CN117314202B - Product carbon efficiency monitoring and optimizing method and system based on industrial Internet - Google Patents
Product carbon efficiency monitoring and optimizing method and system based on industrial Internet Download PDFInfo
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Abstract
The invention belongs to the field of carbon footprint analysis, relates to a data analysis technology, and is used for solving the problems of complex operation and low carbon footprint determination efficiency of the existing carbon footprint determination method and system of an industrial factory, in particular to a product carbon efficiency monitoring and optimizing method and system based on an industrial Internet, which comprises a server, wherein the server is in communication connection with a period management module, a footprint analysis module, a footprint verification module, a dynamic optimizing module and a storage module; the period management module is used for carrying out period management analysis on carbon emission of the industrial factory: generating a management period, and acquiring a device carbon emission value and a product value in the management period; according to the invention, the carbon emission of the industrial factory can be periodically managed and analyzed, the device carbon emission value and the product value are subjected to numerical calculation to obtain the emission average value, the carbon discharge amount generated by each product produced by the industrial factory is fed back through the emission average value, and then the carbon footprint of the analysis period is rapidly calculated through the footprint analysis module.
Description
Technical Field
The invention belongs to the field of carbon footprint analysis, relates to a data analysis technology, and particularly relates to a product carbon efficiency monitoring and optimizing method and system based on an industrial Internet.
Background
The carbon footprint refers to a collection of greenhouse gas emissions caused by enterprises, activities, products or individuals through transportation, food production and consumption, various production processes and the like, describes the influence of energy consciousness and behavior of a person on the nature, calls people to do from the self, and has the environmental protection concept that part of enterprises start to trample to reduce the carbon footprint.
The existing carbon footprint determination method and system for the industrial factory generally acquire the carbon displacement of each device involved in the whole production process of the product, and then perform statistical analysis on the carbon displacement of all devices to obtain a carbon footprint; however, the method needs to collect carbon emission data of all equipment in an industrial factory, is complex in operation and low in carbon footprint determination efficiency.
Aiming at the technical problems, the application provides a solution.
Disclosure of Invention
The invention aims to provide a product carbon efficiency monitoring and optimizing method and system based on an industrial Internet, which are used for solving the problems of complex operation and low carbon footprint determining efficiency of the existing carbon footprint determining method and system of an industrial factory;
the technical problems to be solved by the invention are as follows: how to provide a simple and efficient carbon footprint determination method and system based on industrial Internet.
The aim of the invention can be achieved by the following technical scheme:
the product carbon efficiency monitoring and optimizing system based on the industrial Internet comprises a server, wherein the server is in communication connection with a period management module, a footprint analysis module, a footprint verification module, a dynamic optimizing module and a storage module;
the period management module is used for carrying out period management analysis on carbon emission of the industrial factory: generating a management period, acquiring a device carbon emission value and a product value in the management period, wherein the device carbon emission value is the sum of the total carbon emission values of raw material processing equipment, product transportation equipment and storage equipment in an industrial plant area in the management period, the product value is the product quantity value of the finished processing of the industrial plant area in the management period, and the ratio of the device carbon emission value to the product value is marked as the average value of the products; the method comprises the steps that the average value of products is sent to a server, and the server sends the average value of the products to a footprint analysis module after receiving the average value of the products;
the footprint analysis module is used for analyzing the carbon footprint of the industrial factory: generating an analysis period with the same duration as the management period at the end time of the management period, acquiring the product quantity value of the industrial factory where the processing is completed in the analysis period, marking the product of the product quantity value and the average value as a footprint value of the analysis period, transmitting the footprint value to a server at the end time of the analysis period, and transmitting the footprint value to a mobile phone terminal of a manager after the server receives the footprint value;
the footprint verification module is used for verifying and analyzing the carbon footprint of the industrial factory;
the dynamic optimization module is used for carrying out dynamic optimization analysis on the carbon emission of the industrial factory.
