Special cement production waste resource recycling system

Abstract

The invention discloses a special cement production waste resource recycling system, which belongs to the technical field of cement production waste treatment, and comprises a preprocessing module used for carrying out spectrum analysis and component detection on production waste to obtain a basic data set; the intelligent sorting module is used for dividing the waste into dangerous waste materials, conventional waste residues and heat value-containing waste materials according to the basic data set; the activating treatment module is used for performing plasma activation on the dangerous waste materials to generate building raw materials; the collaborative utilization module is used for doping the conventional waste residues into the raw materials and providing heat compensation by using heat value-containing waste materials; and the optimization control module is used for adjusting operation parameters of each module in real time and calculating an optimal recycling path. According to the method, the waste is subjected to accurate sorting, plasma activating treatment, cooperative utilization and optimal control, and efficient resource utilization of the waste is achieved.

Description

Technical Field

[0001] The invention relates to the technical field of cement production waste treatment, in particular to a resource recycling system for special cement production waste. Background Art

[0002] With the acceleration of the global industrialization process, cement production, as an industry with high energy consumption and high emissions, has increasingly severe problems in waste treatment and resource utilization. Special cements (such as low-alkali cement, oil well cement, nuclear power cement, etc.) have complex production processes and special raw material components, and the types of waste generated are diverse and contain heavy metals (such as chromium, nickel, etc.), high calorific value residues (such as unburned fuel) and difficult-to-degrade industrial waste slag. Traditional disposal methods are mainly landfill or incineration, which not only occupies land resources, but also causes environmental problems such as heavy metal leakage and greenhouse gas emissions, and the compliance cost of hazardous waste treatment is rising year by year.

[0003] At present, the cement industry attempts to realize resource utilization by replacing part of the raw materials or fuels with waste slag, but due to the complex composition of the waste and the low sorting accuracy, multiple technical bottlenecks need to be broken through. First, the efficiency of sorting technology is insufficient. Traditional methods rely on manual or mechanical screening, which makes it difficult to dynamically identify hazardous waste and waste with high calorific value. For example, the misjudgment of metal pollutants may lead to the volatilization of heavy metals during the subsequent calcination process, causing secondary pollution; the inefficient sorting of calorific waste leads to insufficient fuel substitution rate and cannot significantly reduce coal consumption. Secondly, the synergistic utilization technology is extensive. Conventional waste slag has large fluctuations in active components such as SiO2 and Al2O3. Direct addition to raw materials can easily cause mismatch of clinker mineral phases and reduce cement strength; and the calorific waste has large differences in pyrolysis characteristics from coal. Existing combustion control strategies (such as fixed PID parameters) are difficult to suppress the temperature fluctuations of the calcining kiln (fluctuation rate>5%), resulting in uneven clinker sintering and increased energy consumption. Summary of the invention

[0004] To solve the above problems, the present invention provides a resource recycling system for special cement production waste, which realizes efficient resource utilization of waste by precise sorting, plasma activation treatment, coordinated utilization and optimized control of waste.

[0005] The above objectives can be achieved through the following solutions:

[0006] The resource recycling system for special cement production waste includes: a pretreatment module, which is used to perform spectral analysis and component detection on production waste to obtain a basic data set; an intelligent sorting module, which is used to classify the waste into hazardous waste, conventional waste slag and waste containing calorific value according to the basic data set; an activation treatment module, which is used to perform plasma activation on the hazardous waste to generate building material raw materials; a collaborative utilization module, which is used to mix the conventional waste slag into raw materials and use the waste containing calorific value to provide heat compensation; and an optimization control module, which is used to adjust the operating parameters of each module in real time and calculate the optimal resource recovery path.

[0007] Optionally, the intelligent sorting module includes: a dynamic sorting unit, used to detect the metal content data of the waste according to the basic data set; a calorific value measurement unit, used to use a micro oxygen bomb calorimeter to perform rapid pyrolysis, measure the calorific value of the waste, and obtain calorific value data; a hazardous waste identification unit, used to classify the waste according to the metal content data and the calorific value data.

[0008] Optionally, the classification of waste according to the metal content data and the calorific value data includes: according to the metal content data, screening waste with a preset metal content value greater than a preset first threshold value to obtain hazardous waste; according to the calorific value data, screening waste with a calorific value greater than a preset second threshold value from the remaining waste to obtain calorific value-containing waste; marking the remaining waste and inputting it into a raw material batching bin to obtain conventional waste slag.

[0009] Optionally, the plasma activation of the hazardous waste includes: establishing an activation discriminant function for characterizing the activation intensity factor, and for the activation intensity factor α,

[0010]

[0011] Where n is the number of components to be tested in the hazardous waste, B i is the mass percentage of the i-th component to be detected in the hazardous waste, A i is the weight coefficient of the i-th component to be detected; using the basic data set, calculate the mass percentage of the components to be detected in the hazardous waste to obtain an input data set; input the input data set into the activation discriminant function to calculate the activation intensity factor of the hazardous waste; when the activation intensity factor is greater than a preset third threshold, increase the plasma power to a preset power for plasma activation; when the activation intensity factor is less than or equal to the third threshold and greater than a preset fourth threshold, use the rated power for plasma activation; when the activation intensity factor is less than or equal to the fourth threshold, the intermittent pulse interval is set to 0.5s.

