Boiler combustion adjusting and optimizing system based on data analysis

Abstract

The invention relates to the technical field of boiler combustion adjustment, in particular to a boiler combustion adjustment optimization system based on data analysis, which comprises a server, an operation supervision unit, an early warning display unit, a display feedback unit, an efficiency analysis unit and an optimization management unit, according to the invention, the operation data of the quick coal mill is collected, safety supervision and analysis are carried out, and whether the operation condition of the quick coal mill is normal is judged, so that timely early warning management is facilitated, the processing management effect of the pulverized coal is improved, and the working data of the boiler equipment is collected, and combustion supervision and evaluation analysis are carried out on the working data, so that the working efficiency is improved. The working efficiency condition of the boiler equipment is judged so that the boiler can be adjusted in time, analysis is conducted in a combined and progressive mode so that the combustion efficiency of the boiler can be improved, meanwhile, the optimization reasonability and accuracy of the boiler can be improved, meanwhile, the content of combustible matter of fly ash and slag can be reduced, the smoke exhaust temperature can be reduced, and the boiler efficiency can be improved. The coal consumption is reduced.

Description

Technical Field

[0001] This invention relates to the field of boiler combustion adjustment technology, and in particular to a boiler combustion adjustment and optimization system based on data analysis. Background Technology

[0002] Global warming is one of the biggest challenges facing human society today. Reducing CO2 emissions is crucial for controlling the greenhouse effect and mitigating global warming. In the face of a low-carbon economic development model, the power industry will inevitably become the main force in CO2 emission reduction. At present, the thermal power industry is achieving structural emission reduction through the "large-scale replacement of small-scale" policy, gradually phasing out small thermal power units, which greatly reduces the coal consumption coefficient for power generation. Our development goal is to generate the most electricity with the least amount of coal. Existing boiler combustion adjustment methods are generally based on the thermal power plant control system. These systems adjust boiler combustion based on historical experience data, expert database data, and theoretical knowledge. However, the existing optimization control system is too simplistic in its optimization process. Using a simple control system to adjust boiler combustion inevitably leads to significant errors, resulting in large nitrogen oxide emissions that seriously harm the environment. Furthermore, it cannot monitor and provide early warnings for pulverized coal processing, nor can it display data for monitoring and early warning, affecting the accuracy of subsequent optimization adjustments. Moreover, it cannot combine boiler efficiency and pulverized coal conditions for analysis, impacting the accuracy and rationality of optimization. To address the aforementioned technical shortcomings, a solution is proposed. Summary of the Invention

[0003] The purpose of this invention is to provide a boiler combustion adjustment and optimization system based on data analysis to address the aforementioned technical deficiencies. This invention collects operating data from boiler equipment and performs combustion monitoring and evaluation analysis on this data to determine the operating efficiency of the boiler equipment, enabling timely optimization management and adjustments to improve boiler combustion efficiency. The analysis employs a combined and progressive approach to enhance boiler combustion efficiency, improve the rationality and accuracy of boiler optimization, and help reduce the combustible content of fly ash and slag, lower flue gas temperature, increase boiler efficiency, and reduce coal consumption.

[0004] The objective of this invention can be achieved through the following technical solution: a boiler combustion adjustment and optimization system based on data analysis, comprising a server, an operation monitoring unit, an early warning display unit, a display feedback unit, an efficiency analysis unit, and an optimization management unit; After the server generates a monitoring instruction, it sends the instruction to the operation monitoring unit. Upon receiving the instruction, the operation monitoring unit immediately collects the operating data of the high-speed coal mill. The operating data includes the separation speed of the rotary separator inside the high-speed coal mill, the air velocity in the powder pipe of the high-speed coal mill, and the fineness of the coal powder. The unit then performs safety monitoring analysis on the operating data to obtain the runaway risk assessment coefficient S, display signals, and high-risk signals. The display signals are sent to the early warning display unit and the display feedback unit, while the high-risk signals are sent to the efficiency analysis unit and the optimization management unit. After receiving the display signal, the display feedback unit immediately collects the display data from the operation display panel of the equipment. The display data includes the operating temperature of each electrical component in the operation display panel and the reactive power loss value of the line. The unit then performs a monitoring feedback evaluation and analysis on the display data and sends the obtained abnormal risk signals to the early warning display unit through the operation monitoring unit. Upon receiving a high-risk signal, the efficiency analysis unit immediately collects the boiler equipment's operating data, including boiler oxygen supply, boiler flue gas temperature, nitrogen and oxygen concentration, and flue gas dust content. It then performs combustion monitoring and assessment analysis on the operating data and sends the resulting non-compliance signals to the early warning display unit. Upon receiving a high-risk signal, the optimization management unit immediately retrieves the runaway risk assessment coefficient S from the operation monitoring unit and the average efficiency risk assessment value from the efficiency analysis unit. It then conducts in-depth optimization and adjustment assessment analysis on the runaway risk assessment coefficient S and the average efficiency risk assessment value, and sends the resulting first-level optimization signal, second-level optimization signal, and third-level optimization signal to the early warning display unit.