The storage module is used for storing data in the period management module, the footprint analysis module, the footprint verification module and the dynamic optimization module.
As a preferred embodiment of the invention, the specific process of verifying and analyzing the carbon footprint of the industrial factory area by the footprint verification module comprises the following steps: when the execution number of the analysis periods reaches L1, randomly selecting L2 analysis periods from the L1 analysis periods, marking the analysis periods as verification periods, obtaining equipment carbon emission values and output values of the verification periods, marking the ratio of the equipment carbon emission values to the output values as verification values, marking the absolute values of the difference values of the verification values and the emission values as deviation values of the verification periods, summing the deviation values of all the verification periods, taking an average value to obtain a deviation coefficient, forming a deviation set by the deviation values of all the verification periods, and performing variance calculation on the deviation set to obtain a deviation representation value; and judging whether the accuracy of the carbon footprint analysis result of the verification period meets the requirement or not through the deviation coefficient and the deviation representation value.
As a preferred embodiment of the invention, the specific process for judging whether the accuracy of the carbon footprint analysis result of the verification period meets the requirement comprises the following steps: the deviation threshold value and the deviation expression threshold value are acquired through the storage module, and the deviation coefficient and the deviation expression value are compared with the deviation threshold value and the deviation expression threshold value respectively: if the deviation coefficient is smaller than the deviation threshold value and the deviation expression value is smaller than the deviation expression threshold value, judging that the accuracy of the carbon footprint analysis result of the verification period meets the requirement; otherwise, judging that the accuracy of the carbon footprint analysis result in the verification period does not meet the requirement, generating a dynamic analysis signal and sending the dynamic analysis signal to a server, and sending the dynamic analysis signal to a dynamic optimization module after the server receives the dynamic analysis signal.
As a preferred embodiment of the present invention, the dynamic optimization module is configured to perform dynamic optimization analysis on carbon emissions of an industrial factory: establishing a rectangular coordinate system by taking the running time of the management period as an X axis and the product value as a Y axis, drawing a management curve in the rectangular coordinate system by taking the product quantity value of the finished processing in the management period, drawing a verification curve in the rectangular coordinate system by taking the product quantity value of the finished processing in the verification period, marking the intersection point quantity of the management curve and the verification curve as an intersection value JC, marking the sum value of the area values of all the closed graphs formed by the management curve and the verification curve as a deviation value PL, and carrying out numerical calculation on the intersection value JC and the deviation value PL to obtain a progress coefficient JD of the verification period; and obtaining a progress threshold value JDmin through a storage module, comparing the progress coefficient JD of the verification period with the progress threshold value JDmin, and judging whether the product processing progress of the verification period is consistent with that of the management period or not according to a comparison result.
As a preferred embodiment of the present invention, the specific process of comparing the progress factor JD of the verification period with the progress threshold JDmin includes: if the progress coefficient JD is larger than or equal to the progress threshold Jdmin, judging that the product processing progress of the verification period is inconsistent with the product processing progress of the management period, and marking the corresponding verification period as a progress deviation period; if the progress coefficient JD is smaller than the progress threshold Jdmin, judging that the product processing progress of the verification period is consistent with the product processing progress of the management period, and marking the corresponding verification period as a progress coincidence period; marking the number of progress coincidence periods as a coincidence value, acquiring a coincidence threshold value through a storage module, and comparing the coincidence value with the coincidence threshold value: if the coincidence value is smaller than the coincidence threshold value, generating a maintenance signal and sending the maintenance signal to a server, and after receiving the maintenance signal, the server sends the maintenance signal to a mobile phone terminal of a manager; and if the coincidence value is greater than or equal to the coincidence threshold value, carrying out environmental impact analysis on the verification period.
