Pyrolysis-based medical waste harmless disposal and energy recovery method

Abstract

The present application relates to a kind of medical waste harmless disposal and energy recovery method based on pyrolysis applied to the technical field of solid waste treatment, comprising: data-driven intelligent pyrolysis stage, online detection material characteristics generate individualized temperature curve, pyrolysis condition is dynamically corrected based on gas composition by fuzzy PID;Product separation and directional regulation stage, fractional condensation separates heavy tar, light oil and non-condensable combustible gas, and according to the target product demand, adjust condensing temperature to regulate oil / gas ratio;Residue deep harmless and energy reuse stage, pyrolysis residue is converted into vitreous body building material by plasma melting, non-condensable gas is recycled for pyrolysis and / or melting, and plasma tail gas waste heat is recycled for pretreatment.The present application realizes self-adaptive optimization of medical waste treatment process, directional regulation of product, step-by-step utilization of energy and resource utilization of residue through the synergistic effect of information closed loop, energy closed loop and material closed loop.

Description

Technical Field

[0001] This invention relates to the field of solid waste treatment technology, and more specifically, to a method for the harmless disposal and energy recovery of medical waste based on pyrolysis. Background Technology

[0002] Medical waste refers to waste generated by medical and health institutions during medical treatment, prevention, healthcare, and other related activities that possess direct or indirect infectiousness, toxicity, or other hazards. Due to its complex composition (including plastics, rubber, cellulose, glass, metals, etc.) and the potential presence of pathogens, the harmless disposal of medical waste has always been a technical challenge in the field of environmental protection.

[0003] Pyrolysis technology, as an important method for medical waste treatment, has received widespread attention in recent years because it can convert organic matter into combustible gas, tar, and solid residue under anaerobic or hypoxic conditions, thereby achieving volume reduction, harmlessness, and resource recovery.

[0004] However, existing medical waste pyrolysis treatment technologies still have the following shortcomings: the composition of medical waste fluctuates significantly with factors such as source and season, while traditional pyrolysis processes use fixed temperature rise curves, making it difficult to optimize and adjust for the characteristics of different batches of materials, resulting in unstable processing efficiency and large fluctuations in product quality. For example, when the material contains a high content of plastics, a higher pyrolysis temperature and a longer residence time are required for complete pyrolysis; while when the content of cellulose is high, excessively high temperatures can actually lead to a decrease in the yield of the target product. Existing technologies cannot adaptively adjust pyrolysis process parameters according to real-time changes in material composition, limiting the treatment effect and resource recovery value of pyrolysis technology.

[0005] To address the aforementioned issues, Chinese invention patent CN114001357B discloses a mobile medical waste clean thermal treatment device that uses a PLC to monitor and automatically adjust temperature and pressure; Chinese invention patent CN113182311A discloses a hazardous waste treatment system based on medium-temperature pyrolysis and high-temperature plasma melting; and Chinese invention patent CN219976435U discloses a medical waste treatment system using a plasma melting coupled incinerator. Existing technologies also disclose methods for staged condensation and separation of pyrolysis oil and gas. However, these technical solutions are all fragmented disclosures, only addressing a specific aspect of medical waste treatment, and fail to solve the core problem of the pyrolysis process's inability to adapt to material fluctuations at the system level.

[0006] Therefore, there is an urgent need to develop a medical waste treatment method that can adapt to fluctuations in material composition and achieve refined control of the pyrolysis process. Summary of the Invention

[0007] The technical problem that this invention aims to solve in view of the above-mentioned prior art is that the existing medical waste pyrolysis process cannot adaptively adjust the pyrolysis parameters according to the fluctuation of material composition, resulting in unstable processing efficiency and large fluctuations in product quality.

[0008] To address the above problems, this invention provides a method for the harmless disposal and energy recovery of medical waste based on pyrolysis, comprising the following steps:

[0009] Data-driven intelligent pyrolysis stage: Online material characteristic detection is performed on pretreated medical waste, and a personalized heating curve matching the characteristics of the batch of materials is generated based on the detection results; the material is pyrolyzed according to the personalized heating curve, and the composition of pyrolysis gas is monitored in real time during the pyrolysis process. The subsequent pyrolysis conditions are dynamically adjusted according to the real-time changes in gas composition, forming a closed-loop intelligent control of the pyrolysis process.

