CN116316613B - Power equipment operation monitoring method, system, electronic equipment and storage medium - Google Patents
Power equipment operation monitoring method, system, electronic equipment and storage medium Download PDFInfo
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Abstract
The invention discloses a power equipment operation monitoring method, a system, electronic equipment and a storage medium, and belongs to the technical field of power equipment operation monitoring. Acquiring historical operation information and historical environment information of the power equipment according to a preset time granularity; extracting historical fault data and historical maintenance information in the historical operation information, and determining the fault probability of the power equipment according to the historical fault data, the historical maintenance information and corresponding historical environment information; acquiring operation information at the current moment, extracting main parameters, and determining the current operation state of the power equipment according to the main parameters of the operation information; and determining the overhaul time of the power equipment according to the current running state, the fault probability and the historical maintenance information. The running state of the power equipment can be monitored in real time, and the overhaul time of the power equipment can be predicted; the problem of exist among the prior art "rely on-line monitoring, neglect to overhaul or overhaul frequency too high to power equipment, the manpower consumption is big" is solved.
Description
Technical Field
The present invention relates to the field of power equipment operation monitoring technologies, and in particular, to a power equipment operation monitoring method, a power equipment operation monitoring system, an electronic device, and a storage medium.
Background
The statements in this section merely relate to the background of the present disclosure and may not necessarily constitute prior art.
The power equipment mainly comprises two main types of power generation equipment and power supply equipment, and plays an important role in the operation of a power system. For a long time, the electric power system in China executes a regular maintenance system on electric power equipment, namely equipment is detected and maintained according to a planned time period, so that the defects of excessive maintenance and insufficient maintenance exist.
In the prior art, a power monitoring system collects real-time operation data of field devices through a plurality of sensors and analyzes the real-time operation data to monitor the operation state of the power devices. In the prior art, on one hand, only single operation information is considered, the influence of environmental factors and basic attributes of the power equipment on the state and the operation state of the power equipment is ignored, and the operation of the power equipment cannot be accurately monitored; on the other hand, the operation state is monitored on line only by using a sensor or the equipment is detected and maintained according to a planned time period, so that the problem that the abnormal operation of the power equipment cannot be found timely and accurately exists.
Disclosure of Invention
In order to solve the defects in the prior art, the invention provides a power equipment operation monitoring method, a system, electronic equipment and a storage medium, wherein the influence of factors such as environment, history maintenance information and the like on the operation of the power equipment is comprehensively considered, the overhaul time is determined according to the operation information and the fault probability of the power equipment, the excessive or insufficient overhaul is avoided, and the accuracy of the operation monitoring of the power equipment is improved.
In a first aspect, the present invention provides a method for monitoring operation of an electrical device;
the power equipment operation monitoring method comprises the following steps:
acquiring historical operation information of the power equipment and historical environment information associated with the historical operation information according to a preset time granularity;
extracting historical fault data and historical maintenance information in the historical operation information, and determining the fault probability of the power equipment according to the historical fault data, the historical maintenance information and corresponding historical environment information;
acquiring the operation information of the power equipment at the current moment, extracting main parameters affecting the operation state of the power equipment, and determining the current operation state of the power equipment according to the main parameters of the operation information;
and determining the overhaul time of the power equipment according to the current running state, the fault probability and the history maintenance information of the power equipment.
Further, the determining the fault probability of the power equipment according to the historical fault data and the corresponding historical environment information includes:
calculating a first influence factor of the environmental information on the power equipment fault according to the historical fault data and the corresponding historical environmental information;
calculating a second influence factor of the history maintenance information on the power equipment fault according to the history fault data and the history maintenance information;
determining a historical fault rate according to the historical fault frequency; and determining the fault rate according to the first influence factor, the second influence factor and the historical fault rate.
Preferably, the calculating the first influence factor of the environmental information on the power equipment fault according to the historical fault data and the corresponding historical environmental information specifically includes: and determining a first influence factor of the environmental information on the power equipment fault according to the real-time intensity of the abrupt change factor in the environmental information and the weight of the abrupt change factor in the historical environmental information.
Preferably, the calculating the second influence factor of the history maintenance information on the power equipment fault according to the history fault data and the history maintenance information specifically includes: and determining the fault frequency in the period before and after maintenance according to the operation years and the maintenance frequency of the power equipment in the historical maintenance information and combining the historical fault frequency in the historical fault data, and setting a second influence factor according to the fault frequency.
