Road engineering green construction carbon emission evaluation system and method

Abstract

The invention discloses a road engineering green construction carbon emission evaluation system and method, and relates to the technical field of carbon emission evaluation. Comprising an equipment data acquisition module, an equipment carbon emission factor acquisition module, a tail gas carbon emission monitoring module, an equipment carbon emission calculation module, an equipment working condition evaluation module, an equipment construction duration analysis module, an equipment carbon emission prediction module and an equipment power utilization carbon emission calculation module. According to the road engineering green construction carbon emission evaluation system and method, the equipment data acquisition module, the equipment carbon emission factor acquisition module, the tail gas carbon emission monitoring module, the equipment carbon emission calculation module, the equipment working condition evaluation module and the like are arranged, so that the working condition of construction equipment can be evaluated; the carbon emission errors of the construction equipment under various working conditions are calculated, maintenance personnel are reminded to carry out overhaul and maintenance in time, the carbon emission of the construction equipment working under different working conditions in a project can be calculated, and the prediction precision of the carbon emission is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of carbon emission assessment, and in particular to a carbon emission assessment system and method for green construction of road engineering. Background Art

[0002] Carbon emissions refer to the greenhouse gas emissions generated during the production, transportation, use and recycling of a product, generally referring to the emissions of carbon dioxide. Dynamic carbon emissions refer to the cumulative greenhouse gas emissions per unit of goods. Different batches of the same product will have different dynamic carbon emissions. In order to reduce greenhouse gas emissions, it is necessary to monitor carbon emissions.

[0003] The prior art with the publication number CN117933544A discloses a method and system for analyzing the carbon intensity of a road construction process, a storage medium and a terminal, including the following steps: S1. Preprocessing the carbon emission intensity factors involved in the existing itemized summary bill of quantities to obtain a carbon intensity and factor sample set; S2. Constructing a carbon intensity impact analysis model for the urban road construction stage based on the subdivided items of the historical itemized summary bill of quantities of existing urban roads during the construction stage; S3. Training the carbon intensity impact analysis model for the urban road construction stage to make the carbon intensity impact analysis model for the urban road construction stage approach the carbon emission intensity standard value of the road and construction industry; S4. Using the trained carbon intensity impact analysis model for the urban road construction stage to analyze the carbon emission intensity impact of the road construction project that needs to be analyzed. It can solve the carbon intensity impact analysis and evaluation problems of different types of processes and design schemes of road construction projects.

[0004] However, in the process of road construction, the size of the carbon emission factor is not only related to the type of construction and the equipment used, but also to the load size and working hours of the equipment. The different loads and working hours of the equipment use different combustion efficiencies of the fuel, which leads to different carbon emission factors of the equipment, thus affecting the accuracy of carbon emission assessment. Summary of the invention

[0005] The purpose of the present invention is to provide a road engineering green construction carbon emission assessment system and method to solve the above-mentioned deficiencies in the prior art.

[0006] In order to achieve the above-mentioned purpose, the present invention provides the following technical solutions: a road engineering green construction carbon emission assessment system, including an equipment data acquisition module, an equipment carbon emission factor acquisition module, an exhaust gas carbon emission monitoring module, an equipment carbon emission calculation module, an equipment working condition assessment module, an equipment construction time analysis module, an equipment carbon emission prediction module, and an equipment electricity carbon emission calculation module;

[0007] The equipment data acquisition module is arranged on the construction equipment and is used to acquire the equipment working data of the construction equipment. The equipment working data includes the load size, continuous working time, fuel consumption and the type and model of the fuel used by the construction equipment.

[0008] The equipment carbon emission factor acquisition module is used to acquire the carbon emission data per unit of fuel of the construction equipment to obtain the carbon emission factor corresponding to each construction equipment, wherein the carbon emission data per unit of fuel (e.g., per liter or per gallon) can usually be found in the technical specifications of the equipment or the documents provided by the manufacturer, and these data may be given in the form of unit mass (e.g., g / l or g / gallon);

[0009] The tail gas carbon emission monitoring module is used to monitor the tail gas of the construction equipment, monitor the carbon content in the tail gas, and obtain the carbon emission of the equipment;

[0010] The equipment carbon emission calculation module is used to calculate the carbon emission of the construction equipment under perfect equipment working conditions based on the equipment working data, equipment carbon emission and carbon emission factor corresponding to the construction equipment;

[0011] The equipment working condition evaluation module is used to input the equipment working data and carbon emission factors into the corresponding equipment perfect working condition carbon emission calculation module to obtain the corresponding predicted equipment carbon emission, and judge the working condition of the construction equipment based on the carbon emission error between the predicted equipment carbon emission and the equipment carbon emission. The larger the carbon emission error, the worse the working condition of the construction equipment.

