A plastic fractionated pyrolysis temperature control system and method

Abstract

The present application relates to the technical field of waste plastic resource processing and chemical process control, in particular to a plastic grading pyrolysis temperature control system and method. The system comprises the following steps: collecting real-time spectral data and mass flow data of mixed plastics at the inlet; outputting theoretical heat demand power; separating high-frequency fluctuation heat power; collecting real-time change rate of bed temperature; combining high-frequency fluctuation heat power and real-time change rate of bed temperature to calculate heat shock compensation power; obtaining preset single pulse energy; generating theoretical pulse injection frequency; collecting bed pressure drop data; calculating fluidization quality factor based on the bed pressure drop data; and using the fluidization quality factor to attenuate and correct the theoretical pulse injection frequency to generate the final execution frequency. The present application effectively eliminates the temperature fluctuation hysteresis in the pyrolysis process of complex component plastics by collecting real-time spectral and mass flow data of mixed plastics, analyzing the material components in real time and calculating the theoretical heat demand power.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of waste plastic resource processing and chemical process control, in particular to a plastic graded pyrolysis temperature control system and method. BACKGROUND

[0002] Plastic graded pyrolysis is a resource regeneration technology that converts mixed waste plastics into high-value chemical raw materials in an oxygen-free environment using a fluidized bed reactor and a hot carrier; in order to ensure the cracking efficiency and product quality, the system needs to maintain a constant temperature in the reaction zone and keep the bed in good fluidization state;

[0003] However, the actual processing of waste plastic feed has significant heterogeneous characteristics, and the random fluctuations of its composition and flow will cause the reaction heat load to change dramatically and frequently; the existing technology usually simply relies on temperature feedback for adjustment, and when faced with rapid changes in heat demand, there is serious lag, and the heat gap cannot be compensated in time; in addition, if high-intensity heat injection is performed to follow the heat load, it is easy to destroy the gas-solid fluid dynamics balance in the fluidized bed, causing flow instability phenomena such as channeling and slug, which leads to the reactor cannot be continuously and stably operated, and even causes safety accidents;

[0004] Therefore, there is an urgent need for a temperature control scheme that can both anticipate heat demand based on feed characteristics to eliminate lag and prevent heat shock from destroying the stability of the bed flow state.

[0005] The above information disclosed in the above BACKGROUND section is only used to strengthen the understanding of the background of the present disclosure, and therefore it can include information that does not constitute prior art known to those of ordinary skill in the art. SUMMARY

[0006] To solve the above technical problems, the present application discloses a plastic graded pyrolysis temperature control system and method, in particular, the technical scheme of the present application:

[0007] A plastic graded pyrolysis temperature control method, comprising:

[0008] Collecting real-time spectral data and mass flow data of mixed plastics at the inlet;

[0009] Inputting the real-time spectral data and mass flow data into a heterogeneous feed thermodynamic characteristic feedforward mapping model to output a theoretical heat demand power;

[0010] Processing the theoretical heat demand power using a moving average filter to separate out a high-frequency fluctuation heat power;

[0011] Collecting the real-time change rate of the bed temperature;

[0012] Combining the high-frequency fluctuation heat power and the real-time change rate of the bed temperature to calculate a heat shock compensation power;

[0013] acquire a preset single-pulse energy;

[0014] generate a theoretical pulse injection frequency based on the thermal shock compensation power and the single-pulse energy;

[0015] acquire bed pressure drop data;

[0016] calculate a fluidization quality factor based on the bed pressure drop data;

[0017] correct the theoretical pulse injection frequency using the fluidization quality factor to generate a final execution frequency; control the heat carrier pulse injection system according to the final execution frequency;

[0018] Preferably, the real-time spectrum data and the mass flow data are input into a heterogeneous feed thermodynamic characteristic feedforward mapping model to output a theoretical heat demand power, including:

[0019] based on the real-time spectrum data, analyze the material component distribution and convert it into a component mass fraction;

[0020] acquire a reaction zone set target temperature, an initial feed temperature, and specific heat capacities and reaction enthalpies of each component;

[0021] based on the component mass fraction, the reaction zone set target temperature, the initial feed temperature, the specific heat capacities, and the reaction enthalpies, calculate a unit mass heat demand;

[0022] multiply the unit mass heat demand by the mass flow data to obtain the theoretical heat demand power.

[0023] Preferably, the theoretical heat demand power is processed using a moving average filter to separate out a high-frequency fluctuation heat power, including:

[0024] acquire a preset moving time window constant;

[0025] calculate an integral average value of the theoretical heat demand power within the moving time window constant to obtain a low-frequency steady-state component;

[0026] subtract the low-frequency steady-state component from the theoretical heat demand power at the current time to obtain the high-frequency fluctuation heat power.

