CN116050781A - Enterprise intelligent management system based on industrial Internet - Google Patents
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Abstract
The invention discloses an enterprise intelligent management system based on an industrial Internet, which relates to the technical field of enterprise energy consumption management, and solves the technical problems that when specific energy consumption monitoring is processed, equipment abnormal signals are generated due to equipment energy consumption data fluctuation, misjudgment is caused, and when the designated area is subjected to energy consumption management and control, the yield of the corresponding area is caused to slide down, so that the energy consumption management and control effect is poor.
Description
Technical Field
The invention belongs to the technical field of enterprise energy consumption management, and particularly relates to an enterprise intelligent management system based on an industrial Internet.
Background
The industrial internet is a novel infrastructure, an application mode and industrial ecology which are deeply fused with new generation information communication technology and industrial economy, and a brand new manufacturing and service system which covers a full industrial chain and a full value chain is constructed by comprehensively connecting people, machines, objects, systems and the like, so that an implementation way is provided for the development of industrialization and even industrialization digitization, networking and intellectualization, and the industrial internet is an important foundation stone of the fourth industrial revolution.
The invention of patent publication number CN114492875A relates to the technical field of intelligent energy management systems, and discloses an intelligent energy management system based on the industrial Internet, which comprises an energy consumption online management system, wherein the output end of the energy consumption online management system is electrically connected with a data acquisition unit, a real-time monitoring unit, a remote meter reading unit, a report management unit and a comprehensive management unit.
In the specific implementation process, the conventional enterprise intelligent management system generally generates equipment abnormal signals due to equipment energy consumption data fluctuation during specific energy consumption monitoring processing, so that erroneous judgment occurs, and meanwhile, when the designated area is subjected to energy consumption management and control, the yield of the corresponding area is caused to slide downwards to cause poor energy consumption management and control effect.
Disclosure of Invention
The present invention aims to solve at least one of the technical problems existing in the prior art; therefore, the invention provides an enterprise intelligent management system based on the industrial Internet, which is used for solving the technical problems that during specific energy consumption monitoring processing, equipment abnormal signals are generated generally due to fluctuation of equipment energy consumption data, so that erroneous judgment occurs, and meanwhile, when the designated area is subjected to energy consumption management and control, the yield of the corresponding area is reduced, so that the energy consumption management and control effect is poor.
To achieve the above objective, an embodiment according to a first aspect of the present invention provides an industrial internet-based enterprise intelligent management system, which includes an equipment data acquisition end, an equipment data analysis end, a maintenance center, a storage center, a regional data analysis end, and a regional energy consumption management and control end;
the device data acquisition end is used for acquiring device data of workshops in different areas of an enterprise and transmitting the acquired device data into the device data analysis end;
the equipment data analysis end is used for receiving the equipment data, analyzing the equipment energy consumption parameters, obtaining corresponding processing parameter values according to the pre-warning times and the pre-warning time length in the corresponding time period, marking different equipment as abnormal equipment or normal equipment according to the processing parameter values, generating different binding data packages, and transmitting the different binding data packages to the maintenance center;
the maintenance center receives the binding data packet, extracts the serial number and the abnormal signal of the abnormal equipment in the binding data packet according to the received binding data packet, and dispatches external maintenance personnel;
the regional data analysis end analyzes abnormal equipment data existing in different regions, wherein the abnormal equipment data comprise the number of abnormal equipment and specific abnormal energy consumption values of the abnormal equipment, marks the different regions according to analysis processing results, and transmits regional workshops marked as abnormal regions to the regional energy consumption management and control end to perform energy consumption management and control processing work;
the regional energy consumption management and control terminal acquires workshop data of the abnormal region according to the marks, wherein the workshop data comprises yield data and total energy data, sequentially analyzes the workshop data of a plurality of groups of different abnormal regions, classifies the different abnormal regions into standard good regions or standard difference regions, and manages and controls the standard good regions or the standard difference regions by adopting different management and control modes.
