CN112749473B - Energy efficiency safety diagnosis system based on real-time online analysis and simulated offline analysis - Google Patents
Energy efficiency safety diagnosis system based on real-time online analysis and simulated offline analysis Download PDFInfo
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Abstract
The invention discloses an energy efficiency safety diagnosis system based on real-time online analysis and simulated offline analysis. Belonging to the technical field of energy management and energy conservation. The system mainly solves the problem that the existing energy management system cannot obtain accurate energy efficiency difference and safe operation state difference for the state of the operation automatic screening equipment. The main characteristics of the device are as follows: the system comprises an online analysis module, an offline analysis module, a time ratio analysis module and an analogy analysis module; the online analysis module realizes real-time online diagnosis of equipment energy efficiency and safety; the offline analysis module records the energy efficiency and safety parameter variable values related to the equipment; and comprehensively diagnosing to obtain the energy efficiency and safe energy-saving improvement strategy suggestion of the equipment through the time ratio analysis module and the analogy analysis module. The invention solves the diagnosis problems of energy efficiency difference and running state difference under the conditions of big data, multiple variable types and complicated equipment procedures, and is mainly used for improving the practical application energy saving effect of the energy information management platform.
Description
Technical Field
The invention belongs to the technical field of energy management and energy conservation, and particularly relates to an energy efficiency safety diagnosis system based on real-time online analysis and simulated offline analysis.
Background
Currently, the problems of energy shortage and environmental pollution become global problems, the national importance is attached to energy conservation and emission reduction, the assessment and supervision of energy use for enterprises become more and more strict, and meanwhile, the improvement of the energy use efficiency is also the improvement of the competitiveness of enterprises, so that the inherent driving force of sustainable development is realized. In the enterprise level, along with the application of various energy-saving projects, the difficulty of the reduction of the energy consumption of unit products is larger and larger, and more enterprises complete an energy statistics monitoring system by constructing a comprehensive energy information management platform, so that the comprehensive energy management level is improved, and the energy saving of a comprehensive system is realized.
In the existing energy information management platform, the energy saving mode is realized by firstly establishing an energy data acquisition and measurement system, and based on detailed energy information measurement, the statistics of energy consumption efficiency indexes of key equipment, energy media, working procedures and products is realized. Because the running states of various industrial field devices are always in a changing state, the types of parameters reflecting the energy efficiency and running safety of the devices and working procedures are different, the data volume is large, only the data summarization of energy efficiency indexes and safety running parameters is realized in the existing energy management system, only the data sets collected by the system can be provided according to time sequence, and the accurate energy efficiency difference and the safe running state difference can not be obtained for the running automatic screening device state. The energy efficiency and safety diagnosis technology based on real-time online analysis and simulated offline analysis solves the diagnosis problems of energy efficiency difference and running state difference under the complex conditions of big data, multivariable type and equipment procedure by combining the collection period of system data and the specific state period distribution through data rolling circulation calculation, and improves the energy saving effect of the practical application of an energy information management platform
Disclosure of Invention
Aiming at the problems existing in the prior art, the invention provides an energy efficiency safety diagnosis system based on real-time online analysis and simulated offline analysis, which solves the diagnosis problems of energy efficiency difference and running state difference under complex conditions of big data, multivariable type and equipment working procedure by combining the collection period of system data and the specific state period distribution through data rolling circulation calculation.
The technical scheme of the invention is as follows: an energy efficiency safety diagnosis system based on real-time online analysis and simulated offline analysis is characterized in that: the system comprises an online analysis module, an offline analysis module, a time ratio analysis module and an analogy analysis module; the online analysis module determines energy efficiency and safety process parameter variables of equipment and working sections according to equipment and working procedure characteristics, performs data operation and processing, and realizes real-time online diagnosis of the energy efficiency and safety of the equipment according to the difference between the average value of the current time period and the average value of the historical time period; the offline analysis module comprises a historical data recording module for recording the energy efficiency and safety parameter variable values related to the equipment; the time ratio analysis module is used for obtaining state differences of equipment parameters in different time periods; the analog analysis module is used for obtaining state differences of a plurality of devices in a selected period; and comprehensively diagnosing to obtain the energy efficiency and safe energy-saving improvement strategy suggestion of the equipment through the time ratio analysis module and the analogy analysis module.
