Method for efficiently converting solid waste into renewable energy sources and real-time detection and maintenance system thereof

Abstract

The invention discloses a method for efficiently converting solid waste into renewable energy sources and a real-time detection and maintenance system thereof, and the system specifically comprises an abnormal monitoring parameter obtaining module which is used for collecting flue gas monitoring parameters in real time in the waste incineration process, carrying out the analysis and judgment, generating flue gas monitoring parameter abnormal signals, obtaining abnormal flue gas monitoring parameters, and sending the abnormal flue gas monitoring parameters to a control module; determining an abnormal degree sorting table; and the abnormal monitoring parameter acquisition module is used for acquiring flue gas monitoring parameters in real time in the waste incineration process, analyzing and judging the flue gas monitoring parameters and generating flue gas monitoring parameter abnormal signals. According to the method, by determining the optimization parameter sorting table, determining the priority adjustment parameters and adjusting the priority adjustment parameters, manpower, material resources or time and other resources invested for adjusting all abnormal parameters at the same time can be reduced, the parameters which have the largest influence on the system are adjusted preferentially, the abnormal problem can be solved step by step on the premise that the system stability is guaranteed, and the efficiency is improved. The parameter with the largest influence is adjusted preferentially, and the performance improvement of the system can be seen more quickly.

Description

Technical Field

[0001] The present invention relates to the technical field of solid waste conversion, and in particular to a method for efficiently converting solid waste into renewable energy and a real-time detection and maintenance system thereof. Background Art

[0002] Solid waste resource utilization refers to a technical method that takes management and process measures to recover materials and energy from solid waste, accelerates the circulation of materials and energy, and creates a wide range of economic value. Solid waste resource utilization is the main destination of solid waste. With the rapid development of the world economy and the continuous acceleration of urbanization, the output of solid waste, especially urban domestic waste, is increasing, and the pollution to the environment is becoming increasingly serious. In the new century of sustainable development, the application and industrialization of solid waste resource treatment technology, especially waste incineration power generation technology, will have broad prospects;

[0003] However, although the pollutant content in flue gas emissions is currently monitored in real time during the waste incineration power generation process, when it is found that the content of some pollutants is too high, it is difficult to promptly discover and identify abnormal components in the flue gas and their related influencing parameters, which leads to prolonged troubleshooting time and low equipment maintenance efficiency. At the same time, after the relevant influencing parameters are found, all relevant influencing parameters are often adjusted, consuming a lot of manpower, material and time resources, and may cause new environmental problems due to improper adjustment. The lack of targeted optimization of parameter sorting and priority adjustment strategies makes resource processing inefficient and difficult to meet the needs of sustainable development. Summary of the invention

[0004] The object of the present invention is to provide a highly efficient solid waste conversion method for renewable energy and a real-time detection and maintenance system thereof, so as to solve at least one of the above-mentioned prior art problems.

[0005] In a first aspect, the present invention provides a real-time detection and maintenance system for efficient solid waste conversion to renewable energy, the system specifically comprising:

[0006] Abnormal monitoring parameter acquisition module: During the waste incineration process, the flue gas monitoring parameters are collected in real time, analyzed and judged, and abnormal signals of flue gas monitoring parameters are generated, abnormal flue gas monitoring parameters are obtained, and the abnormal degree ranking table is determined;

[0007] Influencing parameter screening module: Based on the abnormal smoke monitoring parameters, the correlation calculation method is used in combination with the abnormal overlap duration to output the relevant impact degree value and determine the abnormal impact parameters of the abnormal smoke monitoring parameters;

[0008] The process of obtaining the relevant impact value is as follows:

[0009] Analyze the abnormal smoke monitoring parameters and influencing parameters, calculate the total overlap duration ratio and the correlation value, and process the data according to the total overlap duration ratio and the correlation value to obtain the correlation influence value;

[0010] Optimization parameter determination module: Based on the abnormal influencing parameters, analyze the abnormal flue gas monitoring parameters corresponding to the abnormal influencing parameters, determine the optimization parameter ranking table, and determine the priority adjustment parameters;

[0011] Among them, the process of determining the optimization parameter sorting table is:

[0012] Perform weighted sum calculation on the relevant impact degree values ​​of the abnormal impact parameters and the number of abnormal smoke monitoring parameters to obtain a ranking value, and determine an optimized parameter ranking table based on the ranking value;

[0013] Optimization parameter adjustment module: Based on the priority adjustment parameters, adjustments are made to optimize the abnormal monitoring parameters.

