CN109902871B - Intelligent optimization energy-saving system combining differentiation characteristics of enterprise production line - Google Patents
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Abstract
The invention discloses an intelligent optimization energy-saving system combining differentiation characteristics of an enterprise production line. Belongs to the technical field of energy management and energy conservation. The system mainly solves the problems that the existing system can not carry out related analysis functions aiming at the differentiation characteristics of the production line and can not know the reason of the differentiation generated by the operation of the production line. It is mainly characterized in that: the system comprises an energy management center system, an energy consumption online monitoring and analyzing system with monitoring and statistical functions and a production line differentiation and analyzing system; the production line differentiation analysis system comprises a production line unit consumption differentiation analysis system, a historical optimal value differentiation analysis system, an equipment operation parameter differentiation analysis system and different production line operation differentiation analysis systems. According to the invention, some conclusions of optimizing the energy consumption of the production line and guaranteeing the safe operation of the production line are obtained through the analysis, and finally, main factors causing the difference are found out, so that the current production process parameters are optimized for enterprises, and a direction is provided for increasing the yield and reducing the energy consumption.
Description
Technical Field
The invention belongs to the technical field of energy management and energy conservation, and particularly relates to an intelligent optimization energy-saving system combining the differentiation characteristics of an enterprise production line.
Background
Currently, the problems of energy shortage and environmental pollution become global problems, and among the energy consumption of China, the industry is a big household of the energy consumption of China, the energy consumption accounts for about 70% of the total energy consumption of China, and the energy conservation and environmental protection become increasingly concerned problems of the whole society. The traditional high-consumption and extensive industrial control management development road of energy resources is difficult to continue, the traditional economic growth mode with high consumption, high pollution and low benefit is changed, and a novel clean production road which takes an intelligent production system as a support and aims at low consumption, low emission and high-efficiency resource-saving circular economy is developed urgently.
At present, most enterprises are low in informatization application degree, the energy management level is relatively extensive, the energy consumption condition is monitored and counted in a manual mode, and the accuracy of data statistics and analysis is poor. Many manufacturers provide energy consumption online monitoring system and energy management center system software, which can basically solve the problems of energy consumption monitoring and energy consumption statistics, but the software generally lacks a related analysis function aiming at the differentiation characteristics of the production line, and cannot know the reason of differentiation generated during the operation of the production line. Mainly manifested by the following defects.
Firstly, when the unit consumption of the product of the production line changes, the result of unit consumption increase can only be accepted passively, and in many cases, due to the lack of sufficient metering equipment and statistical analysis methods, the specific reasons causing unit consumption increase cannot be known, and effective measures cannot be taken to reduce unit consumption.
And secondly, long-term statistical analysis of historical data is lacked, and various core process parameters of the operation of the production line are not recorded when the unit consumption is low. There is no way to provide direction for reducing the unit consumption and reducing the difference from the optimal value of the history.
And thirdly, the real-time operation data and the historical operation data of the equipment are not compared in the production line. When the operation data in the production line are different, the difference cannot be found and adjusted in time. This is mainly reflected in the case where the operating parameters of the plant are within normal ranges, but the fluctuations or the trend of change are abnormal.
And fourthly, the differentiation analysis among a plurality of production lines is lacked, which mainly aims at the mutual comparison among the production lines which adopt the same process and produce the same product. These production line configurations may be different, but the differences of the energy consumption parameters and the operation parameters of the equipment, the working sections and the like in the same process position should be within a reasonable range, and the actual situation is that the energy management system and the energy online monitoring and analyzing system which are seen in the market at present have no relevant aspects to analyze.
Disclosure of Invention
The invention provides an intelligent optimization energy-saving system combining differentiation characteristics of an industrial production line aiming at the problems in the prior art, and the intelligent optimization energy-saving system not only has the functions of the existing energy management center system and the monitoring and counting functions of an energy consumption online monitoring and analyzing system, but also has the functions of analyzing differentiation reasons generated by the production line to obtain the conclusion of optimizing energy consumption of the production line and guaranteeing safe operation of the production line.
