CN114282805A - Industrial energy-saving method and system of multi-dimensional platform based on physical property data generation - Google Patents

Industrial energy-saving method and system of multi-dimensional platform based on physical property data generation Download PDF

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CN114282805A
CN114282805A CN202111592384.7A CN202111592384A CN114282805A CN 114282805 A CN114282805 A CN 114282805A CN 202111592384 A CN202111592384 A CN 202111592384A CN 114282805 A CN114282805 A CN 114282805A
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physical property
property data
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谢玉辉
童大山
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Guangzhou Souliao Information Technology Co ltd
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Abstract

The invention discloses an industrial energy-saving method of a multi-dimensional platform based on physical property data, which comprises the steps of collecting physical property data generated in the multi-dimensional platform, processing the physical property data to obtain a correlation coefficient of the physical property data, calculating a correlation threshold of the physical property data according to an energy-saving instruction, and obtaining an attention list of the physical property data according to the correlation threshold. The invention realizes that the physical property data of specific types can be selectively focused, and the expense of processing capacity is reduced.

Description

Industrial energy-saving method and system of multi-dimensional platform based on physical property data generation
Technical Field
The invention relates to the technical field of energy management and energy conservation, in particular to an industrial energy-saving method and system of a multi-dimensional platform based on physical property data generation.
Background
The production process of large-scale industrial mechanical equipment is complex, the control of the process flow does not depend on single data, the scheduling efficiency is low only by manually controlling the equipment, the problems of energy shortage and environmental pollution become global urgent problems, China is a large industrial country, the industrial energy consumption accounts for a large proportion, under the pressure of current energy reduction, industrial energy conservation becomes the first task, and the method is also an important means for reducing the total carbon emission.
The industrial energy-saving emission-reduction control is generated under the large background of green sustainable development of energy conservation and emission reduction. With the increasing development of the industrial production towards integration and large-scale, the complexity of a modern industrial process system is continuously increased, and energy conservation, consumption reduction, safety and environmental protection become the primary targets of automation.
The characteristics of large-scale industry, such as long process, strong coupling of industrial data, nonlinearity, large time lag, multiple constraints and multiple targets, and multiple uncertain factors, interference sources and the like of the process become main problems of comprehensive control.
The energy management level of the current enterprise is relatively extensive, the energy management level cannot be detailed to each step of industrial production, the existing detection means has single function, each system is isolated, linkage is lacked, for example, a control method of an industrial energy-saving emission-reduction control device with the publication number of CN104122878A is used, a dynamic model capable of predicting the future behavior of the process is built by utilizing a mathematical model, the control action and various constraints in variables and operation variables are repeatedly optimized and calculated on line and are implemented in a rolling manner, and the method is too complex for industrial production, narrow in application range and incapable of coping with variable processes.
Disclosure of Invention
In view of the above, the present invention is directed to an industrial energy saving method for generating a multidimensional platform based on physical property data, so as to solve one or more technical problems in the prior art and provide at least one useful choice or creation condition.
In order to achieve the technical purpose, the technical scheme of the invention is as follows:
an industrial energy saving method for a multi-dimensional platform based on physical property data generation, the method comprising the steps of:
step 1, collecting physical property data generated in a multi-dimensional platform;
step 2, processing the physical property data to obtain a correlation coefficient of the physical property data;
step 3, calculating a correlation threshold value of the physical property data according to the energy-saving instruction;
and 4, obtaining an attention list of the physical property data according to the correlation threshold.
Further, in step 1, the substep of collecting the physical property data generated in the multidimensional platform is:
the physical property data generated in the multi-dimensional platform are collected, the physical property data can be actively acquired or pushed from a data source, the data source can be a sensor and/or an external data source, parameters which can be manually input or parameters which can be automatically generated by a control program are actively acquired, the sensor can acquire the data in the multi-dimensional platform, and the physical property data can be related, namely one physical property data is related to the other physical property data, the relationship can be from the same data source, and the numerical change of the numerical physical property data is related or is read simultaneously.
