An early warning and regulation system and method for anaerobic fermentation based on H2 dynamic response and multi-parameter fusion

Abstract

The application discloses an early warning and regulation system and method for anaerobic fermentation based on H2 dynamic response and multi-parameter fusion. The system adopts a six-layer hierarchical architecture, including a field sensing layer, a data access layer, an edge gateway layer, a platform application layer, a control system layer and a regulation execution layer. The field sensing layer collects gas phase, liquid phase, solid phase and equipment state parameters, and the gas phase parameters at least include H2, CH4 and CO2. The platform application layer performs operation state identification based on H2 dynamic response and multi-parameter combination judgment, generates five-level early warning including normal, attention, early warning, alarm and protection, and outputs intelligent regulation suggestions and feedback optimization. The control system layer and the regulation execution layer are linked to form a complete closed loop from data collection to control execution. Through H2 dynamic response and multi-parameter fusion, the application realizes early identification and intelligent closed-loop regulation of anaerobic fermentation instability.

Description

Technical Field

[0001] This invention belongs to the field of intelligent control technology for anaerobic fermentation processes, specifically relating to an early warning and regulation system and method for anaerobic fermentation based on H2 dynamic response and multi-parameter fusion. Background Technology

[0002] Anaerobic fermentation is an important technical route for the reduction, stabilization, and resource utilization of food waste, wet waste, sludge, livestock and poultry manure, and other organic solid waste. Through the anaerobic fermentation process, organic matter can be converted into biogas, achieving energy recovery and pollutant reduction. However, in actual engineering operation, anaerobic fermentation systems are affected by multiple factors such as feed composition, solids content, temperature, pH, toxic or inhibitory substances, load fluctuations, mixing state, and microbial activity, exhibiting nonlinear, hysteretic, and coupled characteristics, making stable operation and control quite difficult.

[0003] Existing anaerobic fermentation projects typically rely on manual inspections, basic DCS / PLC control, and a limited number of online instruments for operation and management. Online monitoring parameters are mostly concentrated on basic or outcome-based indicators such as temperature, liquid level, pressure, feed rate, and gas production. Some projects are equipped with online instruments for pH, ORP, and biogas components, but most systems remain at the level of data acquisition, curve display, and limit alarms. They lack integrated analysis of gas phase, liquid phase, solid phase, and equipment status data, and also lack a closed-loop mechanism to translate operational status identification results into engineering control actions.

[0004] During anaerobic fermentation acidification, inhibited methanogenesis, or feed shock processes, pH often exhibits a lag due to the system's alkalinity buffering effect. By the time operators detect problems through a significant drop in pH, a marked decrease in gas production, or abnormal effluent quality, the system has often already experienced considerable instability, resulting in a prolonged recovery period.

[0005] H2 is a crucial indicator of electron transfer and metabolic balance between the anaerobic fermentation hydrolysis and acidification stages, as well as acetogenesis and methanogenesis. When an imbalance occurs between the hydrogen and acetogenesis processes and methanogenesis, H2 concentration and its rate of change may appear abnormally earlier than significant pH changes. Therefore, integrating the dynamic response of H2 with parameters such as CH4, CO2, pH, ORP, TS, feed load, circulation flow rate, and equipment status helps to identify early risks of acidification and inhibited methanogenesis.

[0006] However, the H2 concentration varies widely in anaerobic processes, exhibiting an early trend signal in the low concentration range, or rapidly increasing during load shocks or acidification. Using a single-range H2 detection unit can easily lead to problems such as insufficient sensitivity for low concentration detection, exceeding the detection range for high concentrations, sensor contamination, or inadequate protection, affecting the reliability of using H2 signals for process status identification.

[0007] Therefore, there is an urgent need for an intelligent control system and method for the instability mechanism of anaerobic fermentation, so as to realize the transformation of anaerobic fermentation process from experience-based operation to data-driven closed-loop control. Summary of the Invention

[0008] The purpose of this invention is to provide an early warning and control system and method for anaerobic fermentation based on H2 dynamic response and multi-parameter fusion, which aims to achieve real-time transparent perception of the anaerobic fermentation operation status, early and reliable identification of key instability signals, fusion analysis of multi-source data, improved reliability of online H2 detection, and effective transformation of early warning results into engineering control actions.

[0009] To achieve the above objectives, this application provides the following technical solution: An early warning and control method for anaerobic fermentation based on H2 dynamic response and multi-parameter fusion includes the following steps: S1. Collect gas phase parameters, liquid phase parameters, solid phase parameters, and equipment status parameters during the anaerobic fermentation process; the gas phase parameters include at least H2, CH4, and CO2; S2. Connect the parameters to an edge gateway or anaerobic process data platform via an industrial data interface; S3. Perform protocol parsing, time synchronization, data quality marking, trend calculation, and feature extraction on multi-source data through edge gateways or data platforms; S4. Identify the operating status of anaerobic fermentation based on the combined changes in gas phase, liquid phase, solid phase, and equipment status parameters; S5. Generate graded early warning information based on the operational status identification results; S6. Output control suggestions based on the warning level, or generate control commands after confirmation by DCS / PLC; S7. Record the changes in operating parameters before and after regulation, and optimize the state identification threshold, parameter weights, and regulation strategies based on the regulation effect.