[0010] Product separation and targeted control stage: The mixed oil and gas generated by pyrolysis is subjected to gas-solid separation, and then heavy tar, light oil and non-condensable combustible gas are separated by staged condensation; among them, according to the preset target product requirements, the production ratio of oil phase products and non-condensable combustible gas is targeted by adjusting the temperature of staged condensation.

[0011] Deep harmless treatment and energy recovery stage of residue: The solid residue generated after pyrolysis is sent to a plasma melting furnace for high-temperature melting treatment, so that the inorganic matter in the residue is converted into glassy material; at the same time, at least part of the non-condensable combustible gas is returned as a heat source to the pyrolysis and / or plasma melting process, and the waste heat of the tail gas generated in the plasma melting process is recovered for the pretreatment of materials.

[0012] As a further improvement of the present invention, the data-driven intelligent pyrolysis stage specifically includes:

[0013] Online material characteristic detection: Near-infrared spectroscopy is performed on pretreated medical waste samples to obtain spectral data; the spectral data is input into a pre-established pyrolysis characteristic identification model to output the material's composition information;

[0014] Personalized heating curve generation: Based on the component composition information, the pre-stored pyrolysis kinetics database is called to generate a personalized theoretical heating curve for this batch of materials through weighted calculation;

[0015] Intelligent dynamic pyrolysis: The material is fed into the pyrolysis reactor and heated according to the personalized theoretical temperature rise curve. During the pyrolysis process, the composition of the pyrolysis gas is monitored in real time. When the gas composition deviates from the preset target product characteristic spectrum, the heating rate of the subsequent stage is dynamically corrected through the fuzzy PID control algorithm, so that the heating curve of the actual pyrolysis process is consistent with the theoretical optimal state.

[0016] As a further improvement of the present invention, the method for establishing the pyrolysis characteristic identification model includes: collecting medical waste samples with different component ratios and acquiring their near-infrared spectra; preprocessing the spectral data using chemometrics methods; establishing a quantitative correlation model between the spectral data and the material components using principal component analysis or partial least squares discriminant analysis methods, and optimizing the model parameters through cross-validation.

[0017] As a further improvement of the present invention, the generation of the personalized theoretical heating curve is based on a pre-established kinetic database recording the pyrolysis characteristics of pure component materials, and is calculated according to the weighted combination of the proportions of each component. The weighted calculation adopts the following formula: ,in, For the first Mass fraction of the components For the first The optimal temperature rise curve function for the individual pyrolysis of each component.

[0018] As a further improvement of the present invention, the implementation of the fuzzy PID control algorithm includes: setting a target product characteristic spectrum, which includes a target H2 / CH4 ratio range and / or a target CO / CO2 ratio range; real-time monitoring of the concentrations of H2, CH4, CO, and CO2 in the pyrolysis gas, calculating the deviation E and the rate of change of deviation EC between the current gas composition and the target characteristic spectrum; inputting E and EC into the fuzzy controller, performing fuzzy inference through fuzzy rules established based on the experience of pyrolysis process experts, and outputting the correction amount of the PID parameters. The heating power adjustment is calculated using the modified PID parameters to dynamically correct the subsequent heating rate.

[0019] As a further improvement of the present invention, in the product separation and directional control stage, the staged condensation includes: a first stage of condensation, which cools the pyrolysis gas to 140-160°C to separate heavy tar; and a second stage of condensation, which cools the remaining gas to 30-50°C to separate light oil.

[0020] Targeted regulation includes: when it is necessary to maximize the yield of light oil, the second-stage condensation temperature is controlled at 30-35℃; when it is necessary to maximize the yield of non-condensable combustible gas, the second-stage condensation temperature is controlled at 45-50℃.

[0021] As a further improvement of the present invention, in the stage of deep harmless treatment of residue and energy recovery, the melting temperature of the plasma melting furnace is controlled at 1500-1800℃, and the glass material after melting is rapidly cooled by water to form glass particles, whose heavy metal leaching concentration is lower than the limit specified in the national hazardous waste identification standard.

[0022] As a further improvement of the present invention, energy recovery also includes: recovering the waste heat of the high-temperature exhaust gas generated by the plasma melting furnace for use in the material drying process of the pretreatment step; and merging the exhaust gas after the combustion of non-condensable combustible gas with the exhaust gas of the plasma melting furnace, and then discharging it in compliance with emission standards after denitrification, rapid cooling, activated carbon adsorption and bag filter dust removal.

