CN-121981380-A - Biogas purification equipment operation state monitoring method and system based on Internet of things

CN121981380ACN 121981380 ACN121981380 ACN 121981380ACN-121981380-A

Abstract

The invention discloses a method and a system for monitoring the running state of biogas purification equipment based on the Internet of things, and belongs to the technical field of biogas purification. The method comprises the steps of uniformly coding purifying equipment, recording cold start time and residual influence purifying gas quantity, prolonging the cold start time if a threshold value is exceeded, numbering a purifying task, collecting gas quantity data, calculating a difference value, generating a training sample, building a delay time prediction model, substituting the current task data to predict the delay time and control the cold start, recording cold start and stop time nodes, calculating the shutdown feasibility to control the running of the equipment, and injecting the purifying gas until the residual gas quantity reaches the standard. According to the invention, full-flow intelligent monitoring is realized through the Internet of things, the equipment operation is accurately regulated and controlled by depending on the prediction model and the shutdown feasibility evaluation, the purification effect and the operation efficiency are improved, the energy consumption is reduced, and the method is suitable for various marsh gas purification scenes.

Inventors

ZHANG JIANXIA
Zou Zengzhu
ZHANG GUIDE
XUE WENBO
LI WEIMIN
CHEN MUZHI
ZHANG JIE
LI XIN
ZHOU ZHIJUN
LIU RONGLIN

Assignees

南京都乐制冷设备有限公司

Dates

Publication Date: 20260505
Application Date: 20251231

Claims (10)