Further, the obtaining the operation information of the power equipment at the current moment and extracting the main parameters affecting the operation state of the power equipment include:
performing linear combination processing on the operation information to generate a monitoring parameter capable of reflecting the operation state of the power equipment;
according to the magnitude sequence of the characteristic values in the monitoring parameters of each component, calculating the weight occupied by the influence of each component on the running state of the power equipment according to the sequence result;
and filtering redundant information in the monitoring parameters according to the weight occupied by the influence of each component on the operation state of the power equipment and the operation characteristics of the power equipment.
Further, the determining, according to the main parameter, the current operation state of the power device specifically includes: and comparing the main parameters with a prestored operation state template library to determine the current operation state of the power equipment.
Further, determining the overhaul period time of the power equipment according to the current running state, the fault probability and the history maintenance information of the power equipment comprises:
if the current running state of the power equipment is abnormal, immediately sending alarm information to an overhauling personnel, and informing the overhauling personnel to overhaul;
if the running state of the power equipment is normal, determining an actual maintenance period according to the theoretical maintenance period and the history maintenance information of the power equipment; and determining the overhaul time of the power equipment according to the actual maintenance period of the power equipment and the fault probability of the power equipment.
In a second aspect, the present invention provides a power plant operation monitoring system;
an electrical device operation monitoring system comprising:
a failure probability acquisition module configured to: acquiring historical operation information of the power equipment and historical environment information associated with the historical operation information according to a preset time granularity; extracting historical fault data and historical maintenance information in the historical operation information, and determining the fault probability of the power equipment according to the historical fault data, the historical maintenance information and corresponding historical environment information;
an operating state acquisition module configured to: acquiring the operation information of the power equipment at the current moment, extracting main parameters affecting the operation state of the power equipment, and determining the current operation state of the power equipment according to the main parameters;
a service time prediction module configured to: and determining the overhaul time of the power equipment according to the current running state, the fault probability and the history maintenance information of the power equipment.
In a third aspect, the present invention provides an electronic device comprising a memory and a processor, and computer instructions stored on the memory and running on the processor, which when executed by the processor, perform the steps of the above-described power device operation monitoring method.
In a fourth aspect, the present invention provides a storage medium storing computer instructions that, when executed by a processor, perform the steps of the above-described power device operation monitoring method.
Compared with the prior art, the invention has the beneficial effects that:
1. according to the technical scheme provided by the invention, the historical operation information of the power equipment is analyzed by combining the environmental factors, the influence factors of the power equipment faults are obtained, the accurate prediction and early warning of the power equipment fault probability are realized, and the operator can find the potential safety hazard existing in the operation of the power equipment in time.
2. According to the technical scheme provided by the invention, the maintenance period, the current operation information of the power equipment and the fault probability are combined to determine the maintenance time, so that the manpower waste caused by overlong maintenance period and the potential safety hazard caused by overlong maintenance period are avoided, the maintenance efficiency is improved, and the safe operation of the power equipment is ensured.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the invention.
FIG. 1 is a schematic flow chart provided in an embodiment of the present invention;
fig. 2 is a schematic diagram of a system frame according to an embodiment of the present invention.
Detailed Description
It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the invention. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular forms also are intended to include the plural forms, and furthermore, it is to be understood that the terms "comprises" and "comprising" and any variations thereof are intended to cover non-exclusive inclusions, such as, for example, processes, methods, systems, products or devices that comprise a series of steps or units, are not necessarily limited to those steps or units that are expressly listed, but may include other steps or units that are not expressly listed or inherent to such processes, methods, products or devices.
Embodiments of the invention and features of the embodiments may be combined with each other without conflict.
Example 1
In the prior art, the maintenance period is fixed in the operation monitoring of the power equipment, the operation abnormality of the power equipment cannot be found in time, only the operation information of the power equipment is considered, the accuracy of the operation monitoring is low, and the time lag exists; accordingly, the present invention provides a power plant operation monitoring method.
Next, a detailed description will be given of the power equipment operation monitoring method disclosed in this embodiment with reference to fig. 1. The power equipment operation monitoring method comprises the following steps:
s1, acquiring historical operation information of the power equipment and historical environment information related to the historical operation information according to a preset time granularity.
Specifically, through setting up sensor module on power equipment, acquire every power equipment operation information and environmental information, sensor module installs inside power equipment's electronic tags, through power equipment's memory storage information for power equipment past and present operation information and environmental information all couple with electronic equipment's electronic identification, avoid data to appear chaotic phenomenon.
