CN111289036A - Equipment fault early warning method, device, equipment and system - Google Patents
Equipment fault early warning method, device, equipment and system Download PDFInfo
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Abstract
The invention provides a method, a device, equipment and a system for early warning equipment faults, wherein the method comprises the following steps: acquiring the running state parameter value of the equipment in real time during the characteristic value learning period; acquiring a first characteristic value of the running state parameter according to the running state parameter value, wherein the first characteristic value indicates at least one of the following running state parameters in a set change interval when the equipment runs normally: maximum rate of change, maximum amplitude of change, maximum time; acquiring an early warning value of the operating state parameter according to the first characteristic value; and during the equipment monitoring period, acquiring the running state parameters of the equipment in real time, acquiring a second characteristic value of the running state parameters according to the running state parameter values during the equipment monitoring period, and if the second characteristic value is greater than the early warning value, giving an alarm. Compared with the prior art, the method and the device have the advantages that the fault trend of the device is dynamically monitored, abnormal changes of the device are captured earlier, and accordingly hidden dangers of the device can be discovered as early as possible.
Description
Technical Field
The invention relates to the technical field of equipment safety management, in particular to an equipment fault early warning method, device, equipment and system.
Background
The monitoring of the industrial equipment is a main technical means for ensuring the safe operation of the industrial equipment, and can prevent serious equipment accidents and production accidents.
At present, a constant value alarm method is generally adopted in an equipment monitoring method, namely a fixed early warning value and a protection shutdown value are set. And when the equipment state is deteriorated and reaches an alarm value, sending alarm information. However, this method has disadvantages in that: and only after the equipment state continuously deteriorates and reaches a preset alarm value, the alarm information is sent out. It cannot give an early warning in time at the initial stage of deterioration of the equipment state. When the alarm signal is sent out, the alarm signal is not processed in time, and standby damage or serious production accidents are easily caused. Therefore, the existing equipment monitoring method has a large monitoring blind area, which is not beneficial to finding out early abnormality of the equipment.
Disclosure of Invention
In order to overcome the problems in the related art, the embodiments of the present invention provide a method, an apparatus, a device, and a system for early warning of a device failure.
According to a first aspect of the embodiments of the present invention, there is provided an apparatus fault early warning method, including the following steps:
acquiring the running state parameter value of the equipment in real time during the characteristic value learning period;
acquiring a first characteristic value of the running state parameter according to the running state parameter value, wherein the first characteristic value indicates at least one of the following running state parameters in a set change interval when the equipment runs normally:
maximum rate of change, maximum amplitude of change, maximum time;
acquiring an early warning value of the operating state parameter according to the first characteristic value;
and during the equipment monitoring period, acquiring the running state parameters of the equipment in real time, acquiring a second characteristic value of the running state parameters according to the running state parameter values during the equipment monitoring period, and if the second characteristic value is greater than the early warning value, giving an alarm.
Optionally, at least one of the following operational state parameters in the set change interval is calculated in real time: maximum change amplitude, maximum change rate, maximum time;
taking the maximum change rate, the maximum change amplitude or the maximum time as a first characteristic value of the operating state parameter;
during feature value learning, if the maximum change rate, the maximum change amplitude, or the maximum time currently calculated is different from the first feature value, the maximum change rate, the maximum change amplitude, or the maximum time currently calculated is updated to the first feature value.
Optionally, the first characteristic value is added to a preset adjustment value to obtain an early warning value of the operating state parameter.
Optionally, the operating condition parameter includes temperature and/or pressure;
the first characteristic value includes at least one of:
the maximum average speed in the set continuous lifting interval, the maximum instantaneous speed in the set continuous lifting interval, the maximum change amplitude in the set continuous lifting interval, the maximum time in the set continuous lifting interval, the maximum average speed in the set accelerating continuous lifting interval, the maximum instantaneous speed in the set accelerating continuous lifting interval, the maximum time in the set accelerating continuous lifting interval, the maximum change amplitude in the set zigzag lifting interval and the maximum time in the set zigzag lifting interval.
Optionally, the operating state parameter includes vibration amplitude and/or vibration frequency;
the first characteristic value includes at least one of:
the maximum vibration amplitude in the set operation speed interval, the maximum vibration frequency in the set operation speed interval and the maximum lifting speed of the vibration amplitude in the set operation speed interval.