[0005] Preferably, the safety supervision and analysis process of the operation supervision unit is as follows: S1: Collect the duration from the start time to the end time of boiler use and mark it as a time threshold. Divide the time threshold into i sub-time nodes, where i is a natural number greater than zero. Obtain the separation speed of the rotary separator in the high-speed coal mill within each sub-time node and analyze the separation speed with the preset separation speed threshold. If the ratio of the separation speed to the preset separation speed threshold is not equal to one, mark the sub-time node corresponding to the ratio of the separation speed to the preset separation speed threshold as a risk node. Obtain the ratio of the number of analyzed nodes to the total number of sub-time nodes and mark the ratio of the number of analyzed nodes to the total number of sub-time nodes as the risk speed value FZ. S12: Obtain the air velocity of the pulverized coal pipe in the high-speed coal mill at each sub-time node, establish a rectangular coordinate system with time as the X-axis and air velocity of the pulverized coal pipe as the Y-axis, and plot the air velocity curve of the pulverized coal pipe by plotting points. Obtain the number of fluctuations and the mean of the time interval between consecutive fluctuations from the air velocity curve of the pulverized coal pipe. Then, after normalizing the data, the product obtained by normalizing the number of fluctuations and the mean of the time interval between consecutive fluctuations is marked as the fluctuation risk value BF. S13: Obtain the coal powder fineness of the high-speed coal mill within each sub-time node, construct a set A of coal powder fineness, obtain the difference between two consecutive subsets in set A, and mark the difference between two consecutive subsets in set A as the fineness fluctuation value, then obtain the maximum and minimum values ​​of the fineness fluctuation value, and mark the difference between the maximum and minimum values ​​of the fineness fluctuation value as the fineness risk span value XD; S14: Obtain the runaway risk assessment coefficient S according to the formula, and compare and analyze the runaway risk assessment coefficient S with the preset runaway risk assessment coefficient threshold that is internally entered and stored: If the ratio of the runaway risk assessment coefficient S to the preset runaway risk assessment coefficient threshold is less than one, a display signal is generated. If the ratio of the runaway risk assessment coefficient S to the preset runaway risk assessment coefficient threshold is greater than or equal to one, a high-risk signal is generated.

[0006] Preferably, the regulatory feedback evaluation and analysis process of the display feedback unit is as follows: The system obtains the operating temperature of each electrical component in the display panel within a time threshold, and compares and analyzes the operating temperature with a preset operating temperature threshold. If the operating temperature is greater than the preset operating temperature threshold, the portion of the operating temperature that is greater than the preset operating temperature threshold is marked as an overheating risk value. A set B of overheating risk values ​​is constructed. The subsets in set B are compared and analyzed with a preset overheating risk value threshold. If the overheating risk value is greater than the preset overheating risk value threshold, the ratio of the number of subsets corresponding to the overheating risk value that is greater than the preset overheating risk value threshold to the total number of subsets is marked as the component overheating risk ratio. The reactive power loss values ​​of the lines displayed on the operation panel within each sub-time node are obtained. A rectangular coordinate system is established with time as the X-axis and the reactive power loss value as the Y-axis. The reactive power loss value curve is plotted by plotting points. At the same time, a preset reactive power loss value threshold curve is plotted in this coordinate system. The area enclosed by the line segment of the reactive power loss value curve above the preset reactive power loss value threshold curve and the preset reactive power loss value threshold curve is marked as the reactive power risk area. The component overheating risk ratio and the reactive power risk area are analyzed with the preset component overheating risk ratio threshold and the preset reactive power risk area threshold that are recorded and stored internally. If the component overheating risk ratio is less than or equal to the preset component overheating risk ratio threshold, and the line reactive power risk area is less than or equal to the preset line reactive power risk area threshold, then no signal will be generated. If the component overheating risk ratio is greater than the preset component overheating risk ratio threshold, or the line reactive power risk area is greater than the preset line reactive power risk area threshold, an abnormal risk signal will be generated.

