Block chain-based lead-zinc beneficiation whole-process pollution tracing and early warning method and system

Abstract

The invention discloses a lead-zinc beneficiation whole process pollution traceability and early warning method based on a block chain, and the method comprises the following steps: data collection and chaining: collecting environmental parameter data in real time through Internet of Things sensor nodes deployed at all key links of a lead-zinc beneficiation whole process, encrypting and signing the data, and then transmitting the encrypted and signed data to a server; according to the method, a block chain technology and a specific environmental protection scene of lead-zinc ore dressing are deeply fused, so that a complete closed loop from credible data storage to intelligent early warning to accurate tracing is realized, and the method is high in practicability and high in practicability. The credibility of the data is improved by utilizing the tampering resistance of the block chain, and the intelligent contract executes early warning, so that the early warning is quicker and more intelligent, the data chain is complete and credible, the supervision efficiency is high, the traceability accuracy is high, sharing can be performed in a safe and credible environment, and an information island is broken.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of environmental protection technology and information technology, in particular to a lead-zinc ore dressing whole-process pollution traceability and early warning method and system based on block chain. BACKGROUND

[0002] The lead-zinc ore dressing process produces a large amount of wastewater, waste residue and dust containing heavy metals, which poses a serious threat to the environment. Current environmental supervision mainly relies on manual sampling, laboratory analysis and fixed-point online monitoring systems, which have the following inherent defects: 1. Low data reliability: centralized data management systems are prone to data tampering or falsification, forming "yin and yang accounts", so that the supervision data cannot be used as effective law enforcement evidence; 2. Difficult to trace: the migration of pollutants in the environment is a dynamic process. Due to scattered, discontinuous and possibly distorted data, it is difficult to quickly and accurately trace back to the specific pollution leakage link and responsible subject; 3. Early warning lag: the existing early warning relies mainly on manual judgment or simple threshold alarm, lacking intelligent and automated multi-level response mechanism, with slow response speed, which cannot effectively prevent environmental accidents; 4. Information silos: the data standards of enterprises, environmental protection departments and third-party monitoring agencies are different, making it difficult to share and cooperate, resulting in information silos; The block chain technology provides a new way to solve the above problems due to its characteristics of decentralization, non-tamperability and traceability. Therefore, in order to avoid the above technical problems, it is necessary to provide a lead-zinc ore dressing whole-process pollution traceability and early warning method and system based on block chain to overcome the defects in the prior art. SUMMARY

[0003] The present application provides a lead-zinc ore dressing whole-process pollution traceability and early warning method and system based on block chain, which can effectively solve the problems of low data reliability, difficult traceability, early warning lag and information silos in the background art.

[0004] To achieve the above purpose, the present application provides the following technical scheme: a lead-zinc ore dressing whole-process pollution traceability and early warning method based on block chain, comprising the following steps: S1: data acquisition and chain: through the deployment of Internet of Things sensor nodes in each key link of the lead-zinc ore dressing whole process, real-time acquisition of environmental parameter data, encryption and signature of the data, and broadcast to the block chain network, verified by the consensus mechanism, packaged to generate a new block, and complete data notarization; S2: Intelligent early warning: preset the early warning threshold and rule of various pollutants in the smart contract of the blockchain. The smart contract compares the environmental data on the chain with the early warning threshold at regular intervals. Once the data is abnormal, the corresponding graded early warning event is triggered automatically, and early warning information is sent to the relevant responsible nodes. S3: Pollution tracing: when receiving the early warning, based on the time-series environmental data stored on the blockchain, the migration and diffusion path of the pollutant is constructed by analyzing the change trend and correlation of the data at each link, and the specific link and location of the pollution source are located.

[0005] According to the above technical scheme, the key link in step S1 includes at least one of the following: raw ore yard, crushing and grinding workshop, beneficiation workshop, concentrate dewatering workshop, tailings pond, wastewater discharge port, and factory boundary monitoring point. The environmental parameter data includes at least one of the following: water quality pH value, heavy metal ion concentration, chemical oxygen demand, suspended solids concentration, and atmospheric dust concentration.