The online analysis module comprises a data acquisition module, a data processing module and a diagnosis module; the data acquisition module determines energy efficiency and safe process parameter variables of equipment and working sections according to equipment and working procedure characteristics; the data processing module acquires the data of the data acquisition module and performs operation and processing of the data; the diagnosis module realizes real-time online diagnosis of equipment energy efficiency and safety according to the difference between the current time period average value and the historical time period average value.
The data acquisition module in the technical solution of the invention acquires the technological parameter variables of energy efficiency and operation safety related to equipment or working sections at a certain period interval t, and the variable values are respectively defined as A i , B i Corresponding acquisition values are respectively denoted (A) at … 0 ，A 1 ，A 2 ，…，A n ），（B 0 ，B 1 ，B 2 ，…，B n ）,…；
The data processing module obtains the moment of the change of the running state of the equipment and the changed state value S according to the running parameters of the equipment, wherein the moment is defined as 1 when the equipment is in the running state, and the moment is defined as 0 when the equipment is in the shutdown state; setting a time synchronization T, recording that the period is valid when the equipment states are all 1 in one time synchronization T, otherwise, recording that the period is invalid; calculating the average value of each variable of the set time synchronization T, and respectively calculating and obtaining a daily average value, a month average value, a former three-month average value and a historical average value in the normal running state of the equipment according to the calendar time;
the diagnosis module compares the current time period average value with the daily average value, the month average value, the former three-month average value and the historical average value obtained by calculation under the normal running state of the equipment to obtain the difference between the current time period average value and the daily average value, the month average value, the former three-month average value and the historical average value, so that the difference between the current running state and the normal running state of the equipment is found, and the real-time online diagnosis of the energy efficiency and the safety of the equipment is realized.
The data processing module in the technical solution of the invention sets the time synchronization T to 15min;
grouping the process parameter variables of energy consumption and operation safety according to a period of 15min, wherein the number of each group of variables is j=0.25/t;
when T is i When the period is effective, calculating average value of every variable in the period, dividing the variable value into instantaneous value and accumulated value into two algorithms so as to make A i Expressed as instantaneous value type variable, B i The algorithm expressed as cumulative value type variable and the corresponding average value are as follows:
for a variable A of the instantaneous value type i Average value A ave The calculation method comprises the following steps:
variable B for cumulative value type i Average value B ave The calculation method comprises the following steps: for the last value of the variable in each period T,for the previous T weeks of the cycleThe last value of the period;
after the mean value of each variable of the effective T period is obtained through the algorithm, the mean value of each effective period is sequentially defined asRespectively calculating a corresponding hour average value, a daily average value, a month average value, a previous three-month average value and a historical average value according to the calendar time;
the average value of the hours is denoted as Mh, and the effective period number of each hour is denoted as a
Average daily value is denoted as Md, and average value of 12 hours per day is denoted asThe number of cycles per hour of 12 hours per day is recorded asObtaining a daily average value of
The average value of the month is Mm, and the average value of the day of each month is MmThe number of effective cycles per day in the month is recorded asp is the total number of days of the month, and the average value of the month is obtained
The average value of the former March is recorded as M3M, and the average values of the former 1,2 and 3 months are respectively recordedDenoted as Md -1 ，Md -2 ，Md -3 The effective period of three months is recorded asThe average value of the first three months is obtained as
The history mean is recorded as MY, the history mean is the sum of all history effective values divided by the number of all effective values, and in order to realize rapid calculation, the history mean is updated once every month, and the history mean of the last month is defined asThe historical average of the current month is The average value of the current month is calculated by the last month calendar Shi Junzhi and the month average value of the current month. The average value of the current month is Mm, the effective period number of the current month is d, and the calculated historical average value of the previous month isThe total historical effective cycle number is e when the historical average value is counted in the last month, and the current month historical average value calculating method comprises the following steps:
according to the calculation method, the daily average value, the monthly average value, the prior march average value and the historical average value of the monitoring variable are calculated and obtained according to the period of hours, days, months and months in the normal running state of the equipment.