[0012] Optionally, the adding of the conventional waste slag into the raw meal comprises: obtaining the content value of SiO2 in the conventional waste slag to obtain a first measurement value; calculating the replacement rate of the waste slag according to a preset reference value of the SiO2 content in the raw meal and the first measurement value, and for the replacement rate η, there is

[0013]

[0014] In the formula, λ is an adjustment parameter, x1 is the first measured value, and y is the preset reference value; the conventional waste residue is added to the raw meal using the substitution rate.

[0015] Optionally, the adding of the conventional waste residue into the raw meal further comprises: obtaining the C3S content value in the raw meal to obtain a second measurement value; using the second measurement value to calculate the adjustment parameter, and for the adjustment parameter λ,

[0016] λ=0.7+0.05*(x2―0.55),

[0017] In the formula, x2 is the second measurement value; wherein, when the replacement rate is greater than a preset fifth threshold, an early warning is issued.

[0018] Optionally, the real-time adjustment of the operating parameters of each module and the calculation of the optimal resource utilization path include: constructing a multi-objective optimization function for characterizing fitness, and for the fitness F, there is

[0019] F=0.4*K1+0.3*K2+0.2*K3+0.1*K4,

[0020] In the formula, K1 is economic benefit, K2 is carbon emission reduction rate, K3 is energy consumption ratio, and K4 is equipment loss; an initial process chain {1, sorting; 2, activation; 3, batching; 4, calcination} is established, and the processes in the initial process chain are cross-mutated to obtain an iterative process chain; the fitness of the iterative process chain is calculated using the multi-objective optimization function; when the fitness improvement amplitude corresponding to three consecutive generations of iterative process chains is less than a preset amplitude value, the current iterative process chain is output; wherein the fitness of multiple iterative process chains are arranged from large to small, and when the total number of iterations is greater than the preset number, the iteration is stopped, and the iterative process chain with the highest fitness ranking is selected.

[0021] Optionally, the heat compensation provided by using the calorific waste includes: setting a temperature target value of the calcination process and detecting the actual temperature value in real time; calculating a temperature deviation between the actual temperature value and the temperature target value; calculating an opening control parameter of a burner oil valve according to the temperature deviation value, and for the opening control parameter PID, there is

[0022]

[0023] In the formula, k p is the proportionality coefficient, k i is the integration time, k d is the differential coefficient, and T is the temperature deviation value.

[0024] Optionally, the use of the calorific value-containing waste to provide heat compensation further includes: collecting temperature fluctuation rate, pressure fluctuation rate and energy consumption increase rate; calculating the equipment status index according to the temperature fluctuation rate, the pressure fluctuation rate and the energy consumption increase rate, and for the equipment status index Z, there is

[0025] Z=0.1*σ T +1.5*σ P +2*σ E ,

[0026] In the formula, σ T is the temperature fluctuation rate, σ P is the pressure fluctuation rate, σ E is the energy consumption increase rate; when the equipment status index is greater than or equal to the preset sixth threshold, a red alarm is triggered, the production line is stopped urgently and the PID parameter self-tuning is started; when the equipment status index is greater than the preset seventh threshold and less than the sixth threshold, the proportional coefficient and the integral time are reset; when the equipment status index is less than or equal to the seventh threshold, the operating parameters are recorded in the normal operating condition library.

[0027] Optionally, the use of the calorific value-containing waste to provide heat compensation further includes: when the temperature fluctuation rate is sampled for three consecutive times and the value is greater than a preset fluctuation threshold, temporarily storing the current proportional coefficient and the integration time in a buffer register; switching to the standby proportional coefficient and the integration time in a preset order; starting the air cooling unit, wherein the wind speed V is set according to V=5*(σ T ―3) Perform dynamic adjustment; when the temperature fluctuation rate is less than or equal to 1 for 10 minutes, stop the air cooling unit; store the successful control parameter combination in a preset knowledge base.

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

[0029] 1. The present invention uses a pre-treatment module to perform spectral analysis and component detection on production waste, providing accurate basic data for subsequent classification and resource utilization; the intelligent sorting module can accurately classify waste into hazardous waste, conventional waste residue and calorific waste according to the basic data set, achieving effective classification and maximum utilization of resources.

[0030] 2. The present invention adopts plasma activation technology for treatment, which can not only effectively reduce its harmfulness, but also convert it into valuable building materials, thus achieving harmless treatment and resource utilization of hazardous waste;

[0031] 3. The collaborative utilization module mixes conventional waste slag into raw materials and uses waste materials with calorific value to provide heat compensation, which reduces dependence on traditional energy, reduces production costs and carbon emissions; the optimization control module further improves energy utilization efficiency and reduces energy consumption and carbon emissions by adjusting the operating parameters of each module in real time and calculating the optimal resource utilization path;

[0032] 4. The system of the present invention is highly intelligent and automated, and can automatically complete tasks such as waste classification, processing, utilization and monitoring, greatly reducing the complexity and cost of manual operations; the intelligent sorting module adopts advanced detection technology and algorithms, which can quickly and accurately complete the waste classification work, improving work efficiency and accuracy;

[0033] 5. The system of the present invention has high flexibility and scalability, and can adapt to the treatment needs of special cement production waste of different scales and types; the optimization control module adopts advanced technologies such as multi-objective optimization functions and iterative process chains, and can dynamically adjust system parameters and process flows according to actual conditions to achieve the calculation and execution of the optimal resource recovery path;

[0034] 6. In the process of using waste materials containing calorific value to provide heat compensation, the present invention also realizes the real-time monitoring and early warning function of the equipment status. By collecting indicators such as temperature fluctuation rate, pressure fluctuation rate and energy consumption increase rate, calculating the equipment status indicators, and triggering corresponding alarms and countermeasures according to the indicator values, the safe and stable operation of the production line is ensured.