As a preferred embodiment of the present invention, the specific process of performing environmental impact analysis on the verification period includes: the temperature display data WX and the wet display data SX of the verification period are obtained, and the process for obtaining the temperature display data WX comprises the following steps: acquiring an air temperature value and a temperature standard range in an industrial factory, marking an average value of a maximum boundary value and a minimum boundary value of the temperature standard range as a temperature standard value, marking an absolute value of a difference value between the air temperature value and the temperature standard value as a temperature display value, and marking a maximum value of the temperature display value in a verification period as temperature display data WX; the acquisition process of the wet display data SX comprises the following steps: acquiring an air humidity value and a humidity standard range in an industrial factory, marking an average value of a maximum boundary value and a minimum boundary value of the humidity standard range as a humidity standard value, marking an absolute value of a difference value between the air humidity value and the humidity standard value as a humidity display value, and marking a maximum value of the humidity display value in a verification period as humidity display data SX; obtaining an environmental coefficient HJ of a verification period by carrying out numerical calculation on the temperature display data WX and the humidity display data SX; the maximum value and the minimum value of the environment coefficient HJ of all the verification periods form an environment set, the environment set is divided into a plurality of environment intervals, and the verification values of all the verification periods of the environment coefficients in the environment intervals are summed and averaged to obtain an optimized value of the environment interval; the optimization values of all the environment intervals form optimization parameters, the optimization parameters are sent to a server, the server receives the optimization parameters and then sends the optimization parameters to a footprint analysis module, environmental coefficient HJ calculation is carried out when carbon footprint analysis is carried out in the next analysis period, the optimization values of the environment coefficient HJ of the analysis period corresponding to the environment intervals are obtained, and numerical replacement is carried out on the row average value of the optimization values.
A product carbon efficiency monitoring and optimizing method based on industrial Internet comprises the following steps:
step one: and (3) carrying out periodical management analysis on carbon emission of the industrial factory: generating a management period, acquiring equipment carbon emission values and product values in the management period, and marking the ratio of the equipment carbon emission values to the product values as an average value of the products;
step two: analyzing the carbon footprint of the industrial plant area: generating an analysis period with the same duration as the management period at the end time of the management period, acquiring the product quantity value of the industrial factory which is processed in the analysis period, marking the product quantity value as a yield value, and marking the product of the yield value and the average value as a footprint value of the analysis period;
step three: verifying and analyzing the carbon footprint of the industrial factory: when the execution number of the analysis periods reaches L1, randomly selecting L2 analysis periods from the L1 analysis periods, marking the analysis periods as verification periods, acquiring deviation coefficients and deviation expression values of the verification periods, and judging whether the accuracy of carbon footprint analysis results of the verification periods meets the requirements or not through the deviation coefficients and the deviation expression values;
step four: carrying out dynamic optimization analysis on carbon emission of an industrial factory: and establishing a rectangular coordinate system by taking the running time of the management period as an X axis and the product value as a Y axis, drawing a management curve and a verification curve in the rectangular coordinate system, acquiring a coincidence value through the distribution state of the management curve and the verification curve in the rectangular coordinate system, and analyzing the environmental impact when the coincidence value is not smaller than a coincidence threshold value.
The invention has the following beneficial effects:
1. the periodic management analysis can be carried out on the carbon emission of the industrial factory through the period management module, the numerical calculation is carried out on the equipment carbon emission value and the product value to obtain an emission average value, the feedback is carried out on the carbon discharge quantity generated by each product produced by the industrial factory through the emission average value, then the rapid calculation is carried out on the carbon footprint of the analysis period through the footprint analysis module, and the carbon footprint determination efficiency is improved;
2. the carbon footprint verification module can carry out verification analysis on the carbon footprint of the industrial factory, the deviation coefficient and the deviation representation value are obtained by carrying out numerical calculation on the deviation value of the randomly extracted verification period, the accuracy of the carbon footprint analysis result of the verification period is fed back through the deviation coefficient and the deviation representation value, and a corresponding analysis signal is generated and sent to the server when the accuracy does not meet the requirement;
3. the dynamic optimization module can dynamically optimize and analyze the carbon emission of an industrial factory, the progress coefficient is obtained by carrying out distribution analysis on a management curve and a verification curve drawn in a rectangular coordinate system, the consistency of the production progress of a product in the verification period and the management period is monitored by the progress coefficient, the environmental impact analysis is carried out and the optimization parameters are obtained when the accuracy of the carbon footprint analysis result is unqualified and is irrelevant to the production progress of the product, the average value of the row is optimized by adopting the optimization parameters when the carbon footprint analysis is carried out in the subsequent analysis period, and the accuracy of the carbon footprint analysis result is improved.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a system block diagram of a first embodiment of the present invention;
fig. 2 is a flowchart of a method according to a second embodiment of the invention.