[0014] In a second aspect, the present invention provides a method for efficiently converting solid waste into renewable energy, characterized in that the method is used to implement the system described in any one of claims 1 to 9 above, and the method comprises:

[0015] Flue gas purification system: the flue gas at the outlet of the waste heat boiler is deacidified in a semi-dry reaction tower and then enters a bag filter. The pipeline connecting the semi-dry reaction tower and the bag filter is provided with a slaked lime injection port and an activated carbon injection port. The flue gas discharged from the bag filter is discharged into the atmosphere through the chimney through an induced draft fan;

[0016] The continuous emission monitoring system (CEMS) is installed on the chimney. The specific process includes:

[0017] Step 1: During the waste incineration process, the flue gas monitoring parameters are collected in real time, analyzed and judged, abnormal signals of flue gas monitoring parameters are generated, abnormal flue gas monitoring parameters are obtained, and a ranking table of abnormality is determined;

[0018] Step 2: Based on the abnormal smoke monitoring parameters, the correlation calculation method is used in combination with the abnormal overlap duration to output the relevant impact degree value and determine the abnormal impact parameter of the abnormal smoke monitoring parameters;

[0019] The process of obtaining the relevant impact value is as follows:

[0020] Analyze the abnormal smoke monitoring parameters and influencing parameters, calculate the total overlap duration ratio and the correlation value, and process the data according to the total overlap duration ratio and the correlation value to obtain the correlation influence value;

[0021] Step 3: Based on the abnormal influencing parameters, analyze the abnormal flue gas monitoring parameters corresponding to the abnormal influencing parameters, determine the optimization parameter ranking table, and determine the priority adjustment parameters;

[0022] Among them, the process of determining the optimization parameter sorting table is:

[0023] Perform weighted sum calculation on the relevant impact degree values ​​of the abnormal impact parameters and the number of abnormal smoke monitoring parameters to obtain a ranking value, and determine an optimized parameter ranking table based on the ranking value;

[0024] Step 4: Based on the priority adjustment parameters, make adjustments and optimize the abnormal monitoring parameters.

[0025] Beneficial effects of the present invention:

[0026] 1. The present invention integrates multiple modules such as abnormal monitoring, influencing parameter screening and optimization parameter determination. First, the abnormal indicators in the flue gas are detected, marked and sorted. Then, the correlation calculation method and the abnormal overlap duration are used to determine the influencing parameters closely related to these abnormal flue gas monitoring parameters. Finally, according to the abnormal influencing parameters and their corresponding abnormal flue gas monitoring parameters, the optimization parameter sorting table is determined by calculating the sorting value, so as to identify the priority adjustment parameters, adjust the priority adjustment parameters, and then monitor the abnormal components in the flue gas in real time, and quickly determine the influencing parameters related thereto, shorten the troubleshooting time, improve the maintenance efficiency of the equipment, and provide parameter adjustment suggestions to the staff based on the optimization parameter sorting table;

[0027] 2. The present invention determines the priority adjustment parameters by determining the optimization parameter ranking table. Adjusting the priority adjustment parameters can reduce the human, material or time resources invested in adjusting all abnormal parameters at the same time, and gives priority to adjusting the parameters that have the greatest impact on the system. Under the premise of ensuring the stability of the system, abnormal problems can be gradually solved. By giving priority to adjusting the parameters with the greatest impact, the improvement of system performance can be seen more quickly. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0029] Figure 1 is a flow chart of a method for efficiently converting solid waste into renewable energy provided by Embodiment 1 of the present invention;

[0030] Figure 2Schematic diagram of a real-time detection and maintenance system for efficient solid waste conversion to renewable energy provided by Embodiment 2 of the present invention;

[0031] Figure 3 It is a structural diagram of a computer device provided in Embodiment 4 of the present invention.

[0032] In the figure: 3, computer device; 301, processor; 302, memory; 303, computer program; DETAILED DESCRIPTION

[0033] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme 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 only 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 should fall within the scope of protection of the present invention.

[0034] Embodiment 1

[0035] The embodiment of the present invention can be applied to the situation of using waste incineration to convert renewable energy. The high-efficiency solid waste to renewable energy real-time detection and maintenance method can be executed by a high-efficiency solid waste to renewable energy real-time detection and maintenance system. The high-efficiency solid waste to renewable energy real-time detection and maintenance system can be implemented by software and / or hardware. The high-efficiency solid waste to renewable energy real-time detection and maintenance system can be configured in a high-efficiency solid waste to renewable energy real-time detection and maintenance device. Optionally, the high-efficiency solid waste to renewable energy real-time detection and maintenance device can be an electronic device, which can be a notebook, a desktop computer, a smart tablet, etc. The embodiment of the present invention does not limit this.