[0023] As a further improvement of the present invention, the pretreatment step includes: crushing the medical waste to a particle size ≤20mm in a closed negative pressure environment, removing the metal components by magnetic separation and eddy current separation, removing the glass components by air separation, and then drying to a moisture content of less than 10%.

[0024] As a further improvement of the present invention, the method described in the present invention is a fully closed-loop intelligent processing method, wherein:

[0025] Information closed loop: The product distribution information output by the data-driven intelligent pyrolysis stage is used to optimize the control strategies in the product separation and directional control stages;

[0026] Energy closed loop: The non-condensable combustible gas produced in the product separation and directional control stage provides thermal energy for the data-driven intelligent pyrolysis stage and / or the stage of deep harmless treatment and energy recovery of residue;

[0027] Material closed loop: The glassy materials generated during the stage of deep harmless treatment of residues and energy recovery are used as building materials to achieve resource utilization.

[0028] Compared with the prior art, the present invention has the following beneficial effects:

[0029] 1. This invention utilizes near-infrared online detection of material components and combines this with a weighted average of a pyrolysis kinetics database to generate personalized heating curves, enabling pyrolysis process parameters to adapt to real-time fluctuations in the composition of medical waste. Compared to traditional processes using fixed heating curves, stable and efficient pyrolysis can be achieved regardless of changes in the proportions of plastics, cellulose, and rubber in the material.

[0030] 2. Based on the personalized heating curve, this invention further adopts a fuzzy PID control algorithm based on real-time gas component (H2, CH4, CO, CO2) monitoring to dynamically correct the heating rate in subsequent stages, so that the actual pyrolysis process can always approach the theoretical optimal state. This not only improves the temperature control accuracy and shortens the pyrolysis reaction time, but also significantly improves the selectivity of the target product.

[0031] 3. This invention combines staged condensation with directional control, allowing for flexible adjustment of the production ratio of oil phase products and non-condensable combustible gases according to market demand. When maximizing the yield of light oil is required, the second-stage condensation temperature is controlled at 30–35°C; when maximizing the yield of non-condensable combustible gases is required, the second-stage condensation temperature is controlled at 45–50°C, thereby effectively improving economic efficiency.

[0032] 4. This invention reuses the non-condensable combustible gas generated by pyrolysis in the pyrolysis and / or plasma melting process, and recovers the waste heat of the high-temperature tail gas generated by the plasma melting furnace for material drying, forming an energy closed loop within the system.

[0033] 5. This invention uses a plasma melting furnace to treat pyrolysis residue at a high temperature of 1500–1800℃, transforming inorganic matter into a glassy material. Heavy metals are effectively solidified within the glassy structure, and their leaching concentration is far below the limits specified in the national hazardous waste identification standards. After water quenching and rapid cooling, the glassy material forms glassy particles, which can be used as building materials for resource utilization.

[0034] 6. This invention integrates the above features into a three-in-one intelligent processing system comprising information closed loop, energy closed loop, and material closed loop. The information closed loop enables an optimized cycle between front-end detection results and back-end control strategies; the energy closed loop achieves tiered utilization of energy within the system; and the material closed loop ensures the resource utilization of residue. The synergistic effect of these three elements constructs an efficient, intelligent, and clean medical waste treatment system. Attached Figure Description

[0035] Figure 1 This is a flowchart illustrating the overall process flow of the present invention. Detailed embodiments are described below.

[0036] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of protection of this invention.

[0037] Example 1:

[0038] Please see Figure 1 This embodiment provides a method for the harmless disposal and energy recovery of medical waste based on pyrolysis, which includes the following three stages: a data-driven intelligent pyrolysis stage, a product separation and targeted control stage, and a residue deep harmless treatment and energy recovery stage.

[0039] I. Preprocessing

[0040] Before pyrolysis, medical waste undergoes pretreatment. Specifically:

[0041] The collected medical waste is fed into a crusher under a closed negative pressure environment and crushed to a particle size of ≤20mm. The closed negative pressure environment effectively prevents the leakage of dust and volatile organic compounds generated during the crushing process, ensuring a safe operating environment.

[0042] The crushed material is passed through magnetic separation and eddy current separation equipment in sequence to remove the metal components (such as needles, surgical blades, etc.); then it is passed through air separation equipment to remove the glass components (such as medicine bottles, test tubes, etc.) by utilizing the material density difference.