[0006] According to the above technical scheme, in step S1, a consortium chain architecture is used, and the consensus mechanism uses PBFT. Data storage uses a combination of on-chain storage of data hash values and key metadata, and off-chain distributed storage system for storing original detailed data.

[0007] According to the above technical scheme, the graded early warning event in step S2 includes blue early warning, yellow early warning, orange early warning, and red early warning. The trigger conditions include the amplitude, duration, and risk model calculation value of the monitoring data exceeding the threshold. The early warning rules include at least one of the following: automatically notifying the environmental protection person in charge of the enterprise, triggering frequent monitoring, starting the linkage management facility, and sending an alarm to the supervision platform.

[0008] According to the above technical scheme, in step S3, the migration and diffusion path of the pollutant is constructed as follows: taking the pollution discovery point as the starting point, the time-series data of each upstream monitoring point recorded in the blockchain is queried in reverse, the time sequence and concentration gradient change of the pollutant are compared, and the most likely pollution source location is calculated by using the backtracking algorithm combined with geographic information system (GIS) and hydrogeological parameters.

[0009] A lead-zinc ore dressing full-process pollution tracing and early warning system based on blockchain includes: The perception layer is composed of a plurality of Internet of Things sensors arranged in the lead-zinc ore dressing full process, which is used to collect environmental parameter data. The blockchain layer is a consortium blockchain network composed of multiple nodes, which is used to store consensus environmental data and deploy smart contracts for executing intelligent early warning. Application layer: contains pollution traceability module and early warning information display module, provides visual operation interface and data analysis service for users; The perception layer, the blockchain layer and the application layer are connected in sequence.

[0010] According to the technical scheme, the Internet of Things sensor of the perception layer is internally provided with a unique digital identity identifier, and is registered and notarized in the blockchain layer.

[0011] According to the technical scheme, the smart contract of the blockchain layer includes a data verification contract, a warning triggering contract and a traceability query contract.

[0012] According to the technical scheme, the application layer is further integrated with a geographic information system (GIS) for visual display of the monitoring point position, real-time data, early warning information and pollutant diffusion simulation path on an electronic map.

[0013] According to the technical scheme, the blockchain layer is further provided with a sensor credibility evaluation mechanism, which analyzes the consistency of historical data of each Internet of Things sensor node and the cross comparison result with adjacent monitoring node data through a smart contract, calculates and assigns a credibility score for each sensor node; When the credibility score of a certain sensor node is lower than a preset threshold, the data verification contract of the blockchain layer starts an additional verification process for the environmental data uploaded by the node, otherwise the weight of the data in the consensus process is reduced, thereby improving the accuracy and reliability of the environmental data records on the chain.

[0014] Compared with the prior art, the beneficial effects of the present application are: 1. High data credibility: the non-tamperable nature of the blockchain fundamentally eliminates environmental monitoring data fraud, providing strong judicial evidence for environmental law enforcement.

[0015] 2. Early warning intelligence and automation: through the automatic execution of complex warning rules by the smart contract, the transformation from "people defense" to "technology defense" is realized, greatly improving the efficiency of early warning and response.

[0016] 3. Accurate and efficient traceability: based on a complete and reliable data chain, the pollution process can be quickly restored, the responsible link can be accurately located, and the supervision efficiency is improved.

[0017] 4. Break down the information silos: the architecture of the alliance chain promotes data sharing and business collaboration among regulatory departments, enterprises, the public and other parties in a trusted environment In summary, by deeply integrating blockchain technology with specific environmental protection scenarios in lead-zinc ore beneficiation, a complete closed loop is achieved, from credible data storage to intelligent early warning and precise traceability. The immutability of blockchain enhances data credibility, and smart contracts execute early warnings, making them faster and more intelligent. The complete and reliable data chain ensures high regulatory efficiency, high traceability accuracy, and can be shared in a secure and reliable environment, breaking down information silos. Attached Figure Description

[0018] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used together with the embodiments of the invention to explain the invention and do not constitute a limitation thereof.

