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CN-121998348-A - Environment-friendly supervision and management method and system for engineering project construction

CN121998348ACN 121998348 ACN121998348 ACN 121998348ACN-121998348-A

Abstract

The invention discloses an environment-friendly supervision and management method and system for engineering project construction, wherein the method comprises the following steps of firstly collecting multi-source heterogeneous environment-friendly data; the method comprises the steps of firstly, establishing a BP neural network differential preprocessing multi-source heterogeneous environment-friendly data optimized by an improved sparrow search algorithm, establishing a multi-dimensional data association model, calculating association degree of each construction procedure and each pollutant index, setting an association degree threshold value to position a pollution source, generating a targeted modification suggestion by setting up a hierarchical early warning mechanism, finally, establishing a blockchain closed-loop supervision procedure, tracking modification scheme submission, modification progress implementation and modification result review process of a construction unit, and storing whole-procedure data to a alliance chain node. By adopting the environment-friendly supervision and management method and system for engineering project construction, the invention realizes all-weather full-coverage monitoring of construction environment protection, improves data reliability and traceability efficiency, and can effectively adapt to environment-friendly supervision requirements of complex construction scenes such as buildings, mines and the like.

Inventors

  • ZHANG JIAN
  • WEI BAIYIN
  • PAN JIE
  • WANG TIANYUE

Assignees

  • 海口赛一教育科技有限公司

Dates

Publication Date
20260508
Application Date
20260127

Claims (10)

