Soil electrokinetic remediation intelligent power supply device and control method

Abstract

The present application belongs to the technical field of heavy metal contaminated soil remediation, and relates to a soil electrokinetic remediation intelligent power supply device and a control method. The method comprises: collecting real-time working condition data of soil in situ in multiple dimensions and completing signal preprocessing; solving two types of mechanism parameters, i.e. a form stability coefficient and an invalid energy consumption index, based on the collected real-time working condition data; calculating the confidence of each preset operating state, combining the solidified risk priority rule to complete state arbitration, locking the current device operating condition and matching the corresponding regulation and control strategy; generating control instructions for partition power supply parameters and power supply mode switching; adjusting the electric field output parameters and the power supply mode; returning to the soil multidimensional in-situ working condition data collection, starting the next round of regulation and control cycle, and executing in a loop until the soil remediation meets the standard. The present application can significantly reduce the overall energy consumption of the remediation process, effectively prevent the interruption and repetition of the remediation process, shorten the overall remediation cycle, and significantly improve the efficiency of the remediation operation.

Description

Technical Field

[0001] This invention belongs to the field of heavy metal contaminated soil remediation technology, specifically relating to an intelligent power supply device and control method for soil electric remediation. Background Technology

[0002] Electrokinetic remediation (EMR) technology is an important in-situ remediation technique for heavy metal pollution in low-permeability soils. Its core principle involves inserting electrodes into the contaminated soil and applying a direct current electric field. Through electromigration, electroosmosis, and electrophoresis, heavy metal ions in the soil migrate and accumulate towards the electrodes, ultimately achieving pollutant removal and soil purification. This technology boasts significant advantages such as in-situ treatment, adaptability to low-permeability soils, and minimal secondary pollution, making it a promising candidate for heavy metal pollution remediation in farmland and mining areas.

[0003] However, the large-scale engineering application of this technology has long been constrained by industry bottlenecks such as high energy consumption and unstable operation. Existing technologies generally employ constant voltage or constant current DC power supply modes, which are extensive, fixed-parameter power supplies that cannot adaptively adjust to dynamic changes in soil physicochemical properties, the migration process of heavy metal ions, and the real-time evolution of the electrode-soil interface. This power supply mode directly leads to a series of engineering problems such as electrode polarization, pH focusing, localized overheating, and uneven progress in the remediation area, resulting in a high proportion of ineffective energy consumption and high electricity costs, severely restricting the large-scale promotion and commercial application of this technology.

[0004] Existing technologies only replace the form of energy and do not establish an intelligent closed loop that adjusts power supply parameters based on real-time soil condition feedback. Essentially, they still belong to a crude power supply mode with fixed parameters, which cannot fundamentally solve core problems such as electrode polarization, soil overheating, and uneven remediation.

[0005] Relying on complex models and a large amount of computing resources, such as multiphysics simulation, unsteady convolutional networks and third-order differential feature extraction, it has inherent drawbacks such as high online solution requirements, large computing power requirements and poor system real-time performance. It is quite difficult to implement in engineering and achieve long-term stable operation in field sites, and it is difficult to adapt to the low-cost and high-reliability field engineering requirements.

[0006] In summary, existing methods for powering soil electroremediation cannot achieve the organic integration of mechanism-coupled lightweight intelligent decision-making, multi-mode adaptive power supply, precise zoned regulation, and efficient synergy with new energy sources. Therefore, developing an intelligent power supply control device and method that deeply aligns with the electrochemical mechanisms of electroremediation and possesses engineering feasibility, lightweight design, and adaptive closed-loop operation characteristics has become a key technological milestone in promoting the maturity and large-scale application of this technology. Summary of the Invention

[0007] To address the aforementioned technical problems, the present invention provides a solution. The present invention offers an intelligent power supply device and control method for soil electro-remediation.

[0008] In a first aspect, the present invention provides an intelligent power supply device for soil electric remediation, including a main control device, a field execution terminal and an energy supply unit; The main control equipment includes a multi-source signal acquisition and interface unit, a mechanism parameter real-time calculation unit, a multi-state machine decision and arbitration unit, a multi-mode power supply drive unit, and an edge-cloud collaborative communication unit; The multi-source signal acquisition and interface unit is used to connect to the field execution terminal, collect real-time working condition data of multi-dimensional soil in situ, and output the data to the mechanism parameter real-time calculation unit after completing signal preprocessing. The real-time mechanism parameter calculation unit is electrically connected to the multi-source signal acquisition and interface unit, and is used to calculate two types of mechanism parameters, namely morphological stability coefficient and ineffective energy consumption index, based on the acquired real-time operating data. The multi-state machine decision and arbitration unit is electrically connected to the mechanism parameter real-time calculation unit. The unit has a multi-parameter coupled state machine firmware at the bottom layer, which is used to calculate the confidence of each preset operating state based on the mechanism parameters and real-time operating data. Combined with the fixed risk priority rules, the state arbitration is completed, the current equipment operating condition is locked, and the corresponding control strategy is matched. The multi-mode power drive unit is electrically connected to the multi-state machine decision and arbitration unit, and is used to generate power supply control commands according to the control strategy and send them to the field execution terminal. The edge-cloud collaborative communication unit integrates an embedded industrial communication protocol stack to enable bidirectional data interaction between units within the main control device, between the main control device and field execution terminals, and between the main control device and a remote cloud platform. The field execution terminal establishes a communication connection with the main control equipment, including a sensing terminal for collecting real-time operating data and a power execution terminal for outputting repair electric field. The energy supply unit is electrically connected to the main control equipment and the field execution terminal.