The technical solution of the invention is as follows: the utility model provides a combine intelligent optimization economizer system of industrial production line differentiation characteristics, includes energy management center system, has the energy consumption on-line monitoring analytic system of monitoring and statistics function which characterized in that: the production line differentiation analysis system is also included; the production line differentiation analysis system comprises a production line unit consumption differentiation analysis system, a historical optimal value differentiation analysis system, an equipment operation parameter differentiation analysis system and different production line operation differentiation analysis systems.
The production line unit consumption differential analysis system in the technical scheme comprises a team unit consumption differential analysis system and a workshop section (working procedure) daily unit consumption differential analysis system. Aiming at the product unit consumption differences of different groups of production classes, the group unit consumption differentiation analysis system finds out the work sections (processes) influencing unit consumption according to the historical optimal value and the unit consumption comparative analysis of each group, further positions the reasons of unit consumption differences of specific equipment and links, and provides a solution to realize energy conservation and consumption reduction. The daily unit consumption difference analysis system of the working sections (working procedures) aims at the comparative analysis of the unit consumption differences of all the working sections (working procedures) of the whole production line in a selected production period, positions the specific equipment and links generating the unit consumption differences, further analyzes the hourly unit consumption differences of the specific equipment and links, positions the differences to the specific equipment and time, is convenient for enterprise managers to analyze the reasons of the energy consumption differences, and finds corresponding processing methods.
According to the historical optimal value difference analysis system in the technical scheme, the existing unit consumption indexes and the historical optimal unit consumption indexes are compared and analyzed, a link generated by difference is found, the unit consumption difference of the difference link per hour is compared, then the core process parameters of the difference link per hour are compared, and finally the factors causing the difference are found. The method optimizes the current production process parameters for enterprises, and provides a direction for improving the yield and reducing the energy consumption.
The equipment operation parameter differentiation analysis system in the technical scheme comprises an operation parameter and historical operation parameter differentiation comparison analysis system of the same equipment, a fluctuation abnormity differentiation analysis system of the same equipment and a differentiation analysis system of the same working condition equipment. The operation parameter of the same equipment and the historical operation parameter are differentiated, contrasted and analyzed by the system to monitor whether the operation data of the equipment is in a normal range, and when the operation data of the equipment does not reach an off-line alarm condition but exceeds the normal operation range, the equipment is maintained in time. Therefore, the energy consumption of equipment operation is reduced, the operation safety of the equipment is ensured, and the fault shutdown of the equipment is avoided. The fluctuation abnormity differentiation analysis system of the same equipment monitors the fluctuation frequency and range of the equipment load during normal operation, and sends out an alarm prompt when the fluctuation frequency and range are obviously increased. The intelligent optimization energy-saving system can analyze the fluctuation abnormal condition, so that enterprise management can timely discover the fluctuation abnormal condition, and the loss caused by the fault can be avoided. The differential analysis system of the equipment under the same working condition monitors the load size and the difference of the load change trend of the equipment under the same working condition, finds the abnormal operation state of the equipment in time, and takes targeted measures for the abnormal state.
According to the technical scheme, the operation differentiation analysis system of different production lines compares various production indexes and energy consumption indexes of two similar production lines with each other, analyzes the deviation of various indexes and analyzes whether the deviation is in a normal range, so that the point of abnormal operation of the production lines is obtained, the problem is promoted to be solved in time, and safe operation and energy-saving operation of the production lines are realized.