[0012] The equipment working condition assessment module is also used to remind when the carbon emission error exceeds the set carbon emission error reminder threshold, wherein the reminder can be implemented by issuing a notification, information, alarm, etc., to remind maintenance personnel to perform maintenance and repair on the construction equipment in a timely manner;

[0013] The equipment construction time analysis module obtains the engineering quantity of each type of engineering, the corresponding number of construction equipment and the construction speed, and obtains the average construction time of each construction equipment;

[0014] The equipment carbon emission prediction module is used to train a machine learning model based on the load size, continuous working time, construction time and carbon emission error corresponding to the construction time of the construction equipment to obtain a working condition decline prediction model, which is used to output a predicted carbon emission error based on the input load size, continuous working time and construction time;

[0015] The equipment carbon emission prediction module is also used to perform regression analysis based on the predicted carbon emission error, load size, continuous working time and the fuel consumption corresponding to each continuous working time to obtain a fuel consumption prediction model, which is used to output the predicted fuel consumption based on the input predicted carbon emission error, load size, and continuous working time;

[0016] The equipment carbon emission prediction module is also used to obtain the predicted fuel consumption corresponding to each continuous working time based on the equipment working condition, the required load size, and the continuous working time, and then combine the predicted fuel consumption to predict the carbon emission of the average construction time corresponding to the construction equipment operation;

[0017] The equipment electricity carbon emission calculation module is used to obtain the electricity consumption of the construction equipment and the electricity carbon emission factor, and obtain the electricity carbon emission based on the electricity consumption and the electricity carbon emission factor.

[0018] Furthermore, the device data acquisition module acquires the continuous working time, including the following steps:

[0019] The continuous working time is determined by the start-up time of the construction equipment, and the rest time threshold can be set;

[0020] Determine whether the duration between the current start time and the last shutdown time of the construction equipment exceeds the rest time threshold;

[0021] If yes, the continuous working time will be recalculated, otherwise the continuous working time will continue to be counted from the last shutdown time.

[0022] Furthermore, the equipment carbon emissions calculation module is used to calculate the carbon emissions of the construction equipment under perfect equipment working conditions based on the equipment working data, equipment carbon emissions and carbon emission factors corresponding to the construction equipment, including the following steps:

[0023] Overhaul and maintain construction equipment to obtain construction equipment in perfect working condition;

[0024] Using the construction equipment to perform construction work;

[0025] Obtaining equipment working data and equipment carbon emissions during construction operation of the construction equipment;

[0026] Obtaining a carbon emission factor of the construction equipment;

[0027] Based on the equipment working data, carbon emission factor, and equipment carbon emissions, a regression analysis is performed to obtain a carbon emission calculation model for equipment under perfect working conditions, which is used to output predicted equipment carbon emissions based on the input equipment working data and carbon emission factor.

[0028] Furthermore, the equipment working condition evaluation module judges the working condition of the construction equipment based on the carbon emission error between the predicted equipment carbon emission and the equipment carbon emission, and the larger the carbon emission error, the worse the working condition of the construction equipment, including the following steps:

[0029] Calculating the error between the predicted equipment carbon emissions and the equipment carbon emissions to obtain a carbon emissions error;

[0030] Set multiple equipment operating condition labels to correspond to different carbon emission error intervals. For example, in one embodiment, the equipment operating condition labels include perfect, general, poor, and abnormal, and the corresponding carbon emission error intervals are 0-2%, 2% (not included)-5%, 5% (not included)-10%, and more than 10% respectively;

[0031] The equipment operating condition label corresponding to the carbon emission error interval in which the carbon emission error is located is output to obtain the operating condition of the construction equipment.

[0032] Furthermore, the equipment operating condition assessment module is also used to train a deep learning model based on carbon emission errors, load size, continuous working time, and construction time to obtain an equipment operating condition prediction model, which is used to output predicted carbon emission errors and their corresponding equipment operating condition labels based on the input load size, continuous working time, and construction time, wherein load size, continuous working time, and construction time are used as inputs during training, and carbon emissions are used as outputs.