[0007] Preferably, the combustion regulatory assessment analysis process of the efficiency analysis unit is as follows: The boiler oxygen supply within the time threshold is obtained, and the boiler oxygen supply is compared and analyzed with the preset boiler oxygen supply range recorded and stored internally. If the boiler oxygen supply is not within the preset boiler oxygen supply range, a control signal will be generated. If the boiler oxygen supply is within the preset range, a monitoring signal will be generated.

[0008] Preferably, when the efficiency analysis unit generates a regulatory signal: The boiler exhaust temperature, nitrogen and oxygen concentration, and flue gas dust content values ​​are obtained at each sub-time node. These values ​​are then compared with preset threshold values ​​for boiler exhaust temperature, nitrogen and oxygen concentration, and flue gas dust content stored internally. The portions of boiler exhaust temperature, nitrogen and oxygen concentration, and flue gas dust content values ​​that exceed the preset threshold values ​​are identified and marked as risk flue gas temperature value FYi, risk nitrogen and oxygen content value FDi, and risk flue gas dust value FCI, respectively. The efficiency risk assessment coefficient Xi for each sub-time node is obtained according to the formula. The maximum value of the efficiency risk assessment coefficient is then obtained. The mean of the efficiency risk assessment coefficient after removing the maximum value is then obtained and marked as the average efficiency risk assessment value. The average efficiency risk assessment value is then compared and analyzed with the preset average efficiency risk assessment value threshold that is entered and stored internally. If the average efficiency risk assessment value is greater than or equal to the preset average efficiency risk assessment value threshold, no signal will be generated; If the average efficiency risk assessment value is less than the preset average efficiency risk assessment value threshold, an unqualified signal will be generated.

[0009] Preferably, the in-depth optimization adjustment evaluation and analysis process of the optimization management unit is as follows: The portions of the runaway risk assessment coefficient S exceeding the preset runaway risk assessment coefficient threshold and the portions of the average efficiency risk assessment value exceeding the preset average efficiency risk assessment value threshold are obtained and marked as runaway value and combustion risk value, respectively. The product of the runaway value and combustion risk value after data normalization is marked as the optimized assessment value, and the optimized assessment value is compared and analyzed with the preset optimized assessment value range entered and stored internally. If the optimized evaluation value is greater than the maximum value in the preset optimized evaluation value range, a first-level optimization signal is generated; If the optimized evaluation value is within the preset optimized evaluation value range, a secondary optimization signal is generated; If the optimized evaluation value is less than the minimum value in the preset optimized evaluation value range, a third-level optimization signal is generated.

[0010] The beneficial effects of this invention are as follows: (1) This invention collects the operating data of the high-speed coal mill and conducts safety supervision analysis to determine whether the operation of the high-speed coal mill is normal, so as to provide timely early warning management. This helps to optimize the management of the high-speed coal mill, so as to improve the boiler combustion rate and improve the coal powder processing management effect. Furthermore, by evaluating and analyzing from three dimensions—risk speed value, fluctuation risk value, and fineness risk span value—it helps to improve the accuracy of the analysis results. Moreover, by using data feedback and supervision early warning, it provides supervision and early warning for the data display, so as to provide timely early warning management and improve the completeness and accuracy of the data display. (2) This invention collects the working data of the boiler equipment and conducts combustion monitoring and evaluation analysis on the working data to determine the working efficiency of the boiler equipment so as to make timely optimization management and timely optimize and adjust the boiler to improve the combustion efficiency of the boiler. The analysis is carried out in a combined and progressive manner to improve the combustion efficiency of the boiler, while improving the optimization rationality and accuracy of the boiler. It also helps to reduce the combustible content of fly ash and slag, reduce the flue gas temperature, improve boiler efficiency, and reduce coal consumption. Attached Figure Description

[0011] The invention will now be further described with reference to the accompanying drawings; Figure 1 This is a flowchart of the system of the present invention; Figure 2 This is a partial analysis diagram of the present invention. Detailed Implementation