Optionally, if the device fails, the currently calculated first characteristic value is cleared, and updating of the early warning value of the operating state parameter is stopped.
According to a second aspect of the embodiments of the present invention, there is provided an apparatus failure early warning apparatus, including:
the acquisition unit is used for acquiring the running state parameter value of the equipment in real time during the characteristic value learning period;
the characteristic value analysis unit is used for acquiring a first characteristic value of the running state parameter according to the running state parameter value, wherein the first characteristic value indicates at least one of the following running state parameters in a set change interval when the equipment runs normally:
maximum rate of change, maximum amplitude of change, maximum time;
the early warning value setting unit is used for obtaining the early warning value of the operating state parameter according to the first characteristic value;
and the alarm unit is used for acquiring the running state parameters of the equipment in real time during the equipment monitoring period, acquiring a second characteristic value of the running state parameters according to the running state parameter values during the equipment monitoring period, and giving an alarm if the second characteristic value is greater than the early warning value.
According to a third aspect of the embodiments of the present invention, there is provided an equipment fault pre-warning device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor implements the steps of the equipment fault pre-warning method according to the first aspect when executing the computer program.
According to a fourth aspect of the embodiments of the present invention, there is provided an equipment fault early warning system, including an on-site control system, a memory, a controller, and a computer program stored in the memory and operable on the controller, where the on-site control system is configured to obtain an operation state parameter value of an equipment in real time, and the controller implements the steps of the equipment fault early warning method according to the first aspect when executing the computer program.
Comprising a memory, a processor and a computer program stored in said memory and executable on said processor, characterized in that said processor implements the steps of the method of device malfunction alerting as described in the above first aspect when executing said computer program.
Compared with the prior art, the embodiment of the invention acquires the running state parameter value of the equipment in real time during the characteristic value learning period, acquiring a first characteristic value of the running state parameter according to the running state parameter value, wherein the first characteristic value indicates at least one of the maximum change rate, the maximum change amplitude and the longest time of the running state parameter in a set change interval when the equipment runs normally, therefore, the parameter change rule of the equipment in normal work can be summarized by adopting a self-learning method, the early warning value is automatically set according to the first characteristic value of the learning result, the fault trend of the equipment is dynamically monitored, the abnormal change of the equipment is captured earlier, the defect of fixed early warning value is overcome, therefore, the hidden danger of the equipment can be discovered as early as possible in the equipment monitoring period, and a beneficial technical means is provided for preventing large faults or production accidents of industrial equipment.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention, as claimed.
For a better understanding and practice, the invention is described in detail below with reference to the accompanying drawings.
Drawings
Fig. 1 is a schematic view of an application scenario of the device fault early warning method in an exemplary embodiment of the present invention;
fig. 2 is a schematic flowchart of an apparatus fault early warning method according to an exemplary embodiment of the present invention;
fig. 3 is a schematic flowchart of S202 in an apparatus fault early warning method according to an exemplary embodiment of the present invention;
fig. 4 is a schematic structural diagram of an equipment failure early warning apparatus according to an exemplary embodiment of the present invention;
fig. 5 is a schematic structural diagram of an equipment failure early warning device according to an exemplary embodiment of the present invention;
fig. 6 is a schematic structural diagram of an equipment failure early warning system according to an exemplary embodiment of the present invention.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the invention, as detailed in the appended claims.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in this specification and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.
It is to be understood that although the terms first, second, third, etc. may be used herein to describe various information, these information should not be limited to these terms. These terms are only used to distinguish one type of information from another. For example, first information may also be referred to as second information, and similarly, second information may also be referred to as first information, without departing from the scope of the present invention. The word "if/if" as used herein may be interpreted as "at … …" or "when … …" or "in response to a determination", depending on the context.
Referring to fig. 1, fig. 1 is a schematic view of an application scenario of the device fault early warning method in an exemplary embodiment, where the application scenario includes an on-site control system 10, a switch 11, a controller 12, a memory 13, a touch screen 14, an internet of things 15, and a mobile terminal 16.