[0036] Solid waste conversion to renewable energy mainly includes: biomass energy utilization, waste incineration power generation, waste biodegradation, waste pyrolysis gasification. The present invention mainly introduces a method for converting waste incineration to renewable energy and a real-time detection system;

[0037] like Figure 1 As shown, the highly efficient solid waste conversion method for renewable energy provided by the embodiment of the present invention specifically includes the following steps:

[0038] S1: Waste Receiving and Storage System

[0039] After the transport truck loaded with garbage enters the incineration plant, it first passes through the scale for weighing and measurement, then enters the unloading hall, and unloads the garbage into the garbage pit through the unloading door. A garbage grab crane is installed above the garbage pit to move, mix and feed the garbage;

[0040] S2: Waste Incineration System

[0041] The garbage is grabbed by the garbage crane and put into the hopper, then passed through the material chute and pushed into the incinerator by the feeder. The garbage falls onto the grate, and after being dried in the grate drying section, it is pushed to the combustion section and the burnout section with the reciprocating motion of the grate, completing the combustion and burnout processes in sequence. The slag falls into the slag remover through the slag outlet;

[0042] S3: Combustion air piping system

[0043] The primary air is introduced from the space above the garbage pool through the primary fan, while ensuring that the garbage pool is in a negative pressure state to prevent odor leakage. After being preheated by the primary steam-air preheater, the primary air enters the wind chamber through the lower part of the grate, and then enters the furnace through the grate air supply hole and the garbage layer on the grate to assist combustion. The secondary air adopts the flue gas recirculation technology, using the flue gas at the bag filter outlet, after passing through the recirculation air preheater, it is blown into the incinerator from the top of the furnace through the nozzle, which increases the air turbulence in the furnace and reduces the generation of NOx;

[0044] S4: Steam Turbine Generator System

[0045] The superheated steam (400℃, 4MPa, medium temperature and medium pressure) generated by the waste heat boiler is sent to the steam turbine generator set. The steam expands in the steam turbine to generate power for grid connection. The exhaust steam after work is discharged into the condenser. The exhaust steam condenses into water in the condenser. The condensate pump passes through the shaft seal heater and the low-pressure heater and the boiler make-up water and enters the deaerator for deoxidation and is temporarily stored in the deoxidation water tank. The deoxidized water reaching 130℃ is pressurized by the feed water pump and sent to the boiler drum for energy saving and environmental protection.

[0046] S5: Flue gas purification system

[0047] The flue gas at the outlet of the waste heat boiler enters the bag filter after being deacidified in the semi-dry reaction tower. The pipeline connecting the semi-dry reaction tower and the bag filter is provided with a slaked lime injection port and an activated carbon injection port. The flue gas discharged from the bag filter is discharged into the atmosphere through the chimney through the induced draft fan;

[0048] A continuous emissions monitoring system (CEMS) is installed on the chimney to measure, record and report monitoring parameters;

[0049] S6: Fly ash stabilization system

[0050] The discharge from the semi-dry reaction tower and bag filter is fly ash, which is collected by a conveyor and lifted by a bucket elevator to a fly ash storage bin. It is then stabilized by a chelating agent stabilization process. The stabilized fly ash meets the leaching toxicity standard requirements of the "Hazardous Waste Identification Standard: Leaching Toxicity Identification (GB 5085.3-1996)" and is transported to a dedicated area of ​​the landfill for landfill treatment by a special transport vehicle.

[0051] Embodiment 2

[0052] Based on the above embodiments, Figure 2 As shown, the embodiment of the present invention provides a real-time detection and maintenance system for efficient solid waste conversion to renewable energy, which specifically includes:

[0053] Abnormal monitoring parameter acquisition module: During the waste incineration process, the flue gas monitoring parameters are collected in real time, analyzed and judged, abnormal flue gas monitoring parameters are obtained, and the abnormal degree ranking table is determined;

[0054] Among them, flue gas monitoring parameters include but are not limited to: HCl, SO2, O2, CO, NOx, and dust concentration;

[0055] In some embodiments, real-time smoke collection monitoring parameters are preset for analysis periods, wherein the analysis periods are set by those skilled in the art based on experience and analysis requirements;

[0056] In this embodiment, the high temperature direct cold-drying extraction method and Fourier infrared absorption are used to measure the smoke component content (i.e., the smoke monitoring parameter), and the gas sampling probe is a dedicated electric heating automatic temperature control type sampling probe;

[0057] During the analysis period, the collected flue gas monitoring parameters are summed and averaged to obtain the mean value of the flue gas monitoring parameters;

[0058] Compare the collected flue gas monitoring parameter mean with the flue gas monitoring parameter standard limit, wherein the monitoring parameter standard limit is set by technical personnel in this field based on industry specifications (such as the "Standard for Pollution Control of Municipal Waste Incineration" (GB18485-2014)), environmental protection requirements and practices in the solid waste conversion process;

[0059] If the mean value of the smoke monitoring parameter is less than or equal to the standard limit value of the smoke monitoring parameter, a normal signal of the smoke monitoring parameter is generated; if the mean value of the smoke monitoring parameter is greater than the standard limit value of the smoke monitoring parameter, an abnormal signal of the smoke monitoring parameter is generated;

[0060] Based on the abnormal signal of the flue gas monitoring parameter, the flue gas monitoring parameter corresponding to the abnormal signal of the flue gas monitoring parameter is extracted and marked as the abnormal flue gas monitoring parameter;

[0061] The difference between the mean value of the flue gas monitoring parameter corresponding to the abnormal flue gas monitoring parameter and the standard limit value of the flue gas monitoring parameter is calculated to obtain the abnormal degree value;

[0062] The abnormality degree values ​​corresponding to the abnormal smoke monitoring parameters are sorted in order from large to small to obtain an abnormality degree sorting table;

[0063] The core technical solution of this embodiment: During the waste incineration process, by real-time detection and analysis of flue gas monitoring parameters, it is possible to timely understand the flue gas monitoring parameters of excessively high flue gas emissions during the waste incineration process, so that operators can quickly take measures to make adjustments and reduce environmental problems caused by excessive emissions.

