CN117495592A - Alarm grading method and system for mine industrial Internet platform - Google Patents
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Abstract
The disclosure relates to an alarm classification method and system for a mine industrial Internet platform, wherein the method comprises the following steps: the method comprises the steps of obtaining a plurality of grades of each early warning parameter of mine equipment, giving corresponding preset weights to the plurality of grades, determining a first dangerous parameter value of a part of the plurality of early warning parameters including importance degree of the equipment, type of accidents, operation environment of the equipment and possibility of accident solving, determining a second dangerous parameter value of other plurality of early warning parameters, processing the first dangerous parameter value and the second dangerous parameter value according to preset association rules, obtaining final dangerous parameter values of a plurality of alarm events, processing the final dangerous parameter values of the plurality of alarm events according to preset fusion rules, and obtaining alarm events with reduced quantity. The invention can reduce the number of alarm events, improve the alarm value and enable the alarm events to be processed more efficiently.
Description
Technical Field
The embodiment of the disclosure relates to the technical field of coal mine early warning, in particular to an alarm grading method and system of an Internet platform in the mine industry.
Background
Currently, alarm classification standards for the coal mine industry include: gas alarm classification standards, dust concentration alarm classification standards, fire alarm classification standards and the like. However, in practical application, an alarm grading method for the whole coal mine condition is lacking, and if an accident occurs, each system can independently alarm according to the respective functions, and the alarms have no relevance.
Therefore, a method for grading and data fusion of coal mine alarm is required to be provided, so as to solve the problems that the alarm grading standard in the prior art is single, and the load of a server is too high due to a large number of equipment alarms.
It is noted that this section is intended to provide a background or context for the technical solutions of the present disclosure as set forth in the claims. The description herein is not admitted to be prior art by inclusion in this section.
Disclosure of Invention
An object of embodiments of the present disclosure is to provide an alarm classification method and system for a mine industrial internet platform, which further overcome one or more problems due to limitations and disadvantages of the related art to at least some extent.
The embodiment of the disclosure firstly provides an alarm classification method of a mine industrial internet platform, which comprises the following steps:
acquiring a plurality of grades of each early warning parameter of the mine equipment, and giving corresponding preset weights to the plurality of grades, wherein the early warning parameters comprise the importance degree of the equipment, the type of the accident, the operation environment of the equipment and the possibility of solving the accident;
determining first dangerous parameter values of a part of a plurality of early warning parameters;
determining second dangerous parameter values of other early warning parameters;
processing the first dangerous parameter value and the second dangerous parameter value according to a preset association rule to obtain final dangerous parameter values of a plurality of alarm events;
and processing final dangerous parameter values of a plurality of alarm events according to a preset fusion rule to obtain a reduced number of alarm events.
In one embodiment of the present disclosure, the association rule is: weights are set for both the first and second risk parameter values, and final risk parameter values for the plurality of alarm events are calculated based on the weights.
In an embodiment of the present disclosure, determining a first risk parameter value for a portion of a plurality of early warning parameters includes:
determining a first dangerous parameter value according to the first early warning parameter and the second early warning parameter;
determining a second risk parameter value for the other plurality of early warning parameters, comprising:
determining a second dangerous parameter value according to the third early warning parameter and the fourth early warning parameter;
the third early warning parameter is the same as or different from the second early warning parameter;
the sum of the weights of the first early warning parameter, the second early warning parameter, the third early warning parameter and the fourth early warning parameter is 1.
In an embodiment of the present disclosure, processing final dangerous parameter values of a plurality of alarm events according to a preset fusion rule to obtain a reduced number of alarm events includes:
obtaining final dangerous parameter value grades divided according to preset rules;
the number of alarm events is reduced according to the final risk parameter value level.
In one embodiment of the present disclosure, reducing the number of alarm events according to the final risk parameter value level includes:
increasing the alarm frequency of alarm events with high risk levels;
the alarm frequency of alarm events with low risk level is reduced.
In an embodiment of the present disclosure, obtaining a final risk parameter value level divided according to a preset rule includes:
presetting a threshold value of a risk level;
and comparing the final risk parameter value with a threshold value, and determining the risk level to which the final risk parameter value belongs according to the comparison result.