[0012] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0013] Example 1: Please see Figures 1 to 2 As shown, the present invention is a boiler combustion adjustment and optimization system based on data analysis, including a server, an operation monitoring unit, an early warning display unit, a display feedback unit, an efficiency analysis unit, and an optimization management unit. The server and the operation monitoring unit have a one-way communication connection. The operation monitoring unit has a one-way communication connection with both the efficiency analysis unit and the optimization management unit. The efficiency analysis unit has a one-way communication connection with both the optimization management unit and the early warning display unit. The optimization management unit has a one-way communication connection with the early warning display unit. The operation monitoring unit and the display feedback unit have a two-way communication connection. The operation monitoring unit and the early warning display unit have a one-way communication connection. Once the server generates a monitoring command, it sends it to the operation monitoring unit. Upon receiving the command, the unit immediately collects operational data from the rapid coal mill. This data includes the separation speed of the rotary separator, the air velocity in the mill's pulverizer pipe, and the fineness of the pulverized coal. The unit then performs safety monitoring analysis on this data to determine if the mill is operating normally, enabling timely early warning and management to improve boiler combustion efficiency. This also facilitates optimized management of the rapid coal mill. The specific safety monitoring analysis process is as follows: The duration from the start time to the end time of boiler use is collected and marked as a time threshold. The time threshold is divided into i sub-time nodes, where i is a natural number greater than zero. The separation speed of the rotary separator in the high-speed coal mill within each sub-time node is obtained, and the separation speed is analyzed with a preset separation speed threshold. If the ratio of the separation speed to the preset separation speed threshold is not equal to one, the sub-time node corresponding to the ratio of the separation speed to the preset separation speed threshold is marked as a risk node. The ratio of the number of analyzed nodes to the total number of sub-time nodes is obtained and marked as the risk speed value FZ. It should be noted that the larger the risk speed value FZ is, the greater the risk of equipment malfunction. The air velocity of the pulverized coal pipe in the high-speed coal mill at each sub-time node is obtained. A rectangular coordinate system is established with time as the X-axis and air velocity of the pulverized coal pipe as the Y-axis. The air velocity curve of the pulverized coal pipe is plotted by plotting points. The number of fluctuations and the mean of the time interval between consecutive fluctuations are obtained from the air velocity curve. The product of the number of fluctuations and the mean of the time interval between consecutive fluctuations is normalized and labeled as the fluctuation risk value BF. It should be noted that the fluctuation risk value BF is a parameter that reflects the impact of the feed of the equipment. The fineness of coal powder from the high-speed coal mill at each sub-time node is obtained, and a set A of coal powder fineness is constructed accordingly. The difference between two consecutive subsets in set A is obtained, and the difference between two consecutive subsets in set A is marked as the fineness fluctuation value. Then, the maximum and minimum values ​​of the fineness fluctuation value are obtained, and the difference between the maximum and minimum values ​​of the fineness fluctuation value is marked as the fineness risk span value, labeled as XD. According to the formula The runaway risk assessment coefficient is obtained, where a1, a2, and a3 are preset proportional factor coefficients for the risk rotation speed value, volatility risk value, and fineness risk span value, respectively. These proportional factor coefficients are used to correct deviations in the calculation of various parameters, thus making the calculation results more accurate. a1, a2, and a3 are all positive numbers greater than zero. a4 is a preset correction coefficient with a value of 2.468. S is the runaway risk assessment coefficient, and the runaway risk assessment coefficient S