The current time period in the diagnosis module in the technical solution of the invention is hours, and the current hour average value is compared with the daily average value, the month average value, the previous three-month average value and the historical average value in each hour to obtain the difference between the current hour average value and the daily average value, the month average value, the previous three-month average value and the historical average value, thereby finding the difference between the current running state and the normal running state of the equipment and realizing the real-time online diagnosis of the energy efficiency and the safety of the equipment.
The historical data recording module in the technical solution of the invention records the relevant energy efficiency and safety parameter variable values of the equipment according to 15min as a period.
The time ratio analysis module in the technical solution of the invention obtains the state differences of the equipment parameters in different daily periods, monthly periods and annual periods on the basis of the data recording module; the analog analysis module obtains the state differences of a plurality of devices in selected daily periods, month periods and year periods on the basis of the data recording module.
According to the technical scheme, through the time ratio analysis module and the analogy analysis module, the accurate energy efficiency difference and the safe running state difference of the equipment are obtained through comprehensive diagnosis, and corresponding energy saving improvement strategy suggestions are output.
The invention has the advantages that: compared with the existing energy management center system, the invention provides a mode based on data acquisition, data processing and data diagnosis under different running states according to different processes and equipment of enterprises and combining the characteristics of safety and energy efficiency parameters, and solves the diagnosis problems of energy efficiency difference and running state difference under complex conditions of big data, multivariable type and equipment procedures.
The invention is mainly used for improving the practical application energy-saving effect of the energy information management platform.
Detailed Description
The present invention will be further described below.
The invention discloses an embodiment of an energy efficiency safety diagnosis system based on real-time online analysis and simulated offline analysis, which comprises an online analysis module, an offline analysis module, a time ratio analysis module and an analogy analysis module.
The online analysis module comprises a data acquisition module, a data processing module and a diagnosis module.
And the data acquisition module determines energy efficiency and safety process parameter variables of the equipment and the working section according to the characteristics of the equipment and the working procedure.
The data acquisition module acquires technological parameter variables of energy efficiency and operation safety related to equipment or working section according to a certain period interval t, and the variable values are respectively defined as A i ，B i Corresponding acquisition values are respectively denoted (A) at … 0 ，A 1 ，A 2 ，…，A n ），（B 0 ，B 1 ，B 2 ，…，B n ），…。
The data processing module acquires the data of the data acquisition module and performs operation and processing of the data. Comprising the following steps:
and obtaining the moment of the change of the running state of the equipment and the changed state value S according to the running parameters of the equipment. Defined as 1 when the device is in an operational state and defined as 0 when the device is in a shutdown state.
And recording a period of 15min, namely recording the period as T, and recording that the period is valid when the states of the equipment are all 1 in one period of 15min according to the state change moment and the state value of the equipment, or recording that the period is invalid.
The process parameter variables of energy consumption and operation safety are grouped according to the period of 15min, and the number of each group of variables is j=0.25/t.
When T is i When the period is effective, calculating average value of every variable in the period, dividing the variable value into instantaneous value and accumulated value into two algorithms so as to make A i Expressed as instantaneous value type variable, B i The algorithms expressed as cumulative-value type variables and corresponding average values are as follows, respectively.
For a variable A of the instantaneous value type i Average value ofThe calculation method comprises the following steps:。
variable B for cumulative value type i Average value ofThe calculation method comprises the following steps:，for the last value of the variable in each period T,is the last value of the previous T period of the period.