The embodiment of the disclosure also provides an alarm grading system of the mine industry internet platform, the system comprises:
the early warning parameter acquisition module is used for acquiring a plurality of grades of each early warning parameter of the mine equipment and giving corresponding preset weights to the grades, and the early warning parameters comprise the importance degree of the equipment, the type of the accident, the running environment of the equipment and the possibility of solving the accident;
the first dangerous parameter value determining module is used for determining first dangerous parameter values of a part of a plurality of early warning parameters, wherein the sum of weights of all the early warning parameters in the part of parameters is 1;
the second dangerous parameter value determining module is used for determining second dangerous parameter values of other early warning parameters, wherein the sum of weights of all other early warning parameters is 1;
the final risk parameter value calculation module is used for processing the first risk parameter value and the second risk parameter value according to a preset association rule to obtain final risk parameter values of a plurality of alarm events;
and the fusion processing module is used for processing the final dangerous parameter values of the plurality of alarm events according to a preset fusion rule to obtain the alarm events with reduced quantity.
In one embodiment of the present disclosure, the association rule is: weights are set for both the first and second risk parameter values, and final risk parameter values for the plurality of alarm events are calculated based on the weights.
In one embodiment of the present disclosure, a fusion processing module includes:
the risk level classification unit is used for acquiring the final risk parameter value level classified according to a preset rule;
and the alarm event processing unit is used for reducing the number of alarm events according to the final dangerous parameter value level.
In an embodiment of the present disclosure, an alarm event processing unit includes:
an alarm frequency increasing unit for increasing the alarm frequency of the alarm event with high risk level;
and the alarm frequency reducing unit is used for reducing the alarm frequency of the alarm event with low danger level.
The technical scheme provided by the embodiment of the disclosure can comprise the following beneficial effects:
according to the alarm grading method and system for the mine industrial Internet platform, the alarm result is more in accordance with the alarm requirement of the coal mine through setting the first dangerous parameter value and the second dangerous parameter value for part of the plurality of early warning parameters of the coal mine. And finally obtaining the final dangerous parameter value of the alarm event according to the set first dangerous parameter value and the set second dangerous parameter value and preset association rules for the first dangerous parameter value and the second dangerous parameter value, and carrying out fusion processing on the final dangerous parameter value according to the fusion rules, so that the number of the alarm event is reduced, the alarm value is improved, and the alarm event can be processed more efficiently.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the disclosure and together with the description, serve to explain the principles of the disclosure. It will be apparent to those of ordinary skill in the art that the drawings in the following description are merely examples of the disclosure and that other drawings may be derived from them without undue effort.
FIG. 1 illustrates a flow diagram of an alarm classification method for a mining industry Internet platform in an exemplary embodiment of the present disclosure;
FIG. 2 illustrates a flow diagram of processing final risk parameter values for a plurality of alarm events according to preset fusion rules to obtain a reduced number of alarm events in an exemplary embodiment of the present disclosure;
FIG. 3 illustrates a schematic diagram of an alarm classification system of an industrial Internet platform in an exemplary embodiment of the present disclosure;
FIG. 4 illustrates a schematic diagram of a fusion processing module in an exemplary embodiment of the present disclosure;
fig. 5 illustrates a schematic structural diagram of an electronic device in an exemplary embodiment of the present disclosure;
fig. 6 shows a schematic diagram of a program product for implementing an alarm ranking method of the mine industry internet platform in an exemplary embodiment of the present disclosure.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. However, the exemplary embodiments may be embodied in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of the example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
Furthermore, the drawings are merely schematic illustrations of embodiments of the disclosure and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and thus a repetitive description thereof will be omitted. Some of the block diagrams shown in the figures are functional entities and do not necessarily correspond to physically or logically separate entities.
In this example embodiment, firstly, an alarm classification method of a mine industrial internet platform is provided, please refer to fig. 1, which may include: step S101 to step S105. The method comprises the following steps:
step S101, a plurality of grades of each early warning parameter of the mine equipment are obtained, and corresponding preset weights are given to the plurality of grades, wherein the early warning parameters comprise the importance degree of the equipment, the type of the accident, the operation environment of the equipment and the possibility of accident solving.
For example, the plurality of early warning parameters may be, but not limited to, importance of the device, type of accident, operation environment of the device, possibility of accident resolution, and the like.
Further, in this embodiment, after the early warning parameters are obtained, based on a preset data character corresponding relationship, the early warning parameters are quantized, so as to obtain early warning parameters with uniform data formats: the importance degree Imo-eqi of the equipment, the accident type Typ-acc, the running environment Env-eqi of the equipment and the possibility Poa-acc of accident resolution.