[0043] The sorted materials are sent to a drying device and dried until the moisture content is less than 10% to meet the requirements of subsequent pyrolysis treatment.

[0044] II. Data-Driven Intelligent Pyrolysis Stage

[0045] The core of this stage lies in adjusting the pyrolysis process parameters in real time according to the material characteristics, and ensuring that the pyrolysis process is always in the optimal state through dynamic feedback control.

[0046] 1. Online material property detection

[0047] Online sampling was performed on the pretreated material, and the samples were then subjected to near-infrared spectral scanning. This embodiment employed a Fourier transform near-infrared spectrometer with a spectral scanning range of 4000-12000 cm⁻¹. -1 The resolution is 8 cm. -1 .

[0048] The collected spectral data is input into a pre-established pyrolysis characteristic identification model. The model outputs the composition information of the material, including at least: the content of plastic substances (such as polyethylene, polyvinyl chloride, polypropylene, etc.), the content of cellulose substances (such as cotton swabs, gauze, paper, etc.), and the content of rubber substances (such as gloves, tubing, etc.).

[0049] The method for establishing the pyrolysis characteristic identification model is as follows:

[0050] (1) Collect medical waste samples with different component ratios, covering the typical content range of major components such as plastics, cellulose, and rubber;

[0051] (2) Collect near-infrared spectra of each sample;

[0052] (3) Preprocess the spectral data using chemometric methods, including smoothing to eliminate noise, standard normal variable transformation, and multivariate scattering correction to eliminate scattering effects;

[0053] (4) Use principal component analysis (PCA) or partial least squares discriminant analysis (PLS-DA) to establish a quantitative correlation model between spectral data and material components;

[0054] (5) Optimize the model parameters through cross-validation to obtain the pyrolysis characteristic identification model.

[0055] Testing showed that the model achieved an accuracy rate of over 90% in identifying plastics, cellulose, and rubber components, meeting the requirements for online detection. The model establishment method described above can be implemented using conventional techniques in the field, and those skilled in the art can determine the optimal model parameters through experiments based on actual sample conditions.

[0056] 2. Personalized heating curve generation

[0057] Based on the material composition information obtained from online detection, a pre-stored pyrolysis kinetics database is invoked to generate a personalized theoretical temperature rise curve for this batch of materials through weighted calculation.

[0058] The pyrolysis kinetics database contains pre-recorded pyrolysis weight loss curves and product distribution patterns of pure component materials (such as polyethylene, polyvinyl chloride, cellulose, rubber, etc.) at different heating rates. The data in the database can be obtained through experimental methods such as thermogravimetric analysis-mass spectrometry (TG-MS).

[0059] The weighted calculation uses the following formula:

[0060]

[0061] in, For the first Mass fraction of the components For the first The optimal heating curve function for the individual pyrolysis of a component. The optimal heating curve function refers to the heating curve that maximizes the yield of the target product of the pyrolysis of that component, and usually includes multiple heating stages and isothermal stages.

[0062] For example, for a certain batch of materials, the detected content of plastics is 60%, cellulose is 30%, and rubber is 10%, then its personalized theoretical temperature rise curve is: .

[0063] 3. Intelligent dynamic pyrolysis

[0064] The pretreated material is fed into a pyrolysis reactor (an externally heated rotary kiln pyrolysis reactor is used in this embodiment) and heated according to the generated personalized theoretical temperature rise curve. The pyrolysis reactor is maintained under a slight negative pressure (-50 to -200 Pa) and an oxygen-free environment (achieved by nitrogen purging).

[0065] During the pyrolysis process, the composition of the pyrolysis gases, including the concentrations of components such as H2, CH4, CO, and CO2, is monitored in real time using an online gas analyzer (such as a gas chromatograph or an infrared gas analyzer).

[0066] When the gas composition deviates from the preset target product characteristic spectrum, the heating rate in subsequent stages is dynamically corrected using a fuzzy PID control algorithm, ensuring that the heating curve of the actual pyrolysis process remains consistent with the theoretical optimal state. The specific implementation is as follows:

[0067] (1) Set the target product characteristic spectrum: Based on the requirements of the target product, preset the target H2 / CH4 ratio range and the target CO / CO2 ratio range. For example, when the goal is to maximize the gas production rate, the H2 / CH4 ratio can be set to 1.5 to 2.5 and the CO / CO2 ratio to 1.0 to 2.0.