[0033] Furthermore, the equipment carbon emission prediction module is also used to perform regression analysis based on the predicted carbon emission error, load size, continuous working time and fuel consumption corresponding to each continuous working time to obtain a fuel consumption prediction model, which specifically includes the following steps:

[0034] Obtain equipment condition labels for construction equipment conditions based on predicted carbon emission errors;

[0035] The load size, continuous working time and the fuel consumption corresponding to each continuous working time are classified according to different equipment working condition labels to obtain multiple data sets;

[0036] Taking continuous working time as the independent variable and fuel consumption as the dependent variable, regression analysis was performed on each data set to obtain the fuel consumption prediction model corresponding to each data set. The model is used to output the predicted fuel consumption corresponding to the input continuous working time based on the input predicted carbon emission error, load size, and continuous working time.

[0037] Furthermore, the equipment construction time analysis module obtains the engineering quantity of various types of projects, the corresponding number of construction equipment and the construction speed, and obtains the average construction time of each construction equipment, including the following steps:

[0038] Use various types of construction equipment to carry out construction and test the construction speed of various types of construction equipment;

[0039] Obtain the engineering quantities of various projects and the corresponding number of construction equipment;

[0040] Based on the project volume of each type of project, the corresponding number of construction equipment and construction speed, the average construction time of each construction equipment is calculated.

[0041] Furthermore, the equipment carbon emission prediction module is also used to obtain the predicted fuel consumption corresponding to each continuous working time based on the equipment working condition, the required load size, and the continuous working time, and then combine the predicted fuel consumption to predict the carbon emissions of the average construction time corresponding to the construction equipment operation, including the following steps:

[0042] Obtaining an average construction time of the construction equipment, setting the number of construction times based on the average construction time, and obtaining an average continuous working time of each construction;

[0043] Based on the equipment working condition prediction model, the carbon emission error of each average continuous working time of the construction equipment and the equipment working condition are determined to obtain a fuel consumption prediction model corresponding to the equipment working condition;

[0044] Inputting the average continuous working time into a fuel consumption prediction model, and outputting a corresponding predicted fuel consumption;

[0045] Based on the carbon emission calculation model of perfect equipment working conditions, the carbon emission error of each average continuous working time, and the carbon emission factor of the construction equipment, the output predicted fuel consumption and its corresponding real-time judgment of the carbon emission error of the equipment working condition are used to obtain the carbon emissions of the average construction time corresponding to the construction equipment working.

[0046] A method for evaluating carbon emissions from green construction of a road project comprises the following steps:

[0047] Obtain equipment working data, carbon emission factors, and equipment carbon emissions of construction equipment;

[0048] Overhaul and maintain construction equipment to obtain construction equipment in perfect working condition;

[0049] Monitor the construction process of construction equipment with perfect working conditions, and calculate the carbon emissions corresponding to the working data of each piece of equipment with perfect working conditions;

[0050] Monitor the equipment working data and equipment carbon emissions of construction equipment in real time, and judge the working condition of construction equipment based on the error between the real-time monitored equipment carbon emissions and the carbon emissions of the corresponding construction equipment when the equipment is in perfect working condition under the same equipment working data;

[0051] Obtain the engineering quantity of each type of project, the corresponding number of construction equipment and construction speed, and obtain the average construction time of each construction equipment;

[0052] Based on the load size, continuous working hours, construction time and carbon emission error of construction equipment, the machine learning model is trained to obtain the working condition decline prediction model;

[0053] Based on the predicted carbon emission error, load size, continuous working time and the fuel consumption corresponding to each continuous working time, regression analysis is performed to obtain a fuel consumption prediction model;

[0054] Equipment working conditions, required load size, continuous working time, obtain the predicted fuel consumption corresponding to each continuous working time, and then combine the predicted fuel consumption to predict the carbon emissions of the average construction time corresponding to the construction equipment operation;

[0055] The electricity consumption of the construction equipment and the carbon emission factor of electricity consumption are obtained, and the carbon emissions of electricity consumption are obtained based on the electricity consumption and the carbon emission factor of electricity consumption.

[0056] 1. Compared with the prior art, the present invention provides a road engineering green construction carbon emission assessment system and method, which can evaluate the working condition of the construction equipment by setting an equipment data acquisition module, an equipment carbon emission factor acquisition module, an exhaust gas carbon emission monitoring module, an equipment carbon emission calculation module, and an equipment working condition assessment module, calculate the carbon emission error of the construction equipment under various working conditions, and remind maintenance personnel to perform inspection and maintenance when the equipment working condition is too poor.