[0035] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures pointed out in the description, claims and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0037] Figure 1 It is a framework diagram of a resource recycling system for special cement production waste according to an embodiment of the present invention.

[0038] Figure 2 It is a schematic diagram of the execution flow of the resource recycling system of special cement production waste in an embodiment of the present invention.

[0039] Figure 3 It is a structural schematic diagram of a resource recycling system for special cement production waste according to an embodiment of the present invention. DETAILED DESCRIPTION

[0040] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0041] Reference Figure 1 An embodiment of the present invention proposes a resource recycling system for special cement production waste, which realizes efficient resource utilization of waste by precise sorting, plasma activation treatment, coordinated utilization and optimized control of waste.

[0042] The system of this embodiment specifically includes:

[0043] The pre-processing module is used to perform spectral analysis and component detection on production waste to obtain a basic data set;

[0044] An intelligent sorting module, for sorting waste into hazardous waste, conventional waste residue and waste containing calorific value according to the basic data set;

[0045] An activation processing module, used for performing plasma activation on the hazardous waste to generate building material raw materials;

[0046] A collaborative utilization module, for mixing the conventional waste residue into raw materials and using the waste material containing calorific value to provide heat compensation;

[0047] The optimization control module is used to adjust the operating parameters of each module in real time and calculate the optimal resource utilization path.

[0048] Specifically, Figure 2As shown in the figure, the resource recycling system for waste from special cement production realizes efficient resource utilization of waste through the synergy of pretreatment module, intelligent sorting module, activation treatment module, collaborative utilization module and optimization control module. The pretreatment module obtains the basic data set through spectral analysis and component detection to provide data support for subsequent sorting. The intelligent sorting module classifies the waste according to the basic data set, improves the sorting accuracy, and avoids the misjudgment of hazardous waste and calorific value waste. The activation treatment module treats hazardous waste through plasma activation and converts it into usable building materials, reducing the environmental impact of hazardous waste. The collaborative utilization module mixes conventional waste slag into raw materials, uses calorific value waste to provide heat compensation, and improves resource utilization. The optimization control module calculates the optimal resource path by adjusting the operating parameters of each module in real time to ensure the efficient operation of the system. Through these technical means, the system can effectively solve the problem of resource recycling of waste in the production process of special cement.

[0049] Alternatively, if Figure 3 As shown, the intelligent sorting module includes:

[0050] A dynamic sorting unit, used for detecting metal content data of waste according to the basic data set;

[0051] The calorific value calculation unit is used to perform rapid pyrolysis using a micro oxygen bomb calorimeter to measure the calorific value of the waste and obtain calorific value data;

[0052] The hazardous waste identification unit is used to classify the waste according to the metal content data and the calorific value data.

[0053] Specifically, the intelligent sorting module achieves accurate sorting of waste through the cooperation of the dynamic sorting unit, the calorific value calculation unit and the hazardous waste identification unit. The dynamic sorting unit detects the metal content data of the waste, the calorific value calculation unit measures the calorific value of the waste, and the hazardous waste identification unit classifies the waste according to the metal content data and calorific value data, thereby solving the problem of complex waste composition and low sorting accuracy. Through the above means, the intelligent sorting module can efficiently and accurately identify and classify hazardous waste, conventional waste residue and calorific value waste, improving the efficiency and safety of waste resource utilization.

[0054] Exemplarily, the dynamic sorting unit can use advanced sensor technology and data analysis algorithms to monitor the metal components in the waste in real time. The calorific value measurement unit uses a micro oxygen bomb calorimeter to accurately measure the calorific value of the waste through a rapid pyrolysis method. The hazardous waste identification unit accurately classifies different types of waste by comprehensively analyzing the metal content data and calorific value data. Specifically, the dynamic sorting unit may include a highly sensitive metal detector and a data processing system, the calorific value measurement unit may use a high-precision micro oxygen bomb calorimeter and a pyrolysis device, and the hazardous waste identification unit may combine an artificial intelligence algorithm to automatically identify and classify waste. The intelligent sorting module of the present application not only improves the efficiency of waste resource utilization by accurately detecting and classifying waste, but also effectively reduces the risk of environmental pollution. Compared with the prior art, the intelligent sorting module of the present application has significant advantages in recognition accuracy and processing efficiency. Through the collaborative work of the dynamic sorting unit, the calorific value measurement unit and the hazardous waste identification unit, waste can be more accurately identified and classified, avoiding the waste of resources and environmental pollution caused by low sorting accuracy in traditional methods. Therefore, this application has important technical innovation and application value in waste treatment and resource utilization.

[0055] Optionally, the classifying the waste according to the metal content data and the calorific value data comprises:

[0056] According to the metal content data, waste having a preset metal content value greater than a preset first threshold is screened to obtain hazardous waste;

[0057] According to the calorific value data, waste having a calorific value greater than a preset second threshold value is screened out from the remaining waste to obtain waste containing calorific value;

[0058] The remaining waste is marked and input into the raw material batching bin to obtain conventional waste slag.