is compared and analyzed with its internally entered and stored preset runaway risk assessment coefficient threshold. If the ratio of the runaway risk assessment coefficient S to the preset runaway risk assessment coefficient threshold is less than one, a display signal is generated and sent to the early warning display unit and the display feedback unit. Upon receiving the display signal, the early warning display unit immediately displays the separation speed of the rotary separator inside the digital high-speed coal mill, the air velocity in the coal mill's powder pipe, and the fineness of the coal powder, thus providing a direct understanding of the equipment's operating status. If the ratio of the runaway risk assessment coefficient S to the preset runaway risk assessment coefficient threshold is greater than or equal to one, a high-risk signal is generated and sent to the efficiency analysis unit and the optimization management unit. Upon receiving the display signal, the display feedback unit immediately collects the display data from the equipment's operation display panel. This data includes the operating temperature of each electrical component within the panel and the reactive power loss values ​​of the lines. The unit then performs a monitoring feedback assessment and analysis on the display data to determine the risk of malfunctions in the operation display panel, enabling timely early warning management and improving the completeness and accuracy of the data display. The specific monitoring feedback assessment and analysis process is as follows: The system obtains the operating temperature of each electrical component in the operation display panel within a time threshold, and compares and analyzes the operating temperature with a preset operating temperature threshold. If the operating temperature is greater than the preset operating temperature threshold, the portion of the operating temperature that exceeds the preset operating temperature threshold is marked as an overheating risk value, and a set B of overheating risk values ​​is constructed. The subsets in set B are compared and analyzed with the preset overheating risk value threshold. If the overheating risk value is greater than the preset overheating risk value threshold, the ratio of the number of subsets corresponding to the overheating risk value that exceeds the preset overheating risk value threshold to the total number of subsets is marked as the component overheating risk ratio. It should be noted that the larger the component overheating risk ratio, the greater the risk of abnormal display on the operation display panel. The reactive power loss values ​​of the lines displayed on the operation panel within each sub-time node are obtained. A Cartesian coordinate system is established with time as the X-axis and reactive power loss value as the Y-axis. The reactive power loss value curve is plotted by plotting points. Simultaneously, a preset reactive power loss value threshold curve is plotted in this coordinate system. The area enclosed by the line segment of the reactive power loss value curve above the preset reactive power loss value threshold curve and the preset reactive power loss value threshold curve is marked as the reactive power risk area. It should be noted that the reactive power risk area is an impact parameter reflecting the condition of the lines on the operation display panel. The component overheating risk ratio and the reactive power risk area are analyzed with the preset component overheating risk ratio threshold and the preset reactive power risk area threshold recorded and stored internally. If the component overheating risk ratio is less than or equal to the preset component overheating risk ratio threshold, and the line reactive power risk area is less than or equal to the preset line reactive power risk area threshold, then no signal will be generated. If the component overheating risk ratio is greater than the preset component overheating risk ratio threshold, or the line reactive power risk area is greater than the preset line reactive power risk area threshold, an abnormal risk signal is generated and sent to the early warning display unit via the operation monitoring unit. Upon receiving the abnormal risk signal, the early warning display unit immediately controls the alarm light on the operation display panel to turn yellow, thereby reminding staff to perform timely maintenance and management of the operation display panel to improve the completeness and accuracy of data display.