The specific implementation flow of the team consumption differentiation analysis system in the technical solution of the invention comprises the following steps: (1) Firstly, selecting a date, and acquiring team information including team yield data, team energy consumption data and process energy consumption data from the intelligent optimization energy-saving system after selecting a specific date; (2) Calculating unit consumption of the teams and groups, and comparing the unit consumption difference amplitude of the teams and groups; (3) judging whether the current is within a set range; (4) if the range is within, outputting a conclusion 1; conclusion 1 the conclusion can be referred to as "two teams differ less"; (5) If not, continuously analyzing the energy consumption difference and unit consumption difference of each procedure; finding out a process with larger energy consumption difference and unit consumption difference; (6) outputting a conclusion 2; the conclusion 2 comprises three processes of a team unit consumption difference value and the maximum energy consumption difference and three processes of the maximum unit consumption difference, and the energy consumption difference and the unit consumption difference are displayed;
the specific implementation flow of the section or process daily unit consumption differential analysis system comprises the following steps: (1) Firstly, selecting a date, and acquiring daily output data, daily energy consumption data and process energy consumption data from an intelligent optimization energy-saving system after selecting a specific date; (2) Calculating unit consumption of two days of comparison, and comparing daily unit consumption difference amplitude; (3) judging whether the current is in a set range; (4) if the range is within, outputting a conclusion 1; conclusion 1 the conclusion can be referred to as "two-day difference is small"; (5) If not, continuously analyzing the energy consumption difference and unit consumption difference of each procedure; finding out a process with larger energy consumption difference and unit consumption difference; (6) Continuously analyzing the processes with large energy consumption difference and unit consumption difference, and analyzing the difference per hour; (7) outputting a conclusion 2; the conclusion 2 comprises three processes of daily unit consumption difference value and maximum daily difference, three processes of maximum unit consumption difference and time of maximum energy consumption difference and maximum unit consumption difference.
The specific real-time flow of the historical optimal value differentiation analysis system in the technical solution of the invention comprises the following steps: (1) Firstly, selecting conditions for comparative analysis, wherein the conditions comprise bisection time and energy consumption index names; (2) Acquiring data of an intelligent optimization energy-saving system, wherein the data comprises energy consumption data and production data which are necessary for calculating an index value and also comprises standard value data of a specific index; automatically counting the optimal value of the corresponding index and the corresponding production core process parameter value at the optimal value through long-term data acquired by an intelligent optimization energy-saving system during the historical optimal value; (3) calculating corresponding index value comparison according to an index formula; (4) Judging whether the index value is in a range specified by a corresponding standard value; (5) If the index value is in the normal range, prompting that the index value is normal; if the index value is not in the normal range, displaying that the index value is not in the normal range; if the compared standard value is the optimal value, displaying the core process parameter corresponding to the existing index value and the core process parameter corresponding to the optimal value; and providing the direction of deviation adjustment for enterprise management.
The specific implementation indexes of the equipment operation parameter differentiation analysis system in the technical scheme of the invention comprise the following steps: (1) The production line 1 and the production line 2 are required to adopt the same production process and two different production lines for producing the same product, and all indexes of the two production lines are calculated; (2) comparing the difference values of the indexes after calculation; (3) outputting a conclusion; if the comparison is normal, the conclusion that the production line index is normal is output, if the comparison is abnormal, the production link index is positioned to be abnormal, and the conclusion of an abnormal position and an abnormal index value is output.
The specific implementation process of the equipment operation parameter differentiation analysis system in the technical scheme of the invention comprises the following steps: (1) Setting the equipment, fluctuation frequency and fluctuation range of analysis; (2) acquiring n real-time data to judge whether the fluctuation is abnormal; the judgment method is that the former data is subtracted from the latter data, then the obtained data is compared with the set fluctuation range, and if m data exceeds the set fluctuation range in n-1 data obtained by subtracting n real-time data, the fluctuation abnormity alarm is carried out.
The specific implementation flow of the operation differentiation analysis system of different production lines in the technical scheme of the invention comprises the following steps: (1) The equipment data comprises average power, real-time current and operation trend; automatically calculating data acquired by an intelligent optimization energy-saving system; (2) comparing and displaying the data and the trends; and (3) outputting a comparison conclusion.
The system has the monitoring and statistical functions of a common energy management center system and an energy consumption online monitoring and analyzing system on the market, analyzes the reasons of the differences generated by the production line, obtains conclusions for optimizing the energy consumption of the production line and guaranteeing the safe operation of the production line through the analysis, finally finds out the main factors causing the differences, optimizes the current production process parameters for enterprises, and provides a direction for improving the yield and reducing the energy consumption.
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FIG. 1 is a flowchart illustrating the differential analysis of unit consumption of different teams according to the present invention.
FIG. 2 is a flowchart illustrating the differentiation analysis of unit consumption on different days according to the present invention.