[0027] Preferably, the high-frequency fluctuation heat power is combined with a bed temperature real-time change rate to calculate a thermal shock compensation power, including:

[0028] acquire a preset feedforward confidence coefficient and a preset feedback gain coefficient;

[0029] acquire a total bed heat capacity in an effective heating zone of the reactor;

[0030] calculate a product of the feedforward confidence coefficient and the high-frequency fluctuation heat power to obtain a feedforward term;

[0031] The feedback correction term is obtained by multiplying the feedback gain coefficient, the total heat capacity of the bed and the real-time change rate of the bed temperature;

[0032] The heat shock compensation power is obtained by subtracting the feedback correction term from the feedforward term.

[0033] Preferably, the theoretical pulse injection frequency is generated based on the heat shock compensation power and the single pulse energy, comprising:

[0034] If the heat shock compensation power is less than or equal to zero, the theoretical pulse injection frequency is determined to be zero;

[0035] If the heat shock compensation power is greater than zero, the heat shock compensation power is divided by the single pulse energy to obtain a preliminary calculation frequency; to prevent the frequency from exceeding the hardware limit, the preliminary calculation frequency is compared with the preset maximum physical frequency limit The smaller value is taken as the theoretical pulse injection frequency; at the same time, in the division operation, if the single pulse energy is lower than the preset minimum energy threshold , the value of is taken to participate in the calculation to prevent the denominator from being too small.

[0036] Preferably, the fluidization quality factor is calculated based on the bed pressure drop data, comprising:

[0037] The average pressure drop under normal fluidization state is obtained;

[0038] The square of the difference between the bed pressure drop data and the average pressure drop in the preset sliding statistical window is calculated;

[0039] The integral mean value of the square in the sliding statistical window is calculated;

[0040] The integral mean value is divided by the average pressure drop to obtain the fluidization quality factor.

[0041] Preferably, the theoretical pulse injection frequency is attenuated and corrected by using the fluidization quality factor to generate the final execution frequency, comprising:

[0042] The preset fluidization instability critical threshold and the preset sensitivity gain coefficient are obtained;

[0043] The difference between the fluidization quality factor and the fluidization instability critical threshold is calculated;

[0044] The attenuation correction coefficient is calculated by a Logistic function based on the difference and the sensitivity gain coefficient;

[0045] The theoretical pulse injection frequency is multiplied by the attenuation correction coefficient to obtain the final execution frequency.

[0046] Preferably, the preset single pulse energy is obtained, comprising:

[0047] Obtaining single injection heat conduction medium mass, heat conduction medium specific heat capacity, heat carrier storage tank temperature, reaction zone set target temperature and gas-solid contact heat exchange efficiency factor;

[0048] Calculating the temperature difference between the heat carrier storage tank temperature and the reaction zone set target temperature;

[0049] Calculating the continuous product of the single injection heat conduction medium mass, the heat conduction medium specific heat capacity, the temperature difference and the gas-solid contact heat exchange efficiency factor to obtain a single pulse energy.

[0050] A plastic staged pyrolysis temperature control system comprises:

[0051] A data acquisition module is configured to acquire real-time spectral data and mass flow data of mixed plastics at an inlet;

[0052] A heat enthalpy analysis module is configured to input the real-time spectral data and the mass flow data into a heterogeneous feed thermodynamic characteristic feedforward mapping model and output theoretical required heat power;

[0053] A frequency domain filtering module is configured to process the theoretical required heat power by using a sliding average filter to separate out high-frequency fluctuation heat power;

[0054] A heat shock compensation module is configured to acquire a real-time change rate of bed temperature and calculate heat shock compensation power by combining the high-frequency fluctuation heat power and the real-time change rate of bed temperature;

[0055] A frequency modulation module is configured to acquire a preset single pulse energy and generate a theoretical pulse injection frequency based on the heat shock compensation power and the single pulse energy;

[0056] A flow state correction module is configured to acquire bed pressure drop data and calculate a fluidization quality factor, attenuate and correct the theoretical pulse injection frequency by using the fluidization quality factor to generate a final execution frequency, and control a heat carrier pulse injection system according to the final execution frequency.

[0057] Compared with the prior art, the present application has the following beneficial effects:

[0058] 1、The present application can analyze material components and calculate theoretical required heat power in real time by acquiring real-time spectral data and mass flow data of mixed plastics and using a heterogeneous feed thermodynamic characteristic feedforward mapping model.