Further, in step 2, the substep of processing the physical property data to obtain the correlation coefficient of the physical property data comprises:
step 2.1, obtaining physical property data, wherein the physical property data lasts for a first time interval T0, all the physical property data are recorded as a physical property data set WX ═ { WXi }, rlx (WXi) is associated data for obtaining the ith physical property data WXi, and rlx (WXi) refers to a WXi associated data set and comprises physical property data related to WXi;
step 2.2, traversing the correlation coefficient RLC of each physical property data:
Figure BDA0003430231180000021
where RLCi refers to the correlation coefficient of the ith data WXi in the physical property data set, the correlation coefficient is used to describe the correlation size of one physical property data with other physical property data, n (WXi) refers to the number of data homologous to WXi in the physical property data set WX, len (rlxi) refers to the size of the physical property data set WXi, abs () refers to the absolute value, and g (rlx (WXi)j) The time difference from the acquisition time of the jth element in the Wxi associated data set to the current time is obtained, g (Wxi) the time difference from the acquisition time of the physical property data Wxi to the current time is obtained, and T0 is a first time interval;
step 2.3, the correlation coefficients RLC of all the physical data form a relation set RLS;
and (3) if the energy-saving instruction is triggered, skipping to the step 3, and clearing the physical property data set, otherwise, restarting the step 2.
Preferably, the step 2 may further be processing the physical property data, and the sub-step of obtaining the set to be transferred is:
step 2.1, filling the collected physical property data into a temporary area, and skipping to the step 2.2 after the temporary area is filled; initializing a set PND to be transferred as an empty set;
step 2.2, obtaining the number of items of physical property data in the temporary area as nCAT, wherein a physical property data set DAT of all the physical property data is { DATi }, i belongs to [1, nCAT ], and initializing the value of i as 1; a single element DATi in the data set DAT is physical property data under a data set and represents all physical property data in a temporary area under the ith physical property data, the DATi is a dynamic set, the physical property data in the DATi can change in a time period from the current moment to before a first time interval INT0, but the size of the single data set DATi, namely LEN (DATi), can not change in a time interval, and if new same data enters, the data obtained earliest in the single data set DATi is transferred to an archiving area; skipping to the step 2.3; wherein the same physical data represents that the physical data comes from the same source or data source
Step 2.3, if the DATi meets the first condition or the second condition, skipping to step 2.4, and not meeting the skipping to step 2.5;
setting a first condition as follows:
nF(DATi)/LEN(DATi)≤(LEN(DATi)+LEN'(DATi))/LEN(DAT)，
or DIFF (DATi) < WT (DATi) × abs (MEAN (DATi) — MED (DATi));
where nf (dai) indicates the number of accesses to the physical property data under the datati in the period from the current time to the time before the first time interval INT0, the number of accesses being the sum of the number of times of reading and the number of times of writing of the physical property data of the current kind, diff (dai) being the extreme value of all data in the single data set DATi, the extreme value being equal to max (dai) -min (dai), max (dai) being the maximum value in the current DATi, min (dai) being the minimum value in the current DATi, LEN (dai) being the size of the single data set DATi at the current time, i.e. the number of physical property data in the single data set DATi, LEN '(dai) being the size of the single data set DATi in the period from the current time to the time before the first time interval INT0, i.e. the number of physical property data of the single data set DATi in the period from the current time to the first time interval INT0, if the period from the current time to the time before the first time interval INT0 or the absence of the single data set DATi' (dai), taking the value of LEN' (DATi) as LEN (DATi), LEN (DAT) as the size of the physical property data set, namely the total quantity of physical property data in the physical property data set, WT (DATi) as the new data volume of the physical property data type in the time period from the current moment to the time interval before INT0, MEAN (DATi) as the arithmetic mean of the data in the single-term data set DATi, MED (DATi) as the median of the data in the single-term data set DATi, and abs () as the absolute value operation;
the second condition is that the difference GAP (DATi) of DATi satisfies:
GAP(DATi)＜∑((MAX(DATi)/LEN(DATi))-MEAN(DATi))；
and/or hit coefficient HIT (DATi) of DATi satisfies:
HIT(DATi)＜exp(LEN(DATi)/LEN(MAXN(DAT)))2×THIT(DAT)；
wherein the difference value gap (datati) ═ (max (dai) -min (dai))/(avg (fetcht) × LastS × mean (dai)), max (dai)) is, Σ () is a summation operation, mean (dai)) is an arithmetic average of data in the single data set DATi, exp () is an exponential function with a natural logarithm e as a base, hit (dat) is the number of accesses of all physical data in the temporary region in the last first time interval INT0, the number of accesses being the sum of the number of reads and the number of writes of all kinds of physical data;
step 2.4, adding the physical property data of the current single data set DATi into the set PND to be transferred, if i is less than nCAT, increasing the value of i by 1, and skipping to step 2.2, otherwise skipping to step 2.6;
step 2.5, if i is less than nCAT, increasing the value of i by 1, skipping to step 2.2, otherwise skipping to step 2.6; step 2.6, if the set to be transferred PND is empty, waiting for the first time interval INT0, and restarting the step 2.2; otherwise, jumping to step 3.