FIG. 3 is a flowchart illustrating an embodiment of a historical optimal differentiation analysis according to the present invention.
FIG. 4 is a flowchart illustrating an embodiment of a fluctuation anomaly differentiation analysis of the same device according to the present invention.
FIG. 5 is a flowchart illustrating an embodiment of a differential analysis method for a device under the same operating conditions.
FIG. 6 is a flow chart of an embodiment of the present invention for analyzing the running difference of different production lines.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings.
The invention relates to an intelligent optimization energy-saving system combining the differentiation characteristics of an enterprise production line, which comprises an energy management center system, an energy consumption online monitoring and analyzing system with monitoring and counting functions and a production line differentiation analyzing system. The energy management center system and the energy consumption online monitoring and analyzing system with monitoring and statistical functions are the same as or similar to the existing energy management center system. The production line differentiation analysis system comprises a production line unit consumption differentiation analysis system, a historical optimal value differentiation analysis system, an equipment operation parameter differentiation analysis system and different production line operation differentiation analysis systems.
The unit consumption difference comparison analysis of the production line comprises the group difference comparison analysis and the daily unit consumption difference comparison analysis.
The specific implementation flow of the team specific consumption comparison analysis is shown in fig. 1, and comprises the following steps:
(1) Firstly, selecting a date, and acquiring team information including team yield data, team energy consumption data and process energy consumption data from the intelligent optimization energy-saving system after selecting a specific date;
(2) Calculating unit consumption of the teams and groups, and comparing the unit consumption difference amplitude of the teams and groups;
(3) Judging whether the current is within a set range;
(4) If the current is within the range, outputting a conclusion 1; conclusion 1 the conclusion can be referred to as "two teams differ less";
(5) If the energy consumption difference and the unit consumption difference of each procedure are not calculated within the range, continuously analyzing the energy consumption difference and the unit consumption difference of each procedure; finding out a process with larger energy consumption difference and unit consumption difference;
(6) Outputting a conclusion 2; and the conclusion 2 comprises three processes of the unit consumption difference value of the team and the maximum energy consumption difference and three processes of the maximum unit consumption difference, and the energy consumption difference and the unit consumption difference are displayed.
Through the frequent comparative analysis of the teams, the difference points are found, the mutual communication among the teams is promoted, the difference reasons are found, the experience sharing of production personnel can be effectively promoted, the level is improved, and the energy consumption is reduced.
The specific implementation flow of daily unit consumption comparative analysis of the working section (process) is shown in FIG. 2, and comprises the following steps:
(1) Firstly, selecting a date, and acquiring daily output data, daily energy consumption data and process energy consumption data from an intelligent optimization energy-saving system after selecting a specific date;
(2) Calculating unit consumption of two days of comparison, and comparing daily unit consumption difference amplitude;
(3) Judging whether the current is within a set range;
(4) If the current is within the range, outputting a conclusion 1; conclusion 1 the conclusion can be referred to as "two-day difference is small";
(5) If not, continuously analyzing the energy consumption difference and unit consumption difference of each procedure; finding out a process with larger energy consumption difference and unit consumption difference;
(6) Continuously analyzing the processes with large energy consumption difference and unit consumption difference, and analyzing the difference per hour;
(7) Outputting a conclusion 2; the conclusion 2 comprises three processes of daily unit consumption difference value and maximum daily difference, three processes of maximum unit consumption difference and time of maximum energy consumption difference and maximum unit consumption difference.
By finding out the specific reason for the different unit consumptions in two days, the method can take measures in a targeted manner.
The historical optimal value differentiation analysis is to compare and analyze the energy consumption index of the enterprise with the historical optimal value, find the difference with the historical optimal value, and provide a direction for the enterprise to continuously optimize the process, continuously save energy and reduce consumption.