[0059] 2, The application separates the high-frequency fluctuation component from the theoretical heat demand by using a moving average filter, and calculates the heat shock compensation power in combination with the real-time change rate of the bed temperature. This double-dimensional compensation mechanism can accurately identify the steady-state load and transient disturbance, and through the coordinated adjustment of the feedforward confidence and feedback gain, it realizes the rapid response to high-frequency heat load fluctuations, significantly enhancing the temperature stability of the reactor when the feed is subjected to severe fluctuations.

[0060] 3, The application calculates the fluidization quality factor by collecting bed pressure drop data, and uses the factor to attenuate and correct the theoretical pulse injection frequency. This mechanism can monitor the fluidization state in the reactor in real time, and when the risk of fluidization instability is detected, the injection frequency of the heat carrier is automatically limited by the Logistic function, thereby ensuring the temperature control requirements while preventing excessive injection from damaging the gas-solid fluidization balance, ensuring long-term stable operation of the system.

[0061] 4, The application converts the continuous heat demand into discrete theoretical pulse injection frequency based on single pulse energy, and accurately calculates the single energy release in combination with the temperature difference between the heat carrier tank temperature and the target temperature of the reaction zone. This frequency modulation method converts analog heat energy control into digital pulse control, not only overcoming the thermal inertia problem of traditional continuous heating, but also greatly improving the uniformity of temperature distribution inside the reaction bed through high-frequency and small-amount heat carrier injection. BRIEF DESCRIPTION OF DRAWINGS

[0062] The application will be further explained in conjunction with the accompanying drawings and examples:

[0063] Figure 1 is a method flow chart of the application;

[0064] Figure 2 is a system structure diagram of the application. DETAILED DESCRIPTION

[0065] Example 1:

[0066] Please refer to Figure 1 A plastic staged pyrolysis temperature control method, comprising:

[0067] Collecting real-time spectrum data and mass flow data of mixed plastics at the inlet; inputting the real-time spectrum data and mass flow data into a heterogeneous feed thermodynamic characteristic feedforward mapping model to output theoretical heat demand; processing the theoretical heat demand by using a moving average filter to separate high-frequency fluctuation heat demand; collecting the real-time change rate of the bed temperature; combining the high-frequency fluctuation heat demand and the real-time change rate of the bed temperature to calculate the heat shock compensation power;

[0068] acquire a preset single pulse energy; generate a theoretical pulse injection frequency based on the heat shock compensation power and the single pulse energy; collect bed pressure drop data; calculate a fluidization quality factor based on the bed pressure drop data; attenuate correct the theoretical pulse injection frequency using the fluidization quality factor to generate a final execution frequency; and control the heat carrier pulse injection system according to the final execution frequency;

[0069] The embodiment provides a plastic staged pyrolysis temperature control method, aiming to solve the temperature control lag and flow state instability problems caused by component fluctuation in the heterogeneous plastic pyrolysis process; the method is executed in the following logical process:

[0070] The system performs a data acquisition step, that is, acquires real-time spectrum data and mass flow data of mixed plastics at an inlet; in the embodiment, a near-infrared spectrometer is arranged above a feeding conveyor belt, used for continuously scanning and acquiring real-time spectrum data reflecting chemical components of the materials, and at the same time, a high-precision belt scale monitors and sends instantaneous mass flow data of the materials through a transmitter;

[0071] The system performs heat enthalpy analysis, inputs the acquired real-time spectrum data and mass flow data into a pre-constructed heterogeneous feed thermodynamic characteristic feedforward mapping model, and calculates a theoretical heat demand; this step converts invisible component changes into quantitative physical heat value demand through thermodynamic modeling, thereby realizing advanced perception of heat load fluctuation;

[0072] The system performs frequency domain processing on the calculated theoretical heat demand using a sliding average filter, and separates out high-frequency fluctuation heat power; the purpose of this step is to decompose the total heat load into a low-frequency steady-state component borne by a main heating loop and a high-frequency transient component borne by a pulse system, so as to realize staged control;

[0073] At the same time, the system collects bed temperature using a high-frequency thermocouple arranged in a reaction zone, and calculates a differential of the bed temperature with respect to time to obtain a real-time change rate of the bed temperature;

[0074] After the above data is acquired, the system calculates heat shock compensation power in combination with the high-frequency fluctuation heat power and the real-time change rate of the bed temperature; this step introduces a feedback correction mechanism, which corrects the deviation of the feedforward prediction using bed thermal inertia, to ensure the accuracy of the control instruction;

[0075] The system pre-acquires a single pulse energy, which represents the effective heat enthalpy that can be injected by a single action of an actuator; based on the calculated heat shock compensation power and the single pulse energy, the system generates a theoretical pulse injection frequency, which represents the execution action rate required to meet the heat demand in an ideal fluidization state;

[0076] In order to prevent high-frequency injection from destroying the bed layer flow state, the system synchronously collects bed layer pressure drop data and calculates a fluidization quality factor based on the data; the fluidization quality factor is a statistical index for quantitatively representing the stability of a flow field; the system uses the fluidization quality factor to correct the theoretical pulse injection frequency, and generates a final execution frequency;

[0077] The system controls the heat carrier pulse injection system according to the final execution frequency, drives the electromagnetic valve group to inject high-temperature heat carriers into the reactor at a corresponding frequency, so as to maintain the temperature constant while guaranteeing the hydrodynamic stability of the fluidized bed layer; through the above steps, the pyrolysis reactor can improve the adaptability to complex feedstocks, and shorten the temperature control response time to the order of seconds.