Further, in some embodiments, the sensor module includes a main control unit, a temperature sensor, a humidity sensor, a pressure sensor, a current sensor, and a deformation sensor, where the main control unit is in communication with the temperature sensor, the humidity sensor, the pressure sensor, the current sensor, and the deformation sensor, respectively, and the main control unit is in communication with a memory of the electronic tag, and the main control unit is in communication with a processor that executes the power device operation monitoring method of the present embodiment.
S2, extracting historical fault data and historical maintenance information in the historical operation information, and determining the fault probability of the power equipment according to the historical fault data, the historical maintenance information and the corresponding historical environment information. The method comprises the following steps:
s201, calculating a first influence factor of the environmental information on the power equipment faults according to the historical fault data and the corresponding historical environmental information.
Specifically, determining a first influence factor of the environmental information on the power equipment fault according to the real-time intensity of the abrupt change factor in the environmental information, the weight of the abrupt change factor in the historical environmental information and the historical fault rate caused by the abrupt change factor in the environmental information; the real-time intensity of the abrupt change factors can be the level of strong wind, the sudden drop of air temperature, the sudden rise of air temperature and ice coating. The concrete representation is as follows:
wherein A is a first influencing factor, a is a historical failure rate caused by a mutation factor in the environmental information,weight of class n abrupt factor in class m device, +.>And n is the influence weight of the real-time intensity of the mutation factors, n is the category of the mutation factors in the environmental information, and i is the number of the mutation factor categories in the environmental information.
wherein ,weighting the intensity of the n-th class of abrupt change factor in the m-th class of equipment>And d is month, which is the number of faults caused by the nth class mutation factor in the mth class of equipment.
wherein ,weight for the influence of the real-time intensity of the mutation factor, +.>Real-time intensity of mutation factor in environmental information, < + >>And m is the average value of the intensities of the abrupt change factors in the historical environment information, m is the type of the power equipment, and n is the type of the abrupt change factors in the environment information.
S202, calculating a second influence factor of the history maintenance information on the power equipment faults according to the history fault data and the history maintenance information.
Specifically, according to the operation years and the maintenance frequency of the power equipment in the history maintenance information, the second influence factor is set by combining the history fault frequency in the history fault data. The concrete representation is as follows:
wherein ,as the second influencing factor, H is the service life factor of the power equipment, i is the maintenance times，/>For the initial maintenance influence weight, β is 0.5 when a critical component in the power equipment that influences the operation state is maintained, and β is 0.2 when a normal component in the power equipment is maintained.
S203, determining a historical fault rate according to the historical fault frequency; and determining the fault rate according to the first influence factor, the second influence factor and the historical fault rate. The concrete representation is as follows;
wherein ,for failure rate->For the second influencing factor, A is the first influencing factor,>is a historical failure rate.
And S3, acquiring the operation information of the power equipment at the current moment, extracting main parameters affecting the operation state of the power equipment, and determining the current operation state of the power equipment according to the main parameters of the operation information. The method specifically comprises the following steps:
s301, performing linear combination processing on the operation information to generate monitoring parameters capable of reflecting the operation state of the power equipment; according to the magnitude sequence of the characteristic values in the monitoring parameters of each component, calculating the weight occupied by the influence of each component on the running state of the power equipment according to the sequence result; and filtering redundant information in the monitoring parameters according to the weight occupied by the influence of each component on the operation state of the power equipment and the operation characteristics of the power equipment.
The weight of each component on the operation state of the power equipment is expressed as:
wherein ,weight of each component for influencing the operating state of the power plant, < >>And r is the number of the parts of the power equipment, wherein the characteristic value corresponds to the monitoring parameter of the ith part.
S302, comparing the monitoring parameters after filtering the redundant information with a preset operation state template library to determine the operation state of the power equipment. The monitoring parameters can be generator rotating speed, gearbox oil temperature and the like, and the operation state template library is a state identification table established according to historical operation data and comprises threshold ranges of all monitoring parameters corresponding to normal operation states and threshold ranges of all monitoring parameters in abnormal operation states.
And S4, determining the overhaul time of the power equipment according to the current running state, the fault probability and the historical maintenance information of the power equipment. The method comprises the following steps:
s401, if the current running state of the power equipment is abnormal, immediately sending alarm information to an overhauling personnel, and informing the overhauling personnel to overhaul.
And if the running state of the power equipment is normal, determining an actual maintenance period according to the theoretical maintenance period and the history maintenance information of the power equipment. Specifically, according to the history maintenance information, determining a history maintenance period mean value; and determining an actual maintenance period according to the historical maintenance period mean value and the theoretical maintenance period. The concrete representation is as follows:
wherein a and b are preset weights.
