CN113537643A - Internet-based power equipment life prediction algorithm - Google Patents
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Abstract
The invention provides an algorithm for predicting the service life of power equipment based on the Internet, which comprises the following steps: collecting operation evaluation parameters of the power equipment; the second step is that: setting the ratio of related parameters; the third step: carrying out multi-dimensional comprehensive analysis and demonstration on the reliability of the evaluation parameters; the fourth step: and outputting the life prediction time information of the power equipment. The invention combines the arithmetic data operation, analyzes various parameters of the equipment running in the near time, and through the precise calculation and deviation analysis of software, the data is summarized in the form of bar-shaped graphs and curves, and the multidimensional comprehensive analysis and demonstration such as the production time, the commissioning time, the maintenance times and the certification and qualification data related to manufacturers of the equipment are combined, thereby effectively reducing the error of the service life scrapping time of the equipment and improving the market competitiveness.
Description
Technical Field
The invention relates to the technical field of service life detection of internet power equipment, in particular to an algorithm based on service life prediction of the internet power equipment.
Background
With the continuous development and progress of scientific technology and modern industry, mechanical equipment is developing towards large-scale, complicated, high-speed and the like. The influence of the mechanical equipment on daily life and production of people is larger and more obvious. Once equipment fails, not only can serious economic loss be brought, but also personal safety can be threatened. The equipment is evaluated and the service life is predicted, so that the fault can be found early, the development trend of the fault is predicted, the accidents can be prevented, the safety of human bodies and mechanical equipment is ensured, a basis is provided for maintenance decisions, and the economic benefit and the social benefit of enterprises are improved. It is therefore important to evaluate the operating state of the equipment and to predict the life of the equipment.
Therefore, the invention is urgently needed to create an algorithm for predicting the service life of electric or mechanical equipment, and whether certain equipment is in a scrapped stage or not in a certain time period is obtained by taking the actual operating conditions of the field as reference bases for the good and bad operation quality of the equipment, so that the error of the scrapped time of the service life of the equipment is effectively reduced, and the market competitiveness is improved.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide an algorithm for predicting the service life of power equipment based on the Internet, and solves the problems in the prior art.
In order to achieve the purpose, the invention is realized by the following technical scheme: an algorithm based on internet power equipment service life prediction comprises an equipment parameter acquisition module, a management platform, a data analysis module and a data evaluation output module, wherein,
the equipment parameter acquisition module comprises a current acquisition unit, a voltage acquisition unit, an electric equipment load acquisition unit and an equipment information acquisition unit which are respectively connected with the management platform so as to be connected with a management platform port through a built digital interface and transmit a parameter measurement conversion result to the management platform to acquire the analog quantity of the electric equipment;
the data analysis module is connected with the management platform and used for evaluating and analyzing the related parameters of the electric power equipment processed by the management platform, and a multi-dimensional comprehensive analysis algorithm is arranged in the data analysis module and used for reducing the error of the service life scrapping time of the equipment after being analyzed and output;
the data evaluation output module is connected with the data analysis module and used for outputting the service life prediction time information of the power equipment, and the data evaluation output module comprises the following steps:
the first step is as follows: collecting operation rating parameters of power equipment
Acquiring a current parameter, a voltage parameter, a load parameter and an electric equipment operation parameter of the electric equipment in an operation process;
the second step is that: setting the ratio of the related parameters
Carrying out proportion setting on the obtained rating parameters based on a multi-dimensional comprehensive analysis algorithm, and calculating to obtain the corresponding weight of each rating parameter;
the third step: multidimensional comprehensive analysis and demonstration of evaluation parameter reliability
After deviation analysis is carried out on the evaluation parameters through software, data are summarized in a bar graph or curve mode, and the service life and the scrapping time of the power equipment are obtained by combining the production time, the commissioning time, the maintenance times of the power equipment and relevant qualified data of manufacturers;
the fourth step: and outputting the service life prediction time information of the power equipment.