[0078] Embodiment 2:

[0079] The real-time spectral data and the mass flow data are input into a feedstock thermodynamic characteristic feedforward mapping model, and a theoretical heat demand power is output, which is realized by the following mathematical model; including:

[0080] Based on the real-time spectral data, the material component distribution is analyzed and converted into component mass fractions;

[0081] The set target temperature of the reaction zone, the initial temperature of the feedstock, and the specific heat capacity and reaction enthalpy of each component are obtained;

[0082] Based on the component mass fraction, the set target temperature of the reaction zone, the initial temperature of the feedstock, the specific heat capacity, and the reaction enthalpy, the unit mass heat demand is calculated;

[0083] The unit mass heat demand is multiplied by the mass flow data to obtain the theoretical heat demand power;

[0084] In this embodiment, the real-time spectral data and the mass flow data are input into a feedstock thermodynamic characteristic feedforward mapping model and a theoretical heat demand power is output, which is realized by the following mathematical model;

[0085] Based on the real-time spectral data, the system uses a partial least squares regression model pre-trained based on historical spectral data and offline test data to analyze the material component distribution and convert it into the mass fraction of each component; at the same time, the system obtains the set target temperature of the reaction zone, the initial temperature of the feedstock, and the specific heat capacity and reaction enthalpy of each component from a database or a sensor; the system also obtains the material transmission lag time from the inlet to the center of the reaction zone ;

[0086] Based on the above parameters, the system calculates the theoretical heat demand power according to a prediction equation constructed based on the first law of thermodynamics :

[0087]

[0088] wherein, represents the instantaneous mass flow rate of the feed considering the transport lag time, is the total number of identified material components, represents the mass fraction of the i-th component calculated by spectral analysis at the corresponding time, is the preset transport lag constant in seconds, used to compensate for the time delay caused by the physical transmission distance between the belt scale and the reactor; is the specific heat capacity of the i-th component, is the reaction enthalpy of the i-th component, is the reaction enthalpy of the i-th component, is the target temperature of the reaction zone, is the initial temperature of the feed; Through this model, the system can take into account the large differences in the thermal chemical properties of different plastic components, especially accurately capturing the sudden change in thermal load caused by strong endothermic components such as PVC, thereby eliminating the hysteresis of traditional feedback control.

[0089] Example 3:

[0090] The theoretical heat demand is processed using a moving average filter to separate out the high-frequency fluctuating heat demand, including:

[0091] A preset sliding time window constant is obtained;

[0092] The integral average value of the theoretical heat demand within the sliding time window constant is calculated to obtain the low-frequency steady-state component;

[0093] The theoretical heat demand at the current time is subtracted from the low-frequency steady-state component to obtain the high-frequency fluctuating heat demand;

[0094] In this embodiment, the step of processing the theoretical heat demand using a moving average filter to separate out the high-frequency fluctuating heat demand specifically includes the following processes:

[0095] In this embodiment, the step of processing the theoretical heat demand using a moving average filter to separate out the high-frequency fluctuating heat demand specifically includes the following processes:

[0096] The system obtains a preset sliding time window constant , which is usually set to 1.2 to 1.5 times the main heat carrier circulation period of the reactor, aiming to cover and filter out the inherent periodic fluctuations of the system;

[0097] The system calculates the integral average value of the theoretical heat demand within the sliding time window constant, thereby obtaining the low-frequency steady-state component ; The system subtracts the low-frequency steady-state component from the theoretical heat demand at the current time to obtain the high-frequency fluctuating heat demand ; The calculation formula is as follows:

[0098] ​

[0099] wherein, represents the high-frequency fluctuation heat power, in units of watts, which represents the thermal shock load deviating from the steady state in real time; is the theoretical heat demand calculated in the previous step; is the integral variable;

[0100] This embodiment realizes the frequency domain decoupling of the thermal load, and the system sends the calculated low-frequency steady-state component to the main heating loop controller of the reactor as the reference power instruction for maintaining the basic heat balance; while the pulse system focuses on eliminating the high-frequency thermal shock, thereby improving the dynamic response performance of the system while ensuring energy efficiency.