[0009] Secondly, the present invention provides a soil electric remediation intelligent power supply control method based on the aforementioned soil electric remediation intelligent power supply device, comprising: The on-site sensing terminal collects real-time working condition data of multi-dimensional soil conditions in situ and performs signal preprocessing before outputting it to the mechanism parameter real-time calculation unit. The real-time mechanism parameter calculation unit calculates two types of mechanism parameters, namely the morphological stability coefficient and the ineffective energy consumption index, based on the collected real-time operating data. The multi-state machine decision and arbitration unit of the main control equipment calculates the confidence level of each preset operating state based on the mechanism parameters and real-time operating data, and completes the state arbitration in combination with the fixed risk priority rules, locks the current operating condition of the equipment and matches the corresponding control strategy. The multi-mode power drive unit generates zoned power supply parameters and control commands for switching power supply modes; The on-site power execution terminal receives and executes control commands to adjust the electric field output parameters and power supply mode; the system synchronously collects updated operating data, returns multi-dimensional in-situ operating data of the soil, starts the next round of regulation cycle, and repeats the cycle until the soil remediation meets the standards.

[0010] In some optional embodiments, the multi-source signal acquisition and interface unit integrates an RS-485 interface and an analog input interface, as well as a signal conditioning circuit for filtering and isolating preprocessing of the input sensor signals; the field execution terminal connected to the multi-source signal acquisition and interface unit includes a distributed integrated monitoring probe array, a multi-channel programmable power supply, and a partitioned repair electrode array, for in-situ synchronous acquisition of six types of working condition data: soil pH, soil redox potential, soil conductivity, soil temperature, soil moisture content, and soil electrode potential.

[0011] In some optional embodiments, the real-time mechanism parameter calculation unit is equipped with a morphological stability coefficient calculation engine. The morphological stability coefficient calculation engine pre-constructs a digital parameter mapping table of the correspondence between Eh, pH and morphological stability coefficient based on the soil redox potential and pH thermodynamic equilibrium principle of the target heavy metal, and stores it in the device's non-volatile memory. During operation, the engine uses the real-time collected soil redox potential and pH as input coordinates, locates the corresponding grid in the digital parameter mapping table, and calculates the continuous morphological stability coefficient value in the range of 0 to 1 through bilinear interpolation. The morphological stability coefficient value is used to quantitatively characterize the thermodynamic potential of the target heavy metal ions to migrate in the current soil environment.

[0012] In some optional embodiments, the real-time calculation unit for mechanism parameters includes an ineffective energy consumption index calculation engine; the ineffective energy consumption index is used by the calculation engine to acquire soil temperature time-series data in real time and calculate the temperature rise rate, simultaneously acquire the real-time total input power of the system, and continuously perform calculations according to the fixed formula of the ineffective energy consumption index; the ineffective energy consumption index is used to quantify the ineffective heat dissipation rate of the system's electrical energy, directly indicating the system's energy efficiency level and the risk of overheating operation; let the ineffective energy consumption index be... The change in soil temperature is The system's real-time total input power is The fixed formula for the ineffective energy consumption index is then expressed as: .

[0013] In some optional embodiments, the power supply control command includes a target power supply mode, a target voltage gradient, and an operating zone; the target power supply mode includes a DC power supply mode, a pulse power supply mode, and a periodic polarity reversal power supply mode.

[0014] In some optional embodiments, the power execution terminal includes a multi-channel programmable power supply and a zoned intelligent power distribution device; the multi-channel programmable power supply is equipped with a hardware waveform generator; the zoned intelligent power distribution device integrates DC circuit breakers and fuse protection devices, as well as a multi-channel relay array controlled by the main control device's digital I / O, and performs single-power-channel driven repair of multiple electrode pairs through relay switching.

[0015] In some optional embodiments, the calculation of the morphological stability coefficient includes: pre-constructing a digital parameter mapping table based on the Eh-pH thermodynamic equilibrium rule of the target heavy metal and storing it in the device memory; after real-time acquisition of soil redox potential and pH, locating the grid in the mapping table using the two as coordinates, and calculating the continuous morphological stability coefficient value in the 0~1 interval through bilinear interpolation.

[0016] In some optional embodiments, the calculation of the ineffective energy consumption index includes: real-time acquisition of soil temperature time-series data, calculation of the temperature rise rate per unit time, synchronous acquisition of the real-time total input power of the equipment, and continuous calculation of the ineffective energy consumption index value according to the fixed formula of the ineffective energy consumption index; the larger the value of the ineffective energy consumption index, the more ineffective heat is generated per unit power, the lower the system energy efficiency, and the higher the risk of overheating operation.

[0017] In some optional embodiments, completing status arbitration in conjunction with fixed risk prioritization rules includes: The confidence scores of the six operating states are obtained by multi-feature weighted calculation, and the state with the highest confidence score is selected. Determine if the highest confidence level is greater than or equal to the activation threshold. If not, maintain the operating state of the previous control cycle. If the highest confidence level reaches the activation threshold, further determine if there are other states whose confidence level is less than the set threshold and is higher than the activation threshold. If not, directly determine the state with the highest confidence level as the current operating state. If so, sort the risk priorities in descending order and select the state with the highest priority as the current operating state.

[0018] The beneficial effects of this invention are: (1) This invention constructs a dedicated intelligent hardware device for soil electroremediation scenarios by designing a dedicated mechanism calculation engine and a dedicated decision logic unit and other dedicated hardware logic, which deeply couples the electrochemical mechanism with the hardware solidification logic, and can significantly reduce the overall energy consumption of the remediation process. (2) By using a state machine to identify and actively suppress risks such as electrode polarization and heavy metal precipitation in the early stage, the interruption and repetition of the repair process can be effectively prevented, the overall repair cycle can be shortened, and the efficiency of the repair operation can be significantly improved. (3) The equipment relies on an intelligent closed-loop system of perception, diagnosis, execution and feedback to automatically identify, process and restore various risks such as polarization, overheating and precipitation during operation. Through the architecture of edge real-time control and cloud collaborative management, it can achieve truly unattended operation and intelligent maintenance throughout the entire repair process, further significantly reducing long-term maintenance manpower costs. Attached Figure Description

[0019] Figure 1 This is a schematic diagram of a smart power supply device for soil electric remediation provided in Embodiment 1 of the present invention; Figure 2 This is a schematic diagram of the structure of a single probe; Figure 3 This is a schematic diagram of the cross-sectional structure of an integrated multi-parameter monitoring probe; Figure 4 This is a schematic diagram of the on-site deployment of the repair system, including the main control equipment; Figure 5 This is a flowchart of an intelligent power supply control method for soil electro-remediation provided in Embodiment 2 of the present invention; Figure 6 This is a schematic diagram of the multi-mode power supply waveform timing supported by the main control device drive unit.