The specific real-time flow of the standard value analysis is shown in fig. 3, and comprises the following steps:
(1) Firstly, selecting conditions for comparative analysis, wherein the conditions comprise halving time and energy consumption index names;
(2) Acquiring data of an intelligent optimization energy-saving system, wherein the data comprises energy consumption data and production data necessary for calculating an index value, and also comprises standard value data of a specific index;
automatically counting the optimal value of the corresponding index and the corresponding production core process parameter value at the optimal value through long-term data acquired by an intelligent optimization energy-saving system during the historical optimal value;
(3) Calculating corresponding index value comparison according to an index formula;
(4) Judging whether the index value is in a range specified by a corresponding standard value;
(5) If the index value is in the normal range, prompting that the index value is normal; if the index value is not in the normal range, displaying that the index value is not in the normal range; if the compared standard value is the optimal value, displaying the core process parameter corresponding to the existing index value and the core process parameter corresponding to the optimal value; and providing the direction of deviation adjustment for enterprise management.
The production line comparison analysis is to compare production indexes and energy consumption indexes of two similar production lines, analyze the deviation of each index and analyze whether the deviation is in a normal production range. Therefore, the abnormal operation point of the production line is obtained, and the problem is solved in time. The safe operation and the energy-saving operation of the production line are realized.
The specific implementation indexes of the production line comparison are shown in fig. 4, and comprise the following steps:
(1) The production line 1 and the production line 2 require two different production lines which adopt the same production process and produce the same product. Firstly, calculating each index of the two production lines;
(2) And comparing the difference values of the indexes after calculation. Generally, the difference of indexes of two production lines with the same process and the same product is stabilized within a range, and if the difference exceeds the range, the production link is definitely a local problem;
(3) And outputting a conclusion. If the comparison is normal, the conclusion that the production line index is normal is output, if the comparison is abnormal, the production link index is positioned to be abnormal, and the conclusion of an abnormal position and an abnormal index value is output.
The equipment operation parameter differentiation analysis comprises differentiation comparison analysis of operation parameters and historical operation parameters of the same equipment, fluctuation abnormity differentiation analysis of the same equipment and differentiation analysis of the equipment under the same working condition.
And comparing and analyzing the operating data and the historical parameters of the equipment. The operation data of the equipment is compared with the historical data, the analysis is carried out from the two angles of numerical value comparison and operation trend comparison, the data of two times are compared, and if the data exceed the set range, an alarm conclusion is output. And selecting historical data of multiple days for analysis, analyzing the change trend of the operating data, and outputting an alarm conclusion if a continuous increasing trend occurs.
And (4) analyzing abnormal fluctuation of the equipment. In a production field, the fluctuation of a plurality of devices in normal operation is very small, and if the devices fluctuate frequently in a short time, the devices have potential fault hazards and need to be overhauled and removed in time. The intelligent optimization energy-saving system disclosed by the patent integrates an algorithm for judging the fluctuation abnormity of the equipment, and can find the abnormal running state of the equipment in time. The specific implementation flow is shown in fig. 5, and includes the following steps:
(1) Setting the equipment, fluctuation frequency and fluctuation range of analysis;
(2) And acquiring n real-time data to judge whether the fluctuation is abnormal. The judgment method is that the former data is subtracted from the latter data, then the obtained data is compared with the set fluctuation range, and if m data exceeds the set fluctuation range in n-1 data obtained by subtracting n real-time data, the fluctuation abnormity alarm is carried out.
The function can enable production line production management personnel to find out the abnormal condition of fluctuation in time, and avoid bringing greater loss.
And (5) comparing and analyzing with working condition equipment. In the production line, a plurality of devices with the same working condition exist, the power of the devices is the same at adjacent process positions, but the load size and the load variation trend of the devices are different in many cases. The difference is caused by the fact that the operation state of the equipment is not adjusted, and energy consumption waste and potential safety hazards exist in the condition. For the situation, a specific implementation flow of the comparative analysis of the equipment under the same working condition provided by the invention is shown in fig. 6, and comprises the following steps:
(1) The plant data includes average power, real-time current, operational trends. And automatically calculating the data acquired by the intelligent optimization energy-saving system.
(2) These data and trends are shown in comparison.
(3) And outputting a comparison conclusion.