Detailed Description
The technical solutions of the present invention will be clearly and completely described in connection with the embodiments, and it is obvious that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Embodiment one:
as shown in FIG. 1, the product carbon efficiency monitoring and optimizing system based on the industrial Internet comprises a server, wherein the server is in communication connection with a period management module, a footprint analysis module, a footprint verification module, a dynamic optimizing module and a storage module.
The period management module is used for carrying out periodic management analysis on the carbon emission of the industrial factory: generating a management period, acquiring a device carbon emission value and a product value in the management period, wherein the device carbon emission value is the sum of the total carbon emission values of raw material processing equipment, product transportation equipment and storage equipment in an industrial plant area in the management period, the product value is the product quantity value of the finished processing of the industrial plant area in the management period, and the ratio of the device carbon emission value to the product value is marked as the average value of the products; and sending the average value of the products to a server, and sending the average value of the products to a footprint analysis module after the server receives the average value of the products.
The footprint analysis module is used for analyzing the carbon footprint of the industrial factory: generating an analysis period with the same duration as the management period at the end time of the management period, acquiring the product quantity value of the industrial factory where the processing is completed in the analysis period, marking the product of the product quantity value and the average value as a footprint value of the analysis period, transmitting the footprint value to a server at the end time of the analysis period, and transmitting the footprint value to a mobile phone terminal of a manager after the server receives the footprint value; and (3) carrying out periodical management analysis on the carbon emission of the industrial factory, carrying out numerical calculation on the equipment carbon emission value and the product value to obtain an emission average value, feeding back the carbon discharge quantity generated by each product produced by the industrial factory through the emission average value, and then carrying out rapid calculation on the carbon footprint of the analysis period through a footprint analysis module, thereby improving the carbon footprint determination efficiency.
The footprint verification module is used for verifying and analyzing the carbon footprint of the industrial factory: when the execution number of the analysis periods reaches L1, randomly selecting L2 analysis periods from the L1 analysis periods, marking the analysis periods as verification periods, wherein L1 and L2 are numerical constants, and specific numerical values of L1 and L2 are set by a manager; the method comprises the steps of obtaining equipment carbon rank values and output values of verification periods, marking the ratio of the equipment carbon rank values to the output values as verification values, marking the absolute value of the difference value between the verification values and the rank average values as the deviation value of the verification periods, summing the deviation values of all the verification periods, taking an average value to obtain a deviation coefficient, forming a deviation set by the deviation values of all the verification periods, and performing variance calculation on the deviation set to obtain a deviation representation value; the deviation threshold value and the deviation expression threshold value are acquired through the storage module, and the deviation coefficient and the deviation expression value are compared with the deviation threshold value and the deviation expression threshold value respectively: if the deviation coefficient is smaller than the deviation threshold value and the deviation expression value is smaller than the deviation expression threshold value, judging that the accuracy of the carbon footprint analysis result of the verification period meets the requirement; otherwise, judging that the accuracy of the carbon footprint analysis result in the verification period does not meet the requirement, generating a dynamic analysis signal and sending the dynamic analysis signal to a server, and sending the dynamic analysis signal to a dynamic optimization module after the server receives the dynamic analysis signal; and carrying out verification analysis on the carbon footprint of the industrial factory, carrying out numerical calculation on the deviation value of the verification period which is randomly extracted to obtain a deviation coefficient and a deviation expression value, feeding back the accuracy of the analysis result of the carbon footprint of the verification period through the deviation coefficient and the deviation expression value, and generating a corresponding analysis signal to be sent to a server when the accuracy does not meet the requirement.