[0064] Embodiment 3

[0065] Based on the above embodiments, Figure 2 As shown, the embodiment of the present invention provides a real-time detection and maintenance system for efficient solid waste conversion to renewable energy, and the system specifically includes:

[0066] Influencing parameter screening module: Based on the abnormal smoke monitoring parameters, the correlation calculation method is used in combination with the abnormal overlap duration to output the relevant impact degree value and determine the abnormal impact parameters of the abnormal smoke monitoring parameters;

[0067] Among them, the influencing parameters include but are not limited to: incineration temperature, stirring and mixing degree, gas residence time, excess air rate, thickness of the garbage layer in the furnace, ratio of primary air to secondary air, boiler steam parameters;

[0068] In some embodiments, based on the abnormal flue gas monitoring parameters, the influencing parameters are compared with the influencing parameter standard range, wherein the influencing parameter standard range is summarized and set by those skilled in the art based on multiple practices in the solid waste conversion process;

[0069] If the influencing parameter is within the standard range of the influencing parameter, it is marked as a normal period of the influencing parameter; if the influencing parameter is not within the standard range of the influencing parameter, it is marked as an abnormal period of the influencing parameter;

[0070] Compare the abnormal smoke gas monitoring parameters with the standard limits of the smoke gas monitoring parameters. If the abnormal smoke gas monitoring parameters are less than or equal to the standard limits of the smoke gas monitoring parameters, it is marked as a normal period of abnormal smoke gas monitoring parameters. If the abnormal smoke gas monitoring parameters are greater than the standard limits of the smoke gas monitoring parameters, it is marked as an abnormal period of abnormal smoke gas monitoring parameters.

[0071] Extract the overlapping time periods between the abnormal time periods of influencing parameters and the abnormal time periods of abnormal flue gas monitoring parameters, calculate the total duration of the overlapping time periods, calculate the ratio of the total duration of the overlapping time periods to the duration of the analysis period, and obtain the total duration ratio SC of the overlapping time periods;

[0072] Calculate the correlation value between the influencing parameters and the abnormal smoke monitoring parameters by using the correlation calculation method;

[0073] In this embodiment, the Pearson correlation coefficient is used to calculate the correlation coefficient between the abnormal smoke monitoring parameter and each influencing parameter, wherein the calculation formula of the correlation coefficient R(X, Y) is: Where n represents the number of samples, Xi and Yi represent the i-th value of , where i≤n, They represent the means of the variables corresponding to the abnormal smoke monitoring parameters and influencing parameters respectively;

[0074] It should be noted that the sample values ​​of abnormal smoke monitoring parameters and influencing parameters used to calculate the Pearson correlation coefficient are the sample values ​​corresponding to the overlapping time periods;

[0075] The value of the Pearson correlation coefficient is between -1 and 1. The closer the value is to 1, the stronger the correlation between the two variables.

[0076] Take the absolute value of the correlation coefficient R(X,Y) and calculate the difference between it and 1 to get the correlation value XG;

[0077] Substitute the total overlap duration ratio SC and the correlation value XG into the formula to calculate the correlation impact value, where the calculation formula for the correlation impact value YX is: Among them, a1 and a2 are preset proportional coefficients, the value of a1 is 0.684, and the value of a2 is 1.316;

[0078] It should be explained that the relevant influence degree value is calculated by the total overlap duration ratio value SC and the correlation degree value XG, wherein the greater the total overlap duration ratio value, the stronger the abnormal overlap correlation between the abnormal smoke monitoring parameter and the influencing parameter, and the smaller the correlation degree value, the closer the absolute value of the correlation coefficient is to 1, and the stronger the abnormal overlap correlation between the abnormal smoke monitoring parameter and the influencing parameter;

[0079] Compare the relevant impact degree value with the relevant impact degree threshold, wherein the relevant impact degree threshold is summarized and set by technical personnel in this field based on multiple practices and work experience in the solid waste conversion process;

[0080] If the relevant impact degree value is less than or equal to the relevant impact degree threshold, a low impact degree signal is generated; if the relevant impact degree value is greater than the relevant impact degree threshold, a high impact degree signal is generated;