1. The method for monitoring the operation state of the biogas purification equipment based on the Internet of things is characterized by comprising the following steps of: Step S1, uniformly coding and archiving all purifying equipment in the biogas purifying process flow, recording the duration from cold start to stable operation of the equipment and the residual influence purifying gas amount in the equipment, and if the residual gas amount exceeds a preset residual amount threshold value, prolonging the cold start duration of the equipment and recording the prolonged duration; Step S2, uniformly numbering biogas purification tasks, calculating the difference value of the initial purified gas amount and the residual influence purified gas amount in the process of executing the tasks by the acquisition equipment, generating a training sample based on cold start time length, extension time length and gas difference value, and establishing a delay time length prediction model through data fitting; S3, acquiring the cold start time length of the equipment for executing the purification task and a corresponding gas quantity difference value, substituting the cold start time length and the corresponding gas quantity difference value into a delay time length prediction model to obtain a predicted delay time length, and performing extension control on the cold start process of the equipment according to the predicted delay time length; And S4, recording a starting point of cold starting of the equipment and an extended end time node, calculating the shutdown feasibility of the equipment, judging whether the equipment is shutdown according to the shutdown feasibility, and if the shutdown feasibility is not up to a preset feasibility threshold, controlling the equipment to continue to operate until the residual quantity of the influence purified gas in the equipment does not exceed the preset residual quantity threshold, and injecting the purified gas.
2. The method for monitoring the operation state of the biogas purification equipment based on the internet of things according to claim 1, wherein the specific implementation process of the step S1 comprises the following steps: The method comprises the steps of uniformly coding each purifying device in a biogas purifying process flow, recording the cold start duration of a purifying device in a period of reaching a steady operation state before injecting purified gas in the process of executing a biogas purifying task, and collecting the residual influence purified gas quantity of the biogas purifying task executed in the purifying device for the last time after the cold start reaches the steady operation state; If the residual influence purified gas quantity in any purifying equipment exceeds a preset residual quantity threshold value, performing cold start duration extension control on the purifying equipment after cold start and reaching a stable running state and before injecting purified gas, and recording the extension duration after the residual influence purified gas quantity exceeds the preset residual quantity threshold value.
3. The method for monitoring the operation state of the biogas purification equipment based on the internet of things according to claim 2, wherein the specific implementation process of the step S2 comprises the following steps: The biogas purification tasks are numbered uniformly, and the cold start time length of the a purification equipment when the biogas purification tasks are executed for the ith time is recorded as the cold start time length of the a purification equipment The extension time of the a-th purifying equipment when the methane purifying task is executed for the i-th time is recorded as The internal influence purge gas amount of the a-th purge apparatus when the biogas purge task is performed the i-th time is recorded as Collecting initial purified gas amount in a purifying device a before the ith biogas purifying task is executed And the initial purified gas amount is larger than the influence purified gas amount, and the initial purified gas amount is obtained And influence the amount of purge gas Difference in gas quantity ; Generating a simulation model training sample through the numbering index of the biogas purification task Performing data fitting on the training sample of the simulation model, and establishing a delay time length prediction model of the running state of the biogas purifying equipment Wherein x represents a first independent variable in the delay time length prediction model, and the first independent variable corresponds to the cold start time length Y represents a second independent variable in the delay time length prediction model, and the second independent variable corresponds to a gas quantity difference value , 、 And Fitting coefficients are respectively adopted; ; wherein I is the number of the biogas purification task which is executed before the current biogas purification task to be executed.
4. The method for monitoring the operation state of the biogas purification equipment based on the internet of things according to claim 3, wherein the specific implementation process of the step S3 comprises the following steps: acquiring cold start time length of a purifying device a of biogas purifying task to be executed currently And the difference between the gas quantity of the current biogas purification task to be executed and the gas quantity of the a-th purification equipment which executes the biogas purification task in the previous time Order-making , Substituting the time delay time length prediction model to predict the time delay time length of the a-th purifying equipment currently carrying out the biogas purifying task ; And (3) performing cold start duration extension control on the a-th purifying equipment currently to be subjected to biogas purifying task based on the predicted a-th purifying equipment delay duration.
5. The method for monitoring the operation state of the biogas purification equipment based on the internet of things according to claim 4, wherein the specific implementation process of the step S4 comprises the following steps: Acquiring cold start starting point time node of a purifying equipment Acquiring cold start duration extension control of a purification equipment a Post cold start endpoint time node ; Assessment of a-th purification apparatus for Cold Start duration extension control Post shutdown feasibility Wherein A represents the total number of purifying devices, F is a timing function, Representing the maximum endpoint time node among the cold start endpoint time nodes, Representing the smallest of the cold start time nodes, Node for indicating cold start end time And maximum endpoint time node The duration of the interval between them, Representing a minimum origin time node And maximum endpoint time node Interval duration of the interval; if the machine is out of operation If the cold start duration of the purification equipment is greater than or equal to the preset shutdown feasibility threshold value, controlling the purification equipment a to perform cold start duration extension control After stopping, if stopping the machine If the cold start duration of the purification equipment is smaller than the preset shutdown feasibility threshold value, controlling the a purification equipment to perform cold start duration extension control And continuing to operate until the residual influencing purified gas amount in any purifying equipment does not exceed the preset residual amount threshold value, and injecting purified gas.
6. A biogas purification equipment operation state monitoring system based on the internet of things for executing the biogas purification equipment operation state monitoring method based on the internet of things according to any one of claims 1 to 5, wherein the system comprises an equipment coding and basic data acquisition module, a prediction model construction module, a delay time length prediction and cold start control module and a shutdown feasibility assessment and operation control module; the equipment coding and basic data acquisition module is used for uniformly coding and archiving the purifying equipment, recording cold start related data and residual influence purified gas quantity, and prolonging cold start time when the residual quantity exceeds a threshold value; the prediction model construction module is used for managing the number of the purification task, collecting related gas quantity data, calculating a difference value, generating a training sample and building a delay time length prediction model; The delay time length prediction and cold start control module is used for acquiring equipment related data of a current task, obtaining delay time length through a prediction model and controlling cold start time length; and the shutdown feasibility evaluation and operation control module is used for acquiring cold start-stop time nodes, calculating the shutdown feasibility and controlling the running state of the equipment until the residual gas amount reaches the standard, and injecting the purified gas.
7. The system for monitoring the operation state of the biogas purification equipment based on the Internet of things according to claim 6, wherein the equipment coding and basic data acquisition module comprises an equipment coding gear unit, a cold start data recording unit and a residual gas amount detection and extension control unit; the equipment coding and gear entering unit is used for uniformly coding all purifying equipment in the biogas purifying process flow and establishing files; The cold start data recording unit is used for recording the cold start time length from the cold start to the stable operation of the equipment; the residual gas quantity detection and extension control unit is used for detecting the residual influence purified gas quantity in the equipment, and if the residual gas quantity exceeds a preset residual quantity threshold value, the cold start duration of the equipment is prolonged, and the prolonged duration is recorded.
8. The system for monitoring the operation state of the biogas purification equipment based on the Internet of things according to claim 6, wherein the prediction model construction module comprises a task numbering unit, a gas amount data acquisition unit, a training sample generation unit and a prediction model establishment unit; the task numbering unit is used for uniformly numbering the biogas purification tasks executed each time; The gas quantity data acquisition unit is used for acquiring initial purified gas quantity and residual influence purified gas quantity in the equipment and calculating a gas quantity difference value of the initial purified gas quantity and the residual influence purified gas quantity; The training sample generation unit is used for indexing through task numbers and generating a simulation model training sample by combining cold start duration, extension duration and gas quantity difference values of equipment; the prediction model building unit is used for carrying out data fitting on the training samples and building a delay time length prediction model of the running state of the biogas purification equipment.
9. The system for monitoring the operation state of the biogas purification equipment based on the internet of things according to claim 6, wherein the delay time length prediction and cold start control module comprises a current data acquisition unit, a delay time length prediction unit and a cold start time length control unit; the current data acquisition unit is used for acquiring the cold start time length and the corresponding gas quantity difference value of each device in the current purification task to be executed; The delay time length prediction unit is used for substituting the acquired current data into a delay time length prediction model to obtain the cold start delay time length corresponding to each device; The cold start duration control unit is used for performing extension control on the cold start duration of the current equipment according to the predicted delay duration.
10. The biogas purification equipment operation state monitoring system based on the internet of things according to claim 6, wherein the shutdown feasibility evaluation and operation control module comprises a time node acquisition unit, a shutdown feasibility calculation unit and an operation state control unit; the time node acquisition unit is used for acquiring a starting point time node of cold start of each device and an end point time node after cold start extension; The shutdown feasibility calculating unit is used for calculating the shutdown feasibility of the single equipment according to the minimum time of the cold start starting points and the maximum time of the end points of all the equipment; the operation state control unit is used for judging whether the equipment is stopped according to the stopping feasibility, if the stopping feasibility reaches a preset threshold, controlling the equipment to stop, and if the stopping feasibility does not reach the preset threshold, controlling the equipment to continue to operate until the residual quantity of the influence purified gas in all the equipment does not exceed the preset threshold, and controlling the injection of the purified gas.