Further, in step 3, the substep of calculating the correlation threshold value of the physical property data based on the energy saving command is: acquiring a physical property data category related to an energy saving command as a physical property data category set CAT, putting physical property data belonging to a physical property data category in the physical property data category set CAT in a physical property data set WX into a target physical property data set TRF, wherein a correlation coefficient RLC of physical property data of each target physical property data set TRF forms a set target correlation coefficient set RLC which is { RLCk }, the size of the RLC set is K, and K belongs to [1, K ], calculating a correlation threshold RTH:
RTH＝(∑(RCLk)/len(CAT))×exp(len(CAT)/NUM(RCLk))；
in the formula, RTH is a correlation threshold value, Σ (RCLk) is a sum of correlation coefficients of all physical property data in a target correlation coefficient set, len (CAT) is a size of an acquired physical property data type CAT, num (RCLk) is a number of physical property data types to which the physical property data RCLk belongs in a target physical property data set TRF, a data type refers to a source of the physical property data, and physical property data of the same data type indicates that the physical property data come from the same data source.
Preferably, step 3 may be to process the set to be transferred to obtain a set of degraded items, and the sub-step of performing the transfer operation on the set of degraded items is:
step 3.1, calculating the SYI utilization index of each single data set in the to-be-transferred set PND: SYIj＝exp(LastF/INT0)×(LastN/avgN)2；
SYIjThe method comprises the steps that the utilization index of a j-th single data set in a to-be-transferred set PND is obtained, exp () is an exponential function with a natural logarithm e as a base, LastF is the last reading time LastF of physical property data in a current single data set, INT0 is a first time interval, LastN is the access times of the physical property data in the current single data set, the access times are the sum of the reading times and the writing times of all the physical property data of the current single data set in a time period from the current time to before a first time interval INT0, avgN is the average access times, and the average access times are the sum of the reading times and the writing times of all the physical property data in the transfer set PND in the time period from the current time to before the first time interval INT0 divided by the number of physical property data in the transfer set PND;
step 3.2, obtaining SYI utilization indexes of all current single data sets in the PND set to be transferred, screening out the single data sets with the SYI utilization indexes lower than the average value, marking the single data sets as a degradation item set DWS with the size of K, wherein K belongs to [1, K ], and DWSk represents the kth single data set in the degradation item set DWS; bringing the value of k to 1; initializing the value of A to be 0;
step 3.3, if the size of the single data set DWSk, namely len (datk), is larger than 1, the size of the single data set to which the single data set belongs, namely len (datk), is reduced by 1, otherwise, the corresponding single data set is removed from the physical property data set, namely, if new data belonging to the current single data set are not transmitted to a temporary region, the new data are directly put into a database file region for storage, the physical property data of the corresponding single data set are removed from the temporary region to the file region of the database, and the value of a is increased by 1; if K < K, step 3.3 is restarted by increasing the value of K by 1, otherwise step 4 is skipped.