After the mean value of each variable of the effective T period is obtained through the algorithm, the mean value of each effective period is sequentially defined asAnd respectively calculating a corresponding hour average value, a daily average value, a month average value, a previous three-month average value and a historical average value according to the calendar time.
The average value of the hours is denoted as Mh, and the effective period number of each hour is denoted as a
。
Average daily value is denoted as Md, and average value of 12 hours per day is denoted asThe number of cycles per hour of 12 hours per day is recorded asThe daily average value is obtained as follows:
。
the average value of the month is recorded as Mm, and each day of the monthThe daily average value is recorded asThe number of effective cycles per day in the month is recorded asp is the total number of days of the month, and the obtained month average value is:
。
the average value of the former March is marked as M3M, and the average values of the former 1,2 and 3 months are respectively marked as Md -1 ，Md -2 ，Md -3 The effective period corresponding to three months is recorded asThe average value of the first three months is obtained as follows:
。
the history mean is recorded as MY, the history mean is the sum of all history effective values divided by the number of all effective values, and in order to realize rapid calculation, the history mean is updated once every month, and the history mean of the last month is defined asThe historical average of the current month isThe average value of the current month is calculated by the last month calendar Shi Junzhi and the month average value of the current month. The average value of the current month is Mm, the effective period number of the current month is d, and the calculated historical average value of the previous month isThe total historical effective cycle number is e when the historical average value is counted in the last month, and the current month historical average value calculating method comprises the following steps:
。
according to the calculation method, the daily average value, the monthly average value, the prior march average value and the historical average value of the monitoring variable are calculated and obtained according to the period of hours, days, months and months in the normal running state of the equipment.
The online analysis module compares the current hour average value with the daily average value, the month average value, the former three-month average value and the historical average value in each hour to obtain the difference between the current hour average value and the daily average value, the month average value, the former three-month average value and the historical average value, so that the difference between the current running state and the normal running state of the equipment is found, and the real-time online diagnosis of the energy efficiency and the safety of the equipment is realized.
The offline analysis module comprises a historical data recording module, and the data recording module records the relevant energy efficiency and safety parameter variable values of the equipment according to the period of 15 min.
Based on the historical data recording module, the state differences of the equipment parameters in different daily periods, month periods and year periods are obtained through the time ratio analysis module.
Based on the historical data recording module, the state differences of a plurality of devices in selected daily periods, month periods and year periods are obtained through the analogy analysis module.
And comprehensively diagnosing the energy efficiency and the safety problem of the equipment through the time ratio analysis module and the analogy analysis module, and outputting corresponding energy-saving improvement strategy suggestions.
The invention relates to an energy efficiency safety diagnosis system based on real-time online analysis and simulated offline analysis, which comprises the steps of establishing a mathematical analysis model based on process characteristics through various energy consumption data and related operation parameters of equipment and working procedures collected by a system on the basis of an energy monitoring management system; carrying out deep analysis on operation safety and economy of equipment and working procedures and energy efficiency data in time through real-time online analysis, and automatically generating analysis conclusion, improving advice and alarming prompt; by means of off-line simulation analysis, safety hidden danger and energy-saving space existing in equipment and working procedures are diagnosed by combining big data analysis and predictive analysis models aiming at the operation characteristics of the equipment and the working procedures. In a cement mill, aiming at a cement mill system, a data acquisition module acquires data such as temperature, current, active power, yield and the like of the cement mill system in real time, and according to the data processing mode, according to the equipment state, an average value of 15 minutes is obtained every 15 minutes, an average value of hours is obtained every hour, and a daily average value is obtained every day. And updating the month average value, the march average value and the historical average value at the end of each month. According to the process characteristics of the monitoring object, the hour average value and the day average value are respectively compared with the month average value, the March average value or the history average value, when the comparison difference exceeds a certain range, the current running state of the equipment is changed beyond a normal range, the energy consumption change or the running safety failure can be caused, and then the conclusion that the current running state of the cement grinding system exceeds the normal range compared with the history running data can be the problems of unreasonable steel ball grading, unreasonable temperature control, unreasonable material feeding quantity control and the like. And guiding the user to process through the real-time conclusion. If the system is aimed at a plurality of cement grinding systems, comparing the data differences of temperature, current, active power, output and the like among a plurality of cement grinding systems through analog analysis, comparing the current small time difference average value, daily average value and month average value, and the March average value and the history average value, and generating an aimed conclusion to guide a user to process. In the offline analysis, the historical data of the cement grinding mill system is subjected to data comparison in any two selected time periods, or the data of the two cement grinding mill systems in the same time period is compared, the difference of the two cement grinding mill systems in the comparison time periods is obtained, the abnormality is diagnosed, the energy consumption and the safety problem of the cement grinding mill system are found, and a user is guided to carry out improvement optimization.