In the existing equipment fault monitoring method, the field control system 10 is used for acquiring the running state parameter value of the equipment in real time, and judging whether the running state parameter value reaches a preset early warning value and a protection shutdown value, if so, the field control system 10 takes corresponding control measures.
However, this method has disadvantages in that: only after the equipment state continuously deteriorates and reaches a preset alarm value, alarm information is sent out, and early warning cannot be timely carried out at the initial deterioration stage of the equipment state.
In view of the above-mentioned drawbacks of the prior art, an embodiment of the present invention provides an apparatus fault warning method, referring to fig. 2, which in an exemplary embodiment is executed by the controller 12 in fig. 1, and includes the following steps:
s201: and acquiring the running state parameter value of the equipment in real time during the characteristic value learning.
The characteristic value learning period refers to an analysis learning period for judging whether the equipment has a fault trend, and the equipment autonomously learns the characteristic values of the relevant operation state parameters in the period, so that the state characteristics which can be borne by the equipment in a normal operation state are obtained, and whether the equipment has the fault trend and the deterioration trend is accurately mastered.
In the embodiment of the present application, the controller 12 acquires the operation state parameter value of the equipment in real time during the characteristic value learning. The equipment can be any equipment which needs to be subjected to fault early warning, and in some embodiments, the equipment can be an ITM-01 type hydraulic motor.
For the scenario of fig. 1, the controller 12 may obtain the operation state parameter value of the device from the field control system 10 through the switch 11.
Specifically, the operating state parameters are state parameters related to safe operation of the equipment, including temperature, pressure, vibration amplitude, vibration frequency, operating speed, load, voltage, installed power, and the like.
In an optional embodiment, after the controller 12 obtains the operation state parameter value of the device in real time, the operation state parameter value is digitally filtered to remove the abnormal parameter value, so as to ensure the accuracy of the subsequent calculation.
S202: acquiring a first characteristic value of the running state parameter according to the running state parameter value, wherein the first characteristic value indicates at least one of the following running state parameters in a set change interval when the equipment runs normally: maximum rate of change, maximum amplitude of change, maximum time.
In this embodiment, the controller 12 obtains a first characteristic value of the operating state parameter according to the operating state parameter value, where the first characteristic value indicates at least one of a maximum change rate, a maximum change amplitude, and a maximum time of the operating state parameter in a set change interval when the device is in normal operation.
Specifically, the normal operation refers to a state in which the controller 12 has not experienced an abnormality or malfunction of the device during the feature learning period. The set change interval is an interval divided according to the operating state parameter, for example: when the operating state parameter is temperature, the set change interval may be an interval in which the temperature continuously rises, an interval in which the temperature continuously falls, or other types of set change intervals; when the operating state is a load, the set change interval may be an interval in which the load increases in an accelerated manner, or may be an interval in which the load is (0, f)max) Within a range of variation, wherein fmaxIs a preset upper load limit.
In some optional embodiments, the maximum change rate, the maximum change amplitude, and the maximum time in the set change interval represent the maximum change rate, the maximum change amplitude, and the maximum time of the operating state parameter in a plurality of change intervals meeting the set condition. For example: when the operating state parameter is temperature, the plurality of change intervals meeting the set condition are a plurality of intervals in which the temperature continuously rises, the average rate of the temperature continuously rising in each interval is calculated, and the first characteristic value is the maximum average rate of the plurality of intervals in which the temperature continuously rises.
