CN111243250B - Maintenance early warning method, device and equipment based on alarm data - Google Patents
Maintenance early warning method, device and equipment based on alarm data Download PDFInfo
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- CN111243250B CN111243250B CN201911364234.3A CN201911364234A CN111243250B CN 111243250 B CN111243250 B CN 111243250B CN 201911364234 A CN201911364234 A CN 201911364234A CN 111243250 B CN111243250 B CN 111243250B
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B29/00—Checking or monitoring of signalling or alarm systems; Prevention or correction of operating errors, e.g. preventing unauthorised operation
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B29/00—Checking or monitoring of signalling or alarm systems; Prevention or correction of operating errors, e.g. preventing unauthorised operation
- G08B29/18—Prevention or correction of operating errors
- G08B29/185—Signal analysis techniques for reducing or preventing false alarms or for enhancing the reliability of the system
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Abstract
The application discloses a maintenance early warning method, a maintenance early warning device and maintenance early warning equipment based on alarm data, wherein the method comprises the following steps: acquiring alarm data of any equipment, wherein the alarm data comprises alarm time and an alarm value; the alarm value is used for indicating whether an alarm signal exists at the corresponding alarm time; integrating alarm data with alarm time within a preset time influence range to obtain to-be-early-warning data of the equipment; inputting the data to be early-warned into a maintenance early-warning model, and obtaining a maintenance early-warning result of the equipment after the data is processed by the maintenance early-warning model; and the maintenance early warning result is used for indicating whether the equipment needs to be maintained currently. The method and the device can achieve maintenance early warning of the equipment based on the alarm data. Furthermore, the embodiment of the application combines the influence of time attenuation and alarm intensity on the maintenance early warning result to obtain the data to be early warned, and the data is processed by using the maintenance early warning model to obtain the maintenance early warning result of the equipment, so that the accuracy of the maintenance early warning result is further improved.
Description
Technical Field
The application relates to the field of data communication, in particular to a maintenance early warning method, device and equipment based on alarm data.
Background
Maintenance is a problem often faced in the industrial field, and equipment maintenance refers to the maintenance and repair of equipment. In order to prevent the performance degradation of the equipment or reduce the failure probability of the equipment, the industrial field usually maintains the equipment according to a predetermined plan or the management requirements of the equipment in the corresponding technical field.
However, depending on the frequency of use, the speed of performance degradation, and other factors, different devices may need to be maintained at different times. Therefore, how to determine whether to maintain the equipment currently based on the actual operation condition of the equipment so as to prevent the performance degradation of the equipment or reduce the probability of equipment failure is an urgent problem to be solved at present.
Disclosure of Invention
In view of this, the present application provides a maintenance early warning method, apparatus and device based on alarm data, which can implement maintenance early warning on a device based on discontinuous alarm data of the device, so as to determine whether to maintain the device currently based on an actual operation condition of the device.
In a first aspect, to achieve the above object, the present application provides a maintenance early warning method based on alarm data, where the method includes:
acquiring alarm data of any equipment, wherein the alarm data comprises alarm time and an alarm value; the alarm value is used for indicating whether an alarm signal exists at the corresponding alarm time or not;
integrating the alarm data of which the alarm time is within a preset time influence range to obtain data to be early-warned of the equipment;
inputting the data to be early-warned into a maintenance early-warning model, and obtaining a maintenance early-warning result of the equipment after the data is processed by the maintenance early-warning model; and the maintenance early warning result is used for indicating whether the equipment needs to be maintained currently.
In an optional embodiment, the integrating the alarm data of which the alarm time is within a preset time influence range to obtain the data to be early-warned of the device includes:
determining the alarm data with the alarm time within a preset time influence range as data to be integrated;
respectively setting a weight value for each alarm data in the data to be integrated based on the difference value between the alarm time of each alarm data in the data to be integrated and the current time;
and integrating the alarm value in each piece of alarm data in the data to be integrated based on the weight value to obtain the data to be early-warned of the equipment.
In an optional embodiment, the alarm data further includes an alarm signal type, the alarm signal type has a corresponding relationship with the alarm value, and the alarm value is used to indicate whether an alarm signal exists in the corresponding alarm signal type at the alarm time.