[0059] Specifically, waste is classified by metal content data and calorific value data. Metal content data is used to screen out waste containing metal content higher than a preset first threshold value, thereby identifying hazardous waste. Calorific value data is used to screen out waste with a calorific value higher than a preset second threshold value from the remaining waste, thereby identifying waste containing calorific value. Finally, the remaining waste is marked and input into the raw material batching bin to obtain conventional waste slag. The function of this technical feature is to improve the sorting accuracy, ensure the accurate classification of hazardous waste and waste containing calorific value, and avoid secondary pollution and waste of resources. This technical solution solves the problem of complex waste composition and low sorting accuracy by accurately measuring and classifying the metal content and calorific value data of the waste. Through this classification method, hazardous waste and waste containing calorific value can be effectively identified and processed, the efficiency of resource utilization can be improved, and environmental pollution can be reduced. The measurement of metal content data can adopt advanced spectral analysis technology, such as X-ray fluorescence spectrometer or plasma mass spectrometer, to ensure the accuracy and reliability of the data. The measurement of calorific value data can be carried out by rapid pyrolysis using a micro oxygen bomb calorimeter to ensure the efficiency and accuracy of the measurement. The screening process can be achieved through an automated control system to ensure the continuity and stability of the operation.

[0060] Exemplarily, wastes with a preset metal content greater than a preset first threshold value can be screened, and a dynamic sorting unit can be used for real-time detection, combined with an intelligent algorithm to automatically determine whether it is hazardous waste. The screening of calorific value data can be completed by a calorific value measurement unit, using rapid pyrolysis technology to measure the calorific value, and judged by a preset second threshold value. The marking of the remaining waste and the process of inputting it into the raw material batching bin can be completed by an automated marking system and a conveying system to ensure the efficiency and accuracy of the process. Therefore, the present application achieves high-precision sorting of waste by accurately measuring and classifying the metal content and calorific value data of the waste, ensuring the accurate classification of hazardous waste and calorific waste, and avoiding secondary pollution and waste of resources. Compared with the prior art, the present application improves the sorting accuracy, optimizes the efficiency of resource utilization, and solves the technical bottlenecks of complex waste composition and low sorting accuracy.

[0061] Optionally, the plasma activation of the hazardous waste comprises:

[0062] An activation discriminant function is established to characterize the activation intensity factor. For the activation intensity factor α,

[0063]

[0064] Where n is the number of components to be tested in the hazardous waste, B i is the mass percentage of the i-th component to be detected in the hazardous waste, A i is the weight coefficient of the i-th component to be detected;

[0065] Using the basic data set, calculating the mass percentage of the components to be detected in the hazardous waste to obtain an input data set;

[0066] Inputting the input data set into the activation discriminant function to calculate the activation intensity factor of the hazardous waste;

[0067] When the activation intensity factor is greater than a preset third threshold, increasing the plasma power to a preset power for plasma activation;

[0068] When the activation intensity factor is less than or equal to the third threshold value and greater than a preset fourth threshold value, plasma activation is performed using rated power;

[0069] When the activation intensity factor is less than or equal to the fourth threshold, the intermittent pulse interval is set to 0.5 s.

[0070] Specifically, these technical features cooperate with each other to achieve optimized control of the plasma activation process of hazardous waste, ensuring the harmless treatment of hazardous waste and the quality of building materials. Through the above scheme, the problem of how to optimize the technical parameters of plasma activation is solved. An activation discriminant function is established, and the activation intensity factor is calculated according to the mass percentage of the hazardous waste components, and then the power and pulse interval of plasma activation are adjusted to ensure the harmless treatment of hazardous waste and the quality of building materials.

[0071] Specifically, the activation discriminant function can be established by collecting a large amount of hazardous waste sample data and performing multivariate regression analysis to determine the weight coefficient A of each component. i. Specifically, the chemical analysis method can be used to determine the mass percentage of each component in the hazardous waste, and the weight coefficient can be optimized in combination with the experimental data and the actual treatment effect to improve the accuracy of the discriminant function. The calculation of the activation intensity factor can be realized by writing a computer program, inputting the mass percentage of the hazardous waste components, and automatically calculating the activation intensity factor. For the adjustment of power and pulse interval during plasma activation, an automatic control system can be used to adjust the power and pulse parameters of the plasma generator in real time according to the calculated activation intensity factor. For example, when the activation intensity factor is greater than the preset third threshold, the control system automatically increases the power to the preset value and maintains stability; when the activation intensity factor is less than or equal to the third threshold and greater than the preset fourth threshold, the control system adjusts the power to the rated value; when the activation intensity factor is less than or equal to the fourth threshold, the control system sets the pulse interval to 0.5 seconds to ensure the activation effect. Therefore, the present application achieves optimized control of the hazardous waste treatment process by establishing an activation discriminant function, calculating the activation intensity factor of the hazardous waste, and adjusting the power and pulse interval of plasma activation according to different intensity factor intervals. Compared with the prior art, the present application can more accurately control the plasma activation parameters, improve the harmless treatment effect of hazardous waste, and ensure the quality of the generated building materials. This method not only improves the treatment efficiency, but also reduces the treatment cost, and has significant technical advantages.

[0072] Optionally, the adding the conventional waste residue into raw meal comprises:

[0073] Obtaining the content value of SiO2 in the conventional waste slag to obtain a first measurement value;

[0074] According to the preset reference value of SiO2 content in the raw material and the first measured value, the replacement rate of the waste slag is calculated. For the replacement rate η, there is

[0075]

[0076] Wherein, λ is the adjustment parameter, x1 is the first measured value, and y is the preset reference value;

[0077] The conventional waste residue is incorporated into the raw meal using the substitution ratio.