S402, determining the overhaul time of the power equipment according to the actual maintenance period of the power equipment and the fault probability of the power equipment.
Specifically, if the current moment is less than five working days from the actual maintenance time and the fault probability of the power equipment is less than 30%, overhauling is carried out according to the actual maintenance period; if the fault probability of the power equipment is more than 50%, immediately overhauling; if the current moment is greater than five working days from the actual maintenance time and the fault probability of the power equipment is between 30% and 50%, overhauling the power equipment five working days in advance.
Example two
In connection with fig. 2, this embodiment discloses a power equipment operation monitoring system, including:
a failure probability acquisition module configured to: acquiring historical operation information of the power equipment and historical environment information associated with the historical operation information according to a preset time granularity; extracting historical fault data and historical maintenance information in the historical operation information, and determining the fault probability of the power equipment according to the historical fault data, the historical maintenance information and corresponding historical environment information;
an operating state acquisition module configured to: acquiring operation information of the power equipment at the current moment, and determining the current operation state of the power equipment according to the operation information;
a service time prediction module configured to: and determining the overhaul time of the power equipment according to the current running state, the fault probability and the history maintenance information of the power equipment.
Here, it should be noted that the above-mentioned failure probability obtaining module, operation state obtaining module, and maintenance time predicting module correspond to the steps in the first embodiment, and the above-mentioned modules are the same as the examples and application scenarios implemented by the corresponding steps, but are not limited to the disclosure of the first embodiment. It should be noted that the modules described above may be implemented as part of a system in a computer system, such as a set of computer-executable instructions.
Example III
The third embodiment of the invention provides an electronic device, which comprises a memory, a processor and computer instructions stored on the memory and running on the processor, wherein the steps of the power device running monitoring method are completed when the computer instructions are run by the processor.
Example IV
The fourth embodiment of the present invention provides a storage medium, configured to store computer instructions, where the computer instructions, when executed by a processor, complete the steps of the method for monitoring operation of an electrical device.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The foregoing embodiments are directed to various embodiments, and details of one embodiment may be found in the related description of another embodiment.
The above description is only of the preferred embodiments of the present invention and is not intended to limit the present invention, but various modifications and variations can be made to the present invention by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (7)
1. The power equipment operation monitoring method is characterized by comprising the following steps of:
acquiring historical operation information of the power equipment and historical environment information associated with the historical operation information according to a preset time granularity;
extracting historical fault data and historical maintenance information in the historical operation information, and determining the fault probability of the power equipment according to the historical fault data, the historical maintenance information and corresponding historical environment information;
acquiring the operation information of the power equipment at the current moment, extracting main parameters affecting the operation state of the power equipment, and determining the current operation state of the power equipment according to the main parameters;
determining maintenance time of the power equipment according to the current running state, fault probability and history maintenance information of the power equipment;
the determining the fault probability of the power equipment according to the historical fault data, the historical maintenance information and the corresponding historical environment information comprises the following steps:
determining a first influence factor of the environmental information on the power equipment fault according to the real-time intensity of the abrupt change factor in the environmental information and the weight of the abrupt change factor in the historical environmental information;
wherein the first influence factor is expressed as follows:
wherein A is a first influencing factor, a is a factor of environmentThe historical failure rate caused by abrupt factors in the information,weight of class n abrupt factor in class m device, +.>N is the influence weight of the real-time intensity of the mutation factors, n is the category of the mutation factors in the environmental information, and i is the number of the mutation factor categories in the environmental information;
wherein ,weight of class n abrupt factor in class m device, +.>The number of faults caused by the nth type mutation factors in the mth type equipment is the number of faults, and d is month;
wherein ,weight for the influence of the real-time intensity of the mutation factor, +.>Is the real-time intensity of the abrupt change factor in the environmental information,the average value of the mutation factor intensities in the historical environment information is represented by m, the category of the power equipment is represented by n, and the category of the mutation factor in the environment information is represented by n;
determining the fault frequency in the period before and after maintenance according to the operation years and maintenance frequency of the power equipment in the historical maintenance information and combining the historical fault frequency in the historical fault data, and setting a second influence factor according to the fault frequency;
wherein the second influence factor is expressed as:
wherein ,as the second influencing factor, H is the operating life factor of the electrical equipment, i is the number of maintenance operations,/->For initial maintenance impact weight, β is 0.5 when critical components in the power equipment that impact the operational status are maintained, and β is 0.2 when common components in the power equipment are maintained;
determining a historical fault rate according to the historical fault frequency; and determining the fault probability according to the first influence factor, the second influence factor and the historical fault rate.