  1. 1. The environment-friendly supervision and management method for engineering project construction is characterized by comprising the following steps of: S1, collecting multi-source heterogeneous environment-friendly data; s2, adopting a BP neural network optimized by an improved sparrow search algorithm to differentially preprocessing multi-source heterogeneous environment-friendly data; S3, establishing a multidimensional data association model, calculating association degrees of each construction procedure and each pollutant index, and setting an association degree threshold value to position a pollution source; s4, constructing a grading early warning mechanism and generating a targeted rectifying and modifying suggestion; S5, constructing a closed-loop supervision flow of the block chain, tracking the submission of a modification scheme of a construction unit, the implementation of modification progress and the review process of modification results, and storing the whole flow data to the alliance chain node.
  2. 2. The engineering project construction environment-friendly supervision and management method according to claim 1, wherein in S1, the multi-source heterogeneous environment-friendly data pollutant index and the environment-friendly monitoring auxiliary index are specifically: The dust pollutant indexes comprise PM2.5 concentration, PM10 concentration and total suspended particulate matter TSP concentration collected by a dust sensor; Noise pollutant indexes including equivalent continuous A sound level, noise peak value and noise frequency distribution acquired by a noise sensor; The water quality pollutant indexes comprise Chemical Oxygen Demand (COD), ammonia nitrogen (NH 3 -N), suspended Substances (SS), pH value, total Phosphorus (TP) and Total Nitrogen (TN) concentrations acquired by a water quality monitoring sensor; The solid waste pollutant indexes comprise solid waste weight, solid waste type, stacking area and stacking height which are acquired by a solid waste monitoring sensor; the environment-friendly monitoring auxiliary indexes comprise wind speed, humidity, temperature, wind direction and atmospheric pressure which are acquired by a meteorological monitor; And transmitting the original data to a cloud data center by adopting an MQTT protocol through a 5G communication module.
  3. 3. The method for environment-friendly supervision and management of engineering project construction according to claim 2, wherein in S2, the improvement of sparrow search algorithm to optimize BP neural network specifically comprises the following steps: S21, introducing an adaptive weight coefficient Adjusting individual sparrow searching step length: ; Wherein, the For the maximum weight coefficient to be the one, For the minimum weight coefficient to be a minimum, For the current number of iterations, The maximum iteration number; S22, initializing sparrow population by adopting Logistic chaotic mapping, wherein the formula is as follows: ; Wherein, the Is the first The chaos sequence value of the secondary iteration is used for enhancing the uniformity of the initial distribution of the population; s23, taking the minimum predicted mean square error of the BP neural network as an fitness function, wherein the fitness function is as follows: ; Wherein, the For the fitness value, i.e. the predicted mean square error, The number of samples to be taken, Is the first The true value of the individual samples is calculated, Is the first Predicted values for the individual samples; through the iterative optimization of the behavior of discoverers, followers and alerters of the sparrow search algorithm, the predicted mean square error is minimized, and the optimal initial weight and threshold of the BP neural network are obtained; s24, converting the discrete pollutant index into numerical value characteristics by adopting single-heat coding, and inputting the numerical value characteristics into a network, wherein the continuous pollutant index is normalized to a [0,1] interval by adopting a normalization formula: ; Wherein, the As the original value of the value, As a result of the minimum value of the index, Is the maximum value of the index; the structural parameters of the BP neural network after optimization are as follows: the number of the nodes of the input layer is equal to the total number of the pollutant indexes and the environment-friendly monitoring auxiliary indexes, and the number of the nodes of the hidden layer is calculated by an empirical formula Determining; Wherein, the For the number of nodes of the input layer, For the number of output layer nodes, The number of nodes of the output layer is 1, and the nodes are used for outputting the integrated environment-friendly characteristic value after fusion.
  4. 4. The construction environment-friendly supervision and management method for engineering projects according to claim 3, wherein in the step S3, a multi-dimensional data association model of construction procedures and environmental protection influence is established based on an improved gray association analysis algorithm, multi-source heterogeneous data and construction procedure parameters after the pretreatment in the step S2 are input into the model, and the association degree of each construction procedure and each pollutant index is calculated according to the following formula: ; Wherein, the Is the first Contaminant index of (a) Correlation degree of each construction procedure; Is the first after pretreatment A number of contaminant indicators; Is the first The characteristic parameters of each construction process comprise process time, equipment power and material consumption; a resolution factor of 0.5 is used for weakening the influence of the maximum absolute difference; the minimum absolute difference of the double layers is the minimum value of the difference value between all indexes and all process parameters; the maximum absolute difference of the double layers, namely the maximum value of the difference value between all indexes and all process parameters; Setting a correlation threshold, when When the correlation threshold is not less than, judging the first The construction procedure is The main pollution source of the individual pollutant indexes is that the discrete pollutant indexes are converted into standardized process characteristic parameters before the correlation degree calculation.
  5. 5. The engineering project construction environment-friendly supervision and management method according to claim 4, wherein the step S4 is specifically: Dividing three-level early warning thresholds for each pollutant index, comparing the pollutant index pretreated by the S2 with the early warning thresholds, generating early warning information comprising the type, the value and the related procedure of the exceeding standard index by combining the pollution tracing result of the S3, pushing the early warning information to related responsible persons through multiple channels, and optimizing pushing content and strategies through linkage of environment-friendly monitoring auxiliary indexes.