Further, in step 4, the substep of obtaining the attention list of the physical property data based on the correlation threshold value is:
the kind of physical property data of the physical property data of which the correlation coefficient RLC is smaller than the correlation threshold RTH in the physical property data set WX is listed in an attention list, wherein the attention list refers to the physical property data needing attention when the industrial energy-saving measure is executed. Preferably, the substep of adjusting the physical property data set of the temporary region is:
acquiring the free space capacity FS of the current temporary area, acquiring the physical property data FS of the capacity which is read or written into the database archiving area in the time period from the current moment to the first time interval INT0, and adding the physical property data FS into a physical property data set DAT; emptying a degradation item set DWS; waiting for the first time interval INT0, step 2.2 is restarted.
An industrial energy saving system based on a multi-dimensional platform generated from physical property data, the system comprising:
the physical property data acquisition module: the physical property data can be from various sensors of the industrial production line or parameters input by a user;
the physical property data storage module: the system comprises an archiving area and a temporary area, wherein the temporary area is a fixed-capacity quick accessible space;
the physical property data processing module: steps for executing the application of any of claims 1-5.
In a third aspect, the present invention provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the method provided by the first aspect of the present invention.
In a fourth aspect, the present invention provides an electronic device comprising: a memory having a computer program stored thereon; a processor for executing the computer program in the memory to implement the steps of the method provided by the present invention.
Compared with the prior art, the invention has the following beneficial technical effects:
it is possible to selectively focus on specific types of physical data and reduce the overhead of processing capacity.
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The foregoing and other features of the present invention will become more apparent to those skilled in the art from the following detailed description of the embodiments taken in conjunction with the accompanying drawings, in which like reference characters designate the same or similar elements, and in which it is apparent that the drawings described below are merely exemplary of the invention and that other drawings may be derived therefrom without the inventive faculty, to those skilled in the art, and in which:
FIG. 1 is a flow chart of an industrial energy-saving method of a multi-dimensional platform based on physical property data generation provided by the invention;
fig. 2 is a block diagram illustrating an industrial energy saving system of a multi-dimensional platform based on physical property data generation according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more clear, the present invention is further described in detail below with reference to the accompanying drawings and embodiments. The specific embodiments described herein are merely illustrative of the invention and are not intended to be limiting.
It is also to be understood that the following examples are illustrative of the present invention and are not to be construed as limiting the scope of the invention, and that certain insubstantial modifications and adaptations of the invention by those skilled in the art in light of the foregoing description are intended to be included within the scope of the invention. The specific process parameters and the like of the following examples are also only one example within a suitable range, i.e., those skilled in the art can select the appropriate range through the description herein, and are not limited to the specific values exemplified below.
The industrial energy-saving method based on the multi-dimensional platform generated by the physical property data provided by the invention is exemplarily described below.
Referring to fig. 1, a flow chart of an industrial energy saving method for a multi-dimensional platform based on physical property data generation is shown, and the industrial energy saving method for a multi-dimensional platform based on physical property data generation according to an embodiment of the present invention is described below with reference to fig. 1, the method including the following steps:
step 1, collecting physical property data generated in a multi-dimensional platform;
step 2, processing the physical property data to obtain a correlation coefficient of the physical property data;
step 3, calculating a correlation threshold value of the physical property data according to the energy-saving instruction;
and 4, obtaining an attention list of the physical property data according to the correlation threshold.
Further, in step 1, the substep of collecting the physical property data generated in the multidimensional platform is:
the physical property data generated in the multi-dimensional platform are collected, the physical property data can be actively acquired or pushed from a data source, the data source can be a sensor and/or an external data source, parameters which can be manually input or parameters which can be automatically generated by a control program are actively acquired, the sensor can acquire the data in the multi-dimensional platform, and the physical property data can be related, namely one physical property data is related to the other physical property data, the relationship can be from the same data source, and the numerical change of the numerical physical property data is related or is read simultaneously.