[0057] 2. Compared with the prior art, the present invention provides a road engineering green construction carbon emission assessment system and method, which analyzes the construction time of each construction equipment in the project by setting up an equipment construction time analysis module and an equipment carbon emission prediction module, thereby calculating the change in equipment operating conditions of each construction equipment to complete the corresponding work in the project, which is convenient for calculating the carbon emissions of construction equipment working under different working conditions in the project, so that the carbon emissions of the construction can be predicted based on the project volume and equipment operating conditions, thereby improving the accuracy of carbon emission prediction. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0059] Figure 1 A schematic diagram of the overall structure provided by an embodiment of the present invention;

[0060] Figure 2A schematic diagram of the structure provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0061] In order to enable those skilled in the art to better understand the technical solution of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings.

[0062] In the description of the present invention, it should be understood that the terms "first" and "second" are only used for descriptive purposes, and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, "multiple" means two or more, unless otherwise clearly and specifically defined. In addition, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be directly connected, or indirectly connected through an intermediate medium, or it can be the internal communication of two components. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0063] Example embodiments will be described more fully below with reference to the accompanying drawings, but the example embodiments may be embodied in different forms and should not be construed as limited to the embodiments set forth herein. On the contrary, the purpose of providing these embodiments is to make the present disclosure thorough and complete and to enable those skilled in the art to fully understand the scope of the present disclosure.

[0064] In the absence of conflict, the various embodiments of the present disclosure and the various features therein may be combined with each other.

[0065] As used herein, the term "and / or" includes any and all combinations of one or more of the associated listed items.

[0066] The terms used herein are only used to describe specific embodiments and are not intended to limit the present disclosure. As used herein, the singular forms "a", "an" and "the" are also intended to include the plural forms, unless the context clearly indicates otherwise. It will also be understood that when the terms "comprising" and / or "made of" are used in this specification, the presence of the features, wholes, steps, operations, elements and / or components is specified, but the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or groups thereof is not excluded.

[0067] See also Figure 1-Figure 2, a road engineering green construction carbon emission assessment system, including an equipment data acquisition module, an equipment carbon emission factor acquisition module, an exhaust carbon emission monitoring module, an equipment carbon emission calculation module, an equipment working condition assessment module, an equipment construction time analysis module, an equipment carbon emission prediction module, and an equipment electricity carbon emission calculation module;

[0068] The equipment data acquisition module is set on the construction equipment to obtain the equipment working data of the construction equipment. The equipment working data includes the load size of the construction equipment, the continuous working time, the fuel consumption and the type and model of the fuel used; for example, the fuel can be diesel (such as No. 0 diesel), gasoline (such as No. 92 gasoline, No. 95 gasoline), etc.; among them, if the construction equipment itself is equipped with corresponding sensors to obtain the required data, the equipment data acquisition module directly obtains the data collected by the relevant sensors of the construction equipment; if the construction equipment is not equipped with sensors that can collect the required data, the corresponding sensors are set at the required positions to collect the required data to complete the acquisition of relevant data.

[0069] The equipment data acquisition module acquires the continuous working time, including the following steps:

[0070] A1. The continuous working time is determined by the start-up time of the construction equipment, and the rest time threshold can be set;

[0071] A2. Determine whether the duration between the current start time and the last shutdown time of the construction equipment exceeds the rest time threshold;

[0072] A3. If yes, recalculate the continuous working time. Otherwise, continue to count from the continuous working time when the machine was shut down last time.

[0073] The equipment carbon emission factor acquisition module is used to obtain the carbon emission data per unit of fuel of the construction equipment, and obtain the carbon emission factor corresponding to each construction equipment. The carbon emission data per unit of fuel (e.g., per liter or per gallon) can usually be found in the technical specifications of the equipment or the documents provided by the manufacturer. These data may be given in the form of unit mass (e.g., g / l or g / gallon);

[0074] The tail gas carbon emission monitoring module is used to monitor the tail gas of construction equipment, monitor the carbon content in the tail gas, and obtain the carbon emission of the equipment;

[0075] The equipment carbon emissions calculation module is used to calculate the carbon emissions of the construction equipment under perfect equipment working conditions based on the equipment working data, equipment carbon emissions and carbon emission factors corresponding to the construction equipment, including the following steps:

[0076] B1. Inspect and maintain the construction equipment to obtain the construction equipment in perfect working condition;

[0077] B2. Use construction equipment to carry out construction work;

[0078] B3. Obtain equipment working data and equipment carbon emissions during construction operations;

[0079] B4. Obtain the carbon emission factors of construction equipment;