In particular, when the operating state parameter is temperature and/or pressure, the first characteristic value comprises at least one of: (1) the maximum average speed in the set continuous ascending and descending interval, namely the maximum average speed of the temperature and/or the pressure in a plurality of continuous ascending or continuous descending intervals; (2) the maximum instantaneous speed in the set continuous ascending and descending interval, namely the maximum instantaneous speed of the temperature and/or the pressure in a plurality of continuous ascending or continuous descending intervals; (3) the maximum variation amplitude in the set continuous lifting interval, namely the maximum variation amplitude of the temperature and/or the pressure in a plurality of continuous lifting intervals or continuous descending intervals; (4) the maximum time in the set continuous lifting interval, namely the maximum time of the temperature and/or the pressure in a plurality of continuous lifting intervals or continuous descending intervals; (5) the maximum average speed in the set acceleration continuous ascending and descending interval, namely the maximum average speed of the temperature and/or the pressure in a plurality of acceleration continuous ascending intervals or acceleration continuous descending intervals; (6) the maximum instantaneous speed in the set accelerating continuous ascending and descending interval, namely the maximum instantaneous speed of the temperature and/or the pressure in a plurality of accelerating continuous ascending intervals or accelerating continuous descending intervals; (7) the maximum time in the set acceleration continuous lifting interval, namely the maximum time of the temperature and/or the pressure in a plurality of acceleration continuous lifting intervals or acceleration continuous falling intervals; (8) the maximum variation amplitude in the set zigzag lifting interval and the maximum time in the set zigzag lifting interval, namely the maximum time of the temperature and/or the pressure in a plurality of zigzag lifting intervals or zigzag falling intervals.
In other alternative embodiments, the maximum change rate, the maximum change amplitude, and the maximum time in the set change interval may represent the maximum change rate, the maximum change amplitude, and the maximum time of the operating state parameter in an interval meeting the set change condition, for example: and when the operating state parameter is the vibration amplitude, a certain interval meeting the set change condition is an interval with the operating speed in (a, b), all vibration amplitudes in the interval are obtained, and the first characteristic value is the maximum vibration amplitude in the interval (a, b).
Specifically, when the operating state parameter is a vibration amplitude and/or a vibration frequency, the first characteristic value includes at least one of: (1) the maximum vibration amplitude in a set operation speed interval, namely the maximum vibration amplitude in a certain set operation speed interval; (2) the maximum vibration frequency in a set operation speed interval, namely the maximum vibration frequency in a certain set operation speed interval, and the minimum vibration period can be correspondingly obtained according to the maximum vibration frequency; (3) the maximum rising and falling speed of the vibration amplitude in the set running speed interval, namely the maximum rising speed or the maximum falling speed of the vibration amplitude in a certain set running speed interval.
It should be further noted that the set operation speed intervals include at least one, and each set operation speed interval has a maximum vibration amplitude, a maximum vibration frequency, a maximum rising rate of the vibration amplitude, or a maximum falling rate of the vibration amplitude. The set operation speed interval may be divided according to the operation speed of the device, and the specific division standard is not limited herein.
The operation state parameter value of the equipment is acquired in real time during the characteristic value learning period, and the first characteristic value of the operation state parameter is acquired, so that the first characteristic value comprehensively and dynamically reflects the equipment state, and the subsequent setting of the early warning value is facilitated. Compared with the traditional equipment fault alarm method only considering the maximum temperature and the maximum pressure which can be borne by the equipment, the equipment fault alarm method has the advantages that the equipment fault trend can be found earlier through the first characteristic value, and abnormal changes of various kinds of equipment can be captured.
S203: and obtaining an early warning value of the operating state parameter according to the first characteristic value.
And the controller 12 obtains the early warning value of the running state parameter according to the first characteristic value. Specifically, the controller 12 may directly use the first characteristic value as the warning value of the operating state parameter, or may use the first characteristic value multiplied by a preset speed (e.g., 1.1 times, etc.) as the warning value of the operating state parameter.
In an optional embodiment, the controller 12 adds a preset adjustment value to the first characteristic value to obtain an early warning value of the operating state parameter, and the preset adjustment value may be reasonably adjusted according to different devices.
S204: and during the equipment monitoring period, acquiring the running state parameters of the equipment in real time, acquiring a second characteristic value of the running state parameters according to the running state parameter values during the equipment monitoring period, and if the second characteristic value is greater than the early warning value, giving an alarm.
In this embodiment of the present application, during the device monitoring period, the controller 12 obtains the running state parameter of the device in real time, obtains the second characteristic value of the running state parameter according to the running state parameter value during the device monitoring period, and sends an alarm if the second characteristic value is greater than the early warning value.
As shown in fig. 1, in some examples, the controller 12 further sends the alarm information to the touch screen 14 through the switch 11 or further sends the alarm information to the mobile terminal 16 through the internet of things 15. The specific way of sending the alarm is not limited, and the above ways can be combined arbitrarily, so that the purpose of informing the staff can be achieved.