As an improvement of the internet-based power equipment life prediction algorithm in the present invention, in the third step, the specific implementation manner of the multidimensional comprehensive analysis algorithm is as follows:
s3-1, collecting basic information of the equipment, wherein the basic information comprises the production date of the equipment, the commissioning time of the equipment, relevant information of qualified quality of the equipment, the operation environment of the equipment, important parameter performance indexes of the equipment, the manufacturing level of an equipment manufacturer, the normal use scrapping date of the equipment and the information of whether the equipment is maintained or not and the maintenance times;
s3-2, acquiring electrical data of the equipment within 12 months after operation, wherein the electrical data comprise current, line voltage, phase voltage, active electric energy, reactive electric energy, power factors, active power, reactive power and harmonic data;
and S3-3, fusing the electrical data and the basic information, giving corresponding weight to the electrical data and the basic information, and expressing the weight in a ratio form, wherein the electrical data accounts for 70% and the basic information accounts for 30%, so that the information influencing the normal operation of the equipment is accurately analyzed and evaluated.
As an improvement of the algorithm for predicting the service life of the power equipment based on the Internet, the operation parameters of the power equipment comprise the ambient environment parameters of the operation of the power equipment, the production time parameters of the power equipment, the commissioning time parameters of the power equipment, the manufacturer parameters of the power equipment and the maintenance frequency parameters of the power equipment.
As an improvement of the internet-based power equipment service life prediction algorithm, the equipment information acquisition unit comprises an equipment manufacturer information acquisition subunit, an equipment production time acquisition subunit and an equipment maintenance information acquisition subunit.
As an improvement to the algorithm for predicting the service life of the internet-based power equipment in the present invention, based on step S3-3, when the weight output by the management platform accounts for 60% to 85%, the algorithm is a critical value for the power equipment to fail.
Compared with the prior art, the invention has the beneficial effects that:
the invention combines the arithmetic data operation, analyzes various parameters of the equipment running in the near time, and through the precise calculation and deviation analysis of software, the data is summarized in the form of bar-shaped graphs and curves, and the multidimensional comprehensive analysis and demonstration such as the production time, the commissioning time, the maintenance times and the certification and qualification data related to manufacturers of the equipment are combined, thereby effectively reducing the error of the service life scrapping time of the equipment and improving the market competitiveness.
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The disclosure of the present invention is illustrated with reference to the accompanying drawings. It is to be understood that the drawings are designed solely for purposes of illustration and not as a definition of the limits of the invention, for which like reference numerals are used to indicate like parts. Wherein:
fig. 1 is a block diagram of a lifetime prediction structure of an internet-based power device according to an embodiment of the present invention;
fig. 2 is a schematic flow chart of an internet-based power equipment life prediction algorithm according to an embodiment of the present invention;
fig. 3 is a block diagram of a device parameter acquisition module according to an embodiment of the present invention.
Detailed Description
It is easily understood that according to the technical solution of the present invention, a person skilled in the art can propose various alternative structures and implementation ways without changing the spirit of the present invention. Therefore, the following detailed description and the accompanying drawings are merely illustrative of the technical aspects of the present invention, and should not be construed as all of the present invention or as limitations or limitations on the technical aspects of the present invention.
As shown in fig. 1 and 3, the present invention provides a technical solution as an embodiment of the present invention: an algorithm based on internet power equipment service life prediction comprises an equipment parameter acquisition module, a management platform, a data analysis module and a data evaluation output module, wherein,
the equipment parameter acquisition module comprises a current acquisition unit, a voltage acquisition unit, an electrical equipment load acquisition unit and an equipment information acquisition unit which are respectively connected with the management platform so as to be connected with a port of the management platform through a built digital interface and transmit a parameter measurement conversion result to the management platform to acquire the analog quantity of the electrical equipment;
the data analysis module is connected with the management platform and used for evaluating and analyzing the related parameters of the electric power equipment processed by the management platform, and a multi-dimensional comprehensive analysis algorithm is arranged in the data analysis module and used for reducing the error of the service life scrapping time of the equipment after analysis and output;
the data evaluation output module is connected with the data analysis module and used for outputting the life prediction time information of the power equipment, as shown in fig. 2, and comprises the following steps:
the first step is as follows: collecting operation rating parameters of power equipment
Acquiring a current parameter, a voltage parameter, a load parameter and an electric equipment operation parameter of the electric equipment in an operation process;
the second step is that: setting the ratio of the related parameters
Carrying out proportion setting on the obtained rating parameters based on a multi-dimensional comprehensive analysis algorithm, and calculating to obtain the corresponding weight of each rating parameter;
the third step: multidimensional comprehensive analysis and demonstration of evaluation parameter reliability
After deviation analysis is carried out on the evaluation parameters through software, data are summarized in a bar graph or curve mode, and the service life and scrapping time of the power equipment are obtained by combining the production time, commissioning time and maintenance times of the power equipment and relevant qualified data proved by manufacturers;
the fourth step: and outputting the life prediction time information of the power equipment.