The dynamic optimization module is used for carrying out dynamic optimization analysis on the carbon emission of the industrial factory: establishing a rectangular coordinate system by taking the running time of a management period as an X axis and a product value as a Y axis, drawing a management curve in the rectangular coordinate system by taking the product quantity value of finishing processing in the management period, drawing a verification curve in the rectangular coordinate system by taking the product quantity value of finishing processing in the verification period, marking the intersection point quantity of the management curve and the verification curve as a crossing value JC, marking the sum value of the area values of all closed graphs formed by the management curve and the verification curve as a deviation value PL, and obtaining a progress coefficient JD of the verification period by a formula JD=α1xJC+α2xPL, wherein α1 and α2 are proportionality coefficients, and α1 > α2 > 1; the progress threshold JDmin is obtained through the storage module, and the progress coefficient JD of the verification period is compared with the progress threshold JDmin: if the progress coefficient JD is larger than or equal to the progress threshold Jdmin, judging that the product processing progress of the verification period is inconsistent with the product processing progress of the management period, and marking the corresponding verification period as a progress deviation period; if the progress coefficient JD is smaller than the progress threshold Jdmin, judging that the product processing progress of the verification period is consistent with the product processing progress of the management period, and marking the corresponding verification period as a progress coincidence period; marking the number of progress coincidence periods as a coincidence value, acquiring a coincidence threshold value through a storage module, and comparing the coincidence value with the coincidence threshold value: if the coincidence value is smaller than the coincidence threshold value, generating a maintenance signal and sending the maintenance signal to a server, and after receiving the maintenance signal, the server sends the maintenance signal to a mobile phone terminal of a manager; if the coincidence value is greater than or equal to the coincidence threshold value, carrying out environmental impact analysis on the verification period: the temperature display data WX and the wet display data SX of the verification period are obtained, and the process for obtaining the temperature display data WX comprises the following steps: acquiring an air temperature value and a temperature standard range in an industrial factory, marking an average value of a maximum boundary value and a minimum boundary value of the temperature standard range as a temperature standard value, marking an absolute value of a difference value between the air temperature value and the temperature standard value as a temperature display value, and marking a maximum value of the temperature display value in a verification period as temperature display data WX; the acquisition process of the wet display data SX comprises the following steps: acquiring an air humidity value and a humidity standard range in an industrial factory, marking an average value of a maximum boundary value and a minimum boundary value of the humidity standard range as a humidity standard value, marking an absolute value of a difference value between the air humidity value and the humidity standard value as a humidity display value, and marking a maximum value of the humidity display value in a verification period as humidity display data SX; obtaining an environmental coefficient HJ of a verification period through a formula HJ=β1×WX+β2×SX, wherein β1 and β2 are both proportional coefficients, and β1 > β2 > 1; the maximum value and the minimum value of the environment coefficient HJ of all the verification periods form an environment set, the environment set is divided into a plurality of environment intervals, and the verification values of all the verification periods of the environment coefficients in the environment intervals are summed and averaged to obtain an optimized value of the environment interval; the optimization values of all the environment intervals form optimization parameters, the optimization parameters are sent to a server, the server receives the optimization parameters and then sends the optimization parameters to a footprint analysis module, environmental coefficient HJ calculation is carried out when carbon footprint analysis is carried out in the next analysis period, the optimization values of the environment coefficient HJ of the analysis period corresponding to the environment intervals are obtained, and numerical replacement is carried out on the row average value of the optimization values; the method comprises the steps of carrying out dynamic optimization analysis on carbon emission of an industrial factory, carrying out distribution analysis on a management curve and a verification curve drawn in a rectangular coordinate system to obtain a progress coefficient, monitoring the consistency of the production progress of products in the verification period and the management period through the progress coefficient, carrying out environmental impact analysis and obtaining optimization parameters when the accuracy of a carbon footprint analysis result is unqualified and is irrelevant to the production progress of the products, and optimizing a row average value by adopting the optimization parameters when the carbon footprint analysis is carried out in a subsequent analysis period, so that the accuracy of the carbon footprint analysis result is improved.