[0068] (2) Calculate the deviation: calculate the deviation E and the rate of change of deviation EC between the current gas composition and the target characteristic spectrum in real time.

[0069] (3) Fuzzy reasoning: and Input the fuzzy controller. The fuzzy controller has preset fuzzy rules based on the experience of pyrolysis process experts, for example:

[0070] If the H2 / CH4 ratio is higher than the upper limit of the target range and shows an upward trend ( For the sake of righteousness, If the output is positive, it indicates that the pyrolysis temperature is too high, and the heating rate needs to be reduced (output). (for negative large)

[0071] If the H2 / CH4 ratio is below the lower limit of the target range and shows a downward trend ( For a large negative value, If the output is negative (large), it indicates that the pyrolysis reaction is incomplete, and the heating rate needs to be increased or the isothermal time extended (output). (for the sake of righteousness)

[0072] Other rules can be established similarly based on process experience.

[0073] (4) Output correction amount: The correction amount of the PID parameters is output through fuzzy inference. .

[0074] (5) Dynamic correction: The heating power adjustment is calculated using the corrected PID parameters to dynamically adjust the subsequent heating rate.

[0075] Through the above closed-loop control, the actual pyrolysis process is always kept close to the theoretical optimal state, ensuring the stability of processing efficiency and product quality.

[0076] III. Product Separation and Targeted Regulation Stage

[0077] The mixed oil and gas produced by pyrolysis first enters a cyclone separator for gas-solid separation to remove any solid particles that may be carried.

[0078] The separated pyrolysis gas enters a staged condensation system. This embodiment employs a two-stage condensation process:

[0079] First-stage condensation: The pyrolysis gas is cooled to 140-160°C. Within this temperature range, the heavy tar (with a higher boiling point) condenses into a liquid and is collected from the bottom.

[0080] Second-stage condensation: The remaining gas is cooled to 30-50°C. Within this temperature range, the light oil (with a lower boiling point) condenses into a liquid and is separated from the non-condensable combustible gas.

[0081] This embodiment further employs a targeted control strategy. Based on the preset target product requirements, the production ratio of oil phase products to non-condensable combustible gases is flexibly adjusted by regulating the temperature of the second-stage condensation. To verify the control effect within a specific temperature range, a condensation temperature gradient experiment was conducted: with other conditions fixed, the second-stage condensation temperature was controlled at 25℃, 30℃, 33℃, 35℃, 40℃, 45℃, 48℃, 50℃, and 55℃, respectively, and the yield of light oil and the yield of combustible gas were measured. The experimental results show that:

[0082] When the second-stage condensation temperature is controlled at 30-35℃, the yield of light oil reaches its peak (34-35%). Below 30℃, the yield does not increase significantly, and above 35℃, the yield begins to decline.

[0083] When the second-stage condensation temperature is controlled at 45-50℃, the non-condensable combustible gas yield reaches its peak (41-42%). Below 45℃, some light components condense into the oil phase, causing the gas yield to decrease. Above 50℃, the gas yield tends to stabilize.

[0084] The above experiments demonstrate that 30–35℃ and 45–50℃ are the preferred temperature ranges for maximizing light oil yield and non-condensable combustible gas yield, respectively, exhibiting a unique non-linear effect.

[0085] Therefore, this embodiment adjusts the settings according to a preset target:

[0086] When market oil prices are high and it is necessary to maximize the yield of light oil, the second-stage condensation temperature is controlled at 30-35℃ (33℃ in this embodiment) to allow more light components to condense into the oil phase.

[0087] When market demand for gas is high and it is necessary to maximize the production rate of non-condensable combustible gas, the second-stage condensation temperature is controlled at 45-50℃ (48℃ in this embodiment) to retain more light components in the gas phase.

[0088] After purification (removal of acidic gases, moisture, etc.), part of the separated non-condensable combustible gas is returned to the pyrolysis system as fuel, while the rest can be further purified and separated into high-value-added products such as hydrogen or synthetic natural gas through a pressure swing adsorption device.

[0089] IV. Deep harmless treatment and energy recovery stage of residue

[0090] The solid residue (mainly carbon black, inorganic materials, etc.) discharged from the pyrolysis reactor is sent to a plasma melting furnace for high-temperature melting treatment. In this embodiment, a DC arc plasma melting furnace is used, and the melting temperature is controlled at 1500-1800℃ (1600℃ in this embodiment).

