CN-122022124-A - Accurate pyrolysis regulation and control and product analysis system and method for urban biomass solid waste

CN122022124ACN 122022124 ACN122022124 ACN 122022124ACN-122022124-A

Abstract

The invention discloses a system and a method for precise pyrolysis regulation and control and product analysis of urban biomass solid waste, and relates to the technical field of solid waste treatment. The method comprises a material characteristic prediction module, a process pyrolysis regulation and control module and a product collection module, wherein the material characteristic prediction module is used for preprocessing urban biomass solid waste, then carrying out pyrolysis behavior characteristic prediction through a machine learning prediction model to obtain a corresponding pyrolysis behavior characteristic report, the process pyrolysis regulation and control module is used for constructing characteristic target vectors according to the pyrolysis behavior characteristic report and a user product quality target, obtaining a corresponding candidate process track through a deep learning prediction model, simultaneously carrying out real-time adjustment on the candidate process track according to product quality data in the pyrolysis reaction treatment process, and collecting and analyzing products obtained by carrying out pyrolysis reaction according to the candidate process track. The method can solve the problem of unstable product quality caused by raw material fluctuation in the traditional method, and improves the reliability of pyrolysis behavior prediction.

Inventors

DENG SHULI
ZHANG TINGTING
CHEN ZHICHENG
CHEN YU
ZHAO YANG

Assignees

新疆能源科技创新研发中心有限责任公司

Dates

Publication Date: 20260512
Application Date: 20251229

Claims (10)