[0010] As a preferred embodiment: the gas phase parameters include one or more of biogas flow rate, CH4, CO2, O2, H2S, and H2; the liquid phase parameters include one or more of pH, ORP, temperature, liquid level, pressure, feed flow rate, and circulation flow rate; the solid phase parameters include one or more of slurry TS, biogas slurry TS, suspended solids concentration, sludge concentration, and VS; the equipment status parameters include one or more of the following: sampling pump status, gas sampling pretreatment unit status, condensate dehydration device status, filter status, positive pressure explosion-proof cabinet status, circulation pump status, valve status, instrument failure status, and communication status.

[0011] The H2 parameter is obtained by the low-range H2 detection unit and the high-range H2 detection unit. When the measurement value of the low-range detection unit reaches the preset switching condition or an over-range state occurs, the system automatically uses the data of the high-range detection unit to participate in the state identification and puts the low-range detection unit into the purging and purification state. When the measured value returns to the effective measurement range of the low-range detection unit after purging, the low-range detection unit re-participates in state recognition.

[0012] The trend calculation and feature extraction are performed based on a first time window and a second time window; the first time window is used to identify sudden shocks, gas path anomalies, or instrument anomalies; the second time window is used to identify trend instability; the features include one or more of the following: pH decrease rate, ORP offset, H2 increase slope, CH4 decrease slope, CO2 increase slope, CH4 / CO2 ratio decrease rate, biogas production change rate, TS change rate, feed load change rate, and circulation flow fluctuation amplitude.

[0013] The operational status identification includes the following types: (1) Early risk status of acidification: Identified by two or more of the following conditions: pH continues to decrease within the set time window but has not yet fallen below the alarm lower limit; ORP deviates from the normal operating range or shows continuous deviation; H2 concentration increases or the slope of H2 increases exceeds the set threshold; CH4 volume fraction decreases or the slope of CH4 decreases exceeds the set threshold; CO2 volume fraction increases or the CH4 / CO2 ratio decreases; biogas production, CH4 or pH do not show synchronous stable response after the feed load increases; TS increases and is accompanied by a decrease in circulation flow or increased fluctuation.

[0014] (2) Inhibited methanogenesis: Identified by two or more of the following conditions: H2 concentration continues to increase; CH4 volume fraction continues to decrease; biogas production per unit feed load decreases; pH decreases or falls below the set range; ORP deviates from the methanation stability range; H2S concentration increases; O2 concentration increases abnormally; feed load changes do not match the gas production response; CH4 yield decreases when the feed load does not decrease significantly.

[0015] (3) Feed shock state: Identified by two or more of the following conditions: feed flow rate or feed load increases rapidly in a short period of time; slurry TS increases; biogas flow rate, CH4 or CH4 / CO2 ratio decreases with lag; pH decrease rate increases; H2 concentration or H2 rise slope increases; circulation flow rate does not match feed load change.

[0016] (4) Abnormal state of mixing or circulation: Identified by two or more of the following conditions: circulation flow rate is lower than the set lower limit; circulation flow rate fluctuation exceeds the set threshold; abnormal operation of circulation pump; abnormal valve status; TS rises and gas phase gas production response decreases; abnormal changes in temperature or pressure inside the tank.

[0017] (5) Abnormal gas path, safety risk or instrument abnormality: Identify by one or more of the following conditions: abnormal increase in O2; H2S exceeding the safety threshold; abnormal biogas pressure; sudden change in biogas flow; blockage of gas sampling pretreatment unit; abnormal condensation dehydration device; abnormal filter status; abnormal positive pressure in explosion-proof cabinet; communication interruption; instrument exceeding limits, jumping or no change for a long time.

[0018] The graded early warning information includes five levels: normal, attention, warning, alarm, and protection. The normal level indicates that the key parameters and trends are in a stable range. The attention level indicates that a single or a few parameters show a trend change but have not yet formed a clear unstable state. The warning level indicates that a combination of multiple parameters indicates that there is a risk of early acidification, inhibited methanogenesis, or feed shock. The alarm level indicates that the key parameters exceed the process control threshold or safety threshold. The protection level indicates that the system has a serious process instability or safety risk, requiring the suspension of feed, reduction of load, activation of interlocks, or the implementation of protective measures.