[0081] Based on the high impact signal, for each abnormal smoke monitoring parameter, the impact parameter corresponding to the high impact is extracted and marked as an abnormal impact parameter;

[0082] Optimization parameter determination module: Based on the abnormal influencing parameters, analyze the abnormal flue gas monitoring parameters corresponding to the abnormal influencing parameters, determine the optimization parameter ranking table, and determine the priority adjustment parameters;

[0083] In some embodiments, the abnormal impact parameters corresponding to each abnormal smoke monitoring parameter are sorted according to the order of the abnormal degree sorting table to determine the optimized parameter sorting table corresponding to each abnormal smoke monitoring parameter;

[0084] Among them, the determination process of the optimization parameter ranking table corresponding to each abnormal flue gas monitoring parameter is as follows:

[0085] Obtain the abnormal impact parameter corresponding to the abnormal smoke monitoring parameter, and extract the relevant impact degree value YX corresponding to the abnormal impact parameter;

[0086] For each abnormal influencing parameter, obtain the abnormal smoke monitoring parameter affected by the abnormal influencing parameter, and count the number of abnormal smoke monitoring parameters SL;

[0087] Substitute the relevant impact value YX corresponding to each abnormal impact parameter and the number of abnormal smoke monitoring parameters SL into the formula to calculate the ranking value. The calculation formula of the ranking value PX is: PX = s1*YX+s2*SL, where s1 and s2 are weight coefficients, the value of s1 is 0.62, and the value of s2 is 0.38;

[0088] Sort the abnormal influencing parameters in descending order according to the sorting values, form an optimization parameter sorting table corresponding to the abnormal flue gas monitoring parameters, and determine the priority adjustment parameters;

[0089] It should be noted that when the ranking values ​​are the same, the one with the larger relevant impact value will be ranked first. If the relevant impact values ​​are the same and the number of abnormal smoke monitoring parameters is also the same, one will be randomly selected and ranked first.

[0090] In this embodiment, for example, during the waste incineration process, the abnormal monitoring parameter acquisition module detects abnormalities in the concentrations of HCl, NOx, and dust, and marks and sorts the concentrations of HCl, NOx, and dust in the following order: concentrations of HCl, NOx, and dust;

[0091] The influencing parameter screening module determines the influencing parameters related to HCl, NOx and dust concentrations. Among them, HCl abnormality is related to the incineration temperature, excess air rate, and the ratio of primary air to secondary air; NOx abnormality is related to the incineration temperature and the ratio of primary air to secondary air; and dust concentration abnormality is related to the incineration temperature, the degree of stirring and mixing, and the thickness of the garbage layer in the furnace.

[0092] The optimization parameter determination module determines the optimization parameter ranking table corresponding to the HCl, NOx and dust concentrations according to the order of the HCl, NOx and dust concentrations;

[0093] For example, for HCL, the relevant influence value of the combustion temperature is 6.2, the excess air rate is 5.7, and the ratio of primary air to secondary air is 5.6; the combustion temperature affects HCL and NOx, and the corresponding number of abnormal flue gas monitoring parameters is 2, the excess air rate affects HCl, and the corresponding number of abnormal flue gas monitoring parameters is 1, and the ratio of primary air to secondary air affects HCl and NOx, and the corresponding number of abnormal flue gas monitoring parameters is 2;

[0094] The ranking values ​​of the calculated incineration temperature, excess air rate, and primary air to secondary air ratio are as follows: the ranking value of the incineration temperature is 4.604, the ranking value of the excess air rate is 3.914, and the ranking value of the primary air to secondary air ratio is 4.232;

[0095] That is, the ranking table of optimized parameters for HCL is: combustion temperature, primary air to secondary air ratio, excess air rate;

[0096] Based on the above optimization parameter ranking table, the priority adjustment parameter is the incineration temperature;

[0097] The core technology of this embodiment is: based on the acquired abnormal smoke monitoring parameters, the abnormal smoke monitoring parameters and the influencing parameters are analyzed, and the total overlap duration ratio and the correlation value are calculated by using the correlation calculation method in combination with the abnormal overlap duration. Data processing is performed according to the total overlap duration ratio and the correlation value to calculate the relevant influence value, and the abnormal influence parameter is judged to be obtained. Data processing is performed according to the correlation value corresponding to each abnormal influence parameter and the number of abnormal smoke monitoring parameters to calculate the ranking value. According to the ranking value, the abnormal influence parameters are sorted in order from large to small according to the ranking value to form an optimization parameter sorting table corresponding to the abnormal smoke monitoring parameters, and the priority adjustment parameters are determined. Therefore, the abnormal influence parameters that are highly correlated with the abnormal smoke monitoring parameters can be accurately identified through the correlation calculation method and the analysis of the abnormal overlap duration, and the accuracy of problem diagnosis is improved. By forming the optimization parameter sorting table corresponding to the abnormal smoke monitoring parameters, the importance ranking of each abnormal influence parameter can be clearly seen, so that the monitoring personnel can quickly lock the key points and improve the efficiency of the monitoring work. The determination of the priority adjustment parameters is conducive to the reasonable allocation of resources, and the limited resources are used to solve the most critical problems, so as to improve the efficiency and benefits of resource use.