[0020] In the diagram: 210 - pH electrode; 211 - Four-electrode conductivity sensor; 212 - Oxidation-reduction potential electrode; 213 - Temperature and humidity composite sensor; 214 - Signal output interface; 32 - Remediation electrode anode; 33 - Remediation electrode cathode; 35 - Monitoring probe group; 36 - Pollutant migration path; 37 - Waterproof cable; 28 - Corrosion-resistant protective shell; 29 - Sensor cluster; 41 - Farmland remediation demonstration area; 42 - High-pollution remediation zone; 43 - Medium-pollution remediation zone; 44 - Low-pollution remediation zone; 45 - Zone main electrode; 46 - Inter-electrode distributed probe; 47 - Independent zone power supply cable; 48 - Energy supply unit; 49 - Main control equipment; 410 - Cloud data interaction link; 411 - Soil pollution concentration gradient area. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0022] Example 1 As an example, in order to solve the problems existing in the prior art, this embodiment provides an intelligent power supply device for soil electric remediation.

[0023] The implementation details of the device in this embodiment are described below. The following implementation details are provided for ease of understanding and are not necessary for implementing this solution.

[0024] A smart power supply device for soil electric remediation includes a main control device, a field execution terminal, and an energy supply unit; The main control equipment includes a multi-source signal acquisition and interface unit, a mechanism parameter real-time calculation unit, a multi-state machine decision and arbitration unit, a multi-mode power supply drive unit, and an edge-cloud collaborative communication unit; The multi-source signal acquisition and interface unit is used to connect to the field execution terminal, collect real-time working condition data of multi-dimensional soil in situ, and output the data to the mechanism parameter real-time calculation unit after completing signal preprocessing. The real-time mechanism parameter calculation unit is electrically connected to the multi-source signal acquisition and interface unit, and is used to calculate two types of mechanism parameters, namely morphological stability coefficient and ineffective energy consumption index, based on the acquired real-time operating data. The multi-state machine decision and arbitration unit is electrically connected to the mechanism parameter real-time calculation unit. The unit has a multi-parameter coupled state machine firmware at the bottom layer, which is used to calculate the confidence of each preset operating state based on the mechanism parameters and real-time operating data. Combined with the fixed risk priority rules, the state arbitration is completed, the current equipment operating condition is locked, and the corresponding control strategy is matched. The multi-mode power drive unit is electrically connected to the multi-state machine decision and arbitration unit, and is used to generate power supply control commands according to the control strategy and send them to the field execution terminal. The edge-cloud collaborative communication unit integrates an embedded industrial communication protocol stack to enable bidirectional data interaction between units within the main control device, between the main control device and field execution terminals, and between the main control device and a remote cloud platform. The field execution terminal establishes a communication connection with the main control equipment, including a sensing terminal for collecting real-time operating data and a power execution terminal for outputting repair electric field. The energy supply unit is electrically connected to the main control equipment and the field execution terminal.

[0025] Sensing terminals such as Figure 2As shown, a single probe is an independent field monitoring device. Its core is a corrosion-resistant protective housing 28, which integrates multiple commercial sensors as a sensor cluster 29, including: a pH electrode 210, a four-electrode conductivity sensor 211, a redox potential electrode 212, and a temperature and humidity composite sensor 213. All sensors are connected to a unified signal output interface 214 via internal circuitry. This design makes the probe a standardized, plug-and-play detection component that can be independently inserted and reused.

[0026] Deployment plan: such as Figure 3 As shown, during equipment deployment, multiple probes are used as a monitoring probe group 35, inserted into the soil profile at fixed intervals, such as 20 cm, along the line connecting the anode 32 and cathode 33 of a pair of remediation electrodes. The probes are connected to the on-site data acquisition unit via waterproof cables 7, forming a distributed equipment monitoring network that accurately covers the electric field and pollutant migration path 36.

[0027] The device's built-in data acquisition unit is responsible for collecting data from each probe, performing analog-to-digital conversion of the signals, and executing the device's firmware algorithm to complete outlier filtering, digital filtering, and data packaging. The processed standard data frames are then wirelessly transmitted to the device's control host via the device's integrated LoRa or 4G / 5G communication module.

[0028] In some optional embodiments, the multi-source signal acquisition and interface unit integrates an RS-485 interface and an analog input interface, as well as a signal conditioning circuit for filtering and isolating preprocessing of the input sensor signals; the field execution terminal connected to the multi-source signal acquisition and interface unit includes a distributed integrated monitoring probe array, a multi-channel programmable power supply, and a partitioned repair electrode array, for in-situ synchronous acquisition of six types of working condition data: soil pH, soil redox potential, soil conductivity, soil temperature, soil moisture content, and soil electrode potential.

[0029] Specifically, the on-site hardware terminal for multi-source signal acquisition and interface unit includes a distributed integrated monitoring probe array, a multi-channel programmable power supply, and a zoned remediation electrode array. The distributed integrated monitoring probe array is deployed between the remediation electrode pairs to collect multi-dimensional operating condition data such as soil pH, redox potential, conductivity, temperature, moisture content, and electrode potential in situ and synchronously. The multi-channel programmable power supply is used to receive control commands and output precisely adjustable DC, pulse, or periodic polarity reversal electric fields to the remediation electrode array. The zoned remediation electrode array is deployed in the remediation area as an electric field execution terminal.