[0019] The control suggestions or instructions include reducing the feed rate, extending the feed interval, segmented feeding, pausing feeding, increasing the circulation intensity, adjusting the sampling cycle, checking the gas sampling pretreatment unit, checking the biogas pipeline, arranging manual testing, triggering audible and visual alarms, pushing early warning information, and activating one or more of the following: explosion-proof protection or interlock protection. When the system has the conditions for temperature control, the control suggestions also include temperature control or heating / insulation strategy adjustment.

[0020] Feedback optimization includes: recording the results of each operation status identification, warning level, control suggestions, manual confirmation information, control execution information, and parameter changes after execution; when the slope of H2 increase decreases, CH4 volume fraction recovers, CH4 / CO2 ratio rebounds, pH decrease rate slows down, or biogas production recovers after execution, the control strategy is deemed effective, and relevant thresholds or weights are maintained or strengthened; when the above parameters do not improve or continue to deteriorate after execution, the warning level is raised or the relevant thresholds, weights, and strategy mapping relationships are corrected.

[0021] The present invention also provides an early warning and control system for anaerobic fermentation based on H2 dynamic response and multi-parameter fusion, comprising: a multi-parameter online sensing module for collecting gas phase, liquid phase, solid phase and equipment status parameters; The data access module is used to connect field instruments, DCS / PLC and equipment operation signals to the edge gateway or data platform; The data processing module is used to complete protocol parsing, time synchronization, local caching, anomaly detection, missing value handling, trend calculation, and feature extraction. The operating status identification module is used to identify the operating status of anaerobic fermentation based on H2 dynamic response and multi-parameter joint characteristics; The tiered early warning module is used to generate levels of normal, attention, warning, alarm, and protection. The intelligent control module is used to output control suggestions or control commands based on the operating status and warning level; The feedback optimization module is used to correct the state identification threshold, parameter weights, and control strategies based on the changes in parameters before and after regulation.

[0022] As a preferred embodiment, the anaerobic process data platform is used for centralized storage, real-time display, historical trend analysis, alarm recording, equipment status display, operation report generation, model interface management, and user permission management of anaerobic fermentation process data. It also displays the operation status, risk level, control suggestions, manual confirmation records, and control execution results according to different permissions.

[0023] As a preferred embodiment, the H2 parameter is obtained by combining a low-range H2 detection unit and a high-range H2 detection unit, and is configured with over-range switching and purging purification linkage logic.

[0024] Compared with the prior art, the present invention has at least the following beneficial effects: (1) Strong early identification capability: The dynamic response of H2 is introduced into the early identification of anaerobic fermentation instability and is integrated with parameters such as CH4, CO2, pH, ORP, TS, feed load and circulation status. It can identify the early risk of acidification and the inhibited state of methanogenesis before the pH becomes significantly unstable or the gas production decreases significantly.

[0025] (2) High reliability of H2 detection: Low-range and high-range H2 detection units are set up, and over-range switching, purging and purification and protection logic are provided to improve the reliability and continuity of online H2 detection in complex anaerobic engineering environments.

[0026] (3) Data quality is guaranteed: Time synchronization, data quality marking, outlier identification, trend calculation and feature extraction are performed through edge gateways or anaerobic process data platforms, which effectively reduces the interference of raw data noise, communication anomalies and instrument failures on the status identification results.

[0027] (4) Strong closed-loop management capability: It adopts a six-layer hierarchical architecture (perception layer → access layer → gateway layer → platform layer → control layer → execution layer), which transforms the operation status identification results into hierarchical early warning and engineering control suggestions, realizing a complete closed loop from data collection, status identification, intelligent decision-making to control execution.

[0028] (5) Adaptive optimization capability: By adjusting the changes in parameters before and after adjustment, feedback optimization can be carried out, which can gradually adapt to different anaerobic tank types, feed composition, operating load and seasonal conditions, thereby improving the stability of the system in long-term application.

[0029] (6) Wide range of applications: This invention is applicable to anaerobic fermentation systems for kitchen waste, wet waste, sludge, livestock and poultry manure and other wastes with high organic content, and has strong engineering promotion value. Attached Figure Description

[0030] Figure 1 This is a block diagram of the overall structure of the system in this application; Figure 2 This is a flowchart illustrating the method described in this application; Figure 3 This is a schematic diagram of the switching logic for the H2 dual-range detection unit.

[0031] Figure 1 As shown, the system comprises: a field sensing layer, a data access layer, an edge gateway layer, a platform application layer, a control system layer, and a control execution layer. The field sensing layer collects liquid phase parameters, solid phase parameters, gas phase parameters, and equipment status parameters. The data access layer accesses data through various industrial communication protocols. The edge gateway layer completes data access, protocol parsing, time synchronization, and feature extraction. The platform application layer identifies the operating status based on H2 dynamic response and multi-parameter combination judgment, generating five levels of graded early warnings: normal, watch out, warning, alarm, and protection. It outputs intelligent control suggestions and performs feedback optimization. The control system layer, through DCS / PLC / SCADA, links with actuators such as feed pumps, valves, and circulating pumps in the control execution layer to form a closed-loop control system. Detailed Implementation

[0032] To facilitate a clear understanding of the technical means, creative features, objectives, and effects of this application, the following description, in conjunction with specific illustrations, further elaborates on this application.

