the processes described above with reference to the flow diagrams may be implemented as computer software programs. For example, some embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In some such embodiments, the computer program may be downloaded and installed from a network through the communication device 409, or from the storage device 408, or from the ROM 402. Which when executed by the processing means 401, performs the above-described functions defined in the methods of some embodiments of the present disclosure.
It should be noted that the computer readable medium mentioned above in some embodiments of the present disclosure may be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In some embodiments of the disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In some embodiments of the present disclosure, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, optical cables, RF (radio frequency), etc., or any suitable combination of the foregoing.
In some embodiments, the clients, servers may communicate using any currently known or future developed network Protocol, such as HTTP (HyperText Transfer Protocol), and may interconnect with any form or medium of digital data communication (e.g., a communications network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), the Internet (e.g., the Internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future developed network.
The computer readable medium may be embodied in the apparatus; or may exist separately without being assembled into the electronic device. The computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to: acquiring parameters of a target equipment component based on a joint learning architecture; calculating a fouling threshold of the target equipment component according to the parameter; predicting a repair time for the target equipment component using the fouling threshold; transmitting the maintenance time to a target display device, and controlling the target display device to display the maintenance time.
Computer program code for carrying out operations for embodiments of the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + +, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
The flowchart 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 disclosure. 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 units described in some embodiments of the present disclosure may be implemented by software or hardware. The described units may also be provided in a processor, and may be described as: a processor includes an acquisition unit, a calculation unit, a prediction unit, and a display unit. The names of these units do not in some cases constitute a limitation to the unit itself, and for example, the acquiring unit may also be described as a "unit that acquires parameters of a target device component based on a joint learning architecture".
The functions described herein above may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), systems on a chip (SOCs), Complex Programmable Logic Devices (CPLDs), and the like.
The foregoing description is only exemplary of the preferred embodiments of the present disclosure and is provided for the purpose of illustrating the general principles of the technology. It will be appreciated by those skilled in the art that the scope of the invention in the embodiments disclosed in the present application is not limited to the embodiments with specific combinations of the above-mentioned features, but also covers other embodiments with any combination of the above-mentioned features or their equivalents without departing from the inventive concept. For example, the above features and (but not limited to) technical features with similar functions disclosed in the embodiments of the present disclosure are mutually replaced to form the technical solution.
Claims (10)
1. A method of determining repair time for equipment components, comprising:
acquiring parameters of a target equipment component based on a joint learning architecture;
calculating a fouling threshold of the target equipment component according to the parameter;
predicting a repair time for the target equipment component using the fouling threshold;
transmitting the maintenance time to a target display device, and controlling the target display device to display the maintenance time.
2. The method of claim 1, wherein the parameters of the target equipment component comprise: the parameter for characterizing the environmental state of the solution, the thickness parameter of the scale in the target equipment component and the scale rate corresponding to the current environmental state.
3. The method of claim 2, wherein said calculating a fouling threshold of said target equipment component based on said parameter comprises:
fitting a fouling profile of the target equipment component based on the parameters;
determining a fouling threshold of the target equipment component based on the fouling distribution.
4. The method of any of claims 1-3, wherein predicting the repair time for the target equipment component using the fouling threshold comprises:
determining an upper bound for a target cost equation based on the fouling threshold and the target cost equation;
and determining the time corresponding to the upper bound as the maintenance time of the target equipment component.
5. The method of claim 4, wherein the transmitting the repair time to a target display device and controlling the target display device to display the repair time comprises:
generating prompt information for representing prompt maintenance based on the maintenance time;
transmitting the prompt information to the target display equipment, and controlling the target display equipment to display the prompt information.
6. An apparatus for determining a repair time for an equipment component, comprising:
an acquisition unit configured to acquire parameters of a target device component based on a joint learning architecture;
a calculation unit configured to calculate a fouling threshold of the target equipment component according to the parameter;
a prediction unit configured to predict a repair time of the target equipment component using the fouling threshold;
a display unit configured to transmit the repair time to a target display apparatus, and control the target display apparatus to display the repair time.
7. The apparatus of claim 6, wherein the parameters of the target equipment component comprise: the parameter for characterizing the environmental state of the solution, the thickness parameter of the scale in the target equipment component and the scale rate corresponding to the current environmental state.
8. The apparatus for determining repair time of equipment parts according to claim 7, wherein the calculation unit comprises:
a fitting subunit configured to fit a fouling profile of the target equipment component based on the parameters;
a first determining subunit configured to determine a fouling threshold of the target equipment component based on the fouling distribution.
9. An electronic device, comprising:
one or more processors;
a storage device having one or more programs stored thereon;
when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1-5.
10. A computer-readable medium, on which a computer program is stored, wherein the program, when executed by a processor, implements the method of any one of claims 1-5.
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