Step S102, according to a first correlation combination of a plurality of early warning parameters, a first dangerous parameter value of the first correlation combination is determined.
The first dangerous parameter value may be determined by two mine parameter early warning parameters, for example, the first early warning parameter is a device type, a plurality of devices can be arranged under each device type, the second early warning parameter is an accident type, and the first dangerous parameter value Par-dan-1 is determined according to the device type kin-eqi and the accident type Typ-acc, and is as follows:
Par-dan-1＝log 2 (α·kin-eqi+β·Typ-acc)
wherein alpha and beta respectively represent a preset equipment type factor and a preset accident type factor. The above manner is used to represent the risk attribute at the device and incident type level by determining a first risk parameter value based on a combination of the device type and the incident type.
Step S103, determining a second dangerous parameter value of a second correlation combination according to the second correlation combination of the plurality of early warning parameters.
The early warning parameters in the second correlation combination and the first correlation combination can be partially the same. For example, the second risk parameter value may be determined from the third warning parameter and the fourth warning parameter, where the third warning parameter may be the same as or different from the second warning parameter.
Optionally, the third early warning parameter in the second correlation combination may be an operation environment Env-eqi, and the fourth early warning parameter may be a possibility Poa of accident resolution - acc, based on the above information, determines a second risk parameter value Par for the second correlation combination - dan - 2：
Par - dan - 2＝γ·sin Env - eqi+ε·cos Poa - acc
Wherein, gamma and epsilon respectively represent preset environmental factors and accident factors. The above approach is to embody the risk attribute at the incident and environment level by determining a second line parameter value based on a combination of the incident resolution likelihood and the operating environment.
In this embodiment, only the first risk parameter value and the second risk parameter value are taken as examples, and in this application, the number of risk parameters and the parameters of the early warning parameters are not specifically limited. The sum of the weights of the first early warning parameter, the second early warning parameter, the third early warning parameter and the fourth early warning parameter is 1.
Step S104, the first dangerous parameter value and the second dangerous parameter value are processed according to a preset association rule, and final dangerous parameter values of a plurality of alarm events are obtained.
Step S105, processing final dangerous parameter values of a plurality of alarm events according to a preset fusion rule to obtain a reduced number of alarm events.
In the embodiment, the first dangerous parameter value is set for part of the plurality of early warning parameters of the coal mine, and the second dangerous parameter value is set for part of the plurality of early warning parameters of the coal mine, so that the warning result meets the warning requirement of the coal mine. And finally obtaining the final dangerous parameter value of the alarm event according to the set first dangerous parameter value and the set second dangerous parameter value and preset association rules for the first dangerous parameter value and the second dangerous parameter value, and carrying out fusion processing on the final dangerous parameter value according to the fusion rules, so that the number of the alarm event is reduced, the alarm value is improved, and the alarm event can be processed more efficiently.
It should be noted that the association rule preset for the first risk parameter value and the second risk parameter value may be: weights are set for both the first and second risk parameter values, and final risk parameter values for the plurality of alarm events are calculated based on the weights. The final dangerous parameter value obtained by the weight setting has more practical value. On this basis, the weight of the first risk parameter value and the weight of the second risk parameter value are optionally set to 1, but are not limited thereto, and the final risk parameter values of the plurality of alarm events are obtained through calculation.
Optionally, in some embodiments, referring to fig. 2, step S105 may include steps S1051-S1052:
in step S1051, the final risk parameter value level classified according to the preset rule is obtained.
Step S1052, reducing the number of alarm events according to the final risk parameter value level.
In this embodiment, the final risk parameter value is subjected to risk level classification so as to perform corresponding processing on the alarm events with different risk levels, so that the alarm events can be properly processed, and the processing efficiency and the accuracy of solving the alarm problem are improved.
Optionally, in some embodiments, step S1051 may further include steps, specifically as follows:
a threshold value of the risk level is preset.
And comparing the final risk parameter value with a threshold value, and determining the risk level to which the final risk parameter value belongs according to the comparison result.
In this embodiment, for example, the threshold of the first level may be set to 0.1, and then alarm events smaller than 0.1 all belong to the first level hazard; setting the threshold value of the second level to be 0.2, and setting the alarm event which is more than or equal to 0.1 and less than 0.2 to be a second-level danger; and alarm events greater than or equal to 0.2 are all level 3 hazards. And comparing the final dangerous parameter value with the threshold value to further determine the dangerous level of the alarm event.