The innovation points of the invention include: 1. selecting any parameters affecting the economy and operation safety of equipment and working procedures to perform data analysis to obtain a diagnosis conclusion; 2. adopting a dual analysis mode of online analysis and offline simulation analysis; 3. the data representing the characteristic state of the analysis object is obtained from a large amount of data in a time sequence rolling processing mode according to the running state and the characteristic of the data, so that the diagnosis problems of energy efficiency difference and running state difference under the conditions of big data, multiple variable types and complicated equipment procedures are solved, and the processing speed requirement is met. 4. Through data comparison analysis, including time ratio and category analysis, and combining equipment process characteristics, an analysis conclusion is timely generated, a suggestion is improved, and an alarm prompt is given to guide a user to operate on site, so that energy conservation and efficiency improvement are realized.
Claims (5)
1. An energy efficiency safety diagnosis system based on real-time online analysis and simulated offline analysis is characterized in that: the system comprises an online analysis module, an offline analysis module, a time ratio analysis module and an analogy analysis module; the online analysis module comprises a data acquisition module, a data processing module and a diagnosis module;
the data acquisition module acquires the technological parameter variables of energy efficiency and operation safety related to equipment or working sections according to equipment and working procedure characteristics at certain periodic intervals t, and respectively defines variable values as Ai, bi and …, and the corresponding acquisition values are respectively recorded as (A) 0 ，A 1 ，A 2 ，…，A n ），（B 0 ，B 1 ，B 2 ，…，B n ) …, determining energy efficiency and safety process parameter variables of equipment and working sections;
the data processing module acquires the data of the data acquisition module and performs operation and processing of the data; according to the operation parameters of the equipment, the time of the change of the operation state of the equipment and the changed state value S are obtained, the definition is 1 when the equipment is in the operation state, and the definition is 0 when the equipment is in the shutdown state; setting a time synchronization T, wherein the time synchronization T is 15min, and recording that the period is valid when the equipment states are all 1 in one time synchronization T, otherwise, recording that the period is invalid; calculating the average value of each variable in the same period T of the set time, respectively calculating and obtaining the daily average value, the monthly average value, the former three-month average value and the historical average value under the normal running state of the equipment according to the calendar time,
grouping the process parameter variables of energy consumption and operation safety according to a period of 15min, wherein the number of each group of variables is j=0.25/t,
when T is i When the period is effective, calculating the average value of each variable in the period, and taking the variable value as an instantaneous valueAnd the accumulated value are divided into two algorithms, let A i Expressed as instantaneous value type variable, B i Expressed as a cumulative value type variable, the algorithm of the corresponding average value is as follows,
for a variable A of the instantaneous value type i Average value ofThe calculation method comprises the following steps: />,
Variable B for cumulative value type i Average value ofThe calculation method comprises the following steps: />,/>For the last value of the variable in each period T, B 0 For the last value of the previous T period of the period,
after the mean value of each variable of the effective T period is obtained through the algorithm, the mean value of each effective period is sequentially defined as M k Respectively calculating corresponding hour average values, day average values, month average values, previous three-month average values and history average values according to calendar time,
the average value of the hours is denoted as Mh, and the effective period number of each hour is denoted as a
,
The average daily value is denoted as Md, and the average value of 12 hours per day is denoted as Mh 1 ，Mh 2 ，…，Mh 12 The number of effective cycles per hour of 12 hours per day is denoted as a 1 ，a 2 ，…，a 12 The daily average value is obtained as
,
The average value of the month is Mm, and the average value of the day of each month is Md 1 ，Md 2 ，…，Md p The number of effective cycles per day in the month is denoted as b 1 ，b 2 ，…，b p P is the total number of days of the month, and the average value of the month is obtained
,