[0030] Specifically, the multi-state machine decision and arbitration unit is the core hardware decision unit of the device. The underlying multi-parameter coupled state machine firmware has six preset device operating states (high-efficiency migration state S0, polarization risk state S1, overheat warning state S2, precipitation warning state S3, equilibrium repair state S4 and low power consumption termination state S5) and confidence activation thresholds, as well as risk priority rules: S3>S1≈S2>S4>S0>S5.

[0031] All possible operating conditions of the equipment are defined as six clearly defined, mutually exclusive equipment operating states, and encoded into fixed decision logic: S0 represents the high-efficiency migration state, where the equipment is in optimal repair condition. The judgment conditions (must be met simultaneously) are: SS>0.7, IEI<0.15, all electrode potentials are below the safety threshold, conductivity shows a steady downward trend, DC mode, and the control objective is to maintain high-efficiency operation.

[0032] S1 represents the polarization risk state, where abnormal polarization occurs at the electrode interface. The criteria for determination are: the electrode potential of any power supply circuit continuously exceeds the safety threshold, and the soil pH in its vicinity changes significantly and abruptly within a short period. The control objective is to rapidly eliminate polarization.

[0033] S2 is an overheating warning state, indicating excessive ineffective heat dissipation in the system. The criteria for determination are: the average soil temperature rise rate or the IEI value continuously exceeds the preset safety threshold. The control objective is to suppress temperature rise and reduce ineffective energy consumption.

[0034] S3 indicates a precipitation warning state, signifying that the soil environment has entered the range where heavy metals are difficult to dissolve. Criteria for determination: SS values ​​show a rapid downward trend, and soil pH > 8.5 or redox potential Eh < 100mV. Control objective: Prevent heavy metal precipitation.

[0035] S4 represents a balanced repair state, where the repair progress in each zone is uneven. The criteria for determination are: the overall operating conditions meet the characteristics of the efficient migration state (S0), but the difference in the rate of decrease in conductivity calculated from different monitoring zones exceeds a set threshold (e.g., 20%). The control objective is to balance the repair progress.

[0036] S5 represents the low-power final stage of repair, indicating the end of the repair process. The criteria for this stage are: the average conductivity across the entire field has decreased to below 30% of its initial value, and the rate of decrease has significantly slowed. The control objective is to maintain low-power stability and achieve a safe final stage.

[0037] In some optional embodiments, the real-time mechanism parameter calculation unit is equipped with a morphological stability coefficient calculation engine. The morphological stability coefficient calculation engine pre-constructs a digital parameter mapping table of the correspondence between Eh, pH and morphological stability coefficient based on the soil redox potential and pH thermodynamic equilibrium principle of the target heavy metal, and stores it in the device's non-volatile memory. During operation, the engine uses the real-time collected soil redox potential and pH as input coordinates, locates the corresponding grid in the digital parameter mapping table, and calculates the continuous morphological stability coefficient value in the range of 0 to 1 through bilinear interpolation. The morphological stability coefficient value is used to quantitatively characterize the thermodynamic potential of the target heavy metal ions to migrate in the current soil environment.

[0038] In some optional embodiments, the real-time calculation unit for mechanism parameters includes an ineffective energy consumption index calculation engine; the ineffective energy consumption index is used by the calculation engine to acquire soil temperature time-series data in real time and calculate the temperature rise rate, simultaneously acquire the real-time total input power of the system, and continuously perform calculations according to the fixed formula of the ineffective energy consumption index; the ineffective energy consumption index is used to quantify the ineffective heat dissipation rate of the system's electrical energy, directly indicating the system's energy efficiency level and the risk of overheating operation; let the ineffective energy consumption index be... The change in soil temperature is The system's real-time total input power is The fixed formula for the ineffective energy consumption index is then expressed as: .

[0039] In some optional embodiments, the power supply control command includes a target power supply mode, a target voltage gradient, and an operating zone; the target power supply mode includes a DC power supply mode, a pulse power supply mode, and a periodic polarity reversal power supply mode.

[0040] The multi-mode power supply drive unit has embedded hardware drivers for three power supply modes: DC, pulse, and periodic polarity reversal. It receives decision instructions to smoothly adjust the electric field parameters and output waveform.

[0041] The edge-cloud collaborative communication unit integrates an industrial communication protocol stack to enable data interaction between the main control equipment, field terminals, and remote cloud platform.

[0042] In some optional embodiments, the power execution terminal includes a multi-channel programmable power supply and a zoned intelligent power distribution device; the multi-channel programmable power supply is equipped with a hardware waveform generator; the zoned intelligent power distribution device integrates DC circuit breakers and fuse protection devices, as well as a multi-channel relay array controlled by the main control device's digital I / O, and performs single-power-channel driven repair of multiple electrode pairs through relay switching.

[0043] The power execution terminal is responsible for receiving and executing control commands from the multi-mode power drive unit of the main control device, and outputting a controllable electric field.

[0044] The multi-channel programmable power supply unit serves as the core power conversion and modulation unit, employing an industrial-grade multi-channel independent output programmable DC power supply. The voltage (0-50V) and current (0-5A) of each output channel can be independently and continuously adjusted, and it features a built-in hardware waveform generator, supporting millisecond-level software switching between three operating modes: DC, pulse, and periodic polarity reversal. The device boasts high-precision output (voltage accuracy ±0.1%) and real-time status feedback, enabling precise parsing and execution of commands from the control host via communication interfaces (such as RS485 and Ethernet), ensuring accurate control of electric field strength and mode.