[0014] Example 2: Upon receiving a high-risk signal, the efficiency analysis unit immediately collects boiler operating data, including boiler oxygen supply, flue gas temperature, nitrogen and oxygen concentration, and flue gas dust content. It then performs combustion monitoring and assessment analysis on this data to determine the boiler's operating efficiency, enabling timely optimization and management to improve its performance. The specific combustion monitoring and assessment analysis process is as follows: The boiler oxygen supply within the time threshold is obtained, and the boiler oxygen supply is compared and analyzed with the preset boiler oxygen supply range recorded and stored internally. If the oxygen supply to the boiler is not within the preset range, a control signal is generated and sent to the early warning display unit. Upon receiving the control signal, the early warning display unit immediately displays the warning in the form of the text "Oxygen Adjustment", thereby enabling staff to make timely adjustments to the oxygen supply in order to improve the boiler's combustion efficiency. If the boiler oxygen supply is within the preset boiler oxygen supply range, a monitoring signal is generated. When a monitoring signal is generated, the boiler flue gas temperature, nitrogen and oxygen concentration, and flue gas dust content values ​​are obtained at each sub-time node. The boiler flue gas temperature, nitrogen and oxygen concentration, and flue gas dust content values ​​are compared and analyzed with the preset boiler flue gas temperature threshold, preset nitrogen and oxygen concentration threshold, and preset flue gas dust content threshold recorded and stored internally. The portions of the boiler flue gas temperature value, nitrogen and oxygen concentration value, and flue gas dust content value that are greater than the preset boiler flue gas temperature threshold, nitrogen and oxygen concentration value, and flue gas dust content value that are greater than the preset nitrogen and oxygen concentration threshold are obtained and marked as risk flue gas temperature value FYi, risk nitrogen and oxygen content value FDi, and risk flue gas dust value FCI, respectively. According to the formula The efficiency risk assessment coefficients for each sub-time node are obtained, where α, β, and ε are the preset weighting factor coefficients for risky smoke temperature, risky nitrogen oxide content, and risky smoke dust, respectively. α, β, and ε are all positive numbers greater than zero. Xi is the efficiency risk assessment coefficient for each sub-time node. The maximum value of the efficiency risk assessment coefficient is obtained, and then the mean value of the efficiency risk assessment coefficient after removing the maximum value is obtained and marked as the average efficiency risk assessment value. The average efficiency risk assessment value is then compared and analyzed with the preset average efficiency risk assessment value threshold stored internally. If the average efficiency risk assessment value is greater than or equal to the preset average efficiency risk assessment value threshold, no signal will be generated; If the average efficiency risk assessment value is less than the preset average efficiency risk assessment value threshold, a non-compliance signal is generated and sent to the early warning display unit. Upon receiving the non-compliance signal, the early warning display unit immediately displays the message "low efficiency" and promptly optimizes and adjusts the boiler to improve its combustion efficiency. Upon receiving a high-risk signal, the optimization management unit immediately retrieves the runaway risk assessment coefficient S from the operation monitoring unit and the average efficiency risk assessment value from the efficiency analysis unit. It then conducts in-depth optimization and adjustment assessment analysis on the runaway risk assessment coefficient S and the average efficiency risk assessment value to improve the boiler's combustion efficiency, while simultaneously enhancing the rationality and accuracy of boiler optimization. The in-depth optimization and adjustment assessment analysis process is as follows: The portions of the runaway risk assessment coefficient S exceeding the preset runaway risk assessment coefficient threshold and the portions of the average efficiency risk assessment value exceeding the preset average efficiency risk assessment value threshold are obtained and marked as runaway value and combustion risk value, respectively. The product of the runaway value and combustion risk value after data normalization is marked as the optimized assessment value, and the optimized assessment value is compared and analyzed with the preset optimized assessment value range entered and stored internally. If the optimized evaluation value is greater than the maximum value in the preset optimized evaluation value range, a first-level optimization signal is generated; If the optimized evaluation value is within the preset optimized evaluation value range, a secondary optimization signal is generated; If the optimized evaluation value is less than the minimum value in the preset optimized evaluation value range, a three-level optimization signal is generated. The optimization degree corresponding to the first-level, second-level, and third-level optimization signals decreases sequentially. The first-level, second-level, and third-level optimization signals are sent to the early warning display unit. After receiving the first-level, second-level, and third-level optimization signals, the early warning display unit immediately displays the preset optimization schemes corresponding to the first-level, second-level, and third-level optimization signals to improve the rationality and accuracy of boiler optimization. At the same time, it helps to reduce the combustible content of fly ash and slag, reduce the flue gas temperature, improve boiler efficiency, and reduce coal consumption. In summary, this invention collects operational data from a high-speed coal mill and performs safety monitoring analysis to determine whether the mill's operation is normal, enabling timely early warning management. This facilitates optimized management of the high-speed coal mill, improving boiler combustion rate and coal powder processing management. Furthermore, the assessment and analysis from three dimensions—risk speed, fluctuation risk, and fineness risk span—improves the accuracy of the analysis results. Data feedback and monitoring early warning systems provide timely alerts, enhancing the completeness and accuracy of data display. Additionally, by collecting boiler operating data and performing combustion monitoring and analysis, this invention assesses boiler efficiency, enabling timely optimization management and adjustments to improve combustion efficiency. The combined and progressive analysis methods further enhance boiler combustion efficiency, improve the rationality and accuracy of boiler optimization, and help reduce fly ash and slag combustible content, lower flue gas temperature, increase boiler efficiency, and reduce coal consumption.