In an optional implementation manner, before the integrating the alarm data of which the alarm time is within the preset time influence range to obtain the data to be pre-warned of the device, the method further includes:
respectively setting a weighted value for each alarm signal type based on the alarm intensity degree corresponding to each alarm signal type;
correspondingly, the integration of the alarm data with the alarm time within the preset time influence range to obtain the to-be-early-warning data of the equipment includes:
determining the alarm data with the alarm time within a preset time influence range as data to be integrated;
and integrating the alarm value in each piece of alarm data in the data to be integrated based on the weight value of each alarm signal type to obtain the data to be early-warned of the equipment.
In an optional implementation manner, before the integrating the alarm data of which the alarm time is within the preset time influence range to obtain the data to be pre-warned of the device, the method further includes:
and combining alarm values corresponding to different alarm signal types in each alarm data based on the service importance degree and the alarm intensity degree corresponding to each alarm signal type.
In an optional embodiment, the alarm signal type in the alarm data has a corresponding device alarm portion; before the alarm data of which the alarm time is within the preset time influence range is integrated to obtain the data to be pre-warned of the equipment, the method further comprises the following steps:
and combining alarm values corresponding to the alarm signal types of the alarm parts with the same equipment in each alarm data.
In a second aspect, the present application further provides a maintenance early warning device based on alarm data, the device includes:
the device comprises an acquisition module, a processing module and a display module, wherein the acquisition module is used for acquiring alarm data of any equipment, and the alarm data comprises alarm time and an alarm value; the alarm value is used for indicating whether an alarm signal exists at the corresponding alarm time or not;
the integration module is used for integrating the alarm data of which the alarm time is within a preset time influence range to obtain the data to be early-warned of the equipment;
the processing module is used for inputting the data to be pre-warned into a maintenance pre-warning model and obtaining a maintenance pre-warning result of the equipment after the data to be pre-warned is processed by the maintenance pre-warning model; and the maintenance early warning result is used for indicating whether the equipment needs to be maintained currently.
In an alternative embodiment, the integration module includes:
the determining submodule is used for determining the alarm data with the alarm time within the preset time influence range as data to be integrated;
the setting submodule is used for respectively setting a weighted value for each piece of alarm data in the data to be integrated based on the difference value between the alarm time of each piece of alarm data in the data to be integrated and the current time;
and the integration submodule is used for integrating the alarm value in each piece of alarm data in the data to be integrated based on the weight value to obtain the data to be early-warned of the equipment.
In a third aspect, the present application provides a computer-readable storage medium having stored therein instructions that, when run on a terminal device, cause the terminal device to implement any of the methods described above.
In a fourth aspect, the present application provides an apparatus comprising: a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing the method of any one of the above when executing the computer program.
According to the maintenance early warning method based on the alarm data, the alarm data of the equipment are processed to obtain the data to be early warned, the data to be early warned can be used for maintenance early warning, the data to be early warned are processed by the maintenance early warning model, and finally the maintenance early warning result of the equipment is obtained so as to determine whether the equipment needs to be maintained at present. Therefore, the maintenance early warning of the equipment can be realized based on the alarm data.
Furthermore, the embodiment of the application combines the influence of time attenuation and alarm intensity on the maintenance early warning result to obtain the data to be early warned, and processes the data by using the maintenance early warning model to obtain the maintenance early warning result of the equipment. Therefore, the accuracy of the maintenance early warning result can be further improved on the basis of realizing the maintenance early warning of the equipment based on the alarm data.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive labor.
Fig. 1 is a flowchart of a maintenance early warning method based on alarm data according to an embodiment of the present disclosure;
fig. 2 is a flowchart of another maintenance early warning method based on alarm data according to an embodiment of the present disclosure;
fig. 3 is a schematic diagram of a structure of a maintenance early warning device based on alarm data according to an embodiment of the present application;
fig. 4 is a structural diagram of a maintenance early warning device based on alarm data according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
Because data acquisition of some equipment in the industrial field has certain difficulty, how to carry out maintenance early warning on the equipment based on limited data is a problem to be solved at present. The inventor encounters the following problem in practical application, namely how to realize the maintenance early warning for the equipment based on the discontinuous alarm data of the equipment. Because the data base is limited and the alarm data which can be acquired is discontinuous data, the problem how to solve the problem is difficult to solve.
The application provides a maintenance early warning method based on alarm data, which comprises the steps of processing the alarm data of equipment to obtain data to be early warned for maintenance early warning, processing the data to be early warned by using a maintenance early warning model, and finally obtaining a maintenance early warning result of the equipment so as to determine whether the equipment needs to be maintained currently. Therefore, the maintenance early warning of the equipment can be realized based on the alarm data.