[0045] Zonal Power Distribution and Electrode Switching Equipment: To adapt to large-area repair scenarios, this equipment is equipped with a zonal intelligent power distribution cabinet. Each power channel connects to an independent power distribution cabinet, which integrates DC circuit breakers, fuses, and other protective devices, as well as a multi-channel relay array controlled by the control host's digital I / O. This design allows a single multi-channel power supply unit to drive multiple sets of repair electrode pairs sequentially through relay switching in a time-sharing multiplexing manner, achieving flexible deployment of one unit in multiple zones and significantly improving the utilization rate of a single power supply unit and the economy of the entire system. All electrodes are reliably connected to the power distribution cabinet via corrosion-resistant dedicated cables.

[0046] Specifically, the calculation of the morphological stability coefficient includes: pre-constructing a digital parameter mapping table based on the Eh-pH thermodynamic equilibrium rule of the target heavy metal and storing it in the device memory; after real-time acquisition of soil redox potential and pH, locating the grid in the mapping table using these two values ​​as coordinates, and calculating the continuous morphological stability coefficient value in the 0~1 interval through bilinear interpolation.

[0047] Specifically, the calculation of the ineffective energy consumption index includes: real-time collection of soil temperature time-series data, calculation of the temperature rise rate per unit time, synchronous acquisition of the real-time total input power of the equipment, and continuous calculation according to the fixed formula of the ineffective energy consumption index to obtain the value of the ineffective energy consumption index; the larger the value of the ineffective energy consumption index, the more ineffective heat is generated per unit power, the lower the system energy efficiency, and the higher the risk of overheating operation.

[0048] In some optional embodiments, completing status arbitration in conjunction with fixed risk prioritization rules includes: The confidence scores of the six operating states are obtained by multi-feature weighted calculation, and the state with the highest confidence score is selected. Determine if the highest confidence level is greater than or equal to the activation threshold. If not, maintain the operating state of the previous control cycle. If the highest confidence level reaches the activation threshold, further determine if there are other states whose confidence level is less than the set threshold and is higher than the activation threshold. If not, directly determine the state with the highest confidence level as the current operating state. If so, sort the risk priorities in descending order and select the state with the highest priority as the current operating state.

[0049] As an optional implementation method, the energy supply unit provides power supply hardware for the equipment, adopts a photovoltaic-energy storage-grid collaborative architecture, provides power to the main control equipment and field execution terminals, and is controlled by the main control equipment to complete energy dispatch optimization.

[0050] As attached Figure 4 The diagram shown illustrates the on-site deployment of the remediation system, including the main control equipment. It displays the overall system layout of the remediation zones, main control equipment, on-site execution terminals, energy supply units, and cloud data interaction, intuitively reflecting the core technical solution of this invention. Specifically: 41 represents the farmland remediation demonstration area; 42 represents high-pollution remediation zone A; 43 represents medium-pollution remediation zone B; 44 represents low-pollution remediation zone C; 45 represents the zone's main electrode; 46 represents the inter-electrode distributed probe; 47 represents the independent zone power supply cable; 48 represents the energy supply unit; 49 represents the main control equipment; 410 represents the cloud data interaction link; and 411 represents the soil pollution concentration gradient area. The energy supply unit is connected to the on-site execution terminal, supplying power to each zone. The on-site execution terminal and the energy supply unit, along with the main control equipment, collect on-site data and output control commands. Simultaneously, they achieve bidirectional data transmission with the cloud platform through the cloud data interaction link. The overall energy flow and data interaction logic is consistent with... Figure 1 The system architecture remains consistent.

[0051] To achieve green and continuous power supply, this equipment integrates a photovoltaic energy storage collaborative power supply unit. This unit's hardware includes a solar photovoltaic array, a lithium-ion battery energy storage system, and an energy management controller. The EMS monitors the photovoltaic power generation, the energy storage battery's state of charge, and the repair load power in real time, and executes a fixed four-mode energy dispatch strategy. Mode 1 is direct photovoltaic power supply and charging: when photovoltaic output is greater than or equal to load demand, photovoltaic power is directly supplied to the repair equipment, and the surplus power is stored in the battery; Mode 2 is a hybrid power supply of photovoltaic and energy storage: when the photovoltaic output is less than the load demand, the photovoltaic and battery power supply work together. Mode 3 is energy storage power supply: at night or when there is no light, the energy storage battery provides power independently; Mode 4 is grid power backup: When the energy storage capacity is insufficient and the photovoltaic power cannot meet the demand, it automatically and seamlessly switches to grid power to ensure that the repair process is absolutely uninterrupted.

[0052] The power supply unit is connected to the primary input of the multi-channel programmable power supply device through the energy management controller, and exchanges status information with the control host through the communication interface, together forming a stable, efficient and intelligent energy supply system.

[0053] As an optional implementation, this intelligent power supply device is also used in conjunction with a cloud-based collaborative platform deployed on a remote server. This platform does not participate in the millisecond-level real-time control loop of the device; its main functions include: Data aggregation and storage: Continuously receive and securely store full operating data, equipment status logs, event alarms and energy consumption information reported by various field master control devices (through edge-cloud collaborative communication units) via the Internet; Visual monitoring: Provides a web or mobile human-machine interface for managers to remotely and in real time view the equipment operation status, soil parameter change curves and remediation progress of multiple remediation sites; Data analysis and energy efficiency assessment: Based on historical data, conduct repair energy efficiency analysis and root cause analysis, and generate a repair effectiveness assessment report; Strategy library optimization and synchronization: On long-term (e.g., daily or weekly) scales, the platform can optimize repair strategies based on big data analysis results, generate updated strategy parameters (such as state confidence weights, trigger thresholds, etc.), and securely send them to the designated master control device. Upon receiving the updated strategy parameters, the master control device updates them to its local fixed strategy library, enabling iterative optimization of the algorithm. The interaction relationship emphasizes that the "edge-cloud collaborative communication unit" of the main control device is responsible for establishing and maintaining a communication link with the cloud platform, uploading data according to a predetermined protocol and frequency, and receiving configuration instructions and policy update packages from the platform. The core autonomous capabilities of the device do not depend on the real-time online status of the platform.