[0033] In this application, unless otherwise expressly specified and limited, the terms "installation," "connection," "joining," "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this application according to the specific circumstances.

[0034] In this application, unless otherwise expressly specified and limited, "above" or "below" the second feature can include direct contact between the first and second features, or contact between the first and second features through another feature between them. Furthermore, "above," "over," and "on top" of the second feature includes the first feature being directly above or diagonally above the second feature, or simply indicates that the first feature is at a higher horizontal level than the second feature. "Below," "below," and "under" the second feature includes the first feature being directly below or diagonally below the second feature, or simply indicates that the first feature is at a lower horizontal level than the second feature.

[0035] The following disclosure provides numerous different embodiments or examples for implementing various structures of the embodiments of this application. To simplify the disclosure of the embodiments of this application, specific examples of components and arrangements are described below. Of course, these are merely examples and are not intended to limit the scope of this application. Furthermore, reference numerals and / or reference letters may be repeated in different examples of the embodiments of this application; such repetition is for simplification and clarity and does not in itself indicate a relationship between the various embodiments and / or arrangements discussed. In addition, various specific examples of processes and materials are provided in the embodiments of this application, but those skilled in the art will recognize the application of other processes and / or the use of other materials.

[0036] like Figures 1 to 3 As shown, an early warning and control method for anaerobic fermentation based on H2 dynamic response and multi-parameter fusion includes the following steps: S1. Collect gas phase parameters, liquid phase parameters, solid phase parameters, and equipment status parameters during the anaerobic fermentation process; gas phase parameters should include at least H2, CH4, and CO2; S2. Connect the parameters to the edge gateway or anaerobic process data platform via the industrial data interface; S3. Perform protocol parsing, time synchronization, data quality marking, trend calculation, and feature extraction on multi-source data through edge gateways or data platforms; S4. Identify the operating status of anaerobic fermentation based on the combined changes in gas phase, liquid phase, solid phase, and equipment status parameters; S5. Generate graded early warning information based on the operational status identification results; S6. Output control suggestions based on the warning level, or generate control commands after confirmation by DCS / PLC; S7. Record the changes in operating parameters before and after regulation, and optimize the state identification threshold, parameter weights, and regulation strategy based on the regulation effect.

[0037] Specific gas phase parameters include one or more of biogas flow rate, CH4, CO2, O2, H2S, and H2; liquid phase parameters include one or more of pH, ORP, temperature, liquid level, pressure, feed flow rate, and circulation flow rate; solid phase parameters include one or more of slurry TS, biogas slurry TS, suspended solids concentration, sludge concentration, and VS; equipment status parameters include one or more of the following: sampling pump status, gas sampling pretreatment unit status, condensate removal device status, filter status, positive pressure explosion-proof cabinet status, circulation pump status, valve status, instrument failure status, and communication status.

[0038] The H2 parameter is obtained by the low-range H2 detection unit and the high-range H2 detection unit. When the measured value of the low-range detection unit reaches the preset switching condition or an over-range state occurs, the system automatically uses the data from the high-range detection unit to participate in the state identification and puts the low-range detection unit into the purging and purification state; when the measured value returns to the effective measurement range of the low-range detection unit after purging, the low-range detection unit participates in the state identification again.

[0039] Trend calculation and feature extraction are performed based on a first time window and a second time window. The first time window is used to identify sudden shocks, gas path anomalies, or instrument anomalies; the second time window is used to identify trend instability; features include one or more of the following: pH decrease rate, ORP offset, H2 increase slope, CH4 decrease slope, CO2 increase slope, CH4 / CO2 ratio decrease rate, biogas production change rate, TS change rate, feed load change rate, and circulation flow fluctuation amplitude.

[0040] Operational status identification includes the following types: (1) Early risk status of acidification: Identified by two or more of the following conditions: pH continues to decrease within the set time window but has not yet fallen below the alarm lower limit; ORP deviates from the normal operating range or shows continuous deviation; H2 concentration increases or the slope of H2 increases exceeds the set threshold; CH4 volume fraction decreases or the slope of CH4 decreases exceeds the set threshold; CO2 volume fraction increases or the CH4 / CO2 ratio decreases; biogas production, CH4 or pH do not show synchronous stable response after the feed load increases; TS increases and is accompanied by a decrease in circulation flow or increased fluctuation.