The storage module is used for storing the data in the period management module, the footprint analysis module, the footprint verification module and the dynamic optimization module.
Embodiment two:
as shown in fig. 2, a product carbon efficiency monitoring and optimizing method based on industrial internet comprises the following steps:
step one: and (3) carrying out periodical management analysis on carbon emission of the industrial factory: generating a management period, acquiring equipment carbon emission values and product values in the management period, and marking the ratio of the equipment carbon emission values to the product values as an average value of the products;
step two: analyzing the carbon footprint of the industrial plant area: generating an analysis period with the same duration as the management period at the end time of the management period, acquiring the product quantity value of the industrial factory which is processed in the analysis period, marking the product quantity value as a yield value, and marking the product of the yield value and the average value as a footprint value of the analysis period;
step three: verifying and analyzing the carbon footprint of the industrial factory: when the execution number of the analysis periods reaches L1, randomly selecting L2 analysis periods from the L1 analysis periods, marking the analysis periods as verification periods, acquiring deviation coefficients and deviation expression values of the verification periods, and judging whether the accuracy of carbon footprint analysis results of the verification periods meets the requirements or not through the deviation coefficients and the deviation expression values;
step four: carrying out dynamic optimization analysis on carbon emission of an industrial factory: and establishing a rectangular coordinate system by taking the running time of the management period as an X axis and the product value as a Y axis, drawing a management curve and a verification curve in the rectangular coordinate system, acquiring a coincidence value through the distribution state of the management curve and the verification curve in the rectangular coordinate system, and analyzing the environmental impact when the coincidence value is not smaller than a coincidence threshold value.
The method and the system for monitoring and optimizing the carbon efficiency of the product based on the industrial Internet are characterized in that a management period is generated during operation, equipment carbon emission values and product values in the management period are obtained, and the ratio of the equipment carbon emission values to the product values is marked as an average product emission value; generating an analysis period with the same duration as the management period at the end time of the management period, acquiring the product quantity value of the industrial factory which is processed in the analysis period, marking the product quantity value as a yield value, and marking the product of the yield value and the average value as a footprint value of the analysis period; when the execution number of the analysis periods reaches L1, randomly selecting L2 analysis periods from the L1 analysis periods, marking the analysis periods as verification periods, acquiring deviation coefficients and deviation expression values of the verification periods, and judging whether the accuracy of carbon footprint analysis results of the verification periods meets the requirements or not through the deviation coefficients and the deviation expression values; and establishing a rectangular coordinate system by taking the running time of the management period as an X axis and the product value as a Y axis, drawing a management curve and a verification curve in the rectangular coordinate system, acquiring a coincidence value through the distribution state of the management curve and the verification curve in the rectangular coordinate system, and analyzing the environmental impact when the coincidence value is not smaller than a coincidence threshold value.
The foregoing is merely illustrative of the structures of this invention and various modifications, additions and substitutions for those skilled in the art can be made to the described embodiments without departing from the scope of the invention or from the scope of the invention as defined in the accompanying claims.