The following application provides a maintenance early warning method based on alarm data, and with reference to fig. 1, is a flowchart of a maintenance early warning method based on alarm data according to an embodiment of the application, where the method includes:
s101: acquiring alarm data of any equipment, wherein the alarm data comprises alarm time and an alarm value; wherein the alarm value is used for indicating whether an alarm signal exists at the corresponding alarm time.
The alarm data of the equipment acquired by the embodiment of the application comprise alarm time and an alarm value, wherein the alarm value is used for indicating whether an alarm signal exists in the corresponding alarm time.
In an optional implementation manner, whether an alarm signal exists in any equipment can be detected at a preset frequency, the current time is taken as the alarm time of the current detection, and if the alarm signal exists in the equipment, the alarm value of the current detection is set to be 1; otherwise it may be set to 0. By the embodiment, the alarm data including the alarm time and the alarm value of the equipment can be acquired.
In another alternative embodiment, when the alarm signal is detected to exist in the device, the current time is acquired as the alarm time, and the alarm value of the alarm time is set to 1. Through the embodiment, the alarm data including the alarm time and the alarm value of the equipment can also be acquired.
S102: and integrating the alarm data of which the alarm time is within the preset time influence range to obtain the data to be early-warned of the equipment.
Because the influence of the alarm data within a certain time range on the current maintenance early warning is obvious, the time influence range is preset when the to-be-early-warning data used for the current maintenance early warning is determined, and the alarm data is integrated based on the preset time influence range to obtain the to-be-early-warning data.
In the embodiment of the present application, the time influence range may be set based on business experience, for example, the preset time influence range is 24 hours. In practical application, the alarm data with the alarm time within the last 24 hours from the current time can be obtained based on the alarm time in the alarm data, the alarm data are determined to be data to be integrated, then the alarm value of each piece of alarm data in the data to be integrated is accumulated, and the obtained accumulated value and the current time jointly form the data to be early-warned. The accumulated value can represent the alarm condition of the equipment within the last 24 hours so far, so that the accumulated value can be used for maintenance early warning to determine whether the equipment needs to be maintained currently.
In addition, due to the time attenuation principle, each piece of early warning data within the preset time influence range has different influences on the current maintenance early warning result, so that the embodiment of the application can respectively set the weight values for the alarm data based on the time attenuation principle to reflect the influences of the time attenuation on the current maintenance early warning result, and the accuracy of the maintenance early warning result is improved.
Specifically, the application provides a method for acquiring data to be early-warned based on a time attenuation principle, and firstly, determining the alarm data with the alarm time within a preset time influence range as the data to be integrated; secondly, respectively setting a weight value for each piece of alarm data in the data to be integrated based on the difference value between the alarm time of each piece of alarm data in the data to be integrated and the current time; and finally, integrating the alarm value in each piece of alarm data in the data to be integrated based on the weight value to obtain the data to be early-warned of the equipment. The larger the difference between the alarm time and the current time is, the smaller the influence of the alarm data corresponding to the alarm time on the maintenance early warning result is, and the smaller the weight value of the alarm data corresponding to the alarm time is; and vice versa.
In practical application, the method for integrating the alarm value in each piece of alarm data in the data to be integrated based on the weight value specifically includes accumulating the product of the alarm value of each piece of alarm data and the corresponding weight value to serve as the alarm value of the data to be pre-warned.
S103: inputting the data to be early-warned into a maintenance early-warning model, and obtaining a maintenance early-warning result of the equipment after the data is processed by the maintenance early-warning model; and the maintenance early warning result is used for indicating whether the equipment needs to be maintained currently.
Before the maintenance early warning is carried out on the equipment by using the maintenance early warning model, the maintenance early warning model is trained. Specifically, a data sample of the maintenance early-warning model is determined, and in practical application, a data sample corresponding to each piece of alarm data in the historical alarm data is determined respectively on the basis of the historical alarm data.
Specifically, taking any one of the historical alarm data as an example, acquiring alarm time of the alarm data as an end point, integrating the alarm data within a preset time influence range before the end point to obtain a data sample corresponding to the alarm data, and taking a current maintenance identifier corresponding to the alarm data as a label of the data sample. According to the mode, each piece of alarm data in the historical alarm data is integrated to obtain a data sample corresponding to each piece of alarm data, and finally a data sample set of the maintenance early warning model is formed. And training the maintenance early warning model by using the obtained data sample set to obtain the trained maintenance early warning model, and can be used for early warning the equipment maintenance.