The present invention is not limited to the above preferred embodiments, and any modifications, equivalent substitutions and improvements made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (8)
1. The utility model provides a combine intelligent optimization economizer system of industrial production line differentiation characteristics, includes energy management center system, has the energy consumption on-line monitoring analytic system of monitoring and statistics function which characterized in that: the production line differentiation analysis system is also included; the production line differential analysis system comprises a production line unit consumption differential analysis system, a historical optimal value differential analysis system, an equipment operation parameter differential analysis system and different production line operation differential analysis systems;
the production line unit consumption differential analysis system comprises a team unit consumption differential analysis system and a workshop section or working procedure day unit consumption differential analysis system; aiming at the unit consumption differences of products of different groups of production classes, the group unit consumption differentiation analysis system finds out the work sections or processes influencing unit consumption according to the historical optimal value and the unit consumption comparative analysis of each group, further positions the reasons for generating the unit consumption differences of specific equipment and links, and provides a solution to realize energy conservation and consumption reduction;
the historical optimal value differential analysis system compares and analyzes the current unit consumption index and the historical optimal unit consumption index, finds out the link generated by the difference, compares the unit consumption difference of the difference link per hour, then compares the core process parameters of the difference link per hour, and finally finds out the factors causing the difference; optimizing the current production process parameters for enterprises, and providing a direction for improving the yield and reducing the energy consumption;
the equipment operation parameter differentiation analysis system comprises a differentiation comparison analysis system for operation parameters and historical operation parameters of the same equipment, a fluctuation abnormity differentiation analysis system of the same equipment and a differentiation analysis system of the same working condition equipment;
the different production line operation differentiation analysis system mutually compares various production indexes and energy consumption indexes of two similar production lines, analyzes the deviation of various indexes, and analyzes whether the deviation is in a normal range, so that the abnormal point of the production line operation is obtained, the problem is promoted to be solved in time, and the safe operation and the energy-saving operation of the production line are realized.
2. The intelligent optimization energy-saving system combining the differentiated characteristics of the enterprise production line according to claim 1, is characterized in that: the daily unit consumption difference analysis system of the workshop sections or the working procedures aims at the comparative analysis of the unit consumption differences of all the workshop sections or the working procedures of the whole production line in a selected production period, positions the specific equipment and the links generating the unit consumption differences, further analyzes the hourly unit consumption differences of the specific equipment and the links, positions the differences to the specific equipment and time, is convenient for enterprise managers to analyze the reasons of the energy consumption differences and find corresponding processing methods.
3. The intelligent energy-saving optimization system combining the differentiated characteristics of the enterprise production line according to claim 1 or 2, is characterized in that: the operating parameter of the same equipment and the historical operating parameter are differentiated, compared and analyzed by the system to monitor whether the operating data of the equipment is in a normal range, and when the operating data of the equipment does not reach an off-line alarm condition but exceeds the normal operating range, the equipment is required to be maintained in time; the fluctuation abnormity differentiation analysis system of the same equipment monitors the fluctuation frequency and range of the equipment load during normal operation, and sends out an alarm prompt when the fluctuation frequency and range are obviously increased.
4. The intelligent energy-saving optimization system combining the differentiated characteristics of the enterprise production line according to claim 1 or 2, is characterized in that:
the specific implementation flow of the team consumption differential analysis system comprises the following steps: (1) Firstly, selecting a date, and acquiring team information including team yield data, team energy consumption data and process energy consumption data from the intelligent optimization energy-saving system after selecting a specific date; (2) Calculating unit consumption of the teams and groups, and comparing the unit consumption difference amplitude of the teams and groups; (3) judging whether the current is within a set range; (4) if the range is within, outputting a conclusion 1; conclusion 1 the conclusion can be referred to as "two teams differ less"; (5) If not, continuously analyzing the energy consumption difference and unit consumption difference of each procedure; finding out a process with larger energy consumption difference and unit consumption difference; (6) outputting a conclusion 2; the conclusion 2 comprises three processes of a team unit consumption difference value and the maximum energy consumption difference and three processes of the maximum unit consumption difference, and the energy consumption difference and the unit consumption difference are displayed;
the specific implementation flow of the section or process daily unit consumption differential analysis system comprises the following steps: (1) Firstly, selecting a date, and acquiring daily output data, daily energy consumption data and process energy consumption data from the intelligent optimization energy-saving system after selecting a specific date; (2) Calculating unit consumption of two days of comparison, and comparing daily unit consumption difference amplitude; (3) judging whether the current is in a set range; (4) if the range is within, outputting a conclusion 1; conclusion 1 the conclusion can be referred to as "two-day difference is small"; (5) If not, continuously analyzing the energy consumption difference and unit consumption difference of each procedure; finding out a process with larger energy consumption difference and unit consumption difference; (6) Continuously analyzing the processes with large energy consumption difference and unit consumption difference, and analyzing the difference per hour; (7) outputting a conclusion 2; the conclusion 2 comprises three processes of daily unit consumption difference value and maximum daily difference, three processes of maximum unit consumption difference and time of maximum energy consumption difference and maximum unit consumption difference.