[0078] Specifically, the content value of SiO2 in conventional waste slag is obtained, the substitution rate of the waste slag is calculated, and the conventional waste slag is added to the raw meal using the substitution rate. These technical features play a key role in solving the problem of calculating the substitution rate when conventional waste slag is added to the raw meal. By obtaining the content value of SiO2 in conventional waste slag, the composition of the waste slag can be accurately understood; when calculating the substitution rate, the adjustment parameters, measurement values ​​and preset benchmark values ​​are considered to ensure the rationality of the substitution rate; conventional waste slag is added to the raw meal using the substitution rate to ensure the quality and characteristics of the raw meal.

[0079] For example, first, the SiO2 content value in the conventional waste slag needs to be obtained, which can be achieved by chemical analysis or spectral analysis. The measured SiO2 content value is used as the first measured value. Then, according to the preset reference value of the SiO2 content in the raw material and the first measured value, the formula The substitution rate of the waste residue is calculated. The adjustment parameter λ can be set according to the specific production conditions to ensure that the calculated substitution rate is reasonable and applicable. Finally, the conventional waste residue is mixed with the raw material using the calculated substitution rate, thereby realizing the effective utilization of the waste residue. Therefore, through the technical solution of the present application, the substitution rate of the waste residue can be accurately calculated, and the waste residue can be reasonably used to be mixed with the raw material, thus solving the problem of calculating the substitution rate when the conventional waste residue is mixed with the raw material. Compared with the prior art, the technical solution of the present application can more accurately understand the composition of the waste residue, ensure the rationality of the substitution rate, and then ensure the quality and characteristics of the raw material, effectively improve the utilization rate of the waste residue, reduce production costs, and reduce environmental pollution.

[0080] Optionally, the adding the conventional waste residue into raw meal further comprises:

[0081] Obtaining the C3S content in the raw material to obtain a second measurement value;

[0082] The adjustment parameter is calculated using the second measurement value. For the adjustment parameter λ,

[0083] λ=0.7+0.05*(x2―0.55),

[0084] Wherein, x2 is the second measured value;

[0085] When the replacement rate is greater than a preset fifth threshold, an early warning is issued.

[0086] Specifically, the C3S content value in the raw material is obtained, the adjustment parameter λ is calculated, and an early warning is issued when the replacement rate is greater than a preset threshold. The C3S content value in the raw material is obtained, and the composition information of the current raw material can be provided. The adjustment parameter λ is calculated using the composition information, so that the replacement rate can be dynamically adjusted when conventional waste slag is added to ensure that the clinker minerals match. When the replacement rate exceeds the preset threshold, the system will issue an early warning to prompt the operator to make adjustments, thereby avoiding the problem of clinker mineral phase mismatch caused by component fluctuations. The above scheme can solve the problem of clinker mineral phase mismatch caused by component fluctuations when conventional waste slag is added to raw materials. The C3S content value in the raw material is obtained, and the adjustment parameter λ is calculated, so that the waste slag replacement rate can be dynamically adjusted to ensure that the clinker minerals match, thereby improving the quality and performance of cement.

[0087] For example, to obtain the C3S content value in the raw material, an X-ray fluorescence spectrometer (XRF) analyzer can be used for measurement, which has high accuracy and reliability. The calculation of the adjustment parameter can be achieved by writing a corresponding algorithm program, and the program can be embedded in the control system to automatically complete the calculation and adjustment. The early warning function can be achieved by setting a threshold monitoring system. When the replacement rate exceeds the preset threshold, the system will automatically send an alarm signal to remind the operator to make necessary adjustments. In addition, artificial intelligence technology can be introduced to continuously optimize the calculation model of the adjustment parameter λ through a machine learning algorithm to improve the intelligence level and response speed of the system.

[0088] Optionally, the real-time adjustment of operating parameters of each module and calculation of the optimal resource utilization path includes:

[0089] Construct a multi-objective optimization function for characterizing fitness. For the fitness F, there is

[0090] F=0.4*K1+0.3*K2+0.2*K3+0.1*K4,

[0091] In the formula, K1 is the economic benefit, K2 is the carbon emission reduction rate, K3 is the energy consumption ratio, and K4 is the equipment loss;

[0092] Establishing an initial process chain {1. sorting; 2. activation; 3. batching; 4. calcination}, cross-mutating the processes in the initial process chain to obtain an iterative process chain;

[0093] Calculating the fitness of the iterative process chain using the multi-objective optimization function;

[0094] When the fitness improvement corresponding to three consecutive generations of iterative process chains is less than the preset value, the current iterative process chain is output;

[0095] The fitness of the multiple iterative process chains are arranged from large to small, and when the total number of iterations is greater than a preset number, the iteration is stopped, and the iterative process chain with the highest fitness ranking is selected.

[0096] Specifically, when constructing a multi-objective optimization function, the influence of various factors on the system is comprehensively considered through the allocation of weight coefficients to achieve a balance of optimization objectives. The initial process chain is established, including four processes: sorting, activation, batching, and calcination. Through cross-mutation, the processes in the initial process chain are arranged and combined to generate different iterative process chains. The fitness value of each iterative process chain is calculated using the constructed multi-objective optimization function. When the fitness improvement of three consecutive generations of iterative process chains is less than the preset value, the current iterative process chain is output. In order to ensure the effectiveness of the optimization process, the fitness of multiple iterative process chains is arranged from large to small. When the total number of iterations is greater than the preset number, the iteration is stopped, and the iterative process chain with the first fitness ranking is selected as the final output. Through the above technical solution, the present application can realize real-time adjustment of the operating parameters of each module and calculate the optimal resource utilization path, and solves the technical problem of how to adjust the operating parameters of each module in real time and calculate the optimal resource utilization path. Compared with the prior art, the present application can more effectively balance economic benefits, carbon emission reduction rate, energy consumption ratio and equipment loss through multi-objective optimization functions and fitness calculation of iterative process chains, thereby improving the overall optimization effect of the system.