As an embodiment of the present invention, in the third step, a specific implementation manner of the multidimensional comprehensive analysis algorithm is as follows:
s3-1, collecting basic information of the equipment, wherein the basic information comprises the production date of the equipment, the commissioning time of the equipment, relevant information of qualified quality of the equipment, the operation environment of the equipment, important parameter performance indexes of the equipment, the manufacturing level of an equipment manufacturer, the normal use scrapping date of the equipment and the information of whether the equipment is maintained or not and the maintenance times;
s3-2, acquiring electrical data of the equipment within 12 months after operation, wherein the electrical data comprise current, line voltage, phase voltage, active electric energy, reactive electric energy, power factors, active power, reactive power and harmonic data;
s3-3, fusing the electrical data and the basic information, giving corresponding weight to the electrical data and the basic information, and expressing the weight in a form of percentage, wherein the electrical data accounts for 70%, the basic information accounts for 30%, accurate analysis and evaluation of information influencing normal operation of equipment are achieved, each piece of information can influence the normal operation of the equipment, and in specific implementation:
when the weight output by the platform accounts for 60%, a user needs to strengthen the monitoring of the equipment, and when the weight reaches 85%, the equipment needs to be replaced in time, and the service life of the equipment is judged to be about to be stopped, so that the economic loss caused by sudden failure of the equipment is reduced.
As an embodiment of the present invention, the power equipment operation parameters include a peripheral environment parameter of the power equipment operation, a power equipment production time parameter, a power equipment commissioning time parameter, a power equipment manufacturer parameter, and a power equipment maintenance frequency parameter.
As an embodiment of the present invention, the device information collecting unit includes a device manufacturer information collecting subunit, a device production time collecting subunit, and a device maintenance information collecting subunit.
In an embodiment of the present invention, the present invention has the following advantages:
the invention combines the arithmetic data operation, analyzes various parameters of the equipment running in the near time, and through the precise calculation and deviation analysis of software, the data is summarized in the form of bar-shaped graphs and curves, and the multidimensional comprehensive analysis and the argumentation such as the production time, the commissioning time, the maintenance times and the certification qualified data related to manufacturers are combined, thereby effectively reducing the error of the service life scrapping time of the equipment and improving the market competitiveness.
The technical scope of the present invention is not limited to the above description, and those skilled in the art can make various changes and modifications to the above-described embodiments without departing from the technical spirit of the present invention, and such changes and modifications should fall within the protective scope of the present invention.