Optionally, in some embodiments, step S102 may further include
Increasing the alarm frequency of alarm events with high risk levels. For example, the alarm frequency of the alarm event with higher risk level is changed from once 5 seconds to once 2 seconds, so as to be quickly and maximally transferred to the receiving personnel, and prompt the receiving personnel to process the alarm event as soon as possible. The alarm event information can be sent to a preset terminal later, so that the staff members can learn the alarm event.
The alarm frequency of alarm events with low risk level is reduced. For example, the alarm frequency of the low risk level is changed from 5 seconds to 1 minute or 5 minutes. The information of the alarm event can be integrated into one alarm data packet for transmission.
In this embodiment, the alarm frequency is adjusted for the alarm events within a certain period of time, so that the number of alarm events can be reduced, and events with high dangerous levels can be processed more quickly, thereby preventing major accidents.
In order to more specifically describe the embodiments of the present application, a specific example will be described below.
1. Referring to table 1, according to the importance degree (first pre-warning parameter) of the equipment, the weight of the equipment (defining the weight of the whole system (equipment in the mine) so that the sum of the weights of all the equipment is 1) is determined, and the specific weight distribution situation is divided according to the importance degree of the equipment. For example, there are devices 1, 2, 3, and 4 in the system, and weights may be set to 0.2, 0.1, and 0.5, respectively, according to the importance of the devices.
Referring to table 1, according to the type of the accident (the second pre-warning parameter), the weight of the accident is determined (the weights of all accident types are defined so that the sum of the weights of all accident types is 1), the specific weight distribution condition is that all the accidents are classified according to the severity degree according to the consequences that the accident can cause, for example, there are accident 1, accident 2 and accident 3, and the weights corresponding to the accidents are determined to be 0.6, 0.3 and 0.1 according to the severity degree of the consequences of the accident.
TABLE 1 weighting of device importance and Accident type and determination of first risk parameter values
| Device type/Accident type | Accident 1 (0.6) | Accident 2 (0.3) | Accident 3 (0.1) |
| Equipment 1 (0.2) | 0.12 | 0.06 | 0.02 |
| Equipment 2 (0.2) | 0.12 | 0.06 | 0.02 |
| Equipment 3 (0.1) | 0.06 | 0.03 | 0.01 |
| Device 4 (0.5) | 0.3 | 0.15 | 0.05 |
First risk parameter values for the corresponding device at the time of the incident are then determined based on the type of device and the severity of the incident (e.g., the first risk parameter value is the product of the weight of the device and the weight of the incident, and the sum of all the first risk parameter values is 1).
As can be seen from table 1, in one alarm message, the set parameters include the device 3 and the accident 1, and the first risk parameter value is 0.06 according to the calculation.
Similarly, please refer to table 2, the second risk parameter value is obtained by calculating the weight distribution of the environment type (third pre-warning parameter) and the accident type.
TABLE 2 weight assignment of Environment type and Accident type and determination of second risk parameter values
| Environment type/Accident type | Accident 1 (0.6) | Accident 2 (0.3) | Accident 3 (0.1) |
| Environment 1 (0.15) | 0.09 | 0.045 | 0.015 |
| Environment 2 (0.25) | 0.15 | 0.075 | 0.025 |
| Environment 3 (0.6) | 0.36 | 0.18 | 0.06 |
As can be seen from table 2, the set parameters include environment 3 and accident 1, and the second risk parameter value according to the calculation is 0.36.
2. Determining a final risk parameter value based on the weights of the first risk parameter value and the second risk parameter value
For example, the weight ratio of the first risk parameter value to the second risk parameter value may be set to 1:1, and the final risk parameter value is equal to (0.06+0.36)/2=0.21.
3. Presetting a threshold value of a dangerous level, and determining the dangerous level of an alarm event
For example, thresholds of 0.1 and 0.20 may be set, i.e., a first-order hazard if the calculated final hazard parameter value is less than 0.1; if the calculated final dangerous parameter value is more than or equal to 0.1 and less than 0.20, the method belongs to secondary danger; if the calculated final dangerous parameter value is more than or equal to 0.20, the dangerous degree of the third-level danger, the second-level danger and the first-level danger is gradually reduced.