Preferably, the specific way for the device data analysis end to analyze the device energy consumption parameter is as follows:
limiting a monitoring period T, wherein the T takes a value of 24h, acquiring corresponding energy consumption data from equipment data, and marking the energy consumption data of different equipment as NH i Wherein i represents different devices, wherein i=1, 2, … …, n, the preset parameter Y1 is extracted from the storage center;
energy consumption data NH i Comparing with a preset parameter Y1, when NH i When less than Y1, no treatment is carried out, otherwise, the corresponding energy consumption data NH is obtained i Marking as abnormal data;
in the monitoring period T, acquiring the number of times of existence of the abnormal data, and marking the number of times of existence of the abnormal data as CS i Acquiring the existence time length of the abnormal data, and marking the existence time length of the abnormal data as SC i Wherein the unit of time length is h;
by using
Obtaining processing parameter CL belonging to different equipment i Will process the parameter value CL i Comparing with the preset parameter Y2, when CL i And if the number is less than Y2, not performing any processing, otherwise, marking the corresponding equipment as abnormal equipment, binding the number of the abnormal equipment and the abnormal signal, generating a binding data packet, and transmitting the binding data packet into a maintenance center.
Preferably, the specific way for the area data analysis end to analyze the abnormal device data is as follows:
marking the number of abnormal devices as GS k Wherein k represents different regions, wherein i represents different devices, wherein i=1, 2, … …, n, and the abnormal energy consumption values of different abnormal devices in different regions are marked as NH k-i ；
Extracting corresponding preset parameters Y3 from the storage center, wherein the preset parameters Y3 are empirically drawn by operators, and XH is adopted k-i ＝NH k-i Y3 obtains the energy consumption value XH exceeded by each group of different anomalous devices k-i By using
Obtaining the total energy consumption parameter ZH exceeded by different areas k ；
By QU k ＝GS k ×C3+ZH k XC 4 obtaining the determination parameters QU for different regions k And determine the parameter QU k Comparing with the preset parameter Y4 in the storage center, wherein the specific value of the preset parameter Y4 is determined by an operator according to experience, when QU k When the value is less than Y4, no processing signal is generated, otherwise, the corresponding region is marked as an abnormal region;
and transmitting the regional workshop mark k marked as the abnormal region into the regional energy consumption management and control end.
Preferably, the specific way for the regional energy consumption management and control end to sequentially analyze the workshop data of multiple groups of different abnormal regions is as follows:
marking yield data for different abnormal area workshops as CL t-o Wherein t represents different abnormal area workshops, o represents different yield data, wherein t ε k, will correspond to yield data CL t-o The corresponding total energy consumption data is marked as ZT t-o By using
Obtaining the corresponding guide factor D t-o ；
Determining an abnormal region workshop t, and obtaining a maximum guide factor D in the abnormal region workshop t t-omax ；
Directing the maximum to factor D t-omax Sequentially comparing with the preset parameter Y5, when D t-omax Y5, classifying the corresponding abnormal region workshop t as a standard deviation region, and otherwise classifying the corresponding abnormal region workshop t as a standard deviation region;
when the energy consumption control is carried out on the abnormal area workshop t belonging to the standard area, the energy source is not changed, and staff is controlled;
when the energy consumption control is carried out on the abnormal area workshop t belonging to the standard deviation area, the conveying energy is reduced, the specific reduction parameters are automatically drawn by operators, and then the operators are controlled in real time.
Compared with the prior art, the invention has the beneficial effects that: analyzing the energy consumption parameters of the equipment, obtaining corresponding processing parameter values according to the pre-warning times and the pre-warning time length in the corresponding time period, and marking different equipment as abnormal equipment or normal equipment according to the processing parameter values;
and analyzing abnormal equipment data existing in different areas, classifying the different abnormal areas into a standard good area or a standard bad area according to analysis processing results, and performing control processing on the standard good area or the standard bad area by adopting different control modes.
Drawings
Fig. 1 is a schematic diagram of a principle frame of the present invention.