[0080] B5. Based on the equipment working data, carbon emission factors, and equipment carbon emissions, regression analysis is performed to obtain a calculation model for carbon emissions under perfect working conditions of the equipment, which is used to output predicted equipment carbon emissions based on the input equipment working data and carbon emission factors. When performing regression analysis, a scatter plot is first made with the fuel consumption in the equipment working data as the independent variable and the equipment carbon emissions as the dependent variable; then, according to the shape and trend of the scatter plot, a regression line is added to describe the relationship between the independent variable and the dependent variable; according to the characteristics of the scatter plot and the requirements of the problem, a suitable regression model is selected, such as linear regression, polynomial regression, ridge regression, Lasso regression, etc.; statistical software or programming language is used to fit the regression model to obtain the estimated values ​​of the model parameters; evaluation indicators such as goodness of fit (R-squared), mean square error (MSE), etc. are used to evaluate the degree of fit and predictive ability of the model to the data, thereby obtaining a calculation model for carbon emissions under perfect working conditions of the equipment whose degree of fit and predictive ability meet the accuracy requirements;

[0081] The equipment working condition evaluation module is used to input the equipment working data and carbon emission factors into the corresponding equipment perfect working condition carbon emission calculation module to obtain the corresponding predicted equipment carbon emission; then, based on the carbon emission error between the predicted equipment carbon emission and the equipment carbon emission, the working condition of the construction equipment is judged. The larger the carbon emission error, the worse the working condition of the construction equipment, including the following steps:

[0082] C1. Calculate the error between the predicted equipment carbon emissions and the equipment carbon emissions to obtain the carbon emissions error;

[0083] C2. Set multiple equipment operating condition labels to correspond to different carbon emission error intervals. For example, in one embodiment, the equipment operating condition labels include perfect, general, poor, and abnormal, and the corresponding carbon emission error intervals are 0-2%, 2% (not included)-5%, 5% (not included)-10%, and more than 10% respectively;

[0084] C3. Output the equipment operating condition label corresponding to the carbon emission error interval where the carbon emission error is located to obtain the operating condition of the construction equipment.

[0085] The equipment operating condition assessment module is also used to give a reminder when the carbon emission error exceeds the set carbon emission error reminder threshold, wherein the reminder can be achieved by issuing notifications, information, alarms, etc., to remind maintenance personnel to perform maintenance and repairs on construction equipment in a timely manner; the equipment operating condition assessment module is also used to train a deep learning model based on carbon emission error, load size, continuous working time, and construction time to obtain an equipment operating condition prediction model, which is used to output the predicted carbon emission error and its corresponding equipment operating condition label based on the input load size, continuous working time, and construction time, wherein the load size, continuous working time, and construction time are used as input during training, and the carbon emissions are used as output.

[0086] The equipment construction time analysis module obtains the engineering quantity of various projects, the corresponding number of construction equipment and the construction speed, and obtains the average construction time of each construction equipment, including the following steps:

[0087] D1. Use various construction equipment to carry out construction and test the construction speed of various construction equipment;

[0088] D2. Obtain the engineering quantities of various projects and the corresponding number of construction equipment;

[0089] D3. Based on the project volume of each type of project, the corresponding number of construction equipment and construction speed, calculate the average construction time of each construction equipment.

[0090] The equipment carbon emission prediction module is used to train the machine learning model based on the load size, continuous working time, construction time and carbon emission error corresponding to the construction time of the construction equipment to obtain the working condition decline prediction model, which is used to output the predicted carbon emission error based on the input load size, continuous working time and construction time. Specifically, it includes the following steps:

[0091] E1. Obtain equipment condition labels for construction equipment conditions based on predicted carbon emission errors;

[0092] E2. Classify the load size, continuous working time and the fuel consumption corresponding to each continuous working time according to different equipment working condition labels to obtain multiple data sets;

[0093] E3. Taking the continuous working time as the independent variable and the fuel consumption as the dependent variable, regression analysis is performed on each data set to obtain the fuel consumption prediction model corresponding to each data set, which is used to output the predicted fuel consumption corresponding to the input continuous working time based on the input predicted carbon emission error, load size, and continuous working time.