In the embodiment of the application, the trained maintenance early warning model is used for processing the data to be early warned to obtain the maintenance early warning result of the equipment so as to determine whether the equipment needs to be maintained currently.
In the maintenance early warning method based on the alarm data provided by the embodiment of the application, the alarm data of the equipment is processed to obtain the data to be early warned, which can be used for maintenance early warning, the data to be early warned is processed by using the maintenance early warning model, and finally the maintenance early warning result of the equipment is obtained to determine whether the equipment needs to be maintained currently. Therefore, the maintenance early warning of the equipment can be realized based on the alarm data.
Generally, the alarm data includes not only alarm time and alarm value, but also alarm signal type, wherein the alarm signal type includes temperature alarm, pressure alarm, speed alarm, etc., specifically, the alarm signal type belonging to the same alarm data has a corresponding relationship with the alarm value, and the alarm value is used to indicate whether there is an alarm signal in the alarm time of the corresponding alarm signal type in the alarm data. If the type of the alarm signal is temperature alarm, the alarm value is 1, and the alarm time is 10:00, it can be shown that temperature alarm is acquired at 10: 00.
However, due to the large number of alarm signal types, there are typically as many as thousands of alarm signal types for a device, as shown in table 1:
| time \ alarm signal type | Signal 1 | Signal 2 | Signal 3 | Signal 4 | Signal 5 | …… | 1000+ |
| 19-11-5 05:20:15 | 1 | 1 | 1 | 1 | |||
| 19-11-5 20:08:20 | 1 | ||||||
| 19-11-5 20:25:10 | 1 | 1 | 1 | 1 | |||
| 19-11-6 07:30:15 | 1 | 1 | 1 | ||||
| 19-11-6 08:20:10 | 1 | 1 | 1 | ||||
| 19-11-6 10:42:35 | 1 | 1 |
TABLE 1
As can be seen from table 1, the alarm data has the characteristics of sparseness and higher dimensionality, and therefore, in order to improve subsequent processing efficiency, the embodiment of the present application may perform dimensionality reduction on the alarm data in advance.
In an optional implementation manner, the alarm values corresponding to different alarm signal types in each piece of alarm data may be combined based on the service importance degree and the alarm intensity degree corresponding to each alarm signal type, so as to implement the dimension reduction of the alarm data.
Specifically, for the types of alarm signals with lower service importance and alarm intensity, the alarm values corresponding to the types of alarm signals may be combined. For example, the alarm intensity of the signal 4 and the signal 5 in table 1 is low, and if the service importance of the signal 4 and the signal 5 is low, the signal 4 and the signal 5 in each piece of alarm data may be merged corresponding to the alarm value respectively to serve as the alarm value of the merged signal 4+ 5. As shown in table 2 below, where the signal 4+5 is a dimensionality reduction result obtained by combining the signal 4 and the signal 5 corresponding to the alarm values respectively.
TABLE 2
In another alternative embodiment, the alarm signal type in the alarm data typically has a corresponding device alarm location, for example, the alarm data including a temperature alarm and the device alarm location including a fan. The embodiment of the application can also combine the alarm values corresponding to the alarm signal types with the same equipment alarm part in each alarm data. For example, the fan may have a temperature alarm or a rotational speed alarm, and therefore, alarm values corresponding to alarm data including the fan may be combined, thereby achieving the dimension reduction of the alarm data.
Because different alarm signal types in the alarm data may have different influences on the equipment maintenance early warning, the embodiment of the application can set the weight value for each alarm signal type in the alarm data.
In an optional implementation manner, because the alarm intensity levels corresponding to different alarm signal types are different, and the more intensive the alarm intensity level is, the higher the urgency level for maintenance may be, therefore, in the embodiment of the present application, a weight value may be set for each alarm signal type respectively based on the alarm intensity level corresponding to each alarm signal type.
Specifically, the alarm data in a preset time period (for example, the last year) may be obtained, and then the alarm times corresponding to each alarm signal type in the alarm data in the time period are counted, and the alarm times are respectively used for indicating the alarm intensity of the corresponding alarm signal type.
In practical application, after the alarm data with the alarm time within the preset time influence range is determined as the data to be integrated, the alarm values in each piece of alarm data in the data to be integrated are integrated based on the determined weight value of each alarm signal type, so as to obtain the data to be early-warned of the equipment.