Further, in step 2, the substep of processing the physical property data to obtain the correlation coefficient of the physical property data comprises:
step 2.1, obtaining physical property data, wherein the physical property data lasts for a first time interval T0, all the physical property data are recorded as a physical property data set WX ═ { WXi }, rlx (WXi) is associated data for obtaining the ith physical property data WXi, and rlx (WXi) refers to a WXi associated data set and comprises physical property data related to WXi;
step 2.2, traversing the correlation coefficient RLC of each physical property data:
Figure BDA0003430231180000051
where RLCi refers to the correlation coefficient of the ith data WXi in the physical property data set, the correlation coefficient is used to describe the correlation size of one physical property data with other physical property data, n (WXi) refers to the number of data homologous to WXi in the physical property data set WX, len (rlxi) refers to the size of the physical property data set WXi, abs () refers to the absolute value, and g (rlx (WXi)j) The time difference from the acquisition time of the jth element in the Wxi associated data set to the current time is obtained, g (Wxi) the time difference from the acquisition time of the physical property data Wxi to the current time is obtained, and T0 is a first time interval;
step 2.3, the correlation coefficients RLC of all the physical data form a relation set RLS;
and (3) if the energy-saving instruction is triggered, skipping to the step 3, and clearing the physical property data set, otherwise, restarting the step 2.
Preferably, the step 2 may further be processing the physical property data, and the sub-step of obtaining the set to be transferred is:
step 2.1, filling the collected physical property data into a temporary area, and skipping to the step 2.2 after the temporary area is filled; initializing a set PND to be transferred as an empty set;
step 2.2, obtaining the number of items of physical property data in the temporary area as nCAT, wherein a physical property data set DAT of all the physical property data is { DATi }, i belongs to [1, nCAT ], and initializing the value of i as 1; a single element DATi in the data set DAT is physical property data under a data set and represents all physical property data in a temporary area under the ith physical property data, the DATi is a dynamic set, the physical property data in the DATi can change in a time period from the current moment to before a first time interval INT0, but the size of the single data set DATi, namely LEN (DATi), can not change in a time interval, and if new same data enters, the data obtained earliest in the single data set DATi is transferred to an archiving area; skipping to the step 2.3; wherein the same physical data represents that the physical data comes from the same source or data source
Step 2.3, if the DATi meets the first condition or the second condition, skipping to step 2.4, and not meeting the skipping to step 2.5;
setting a first condition as follows:
nF(DATi)/LEN(DATi)≤(LEN(DATi)+LEN'(DATi))/LEN(DAT)，
or DIFF (DATi) < WT (DATi) × abs (MEAN (DATi) — MED (DATi));
where nf (dai) indicates the number of accesses to the physical property data under the datati in the period from the current time to the time before the first time interval INT0, the number of accesses being the sum of the number of times of reading and the number of times of writing of the physical property data of the current kind, diff (dai) being the extreme value of all data in the single data set DATi, the extreme value being equal to max (dai) -min (dai), max (dai) being the maximum value in the current DATi, min (dai) being the minimum value in the current DATi, LEN (dai) being the size of the single data set DATi at the current time, i.e. the number of physical property data in the single data set DATi, LEN '(dai) being the size of the single data set DATi in the period from the current time to the time before the first time interval INT0, i.e. the number of physical property data of the single data set DATi in the period from the current time to the first time interval INT0, if the period from the current time to the time before the first time interval INT0 or the absence of the single data set DATi' (dai), taking the value of LEN' (DATi) as LEN (DATi), LEN (DAT) as the size of the physical property data set, namely the total quantity of physical property data in the physical property data set, WT (DATi) as the new data volume of the physical property data type in the time period from the current moment to the time interval before INT0, MEAN (DATi) as the arithmetic mean of the data in the single-term data set DATi, MED (DATi) as the median of the data in the single-term data set DATi, and abs () as the absolute value operation;
the second condition is that the difference GAP (DATi) of DATi satisfies:
GAP(DATi)＜∑((MAX(DATi)/LEN(DATi))-MEAN(DATi))；
and/or hit coefficient HIT (DATi) of DATi satisfies:
HIT(DATi)＜exp(LEN(DATi)/LEN(MAXN(DAT)))2×THIT(DAT)；
wherein the difference value gap (datati) ═ (max (dai) -min (dai))/(avg (fetcht) × LastS × mean (dai)), max (dai)) is, Σ () is a summation operation, mean (dai)) is an arithmetic average of data in the single data set DATi, exp () is an exponential function with a natural logarithm e as a base, hit (dat) is the number of accesses of all physical data in the temporary region in the last first time interval INT0, the number of accesses being the sum of the number of reads and the number of writes of all kinds of physical data;
step 2.4, adding the physical property data of the current single data set DATi into the set PND to be transferred, if i is less than nCAT, increasing the value of i by 1, and skipping to step 2.2, otherwise skipping to step 2.6;
step 2.5, if i is less than nCAT, increasing the value of i by 1, skipping to step 2.2, otherwise skipping to step 2.6;
step 2.6, if the set to be transferred PND is empty, waiting for the first time interval INT0, and restarting the step 2.2; otherwise, jumping to step 3.