1. Accurate pyrolysis regulation and control and result analysis system to urban biomass solid waste, characterized by comprising: the material characteristic prediction module is used for predicting pyrolysis behavior characteristics through a machine learning prediction model after preprocessing urban biomass solid waste, and obtaining a corresponding pyrolysis behavior characteristic report; the process pyrolysis regulation and control module constructs a characteristic target vector according to the pyrolysis behavior characteristic report and a user product quality target, takes the characteristic target vector as the input of a deep learning prediction model, outputs and acquires a corresponding candidate process track, monitors and acquires product quality data in the pyrolysis reaction treatment process, and adjusts the candidate process track in real time according to a comparison result between the product quality data and the user product quality target; And the product collection module is used for collecting and analyzing the products obtained after the pyrolysis reaction according to the candidate process track.
2. The system for precise pyrolysis regulation and product analysis of municipal solid waste according to claim 1, wherein the obtaining of the corresponding pyrolysis behavior characteristic report comprises: SA1, physical pretreatment, namely crushing, drying and homogenizing urban biomass solid waste to obtain pretreated urban biomass solid waste; SA2, characteristic identification, namely scanning the pretreated urban biomass solid waste through a near infrared spectrum probe to obtain a biomass solid waste spectrum signal, taking the biomass solid waste spectrum signal and a spectrum fingerprint library as input based on a principal component analysis model, and outputting and obtaining a corresponding characteristic probability distribution result; And SA3, predicting, namely determining at least one corresponding material quantitative correction model according to the characteristic probability distribution result, taking the biomass solid waste spectrum signal as the input of each material quantitative correction model, outputting and obtaining a corresponding characteristic value, taking the characteristic value as the input of a machine learning prediction model, outputting and obtaining a corresponding prediction index, and carrying out weighted fusion on the prediction index corresponding to each material quantitative correction model according to the similarity probability corresponding to the characteristic probability distribution result to obtain a corresponding pyrolysis behavior characteristic prediction report.
3. The system for precise pyrolysis regulation and product analysis of municipal solid waste according to claim 2, wherein the pretreated municipal solid waste is obtained by: Crushing treatment, namely sequentially conveying urban biomass solid waste to be treated into a coarse crusher and a fine crusher through a conveying mechanism to perform crushing treatment, and obtaining final waste fragments; SA1.2, drying the final waste fragments through a roller dryer and a hot blast furnace which are communicated with each other; and SA1.3, homogenizing, namely layering and spreading the dried final waste fragments in a homogenizing bin, and performing shearing movement to obtain pretreated municipal biomass solid waste.
4. The system for precise pyrolysis regulation and product analysis of municipal solid waste according to claim 2, wherein the spectral fingerprint library is constructed and obtained according to known spectral data corresponding to a plurality of different biomass solid waste, and the corresponding similar reference spectral signals and similar probabilities are determined by comparing the biomass solid waste spectral signals with a plurality of reference spectral signals in the spectral fingerprint library based on the principal component analysis model.
5. The system for precise pyrolysis regulation and product analysis of municipal solid waste according to claim 1, wherein the candidate process trajectory is adjusted in real time, comprising: the method comprises the steps of SB1, track determination, namely taking a pyrolysis behavior feature prediction report and a feature target vector formed by a user product quality target as input of a deep learning prediction model, outputting and obtaining a plurality of corresponding different candidate process tracks, simultaneously carrying out simulation deduction on all the candidate process tracks, and determining a corresponding optimal candidate process track according to a simulation deduction result; SB2, track monitoring, namely analyzing the optimal candidate process track through a distributed control system to obtain corresponding execution instructions, driving different execution mechanisms in the pyrolysis reactor according to the execution instructions, and acquiring detection data in the pyrolysis reactor in the driving process of the execution mechanisms, wherein the detection data comprises temperature data, pressure data and gas component content data; And SB3, track adjustment, namely comparing the detection data with a process predicted value in the optimal candidate process track to obtain corresponding real-time data deviation, and simultaneously comparing the real-time data deviation with a preset track threshold value to determine the adjustment state of the candidate process track, wherein the adjustment state comprises the following specific steps: And when the real-time data deviation is larger than a preset track threshold, repeating the step SB1 and the step SB2, and adjusting the candidate process track until the real-time data deviation is not larger than the preset track threshold, otherwise, not adjusting the candidate process track.
6. The system for precise pyrolysis control and product analysis of municipal solid waste according to claim 5, wherein determining the corresponding optimal candidate process trajectory comprises: SB1.1, data prediction, namely determining a corresponding objective function according to a set user product quality target, splicing and combining the objective function and a final prediction index corresponding to a pyrolysis behavior feature prediction report to obtain a corresponding feature target vector, and simultaneously taking the feature target vector as the input of a deep learning prediction model to output and obtain a plurality of corresponding candidate process tracks; SB1.2, simulation determination, namely, performing simulation deduction on each candidate process track through a set digital twin body to obtain a corresponding simulation result, and determining a maximum simulation result from the simulation results corresponding to each candidate process track, wherein the candidate process track corresponding to the maximum simulation result is the optimal candidate process track.
7. The system for precise pyrolysis regulation and product analysis of urban biomass solid waste according to claim 5, wherein the constraint conditions set in the track prediction process of the deep learning prediction model comprise safety constraint, process constraint, environment-friendly constraint and product quality constraint.
8. The system for precise pyrolysis regulation and product analysis of municipal solid waste according to claim 5, wherein the gas sample in the pyrolysis reactor is collected and obtained through a high-temperature sampling probe and a heat-tracing and heat-preserving sampling pipeline, and is pretreated through a primary condenser, a filter and a dryer in sequence, and the pretreated gas sample is analyzed through a gas analyzer to obtain corresponding gas component content data.
9. The system for precise pyrolysis regulation and product analysis of municipal solid waste according to claim 1, wherein the system for collecting and analyzing the products obtained after pyrolysis according to the candidate process trajectory comprises: SC1, gas phase product treatment, namely cooling and separating high-temperature gas in a pyrolysis reactor, sequentially deacidifying and filtering to obtain pretreated gas, and temporarily storing the pretreated gas in a gas storage cabinet; SC2, liquid phase product treatment, namely layering the condensed liquid product by a centrifuge, and storing the layered liquid product in a storage; And SC3, solid product treatment, namely cooling the solid product to room temperature in a closed cooler through inert gas, and conveying the solid product to a biochar storage bin for temporary storage.
10. A method for precise pyrolysis regulation and product analysis of municipal solid waste, characterized in that the precise pyrolysis regulation and product analysis system of any one of claims 1-9 is used.