The formulas are all formulas obtained by collecting a large amount of data for software simulation and selecting a formula close to a true value, and coefficients in the formulas are set by a person skilled in the art according to actual conditions; such as: the formula jd=α1×jc+α2×pl; collecting a plurality of groups of sample data by a person skilled in the art and setting a corresponding progress coefficient for each group of sample data; substituting the set progress coefficient and the acquired sample data into a formula, forming a ternary one-time equation set by any three formulas, screening the calculated coefficient, and taking an average value to obtain values of alpha 1 and alpha 2 which are 3.68 and 2.15 respectively;
the size of the coefficient is a specific numerical value obtained by quantizing each parameter, so that the subsequent comparison is convenient, and the size of the coefficient depends on the number of sample data and the corresponding progress coefficient is preliminarily set for each group of sample data by a person skilled in the art; as long as the proportional relation between the parameter and the quantized value is not affected, for example, the progress coefficient is proportional to the value of the crossing value.
In the description of the present specification, the descriptions of the terms "one embodiment," "example," "specific example," and 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 present invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The preferred embodiments of the invention disclosed above are intended only to assist in the explanation of the invention. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise form disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best understand and utilize the invention. The invention is limited only by the claims and the full scope and equivalents thereof.
Claims (1)
1. The product carbon efficiency monitoring and optimizing system based on the industrial Internet is characterized by comprising a server, wherein the server is in communication connection with a period management module, a footprint analysis module, a footprint verification module, a dynamic optimizing module and a storage module;
the period management module is used for carrying out period management analysis on carbon emission of the industrial factory: generating a management period, acquiring a device carbon emission value and a product value in the management period, wherein the device carbon emission value is the sum of the total carbon emission values of raw material processing equipment, product transportation equipment and storage equipment in an industrial plant area in the management period, the product value is the product quantity value of the finished processing of the industrial plant area in the management period, and the ratio of the device carbon emission value to the product value is marked as the average value of the products; the method comprises the steps that the average value of products is sent to a server, and the server sends the average value of the products to a footprint analysis module after receiving the average value of the products;
the footprint analysis module is used for analyzing the carbon footprint of the industrial factory: generating an analysis period with the same duration as the management period at the end time of the management period, acquiring the product quantity value of the industrial factory where the processing is completed in the analysis period, marking the product of the product quantity value and the average value as a footprint value of the analysis period, transmitting the footprint value to a server at the end time of the analysis period, and transmitting the footprint value to a mobile phone terminal of a manager after the server receives the footprint value;
the footprint verification module is used for verifying and analyzing the carbon footprint of the industrial factory;
the dynamic optimization module is used for carrying out dynamic optimization analysis on the carbon emission of the industrial factory;
the storage module is used for storing data in the period management module, the footprint analysis module, the footprint verification module and the dynamic optimization module;
the specific process of verifying and analyzing the carbon footprint of the industrial factory by the footprint verification module comprises the following steps: when the execution number of the analysis periods reaches L1, randomly selecting L2 analysis periods from the L1 analysis periods, marking the analysis periods as verification periods, obtaining equipment carbon emission values and output values of the verification periods, marking the ratio of the equipment carbon emission values to the output values as verification values, marking the absolute values of the difference values of the verification values and the emission values as deviation values of the verification periods, summing the deviation values of all the verification periods, taking an average value to obtain a deviation coefficient, forming a deviation set by the deviation values of all the verification periods, and performing variance calculation on the deviation set to obtain a deviation representation value; judging whether the accuracy of the carbon footprint analysis result of the verification period meets the requirement or not through the deviation coefficient and the deviation representation value;