[0101] Example 4:

[0102] The high-frequency fluctuation heat power and the real-time change rate of the bed temperature are combined to calculate the thermal shock compensation power, including:

[0103] The preset feedforward confidence coefficient and the preset feedback gain coefficient are obtained;

[0104] The total bed heat capacity in the effective heating zone of the reactor is obtained;

[0105] The product of the feedforward confidence coefficient and the high-frequency fluctuation heat power is calculated to obtain the feedforward term;

[0106] The product of the feedback gain coefficient, the total bed heat capacity, and the real-time change rate of the bed temperature is calculated to obtain the feedback correction term;

[0107] The feedforward term is subtracted by the feedback correction term to obtain the thermal shock compensation power;

[0108] In this embodiment, the step of calculating the thermal shock compensation power in combination with the high-frequency fluctuation heat power and the real-time change rate of the bed temperature adopts a composite control strategy combining feedforward and feedback;

[0109] The system obtains a preset feedforward confidence coefficient and a preset feedback gain coefficient ; wherein the value of the feedforward confidence coefficient is in the range of 0 to 1, and its value is positively correlated with the accuracy of spectral identification; and is usually taken as 1.0 to 1.2; the system simultaneously estimates the real-time mass of the bed based on the real-time collected bed pressure drop data and calculates the dynamic total bed heat capacity in the effective heating zone of the reactor based on the average specific heat capacity to reflect the real-time change of the material residence amount; the specific calculation steps are as follows: the system pre-stores the effective cross-sectional area of the reactor in square meters; the gravitational acceleration in meters per square second;

[0110] The instantaneous mass of the bed material is estimated by the formula Where is the weighted average specific heat capacity of the bed material; the system calculates the total heat capacity of the dynamic bed in the effective heating zone of the reactor based on real-time pressure drop data , which is calculated from the real-time estimated total mass of the material and heat carrier and the average specific heat capacity

[0111] In the specific calculation, the system obtains the heat shock compensation power according to the following formula

[0112]

[0113] Where, represents the heat compensation power required by the pulse system as the final instruction, in watts; is the high-frequency fluctuating heat power; is the real-time change rate of the bed temperature, in Kelvin per second;

[0114] The first term of the formula constitutes the feedforward term, which directly responds to changes in the feed; the second term constitutes the feedback correction term; when the actual temperature change of the bed does not match the feedforward prediction, the feedback term automatically corrects the compensation power to prevent excessive injection or insufficient response due to model errors, ensuring the robustness of the temperature control system.

[0115] Example 5:

[0116] Based on the heat shock compensation power and the single pulse energy, the theoretical pulse injection frequency is generated, including:

[0117] If the heat shock compensation power is less than or equal to zero, the theoretical pulse injection frequency is determined to be zero;

[0118] If the heat shock compensation power is greater than zero, the heat shock compensation power is divided by the single pulse energy to obtain a preliminary calculation frequency; to prevent the frequency from exceeding the hardware limit, the preliminary calculation frequency is compared with the preset maximum physical frequency limit , and the smaller value is taken as the theoretical pulse injection frequency; at the same time, in the division operation, if the single pulse energy is lower than the preset minimum energy threshold , then participates in the calculation to prevent the denominator from being too small;

[0119] In this embodiment, the step of generating the theoretical pulse injection frequency based on the heat shock compensation power and the single pulse energy uses variable frequency pulse modulation logic;

[0120] The system determines the heat shock compensation power​​ the numerical value of the thermal shock compensation power; if the thermal shock compensation power is less than or equal to zero, it means that the system is in a thermal surplus state or does not need high-frequency compensation, at this time the system determines the theoretical pulse injection frequency to be zero;

[0121] If the thermal shock compensation power is greater than zero, the system divides the thermal shock compensation power by the single pulse energy to calculate the theoretical pulse injection frequency; in order to prevent overflow and exceed the hardware response limit due to too small temperature difference, a minimum energy threshold is introduced and a maximum physical frequency limit ; the calculation logic is as follows:

[0122]

[0123] wherein, represents the theoretically required pulse injection frequency, in hertz; is the single pulse energy, in joules; is a preset maximum physical frequency limit, used to prevent exceeding the hardware response limit; is a preset minimum energy threshold, used to prevent overflow due to too small denominator;

[0124] This embodiment realizes one-way rectification control of on-demand heating, ensuring that high-temperature heat carrier pulses are triggered only when the system is lacking heat, avoiding control conflicts caused by logical inversion.