[0019] In the attached diagram: Fig. 1 This is a schematic diagram of the overall architecture of the system of the present invention; Fig. 2 This is a flowchart of the method of the present invention; Fig. 3 This is a logical diagram illustrating the intelligent early warning and tracing process of this invention. Detailed Implementation

[0020] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0021] Example: Figs. 1-3 As shown, this invention provides a technical solution: a blockchain-based method for tracing and early warning of pollution sources throughout the lead-zinc ore beneficiation process, comprising the following steps: S1: Data Acquisition and On-Chain: By deploying IoT sensor nodes at key stages of the lead-zinc ore beneficiation process, environmental parameter data is collected in real time. After the data is encrypted and signed, it is broadcast to the blockchain network. After verification by the consensus mechanism, it is packaged to generate a new block and the data is stored. S2: Smart Early Warning: Preset early warning thresholds and rules for various pollutants in the blockchain smart contract. The smart contract compares the on-chain environmental data with the early warning thresholds at regular intervals. Once the data is abnormal, it automatically triggers the corresponding graded early warning event and sends early warning information to the relevant responsible nodes. S3: Pollution Source Tracing: When an early warning is received, based on the time-series environmental data stored on the blockchain, the migration and diffusion paths of pollutants are constructed by analyzing the changing trends and correlations of data at each stage, and the specific stages and locations of pollution sources are located.

[0022] Key components in step S1 include: raw ore stockpile, crushing and grinding workshop, beneficiation workshop, concentrate dewatering workshop, tailings dam, wastewater discharge outlet, and plant boundary monitoring point; The environmental parameter data includes water quality pH value, heavy metal ion concentration, chemical oxygen demand, suspended substance concentration, and atmospheric dust concentration.

[0023] In step S1, a consortium chain architecture is adopted, and a PBFT consensus mechanism is adopted. Data storage adopts a combination of on-chain storage of data hash values and key metadata and off-chain distributed storage of original detailed data.

[0024] The hierarchical early warning events in step S2 include blue early warning, yellow early warning, orange early warning, and red early warning. The triggering conditions include the amplitude, duration, and risk model calculation value of the monitoring data exceeding the threshold value. The early warning rules include automatically notifying the enterprise environmental protection person in charge, triggering frequent monitoring, starting the linkage management facility, and sending an alarm to the supervision platform.

[0025] In step S3, the migration and diffusion path of the pollutant is specifically constructed as follows: taking the pollution discovery point as the starting point, the time sequence data of each upstream monitoring point recorded in the blockchain is reversely queried, the time sequence and concentration gradient change of the pollutant are compared, geographic information system (GIS) and hydrogeological parameters are combined, and the most possible pollution source position is calculated by using a backtracking algorithm.

[0026] A lead-zinc ore dressing full-process pollution traceability and early warning system based on a blockchain includes the following system building process: The perception layer is composed of a plurality of Internet of Things sensors arranged in the lead-zinc ore dressing full process, which is used to collect environmental parameter data. Specifically, Internet of Things devices including pH sensors, heavy metal online analyzers, and turbidimeters are arranged at key points such as the crushing workshop, the separation workshop, the concentrate storage, the tailings dam body, the leachate collection well, and the total drainage outlet. Each device is burned with a unique DID as an identity identifier when it is manufactured.