[0015] The threshold is set to facilitate comparison. The size of the threshold depends on the amount of sample data and the number of bases set by those skilled in the art for each set of sample data; as long as it does not affect the ratio between the parameter and the quantized value, it is acceptable.

[0016] The above formulas are all derived from software simulation using a large amount of data and are selected to be close to the actual values. The coefficients in the formulas are set by those skilled in the art according to the actual situation. The above description is only a preferred embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any equivalent substitutions or changes made by those skilled in the art within the technical scope disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the protection scope of the present invention.

Claims

1. A data analysis based boiler combustion adjustment optimization system, characterized by, The server, the operation supervision unit, the early warning display unit, the display feedback unit, the efficiency analysis unit and the optimization management unit are included; When the server generates the supervision instruction, the supervision instruction is sent to the operation supervision unit. After receiving the supervision instruction, the operation supervision unit immediately collects the operation data of the speed mill, including the separation speed of the rotating separator in the speed mill, the powder pipe wind speed of the speed mill and the coal powder fineness of the speed mill, and performs safety supervision analysis on the operation data to obtain the out-of-control risk evaluation coefficient S, the display signal and the high-risk signal. The display signal is sent to the early warning display unit and the display feedback unit, and the high-risk signal is sent to the efficiency analysis unit and the optimization management unit; After receiving the display signal, the display feedback unit immediately collects the display data of the operation display panel of the equipment, including the running temperature of each electrical element in the operation display panel and the line reactive loss value, and performs supervision feedback evaluation analysis on the display data. The obtained abnormal risk signal is sent to the early warning display unit through the operation supervision unit; After receiving the high-risk signal, the efficiency analysis unit immediately collects the working data of the boiler equipment, including the oxygen content of the boiler, the boiler exhaust gas temperature value, the nitrogen oxygen concentration content value and the flue gas dust content value, and performs combustion supervision evaluation analysis on the working data. The obtained unqualified signal is sent to the early warning display unit; After receiving the high-risk signal, the optimization management unit immediately retrieves the out-of-control risk evaluation coefficient S from the operation supervision unit and the average efficiency risk evaluation value from the efficiency analysis unit, and performs in-depth optimization adjustment evaluation analysis on the out-of-control risk evaluation coefficient S and the average efficiency risk evaluation value. The obtained first-level optimization signal, second-level optimization signal and third-level optimization signal are sent to the early warning display unit.

2. The data analysis based boiler combustion adjustment optimization system of claim 1, wherein, The safety supervision analysis process of the operation supervision unit is as follows: S1: Collect the time length from the start time to the end time of the use of the boiler, and mark it as a time threshold. Divide the time threshold into i sub-time nodes, i is a natural number greater than zero. Get the separation speed of the rotating separator in the speed mill in each sub-time node, and analyze the separation speed with the preset separation speed threshold. If the ratio of the separation speed to the preset separation speed threshold is not equal to one, the sub-time node corresponding to the ratio of the separation speed to the preset separation speed threshold which is not equal to one is marked as a risk node. Get the ratio of the number of analysis nodes to the total number of sub-time nodes, and mark the ratio of the number of analysis nodes to the total number of sub-time nodes as the risk speed value FZ; S12: Get the powder pipe wind speed of the speed mill in each sub-time node. Establish a rectangular coordinate system with time as the X-axis and powder pipe wind speed as the Y-axis, and draw a powder pipe wind speed curve in a dotting manner. Get the fluctuation frequency and the average time interval between connected fluctuation frequencies from the powder pipe wind speed curve. Then, after data normalization processing of the fluctuation frequency and the average time interval between connected fluctuation frequencies, the product obtained is marked as the fluctuation risk value BF; S13: Obtain the coal fineness of the pulverizing coal mill in each sub-time node, thereby constructing a set A of coal fineness, obtaining the difference between two connected subsets in set A, and marking the difference between two connected subsets in set A as a fineness fluctuation value, and then obtaining the maximum and minimum values of the fineness fluctuation value, and marking the difference between the maximum and minimum values of the fineness fluctuation value as a fineness risk span value XD; S14: Obtain a runaway risk assessment coefficient S according to the formula, and compare and analyze the runaway risk assessment coefficient S with a preset runaway risk assessment coefficient threshold value stored therein: If the ratio of the runaway risk assessment coefficient S to the preset runaway risk assessment coefficient threshold value is less than one, a display signal is generated; If the ratio of the runaway risk assessment coefficient S to the preset runaway risk assessment coefficient threshold value is greater than or equal to one, a high-risk signal is generated.