[0125] Example 6:

[0126] The fluidization quality factor is calculated based on bed pressure drop data, including:

[0127] The average pressure drop under normal fluidization state is obtained;

[0128] In a preset sliding statistical window, the square of the difference between the bed pressure drop data and the average pressure drop is calculated;

[0129] The integral mean of the square in the sliding statistical window is calculated and the square root operation is performed to obtain the pressure drop standard deviation, and the pressure drop standard deviation is divided by the average pressure drop to obtain the fluidization quality factor;

[0130] In this embodiment, the step of calculating the fluidization quality factor based on the bed pressure drop data aims to quantify the stability of the flow field in real time;

[0131] The system obtains the average pressure drop under normal fluidization state ; this parameter is obtained by collecting historical pressure drop data under stable fluidization state for a period of time and calculating the arithmetic mean during the system calibration stage;

[0132] During operation, the system calculates the square of the difference between the real-time collected bed pressure drop data and the average pressure drop in a preset sliding statistical window , calculates the integral mean of the square value in the window, then takes the square root of the integral mean to obtain the pressure drop standard deviation, and finally divides the pressure drop standard deviation by the average pressure drop to obtain the fluidization quality factor ; The calculation formula is as follows:

[0133]

[0134] , wherein is a dimensionless fluidization quality factor, and the larger the value is, the more violent the pressure drop fluctuation of the flow field is, in this model, it specifically refers to abnormal oscillation that deviates greatly from the normal bubbling fluidization characteristics, indicating the occurrence of serious channeling or burst slugging and other instability phenomena; is the time length of the sliding statistical window, in seconds; is the average pressure drop under normal fluidization state, is the real-time collected bed pressure drop data;

[0135] Through real-time monitoring of the index, the system can digitally perceive the fluid dynamics state of the bed, providing a quantitative basis for subsequent safety correction.

[0136] Example 7:

[0137] The fluidization quality factor is used to attenuate and correct the theoretical pulse injection frequency to generate the final execution frequency, including:

[0138] A preset fluidization instability critical threshold and a preset sensitivity gain coefficient are obtained;

[0139] The difference between the fluidization quality factor and the fluidization instability critical threshold is calculated;

[0140] Based on the difference and the sensitivity gain coefficient, an attenuation correction coefficient is calculated through a Logistic function;

[0141] The theoretical pulse injection frequency is multiplied by the attenuation correction coefficient to obtain the final execution frequency;

[0142] In this embodiment, the step of using the fluidization quality factor to attenuate and correct the theoretical pulse injection frequency to generate the final execution frequency is realized by introducing a Logistic smooth switch function;

[0143] The system obtains a preset fluidization instability critical threshold and a preset sensitivity gain coefficient ; is a safety upper limit set based on historical statistical data of the maximum allowed channeling coefficient of the device;​​ is a preset positive real number, used to control the sensitivity of the intervention of the suppression effect;

[0144] The system calculates the difference between the fluidization quality factor and the fluidization instability critical threshold, and calculates the final execution frequency based on the difference by the following formula :

[0145]

[0146] wherein, represents the final execution frequency sent to the electromagnetic valve, in hertz; is the theoretical pulse injection frequency; is a preset sensitivity gain coefficient, used to control the intervention rate of the suppression effect; is a preset fluidization instability critical threshold, is the fluidization quality factor calculated in the previous step;

[0147] The correction mechanism ensures that when the fluidization quality factor is less than the critical threshold , the correction coefficient is close to 1, and the system performs injection according to the theoretical demand; when the threshold is exceeded, indicating that the flow state is deteriorating, the correction coefficient quickly approaches 0, forcing the injection to be reduced or stopped; this adaptive attenuation strategy establishes a dynamic balance between meeting temperature control requirements and maintaining a stable flow state, effectively preventing the collapse of the fluidized bed caused by excessive injection.

[0148] Example 8:

[0149] Obtaining a preset single-pulse energy, comprising:

[0150] Obtaining the single injection heat transfer medium mass, the heat transfer medium specific heat capacity, the heat carrier tank temperature, the reaction zone set target temperature, and the gas-solid contact heat exchange efficiency factor;

[0151] Calculating the temperature difference between the heat carrier tank temperature and the reaction zone set target temperature;

[0152] Calculating the continuous product of the single injection heat transfer medium mass, the heat transfer medium specific heat capacity, the temperature difference, and the gas-solid contact heat exchange efficiency factor to obtain the single-pulse energy;

[0153] In this embodiment, the step of obtaining a preset single-pulse energy involves quantitative calculation of the physical characteristics of the actuator;

[0154] The system obtains the single injection heat transfer medium mass , the heat transfer medium specific heat capacity , the heat carrier tank temperature , the reaction zone set target temperature , and the gas-solid contact heat exchange efficiency factor ; wherein, is determined by the nozzle volume; is a dimensionless coefficient obtained by linear regression fitting of cold experiment data, usually taking a value between 0.8 and 0.9;