Based on the above embodiment, the application also provides a maintenance early warning method based on the alarm data, which analyzes the factors influencing the accuracy of the maintenance early warning result from two different dimensions, and finally improves the accuracy of the maintenance early warning result.
Specifically, referring to fig. 2, a flowchart of another maintenance early warning method based on alarm data provided by the present application is shown, where the method includes:
s201: acquiring alarm data of any equipment, wherein the alarm data comprises alarm time, an alarm value and an alarm signal type; wherein the alarm value is used for indicating whether an alarm signal exists in the corresponding alarm signal type at the alarm time.
S202: and determining the alarm data with the alarm time within the preset time influence range as the data to be integrated.
S203: and respectively setting a weight value for each alarm data in the data to be integrated based on the difference value between the alarm time of each alarm data in the data to be integrated and the current time.
S204: and respectively setting a weight value for each alarm signal type based on the alarm intensity corresponding to each alarm signal type.
S201-S204 can be understood with reference to the above embodiments, and will not be described herein.
S205: and integrating the alarm value in each piece of alarm data in the data to be integrated by combining the weight value of each piece of alarm data and the weight value of each type of the alarm signal to obtain the data to be early-warned of the equipment.
In the embodiment of the application, after the weight value of each piece of alarm data in the data to be integrated is determined, the alarm data in the integrated data can be integrated from the horizontal direction of the tables 1 and 2, and the influence of time attenuation on the maintenance early warning result is reflected. In addition, after the weight value of each alarm signal type is determined, the alarm data in the data to be integrated can be integrated from the longitudinal direction of the tables 1 and 2, so that the influence of the alarm intensity on the maintenance early warning result is reflected. By combining the transverse and longitudinal weight setting, the accuracy of the maintenance early warning result can be further improved.
In an alternative embodiment, the acquisition of the data to be warned of the device may be implemented by the following formula (1), as follows:
wherein alpha is a time attenuation coefficient, beta is an influence coefficient, and the alpha and the beta are all preset constants between 0 and 1. X represents data to be pre-warned, X is a warning value in the warning data with warning time in a preset time influence range, the value of the warning signal is defaulted to be 1, and if the warning values corresponding to the types of the warning signals are combined, the value is a combined value; t is a target time point, namely a time point for whether maintenance is carried out or not in the early warning; t is tnFor alarm times within a predetermined time influence range, tn-1For t within a predetermined time influence rangenThe alarm time of the previous alarm data.
S206: inputting the data to be early-warned into a maintenance early-warning model, and obtaining a maintenance early-warning result of the equipment after the data is processed by the maintenance early-warning model; and the maintenance early warning result is used for indicating whether maintenance is required to be carried out on the equipment at present.
The acquisition of each data sample of the maintenance early warning model in the embodiment of the application is the same as the acquisition of the data to be early warned, and details are not repeated here. The maintenance early warning model which completes training by using the data sample is used for processing the data to be early warned of the equipment to obtain the maintenance early warning result of the equipment so as to indicate whether the equipment needs to be maintained at present.
The maintenance early warning method based on the alarm data provided by the embodiment of the application combines the influence of time attenuation and alarm intensity on the maintenance early warning result to obtain the data to be early warned, and processes the data by using the maintenance early warning model to obtain the maintenance early warning result of the equipment. Therefore, the accuracy of the maintenance early warning result can be further improved on the basis of realizing the maintenance early warning of the equipment based on the alarm data.
Corresponding to the above method embodiment, the present application further provides a maintenance early warning device based on alarm data, and referring to fig. 3, a schematic structural diagram of the maintenance early warning device based on alarm data provided in the embodiment of the present application is provided, where the device includes:
an obtaining module 301, configured to obtain alarm data of any device, where the alarm data includes alarm time and an alarm value; the alarm value is used for indicating whether an alarm signal exists at the corresponding alarm time or not;
an integration module 302, configured to integrate the alarm data of which the alarm time is within a preset time influence range, so as to obtain to-be-early-warning data of the device;
the processing module 303 is configured to input the data to be pre-warned into a maintenance pre-warning model, and obtain a maintenance pre-warning result of the device after the data is processed by the maintenance pre-warning model; and the maintenance early warning result is used for indicating whether the equipment needs to be maintained currently.