Further, in step 3, the substep of calculating the correlation threshold value of the physical property data based on the energy saving command is:
acquiring a physical property data category related to an energy saving command as a physical property data category set CAT, putting physical property data belonging to a physical property data category in the physical property data category set CAT in a physical property data set WX into a target physical property data set TRF, wherein a correlation coefficient RLC of physical property data of each target physical property data set TRF forms a set target correlation coefficient set RLC which is { RLCk }, the size of the RLC set is K, and K belongs to [1, K ], calculating a correlation threshold RTH:
RTH＝(∑(RCLk)/len(CAT))×exp(len(CAT)/NUM(RCLk))；
in the formula, RTH is a correlation threshold value, Σ (RCLk) is a sum of correlation coefficients of all physical property data in a target correlation coefficient set, len (CAT) is a size of an acquired physical property data type CAT, num (RCLk) is a number of physical property data types to which the physical property data RCLk belongs in a target physical property data set TRF, a data type refers to a source of the physical property data, and physical property data of the same data type indicates that the physical property data come from the same data source.
Preferably, step 3 may be to process the set to be transferred to obtain a set of degraded items, and the sub-step of performing the transfer operation on the set of degraded items is:
step 3.1, calculating the SYI utilization index of each single data set in the to-be-transferred set PND:
SYIj＝exp(LastF/INT0)×(LastN/avgN)2；
SYIjthe method comprises the steps that the utilization index of a j-th single data set in a to-be-transferred set PND is obtained, exp () is an exponential function with a natural logarithm e as a base, LastF is the last reading time LastF of physical property data in a current single data set, INT0 is a first time interval, LastN is the access times of the physical property data in the current single data set, the access times are the sum of the reading times and the writing times of all the physical property data of the current single data set in a time period from the current time to before a first time interval INT0, avgN is the average access times, and the average access times are the sum of the reading times and the writing times of all the physical property data in the transfer set PND in the time period from the current time to before the first time interval INT0 divided by the number of physical property data in the transfer set PND;
step 3.2, obtaining SYI utilization indexes of all current single data sets in the PND set to be transferred, screening out the single data sets with the SYI utilization indexes lower than the average value, marking the single data sets as a degradation item set DWS with the size of K, wherein K belongs to [1, K ], and DWSk represents the kth single data set in the degradation item set DWS; bringing the value of k to 1; initializing the value of A to be 0;
step 3.3, if the size of the single data set DWSk, namely len (datk), is larger than 1, the size of the single data set to which the single data set belongs, namely len (datk), is reduced by 1, otherwise, the corresponding single data set is removed from the physical property data set, namely, if new data belonging to the current single data set are not transmitted to a temporary region, the new data are directly put into a database file region for storage, the physical property data of the corresponding single data set are removed from the temporary region to the file region of the database, and the value of a is increased by 1; if K < K, step 3.3 is restarted by increasing the value of K by 1, otherwise step 4 is skipped.
Further, in step 4, the substep of obtaining the attention list of the physical property data based on the correlation threshold value is: the kind of physical property data of the physical property data of which the correlation coefficient RLC is smaller than the correlation threshold RTH in the physical property data set WX is listed in an attention list, wherein the attention list refers to the physical property data needing attention when the industrial energy-saving measure is executed. Preferably, step 4 may be a substep of adjusting the set of physical property data of the temporary region, comprising:
acquiring the free space capacity FS of the current temporary area, acquiring the physical property data FS of the capacity which is read or written into the database archiving area in the time period from the current moment to the first time interval INT0, and adding the physical property data FS into a physical property data set DAT; emptying a degradation item set DWS; waiting for the first time interval INT0, step 2.2 is restarted.