[0155] The system calculates the temperature difference between the heat carrier tank temperature and the set target temperature of the reaction zone, and then calculates the product of each parameter to obtain the single pulse energy :

[0156]

[0157] wherein, represents the effective heat released by a single pulse, in joules; is the mass of the heat conduction medium for a single injection, is the specific heat capacity of the heat conduction medium, is the heat carrier tank temperature, is the set target temperature of the reaction zone, is the gas-solid contact heat exchange efficiency factor;

[0158] This calculation process clearly defines the minimum energy resolution of the pulse injection system, converts continuous power requirements into discrete physical action energy values, and provides accurate quantitative benchmarks for frequency modulation.

[0159] Example 9:

[0160] Please refer to Figure 2 , a data acquisition module for acquiring real-time spectral data and mass flow data of mixed plastics at the inlet;

[0161] A heat enthalpy analysis module for inputting real-time spectral data and mass flow data into a heterogeneous feed thermodynamic characteristic feedforward mapping model and outputting theoretical required heat power;

[0162] A frequency domain filtering module for processing theoretical required heat power using a sliding average filter to separate out high-frequency fluctuation heat power;

[0163] A thermal shock compensation module for acquiring real-time rate of change of bed temperature and calculating thermal shock compensation power based on high-frequency fluctuation heat power and real-time rate of change of bed temperature;

[0164] A frequency modulation module for obtaining a preset single pulse energy and generating a theoretical pulse injection frequency based on thermal shock compensation power and single pulse energy;

[0165] A flow state correction module for acquiring bed pressure drop data and calculating fluidization quality factor, attenuating and correcting the theoretical pulse injection frequency using the fluidization quality factor to generate a final execution frequency, and controlling the heat carrier pulse injection system according to the final execution frequency;

[0166] The embodiment also provides a plastic staged pyrolysis temperature control system, which comprises a data acquisition module, a heat content analysis module, a frequency domain filtering module, a thermal shock compensation module, a frequency modulation module and a flow state correction module;

[0167] The data acquisition module is configured with a near-infrared spectrometer and a belt scale, and is used for performing the above-mentioned data acquisition step; the heat content analysis module integrates a processor, and is used for running a heterogeneous feed thermodynamic characteristic feedforward mapping model and outputting a theoretical heat demand power; the frequency domain filtering module is configured to process data by using a sliding average filter, and separate out a high-frequency fluctuation heat power; the thermal shock compensation module is connected with a bed temperature sensor, and is used for calculating a thermal shock compensation power in combination with a bed temperature change rate;

[0168] The frequency modulation module stores preset single-pulse energy parameters, and is responsible for generating a theoretical pulse injection frequency; the flow state correction module is connected with a differential pressure transmitter, and is used for monitoring a fluidization quality factor in real time and performing attenuation correction on the frequency, and finally outputs a control signal to a heat carrier pulse injection system; the modules of the system work cooperatively, and together realize high-precision and high-stability temperature control of a plastic pyrolysis process under complex working conditions.

[0169] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present application but not limit the present application. Although the present application has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present application can be modified or replaced equivalently without departing from the spirit and scope of the technical solutions of the present application.

Claims

1. A method for temperature control in the graded pyrolysis of plastics, characterized in that, include: Collect real-time spectral data and mass flow rate data of the mixed plastic at the feed inlet; Real-time spectral data and mass flow rate data are input into the feedforward mapping model of the thermodynamic characteristics of heterogeneous feed, and the theoretical heat demand is output. The theoretical heat power is processed by using a moving average filter to separate the high-frequency fluctuating heat power. Collect the real-time rate of change of bed temperature; The thermal shock compensation power is calculated by combining the high-frequency fluctuating thermal power with the real-time rate of change of bed temperature. Obtain the preset single pulse energy; Based on thermal shock compensation power and single-pulse energy, a theoretical pulse jet frequency is generated. Collect bed pressure drop data; Fluidization quality factor is calculated based on bed pressure drop data; The theoretical pulse jet frequency is attenuated and corrected using the fluidization quality factor to generate the final execution frequency. The heat transfer fluid pulse injection system is controlled based on the final execution frequency.

2. The method for temperature control in graded pyrolysis of plastics according to claim 1, characterized in that, Real-time spectral data and mass flow rate data are input into a feedforward mapping model of the thermodynamic characteristics of a heterogeneous feed, and the theoretical heat power required is output, including: Based on real-time spectral data, the material component distribution is analyzed and converted into component mass fraction; Obtain the target temperature of the reaction zone, the initial feed temperature, and the specific heat capacity and enthalpy of each component; Calculate the heat required per unit mass based on the component mass fraction, target temperature of the reaction zone, initial feed temperature, specific heat capacity, and enthalpy of reaction. Multiply the heat demand per unit mass by the mass flow rate data to obtain the theoretical heat demand power.