Detailed Description
The technical solutions of the present invention will be clearly and completely described in connection with the embodiments, and it is obvious that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, the application provides an enterprise intelligent management system based on an industrial internet, which comprises an equipment data acquisition end, an equipment data analysis end, a maintenance center, a storage center, a regional data analysis end and a regional energy consumption management and control end;
the device data acquisition end output end is in bidirectional connection with the device data analysis end input end, the device data analysis end is in bidirectional connection with the maintenance center, the device data analysis end is in bidirectional connection with the storage center, the device data analysis end output end is electrically connected with the region data analysis end input end, and the region data analysis end output end is electrically connected with the region energy consumption control end input end;
the equipment data acquisition end is used for acquiring equipment data of workshops in different areas of the enterprise and transmitting the acquired equipment data into the equipment data analysis end;
the device data analysis end receives device data, analyzes device energy consumption parameters, obtains corresponding processing parameter values according to the pre-warning times and the pre-warning time length existing in the corresponding time period, and marks different devices as abnormal devices or normal devices according to the processing parameter values, wherein the specific mode of processing is as follows:
limiting a monitoring period T, wherein the T takes a value of 24h, acquiring corresponding energy consumption data from equipment data, and marking the energy consumption data of different equipment as NH i Wherein i represents different devices, wherein i=1, 2, … …, n, the preset parameter Y1 is extracted from the storage center;
energy consumption data NH i Comparing with a preset parameter Y1, when NH i When less than Y1, no treatment is carried out, otherwise, the corresponding energy consumption data NH is obtained i Marking as abnormal data;
in the monitoring period T, acquiring the number of times of existence of the abnormal data, and marking the number of times of existence of the abnormal data as CS i Acquiring the existence time length of the abnormal data, and marking the existence time length of the abnormal data as SC i Wherein the unit of time length is h;
by using
Obtaining processing parameter CL belonging to different equipment i Will process the parameter value CL i Comparing with the preset parameter Y2, when CL i And if the number is less than Y2, not performing any processing, otherwise, marking the corresponding equipment as abnormal equipment, binding the number of the abnormal equipment and the abnormal signal, generating a binding data packet, and transmitting the binding data packet into a maintenance center.
Wherein the preset parameters Y1 and Y2 are provided by a storage center, and the specific values of Y1 and Y2 are drawn by an operator according to experience;
the maintenance center receives the binding data packet, extracts the serial numbers and the abnormal signals of the abnormal equipment in the binding data packet according to the received binding data packet, dispatches external maintenance personnel to enable the maintenance personnel to reach the appointed abnormal equipment point, and maintains and processes the abnormal equipment.
The area data analysis end analyzes abnormal equipment data existing in different areas, wherein the abnormal equipment data comprises the number of abnormal equipment and specific abnormal energy consumption values of the abnormal equipment, different areas are marked according to analysis processing results, and area workshops marked as abnormal areas are transmitted into the area energy consumption management and control end to perform energy consumption management and control processing work, wherein the specific mode for analyzing the abnormal equipment data is as follows:
marking the number of abnormal devices as GS k Wherein k represents different regions, wherein i represents different devices, wherein i=1, 2, … …, n, and the abnormal energy consumption values of different abnormal devices in different regions are marked as NH k-i ；
Extracting corresponding preset parameters Y3 from the storage center, wherein the preset parameters Y3 are empirically drawn by operators, and XH is adopted k-i ＝NH k-i Y3 obtains the energy consumption value XH exceeded by each group of different anomalous devices k-i By using
Obtaining the total energy consumption parameter ZH exceeded by different areas k ；
By QU k ＝GS k ×C3+ZH k XC 4 obtaining the determination parameters QU for different regions k And determine the parameter QU k Comparing with the preset parameter Y4 in the storage center, wherein the specific value of the preset parameter Y4 is determined by an operator according to experience, when QU k When the value is less than Y4, no processing signal is generated, otherwise, the corresponding region is marked as an abnormal region;
and transmitting the regional workshop mark k marked as the abnormal region into the regional energy consumption management and control end.