[0041] (2) Inhibited methanogenesis: Identified by two or more of the following conditions: H2 concentration continues to increase; CH4 volume fraction continues to decrease; biogas production per unit feed load decreases; pH decreases or falls below the set range; ORP deviates from the methanation stability range; H2S concentration increases; O2 concentration increases abnormally; feed load changes do not match the gas production response; CH4 yield decreases when the feed load does not decrease significantly.

[0042] (3) Feed shock state: Identified by two or more of the following conditions: feed flow rate or feed load increases rapidly in a short period of time; slurry TS increases; biogas flow rate, CH4 or CH4 / CO2 ratio decreases with lag; pH decrease rate increases; H2 concentration or H2 rise slope increases; circulation flow rate does not match feed load change.

[0043] (4) Abnormal state of mixing or circulation: Identified by two or more of the following conditions: circulation flow rate is lower than the set lower limit; circulation flow rate fluctuation exceeds the set threshold; abnormal operation of circulation pump; abnormal valve status; TS rises and gas phase gas production response decreases; abnormal changes in temperature or pressure inside the tank.

[0044] (5) Abnormal gas path, safety risk or instrument abnormality: Identify by one or more of the following conditions: abnormal increase in O2; H2S exceeding the safety threshold; abnormal biogas pressure; sudden change in biogas flow; blockage of gas sampling pretreatment unit; abnormal condensation dehydration device; abnormal filter status; abnormal positive pressure in explosion-proof cabinet; communication interruption; instrument exceeding limits, jumping or no change for a long time.

[0045] The tiered early warning information includes five levels: Normal, Attention, Warning, Alarm, and Protection. The Normal level indicates that key parameters and trends are within a stable range; the Attention level indicates that a single or a few parameters show trend changes but have not yet formed a clear unstable state; the Warning level indicates that multiple parameter combinations suggest the presence of early acidification, inhibited methanogenesis, or feed shock risks; the Alarm level indicates that key parameters exceed process control or safety thresholds; and the Protection level indicates that the system has serious process instability or safety risks, requiring suspension of feed, reduction of load, activation of interlocks, or implementation of protective measures.

[0046] Control suggestions or instructions include reducing feed rate, extending feed interval, segmented feeding, pausing feed, increasing circulation intensity, adjusting sampling cycle, checking gas sampling pretreatment unit, checking biogas pipeline, arranging manual testing, triggering audible and visual alarms, pushing early warning information, and activating one or more of explosion-proof protection or interlocking protection. When the system has the conditions for temperature control, control suggestions also include temperature control or heating / insulation strategy adjustment.

[0047] Feedback optimization includes: recording parameter changes before and after regulation, and determining the effectiveness of the regulation strategy based on one or more of the following: a decrease in the slope of H2 increase, recovery of CH4 volume fraction, recovery of CH4 / CO2 ratio, slowdown in pH decrease rate, or recovery of biogas production. The relevant thresholds or weights are maintained or strengthened. When the above parameters do not improve or continue to deteriorate after implementation, the warning level is raised or the mapping relationship between relevant thresholds, weights, and strategies is corrected.

[0048] This invention also provides an early warning and control system for anaerobic fermentation based on H2 dynamic response and multi-parameter fusion. For example... Figure 1 As shown, the system adopts a layered architecture, including: field perception layer, data access layer, edge gateway layer, platform application layer, control system layer, and control execution layer.

[0049] The field sensing layer collects liquid phase parameters (pH, ORP, temperature, liquid level, pressure, feed flow rate, circulation flow rate), solid phase parameters (slurry TS, biogas slurry TS, suspended solids concentration, etc.), gas phase parameters (biogas flow rate, H2, CH4, CO2, O2, H2S, etc.) and equipment status parameters (sampling pump status, pretreatment unit status, filter status, instrument fault status, communication status, etc.) through online instruments.

[0050] The data access layer uses one or more communication protocols, such as 4-20mA, RS485, Modbus, Industrial Ethernet, OPC UA, MQTT, 4G / 5G, and fiber optic, to connect the data collected by the field sensing layer to the edge gateway.

[0051] The edge gateway layer completes data access, protocol parsing, time synchronization, local caching, anomaly identification and marking, missing value handling, trend calculation, and feature extraction.

[0052] The platform application layer includes an anaerobic process data platform, which identifies the operating status based on H2 dynamic response and multi-parameter combination judgment, generates five levels of graded early warning: normal, attention, early warning, alarm, and protection, outputs intelligent control suggestions, and performs threshold adjustment, weight adjustment, and strategy optimization through the feedback optimization module.

[0053] The control system layer receives control commands issued by the platform application layer through DCS / PLC / SCADA, and generates control commands after manual confirmation.

[0054] The control and execution layer includes actuators such as feed pumps and valves, circulation pumps and valves, and temperature control units. Based on control commands, it performs actions such as feed adjustment, circulation adjustment, temperature control, sampling / analysis adjustment, and alarm linkage, forming a complete closed loop from data acquisition to control execution.