3. The method for temperature control in graded pyrolysis of plastics according to claim 1, characterized in that, Using a moving average filter to process the theoretically required heat power, high-frequency fluctuating heat power is separated, including: Obtain the preset sliding time window constant; The integral average value of the theoretically required heat power within the constant sliding time window is calculated to obtain the low-frequency steady-state component. Subtracting the low-frequency steady-state component from the theoretical heat power required at the current moment yields the high-frequency fluctuating heat power.

4. The method for temperature control in the graded pyrolysis of plastics according to claim 1, characterized in that, The thermal shock compensation power is calculated by combining the high-frequency fluctuating thermal power with the real-time rate of change of bed temperature, including: Obtain the preset feedforward confidence coefficient and the preset feedback gain coefficient; Obtain the total heat capacity of the bed within the effective heating zone of the reactor; The product of the feedforward confidence coefficient and the high-frequency fluctuating thermal power is calculated to obtain the feedforward term; The feedback correction term is obtained by multiplying the feedback gain coefficient, the total heat capacity of the bed, and the real-time temperature change rate of the bed. Subtracting the feedback correction term from the feedforward term yields the thermal shock compensation power.

5. The method for temperature control in the graded pyrolysis of plastics according to claim 1, characterized in that, Based on thermal shock compensation power and single-pulse energy, a theoretical pulse jet frequency is generated, including: If the thermal shock compensation power is less than or equal to zero, the theoretical pulse jet frequency is determined to be zero. If the thermal shock compensation power is greater than zero, divide the thermal shock compensation power by the single pulse energy to obtain the theoretical pulse jet frequency.

6. The method for controlling the temperature of graded pyrolysis of plastics according to claim 1, characterized in that, The fluidization quality factor is calculated based on bed pressure drop data, including: Obtain the average pressure drop under normal fluidization conditions; Within a preset sliding statistical window, calculate the square of the difference between the bed pressure drop data and the average pressure drop; Calculate the mean of the integral of the square over the sliding statistical window; Dividing the integral mean by the average pressure drop yields the fluidization quality factor.

7. The method for temperature control in the graded pyrolysis of plastics according to claim 1, characterized in that, The theoretical pulse jet frequency is attenuated and corrected using a fluidization quality factor to generate the final execution frequency, including: Obtain the preset fluidization instability critical threshold and the preset sensitivity gain coefficient; Calculate the difference between the fluidization quality factor and the critical threshold for fluidization instability; Based on the difference and sensitivity gain coefficient, the attenuation correction coefficient is calculated using the Logistic function; The final execution frequency is obtained by multiplying the theoretical pulse injection frequency by the attenuation correction factor.

8. The method for temperature control in graded pyrolysis of plastics according to claim 1, characterized in that, Obtain the preset single pulse energy, including: The mass of the heat transfer medium injected in a single operation, the specific heat capacity of the heat transfer medium, the temperature of the heat carrier tank, the target temperature of the reaction zone, and the gas-solid contact heat transfer efficiency factor are obtained. Calculate the temperature difference between the heat transfer fluid storage tank temperature and the set target temperature in the reaction zone; The single-pulse energy is obtained by multiplying the mass of the heat transfer medium in a single injection, the specific heat capacity of the heat transfer medium, the temperature difference, and the gas-solid contact heat transfer efficiency factor.

9. A temperature control system for graded pyrolysis of plastics, applied to the temperature control method for graded pyrolysis of plastics according to any one of claims 1-8, characterized in that, include: The data acquisition module is used to collect real-time spectral data and mass flow rate data of the mixed plastic at the feed inlet; The enthalpy analysis module is used to input real-time spectral data and mass flow rate data into the feedforward mapping model of the thermodynamic characteristics of heterogeneous feed and output the theoretical heat demand power. The frequency domain filtering module is used to process the theoretically required heat power using a moving average filter and separate out the high-frequency fluctuating heat power. The thermal shock compensation module is used to collect the real-time rate of change of bed temperature and calculate the thermal shock compensation power by combining the high-frequency fluctuating heat power with the real-time rate of change of bed temperature. The frequency modulation module is used to acquire the preset single pulse energy and generate the theoretical pulse jet frequency based on the thermal shock compensation power and the single pulse energy. The fluidization correction module is used to collect bed pressure drop data and calculate the fluidization quality factor. It uses the fluidization quality factor to attenuate and correct the theoretical pulse jet frequency, generate the final execution frequency, and control the heat carrier pulse jet system based on the final execution frequency.

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