The regional energy consumption management and control terminal acquires workshop data of an abnormal region according to a mark k, wherein the workshop data comprises yield data and total energy data, sequentially analyzes the workshop data of a plurality of groups of different abnormal regions, classifies the different abnormal regions into a standard good region or a standard bad region, and manages and controls the standard good region or the standard bad region by adopting different management and control modes, wherein the specific mode for sequentially analyzing the workshop data of the plurality of groups of different abnormal regions is as follows:
marking yield data for different abnormal area workshops as CL t-o Wherein t represents different abnormal area workshops, o represents different yield data, wherein t ε k, will correspond to yield data CL t-o The corresponding total energy consumption data is marked as ZT t-o By using
Obtaining the corresponding guide factor D t-o ；
Determining an abnormal region workshop t, and obtaining a maximum guide factor D in the abnormal region workshop t t-omax ；
Directing the maximum to factor D t-omax Sequentially comparing with the preset parameter Y5, when D t-omax Y5, classifying the corresponding abnormal region workshop t as a standard deviation region, and otherwise classifying the corresponding abnormal region workshop t as a standard deviation region;
when the energy consumption control is carried out on the abnormal area workshop t belonging to the standard area, the energy is not changed, the staff is controlled, and the working efficiency of the workshop staff is enhanced;
when the energy consumption control is carried out on the abnormal area workshop t belonging to the standard deviation area, the conveying energy is reduced, the specific reduction parameters are automatically drawn by operators, and then the staff are controlled in real time, so that the working efficiency of the staff in the workshop is enhanced.
The partial data in the formula are all obtained by removing dimension and taking the numerical value for calculation, and the formula is a formula closest to the real situation obtained by simulating a large amount of collected data through software; the preset parameters and the preset threshold values in the formula are set by those skilled in the art according to actual conditions or are obtained through mass data simulation.
The working principle of the invention is as follows: acquiring device data of workshops in different areas of an enterprise in advance, receiving the device data, analyzing device energy consumption parameters, obtaining corresponding processing parameter values according to the pre-warning times and the pre-warning time length existing in the corresponding time period, marking different devices as abnormal devices or normal devices according to the processing parameter values, and maintaining the abnormal devices through a maintenance center;
and analyzing abnormal equipment data existing in different areas, wherein the abnormal equipment data comprise the number of abnormal equipment and specific abnormal energy consumption values of the abnormal equipment, marking different areas according to analysis and processing results, transmitting area workshops marked as the abnormal areas into an area energy consumption management and control end to perform energy consumption management and control processing work, sequentially analyzing the workshop data of a plurality of groups of different abnormal areas, classifying the different abnormal areas into standard area or standard deviation area, and managing and controlling the standard area or the standard deviation area by adopting different management and control modes.
The above embodiments are only for illustrating the technical method of the present invention and not for limiting the same, and it should be understood by those skilled in the art that the technical method of the present invention may be modified or substituted without departing from the spirit and scope of the technical method of the present invention.
Claims (4)
1. An enterprise intelligent management system based on an industrial Internet is characterized by comprising an equipment data acquisition end, an equipment data analysis end, a maintenance center, a storage center, a regional data analysis end and a regional energy consumption management and control end;
the device data acquisition end is used for acquiring device data of workshops in different areas of an enterprise and transmitting the acquired device data into the device data analysis end;
the equipment data analysis end is used for receiving the equipment data, analyzing the equipment energy consumption parameters, obtaining corresponding processing parameter values according to the pre-warning times and the pre-warning time length in the corresponding time period, marking different equipment as abnormal equipment or normal equipment according to the processing parameter values, generating different binding data packages, and transmitting the different binding data packages to the maintenance center;
the maintenance center receives the binding data packet, extracts the serial number and the abnormal signal of the abnormal equipment in the binding data packet according to the received binding data packet, and dispatches external maintenance personnel;
the regional data analysis end analyzes abnormal equipment data existing in different regions, wherein the abnormal equipment data comprise the number of abnormal equipment and specific abnormal energy consumption values of the abnormal equipment, marks the different regions according to analysis processing results, and transmits regional workshops marked as abnormal regions to the regional energy consumption management and control end to perform energy consumption management and control processing work;
the regional energy consumption management and control terminal acquires workshop data of the abnormal region according to the marks, wherein the workshop data comprises yield data and total energy data, sequentially analyzes the workshop data of a plurality of groups of different abnormal regions, classifies the different abnormal regions into standard good regions or standard difference regions, and manages and controls the standard good regions or the standard difference regions by adopting different management and control modes.