[0055] The anaerobic process data platform is used for centralized storage, real-time display, historical trend analysis, alarm recording, equipment status display, operation report generation, model interface management, and user permission management of anaerobic fermentation process data. It displays operating status, risk level, control suggestions, manual confirmation records, and control execution results according to different user permissions. H2 parameters are obtained by a combination of low-range and high-range H2 detection units, and are configured with over-range switching and purging / purging linkage logic. Specific Implementation

[0056] This embodiment provides an early warning and control system for anaerobic fermentation based on H2 dynamic response and multi-parameter fusion, which is applied to the anaerobic fermentation tank of a food waste treatment plant.

[0057] System deployment: such as Figure 1 As shown, this system is deployed using a layered architecture.

[0058] The on-site sensing layer is equipped with a biogas component analyzer (CH4, CO2, H2, O2, H2S), pH meter, ORP meter, temperature sensor, liquid level sensor, pressure sensor, feed flow meter, circulation flow meter, TS online monitor, etc., and is equipped with dual H2 detection units with low range (0-1000ppm) and high range (0-2%), and is matched with an automatic purging and purification device.

[0059] The data access layer connects field instrument data to the edge gateway via the Modbus TCP protocol.

[0060] The edge gateway layer is deployed on edge gateway devices to complete data access, protocol parsing, time synchronization, anomaly identification, missing value handling, trend calculation, and feature extraction.

[0061] The platform application layer deploys an anaerobic process data platform, which identifies the operating status based on H2 dynamic response and multi-parameter combination judgment, generates graded early warnings, outputs intelligent control suggestions, and performs feedback optimization.

[0062] The control system layer receives control commands from the platform application layer via DCS / PLC, and after manual confirmation, sends them to the control execution layer.

[0063] The control and execution layer includes actuators such as feed pumps and valves, circulation pumps and valves.

[0064] Operation process: The system continuously collects gas phase parameters (CH4, CO2, H2, O2, H2S, biogas flow rate), liquid phase parameters (pH, ORP, temperature, liquid level, feed flow rate, circulation flow rate), solid phase parameters (slurry TS), and equipment status parameters during the anaerobic fermentation process.

[0065] The edge gateway performs protocol parsing and time synchronization on the data. Based on the first time window (5 minutes), it identifies sudden shocks and instrument anomalies. Based on the second time window (2 hours), it calculates trend characteristics such as pH decrease rate, H2 increase slope, and CH4 decrease slope.

[0066] When the measured value of the low-range H2 detection unit reaches the preset switching condition or an over-range state occurs, the system automatically switches to use the data from the high-range detection unit while simultaneously purging the low-range unit with nitrogen. When the measured value returns to the effective range of the low-range unit after purging, the low-range detection unit re-participates in the state identification.

[0067] The operation status identification module makes judgments based on multiple parameters: when the H2 rise rate exceeds 0.5 ppm / min, the pH decreases by 0.15 within 2 hours, and the CH4 decrease rate exceeds 0.1% / min, it is judged as "early acidification risk" and an early warning level is generated; after the early warning level is triggered, the intelligent control module outputs control suggestions such as "reduce the feed rate by 20%, extend the feed interval by 2 hours, and arrange manual testing of VFA and alkalinity"; the control suggestions are automatically executed after being confirmed by DCS / PLC.

[0068] The feedback optimization module records the parameter changes before and after regulation: after regulation, the H2 rise slope decreased to below 0.2 ppm / min, the CH4 volume fraction returned to the normal range, the regulation strategy was determined to be effective, and the relevant thresholds and weights were maintained and strengthened.

[0069] Execution result: The system operated continuously for 6 months, identifying 8 early acidification risks, 3 methanogenesis inhibition risks, and 5 feed shock risks. Each time, an early warning was issued 4-12 hours before a significant pH drop, and the system returned to stable operation within 24 hours after adjustments. No significant decrease in biogas production or system shutdown due to instability occurred. Specific Implementation

[0070] The difference between this embodiment and Embodiment 1 is that the object of this embodiment is a municipal sludge anaerobic fermentation system.

[0071] Because anaerobic fermentation of sludge results in higher solids content and higher ammonia nitrogen concentration, the system has a greater need for monitoring H2S and ammonia nitrogen inhibition. This embodiment adds online monitoring of H2S concentration and ammonia nitrogen in parameter acquisition and adds a "high ammonia nitrogen inhibition risk" identification condition to the operating status identification module.

[0072] During the six months of operation, the system successfully identified two instances of inhibited methanogenesis caused by ammonia nitrogen accumulation. The control recommendations included "suspending feed, increasing circulation intensity, and supplementing trace elements." After the control measures were implemented, the system returned to normal operation.