[0097] Optionally, the using the waste material containing calorific value to provide heat compensation comprises:

[0098] Set the temperature target value of the calcination process and detect the actual temperature value in real time;

[0099] Calculating a temperature deviation between the actual temperature value and the temperature target value;

[0100] The opening control parameter of the burner oil valve is calculated according to the temperature deviation value. For the opening control parameter PID, there is:

[0101]

[0102] In the formula, k p is the proportionality coefficient, k i is the integration time, k d is the differential coefficient, and T is the temperature deviation value.

[0103] Specifically, the temperature target value of the calcining process is set, and the actual temperature value is detected in real time; the temperature deviation value between the actual temperature value and the temperature target value is calculated; the opening control parameter of the burner oil valve is calculated according to the temperature deviation value, and the temperature is adjusted using the PID control algorithm, thereby solving the problem of unstable temperature control in the calcining process. Through this technical solution, calorific waste can be effectively used to provide heat compensation, ensure the temperature stability of the calcining process, and avoid the impact of temperature fluctuations on clinker sintering and energy consumption.

[0104] Specifically, temperature detection can use high-precision temperature sensors to monitor temperature changes in the calcination process in real time. The PID control algorithm can be implemented through programming to control the opening of the burner oil valve, adjust the heat input, and ensure temperature stability. Specifically, the PID parameters can be set in the control system, and the optimal proportional coefficient, integral time, and differential coefficient can be determined through experiments and debugging to achieve the best temperature control effect.

[0105] Exemplarily, the calculation of the temperature deviation value can adopt digital filtering technology to reduce the impact of noise on temperature detection and improve the accuracy of temperature control. The PID control algorithm can adopt adaptive adjustment technology to dynamically adjust the PID parameters according to the actual operating conditions to further improve the stability and response speed of temperature control. The technical solution of the present application realizes the precise control of temperature in the calcination process by using waste materials containing calorific value to provide heat compensation, and solves the problem of unstable temperature control. Compared with the prior art, the present application has the following advantages: first, through real-time detection and PID control algorithm, it can quickly respond to temperature changes and keep the temperature stable; second, by using waste materials containing calorific value to provide heat compensation, it improves resource utilization and reduces energy consumption; finally, by adaptively adjusting PID parameters, the accuracy and stability of temperature control are further improved. Therefore, the technical solution of the present application has significant advantages in improving the stability of temperature control in the calcination process.

[0106] Optionally, the step of using the waste material containing calorific value to provide heat compensation further comprises:

[0107] Collect temperature fluctuation rate, pressure fluctuation rate and energy consumption increase rate;

[0108] The equipment status index is calculated according to the temperature fluctuation rate, the pressure fluctuation rate and the energy consumption increase rate. For the equipment status index Z, there is

[0109] Z=0.1*σ T +1.5*σ P +2*σ E ,

[0110] In the formula, σ T is the temperature fluctuation rate, σ P is the pressure fluctuation rate, σ E is the energy consumption increase rate;

[0111] When the equipment status indicator is greater than or equal to a preset sixth threshold, a red alarm is triggered, the production line is stopped urgently and PID parameter self-tuning is started;

[0112] When the device status indicator is greater than a preset seventh threshold value and less than the sixth threshold value, resetting the proportional coefficient and the integration time;

[0113] When the equipment status indicator is less than or equal to the seventh threshold, the operating parameters are recorded in the normal operating condition library.

[0114] Specifically, the present application includes collecting temperature fluctuation rate, pressure fluctuation rate and energy consumption increase rate, and calculating equipment status indicators; when the equipment status indicator is greater than or equal to the preset sixth threshold, a red alarm is triggered, the production line is stopped urgently and PID parameter self-tuning is started; when the equipment status indicator is greater than the preset seventh threshold and less than the sixth threshold, the proportional coefficient and integral time are reset; when the equipment status indicator is less than or equal to the seventh threshold, the operating parameters are recorded in the normal operating condition library. These technical features can take corresponding measures in a timely manner when abnormal fluctuations occur in the equipment status by real-time monitoring and calculation of equipment status indicators, such as emergency stopping of the production line, starting PID parameter self-tuning or resetting the proportional coefficient and integral time, thereby effectively solving the problem of equipment status fluctuations in the process of providing heat compensation for calorific waste and ensuring stable operation of the system.