  6. 6. The method for environmental protection supervision and management of engineering project construction according to claim 5, wherein in S4, the dividing criteria of the three-level early warning threshold are: the first-level early warning is that the monitoring value exceeds the standard value by 10% -20%, and the light exceeding is judged; The second-level early warning is that the monitoring value exceeds the standard value by 20% -50%, and the second-level early warning is judged to be the moderate exceeding standard; the third-level early warning is that the monitoring value exceeds the standard value by more than 50%, and the weight exceeding is judged; the early warning information comprises an exceeding index name, an exceeding numerical value, exceeding duration, associated construction procedures, targeted correction suggestions and correction time limits; The pushing channel comprises a short message, a system popup window and an audible and visual alarm, and the pushing object is a construction unit site responsible person, an environment-friendly supervision person and project supervision.
  7. 7. The method for environmental protection supervision and management of engineering project construction according to claim 6, wherein in S4, for the dust pollutant index, the pushing priority is: When triggering any grade early warning, the construction site audible and visual alarm immediately starts a grading audible and visual signal, wherein the primary early warning is yellow, the secondary early warning is orange, and the tertiary early warning is red, and the construction site audible and visual alarm is continued until the rectification is started; for noise pollutant indexes, the push priority is as follows: When the resident rest period triggers the early warning, the on-site audible and visual alarm is closed, and forced rectifying and modifying advice for immediately suspending the high-noise working procedure is added only through the short message pushing of the high-brightness popup window and the standard red night emergency early warning; For the water quality pollutant index, the push priority is as follows: When triggering early warning, the environmental protection supervisory personnel and project supervision terminal popup windows display full-dimensional pollutant index data, historical trend curves, associated procedures and potential hazards; the short message pushing content comprises an exceeding water quality pollutant index, a numerical value and a modification scheme template downloading link, wherein a construction technology responsible person receives a site notice and synchronously acquires a real-time monitoring position of a water quality sensor to position a stain discharge; For solid waste pollutant indexes, the pushing priority is as follows: When triggering early warning, the full-terminal popup window displays the accurate solid waste stacking coordinates, the exceeding standard proportion, the solid waste types and related procedures, and the short beacon stacking area field numbers; for the environment-friendly monitoring auxiliary index, the early warning is not triggered independently, and the environment-friendly monitoring auxiliary index is pushed only in linkage with the pollutant index, wherein the pushing priority is as follows: when the wind speed is more than or equal to 5m/s, the linked dust pollutant indexes are pushed to prompt that the dust diffusion is easy to be aggravated in windy weather, and the spraying equipment is started after strengthening coverage; when the humidity is less than or equal to 30%, the linked solid waste pollutant index is pushed to prompt that dust is easy to generate in dry weather, and the sprinkling frequency is increased.
  8. 8. The engineering project construction environment-friendly supervision and management method according to claim 7, wherein in S5, the alliance chain node comprises a construction unit node, an environment-friendly supervision department node, a supervision unit node and a third party detection mechanism node; The construction unit node is used for uploading real-time pollutant index and environment-friendly monitoring auxiliary index data in the rectification scheme and rectification process; the environment-friendly supervision department node is used for auditing the pertinence and feasibility of the rectification scheme; The supervision unit node is used for rechecking the standard condition of the pollutant index after correction; And the third-party detection mechanism nodes are used for uploading all-dimensional pollutant index reports which are independently detected, and each node adopts PBFT consensus mechanism and has data read-write authority and consensus verification authority.
  9. 9. An environmental protection supervisory management system for engineering project construction for implementing the method of any one of claims 1-8, comprising: the data acquisition and communication module is used for acquiring multi-source heterogeneous environment-friendly data through the multi-sensor and the monitoring equipment and transmitting the original multi-source heterogeneous data to the cloud data center through the 5G communication module and the MQTT protocol; The data fusion and preprocessing module is internally provided with a BP neural network optimized by an improved sparrow search algorithm, and is used for carrying out differential preprocessing and feature fusion on the multi-source heterogeneous environment-friendly data and outputting a comprehensive environment-friendly feature value; The pollution tracing analysis module is used for establishing a multidimensional data association model based on an improved grey association analysis algorithm, calculating and positioning association relations between construction procedures and pollutant indexes and main pollution sources; the intelligent early warning and pushing module is internally provided with a grading early warning mechanism and is used for generating and pushing early warning information containing targeted correction suggestions in multiple channels according to the exceeding grade and the pollution tracing result; and the block chain closed-loop supervision module is used for constructing a alliance chain network, and tracking and storing full-flow data from the submission of the rectification scheme, the progress implementation and the result review.
  10. 10. The project construction environmental protection supervisory control system according to claim 9, wherein the data fusion and preprocessing module comprises: The computing processing unit is used for executing an iterative optimization process of the improved sparrow searching algorithm so as to determine the optimal initial weight and the threshold value of the BP neural network; The data normalization unit is used for performing single-heat coding on the discrete pollutant indexes and normalizing the continuous pollutant indexes to a [0,1] interval; the block chain closed loop supervision module comprises a verification and audit unit, and cross-verifies the correction related data submitted by each node and the report based on a consensus mechanism of the alliance chain node and generates an audit trail record.