[0073] The foregoing has shown and described the basic principles, main features, and advantages of this application. Those skilled in the art should understand that this application is not limited to the above embodiments, and various changes and modifications can be made without departing from the spirit and scope of this application; all such changes and modifications fall within the scope of the claims. The scope of protection of this application is defined by the appended claims and their equivalents.

Claims

1. A method for early warning and regulation of anaerobic fermentation based on H2 dynamic response and multi-parameter fusion, characterized in that, Includes the following steps: S1. Collect gas phase parameters, liquid phase parameters, solid phase parameters, and equipment status parameters during the anaerobic fermentation process; the gas phase parameters include at least H2, CH4, and CO2; S2. Connect the parameters to an edge gateway or anaerobic process data platform via an industrial data interface; S3. Perform protocol parsing, time synchronization, data quality marking, trend calculation, and feature extraction on multi-source data through edge gateways or data platforms; S4. Identify the operating status of anaerobic fermentation based on the combined changes in gas phase, liquid phase, solid phase, and equipment status parameters; S5. Generate graded early warning information based on the operational status identification results; S6. Output control suggestions based on the warning level, or generate control commands after confirmation by DCS / PLC; S7. Record the changes in operating parameters before and after regulation, and optimize the state identification threshold, parameter weights, and regulation strategy based on the regulation effect.

2. The method for early warning and regulation of anaerobic fermentation based on H2 dynamic response and multi-parameter fusion as described in claim 1, characterized in that: The gas phase parameters include one or more of biogas flow rate, CH4, CO2, O2, H2S, and H2; the liquid phase parameters include one or more of pH, ORP, temperature, liquid level, pressure, feed flow rate, and circulation flow rate; the solid phase parameters include one or more of slurry TS, biogas slurry TS, suspended solids concentration, sludge concentration, and VS; the equipment status parameters include one or more of the following: sampling pump status, gas sampling pretreatment unit status, condensate dehydration device status, filter status, positive pressure explosion-proof cabinet status, circulation pump status, valve status, instrument failure status, and communication status.

3. The method for early warning and regulation of anaerobic fermentation based on H2 dynamic response and multi-parameter fusion as described in claim 1, characterized in that: The H2 parameter is obtained by the low-range H2 detection unit and the high-range H2 detection unit; When the measured value of the low-range detection unit reaches the preset switching condition or an over-range state occurs, the system automatically uses the data from the high-range detection unit to participate in the state identification and puts the low-range detection unit into the purging and purification state. When the measured value returns to the effective measurement range of the low-range detection unit after purging, the low-range detection unit re-participates in state recognition.

4. The method for early warning and regulation of anaerobic fermentation based on H2 dynamic response and multi-parameter fusion as described in claim 1, characterized in that: The trend calculation and feature extraction are performed based on a first time window and a second time window; The first time window is used to identify sudden shocks, gas path anomalies, or instrument anomalies; the second time window is used to identify trend instability; the features include one or more of the following: pH decrease rate, ORP offset, H2 increase slope, CH4 decrease slope, CO2 increase slope, CH4 / CO2 ratio decrease rate, biogas production change rate, TS change rate, feed load change rate, and circulation flow fluctuation amplitude.

5. The method for early warning and control of anaerobic fermentation based on H2 dynamic response and multi-parameter fusion as described in claim 1, characterized in that: Early-stage acidification risk status is identified by two or more of the following criteria: pH continues to decrease within the set time window but has not yet fallen below the alarm lower limit; ORP deviates from the normal operating range or shows continuous deviation; H2 concentration increases or the slope of H2 increase exceeds the set threshold; CH4 volume fraction decreases or the slope of CH4 decrease exceeds the set threshold; CO2 volume fraction increases or the CH4 / CO2 ratio decreases. After the feed load was increased, biogas production, CH4 or pH did not show a synchronous stable response; TS increases and is accompanied by a decrease in circulating flow or increased fluctuations.

6. The method for early warning and regulation of anaerobic fermentation based on H2 dynamic response and multi-parameter fusion as described in claim 1, characterized in that: An inhibited methanogenesis state is identified by two or more of the following conditions: H2 concentration continues to rise; CH4 volume fraction continues to fall; biogas production per unit feed load decreases; pH decreases or falls below the set range; ORP deviates from the methanation stability range; H2S concentration increases; O2 concentration increases abnormally; feed load changes do not match gas production response; CH4 yield decreases when feed load does not decrease significantly.

7. The method for early warning and regulation of anaerobic fermentation based on H2 dynamic response and multi-parameter fusion as described in claim 1, characterized in that: Feed impact condition is identified by two or more of the following conditions: The feed flow rate or feed load increases rapidly in a short period of time; the slurry TS increases; the biogas flow rate, CH4 or CH4 / CO2 ratio decreases with lag; the pH decrease rate increases; the H2 concentration or H2 rise slope increases; and the circulation flow rate does not match the changes in feed load.