[0094] Among them, construction time refers to the time that the construction equipment has been working in the project, and continuous working time refers to the time that the construction equipment works once; when training the machine learning model, the present invention does not limit the specific machine learning model, and a specific machine learning model can be selected according to the actual training situation, such as a linear regression model, a polynomial regression model, a decision tree model, a random forest model, a deep learning model, etc.; and during training, the load size, continuous working time, construction time and carbon emission error corresponding to the construction time of the construction equipment are used as samples, and the samples are divided into a training set and a verification set according to a certain ratio (such as 7:3); the training set is used to train the selected machine learning model, and the load size, continuous working time and construction time are used as the input of the model during training, and the corresponding carbon emission error is used as the output of the model to obtain the parameters of the model; after substituting the model into the parameters, the verification set is used to verify the accuracy of the model. If the model accuracy meets the preset requirements, the model training is completed. If not, the parameters are adjusted and the selected model is retrained until the model verification accuracy meets the preset requirements.

[0095] The equipment carbon emission prediction module is also used to perform regression analysis based on the predicted carbon emission error, load size, continuous working time and the fuel consumption corresponding to each continuous working time to obtain a fuel consumption prediction model, which is used to output the predicted fuel consumption based on the input predicted carbon emission error, load size, and continuous working time;

[0096] The equipment carbon emission prediction module is also used to obtain the predicted fuel consumption corresponding to each continuous working time based on the equipment working condition, the required load size, and the continuous working time, and then combine the predicted fuel consumption to predict the carbon emissions of the average construction time corresponding to the construction equipment work, including the following steps:

[0097] F1. Obtain the average construction time of the construction equipment, set the number of construction times based on the average construction time, and obtain the average continuous working time of each construction;

[0098] F2. Based on the equipment working condition prediction model, the carbon emission error and equipment working condition of each average continuous working time of the construction equipment are judged to obtain the fuel consumption prediction model corresponding to the equipment working condition; for example, in one embodiment, in the construction of the 1st to 20th average continuous working time, the equipment working condition corresponding to the construction equipment is perfect, and in the construction of the 21st to 50th average continuous working time, the equipment working condition corresponding to the construction equipment is general. Then, for the construction of the 1st to 20th average continuous working time, the fuel consumption prediction model corresponding to the perfect working condition is used to predict the fuel consumption, and for the construction of the 21st to 50th average continuous working time, the fuel consumption prediction model corresponding to the general working condition is used to predict the fuel consumption;

[0099] F3. Input the average continuous working time into the fuel consumption prediction model and output the corresponding predicted fuel consumption;

[0100] F4. Based on the carbon emission calculation model of the equipment's perfect working condition, the carbon emission error of each average continuous working time is calculated, and the carbon emission factor of the construction equipment is used to output the predicted fuel consumption and its corresponding real-time judgment of the carbon emission error of the equipment working condition to obtain the carbon emission of the average construction time corresponding to the construction equipment's work.

[0101] The equipment electricity carbon emission calculation module is used to obtain the electricity consumption of construction equipment and the electricity carbon emission factor, and obtain the electricity carbon emission based on the electricity consumption and the electricity carbon emission factor.

[0102] A method for evaluating carbon emissions from green construction of a road project comprises the following steps:

[0103] Obtain equipment working data, carbon emission factors, and equipment carbon emissions of construction equipment;

[0104] Overhaul and maintain construction equipment to obtain construction equipment in perfect working condition;

[0105] Monitor the construction process of construction equipment with perfect working conditions, and calculate the carbon emissions corresponding to the working data of each piece of equipment with perfect working conditions;

[0106] Monitor the equipment working data and equipment carbon emissions of construction equipment in real time, and judge the working condition of construction equipment based on the error between the real-time monitored equipment carbon emissions and the carbon emissions of the corresponding construction equipment when the equipment is in perfect working condition under the same equipment working data;

[0107] Obtain the engineering quantity of each type of project, the corresponding number of construction equipment and construction speed, and obtain the average construction time of each construction equipment;

[0108] Based on the load size, continuous working hours, construction time and carbon emission error of construction equipment, the machine learning model is trained to obtain the working condition decline prediction model;

[0109] Based on the predicted carbon emission error, load size, continuous working time and the fuel consumption corresponding to each continuous working time, regression analysis is performed to obtain a fuel consumption prediction model;

[0110] Equipment working conditions, required load size, continuous working time, obtain the predicted fuel consumption corresponding to each continuous working time, and then combine the predicted fuel consumption to predict the carbon emissions of the average construction time corresponding to the construction equipment operation;

[0111] The electricity consumption of the construction equipment and the carbon emission factor of electricity consumption are obtained, and the carbon emissions of electricity consumption are obtained based on the electricity consumption and the carbon emission factor of electricity consumption.