Compared with the prior art, the invention has the following beneficial technical effects:
it is possible to selectively focus on specific types of physical data and reduce the overhead of processing capacity.
Fig. 2 is a block diagram illustrating an industrial energy saving system of a multi-dimensional platform based on physical property data generation according to an embodiment of the present invention.
An industrial energy saving system based on a multi-dimensional platform generated from physical property data, the system comprising:
the physical property data acquisition module: the physical property data can be from various sensors of the industrial production line or parameters input by a user;
the physical property data storage module: the system comprises an archiving area and a temporary area, wherein the temporary area is a fixed-capacity quick accessible space;
the physical property data processing module: steps for executing the application of any of claims 1-5.
In a third aspect, the present invention provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the method provided by the first aspect of the present invention.
In a fourth aspect, the present invention provides an electronic device comprising: a memory having a computer program stored thereon; a processor for executing the computer program in the memory to implement the steps of the method provided by the present invention.
The industrial energy-saving system based on the multi-dimensional platform generated based on the physical property data can be operated in computing equipment such as desktop computers, notebooks, palm computers and cloud servers. The industrial energy-saving system based on the multi-dimensional platform generated by the physical property data can be operated by a system comprising, but not limited to, a processor and a memory. Those skilled in the art will appreciate that the example is only an example of the industrial energy saving system of the multi-dimensional platform generated based on the physical property data, and does not constitute a limitation of the industrial energy saving system of the multi-dimensional platform generated based on the physical property data, and may include more or less components than a proportion, or combine some components, or different components, for example, the industrial energy saving system of the multi-dimensional platform generated based on the physical property data may further include an input and output device, a network access device, a bus, and the like.
The Processor may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component, or the like. The general-purpose processor may be a microprocessor, which is a control center of the industrial economizer system operating system of the multi-dimensional platform generated based on the physical property data, and various interfaces and lines are used to connect the respective parts of the industrial economizer system operating system of the multi-dimensional platform generated based on the physical property data.
The memory can be used for storing the computer program and/or the module, and the processor can realize various functions of the industrial energy-saving system of the multi-dimensional platform based on physical property data generation by running or executing the computer program and/or the module stored in the memory and calling the data stored in the memory. The memory may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data (such as audio data, a phonebook, etc.) created according to the use of the cellular phone. In addition, the memory may include high speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), at least one magnetic disk storage device, a Flash memory device, or other volatile solid state storage device.
Although the present invention has been described in considerable detail and with reference to certain illustrated embodiments, it is not intended to be limited to any such details or embodiments or any particular embodiment, so as to effectively encompass the intended scope of the invention. Furthermore, the foregoing describes the invention in terms of embodiments foreseen by the inventor for which an enabling description was available, notwithstanding that insubstantial modifications of the invention, not presently foreseen, may nonetheless represent equivalent modifications thereto.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an illustrative embodiment," "an example," "a specific example," or "some examples" or the like mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
While embodiments of the invention have been shown and described, it will be understood by those of ordinary skill in the art that: various changes, modifications, substitutions and alterations can be made to the embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.

Claims (8)

1. An industrial energy-saving method of a multi-dimensional platform based on physical property data generation is characterized by comprising the following steps:
step 1, collecting physical property data generated in a multi-dimensional platform;
step 2, processing the physical property data to obtain a correlation coefficient of the physical property data;
step 3, calculating a correlation threshold value of the physical property data according to the energy-saving instruction;
and 4, obtaining an attention list of the physical property data according to the correlation threshold.