Description

Accurate pyrolysis regulation and control and product analysis system and method for urban biomass solid waste Technical Field The invention relates to the technical field of solid waste treatment, in particular to a system and a method for precise pyrolysis regulation and control and product analysis of urban biomass solid waste. Background With the acceleration of urban process and the continuous improvement of living standard of residents in China, the production of urban solid waste (Municipal Solid Waste, MSW) is continuously increased. According to statistics of the living establishment, the clean transportation amount of the urban domestic garbage nationwide in 2023 is over 2.7 hundred million tons, wherein the biomass components (such as kitchen garbage, garden waste, waste paper, woody materials and the like) account for more than 50 percent. The urban biomass solid waste has the characteristics of high water content, complex components, easy decay and the like, and if treated by adopting a traditional landfill or incineration mode, the urban biomass solid waste not only occupies a large amount of land resources, but also easily causes the emission of greenhouse gases, the pollution of percolate, the generation of toxic byproducts such as dioxin and the like, and forms serious threat to ecological environment and public health. In recent years, pyrolysis technology is regarded as an important path for realizing the recycling of urban biomass waste because the pyrolysis technology can convert organic matters into high-added-value energy products (such as bio-oil, synthesis gas and biochar) under anaerobic or anoxic conditions. The Chinese patent application with publication number of CN115746886A discloses a multi-source solid waste cooperative heat treatment method for soil ecological restoration, which comprises the following steps of screening and crushing; pretreatment; the invention adopts a method of firstly performing anaerobic pyrolysis and then performing high-temperature melting to effectively treat the solid waste, avoids various problems of incomplete treatment, secondary pollution, serious resource waste and the like in the existing treatment modes of sanitary landfill, biological composting, incineration and the like, fully recycles and recycles combustible gas, organic liquid and solid residues generated in the treatment process, saves energy, protects environment and is suitable for large-scale popularization. However, the above and similar technical solutions still have the following defects that the pyrolysis behavior of the urban biomass solid waste is difficult to predict due to the complex sources and large component fluctuation, so that the yield distribution (gas, liquid and solid three-phase ratio) and the quality (such as heat value and component purity) of the final product have significant fluctuation, and the consistency and high-value utilization of the product are severely restricted. And the regulation and control means of key technological parameters are single, dynamic response to specific material characteristics cannot be carried out, and further, a target product cannot be obtained stably and accurately. Disclosure of Invention The invention aims to provide a system and a method for precise pyrolysis regulation and product analysis of urban biomass solid waste, so as to solve the problems in the background technology. In order to achieve the aim, the invention provides the following technical scheme that the system for accurately controlling pyrolysis and analyzing products of urban biomass solid wastes comprises: the material characteristic prediction module is used for predicting pyrolysis behavior characteristics through a machine learning prediction model after preprocessing urban biomass solid waste, and obtaining a corresponding pyrolysis behavior characteristic report; the process pyrolysis regulation and control module constructs a characteristic target vector according to the pyrolysis behavior characteristic report and a user product quality target, takes the characteristic target vector as the input of a deep learning prediction model, outputs and acquires a corresponding candidate process track, monitors and acquires product quality data in the pyrolysis reaction treatment process, and adjusts the candidate process track in real time according to a comparison result between the product quality data and the user product quality target; And the product collection module is used for collecting and analyzing the products obtained after the pyrolysis reaction according to the candidate process track. Further, the obtaining of the corresponding pyrolysis behavior characteristic report includes: SA1, physical pretreatment, namely crushing, drying and homogenizing urban biomass solid waste to obtain pretreated urban biomass solid waste; SA2, characteristic identification, namely scanning the pretreated urban biomass solid waste through a near infrared spectrum