[0112] The above description is only by way of illustration of certain exemplary embodiments of the present invention. It is undoubted that those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the above drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

Claims

1. A road engineering green construction carbon emission assessment system, characterized by: It includes equipment data acquisition module, equipment carbon emission factor acquisition module, tail gas carbon emission monitoring module, equipment carbon emission calculation module, equipment working condition evaluation module, equipment construction time analysis module, equipment carbon emission prediction module, and equipment electricity carbon emission calculation module; The equipment data acquisition module is arranged on the construction equipment and is used to acquire the equipment working data of the construction equipment, wherein the equipment working data includes the load size, continuous working time, fuel consumption and type and model of the fuel used by the construction equipment; The equipment carbon emission factor acquisition module is used to acquire the carbon emission data per unit fuel of the construction equipment to obtain the carbon emission factor corresponding to each construction equipment; The tail gas carbon emission monitoring module is used to monitor the tail gas of the construction equipment, monitor the carbon content in the tail gas, and obtain the carbon emission of the equipment; The equipment carbon emission calculation module is used to calculate the carbon emission of the construction equipment under perfect equipment working conditions based on the equipment working data, equipment carbon emission and carbon emission factor corresponding to the construction equipment; The equipment working condition evaluation module is used to input the equipment working data and carbon emission factors into the corresponding equipment perfect working condition carbon emission calculation module to obtain the corresponding predicted equipment carbon emission, and judge the working condition of the construction equipment based on the carbon emission error between the predicted equipment carbon emission and the equipment carbon emission. The larger the carbon emission error, the worse the working condition of the construction equipment. The equipment operating condition assessment module is also used to give a reminder when the carbon emission error exceeds a set carbon emission error reminder threshold; The equipment construction time analysis module obtains the engineering quantity of each type of engineering, the corresponding number of construction equipment and the construction speed, and obtains the average construction time of each construction equipment; The equipment carbon emission prediction module is used to train a machine learning model based on the load size, continuous working time, construction time and carbon emission error corresponding to the construction time of the construction equipment to obtain a working condition decline prediction model, which is used to output a predicted carbon emission error based on the input load size, continuous working time and construction time; The equipment carbon emission prediction module is also used to perform regression analysis based on the predicted carbon emission error, load size, continuous working time and the fuel consumption corresponding to each continuous working time to obtain a fuel consumption prediction model, which is used to output the predicted fuel consumption based on the input predicted carbon emission error, load size, and continuous working time; The equipment carbon emission prediction module is also used to obtain the predicted fuel consumption corresponding to each continuous working time based on the equipment working condition, the required load size, and the continuous working time, and then combine the predicted fuel consumption to predict the carbon emission of the average construction time corresponding to the construction equipment operation; The equipment electricity carbon emission calculation module is used to obtain the electricity consumption of the construction equipment and the electricity carbon emission factor, and obtain the electricity carbon emission based on the electricity consumption and the electricity carbon emission factor.

2. A road engineering green construction carbon emission assessment system according to claim 1, characterized in that: The device data acquisition module acquires the continuous working time, including the following steps: Set a break duration threshold; Determine whether the duration between the current start time and the last shutdown time of the construction equipment exceeds the rest time threshold; If yes, the continuous working time will be recalculated, otherwise the continuous working time will be counted from the last shutdown time.

3. A road engineering green construction carbon emission assessment system according to claim 2, characterized in that: The equipment carbon emission calculation module is used to calculate the carbon emission of the construction equipment under perfect equipment working conditions based on the equipment working data, equipment carbon emission and carbon emission factor corresponding to the construction equipment, and includes the following steps: Overhaul and maintain construction equipment to obtain construction equipment in perfect working condition; Using the construction equipment to perform construction work; Obtaining equipment working data and equipment carbon emissions during construction operation of the construction equipment; Obtaining a carbon emission factor of the construction equipment; Based on the equipment working data, carbon emission factor, and equipment carbon emissions, a regression analysis is performed to obtain a carbon emission calculation model for equipment under perfect working conditions, which is used to output predicted equipment carbon emissions based on the input equipment working data and carbon emission factor.

4. A road engineering green construction carbon emission assessment system according to claim 3, characterized in that: The equipment working condition evaluation module judges the working condition of the construction equipment based on the carbon emission error between the predicted equipment carbon emission and the equipment carbon emission. The larger the carbon emission error, the worse the working condition of the construction equipment, including the following steps: Calculating the error between the predicted equipment carbon emissions and the equipment carbon emissions to obtain a carbon emissions error; Set multiple equipment operating condition labels to correspond to different carbon emission error ranges; The equipment operating condition label corresponding to the carbon emission error interval in which the carbon emission error is located is output to obtain the operating condition of the construction equipment.