In the embodiment of the application, the second characteristic value of the device during monitoring is acquired, the second characteristic value is compared with the early warning value, and then the alarm mode is sent out, the defect of traditional parameter fixed value alarm is overcome, device monitoring can be carried out from different dimensions of multiple running state parameters of the device, and the early warning value is determined according to the first characteristic value calculated during characteristic value learning, so that the real-time state of the device and the device fault trend can be reflected, the fact that the controller 12 can send out alarm information at the first time is guaranteed, and the device accident can be prevented to the greatest extent.
In an alternative embodiment, in order to make the learning of the feature value reach the optimal state, step S20 includes steps S2021 to S2022, please refer to fig. 3, which is a schematic flow chart of step S202 in the equipment failure warning method according to an exemplary embodiment of the present invention, and steps S2021 to S2022 are as follows:
s2021: calculating at least one of the following running state parameters in a set change interval in real time: maximum change amplitude, maximum change rate, maximum time;
during the characteristic value learning period of the equipment, the maximum change amplitude, the maximum change rate and the maximum time of the operation state parameters in the set change interval are continuously changed. Thus, before finally determining the first characteristic value, the controller 12 calculates at least one of the maximum variation amplitude, the maximum variation rate and the maximum time of the operating state parameter within the set variation interval in real time.
S2022: the maximum change rate, the maximum change amplitude or the maximum time is taken as a first characteristic value of the operating state parameter.
In the initial state during the characteristic value learning period, the controller 12 directly uses the first calculated maximum change rate, maximum change amplitude or maximum time as the first characteristic value of the operating state parameter. Meanwhile, the controller 12 stores the first characteristic value.
S2023: during feature value learning, if the maximum change rate, the maximum change amplitude, or the maximum time currently calculated is different from the first feature value, the maximum change rate, the maximum change amplitude, or the maximum time currently calculated is updated to the first feature value.
During the characteristic value learning, the maximum change amplitude, the maximum change rate or the maximum time of the operation state parameter in a set change interval may be continuously changed, and if the currently calculated maximum change rate, the currently calculated maximum change amplitude or the currently calculated maximum time is different from the first characteristic value, the currently calculated maximum change rate, the currently calculated maximum change amplitude or the currently calculated maximum time is updated to the first characteristic value.
In this case, a difference from the first characteristic values should be understood as a difference from all first characteristic values already stored. For example, when the first characteristic value is the maximum average rate of the temperature over a plurality of continuous rises, the controller 12 has stored the temperature at the maximum average rate of { a1, a2,, an } over a plurality of continuous rises, and the above-described updating operation is performed when there is a maximum average rate other than { a1, a2,, an }.
In an alternative embodiment, during the characteristic value learning, if the device fails, the first currently calculated characteristic value is cleared, and updating of the warning value of the operating state parameter is stopped. Therefore, abnormal learning results are effectively removed, and reasonable setting of the early warning value is guaranteed.
Referring to fig. 4, fig. 4 is a schematic structural diagram of an equipment failure early warning apparatus according to an exemplary embodiment of the present invention. The included units are used for executing the steps in the embodiments corresponding to fig. 4 and fig. 4, and refer to the relevant description in the embodiments corresponding to fig. 4 and fig. 4. For convenience of explanation, only the portions related to the present embodiment are shown. Referring to fig. 4, the equipment failure early warning apparatus 4 includes:
an acquisition unit 41 for acquiring an operation state parameter value of the device in real time during the characteristic value learning;
a characteristic value analyzing unit 42, configured to obtain a first characteristic value of the operating state parameter according to the operating state parameter value, where the first characteristic value indicates at least one of the following operating state parameters in a set change interval when the device is in normal operation: maximum rate of change, maximum amplitude of change, maximum time;
an early warning value setting unit 43, configured to obtain an early warning value of the operating state parameter according to the first characteristic value;
and the alarm unit 44 is configured to obtain the running state parameter of the device in real time during the device monitoring period, obtain a second characteristic value of the running state parameter according to the running state parameter value during the device monitoring period, and send an alarm if the second characteristic value is greater than the early warning value.