[0091] At high temperatures, inorganic substances in the residue (such as glass, ceramics, and metal oxides) melt into liquid slag, organic matter decomposes completely, and heavy metals are solidified within the vitreous network of the slag. The molten vitreous material is then rapidly cooled in water to form vitreous particles. The heavy metal leaching concentration of the obtained vitreous particles (using the sulfuric acid-nitric acid method according to GB 5085.3-2007) is as follows:

[0092] heavy metal Leaching concentration (mg / L) Standard limit (mg / L) Pb 0.05 ≤5 Cd 0.01 ≤1 Cr 0.12 ≤15 As 0.03 ≤5 Ni 0.08 ≤5 Hg 0.002 ≤0.1

[0093] The above data shows that the heavy metal leaching concentration is far below the national standard limit, and the vitreous material can be used as a building material to achieve resource utilization.

[0094] Energy recycling is another important feature of this invention:

[0095] Non-condensable gas reuse: Part of the non-condensable combustible gas produced in the product separation stage is returned to the heating system of the pyrolysis reactor as a heat source, and / or used as auxiliary fuel for the plasma melting furnace to achieve energy self-sufficiency within the system;

[0096] Waste heat recovery: The high-temperature exhaust gas (temperature can reach above 800℃) generated by the plasma melting furnace is recovered through a waste heat boiler. The generated steam or hot air is used for material drying in the pretreatment stage, realizing the cascade utilization of energy.

[0097] Exhaust gas purification: The exhaust gas from the combustion of non-condensable combustible gas is combined with the exhaust gas from the plasma melting furnace and then purified through denitrification (SNCR or SCR), rapid cooling, activated carbon adsorption and bag filter dust removal before being discharged in compliance with standards.

[0098] Calculations show that the heat energy provided by the non-condensable combustible gas can meet most of the energy consumption needs of the pyrolysis system and plasma melting furnace. Combined with the waste heat recovery of the tail gas, the overall energy self-sufficiency rate of the system reaches more than 85%.

[0099] V. Closed-loop collaboration throughout the entire process

[0100] The method described in this embodiment forms the following three closed loops:

[0101] Information Closed Loop: Product distribution information (such as gas composition and residue characteristics) output from the intelligent pyrolysis stage is fed back to the control system to optimize the control strategies for product separation and directional regulation stages, achieving closed-loop optimization based on processing results. For example, during the pyrolysis of a certain batch, the online gas analyzer detected a persistently high H2 / CH4 ratio (reaching 2.3). Based on preset rules, the system judges that the current pyrolysis reaction is shifting towards gas production. Combined with the preset target of high market demand for fuel gas, the system automatically increases the second-stage condensation temperature from the preset 35℃ to 48℃ to maximize the yield of non-condensable combustible gas. Simultaneously, after the batch is processed, the system stores the actual product distribution data (such as light oil yield and non-condensable gas yield) in the historical database for optimization of control strategies in subsequent batches, forming a complete information closed loop.

[0102] Energy closed loop: The non-condensable combustible gas produced in the product separation stage provides thermal energy for the intelligent pyrolysis stage and the deep harmless treatment stage of the residue. The waste heat of the plasma melting tail gas is recovered for pretreatment, forming an energy self-circulation within the system.

[0103] Material closed loop: Pyrolysis residue is transformed into glass material through plasma melting, which is then used as building material to achieve resource utilization, realizing a full-chain material cycle from waste to resource.

[0104] The three closed-loop systems mentioned above work together to create an efficient, intelligent, and clean medical waste treatment system.

[0105] Example 2

[0106] This embodiment is basically the same as Embodiment 1, except that the target product requirements are different.

[0107] In this embodiment, the market demand for light oil is high. Therefore, during the product separation and targeted control stage, the second-stage condensation temperature is controlled at 30-35°C (32°C in this embodiment) to maximize the light oil yield. Simultaneously, based on market demand, the separated light oil can be further processed (e.g., hydrorefining) to produce fuel oil or chemical feedstock.

[0108] Non-condensable combustible gas is prioritized to meet the self-use needs of the pyrolysis system and plasma melting furnace, with the remainder used for power generation or steam production.

[0109] Example 3

[0110] This embodiment is basically the same as Embodiment 1, except that the target product requirements are different.

[0111] In this embodiment, the market demand for natural gas is high. Therefore, during the product separation and targeted control stage, the second-stage condensation temperature is controlled at 45-50℃ (47℃ in this embodiment) to maximize the yield of non-condensable combustible gas. The separated non-condensable combustible gas is purified by pressure swing adsorption to produce hydrogen (purity can reach over 99.9%) or synthetic natural gas, which are then sold as high-value-added products.