Wherein the integration module comprises:
the determining submodule is used for determining the alarm data with the alarm time within the preset time influence range as the data to be integrated;
the setting submodule is used for respectively setting a weighted value for each piece of alarm data in the data to be integrated based on the difference value between the alarm time of each piece of alarm data in the data to be integrated and the current time;
and the integration submodule is used for integrating the alarm value in each piece of alarm data in the data to be integrated based on the weight value to obtain the data to be early-warned of the equipment.
In an optional embodiment, the alarm data further includes an alarm signal type, the alarm signal type has a corresponding relationship with the alarm value, and the alarm value is used to indicate whether an alarm signal exists in the corresponding alarm signal type at the alarm time.
In an alternative embodiment, the apparatus further comprises:
the setting module is used for setting a weight value for each alarm signal type respectively based on the alarm intensity degree corresponding to each alarm signal type;
accordingly, the integration module comprises:
the determining submodule is used for determining the alarm data with the alarm time within the preset time influence range as the data to be integrated;
and the first integration submodule is used for integrating the alarm value in each piece of alarm data in the data to be integrated based on the weighted value of each alarm signal type to obtain the data to be early-warned of the equipment.
In an alternative embodiment, the apparatus further comprises:
and the first merging module is used for merging the alarm values corresponding to different alarm signal types in each alarm data based on the service importance degree and the alarm intensity degree corresponding to each alarm signal type.
In an optional embodiment, the alarm signal type in the alarm data has a corresponding device alarm portion; the device further comprises:
and the second merging module is used for merging the alarm values corresponding to the alarm signal types with the same equipment alarm part in each alarm data.
In the maintenance early warning method based on the alarm data provided by the embodiment of the application, the alarm data of the equipment is processed to obtain the data to be early warned, which can be used for maintenance early warning, the data to be early warned is processed by using the maintenance early warning model, and finally the maintenance early warning result of the equipment is obtained to determine whether the equipment needs to be maintained currently. Therefore, the maintenance early warning of the equipment can be realized based on the alarm data.
Furthermore, the embodiment of the application combines the influence of time attenuation and alarm intensity on the maintenance early warning result to obtain the data to be early warned, and processes the data by using the maintenance early warning model to obtain the maintenance early warning result of the equipment. Therefore, the accuracy of the maintenance early warning result can be further improved on the basis of realizing the maintenance early warning of the equipment based on the alarm data.
In addition, an embodiment of the present application further provides a maintenance early warning device based on alarm data, as shown in fig. 4, which may include:
a processor 401, a memory 402, an input device 403, and an output device 404. The number of processors 401 in the maintenance pre-warning device based on the alarm data may be one or more, and one processor is taken as an example in fig. 4. In some embodiments of the present invention, the processor 401, the memory 402, the input device 403, and the output device 404 may be connected by a bus or other means, wherein the connection by the bus is illustrated in fig. 4.
The memory 402 may be used to store software programs and modules, and the processor 401 executes various functional applications and data processing of the maintenance and early warning device based on the alarm data by operating the software programs and modules stored in the memory 402. The memory 402 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required for at least one function, and the like. Further, the memory 402 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device. The input means 403 may be used to receive input numeric or character information and generate signal inputs related to user settings and function control of the maintenance warning device based on the warning data.
Specifically, in this embodiment, the processor 401 loads an executable file corresponding to a process of one or more application programs into the memory 402 according to the following instructions, and the processor 401 runs the application program stored in the memory 402, thereby implementing various functions of the maintenance and early warning device based on the alarm data.
In addition, the application also provides a computer-readable storage medium, wherein instructions are stored in the computer-readable storage medium, and when the instructions are run on the terminal equipment, the terminal equipment is enabled to realize a maintenance and early warning function based on the alarm data.
It is understood that for the apparatus embodiments, since they correspond substantially to the method embodiments, reference may be made to the partial description of the method embodiments for relevant points. The above-described embodiments of the apparatus are merely illustrative, and 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 modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The maintenance early warning method, the maintenance early warning device and the maintenance early warning equipment based on the alarm data provided by the embodiment of the application are introduced in detail, a specific example is applied to explain the principle and the implementation mode of the application, and the description of the embodiment is only used for helping to understand the method and the core idea of the application; meanwhile, for a person skilled in the art, according to the idea of the present application, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present application.