2. The industrial energy saving method for the multi-dimensional platform based on the physical property data generation as claimed in claim 1, wherein the sub-step of collecting the physical property data generated in the multi-dimensional platform in step 1 is:
the physical property data generated in the multi-dimensional platform are collected, the physical property data can be actively acquired or pushed from a data source, the data source can be a sensor and/or an external data source, parameters which can be manually input or parameters which can be automatically generated by a control program are actively acquired, the sensor can acquire the data in the multi-dimensional platform, and the physical property data can be related, namely one physical property data is related to the other physical property data, the relationship can be from the same data source, and the numerical change of the numerical physical property data is related or is read simultaneously.
3. The industrial energy saving method for the multi-dimensional platform based on the physical property data generation as claimed in claim 1, wherein in the step 2, the physical property data is processed, and the sub-step of obtaining the correlation coefficient of the physical property data comprises:
step 2.1, obtaining physical property data, wherein the physical property data lasts for a first time interval T0, all the physical property data are recorded as a physical property data set WX ═ { WXi }, rlx (WXi) is associated data for obtaining the ith physical property data WXi, and rlx (WXi) refers to a WXi associated data set and comprises physical property data related to WXi;
step 2.2, traversing the correlation coefficient RLC of each physical property data:
Figure FDA0003430231170000011
where RLCi refers to the correlation coefficient of the ith data WXi in the physical property data set, the correlation coefficient is used to describe the correlation size of one physical property data with other physical property data, n (WXi) refers to the number of data homologous to WXi in the physical property data set WX, len (rlxi) refers to the size of the physical property data set WXi, abs () refers to the absolute value, and g (rlx (WXi)j) The time difference from the acquisition time of the jth element in the Wxi associated data set to the current time is obtained, g (Wxi) the time difference from the acquisition time of the physical property data Wxi to the current time is obtained, and T0 is a first time interval;
step 2.3, the correlation coefficients RLC of all the physical data form a relation set RLS;
and (3) if the energy-saving instruction is triggered, skipping to the step 3, and clearing the physical property data set, otherwise, restarting the step 2.
4. The industrial energy saving method for the multi-dimensional platform based on physical property data generation as claimed in claim 1, wherein the substep of calculating the correlation threshold of the physical property data according to the energy saving command in step 3 is:
acquiring a physical property data category related to an energy saving command as a physical property data category set CAT, putting physical property data belonging to a physical property data category in the physical property data category set CAT in a physical property data set WX into a target physical property data set TRF, wherein a correlation coefficient RLC of physical property data of each target physical property data set TRF forms a set target correlation coefficient set RLC which is { RLCk }, the size of the RLC set is K, and K belongs to [1, K ], calculating a correlation threshold RTH:
RTH＝(∑(RCLk)/len(CAT))×exp(len(CAT)/NUM(RCLk))；
in the formula, RTH is a correlation threshold value, Σ (RCLk) is a sum of correlation coefficients of all physical property data in a target correlation coefficient set, len (CAT) is a size of an acquired physical property data type CAT, num (RCLk) is a number of physical property data types to which the physical property data RCLk belongs in a target physical property data set TRF, a data type refers to a source of the physical property data, and physical property data of the same data type indicates that the physical property data come from the same data source.
5. The industrial energy saving method for the multi-dimensional platform based on physical property data generation as claimed in claim 1, wherein the sub-step of obtaining the attention list of the physical property data according to the correlation threshold in step 4 is:
the kind of physical property data of the physical property data of which the correlation coefficient RLC is smaller than the correlation threshold RTH in the physical property data set WX is listed in an attention list, wherein the attention list refers to the physical property data needing attention when the industrial energy-saving measure is executed.
6. An industrial energy saving system based on a multi-dimensional platform generated by physical property data, the system comprising:
the physical property data acquisition module: the physical property data can be from various sensors of the industrial production line or parameters input by a user;
the physical property data storage module: the system comprises an archiving area and a temporary area, wherein the temporary area is a fixed-capacity quick accessible space;
the physical property data processing module: steps for executing the application of any of claims 1-5.
7. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 5.
8. An electronic device, comprising: a memory having a computer program stored thereon; a processor for executing the computer program in the memory to carry out the steps of the method of any one of claims 1 to 5.
CN202111592384.7A 2021-12-23 2021-12-23 Industrial energy-saving method and system of multi-dimensional platform based on physical property data generation Withdrawn CN114282805A (en)

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