5. A road engineering green construction carbon emission assessment system according to claim 4, characterized in that: The equipment operating condition assessment module is also used to train a deep learning model based on carbon emission errors, load size, continuous working time, and construction time to obtain an equipment operating condition prediction model, which is used to output predicted carbon emission errors and their corresponding equipment operating condition labels based on the input load size, continuous working time, and construction time.

6. A road engineering green construction carbon emission assessment system according to claim 5, characterized in that: The equipment carbon emission prediction module is also used to perform regression analysis based on the predicted carbon emission error, load size, continuous working time and fuel consumption corresponding to each continuous working time to obtain a fuel consumption prediction model, which specifically includes the following steps: Obtain equipment condition labels for construction equipment conditions based on predicted carbon emission errors; The load size, continuous working time and the fuel consumption corresponding to each continuous working time are classified according to different equipment working condition labels to obtain multiple data sets; Taking continuous working time as the independent variable and fuel consumption as the dependent variable, regression analysis was performed on each data set to obtain the fuel consumption prediction model corresponding to each data set. The model is used to output the predicted fuel consumption corresponding to the input continuous working time based on the input predicted carbon emission error, load size, and continuous working time.

7. A road engineering green construction carbon emission assessment system according to claim 6, characterized in that: The equipment construction time analysis module obtains the engineering quantity of various types of projects, the corresponding number of construction equipment and the construction speed, and obtains the average construction time of each construction equipment, including the following steps: Use various types of construction equipment to carry out construction and test the construction speed of various types of construction equipment; Obtain the engineering quantities of various projects and the corresponding number of construction equipment; Based on the project volume of each type of project, the corresponding number of construction equipment and construction speed, the average construction time of each construction equipment is calculated.

8. A road engineering green construction carbon emission assessment system according to claim 7, characterized in that: The equipment carbon emission prediction module is also used to obtain the predicted fuel consumption corresponding to each continuous working time based on the equipment working condition, the required load size, and the continuous working time, and then combine the predicted fuel consumption to predict the carbon emissions of the average construction time corresponding to the construction equipment operation, including the following steps: Obtaining an average construction time of the construction equipment, setting the number of construction times based on the average construction time, and obtaining an average continuous working time of each construction; Based on the equipment working condition prediction model, the carbon emission error of each average continuous working time of the construction equipment and the equipment working condition are determined to obtain a fuel consumption prediction model corresponding to the equipment working condition; Inputting the average continuous working time into a fuel consumption prediction model, and outputting a corresponding predicted fuel consumption; Based on the carbon emission calculation model of perfect equipment working conditions, the carbon emission error of each average continuous working time, and the carbon emission factor of the construction equipment, the output predicted fuel consumption and its corresponding real-time judgment of the carbon emission error of the equipment working condition are used to obtain the carbon emissions of the average construction time corresponding to the construction equipment working.

9. A road engineering green construction carbon emission assessment method, applicable to a road engineering green construction carbon emission assessment system according to any one of claims 1 to 8, characterized in that: The following steps are involved: Obtain equipment working data, carbon emission factors, and equipment carbon emissions of construction equipment; Overhaul and maintain construction equipment to obtain construction equipment in perfect working condition; Monitor the construction process of construction equipment with perfect working conditions, and calculate the carbon emissions corresponding to the working data of each piece of equipment with perfect working conditions; Monitor the equipment working data and equipment carbon emissions of construction equipment in real time, and judge the working condition of construction equipment based on the error between the real-time monitored equipment carbon emissions and the carbon emissions of the corresponding construction equipment when the equipment is in perfect working condition under the same equipment working data; Obtain the engineering quantity of each type of project, the corresponding number of construction equipment and construction speed, and obtain the average construction time of each construction equipment; Based on the load size, continuous working hours, construction time and carbon emission error of construction equipment, the machine learning model is trained to obtain the working condition decline prediction model; Based on the predicted carbon emission error, load size, continuous working time and the fuel consumption corresponding to each continuous working time, regression analysis is performed to obtain a fuel consumption prediction model; Equipment working conditions, required load size, continuous working time, obtain the predicted fuel consumption corresponding to each continuous working time, and then combine the predicted fuel consumption to predict the carbon emissions of the average construction time corresponding to the construction equipment operation; The electricity consumption of the construction equipment and the carbon emission factor of electricity consumption are obtained, and the carbon emissions of electricity consumption are obtained based on the electricity consumption and the carbon emission factor of electricity consumption.

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