[0115] Exemplarily, the collection of temperature fluctuation rate, pressure fluctuation rate and energy consumption increase rate can be achieved by installing corresponding sensors and data acquisition systems. The temperature fluctuation rate sensor can be installed in the waste combustion area, the pressure fluctuation rate sensor can be installed in the combustion chamber, and the energy consumption increase rate sensor can be installed at the energy input end. Secondly, the equipment status index can be calculated by writing a corresponding algorithm and inputting the collected data into the formula for calculation. Finally, according to the different intervals of the equipment status index, take corresponding measures. For example, when the equipment status index is greater than or equal to the preset sixth threshold, the system will automatically trigger a red alarm and stop the production line, and start the PID parameter self-tuning function at the same time; when the equipment status index is greater than the preset seventh threshold and less than the sixth threshold, the system will reset the proportional coefficient and integral time; when the equipment status index is less than or equal to the seventh threshold, the system will record the operating parameters to the normal operating condition library. This application can timely detect abnormal fluctuations in the equipment status by real-time monitoring of the temperature fluctuation rate, pressure fluctuation rate and energy consumption increase rate, and calculate the equipment status index, and take corresponding countermeasures to ensure the stable operation of the system. Compared with the prior art, the present application can more effectively solve the problem of equipment state fluctuations in the process of heat compensation provided by calorific waste, and improve the stability and safety of the system. Specifically, by introducing the calculation and monitoring of equipment state indicators, the present application can more accurately judge the changes in equipment state and take corresponding measures to make adjustments, thereby avoiding the problem of production line shutdown or increased energy consumption caused by equipment state fluctuations. Therefore, while improving the stability and safety of the system, the present application also improves the effect of waste resource utilization.

[0116] Optionally, the step of using the waste material containing calorific value to provide heat compensation further comprises:

[0117] When the temperature fluctuation rate sampling values ​​are greater than the preset fluctuation threshold for three consecutive times, the current proportional coefficient and the integration time are temporarily stored in a buffer register;

[0118] Switching to the standby proportional coefficient and the standby integral time in a preset order;

[0119] Start the air-cooled unit, where the wind speed V is V = 5*(σ T 3) Perform dynamic adjustments;

[0120] When the temperature fluctuation rate is less than or equal to 1 for 10 minutes, the air cooling unit is stopped;

[0121] The successful control parameter combination is stored in the preset knowledge base.

[0122] Specifically, when the temperature fluctuation rate continuously exceeds the preset threshold, the current proportional coefficient and integral time are temporarily stored and switched to the backup parameters; the air-cooling unit is started and the wind speed is dynamically adjusted; when the temperature fluctuation rate returns to normal, the air-cooling unit is stopped, and the successful control parameters are stored in the knowledge base. These technical features work together to solve the problem of excessive temperature fluctuation rate of calorific waste in the process of providing heat compensation. This solution can effectively control temperature fluctuations and ensure the stability and energy efficiency of the calcination process by dynamically adjusting PID parameters and starting the air-cooling unit. At the same time, successful parameter combinations are recorded in the knowledge base, which provides a reference for future regulation and further improves the intelligence level of the system.

[0123] Specifically, when the temperature fluctuation rate is sampled for three consecutive times and the value is greater than the preset fluctuation threshold, the current proportional coefficient and integral time are temporarily stored in the buffer register. This step ensures that when the temperature fluctuation rate is too high, the system can save the current control parameters for subsequent adjustment. Switch to the spare proportional coefficient and integral time in the preset order. This step enables the system to quickly switch to the spare parameters to avoid further increase in the temperature fluctuation rate. Start the air-cooled unit, and dynamically adjust the wind speed according to the temperature fluctuation rate. Adjust it through the formula to ensure that the wind speed can respond to temperature changes in time. When the temperature fluctuation rate is less than or equal to 1 for 10 minutes, stop the air-cooled unit, indicating that the temperature has stabilized. The successful control parameter combination is stored in the preset knowledge base for reference in similar situations in the future. The present application can effectively control temperature fluctuations and ensure the stability and energy efficiency of the calcination process by dynamically adjusting the PID parameters and the start-up of the air-cooled unit. Compared with the prior art, the advantage of the present application is that it can respond to temperature fluctuations in real time, avoiding the limitations of the traditional fixed parameter method. The successful parameter combination is recorded in the knowledge base, which provides a reference for future regulation and further improves the intelligence level of the system. Therefore, the present application has significant technical advantages in solving the problem of excessively high temperature fluctuation rate of calorific waste in the process of providing heat compensation.

[0124] It should be noted that the electrical connection between the above-mentioned units does not necessarily mean direct connection of the lines, and the indirect connection mode can be applied to the embodiments of the present invention as long as the purpose of the present invention is achieved. The above is only an exemplary embodiment of the present invention and cannot be used to limit the scope of the present invention.

[0125] That is, any equivalent changes and modifications made according to the teachings of the present invention are still within the scope of the present invention. After considering the disclosure of the specification and the truth of practice, those skilled in the art will easily think of other embodiments of the present invention. This application is intended to cover any variation, use or adaptive change of the present invention, which follows the general principles of the present invention and includes common knowledge or customary technical means in the art that are not described in the present invention.

Claims

1. The resource recycling system of special cement production waste is characterized by: The system comprises: The pre-processing module is used to perform spectral analysis and component detection on production waste to obtain a basic data set; An intelligent sorting module, used for classifying waste into hazardous waste, conventional waste residue and waste containing calorific value according to the basic data set; An activation processing module, used for performing plasma activation on the hazardous waste to generate building material raw materials; A collaborative utilization module, used for mixing the conventional waste residue into raw materials and using the waste material containing calorific value to provide heat compensation; The optimization control module is used to adjust the operating parameters of each module in real time and calculate the optimal resource utilization path.

2. The resource recycling system for special cement production waste according to claim 1 is characterized in that: The intelligent sorting module comprises: A dynamic sorting unit, used for detecting metal content data of waste according to the basic data set; The calorific value calculation unit is used to perform rapid pyrolysis using a micro oxygen bomb calorimeter to measure the calorific value of the waste and obtain calorific value data; The hazardous waste identification unit is used to classify the waste according to the metal content data and the calorific value data.