[0098] Embodiment 4

[0099] Based on the above embodiments, Figure 2 As shown, the embodiment of the present invention provides a real-time detection and maintenance system for efficient solid waste conversion to renewable energy, and the system specifically includes:

[0100] Optimization parameter adjustment module: Based on the priority adjustment parameters, adjustments are made to optimize the abnormal monitoring parameters;

[0101] In some embodiments, the abnormal smoke monitoring parameters are adjusted in sequence according to the order of the abnormality degree ranking table. The specific process is as follows:

[0102] Extract the influencing parameter ranked 1 in the optimization parameter sorting table as the priority adjustment parameter, obtain the current priority adjustment parameter value, and adjust it to the influencing parameter standard value, wherein the influencing parameter standard value is calculated by summing and averaging the maximum and minimum values ​​of the influencing parameter standard range;

[0103] It should be noted that if the current priority adjustment parameter value is equal to the standard value of the influencing parameter, the influencing parameter ranked 2 in the optimization parameter sorting table is extracted as the priority adjustment parameter for adjustment, and so on;

[0104] Similarly, if the abnormal smoke gas monitoring parameter ranked 1 in the abnormality degree ranking table has adjusted its corresponding priority adjustment parameter, when the abnormal smoke gas monitoring parameter ranked 2 in the abnormality degree ranking table begins to be adjusted, if the priority adjustment parameter corresponding to the abnormal smoke gas monitoring parameter ranked 2 is the same as the priority adjustment parameter corresponding to the abnormal smoke gas monitoring parameter ranked 1, then when optimizing the influence parameter corresponding to the abnormal smoke gas monitoring parameter ranked 2, the influence parameter ranked 2 in the optimization parameter ranking table is selected as the priority adjustment parameter, and so on;

[0105] The technical solution of this embodiment is: by combining the abnormality degree ranking table with the optimization parameter ranking table, the abnormal flue gas monitoring parameters are adjusted in turn. Since different parameters have different degrees of influence on the overall performance of the system, some parameter abnormalities may have a greater impact on the system and may even trigger a chain reaction, leading to more serious consequences. Therefore, through comprehensive analysis, it is possible to determine which parameters have the greatest impact on the system, so as to give priority to adjustment and see the improvement in system performance more quickly.

[0106] Embodiment 5

[0107] Based on the above embodiments, the embodiment of the present invention provides a real-time detection and maintenance method for efficient solid waste conversion to renewable energy, which specifically includes the following steps:

[0108] Step 1: During the waste incineration process, the flue gas monitoring parameters are collected in real time, analyzed and judged, abnormal flue gas monitoring parameters are obtained, and the abnormal degree ranking table is determined;

[0109] Among them, flue gas monitoring parameters include but are not limited to: HCl, SO2, O2, CO, NOx, and dust concentration;

[0110] Step 2: Based on the abnormal smoke monitoring parameters, the correlation calculation method is used in combination with the abnormal overlap duration to output the relevant impact degree value and determine the abnormal impact parameter of the abnormal smoke monitoring parameters;

[0111] Among them, the influencing parameters include but are not limited to: incineration temperature, stirring and mixing degree, gas residence time, excess air rate, thickness of the garbage layer in the furnace, ratio of primary air to secondary air, boiler steam parameters;

[0112] Step 3: Based on the abnormal influencing parameters, analyze the abnormal flue gas monitoring parameters corresponding to the abnormal influencing parameters, determine the optimization parameter ranking table, and determine the priority adjustment parameters;

[0113] Step 4: Based on the priority adjustment parameters, make adjustments and optimize the abnormal monitoring parameters.

[0114] Embodiment 6

[0115] like Figure 3 As shown, an embodiment of the present invention further provides a computer device 3, comprising: a memory 302 and a processor 301 and a computer program 303 stored on the memory 302. When the computer program 303 is executed on the processor 301, a high-efficiency real-time detection and maintenance method for converting solid waste into renewable energy as described in any of the above methods is implemented.

[0116] The computer device 3 may be a computing device such as a desktop computer, a notebook, a PDA, or a cloud server. The computer device 3 may include, but is not limited to, a processor 301 and a memory 302. Those skilled in the art will appreciate that

[0117] Figure 3 It is only an example of computer device 3 and does not constitute a limitation on computer device 3. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components, for example, it may also include input and output devices, network access devices, etc.