[0112] Light oil is collected as a byproduct and can be used to blend fuel oil.

[0113] Comparative Example 1

[0114] This comparative example uses a traditional pyrolysis method with a fixed temperature rise curve to treat the same batch of medical waste. There is no online material monitoring during the pyrolysis process, and the temperature rise curve is fixed in three stages: room temperature → 250℃ (heating rate 10℃ / min), 250℃ → 450℃ (heating rate 5℃ / min), 450℃ → 550℃ (heating rate 8℃ / min), and a constant temperature of 550℃ for 30 min.

[0115] The pyrolysis products are separated using conventional condensation (with a fixed condensation temperature of 40°C) without any directional control function. The residue is directly landfilled without plasma melting treatment. There is no energy recovery system.

[0116] The results showed that due to fluctuations in material composition, the processing efficiency and product quality of this comparative example fluctuated significantly, with the target product yield varying by more than ±20%, and the risk of heavy metal leaching from the residue was high.

[0117] Comparison of effects between the examples and the comparative examples

[0118] Compared with Comparative Example 1, Examples 1-3 have the following advantages:

[0119] Comparison Projects Comparative Example 1 Examples 1-3 Improved results Processing stability The yield of the target product fluctuated by more than ±20%. The yield of the target product fluctuates within ±5%. Significantly improved stability Temperature control accuracy ±15℃ Within ±5℃ Improved control precision pyrolysis time 90-120 minutes 70-90 minutes shorten by 10-20% Product flexibility Fixed ratio The oil / gas ratio can be adjusted according to market demand. Improved economic efficiency Residue treatment Landfilling poses environmental risks. Vitreous building materials, heavy metal curing Deep harmlessness Energy consumption External power supply Energy self-sufficiency rate of over 85% Energy consumption reduced by more than 50%

[0120] The above data shows that the method described in this invention is superior to traditional methods in terms of adaptive material fluctuations, dynamic control precision, product regulation flexibility, residue harmlessness, and energy utilization efficiency, achieving efficient, intelligent, and clean treatment of medical waste.

[0121] The above description is merely a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Various changes made within the scope of knowledge possessed by those skilled in the art without departing from the concept of the present invention still fall within the scope of protection of the present invention.

Claims

1. A method for the harmless disposal and energy recovery of medical waste based on pyrolysis, characterized in that, Includes the following steps: Data-driven intelligent pyrolysis stage: Online material characteristic detection is performed on the pretreated medical waste, and a personalized heating curve matching the characteristics of the batch of materials is generated based on the detection results; the material is pyrolyzed according to the personalized heating curve, and the composition of the pyrolysis gas is monitored in real time during the pyrolysis process, and the subsequent pyrolysis conditions are dynamically corrected according to the real-time changes in the gas composition, forming a closed-loop intelligent control of the pyrolysis process. Product separation and targeted control stage: The mixed oil and gas generated by pyrolysis is subjected to gas-solid separation, and then heavy tar, light oil and non-condensable combustible gas are separated by staged condensation; among them, according to the preset target product requirements, the production ratio of oil phase products and non-condensable combustible gas is targeted by adjusting the temperature of staged condensation. Deep harmless treatment and energy recovery stage of residue: The solid residue generated after pyrolysis is sent to a plasma melting furnace for high-temperature melting treatment, so that the inorganic matter in the residue is converted into glassy material; at the same time, at least part of the non-condensable combustible gas is returned as a heat source to the pyrolysis and / or plasma melting process, and the waste heat of the tail gas generated in the plasma melting process is recovered for the pretreatment of materials.

2. The method for harmless disposal and energy recovery of medical waste based on pyrolysis according to claim 1, characterized in that, The data-driven intelligent pyrolysis stage specifically includes: Online material characteristic detection: Near-infrared spectroscopy is performed on the pretreated medical waste sample to obtain spectral data; the spectral data is input into a pre-established pyrolysis characteristic identification model to output the component composition information of the material; Personalized heating curve generation: Based on the component composition information, a pre-stored pyrolysis kinetics database is called to generate a personalized theoretical heating curve for this batch of materials through weighted calculation; Intelligent dynamic pyrolysis: The material is fed into the pyrolysis reactor and heated according to the personalized theoretical heating curve. During the pyrolysis process, the composition of the pyrolysis gas is monitored in real time. When the gas composition deviates from the preset target product characteristic spectrum, the heating rate of the subsequent stage is dynamically corrected through the fuzzy PID control algorithm so that the heating curve of the actual pyrolysis process is consistent with the theoretical optimal state.