Optionally, the eigenvalue analysis unit 42 includes:
the first analyzing unit 421 is configured to calculate at least one of the following operating state parameters in a set change interval in real time: maximum change amplitude, maximum change rate, maximum time;
a setting unit 422, configured to use the maximum change rate, the maximum change amplitude, or the maximum time as a first characteristic value of the operating state parameter;
an updating unit 423, configured to update the currently calculated maximum change rate, maximum change amplitude, or maximum time to be the first feature value if the currently calculated maximum change rate, maximum change amplitude, or maximum time is different from the first feature value during feature value learning.
Optionally, the early warning value setting unit 43 further includes:
and a first warning value setting unit 431, configured to add a preset adjustment value to the first characteristic value to obtain a warning value of the operating state parameter.
Optionally, the eigenvalue analysis unit 42 further includes:
and a stop updating unit 424, configured to clear the currently calculated first feature value and stop updating the early warning value of the operating state parameter if the device fails.
Referring to fig. 5, fig. 5 is a schematic diagram of an equipment failure early warning device according to an exemplary embodiment of the present invention. As shown in fig. 5, the device malfunction early warning device 5 of this embodiment includes: a processor 50, a memory 51 and a computer program 52, such as an equipment failure warning program, stored in said memory 51 and operable on said processor 50. When the processor 50 executes the computer program 52, the steps in the above embodiments of the device fault warning method, such as steps S201 to S204 shown in fig. 2, are implemented. Alternatively, the processor 50, when executing the computer program 52, implements the functions of the units/units in the above-mentioned device embodiments, such as the functions of the units 41 to 44 shown in fig. 4.
Illustratively, the computer program 52 may be divided into one or more units/units, which are stored in the memory 51 and executed by the processor 50 to accomplish the present invention. The one or more units/units may be a series of computer program instruction segments capable of performing specific functions, which are used to describe the execution process of the computer program 52 in the device malfunction alerting device 5. For example, the computer program 52 may be divided into an acquisition unit, a feature value analysis unit, an early warning value setting unit, and an alarm unit, each unit functioning as follows:
the acquisition unit is used for acquiring the running state parameter value of the equipment in real time during the characteristic value learning period;
the characteristic value analysis unit is used for acquiring a first characteristic value of the running state parameter according to the running state parameter value, wherein the first characteristic value indicates at least one of the following running state parameters in a set change interval when the equipment runs normally: maximum rate of change, maximum amplitude of change, maximum time;
the early warning value setting unit is used for obtaining the early warning value of the operating state parameter according to the first characteristic value;
and the alarm unit is used for acquiring the running state parameters of the equipment in real time during the equipment monitoring period, acquiring a second characteristic value of the running state parameters according to the running state parameter values during the equipment monitoring period, and giving an alarm if the second characteristic value is greater than the early warning value.
Optionally, the eigenvalue analysis unit includes:
the first analysis unit is used for calculating the maximum change amplitude, the maximum change rate or the maximum time of the running state parameter in a set change interval in real time;
the setting unit is used for taking the maximum change rate, the maximum change amplitude or the longest time as a first characteristic value of the running state parameter;
and the updating unit is used for updating the currently calculated maximum change rate, maximum change amplitude or maximum time to be the first characteristic value if the currently calculated maximum change rate, maximum change amplitude or maximum time is different from the first characteristic value during characteristic value learning.
Optionally, the early warning value setting unit further includes:
and the first early warning value setting unit is used for adding a preset adjusting value to the first characteristic value to obtain an early warning value of the running state parameter.
Optionally, the eigenvalue analysis unit further includes:
and the updating stopping unit is used for clearing the currently calculated first characteristic value and stopping updating the early warning value of the running state parameter if the equipment fails.
The device failure warning device 5 may include, but is not limited to, a processor 50 and a memory 51. It will be understood by those skilled in the art that fig. 5 is only an example of the device failure warning device 5, and does not constitute a limitation to the device failure warning device 5, and may include more or less components than those shown, or combine some components, or different components, for example, the device failure warning device 5 may further include an input/output device, a network access device, a bus, and the like.