[0027] The blockchain layer is a consortium blockchain network composed of multiple nodes, which is used to store environmental data that has passed consensus, and has a smart contract for executing intelligent early warning. Specifically, the Hyperledger Fabric consortium chain framework is used to build the nodes, which include municipal ecological environment bureau nodes, enterprise environmental protection department nodes, and third-party audit agency nodes. The consensus algorithm adopts an efficient consensus mechanism Kafka, and the data verification contract, the early warning triggering contract, and the traceability query contract are deployed. The application layer includes a pollution traceability module and an early warning information display module, which provide a visual operation interface and data analysis service for users. Specifically, a B / S architecture Web application is developed, a Leaflet open source GIS component is integrated, real-time data dashboards, early warning management, and traceability analysis function interfaces are provided, and the monitoring point position, real-time data, early warning information, and pollutant diffusion simulation path are visually displayed on an electronic map. The blockchain layer further deploys a sensor credibility assessment mechanism, which analyzes the consistency of historical data of each IoT sensor node and the results of cross-comparison with data from neighboring monitoring nodes through smart contracts, and calculates and assigns a credibility score to each sensor node. When the credibility score of a sensor node falls below a preset threshold, the data verification contract in the blockchain layer initiates an additional verification process for the environmental data uploaded by that node; otherwise, it reduces the weight of its data in the consensus process, thereby improving the accuracy and reliability of on-chain environmental data recording.

[0028] The perception layer, blockchain layer, and application layer are connected sequentially.

[0029] The threshold setting for triggering the early warning contract refers to the "Emission Standard of Pollutants for Lead and Zinc Industry (GB25466-2010)".

[0030] Workflow of this invention: Data uplink: Zn from tailings dam leachate collection well 2+ The sensor collects data once per minute. After the data is encrypted by the gateway, it is uploaded to the blockchain node via its API interface. The blockchain only stores the encrypted data hash, timestamp, sensor DID, and Zn. 2+ Concentration value.

[0031] Warning triggered: At 15:00 on a certain day, Zn 2+ The concentration exceeded the threshold by 1.5 times for 5 consecutive minutes. The alert was triggered, the contract was automatically executed, and the alert was classified as "orange alert". The contract will automatically perform the following operations: 1. Permanently record the event on the blockchain; 2. Push alert information to the company's environmental protection manager's APP; 3. Send early warning messages to the municipal ecological and environmental protection bureau's monitoring platform.

[0032] Pollution source tracing: After receiving the warning, regulatory personnel click "One-click source tracing" at the application layer. The system initiates the source tracing query contract, starting from the leachate collection well, and reverse-queries the historical data on the chain: First, it finds that the data of the tailings dam return water pump station is abnormal, 2 minutes earlier than the collection well. Then, it finds that the data of the beneficiation workshop drainage outlet is abnormal earliest, specifically 10 minutes earlier than the return water pump station. Combining the hydrogeological parameter model, the system highlights the pollution path on the GIS map, showing that it originated from an accidental leak in the beneficiation workshop, and generates a source tracing report.

[0033] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A blockchain-based method for tracing and early warning of pollution sources throughout the lead-zinc ore beneficiation process, characterized in that, Includes the following steps: S1: Data Acquisition and On-Chain: By deploying IoT sensor nodes at key stages of the lead-zinc ore beneficiation process, environmental parameter data is collected in real time. After the data is encrypted and signed, it is broadcast to the blockchain network. After verification by the consensus mechanism, it is packaged to generate a new block and the data is stored. S2: Intelligent Early Warning: The smart contract of the blockchain presets early warning thresholds and rules for various pollutants. The smart contract compares the on-chain environmental data with the early warning thresholds at regular intervals. Once the data is abnormal, the corresponding graded early warning event is automatically triggered and the early warning information is sent to the relevant responsible nodes. S3: Pollution Source Tracing: When an early warning is received, based on the time-series environmental data stored on the blockchain, the migration and diffusion paths of pollutants are constructed by analyzing the changing trends and correlations of data at each stage, and the specific stages and locations of pollution sources are located.