8. The method for early warning and regulation of anaerobic fermentation based on H2 dynamic response and multi-parameter fusion as described in claim 1, characterized in that: Mixed or cyclic abnormal states are identified by two or more of the following criteria: The circulating flow rate is lower than the set lower limit; the fluctuation range of the circulating flow rate exceeds the set threshold; the circulating pump is in abnormal operation; the valve is in abnormal condition; TS rises and the gas phase gas production response decreases; the temperature or pressure change inside the tank is abnormal.

9. The method for early warning and regulation of anaerobic fermentation based on H2 dynamic response and multi-parameter fusion as described in claim 1, characterized in that: Gas path abnormalities, safety risks, or instrument malfunctions are identified by one or more of the following conditions: O2 abnormally high; H2S exceeding the safety threshold; abnormal biogas pressure; sudden change in biogas flow rate; blockage of the gas sampling and pretreatment unit; malfunction of the condensate removal device; Filter malfunction; abnormal positive pressure in explosion-proof cabinet; communication interruption; instrument exceeding limits, fluctuating, or remaining unchanged for an extended period.

10. The method for early warning and control of anaerobic fermentation based on H2 dynamic response and multi-parameter fusion according to claim 1, characterized in that: The tiered early warning information includes five levels: normal, attention, warning, alarm, and protection. The normal level indicates that key parameters and trends are within a stable range; the attention level indicates that a single or a few parameters show trend changes but have not yet formed a clear unstable state; the warning level indicates that multiple parameter combinations indicate the presence of early acidification, suppressed methanogenesis, or feed shock risks; the alarm level indicates that key parameters exceed process control thresholds or safety thresholds; and the protection level indicates that the system has serious process instability or safety risks, requiring the suspension of feed, reduction of load, activation of interlocks, or the implementation of protective measures.

11. The method for early warning and regulation of anaerobic fermentation based on H2 dynamic response and multi-parameter fusion as described in claim 1, characterized in that: The control suggestions or instructions include reducing the feed rate, extending the feed interval, segmented feeding, pausing feeding, increasing the circulation intensity, adjusting the sampling cycle, checking the gas sampling pretreatment unit, checking the biogas pipeline, arranging manual testing, triggering audible and visual alarms, pushing early warning information, and activating one or more of the following: explosion-proof protection or interlock protection. When the system has the conditions for temperature control, the control suggestions also include temperature control or heating / insulation strategy adjustment.

12. The method for early warning and regulation of anaerobic fermentation based on H2 dynamic response and multi-parameter fusion according to claim 1, characterized in that: Feedback optimization includes: Record the results of each operation status identification, warning level, control suggestions, manual confirmation information, control execution information, and parameter changes after execution; When the slope of H2 increase decreases, the volume fraction of CH4 recovers, the CH4 / CO2 ratio rebounds, the rate of pH decrease slows down, or biogas production recovers after execution, the control strategy is deemed effective, and the relevant thresholds or weights are maintained or strengthened. If the above parameters do not improve or continue to deteriorate after execution, the warning level will be raised or the relevant thresholds, weights and policy mapping relationships will be corrected.

13. An early warning and control system for anaerobic fermentation based on H2 dynamic response and multi-parameter fusion, characterized in that, include: A multi-parameter online sensing module is used to collect gas phase, liquid phase, solid phase, and equipment status parameters; The data access module is used to connect field instruments, DCS / PLC and equipment operation signals to the edge gateway or data platform; The data processing module is used to complete protocol parsing, time synchronization, local caching, anomaly detection, missing value handling, trend calculation, and feature extraction. The operating status identification module is used to identify the operating status of anaerobic fermentation based on H2 dynamic response and multi-parameter joint characteristics; The tiered early warning module is used to generate levels of normal, attention, warning, alarm, and protection. The intelligent control module is used to output control suggestions or control commands based on the operating status and warning level; The feedback optimization module is used to correct the state identification threshold, parameter weights, and control strategies based on the changes in parameters before and after regulation.

14. The anaerobic fermentation early warning and control system based on H2 dynamic response and multi-parameter fusion as described in claim 13, characterized in that: The anaerobic process data platform is used for centralized storage, real-time display, historical trend analysis, alarm recording, equipment status display, operation report generation, model interface management, and user permission management of anaerobic fermentation process data. It also displays the operation status, risk level, control suggestions, manual confirmation records, and control execution results according to different permissions.

15. The anaerobic fermentation early warning and control system based on H2 dynamic response and multi-parameter fusion according to claim 13, characterized in that: The H2 parameter is obtained by combining a low-range H2 detection unit and a high-range H2 detection unit, and is configured with over-range switching and purging purification linkage logic.

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