The average value of the former March is marked as M3M, and the average values of the former 1,2 and 3 months are respectively marked as Md -1 ，Md -2 ，Md -3 The effective period corresponding to three months is marked as c 1 ，c 2 ，c 3 The average value of the first three months is obtained as
,
The history mean is recorded as MY, the history mean is the sum of all history effective values divided by the number of all effective values, and in order to realize rapid calculation, the history mean is updated once every month, and the history mean of the last month is defined as MY -1 The historical average of the current month is MY 0 Calculating the average value of the current month by using the last month calendar Shi Junzhi and the month average value of the current month to ensure that the month average value of the current month is Mm, the effective cycle number of the current month is d, and the history average value calculated in the last month is MY -1 The total historical effective cycle number is e when the historical average value is counted in the last month, and the current month historical average value calculating method comprises the following steps:
,
according to the calculation method, the daily average value, the monthly average value, the former three-month average value and the historical average value of the monitoring variable are calculated and obtained according to the period of hours, days, months and months in the normal running state of the equipment;
the diagnosis module realizes real-time online diagnosis of equipment energy efficiency and safety according to the difference between the current time period average value and the historical time period average value; the diagnosis module compares the current time period average value with the daily average value, the monthly average value, the former three-month average value and the historical average value which are obtained in the normal running state of the equipment through calculation, and obtains the difference between the current time period average value and the daily average value, the monthly average value, the former three-month average value and the historical average value, so that the difference between the current running state and the normal running state of the equipment is found, and the real-time online diagnosis of the equipment energy efficiency and safety is realized;
the offline analysis module comprises a historical data recording module for recording the energy efficiency and safety parameter variable values related to the equipment;
the time ratio analysis module is used for obtaining state differences of equipment parameters in different time periods;
the analog analysis module is used for obtaining state differences of a plurality of devices in a selected period;
and comprehensively diagnosing to obtain the energy efficiency and safe energy-saving improvement strategy suggestion of the equipment through the time ratio analysis module and the analogy analysis module.
2. The energy efficiency security diagnostic system based on real-time online analysis and simulated offline analysis of claim 1, wherein: the current time period in the diagnosis module is hours, the current hour average value is compared with the daily average value, the month average value, the previous three-month average value and the historical average value in each hour, and the difference between the current hour average value and the daily average value, the month average value, the previous three-month average value and the historical average value is obtained, so that the difference between the current running state and the normal running state of equipment is found, and the real-time online diagnosis of the energy efficiency and the safety of the equipment is realized.
3. The energy efficiency security diagnostic system based on real-time online analysis and simulated offline analysis of claim 1, wherein: the historical data recording module records the relevant energy efficiency and safety parameter variable values of the equipment according to the period of 15 min.
4. The energy efficiency security diagnostic system based on real-time online analysis and simulated offline analysis of any of claims 1-3, wherein: the time ratio analysis module obtains the state differences of the equipment parameters in different daily periods, month periods and year periods on the basis of the data recording module; the analog analysis module obtains the state differences of a plurality of devices in selected daily periods, month periods and year periods on the basis of the data recording module.
5. The energy efficiency security diagnostic system based on real-time online analysis and simulated offline analysis of any of claims 1-3, wherein: and through the time ratio analysis module and the analogy analysis module, the accurate energy efficiency difference and the safe running state difference of the equipment are obtained through comprehensive diagnosis, and corresponding energy saving improvement strategy suggestions are output.
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