2. The blockchain-based method for pollution source tracing and early warning throughout the lead-zinc ore beneficiation process according to claim 1, characterized in that, The key components in step S1 include at least one of the following: raw ore stockpile, crushing and grinding workshop, beneficiation workshop, concentrate dewatering workshop, tailings dam, wastewater discharge outlet, and plant boundary monitoring point; The environmental parameter data includes at least one of the following: water pH value, heavy metal ion concentration, chemical oxygen demand, suspended solids concentration, and atmospheric dust concentration.

3. The blockchain-based method for pollution source tracing and early warning throughout the lead-zinc ore beneficiation process according to claim 1, characterized in that, In step S1, a consortium blockchain architecture is adopted, and the consensus mechanism is PBFT. Data storage employs a combination of on-chain storage of data hash values ​​and key metadata, and off-chain distributed storage system storage of raw, detailed data.

4. The blockchain-based method for pollution source tracing and early warning throughout the lead-zinc ore beneficiation process according to claim 1, characterized in that, The graded warning events in step S2 include blue warning, yellow warning, orange warning and red warning; Triggering conditions include the magnitude and duration of monitored data exceeding the threshold, and the value calculated by the risk model; The early warning rules include at least one of the following: automatically notifying the company's environmental protection manager, triggering frequency-enhanced monitoring, activating the coordinated treatment facilities, and sending an alarm to the regulatory platform.

5. A blockchain-based method for tracing and early warning of pollution sources throughout the lead-zinc ore beneficiation process, as described in claim 1, is characterized in that... In step S3, the specific steps for constructing the migration and diffusion path of pollutants are as follows: starting from the pollution discovery point, the time-series data of each upstream monitoring point recorded in the blockchain are queried in reverse. By comparing the time sequence of the pollutant's appearance and the changes in concentration gradient, and combining geographic information system (GIS) and hydrogeological parameters, the most likely location of the pollution source is calculated using a backtracking algorithm.

6. A blockchain-based pollution source tracing and early warning system for the entire lead-zinc ore beneficiation process, used to implement the method described in any one of claims 1-5, characterized in that, include: The perception layer consists of several IoT sensors deployed throughout the lead-zinc ore beneficiation process, used to collect environmental parameter data. Blockchain layer: A consortium blockchain network composed of multiple nodes, used to store consensus-based environmental data and deploy smart contracts for executing intelligent early warnings; Application layer: Includes pollution source tracing module and early warning information display module, providing users with a visual operation interface and data analysis services; The perception layer, blockchain layer, and application layer are connected in sequence.

7. A blockchain-based pollution source tracing and early warning system for the entire lead-zinc ore beneficiation process according to claim 6, characterized in that, The IoT sensors in the perception layer have built-in unique digital identity identifiers and are registered and stored in the blockchain layer.

8. A blockchain-based pollution source tracing and early warning system for the entire lead-zinc ore beneficiation process according to claim 6, characterized in that, The smart contracts in the blockchain layer include: data verification contracts, early warning trigger contracts, and traceability query contracts.

9. A blockchain-based pollution source tracing and early warning system for the entire lead-zinc ore beneficiation process according to claim 6, characterized in that, The application layer also integrates a Geographic Information System (GIS) to visualize the location of monitoring points, real-time data, early warning information, and simulated paths of pollutant diffusion on electronic maps.

10. A blockchain-based pollution source tracing and early warning system for the entire lead-zinc ore beneficiation process according to claim 6, characterized in that: The blockchain layer is further deployed with a sensor credibility assessment mechanism, which analyzes the consistency of historical data of each IoT sensor node and the results of cross-comparison with data of neighboring monitoring nodes through smart contracts, and calculates and assigns a credibility score to each sensor node. When the credibility score of a sensor node is lower than a preset threshold, the data verification contract of the blockchain layer initiates an additional verification process for the environmental data uploaded by the node; otherwise, it reduces the weight of the data in the consensus process, thereby improving the accuracy and reliability of on-chain environmental data recording.

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