The Processor 50 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The storage 51 may be an internal storage unit of the equipment failure warning device 5, such as a hard disk or a memory of the equipment failure warning device 5. The memory 51 may also be an external storage device of the device failure warning apparatus 5, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, which are equipped on the device failure warning apparatus 5. Further, the memory 51 may include both an internal storage unit provided with the malfunction early warning apparatus 5 and an external storage apparatus. The memory 51 is used for storing the computer program and other programs and data required by the device failure warning device. The memory 51 may also be used to temporarily store data that has been output or is to be output.
Referring to fig. 6, fig. 6 is a schematic structural diagram of an equipment failure early warning system according to an exemplary embodiment of the present invention. As shown in fig. 6, the equipment failure early warning system 6 in the embodiment of the present invention includes: the system comprises a field control system 61, a memory 62, a controller 63 and a computer program stored in the memory 62 and operable on the controller, wherein the field control system 61 is configured to obtain an operation state parameter value of a device in real time, and the controller implements the steps in each of the above embodiments of the device fault warning method when executing the computer program, for example, steps S201 to S204 shown in fig. 2. Alternatively, the controller 63, when executing the computer program, implements the functions of the units/units in the above-described device embodiments, such as the functions of the units 41 to 44 shown in fig. 4.
The field control system 61 is a system for controlling the operation of the device according to the operation parameters of the device, and may be an instrument control system, a PLC control system, a DCS system, or the like.
In an exemplary embodiment, the equipment failure early warning system 6 further includes: a switch 64 and a touch screen 65, wherein the switch 64 is connected to the field control system 61, the controller 63 and the touch screen 65 respectively; the switch 64 is configured to forward an operation state parameter value obtained by the field control system 61 in real time to the controller 63, receive an alarm signal sent by the controller 63, and forward the alarm signal to the touch screen 65 for display.
It will be clear to those skilled in the art that, for convenience and simplicity of description, the foregoing functional units and units are merely illustrated in terms of division, and in practical applications, the foregoing functional allocation may be performed by different functional units and units as needed, that is, the internal structure of the device is divided into different functional units or units to perform all or part of the above described functions. Each functional unit and unit in the embodiments may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and units are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The units in the system and the specific working processes of the units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus/terminal device and method may be implemented in other ways. For example, the above-described embodiments of the apparatus/terminal device are merely illustrative, and for example, the division of the unit or unit is only one logical division, and there may be other divisions when the actual implementation is performed, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated units/units, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. Based on such understanding, all or part of the flow of the method according to the embodiments of the present invention may also be implemented by a computer program, which may be stored in a computer-readable storage medium, and when the computer program is executed by a processor, the steps of the method embodiments may be implemented. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be noted that the computer readable medium may contain content that is subject to appropriate increase or decrease as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media does not include electrical carrier signals and telecommunications signals as is required by legislation and patent practice. The present invention is not limited to the above-described embodiments, and various modifications and variations of the present invention are intended to be included within the scope of the claims and the equivalent technology of the present invention if they do not depart from the spirit and scope of the present invention.
Claims (10)
1. An equipment fault early warning method is characterized by comprising the following steps:
acquiring the running state parameter value of the equipment in real time during the characteristic value learning period;
acquiring a first characteristic value of the running state parameter according to the running state parameter value, wherein the first characteristic value indicates at least one of the following running state parameters in a set change interval when the equipment runs normally:
maximum rate of change, maximum amplitude of change, maximum time;
acquiring an early warning value of the operating state parameter according to the first characteristic value;
and during the equipment monitoring period, acquiring the running state parameters of the equipment in real time, acquiring a second characteristic value of the running state parameters according to the running state parameter values during the equipment monitoring period, and if the second characteristic value is greater than the early warning value, giving an alarm.
2. The equipment fault early warning method according to claim 1, wherein the step of obtaining the first characteristic value of the operating state parameter according to the operating state parameter value comprises the steps of:
calculating at least one of the following running state parameters in a set change interval in real time: maximum change amplitude, maximum change rate, maximum time;
taking the maximum change rate, the maximum change amplitude or the maximum time as a first characteristic value of the operating state parameter;
during feature value learning, if the maximum change rate, the maximum change amplitude, or the maximum time currently calculated is different from the first feature value, the maximum change rate, the maximum change amplitude, or the maximum time currently calculated is updated to the first feature value.