the specific process for judging whether the accuracy of the carbon footprint analysis result of the verification period meets the requirement comprises the following steps: the deviation threshold value and the deviation expression threshold value are acquired through the storage module, and the deviation coefficient and the deviation expression value are compared with the deviation threshold value and the deviation expression threshold value respectively: if the deviation coefficient is smaller than the deviation threshold value and the deviation expression value is smaller than the deviation expression threshold value, judging that the accuracy of the carbon footprint analysis result of the verification period meets the requirement; otherwise, judging that the accuracy of the carbon footprint analysis result in the verification period does not meet the requirement, generating a dynamic analysis signal and sending the dynamic analysis signal to a server, and sending the dynamic analysis signal to a dynamic optimization module after the server receives the dynamic analysis signal;
the dynamic optimization module is used for carrying out dynamic optimization analysis on the carbon emission of the industrial factory: establishing a rectangular coordinate system by taking the running time of the management period as an X axis and the product value as a Y axis, drawing a management curve in the rectangular coordinate system by taking the product quantity value of the finished processing in the management period, drawing a verification curve in the rectangular coordinate system by taking the product quantity value of the finished processing in the verification period, marking the intersection point quantity of the management curve and the verification curve as an intersection value JC, marking the sum value of the area values of all the closed graphs formed by the management curve and the verification curve as a deviation value PL, and carrying out numerical calculation on the intersection value JC and the deviation value PL to obtain a progress coefficient JD of the verification period; acquiring a progress threshold value JDmin through a storage module, comparing the progress coefficient JD of the verification period with the progress threshold value JDmin, and judging whether the product processing progress of the verification period is consistent with that of the management period or not according to a comparison result;
the specific process of comparing the progress coefficient JD of the verification period with the progress threshold Jdmin comprises the following steps: if the progress coefficient JD is larger than or equal to the progress threshold Jdmin, judging that the product processing progress of the verification period is inconsistent with the product processing progress of the management period, and marking the corresponding verification period as a progress deviation period; if the progress coefficient JD is smaller than the progress threshold Jdmin, judging that the product processing progress of the verification period is consistent with the product processing progress of the management period, and marking the corresponding verification period as a progress coincidence period; marking the number of progress coincidence periods as a coincidence value, acquiring a coincidence threshold value through a storage module, and comparing the coincidence value with the coincidence threshold value: if the coincidence value is smaller than the coincidence threshold value, generating a maintenance signal and sending the maintenance signal to a server, and after receiving the maintenance signal, the server sends the maintenance signal to a mobile phone terminal of a manager; if the coincidence value is greater than or equal to the coincidence threshold value, carrying out environmental impact analysis on the verification period;
the specific process of environmental impact analysis for the verification period includes: the temperature display data WX and the wet display data SX of the verification period are obtained, and the process for obtaining the temperature display data WX comprises the following steps: acquiring an air temperature value and a temperature standard range in an industrial factory, marking an average value of a maximum boundary value and a minimum boundary value of the temperature standard range as a temperature standard value, marking an absolute value of a difference value between the air temperature value and the temperature standard value as a temperature display value, and marking a maximum value of the temperature display value in a verification period as temperature display data WX; the acquisition process of the wet display data SX comprises the following steps: acquiring an air humidity value and a humidity standard range in an industrial factory, marking an average value of a maximum boundary value and a minimum boundary value of the humidity standard range as a humidity standard value, marking an absolute value of a difference value between the air humidity value and the humidity standard value as a humidity display value, and marking a maximum value of the humidity display value in a verification period as humidity display data SX; obtaining an environmental coefficient HJ of a verification period by carrying out numerical calculation on the temperature display data WX and the humidity display data SX; the maximum value and the minimum value of the environment coefficient HJ of all the verification periods form an environment set, the environment set is divided into a plurality of environment intervals, and the verification values of all the verification periods of the environment coefficients in the environment intervals are summed and averaged to obtain an optimized value of the environment interval; the optimization values of all the environment intervals form optimization parameters, the optimization parameters are sent to a server, the server receives the optimization parameters and then sends the optimization parameters to a footprint analysis module, environmental coefficient HJ calculation is carried out when carbon footprint analysis is carried out in the next analysis period, the optimization values of the environment coefficient HJ of the analysis period corresponding to the environment intervals are obtained, and numerical replacement is carried out on the row average value of the optimization values.
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