Claims (5)
1. An algorithm based on internet power equipment life prediction is characterized in that: comprises an equipment parameter acquisition module, a management platform, a data analysis module and a data evaluation output module, wherein,
the equipment parameter acquisition module comprises a current acquisition unit, a voltage acquisition unit, an electric equipment load acquisition unit and an equipment information acquisition unit which are respectively connected with the management platform so as to be connected with a management platform port through a built digital interface and transmit a parameter measurement conversion result to the management platform to acquire the analog quantity of the electric equipment;
the data analysis module is connected with the management platform and used for evaluating and analyzing the related parameters of the electric power equipment processed by the management platform, and a multi-dimensional comprehensive analysis algorithm is arranged in the data analysis module and used for reducing the error of the service life scrapping time of the equipment after being analyzed and output;
the data evaluation output module is connected with the data analysis module and used for outputting the service life prediction time information of the power equipment, and the data evaluation output module comprises the following steps:
the first step is as follows: collecting operation rating parameters of power equipment
Acquiring a current parameter, a voltage parameter, a load parameter and an electric equipment operation parameter of the electric equipment in an operation process;
the second step is that: setting the ratio of the related parameters
Carrying out proportion setting on the obtained rating parameters based on a multi-dimensional comprehensive analysis algorithm, and calculating to obtain the corresponding weight of each rating parameter;
the third step: multidimensional comprehensive analysis and demonstration of evaluation parameter reliability
After deviation analysis is carried out on the evaluation parameters through software, data are summarized in a bar graph or curve mode, and the service life and the scrapping time of the power equipment are obtained by combining the production time, the commissioning time, the maintenance times of the power equipment and relevant qualified data of manufacturers;
the fourth step: and outputting the service life prediction time information of the power equipment.
2. The internet-based power equipment life prediction algorithm of claim 1, wherein: in the third step, the specific implementation manner of the multidimensional comprehensive analysis algorithm is as follows:
s3-1, collecting basic information of the equipment, wherein the basic information comprises the production date of the equipment, the commissioning time of the equipment, relevant information of qualified quality of the equipment, the operation environment of the equipment, important parameter performance indexes of the equipment, the manufacturing level of an equipment manufacturer, the normal use scrapping date of the equipment and the information of whether the equipment is maintained or not and the maintenance times;
s3-2, acquiring electrical data of the equipment within 12 months after operation, wherein the electrical data comprise current, line voltage, phase voltage, active electric energy, reactive electric energy, power factors, active power, reactive power and harmonic data;
and S3-3, fusing the electrical data and the basic information, giving corresponding weight to the electrical data and the basic information, and expressing the weight in a ratio form, wherein the electrical data accounts for 70% and the basic information accounts for 30%, so that the information influencing the normal operation of the equipment is accurately analyzed and evaluated.
3. The internet-based power equipment life prediction algorithm of claim 1, wherein: the power equipment operation parameters comprise a power equipment operation peripheral environment parameter, a power equipment production time parameter, a power equipment commissioning time parameter, a power equipment manufacturer parameter and a power equipment maintenance frequency parameter.
4. The internet-based power equipment life prediction algorithm of claim 1, wherein: the equipment information acquisition unit comprises an equipment manufacturer information acquisition subunit, an equipment production time acquisition subunit and an equipment maintenance information acquisition subunit.
5. The internet-based power equipment life prediction algorithm of claim 2, wherein: and based on the step S3-3, when the weight output by the management platform accounts for 60% -85%, the power equipment is a failure critical value.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114429250A (en) * | 2022-04-06 | 2022-05-03 | 深圳市玄羽科技有限公司 | Fault prediction method and device applied to industrial Internet and electronic equipment |
| CN114488996A (en) * | 2021-12-27 | 2022-05-13 | 山东浪潮工业互联网产业股份有限公司 | Equipment health monitoring and early warning method and system |
| CN115982942A (en) * | 2022-11-25 | 2023-04-18 | 浙江长龙航空有限公司 | Method, device, equipment and storage medium for predicting residual life of aviation precooler |
-
2021
- 2021-08-20 CN CN202110963153.6A patent/CN113537643A/en not_active Withdrawn
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114488996A (en) * | 2021-12-27 | 2022-05-13 | 山东浪潮工业互联网产业股份有限公司 | Equipment health monitoring and early warning method and system |
| CN114429250A (en) * | 2022-04-06 | 2022-05-03 | 深圳市玄羽科技有限公司 | Fault prediction method and device applied to industrial Internet and electronic equipment |
| CN115982942A (en) * | 2022-11-25 | 2023-04-18 | 浙江长龙航空有限公司 | Method, device, equipment and storage medium for predicting residual life of aviation precooler |
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