[0118] The processor 301 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0119] In some embodiments, the memory 302 may be an internal storage unit of the computer device 3, such as a hard disk or memory of the computer device 3. In other embodiments, the memory 302 may also be an external storage device of the computer device 3, such as a plug-in hard disk, a smart memory card (SmartMediaCard, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the computer device 3. Further, the memory 302 may also include both an internal storage unit of the computer device 3 and an external storage device. The memory 302 is used to store an operating system, an application program, a boot loader (BootLoader), data, and other programs, such as the program code of the computer program. The memory 302 may also be used to temporarily store data that has been output or is to be output.

[0120] Embodiment 7

[0121] An embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the real-time detection and maintenance method for efficient conversion of solid waste into renewable energy as described in any of the above methods is implemented.

[0122] In this embodiment, if the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the processes in the above-mentioned embodiment method, which can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, the steps of the above-mentioned various method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium can at least include: any entity or device that can carry the computer program code to the camera / terminal device, recording medium, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium. For example, a USB flash drive, a mobile hard disk, a disk or an optical disk. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electric carrier signals and telecommunication signals.

[0123] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0124] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in a combination of electronic hardware, computer software, and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0125] In the embodiments disclosed in the present application, it should be understood that the disclosed devices / terminal equipment and methods can be implemented in other ways. For example, the device / terminal equipment embodiments described above are only schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0126] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0127] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0128] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. High-efficiency solid waste to renewable energy real-time detection and maintenance system, characterized by: The system specifically includes: Abnormal monitoring parameter acquisition module: During the waste incineration process, the flue gas monitoring parameters are collected in real time, analyzed and judged, and abnormal signals of flue gas monitoring parameters are generated, abnormal flue gas monitoring parameters are obtained, and the abnormal degree ranking table is determined; Influencing parameter screening module: Based on the abnormal smoke monitoring parameters, the correlation calculation method is used in combination with the abnormal overlap duration to output the relevant impact degree value and determine the abnormal impact parameters of the abnormal smoke monitoring parameters; The process of obtaining the relevant impact value is as follows: Analyze the abnormal smoke monitoring parameters and influencing parameters, calculate the total overlap duration ratio and the correlation value, and process the data according to the total overlap duration ratio and the correlation value to obtain the correlation influence value; Optimization parameter determination module: Based on the abnormal influencing parameters, analyze the abnormal flue gas monitoring parameters corresponding to the abnormal influencing parameters, determine the optimization parameter ranking table, and determine the priority adjustment parameters; Among them, the process of determining the optimization parameter sorting table is: Perform weighted sum calculation on the relevant impact degree values ​​of the abnormal impact parameters and the number of abnormal smoke monitoring parameters to obtain a ranking value, and determine an optimized parameter ranking table based on the ranking value; Optimization parameter adjustment module: Based on the priority adjustment parameters, adjustments are made to optimize the abnormal monitoring parameters.

2. The high-efficiency real-time detection and maintenance system for solid waste conversion to renewable energy according to claim 1 is characterized in that: The process of obtaining the abnormality degree ranking table is as follows: Based on the abnormal signal of the flue gas monitoring parameter, the flue gas monitoring parameter corresponding to the abnormal signal of the flue gas monitoring parameter is extracted and marked as the abnormal flue gas monitoring parameter; The difference between the mean value of the flue gas monitoring parameter corresponding to the abnormal flue gas monitoring parameter and the standard limit value of the flue gas monitoring parameter is calculated to obtain the abnormal degree value; The abnormality degree values ​​corresponding to the abnormal flue gas monitoring parameters are sorted in order from large to small to obtain an abnormality degree sorting table.

3. The real-time detection and maintenance system for efficient solid waste conversion to renewable energy according to claim 1 is characterized in that: The generation process of the abnormal signal of the flue gas monitoring parameter is as follows: Real-time flue gas collection and monitoring parameters, preset analysis time period; During the analysis period, the collected flue gas monitoring parameters are summed and averaged to obtain the mean value of the flue gas monitoring parameters; Compare the collected mean values ​​of the smoke monitoring parameters with the standard limits of the smoke monitoring parameters; If the mean value of the flue gas monitoring parameter is greater than the standard limit value of the flue gas monitoring parameter, a flue gas monitoring parameter abnormal signal is generated.

4. The high-efficiency real-time detection and maintenance system for solid waste conversion to renewable energy according to claim 1 is characterized in that: The process of obtaining the relevant impact value is as follows: Obtain the total overlap duration ratio SC and the correlation value XG; Substitute the total overlap duration ratio SC and the correlation value XG into the formula to calculate the correlation impact value, where the calculation formula for the correlation impact value YX is: Among them, a1 and a2 are preset proportional coefficients.