[0054] Example 2 It adopts the same principle as the device in Example 1, as shown in the attached document. Figure 5 As shown, this embodiment provides a smart power supply control method for soil electroremediation, including steps 110-150.

[0055] Step 110: The field sensing terminal collects real-time working condition data of multi-dimensional soil in situ and completes signal preprocessing, and then outputs it to the mechanism parameter real-time calculation unit. Step 120: The real-time mechanism parameter calculation unit calculates two types of mechanism parameters, namely the morphological stability coefficient and the ineffective energy consumption index, based on the collected real-time operating data.

[0056] Specifically, the calculation of the morphological stability coefficient includes: pre-constructing a digital parameter mapping table based on the Eh-pH thermodynamic equilibrium rule of the target heavy metal and storing it in the device memory; after real-time acquisition of soil redox potential and pH, locating the grid in the mapping table using these two values ​​as coordinates, and calculating the continuous morphological stability coefficient value in the 0~1 interval through bilinear interpolation.

[0057] Specifically, the calculation of the ineffective energy consumption index includes: real-time collection of soil temperature time-series data, calculation of the temperature rise rate per unit time, synchronous acquisition of the real-time total input power of the equipment, and continuous calculation according to the fixed formula of the ineffective energy consumption index to obtain the value of the ineffective energy consumption index; the larger the value of the ineffective energy consumption index, the more ineffective heat is generated per unit power, the lower the system energy efficiency, and the higher the risk of overheating operation.

[0058] Step 130: The multi-state machine decision and arbitration unit of the main control equipment calculates the confidence level of each preset operating state based on the mechanism parameters and real-time operating condition data, completes the state arbitration in combination with the fixed risk priority rules, locks the current operating condition of the equipment and matches the corresponding control strategy.

[0059] Specifically, completing status arbitration by combining fixed risk priority rules includes: The confidence scores of the six operating states are obtained by multi-feature weighted calculation, and the state with the highest confidence score is selected. Determine if the highest confidence level is greater than or equal to the activation threshold. If not, maintain the operating state of the previous control cycle. If the highest confidence level reaches the activation threshold, further determine if there are other states whose confidence level is less than the set threshold and is higher than the activation threshold. If not, directly determine the state with the highest confidence level as the current operating state. If so, sort the risk priorities in descending order and select the state with the highest priority as the current operating state.

[0060] In practical applications, specifically, to accurately identify the status, the firmware employs a multi-feature weighted confidence calculation and arbitration mechanism, and its solidified logic executes the following process: Feature extraction and confidence calculation: For each predefined state S i Key features are extracted from the judgment criteria and normalized to obtain the feature value V. ij And combined with the preset weight w ij According to the formula C(S) i )=∑(w ij ·V ij Parallel calculation of confidence scores for each state; State determination: Select the state S with the highest confidence level. max If C(S) maxIf the activation threshold is exceeded (e.g., 0.6), the next arbitration step will be initiated; otherwise, the device will maintain its previous operating state. Risk Priority Arbitration: When multiple states have similar confidence levels (e.g., the difference is less than 0.1) and are all above the activation threshold, a final decision is made according to the fixed risk priority rules, with the priority order being: S3>S1≈S2>S4>S0>S5. This rule ensures that the equipment always prioritizes handling high-risk operating conditions.

[0061] Step 140: The multi-mode power drive unit generates partition power supply parameters and control commands for switching power supply modes.

[0062] Step 150: The on-site power execution terminal receives and executes control commands, adjusts the electric field output parameters and power supply mode; the system synchronously collects updated operating data, returns multi-dimensional in-situ operating data of the soil, starts the next round of regulation cycle, and repeats the cycle until the soil remediation meets the standards.

[0063] This invention does not employ the conventional approach of combining general-purpose hardware with general-purpose software. Instead, it constructs a dedicated intelligent hardware device for soil electroremediation scenarios by designing a specialized mechanism-based computation engine, a dedicated decision-making logic unit, and other specialized hardware logic. The device deeply couples electrochemical mechanisms with hardware-based solidified logic.

[0064] Practical engineering applications have verified that the intelligent decision-making and control based on this invention can reduce the overall energy consumption of the repair process by more than 20%. By using a state machine to identify and actively suppress risks such as electrode polarization and heavy metal precipitation in the early stages, the interruption and recurrence of the repair process can be effectively prevented. It is estimated that the overall repair cycle can be shortened by 10%-20%, significantly improving the time economy and cost controllability of the repair operation.

[0065] As a standardized industrial product, the equipment features clear input and output interfaces, is easy to install on-site, and can be used immediately upon plugging in, significantly reducing the complexity of system integration and debugging. The device has zoned differentiated power supply capabilities, adapting to the spatial heterogeneity of contaminated sites; it can also integrate renewable energy sources such as photovoltaics, making it well-suited for complex application scenarios with limited power supply in fields such as farmland and mining areas, demonstrating strong engineering adaptability.

[0066] The equipment relies on an intelligent closed-loop system of sensing, diagnosis, execution, and feedback to automatically identify, handle, and recover from various risks during operation, such as polarization, overheating, and precipitation. Through an architecture of edge real-time control and cloud-based collaborative management, it achieves truly unattended operation and intelligent maintenance throughout the entire repair process, further significantly reducing long-term maintenance manpower costs.

[0067] As attached Figure 6The diagram shows the timing sequence of the multi-mode power supply waveforms supported by the main control device's drive unit. This embodiment uses a typical electrode polarization risk handling process as an example to demonstrate how intelligent power supply equipment achieves a complete autonomous working cycle from anomaly detection, autonomous decision-making, and precise execution to restoration to normal operation. This process intuitively demonstrates the effectiveness of the operational logic of the device's embedded state machine decision firmware and the closed loop of perception-decision-execution-feedback.