2. The enterprise intelligent management system based on the industrial internet as claimed in claim 1, wherein the specific way for the device data analysis end to analyze the device energy consumption parameters is:
limiting a monitoring period T, wherein the T takes a value of 24h, acquiring corresponding energy consumption data from equipment data, and marking the energy consumption data of different equipment as NH i Wherein i represents different devices, wherein i=1, 2, … …, n, slaveExtracting a preset parameter Y1 from the storage center;
energy consumption data NH i Comparing with a preset parameter Y1, when NH i When less than Y1, no treatment is carried out, otherwise, the corresponding energy consumption data NH is obtained i Marking as abnormal data;
in the monitoring period T, acquiring the number of times of existence of the abnormal data, and marking the number of times of existence of the abnormal data as CS i Acquiring the existence time length of the abnormal data, and marking the existence time length of the abnormal data as SC i Wherein the unit of time length is h;
by using
Obtaining processing parameter CL belonging to different equipment i Will process the parameter value CL i Comparing with the preset parameter Y2, when CL i And if the number is less than Y2, not performing any processing, otherwise, marking the corresponding equipment as abnormal equipment, binding the number of the abnormal equipment and the abnormal signal, generating a binding data packet, and transmitting the binding data packet into a maintenance center.
3. The industrial internet-based enterprise intelligent management system according to claim 2, wherein the specific way for the regional data analysis terminal to analyze the abnormal device data is as follows:
marking the number of abnormal devices as GS k Wherein k represents different regions, wherein i represents different devices, wherein i=1, 2, … …, n, and the abnormal energy consumption values of different abnormal devices in different regions are marked as NH k-i ；
Extracting corresponding preset parameters Y3 from the storage center, wherein the preset parameters Y3 are empirically drawn by operators, and XH is adopted k-i ＝NH k-i Y3 obtains the energy consumption value XH exceeded by each group of different anomalous devices k-i By using
Obtaining the total energy consumption parameter ZH exceeded by different areas k ；
By QU k ＝GS k ×C3+ZH k XC 4 obtaining the determination parameters QU for different regions k And determine the parameter QU k Comparing with the preset parameter Y4 in the storage center, wherein the specific value of the preset parameter Y4 is determined by an operator according to experience, when QU k When the value is less than Y4, no processing signal is generated, otherwise, the corresponding region is marked as an abnormal region;
and transmitting the regional workshop mark k marked as the abnormal region into the regional energy consumption management and control end.
4. The industrial internet-based enterprise intelligent management system according to claim 3, wherein the specific way for the regional energy consumption management and control terminal to sequentially analyze the workshop data of multiple groups of different abnormal regions is as follows:
marking yield data for different abnormal area workshops as CL t-o Wherein t represents different abnormal area workshops, o represents different yield data, wherein t ε k, will correspond to yield data CL t-o The corresponding total energy consumption data is marked as ZT t-o By using
Obtaining the corresponding guide factor D t-o ；
Determining an abnormal region workshop t, and obtaining a maximum guide factor D in the abnormal region workshop t t-omax ；
Directing the maximum to factor D t-omax Sequentially comparing with the preset parameter Y5, when D t-omax Y5, classifying the corresponding abnormal region workshop t as a standard deviation region, and otherwise classifying the corresponding abnormal region workshop t as a standard deviation region;
when the energy consumption control is carried out on the abnormal area workshop t belonging to the standard area, the energy source is not changed, and staff is controlled;
when the energy consumption control is carried out on the abnormal area workshop t belonging to the standard deviation area, the conveying energy is reduced, the specific reduction parameters are automatically drawn by operators, and then the operators are controlled in real time.
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| CN116957887A (en) * | 2023-09-20 | 2023-10-27 | 南京快萤科技有限公司 | Intelligent meter reading method and meter reading system |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116957887A (en) * | 2023-09-20 | 2023-10-27 | 南京快萤科技有限公司 | Intelligent meter reading method and meter reading system |
| CN116957887B (en) * | 2023-09-20 | 2023-12-01 | 南京快萤科技有限公司 | Intelligent meter reading method and meter reading system |
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