5. The high-efficiency real-time detection and maintenance system for solid waste conversion to renewable energy according to claim 1 is characterized in that: The process of obtaining the value of the total overlap duration ratio is as follows: Based on the abnormal smoke monitoring parameters, the influencing parameters are compared with the standard range of the influencing parameters; If the influencing parameter is not within the standard range of the influencing parameter, it is marked as an abnormal period of influencing parameter; The abnormal smoke monitoring parameter is compared with the standard limit of the smoke monitoring parameter. If the abnormal smoke monitoring parameter is greater than the standard limit of the smoke monitoring parameter, it is marked as an abnormal period of abnormal smoke monitoring parameter; The overlapping periods between the abnormal periods of influencing parameters and the abnormal periods of abnormal flue gas monitoring parameters are extracted, the total duration of the overlapping periods is calculated, and the ratio of the total duration of the overlapping periods to the duration of the analysis period is calculated to obtain the total overlapping duration ratio SC.

6. The high-efficiency real-time detection and maintenance system for solid waste conversion to renewable energy according to claim 1 is characterized in that: The process of obtaining the correlation value is as follows: The Pearson correlation coefficient is used to calculate the correlation coefficient between the abnormal smoke monitoring parameters and each influencing parameter, where the calculation formula of the correlation coefficient R(X,Y) is: Where n represents the number of samples, Xi and Yi represent the i-th value of , where i≤n, They represent the means of the variables corresponding to the abnormal smoke monitoring parameters and influencing parameters respectively; Take the absolute value of the correlation coefficient R(X,Y) and calculate the difference between it and 1 to get the correlation value XG.

7. The high-efficiency real-time detection and maintenance system for solid waste conversion to renewable energy according to claim 1 is characterized in that: The determination process of the optimization parameter sorting table is as follows: Get the parameters affected by the exception according to the sorting value; Sort the abnormal influencing parameters in descending order according to the sorting value, form an optimized parameter sorting table corresponding to the abnormal flue gas monitoring parameters, and determine the priority adjustment parameters.

8. The real-time detection and maintenance system for efficient solid waste conversion to renewable energy according to claim 1 is characterized in that: The calculation process of the ranking value is: Obtain the abnormal impact parameter corresponding to the abnormal smoke monitoring parameter, and extract the relevant impact degree value YX corresponding to the abnormal impact parameter; For each abnormal influencing parameter, obtain the abnormal smoke monitoring parameter affected by the abnormal influencing parameter, and count the number of abnormal smoke monitoring parameters SL; Substitute the relevant impact degree value YX corresponding to each abnormal impact parameter and the number of abnormal flue gas monitoring parameters SL into the formula to calculate the ranking value. The calculation formula of the ranking value PX is: PX=s1*YX+s2*SL, where s1 and s2 are weight coefficients.

9. The high-efficiency real-time detection and maintenance system for solid waste conversion to renewable energy according to claim 1 is characterized in that: The process of optimizing the abnormal monitoring parameters is as follows: According to the order of the abnormality degree ranking table, the abnormal flue gas monitoring parameters are adjusted in sequence. The specific process is as follows: The influencing parameter ranked 1 in the optimization parameter sorting table is extracted as the priority adjustment parameter, the current priority adjustment parameter value is obtained, and it is adjusted to the influencing parameter standard value, wherein the influencing parameter standard value is calculated by summing and averaging the maximum and minimum values ​​of the influencing parameter standard range.

10. A highly efficient method for converting solid waste into renewable energy, characterized in that: The method is used to execute the system described in any one of claims 1 to 9 above, and the method comprises: Flue gas purification system: the flue gas at the outlet of the waste heat boiler is deacidified in a semi-dry reaction tower and then enters a bag filter. The pipeline connecting the semi-dry reaction tower and the bag filter is provided with a slaked lime injection port and an activated carbon injection port. The flue gas discharged from the bag filter is discharged into the atmosphere through the chimney through an induced draft fan; The continuous emission monitoring system (CEMS) is installed on the chimney. The specific process includes: Step 1: During the waste incineration process, the flue gas monitoring parameters are collected in real time, analyzed and judged, abnormal signals of flue gas monitoring parameters are generated, abnormal flue gas monitoring parameters are obtained, and a ranking table of abnormality is determined; Step 2: Based on the abnormal smoke monitoring parameters, the correlation calculation method is used in combination with the abnormal overlap duration to output the relevant impact degree value and determine the abnormal impact parameter of the abnormal smoke monitoring parameters; The process of obtaining the relevant impact value is as follows: Analyze the abnormal smoke monitoring parameters and influencing parameters, calculate the total overlap duration ratio and the correlation value, and process the data according to the total overlap duration ratio and the correlation value to obtain the correlation influence value; Step 3: Based on the abnormal influencing parameters, analyze the abnormal flue gas monitoring parameters corresponding to the abnormal influencing parameters, determine the optimization parameter ranking table, and determine the priority adjustment parameters; Among them, the process of determining the optimization parameter sorting table is: Perform weighted sum calculation on the relevant impact degree values ​​of the abnormal impact parameters and the number of abnormal smoke monitoring parameters to obtain a ranking value, and determine an optimized parameter ranking table based on the ranking value; Step 4: Based on the priority adjustment parameters, make adjustments and optimize the abnormal monitoring parameters.

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