For example, the dangerous level of the coal mine may be classified into twelve levels by setting eleven thresholds, and specifically, the method of setting eleven thresholds is not particularly limited herein, and only after setting eleven thresholds, the dangerous level of the coal mine may be classified into twelve levels according to eleven thresholds. In practical application, the specific grading scheme of the coal mine danger is determined according to practical needs, and is not particularly limited herein.
The scheme provided by the scheme can be independently used for grading the coal mine danger degree, and can also be used for grading the alarm information sent by the equipment through a plurality of parameters, so that when the alarm information of the equipment is processed subsequently, the alarm information after grading can be processed further according to the alarm information, and the repeated description is omitted here.
4. Alarm data fusion
According to the continuous alarm of a certain device, and the same alarm accident, the final dangerous parameter value of the device is obtained, the time interval of the alarm information is adjusted according to the dangerous grade of the alarm time, if the dangerous grade of the alarm time is lower (first-level danger), the time interval of the alarm information is adjusted and increased (for example, the alarm of once in five seconds is adjusted to be accepted once in 5 minutes), and the alarm information of the device in the interval time is integrated into one alarm data packet to be sent;
if the alarm danger level is higher (secondary danger), the alarm information is pushed according to the normal frequency until the alarm is released.
If the alarm risk level is highest (three-level risk), the time interval for reducing the alarm information is adjusted (for example, an alarm is adjusted once for 5 seconds to an alarm for 2 seconds), and the alarm information of the device is sent to a preset terminal (the alarm information corresponding to the three-level risk is advertised).
According to a preset alarm processing flow, determining a receiving object (a processor) of alarm information corresponding to equipment, wherein the processor is used for enabling an alarm to be efficiently processed by a corresponding responsible person;
and according to the determined alarm processing time corresponding to the equipment, if the corresponding alarm information is not processed within the alarm processing time, sending the alarm information to the receiving object of the upper level of the receiving object according to a preset alarm processing flow.
In addition, an alarm operation manual can be formed according to the processing flow:
and recording the alarm and the processing flow to form an alarm operation manual, and transmitting the alarm information and the alarm operation manual to a receiving object when the same alarm exists next time.
According to the method and the device, the alarm information is divided into a plurality of grades through the importance degree of the device and the type of the accident, and the alarm data are fused according to the dangerous degree of the accident of the same grade, so that the problem that the underground alarm data quantity of the coal mine is large is solved.
In this embodiment, the alarm information sent by the device is classified by multiple parameters, so that when the alarm information of the device is processed later, further processing can be performed according to the alarm information after grading, and the scheme of the application also provides a scheme for performing fusion processing on the alarm information after grading, so that a huge amount of alarm information which needs to be processed by the original server is fused into a small amount of alarm information according to the alarm fusion rule of the scheme.
Next, in this exemplary embodiment, an alarm classification system of a mine industrial internet platform is provided, please refer to fig. 3, which may include: the early warning parameter acquisition module 201, the first risk parameter value determination module 202, the second risk parameter value determination module 203, the final risk parameter value calculation module 204 and the fusion processing module 205. Specifically, the early warning parameter obtaining module 201 is configured to obtain a plurality of levels of each early warning parameter of the mine equipment, and assign corresponding preset weights to the plurality of levels, where the early warning parameter includes an importance degree of the equipment, a type of an accident, an operation environment of the equipment, and a possibility of solving the accident; the first risk parameter value determining module 202 is configured to determine a first risk parameter value of a first correlation combination according to the first correlation combination of the plurality of early warning parameters; the second risk parameter value determining module 203 is configured to determine a second risk parameter value of a second correlation combination according to the second correlation combination of the plurality of early warning parameters; the final risk parameter value calculation module 204 is configured to process the first risk parameter value and the second risk parameter value according to a preset association rule, and obtain final risk parameter values of a plurality of alarm events; the fusion processing module 205 is configured to process final dangerous parameter values of the plurality of alarm events according to a preset fusion rule, and obtain a reduced number of alarm events.
In the embodiment, the first dangerous parameter value is set for part of the plurality of early warning parameters of the coal mine, and the second dangerous parameter value is set for part of the plurality of early warning parameters of the coal mine, so that the warning result meets the warning requirement of the coal mine. And finally obtaining the final dangerous parameter value of the alarm event according to the set first dangerous parameter value and the set second dangerous parameter value and preset association rules for the first dangerous parameter value and the second dangerous parameter value, and carrying out fusion processing on the final dangerous parameter value according to the fusion rules, so that the number of the alarm event is reduced, the alarm value is improved, and the alarm event can be processed more efficiently.