2. The power equipment operation monitoring method according to claim 1, wherein the obtaining the operation information of the current time of the power equipment and extracting the main parameters affecting the operation state of the power equipment comprises:
performing linear combination processing on the operation information to generate a monitoring parameter capable of reflecting the operation state of the power equipment;
according to the magnitude sequence of the characteristic values in the monitoring parameters of each component, calculating the weight occupied by the influence of each component on the running state of the power equipment according to the sequence result;
and filtering redundant information in the monitoring parameters according to the weight occupied by the influence of each component on the operation state of the power equipment and the operation characteristics of the power equipment.
3. The method for monitoring operation of electrical equipment according to claim 1, wherein the determining the current operation state of the electrical equipment according to the main parameter is specifically: and comparing the main parameters with a prestored operation state template library to determine the current operation state of the power equipment.
4. The power equipment operation monitoring method of claim 1, wherein determining a service time of the power equipment based on the current operation state, the failure probability, and the history maintenance information of the power equipment comprises:
if the current running state of the power equipment is abnormal, immediately sending alarm information to an overhauling personnel, and informing the overhauling personnel to overhaul;
if the running state of the power equipment is normal, determining an actual maintenance period according to the theoretical maintenance period and the history maintenance information of the power equipment; and determining the overhaul time of the power equipment according to the actual maintenance period of the power equipment and the fault probability of the power equipment.
5. The utility model provides an electrical equipment operation monitoring system which characterized in that includes:
a failure probability acquisition module configured to: acquiring historical operation information of the power equipment and historical environment information associated with the historical operation information according to a preset time granularity; extracting historical fault data and historical maintenance information in the historical operation information, and determining the fault probability of the power equipment according to the historical fault data, the historical maintenance information and corresponding historical environment information;
the determining the fault probability of the power equipment according to the historical fault data, the historical maintenance information and the corresponding historical environment information comprises the following steps:
determining a first influence factor of the environmental information on the power equipment fault according to the real-time intensity of the abrupt change factor in the environmental information and the weight of the abrupt change factor in the historical environmental information;
wherein the first influence factor is expressed as follows:
wherein A is a first influencing factor, a is a historical failure rate caused by a mutation factor in the environmental information,weight of class n abrupt factor in class m device, +.>N is the influence weight of the real-time intensity of the mutation factors, n is the category of the mutation factors in the environmental information, and i is the number of the mutation factor categories in the environmental information;
wherein ,weight of class n abrupt factor in class m device, +.>The number of faults caused by the nth type mutation factors in the mth type equipment is the number of faults, and d is month;
wherein ,weight for the influence of the real-time intensity of the mutation factor, +.>Is the real-time intensity of the abrupt change factor in the environmental information,the average value of the mutation factor intensities in the historical environment information is represented by m, the category of the power equipment is represented by n, and the category of the mutation factor in the environment information is represented by n;
determining the fault frequency in the period before and after maintenance according to the operation years and maintenance frequency of the power equipment in the historical maintenance information and combining the historical fault frequency in the historical fault data, and setting a second influence factor according to the fault frequency;
wherein the second influence factor is expressed as:
wherein ,as the second influencing factor, H is the operating life factor of the electrical equipment, i is the number of maintenance operations,/->For initial maintenance impact weight, β is 0.5 when critical components in the power equipment that impact the operational status are maintained, and β is 0.2 when common components in the power equipment are maintained;
determining a historical fault rate according to the historical fault frequency; determining a fault probability according to the first influence factor, the second influence factor and the historical fault rate;
an operating state acquisition module configured to: acquiring the operation information of the power equipment at the current moment, extracting main parameters affecting the operation state of the power equipment, and determining the current operation state of the power equipment according to the main parameters;
a service time prediction module configured to: and determining the overhaul time of the power equipment according to the current running state, the fault probability and the history maintenance information of the power equipment.
6. An electronic device comprising a memory and a processor and computer instructions stored on the memory and running on the processor, which when executed by the processor, perform the power device operation monitoring method of any of claims 1-4.
7. A storage medium storing computer instructions which, when executed by a processor, perform the power device operation monitoring method of any one of claims 1-4.
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| CN117040137A (en) * | 2023-10-09 | 2023-11-10 | 国网山东省电力公司聊城供电公司 | Ring main unit temperature rise early warning method, system, terminal and medium based on multi-source data |
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