Description

Environment-friendly supervision and management method and system for engineering project construction Technical Field The invention relates to the technical field of engineering environment-friendly supervision, in particular to an engineering project construction environment-friendly supervision and management method and system. Background Along with the continuous increase of ecological environment protection, environmental protection supervision in the construction stage of engineering projects becomes an important concern for industries. And if the control is improper, the surrounding ecological environment can be seriously damaged, the normal life of residents is influenced, and even the environmental pollution dispute is caused. The existing construction environment-friendly supervision and management means still takes the traditional mode as the main mode, manual inspection is limited by manpower cost, inspection period and coverage range, all-weather and full-area continuous monitoring is difficult to realize, obvious supervision blind areas and hysteresis exist, a single-sensor monitoring scheme can only acquire single-dimension pollutant index data, systematic fusion and standardized pretreatment of multi-source data are lacking, standard of index classification and parameter definition are not clear, data precision is easily interfered by complex construction environment, and accurate support cannot be provided for supervision decision. Meanwhile, the traditional early warning mechanism mostly adopts a unified threshold comparison mode, and a differentiation strategy is designed without combining the related characteristics of the construction process and pollutant emission, so that early warning information is insufficient in pertinence and weak in pollution tracing capability, and the rectification work is lack of definite direction and low in efficiency. In the prior art, partial environment-friendly monitoring systems attempt to introduce sensing equipment and data processing technology, but still have obvious short plates, namely, the acquisition range of a sensor, the parameters of a core algorithm and index distinguishing rules are not clarified, the multi-source data fusion effect is poor, the monitoring precision is difficult to meet the requirement of fine supervision, or the block chain technology is adopted to realize data storage, but key technical details such as a perfect consensus mechanism and a data storage medium are not adopted, and an adaptive early warning pushing scheme is not designed according to different pollutant characteristics, so that early warning response timeliness is insufficient, and the current intelligent and fine environment-friendly supervision requirement is difficult to adapt. In summary, the prior art generally has the problems of incomplete monitoring coverage, insufficient data precision, fuzzy definition of core parameters, weak pollution tracing capability, non-closed loop of supervision flow, lack of pertinence of early warning pushing and the like, and cannot meet the environmental protection supervision requirements of complex construction scenes of various engineering projects such as buildings, mines and the like. Therefore, there is a need for a method and a system for managing environmental protection supervision of construction with high efficiency of data processing, adaptive early warning strategy and closed-loop controllable flow. Disclosure of Invention The invention aims to provide an environment-friendly supervision and management method and system for engineering project construction, which aim to provide intelligent and closed-loop support for environment-friendly supervision of construction so as to realize the aims of all-weather monitoring, high-reliability data, high-efficiency traceability and accurate early warning. In order to achieve the above purpose, the invention provides an environment-friendly supervision and management method for engineering project construction, which comprises the following steps: S1, collecting multi-source heterogeneous environment-friendly data; s2, adopting a BP neural network optimized by an improved sparrow search algorithm to differentially preprocessing multi-source heterogeneous environment-friendly data; S3, establishing a multidimensional data association model, calculating association degrees of each construction procedure and each pollutant index, and setting an association degree threshold value to position a pollution source; s4, constructing a grading early warning mechanism and generating a targeted rectifying and modifying suggestion; S5, constructing a closed-loop supervision flow of the block chain, tracking the submission of a modification scheme of a construction unit, the implementation of modification progress and the review process of modification results, and storing the whole flow data to the alliance chain node. Preferably, in S1, the multi-source heterogeneous environmenta