3. The resource recycling system for special cement production waste according to claim 2 is characterized in that: The classifying of waste according to the metal content data and the calorific value data comprises: According to the metal content data, waste having a preset metal content value greater than a preset first threshold value is screened to obtain hazardous waste; According to the calorific value data, waste having a calorific value greater than a preset second threshold value is screened out from the remaining waste to obtain waste containing calorific value; The remaining waste is marked and input into the raw material batching bin to obtain conventional waste slag.

4. The resource recycling system for special cement production waste according to claim 1 is characterized in that: The plasma activation of the hazardous waste comprises: An activation discriminant function is established to characterize the activation intensity factor. For the activation intensity factor α, Where n is the number of components to be tested in the hazardous waste, B i is the mass percentage of the i-th component to be detected in the hazardous waste, A i is the weight coefficient of the i-th component to be detected; Using the basic data set, calculating the mass percentage of the components to be detected in the hazardous waste to obtain an input data set; Inputting the input data set into the activation discriminant function to calculate the activation intensity factor of the hazardous waste; When the activation intensity factor is greater than a preset third threshold, increasing the plasma power to a preset power for plasma activation; When the activation intensity factor is less than or equal to the third threshold value and greater than a preset fourth threshold value, plasma activation is performed using rated power; When the activation intensity factor is less than or equal to the fourth threshold, the intermittent pulse interval is set to 0.5 s.

5. The resource recycling system for special cement production waste according to claim 1 is characterized in that: The adding of the conventional waste residue into the raw material comprises: Obtaining the content value of SiO2 in the conventional waste slag to obtain a first measurement value; According to the preset reference value of SiO2 content in the raw material and the first measured value, the replacement rate of the waste slag is calculated. For the replacement rate η, there is Wherein, λ is the adjustment parameter, x1 is the first measured value, and y is the preset reference value; The conventional waste residue is incorporated into the raw meal using the substitution ratio.

6. The resource recycling system for special cement production waste according to claim 5 is characterized in that: The adding of the conventional waste residue into the raw meal also includes: Obtaining the C3S content in the raw material to obtain a second measurement value; The adjustment parameter is calculated using the second measurement value. For the adjustment parameter λ, λ=0.7+0.05*(x2―0.55), Wherein, x2 is the second measured value; When the replacement rate is greater than a preset fifth threshold, an early warning is issued.

7. The resource recycling system for special cement production waste according to claim 1 is characterized in that: The real-time adjustment of the operating parameters of each module and the calculation of the optimal resource utilization path include: Construct a multi-objective optimization function for characterizing fitness. For the fitness F, there is F=0.4*K1+0.3*K2+0.2*K3+0.1*K4, In the formula, K1 is the economic benefit, K2 is the carbon emission reduction rate, K3 is the energy consumption ratio, and K4 is the equipment loss; Establishing an initial process chain {1. sorting; 2. activation; 3. batching; 4. calcination}, cross-mutating the processes in the initial process chain to obtain an iterative process chain; Calculating the fitness of the iterative process chain using the multi-objective optimization function; When the fitness improvement corresponding to three consecutive generations of iterative process chains is less than the preset value, the current iterative process chain is output; The fitness of the multiple iterative process chains are arranged from large to small, and when the total number of iterations is greater than a preset number, the iteration is stopped, and the iterative process chain with the highest fitness ranking is selected.

8. The resource recycling system for special cement production waste according to claim 1 is characterized in that: The use of the waste material containing calorific value to provide heat compensation comprises: Set the temperature target value of the calcination process and detect the actual temperature value in real time; Calculating a temperature deviation between the actual temperature value and the temperature target value; The opening control parameter of the burner oil valve is calculated according to the temperature deviation value. For the opening control parameter PID, there is: In the formula, k p is the proportionality coefficient, k i is the integration time, k d is the differential coefficient, and T is the temperature deviation value.

9. The resource recycling system for special cement production waste according to claim 8, characterized in that: The use of the waste material containing calorific value to provide heat compensation also includes: Collect temperature fluctuation rate, pressure fluctuation rate and energy consumption increase rate; The equipment status index is calculated according to the temperature fluctuation rate, the pressure fluctuation rate and the energy consumption increase rate. For the equipment status index Z, there is Z=0.1*σ T +1.5*s P +2*s E , In the formula, σ T is the temperature fluctuation rate, σ P is the pressure fluctuation rate, σ E is the energy consumption increase rate; When the equipment status indicator is greater than or equal to a preset sixth threshold, a red alarm is triggered, the production line is stopped urgently and PID parameter self-tuning is started; When the device status indicator is greater than a preset seventh threshold value and less than the sixth threshold value, resetting the proportional coefficient and the integration time; When the equipment status indicator is less than or equal to the seventh threshold, the operating parameters are recorded in the normal operating condition library.

10. The resource recycling system for special cement production waste according to claim 9, characterized in that: The use of the waste material containing calorific value to provide heat compensation also includes: When the temperature fluctuation rate sampling values ​​are greater than the preset fluctuation threshold for three consecutive times, the current proportional coefficient and the integration time are temporarily stored in a buffer register; Switching to the standby proportional coefficient and the standby integral time in a preset order; Start the air-cooled unit, where the wind speed V is V = 5*(σ T 3) Perform dynamic adjustments; When the temperature fluctuation rate is less than or equal to 1 for 10 minutes, the air cooling unit is stopped; The successful control parameter combination is stored in the preset knowledge base.

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