[0068] Background setting: On the third day of the repair project, the equipment was in a high-efficiency operating state; the control host determined that the equipment was operating in the high-efficiency range S0 and controlled the multi-channel programmable power supply to output in DC mode with a voltage gradient of 1.2 V / cm, and the repair process was stable; Closed-loop control cycle: Equipment data acquisition, starting from the second day of repair, the integrated monitoring probe deployed near anode No. 2 transmits data trends and controls the multi-channel programmable power supply to output voltage gradient in pulse mode. The anode potential slowly and continuously rises from 1.8V to 2.1V within a few hours, achieving polarization risk suppression; at the same time, the soil pH value in its adjacent area drops significantly from 6.5 to 4.0 during the same period, and the equipment data acquisition unit uploads the processed data to the control host in real time; Intelligent Diagnosis and Decision Making (Control Host Firmware Operation): The state machine decision firmware in the control host starts real-time calculation. Based on the strong coupling characteristics of potential increase and pH change, the confidence level C calculated by the firmware for "polarization treatment mode S1" rapidly increases and exceeds the activation threshold (e.g., 0.6), and is significantly higher than other modes. According to the risk priority rules preset in the firmware, the control host determines that the device needs to immediately enter polarization treatment mode S1. Strategy Execution: Based on the preset strategy matched to polarization setting S1, the control host immediately generates a control command: "Switch power supply circuit 2 to pulse mode, parameters 1Hz and 50%, voltage gradient maintained at 1.2 V / cm." This command is sent to the multi-channel programmable power supply device via the communication interface. The power supply device responds within milliseconds, switching the output waveform of channel 2 from DC to a square wave pulse with specified parameters to suppress precipitation risk. Closed-loop feedback and state transition: The equipment continued to operate in pulse mode and was continuously monitored. After about 6 hours, the monitoring data showed that the potential of anode 2 had dropped and stabilized below 1.8V, and the pH value of the nearby soil had also stabilized. At this time, the control host recalculated the confidence levels of each state. The confidence level of polarization treatment mode S1 had dropped below the threshold, while the confidence level of high-efficiency mode S0 had regained dominance. Based on this, the control host determined that the equipment risk had been eliminated, automatically returned the operating mode to high-efficiency mode S0, and instructed the power supply equipment to restore channel 2 to DC power supply mode, with the voltage gradient smoothly transitioning to 1.2 V / cm.

[0069] The potential risk of electrode polarization was detected autonomously by the device at its initial stage, and the device completed automatic identification, targeted suppression, and safe recovery within approximately 6 hours. The entire process required no manual intervention, effectively avoiding potential repair stagnation, efficiency reduction, and energy consumption surges caused by polarization. This fully demonstrates the adaptive and closed-loop autonomous capabilities of the intelligent power supply device in response to operational risks.

[0070] Experimental Results and Data Comparison: To verify the actual effectiveness of the intelligent power supply equipment and power supply control method, an experimental group and a control group were set up in the same cadmium-contaminated farmland plot, and an in-situ comparative remediation experiment was carried out for 14 days.

[0071] Experimental conditions included: soil conditions: the experimental soil was typical cadmium-contaminated farmland soil with an initial cadmium content of 9.2 mg / kg, within the specified risk screening range (0.3 mg / kg, pH ≤ 7.5); experimental group: used the intelligent power supply equipment of this invention, including a distributed monitoring probe, an edge control host, and a multi-channel programmable power supply, operating in a closed-loop adaptive mode; control group: used the same electrode arrangement, but the power supply equipment was a traditional constant voltage DC power supply, with the output voltage set to a fixed 1.2 V / cm, without intelligent adjustment function. All other experimental conditions were identical for both groups, making them comparable.

[0072] Remediation Results: After the same remediation cycle, the pollutant content in both groups of soils decreased to below the national standard risk screening value, and both met the requirements for safe utilization.

[0073] Energy consumption and process stability comparison: Although the repair effects were the same, the two groups showed significant differences in energy consumption and operation process. The core comparison is shown in Table 1: Table 1. Energy Consumption Ratio to Operating Process

[0074] This comparative experiment confirms that the intelligent power supply equipment and power control method for soil electric remediation provided by this invention achieves significant energy saving and consumption reduction (23.5% reduction in this example) while ensuring the remediation effect meets the standards, directly reducing the power cost of remediation; through the built-in state machine decision firmware, the equipment is endowed with the ability to autonomously cope with operational risks (polarization and overheating), ensuring the continuity and stability of the remediation process and avoiding remediation stagnation and cycle extension caused by faults; it realizes full automation and unmanned operation of the remediation process, reduces the dependence on professional operation and maintenance personnel, and improves the level of engineering application of the technology.

[0075] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A smart power supply device for soil electric remediation, characterized in that, Includes main control equipment, field execution terminals, and energy supply units; The main control equipment includes a multi-source signal acquisition and interface unit, a mechanism parameter real-time calculation unit, a multi-state machine decision and arbitration unit, a multi-mode power supply drive unit, and an edge-cloud collaborative communication unit; The multi-source signal acquisition and interface unit is used to connect to the field execution terminal, collect real-time working condition data of multi-dimensional soil in situ, and output the data to the mechanism parameter real-time calculation unit after completing signal preprocessing. The real-time mechanism parameter calculation unit is electrically connected to the multi-source signal acquisition and interface unit, and is used to calculate two types of mechanism parameters, namely morphological stability coefficient and ineffective energy consumption index, based on the acquired real-time operating data. The multi-state machine decision and arbitration unit is electrically connected to the mechanism parameter real-time calculation unit. It is used to calculate the confidence level of each preset operating state based on the mechanism parameters and real-time operating condition data, and complete the state arbitration in combination with the fixed risk priority rules to lock the current equipment operating condition and match the corresponding control strategy. The multi-mode power drive unit is electrically connected to the multi-state machine decision and arbitration unit, and is used to generate control commands for partitioned power supply parameters and power supply mode switching and send them to the field execution terminal. The edge-cloud collaborative communication unit integrates an embedded industrial communication protocol stack to enable bidirectional data interaction between units within the main control device, between the main control device and field execution terminals, and between the main control device and a remote cloud platform. The field execution terminal establishes a communication connection with the main control equipment, including a sensing terminal for collecting real-time operating data and a power execution terminal for outputting repair electric field. The energy supply unit is electrically connected to the main control equipment and the field execution terminal.