3. The method for harmless disposal and energy recovery of medical waste based on pyrolysis according to claim 2, characterized in that, The method for establishing the pyrolysis characteristic identification model includes: collecting medical waste samples with different component ratios and acquiring their near-infrared spectra; preprocessing the spectral data using chemometrics methods; establishing a quantitative correlation model between the spectral data and the material components using principal component analysis or partial least squares discriminant analysis methods, and optimizing the model parameters through cross-validation.

4. The method for harmless disposal and energy recovery of medical waste based on pyrolysis according to claim 2, characterized in that, The personalized theoretical heating curve is generated based on a pre-established kinetic database recording the pyrolysis characteristics of pure component materials, and is calculated according to a weighted combination of the proportions of each component. The weighted calculation uses the following formula: ,in, For the first Mass fraction of the components For the first The optimal temperature rise curve function for the individual pyrolysis of each component.

5. The method for harmless disposal and energy recovery of medical waste based on pyrolysis according to claim 2, characterized in that, The implementation of the fuzzy PID control algorithm includes: setting a target product characteristic spectrum, which includes a target H2 / CH4 ratio range and / or a target CO / CO2 ratio range; real-time monitoring of the concentrations of H2, CH4, CO, and CO2 in the pyrolysis gas, calculating the deviation E and the rate of change EC between the current gas composition and the target characteristic spectrum; inputting E and EC into the fuzzy controller, performing fuzzy inference through fuzzy rules established based on the experience of pyrolysis process experts, and outputting the correction amount of the PID parameters. The heating power adjustment is calculated using the modified PID parameters to dynamically correct the subsequent heating rate.

6. The method for harmless disposal and energy recovery of medical waste based on pyrolysis according to claim 1, characterized in that, In the product separation and directional control stage, the staged condensation includes: first-stage condensation, which cools the pyrolysis gas to 140-160°C to separate heavy tar; and second-stage condensation, which cools the remaining gas to 30-50°C to separate light oil. The targeted regulation includes: when it is necessary to maximize the yield of light oil, controlling the second-stage condensation temperature at 30-35°C; when it is necessary to maximize the yield of non-condensable combustible gas, controlling the second-stage condensation temperature at 45-50°C.

7. The method for harmless disposal and energy recovery of medical waste based on pyrolysis according to claim 1, characterized in that, In the stage of deep harmless treatment and energy recovery of the residue, the melting temperature of the plasma melting furnace is controlled at 1500-1800℃. The molten glass material is rapidly cooled by water to form glass particles, and the heavy metal leaching concentration is lower than the limit specified in the national hazardous waste identification standard.

8. The method for harmless disposal and energy recovery of medical waste based on pyrolysis according to claim 1, characterized in that, The energy recovery also includes: recovering the waste heat from the high-temperature exhaust gas generated by the plasma melting furnace for use in the material drying process of the pretreatment step; the exhaust gas after the combustion of the non-condensable combustible gas is combined with the exhaust gas from the plasma melting furnace and then discharged in compliance with standards after denitrification, rapid cooling, activated carbon adsorption and bag filter dust removal.

9. The method for harmless disposal and energy recovery of medical waste based on pyrolysis according to claim 1, characterized in that, The pretreatment steps include: crushing medical waste to a particle size ≤20mm in a closed negative pressure environment, removing metal components by magnetic separation and eddy current separation, removing glass components by air separation, and then drying to a moisture content of less than 10%.

10. The method for harmless disposal and energy recovery of medical waste based on pyrolysis according to claim 1, characterized in that, This method is a closed-loop intelligent processing method, wherein: Information closed loop: The product distribution information output by the data-driven intelligent pyrolysis stage is used to optimize the control strategy of the product separation and directional control stage; Energy closed loop: The non-condensable combustible gas produced in the product separation and directional control stage provides thermal energy for the data-driven intelligent pyrolysis stage and / or the residue deep harmlessness and energy recovery stage; Material closed loop: The glassy material generated during the deep harmlessness treatment and energy recovery stage of the residue is used as a building material to achieve resource utilization.

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