Wherein, the association rule may be: weights are set for both the first and second risk parameter values, and final risk parameter values for the plurality of alarm events are calculated based on the weights.
It should be understood that referring to fig. 4, the fusion processing module 205 includes: the risk level classification unit 2051 and the alarm event processing unit 2052. Specifically, the risk level classification unit 2051 is configured to obtain a final risk parameter value level classified according to a preset rule; the alarm event handling unit 2052 is configured to reduce the number of alarm events according to the final risk parameter value level.
In one embodiment, the hazard classification unit 2051 may further include: a threshold value presetting unit and a risk level determining unit. Specifically, the threshold value presetting unit is used for presetting a threshold value of the danger level; the risk level determining unit is used for comparing the final risk parameter value with a threshold value and determining the risk level to which the final risk parameter value belongs according to the comparison result.
In addition, in performing alarm event processing, the alarm event processing unit 2052 further includes: an alarm frequency increasing unit, and an alarm frequency decreasing unit. Specifically, the alarm frequency increasing unit is used for increasing the alarm frequency of the alarm event with high risk level; the alarm frequency reducing unit is used for reducing the alarm frequency of alarm events with low risk level.
The specific manner in which the various modules perform the operations in the apparatus of the above embodiments have been described in detail in connection with the embodiments of the method, and will not be described in detail herein.
It should be noted that although several modules of the system for action execution are mentioned in the detailed description above, this partitioning is not mandatory. Indeed, the features and functions of two or more modules described above may be embodied in one module in accordance with embodiments of the present invention. Conversely, the features and functions of one module described above may be further divided into a plurality of modules to be embodied. The components shown as modules may or may not be physical units, may be located in one place, or may be distributed across multiple network elements. Some or all of the modules may be selected according to actual needs to achieve the purposes of the present invention. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
Referring to fig. 5, an embodiment of the present invention also provides an electronic device 300, the electronic device 300 comprising at least one memory 310, at least one processor 320, and a bus 330 connecting the different platform systems.
Memory 310 may include readable media in the form of volatile memory, such as Random Access Memory (RAM) 211 and/or cache memory 312, and may further include Read Only Memory (ROM) 313.
The memory 310 further stores a computer program, where the computer program may be executed by the processor 320, so that the processor 320 executes the steps of the alarm classification method for the mine industrial internet platform according to any one embodiment of the present invention, and a specific implementation manner of the method is consistent with the implementation manner and the achieved technical effect described in the embodiment of the alarm classification method for the mine industrial internet platform, and some contents are not repeated.
Memory 310 may also include utility 314 having at least one program module 315, such program modules 315 include, but are not limited to: an operating system, one or more application programs, other program modules, and program data, each or some combination of which may include an implementation of a network environment.
Accordingly, processor 320 may execute the computer programs described above, as well as may execute utility 314.
Bus 330 may represent one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor, or a local bus using any of a variety of bus architectures.
The electronic device 300 may also communicate with one or more external devices 340, such as a keyboard, pointing device, bluetooth device, etc., as well as with one or more devices capable of interacting with the electronic device 300, and/or with any device (e.g., router, modem, etc.) that enables the electronic device 300 to communicate with one or more other computing devices. Such communication may occur through input-output interface 350. Also, electronic device 300 may communicate with one or more networks such as a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network, such as the Internet, through network adapter 360. The network adapter 360 may communicate with other modules of the electronic device 300 via the bus 330. It should be appreciated that although not shown, other hardware and/or software modules may be used in connection with electronic device 300, including, but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID systems, tape drives, data backup storage platforms, and the like.
The embodiment of the invention also provides a computer readable storage medium, which is used for storing a computer program, and the specific implementation mode of the computer program is consistent with the implementation mode and the achieved technical effect recorded in the embodiment of the alarm classification method of the mine industrial internet platform and is not repeated in part when the computer program is executed.
Fig. 6 shows a program product 400 provided by the present embodiment for implementing the alarm classification method of the mine industry internet platform described above, which may employ a portable compact disc read only memory (CD-ROM) and comprise program code, and which may be run on a terminal device, such as a personal computer. However, the program product 400 of the present invention is not limited thereto, and in the present invention, the readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. Program product 400 may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium can be, for example, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium would include the following: an electrical connection having one or more wires, a portable disk, a hard disk, random Access Memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
The computer readable storage medium may include a data signal propagated in baseband or as part of a carrier wave, with readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A readable storage medium may also be any readable medium that can transmit, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a readable storage medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing. Program code for carrying out operations of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C++ or the like and conventional procedural programming languages, such as the C programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device, partly on a remote computing device, or entirely on the remote computing device or server. In the case of remote computing devices, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., connected via the Internet using an Internet service provider).