3. The equipment fault early warning method according to claim 1, wherein the obtaining of the early warning value of the operating state parameter according to the operating state characteristic value comprises the steps of:
and adding a preset adjusting value to the first characteristic value to obtain an early warning value of the running state parameter.
4. The equipment fault early warning method according to claim 1, characterized in that: the operating condition parameters include temperature and/or pressure;
the first characteristic value includes at least one of:
the maximum average speed in the set continuous lifting interval, the maximum instantaneous speed in the set continuous lifting interval, the maximum change amplitude in the set continuous lifting interval, the maximum time in the set continuous lifting interval, the maximum average speed in the set accelerating continuous lifting interval, the maximum instantaneous speed in the set accelerating continuous lifting interval, the maximum time in the set accelerating continuous lifting interval, the maximum change amplitude in the set zigzag lifting interval and the maximum time in the set zigzag lifting interval.
5. The equipment fault early warning method according to claim 1, characterized in that: the operating state parameters comprise vibration amplitude and/or vibration frequency;
the first characteristic value includes at least one of:
the maximum vibration amplitude in the set operation speed interval, the maximum vibration frequency in the set operation speed interval and the maximum lifting speed of the vibration amplitude in the set operation speed interval.
6. The equipment fault early warning method according to claim 2, further comprising the steps of:
and if the equipment fails, clearing the currently calculated first characteristic value, and stopping updating the early warning value of the running state parameter.
7. An equipment fault early warning device, comprising:
the acquisition unit is used for acquiring the running state parameter value of the equipment in real time during the characteristic value learning period;
the characteristic value analysis unit is used for acquiring a first characteristic value of the running state parameter according to the running state parameter value, wherein the first characteristic value indicates at least one of the following running state parameters in a set change interval when the equipment runs normally:
maximum rate of change, maximum amplitude of change, maximum time;
the early warning value setting unit is used for obtaining the early warning value of the operating state parameter according to the first characteristic value;
and the alarm unit is used for acquiring the running state parameters of the equipment in real time during the equipment monitoring period, acquiring a second characteristic value of the running state parameters according to the running state parameter values during the equipment monitoring period, and giving an alarm if the second characteristic value is greater than the early warning value.
8. An equipment failure warning device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method according to any one of claims 1 to 6 when executing the computer program.
9. An equipment fault early warning system, comprising an on-site control system, a memory, a controller and a computer program stored in the memory and operable on the controller, the on-site control system being configured to obtain an operating state parameter value of an equipment in real time, characterized in that:
the steps of the method according to any one of claims 1 to 6 being implemented when the computer program is executed by the controller.
10. The equipment fault warning system of claim 9, further comprising: the switch is respectively connected with the controller, the field control system and the touch screen;
the switch is used for forwarding the operation state parameter values acquired by the field control system in real time to the controller, receiving the alarm signal sent by the controller and forwarding the alarm signal to the touch screen for display.
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| CN202010045895.6A CN111289036A (en) | 2020-01-16 | 2020-01-16 | Equipment fault early warning method, device, equipment and system |
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| Application Number | Priority Date | Filing Date | Title |
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| CN202010045895.6A CN111289036A (en) | 2020-01-16 | 2020-01-16 | Equipment fault early warning method, device, equipment and system |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN111738463A (en) * | 2020-06-17 | 2020-10-02 | 深圳华远云联数据科技有限公司 | Operation and maintenance method, device, system, electronic equipment and storage medium |
| CN114626707A (en) * | 2022-03-05 | 2022-06-14 | 中密控股股份有限公司 | Mechanical seal self-adaptive early warning method and device |
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| CN109901537A (en) * | 2019-03-18 | 2019-06-18 | 北京大通惠德科技有限公司 | Mechanical equipment method for monitoring operation states and system for edge calculations side |
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| CN105181019A (en) * | 2015-09-15 | 2015-12-23 | 安徽精科检测技术有限公司 | Computer program product for early fault early-warning and analysis of rotation type machine |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN111738463A (en) * | 2020-06-17 | 2020-10-02 | 深圳华远云联数据科技有限公司 | Operation and maintenance method, device, system, electronic equipment and storage medium |
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