Description

Biogas purification equipment operation state monitoring method and system based on Internet of things Technical Field The invention relates to the technical field of biogas purification, in particular to a method and a system for monitoring the running state of biogas purification equipment based on the Internet of things. Background Biogas is used as clean renewable energy, is widely applied in the fields of industrial production, agricultural cultivation and civil use, and the purification effect directly influences the energy utilization efficiency and the environmental safety. The biogas purification process needs to cooperatively operate through a plurality of purification devices to remove impurity gases such as hydrogen sulfide, carbon dioxide and the like, and the stability and the regulation scientificity of the running state of the devices are the core for guaranteeing the purification quality. However, the existing operation state monitoring technology of the biogas purification equipment has a plurality of problems to be solved urgently: Firstly, the equipment management lacks unified specification, and a plurality of equipment does not have a standardized coding system, so that equipment operation data and task execution records cannot be accurately associated, historical data is difficult to trace, and targeted state regulation and control are difficult to realize. Secondly, setting cold start duration depends on manual experience, the residual of unbound equipment affects the dynamic adjustment of the purified gas quantity, when the residual gas quantity exceeds the standard, the fixed cold start duration cannot thoroughly remove the residual gas, so that the subsequent purification effect is reduced, and if the duration is prolonged blindly, the energy waste and the efficiency are reduced. Thirdly, a scientific delay time prediction mechanism is lacking, a correlation model of cold start time, gas quantity difference and delay time is not established in the prior art, the required extension time cannot be accurately predicted according to actual working conditions, and the regulation hysteresis is strong. Fourth, the shutdown judgment standard is single, whether shutdown is carried out is judged only according to the operation time length or the residual gas quantity of a single device, the time synchronism of the cooperative operation of multiple devices is not considered, and the problems that partial devices are stopped too early to cause incomplete purification or excessive operation to increase energy consumption are easily caused. Fifthly, the technology integration of the Internet of things is insufficient, the links of data acquisition, analysis and equipment control are mutually split, the real-time monitoring and intelligent regulation and control of the running state cannot be realized, the whole intelligent level is low, and the large-scale and fine biogas purification requirements are difficult to adapt. These problems lead to the difficulty in balancing the purification effect, the operation efficiency and the energy consumption control of the existing monitoring technology, and restrict the high-quality development of the biogas purification industry. Therefore, there is a need for an internet of things monitoring method and system capable of realizing accurate management of equipment, scientific prediction of time delay duration and intelligent evaluation of shutdown state, so as to solve the defects of the prior art. Disclosure of Invention The invention aims to provide a biogas purification equipment running state monitoring method and system based on the Internet of things, which are used for solving the problems in the background technology, and the invention constructs a closed loop monitoring system of data acquisition, model prediction, intelligent regulation and control and effect evaluation based on the Internet of things technology, and the core principle is as follows: Through unified coding of equipment and task numbers, a unique association of 'equipment-task-data' is established, accurate tracing and efficient management of operation data are realized, and a reliable data base is provided for subsequent analysis (step S1); Generating a training sample based on historical operation data (cold start time, extension time and gas quantity difference), constructing a multi-element linear delay time prediction model through data fitting, quantifying the association relation between the cold start time, the gas quantity difference and the delay time, and realizing accurate prediction of the delay time (step S2); introducing a shutdown feasibility evaluation index, combining a multi-device cold start-up time node, judging the shutdown rationality of the device from a global view, and balancing the single-device running state and the multi-device cooperative efficiency (step S3); and integrating all modules by means of the Internet of things technology, realizing data r