2. The intelligent power supply device for soil electric remediation according to claim 1, characterized in that, The multi-source signal acquisition and interface unit integrates an RS-485 interface and an analog input interface, as well as a signal conditioning circuit for filtering and isolating preprocessing of the input sensor signals. The field execution terminal connected to the multi-source signal acquisition and interface unit includes a distributed integrated monitoring probe array, a multi-channel programmable power supply, and a partitioned repair electrode array, used for in-situ synchronous acquisition of six types of working condition data: soil pH, soil redox potential, soil conductivity, soil temperature, soil moisture content, and soil electrode potential.

3. The intelligent power supply device for soil electric remediation according to claim 1, characterized in that, The real-time mechanism parameter calculation unit is equipped with a morphological stability coefficient calculation engine; The morphological stability coefficient calculation engine pre-constructs a digital parameter mapping table of the correspondence between Eh, pH and morphological stability coefficient based on the soil redox potential and acid-base thermodynamic equilibrium principle of the target heavy metal, and stores it in the device's non-volatile memory. During operation, the soil redox potential and pH were collected in real time as input coordinates. The corresponding grid was located in the digital parameter mapping table and the continuous morphological stability coefficient value in the range of 0 to 1 was obtained through bilinear interpolation. The morphological stability coefficient value is used to quantitatively characterize the thermodynamic potential of target heavy metal ions to migrate in the current soil environment.

4. The intelligent power supply device for soil electric remediation according to claim 1, characterized in that, The mechanism parameter real-time calculation unit includes an ineffective energy consumption index calculation engine; the ineffective energy consumption index is used by the calculation engine to obtain soil temperature time series data in real time and calculate the temperature rise rate, synchronously obtain the system's real-time total input power, and continuously perform calculations according to the fixed formula of the ineffective energy consumption index; The ineffective energy consumption index is used to quantify the rate of ineffective heat dissipation of electrical energy in a system, directly indicating the system's energy efficiency level and the risk of overheating; let the ineffective energy consumption index be... The change in soil temperature is The system's real-time total input power is The fixed formula for the ineffective energy consumption index is then expressed as: 。 5. The intelligent power supply device for soil electric remediation according to claim 1, characterized in that, The power supply control commands include the target power supply mode, target voltage gradient, and operating zone; the target power supply mode includes DC power supply mode, pulse power supply mode, and periodic polarity reversal power supply mode.

6. The intelligent power supply device for soil electric remediation according to claim 1, characterized in that, The power execution terminal includes a multi-channel programmable power supply and a zoned intelligent power distribution device; the multi-channel programmable power supply is equipped with a hardware waveform generator; the zoned intelligent power distribution device integrates DC circuit breakers and fuse protection devices, as well as a multi-channel relay array controlled by the main control device's digital I / O, which performs single-power-channel driven repair of multiple electrode pairs through relay switching.

7. A soil electro-remediation intelligent power supply control method based on the soil electro-remediation intelligent power supply device according to any one of claims 1-6, characterized in that, include: The on-site sensing terminal collects real-time working condition data of multi-dimensional soil conditions in situ and performs signal preprocessing before outputting it to the mechanism parameter real-time calculation unit. The real-time mechanism parameter calculation unit calculates two types of mechanism parameters, namely the morphological stability coefficient and the ineffective energy consumption index, based on the collected real-time operating data. The multi-state machine decision and arbitration unit of the main control equipment calculates the confidence level of each preset operating state based on the mechanism parameters and real-time operating data, and completes the state arbitration in combination with the fixed risk priority rules, locks the current operating condition of the equipment and matches the corresponding control strategy. The multi-mode power drive unit generates zoned power supply parameters and control commands for switching power supply modes; The on-site power execution terminal receives and executes control commands to adjust the electric field output parameters and power supply mode; the system synchronously collects updated operating data, returns multi-dimensional in-situ operating data of the soil, starts the next round of regulation cycle, and repeats the cycle until the soil remediation meets the standards.

8. The intelligent power supply control method for soil electro-remediation according to claim 7, characterized in that, The calculation of the morphological stability coefficient includes: pre-constructing a digital parameter mapping table based on the Eh-pH thermodynamic equilibrium rule of the target heavy metal and storing it in the device memory; after real-time acquisition of soil redox potential and pH, locating the grid in the mapping table using the two as coordinates, and calculating the continuous morphological stability coefficient value in the 0~1 interval through bilinear interpolation.

9. The intelligent power supply control method for soil electro-remediation according to claim 7, characterized in that, The calculation of the ineffective energy consumption index includes: real-time collection of soil temperature time-series data, calculation of the temperature rise rate per unit time, synchronous acquisition of the real-time total input power of the equipment, and continuous calculation according to the fixed formula of the ineffective energy consumption index to obtain the value of the ineffective energy consumption index; the larger the value of the ineffective energy consumption index, the more ineffective heat is generated per unit power, the lower the system energy efficiency, and the higher the risk of overheating operation.

10. The intelligent power supply control method for soil electro-remediation according to claim 7, characterized in that, The status arbitration, which is completed by combining the established risk priority rules, includes: The confidence scores of the six operating states are obtained by multi-feature weighted calculation, and the state with the highest confidence score is selected. Determine if the highest confidence level is greater than or equal to the activation threshold. If not, maintain the operating state of the previous control cycle. If the highest confidence level reaches the activation threshold, further determine if there are other states whose confidence level is less than the set threshold and is higher than the activation threshold. If not, directly determine the state with the highest confidence level as the current operating state. If so, sort the risk priorities in descending order and select the state with the highest priority as the current operating state.

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