5. The industrial intelligent optimization energy-saving system based on the diagnosis and analysis of the key energy consumption equipment model is characterized in that: the specific real-time process of the historical optimal value differentiation analysis system comprises the following steps: (1) Firstly, selecting conditions for comparative analysis, wherein the conditions comprise halving time and energy consumption index names; (2) Acquiring data of an intelligent optimization energy-saving system, wherein the data comprises energy consumption data and production data which are necessary for calculating an index value and also comprises standard value data of a specific index; automatically counting the optimal value of the corresponding index and the corresponding production core process parameter value at the optimal value through long-term data acquired by an intelligent optimization energy-saving system during the historical optimal value; (3) calculating corresponding index value comparison according to an index formula; (4) Judging whether the index value is in a range specified by a corresponding standard value; (5) If the index value is in the normal range, prompting that the index value is normal; if the index value is not in the normal range, displaying that the index value is not in the normal range; if the compared standard value is the optimal value, displaying the core process parameter corresponding to the existing index value and the core process parameter corresponding to the optimal value; and providing the direction of deviation adjustment for enterprise management.
6. The intelligent optimization energy-saving system combining the differentiated characteristics of the enterprise production line according to claim 2, is characterized in that: the specific implementation indexes of the equipment operation parameter differentiation analysis system comprise the following steps: (1) The production line 1 and the production line 2 are required to adopt two different production lines which have the same production process and produce the same product, and all indexes of the two production lines are calculated; (2) comparing the difference values of the indexes after calculation; (3) outputting a conclusion; if the comparison is normal, the conclusion that the production line index is normal is output, if the comparison is abnormal, the production link index is positioned to be abnormal, and the conclusion of an abnormal position and an abnormal index value is output.
7. The intelligent optimization energy-saving system combined with differentiated characteristics of enterprise production lines according to claim 3, characterized in that: the specific implementation process of the equipment operation parameter differentiation analysis system comprises the following steps: (1) Setting the equipment, fluctuation frequency and fluctuation range of analysis; (2) acquiring n real-time data to judge whether the fluctuation is abnormal; the judgment method is that the former data is subtracted from the latter data, then the obtained data is compared with the set fluctuation range, and if m data in n-1 data obtained by subtracting n real-time data exceeds the set fluctuation range, the fluctuation abnormity alarm is carried out.
8. The intelligent energy-saving optimization system combining the differentiated characteristics of the enterprise production line according to claim 1 or 2, is characterized in that: the specific implementation flow of the differential analysis system for the operation of different production lines comprises the following steps: (1) The equipment data comprises average power, real-time current and operation trend; automatically calculating data acquired by an intelligent optimization energy-saving system; (2) comparing and displaying the data and the trend; and (3) outputting a comparison conclusion.
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| CN105956786A (en) * | 2016-05-13 | 2016-09-21 | 河南心连心化肥有限公司 | Energy management system used for fertilizer enterprise |
| CN106408192A (en) * | 2016-09-23 | 2017-02-15 | 东北大学 | Mineral processing equipment operating state monitoring system and method |
| CN107146004A (en) * | 2017-04-20 | 2017-09-08 | 浙江大学 | A kind of slag milling system health status identifying system and method based on data mining |
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