The embodiments of the present invention have been described above with reference to the accompanying drawings, but the present invention is not limited to the above-described embodiments, which are merely illustrative and not restrictive, and many forms may be made by those having ordinary skill in the art without departing from the spirit of the present invention and the scope of the claims, which are to be protected by the present invention.
Claims (10)
1. An alarm grading method of a mine industrial internet platform is characterized by comprising the following steps:
acquiring a plurality of grades of each early warning parameter of the mine equipment, and giving corresponding preset weights to the plurality of grades, wherein the early warning parameters comprise the importance degree of the equipment, the type of the accident, the operation environment of the equipment and the possibility of solving the accident;
determining a first dangerous parameter value of a first relevant combination according to the first relevant combination of the plurality of early warning parameters;
determining a second dangerous parameter value of a second correlation combination according to the second correlation combination of the plurality of early warning parameters;
processing the first dangerous parameter value and the second dangerous parameter value according to a preset association rule to obtain final dangerous parameter values of a plurality of alarm events;
and processing final dangerous parameter values of a plurality of alarm events according to a preset fusion rule to obtain a reduced number of alarm events.
2. The alarm classification method of mine industry internet platform according to claim 1, wherein said association rule comprises:
the final risk parameter value for the plurality of alarm events is calculated based on the respective weights of the first risk parameter value and the second risk parameter value.
3. The alarm classification method of mine industrial internet platform according to claim 1, wherein the sum of the weights of the plurality of levels of each early warning parameter is 1.
4. The alarm classification method of mine industrial internet platform according to claim 1, wherein the processing of final risk parameter values of a plurality of alarm events according to a preset fusion rule to obtain a reduced number of alarm events comprises:
obtaining final dangerous parameter value grades divided according to preset rules;
the number of alarm events is reduced according to the final risk parameter value level.
5. The alarm classification method for mine industry internet platform according to claim 4, wherein obtaining the final risk parameter value level classified according to the preset rule comprises:
presetting a threshold value of a risk level;
and comparing the final risk parameter value with a threshold value, and determining the risk level to which the final risk parameter value belongs according to the comparison result.
6. The method of alarm classification for mine industry internet platforms of claim 4, wherein reducing the number of alarm events based on the final risk parameter value level comprises:
increasing the alarm frequency of alarm events with high risk levels;
the alarm frequency of alarm events with low risk level is reduced.
7. An alarm grading system of a mine industry internet platform, which is characterized by comprising:
the early warning parameter acquisition module is used for acquiring a plurality of grades of each early warning parameter of the mine equipment and giving corresponding preset weights to the grades, and the early warning parameters comprise the importance degree of the equipment, the type of the accident, the running environment of the equipment and the possibility of solving the accident;
the first dangerous parameter value determining module is used for determining a first dangerous parameter value of a first relevant combination according to the first relevant combination of the plurality of early warning parameters;
the second dangerous parameter value determining module is used for determining a second dangerous parameter value of a second correlation combination according to the second correlation combination of the plurality of early warning parameters;
the final risk parameter value calculation module is used for processing the first risk parameter value and the second risk parameter value according to a preset association rule to obtain final risk parameter values of a plurality of alarm events;
and the fusion processing module is used for processing the final dangerous parameter values of the plurality of alarm events according to a preset fusion rule to obtain the alarm events with reduced quantity.
8. The alarm classification system of mine industry internet platform according to claim 7, wherein the association rule is: the final risk parameter value for the plurality of alarm events is calculated based on the respective weights of the first risk parameter value and the second risk parameter value.
9. The alarm classification system of claim 7, wherein the fusion processing module comprises:
the risk level classification unit is used for acquiring the final risk parameter value level classified according to a preset rule;
and the alarm event processing unit is used for reducing the number of alarm events according to the final dangerous parameter value level.
10. The alarm ranking system of claim 9 in which the alarm event processing unit includes:
an alarm frequency increasing unit for increasing the alarm frequency of the alarm event with high risk level;
and the alarm frequency reducing unit is used for reducing the alarm frequency of the alarm event with low danger level.
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