Claims (8)
1. A maintenance early warning method based on alarm data is characterized by comprising the following steps:
acquiring alarm data of any equipment, wherein the alarm data comprises alarm time and an alarm value; the alarm value is used for indicating whether an alarm signal exists at the corresponding alarm time or not;
integrating the alarm data of which the alarm time is within a preset time influence range to obtain data to be early-warned of the equipment; and
inputting the data to be early-warned into a maintenance early-warning model, and obtaining a maintenance early-warning result of the equipment after the data is processed by the maintenance early-warning model; the maintenance early warning result is used for indicating whether the equipment needs to be maintained currently;
the alarm data also comprises an alarm signal type, the alarm signal type and the alarm value have a corresponding relation, and the alarm value is used for indicating whether the corresponding alarm signal type has an alarm signal at the alarm time;
before the alarm data of which the alarm time is within the preset time influence range is integrated to obtain the data to be pre-warned of the equipment, the method further comprises the following steps:
and combining alarm values corresponding to different alarm signal types in each alarm data based on the service importance degree and the alarm intensity degree corresponding to each alarm signal type.
2. The method according to claim 1, wherein the integrating the alarm data of which the alarm time is within a preset time influence range to obtain the data to be early-warned of the equipment comprises:
determining the alarm data with the alarm time within a preset time influence range as data to be integrated;
respectively setting a weight value for each alarm data in the data to be integrated based on the difference value between the alarm time of each alarm data in the data to be integrated and the current time;
and integrating the alarm value in each piece of alarm data in the data to be integrated based on the weight value to obtain the data to be early-warned of the equipment.
3. The method according to claim 1, wherein before the integrating the alarm data of which the alarm time is within the preset time influence range to obtain the data to be pre-warned of the equipment, the method further comprises:
respectively setting a weighted value for each alarm signal type based on the alarm intensity degree corresponding to each alarm signal type;
correspondingly, the integration of the alarm data with the alarm time within the preset time influence range to obtain the to-be-early-warning data of the equipment includes:
determining the alarm data with the alarm time within a preset time influence range as data to be integrated;
and integrating the alarm value in each piece of alarm data in the data to be integrated based on the weight value of each alarm signal type to obtain the data to be early-warned of the equipment.
4. The method of claim 1, wherein the alarm signal type in the alarm data has a corresponding device alarm location; before the alarm data of which the alarm time is within the preset time influence range is integrated to obtain the data to be pre-warned of the equipment, the method further comprises the following steps:
and combining alarm values corresponding to the alarm signal types of the alarm parts with the same equipment in each alarm data.
5. A maintenance early warning device based on alarm data is characterized in that the device comprises:
the device comprises an acquisition module, a processing module and a display module, wherein the acquisition module is used for acquiring alarm data of any equipment, and the alarm data comprises alarm time and an alarm value; the alarm value is used for indicating whether an alarm signal exists at the corresponding alarm time or not;
the integration module is used for integrating the alarm data of which the alarm time is within a preset time influence range to obtain the data to be early-warned of the equipment; and
the processing module is used for inputting the data to be pre-warned into a maintenance pre-warning model and obtaining a maintenance pre-warning result of the equipment after the data to be pre-warned is processed by the maintenance pre-warning model; the maintenance early warning result is used for indicating whether the equipment needs to be maintained currently;
the alarm data also comprises an alarm signal type, the alarm signal type and the alarm value have a corresponding relation, and the alarm value is used for indicating whether the corresponding alarm signal type has an alarm signal at the alarm time;
before the alarm data of which the alarm time is within the preset time influence range is integrated to obtain the data to be pre-warned of the equipment, the method further comprises the following steps:
and combining alarm values corresponding to different alarm signal types in each alarm data based on the service importance degree and the alarm intensity degree corresponding to each alarm signal type.
6. The apparatus of claim 5, wherein the integration module comprises:
the determining submodule is used for determining the alarm data with the alarm time within the preset time influence range as the data to be integrated;
the setting submodule is used for respectively setting a weighted value for each piece of alarm data in the data to be integrated based on the difference value between the alarm time of each piece of alarm data in the data to be integrated and the current time;
and the integration submodule is used for integrating the alarm value in each piece of alarm data in the data to be integrated based on the weight value to obtain the data to be early-warned of the equipment.
7. A computer-readable storage medium having stored therein instructions which, when run on a terminal device, cause the terminal device to implement the method of any one of claims 1-4.
8. An apparatus, comprising: memory, a processor, and a computer program stored on the memory and executable on the processor, when executing the computer program, implementing the method of any of claims 1-4.
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