3. The data analysis based boiler combustion adjustment optimization system of claim 1, wherein, The regulatory feedback evaluation and analysis process of the display feedback unit is as follows: Obtain the operating temperature of each electrical element in the operation display panel within the time threshold, and compare and analyze the operating temperature with a preset operating temperature threshold value. If the operating temperature is greater than the preset operating temperature threshold value, mark the part with the operating temperature greater than the preset operating temperature threshold value as an overheating risk value, construct a set B of overheating risk values, compare and analyze the subsets in set B with a preset overheating risk value threshold value, and if the overheating risk value is greater than the preset overheating risk value threshold value, mark the ratio of the number of subsets with the overheating risk value greater than the preset overheating risk value threshold value to the total number of subsets as an element overheating risk ratio; Obtain the line reactive loss value in the operation display panel within each sub-time node, and establish a rectangular coordinate system with time as the X-axis and the line reactive loss value as the Y-axis. Draw the line reactive loss value curve by dotting, and at the same time, draw the preset line reactive loss value threshold curve in the coordinate system. Obtain the area above the line segment of the line reactive loss value curve above the preset line reactive loss value threshold curve and the area enclosed by the preset line reactive loss value threshold curve, and mark it as a line reactive risk area. Analyze the element overheating risk ratio and the line reactive risk area with the preset element overheating risk ratio threshold value and the preset line reactive risk area threshold value stored therein: If the element overheating risk ratio is less than or equal to the preset element overheating risk ratio threshold value, and the line reactive risk area is less than or equal to the preset line reactive risk area threshold value, no signal is generated; If the element overheating risk ratio is greater than the preset element overheating risk ratio threshold value, or the line reactive risk area is greater than the preset line reactive risk area threshold value, an abnormal risk signal is generated.

4. The data analysis based boiler combustion adjustment optimization system of claim 1, wherein, The combustion regulatory evaluation and analysis process of the efficiency analysis unit is as follows: Obtain the oxygen flow rate of the boiler within the time threshold, and compare and analyze the oxygen flow rate of the boiler with a preset oxygen flow rate interval of the boiler stored therein: If the oxygen flow rate of the boiler is not within the preset oxygen flow rate interval of the boiler, a regulation signal is generated; If the oxygen flow rate of the boiler is within the preset oxygen flow rate interval of the boiler, a regulatory signal is generated.

5. A data analysis based boiler combustion adjustment optimization system as claimed in claim 4 wherein, When a regulatory signal is generated in the efficiency analysis unit, The boiler flue gas temperature value, nitrogen oxygen concentration content value and flue gas dust content value in each sub-time node are obtained, and the boiler flue gas temperature value, nitrogen oxygen concentration content value and flue gas dust content value are compared and analyzed with the preset boiler flue gas temperature value threshold, preset nitrogen oxygen concentration content value threshold and preset flue gas dust content value threshold stored in the internal recording, so that the part of the boiler flue gas temperature value greater than the preset boiler flue gas temperature value threshold, the part of the nitrogen oxygen concentration content value greater than the preset nitrogen oxygen concentration content value threshold and the part of the flue gas dust content value greater than the preset flue gas dust content value threshold are obtained, and they are marked as risk flue gas temperature value FYi, risk nitrogen oxygen content value FDi and risk smoke dust value FCi respectively; According to the formula, the efficiency risk assessment coefficient Xi of each sub-time node is obtained, the maximum value of the efficiency risk assessment coefficient is obtained, and then the average value of the efficiency risk assessment coefficient after removing the maximum value of the efficiency risk assessment coefficient is obtained, which is marked as the average efficiency risk assessment value, and the average efficiency risk assessment value is compared and analyzed with the preset average efficiency risk assessment value threshold stored in the internal recording: If the average efficiency risk assessment value is greater than or equal to the preset average efficiency risk assessment value threshold, no signal is generated; If the average efficiency risk assessment value is less than the preset average efficiency risk assessment value threshold, an unqualified signal is generated.

6. The data analysis based boiler combustion adjustment optimization system, as recited in claim 1, c h a r a c t e r i z e d b y, The in-depth optimization adjustment evaluation analysis process of the optimization management unit is as follows: The part of the runaway risk assessment coefficient S exceeding the preset runaway risk assessment coefficient threshold and the part of the average efficiency risk assessment value exceeding the preset average efficiency risk assessment value threshold are obtained, and they are marked as runaway value and combustion risk value respectively, and the product obtained after data normalization processing of the runaway value and the combustion risk value is marked as optimization evaluation value, and the optimization evaluation value is compared and analyzed with the preset optimization evaluation value interval stored in the internal recording: If the optimization evaluation value is greater than the maximum value in the preset optimization evaluation value interval, a first-level optimization signal is generated; If the optimization evaluation value is located in the preset optimization evaluation value interval, a second-level optimization signal is generated; If the optimization evaluation value is less than the minimum value in the preset optimization evaluation value interval, a third-level optimization signal is generated.

Images