Intelligent monitoring and evaluating system for boiler combustion performance optimization

Abstract

The invention relates to the technical field of boiler monitoring and evaluation, and discloses an intelligent monitoring and evaluation system for boiler combustion performance optimization, a set construction module acquires combustion performance feedback parameters of a boiler based on a plurality of acquisition moments to obtain a plurality of combustion performance feedback parameter sets; the parameter analysis module analyzes each combustion performance feedback parameter set and determines a combustion feedback factor of each combustion performance feedback parameter; the factor calculation module divides all the combustion feedback abnormal factors based on the characteristic combustion feedback abnormal factors and calculates comprehensive combustion feedback factors; and the monitoring evaluation module analyzes all the comprehensive combustion feedback factors, calculates a monitoring evaluation coefficient and judges whether the combustion performance optimization of the boiler meets the requirement or not, so that intelligent monitoring evaluation of a boiler combustion performance optimization strategy can be realized, the monitoring evaluation precision and evaluation efficiency of the boiler are ensured, and the monitoring evaluation efficiency of the boiler is improved. Therefore, the operation stability and economy of the boiler are remarkably improved, and energy waste is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of boiler monitoring and evaluation, and in particular to an intelligent monitoring and evaluation system for optimizing boiler combustion performance. Background Art

[0002] Amidst the ongoing global energy restructuring and increasingly stringent environmental standards, boilers, as key components of thermal power generation and industrial production, are facing increasing scrutiny for improving combustion efficiency and effectively controlling pollutant emissions. Optimizing boiler combustion performance is crucial and urgent. However, once a new optimization strategy has been developed, accurately and comprehensively evaluating it remains a crucial technical challenge.

[0003] In the existing technology, models are generally used to predict the carbon content of fly ash, the carbon content of slag and the carbon monoxide content, and then these parameters are substituted into the counter-balance model to realize intelligent monitoring and evaluation. However, these methods have obvious shortcomings: on the one hand, the accuracy of model prediction is easily affected by a variety of complex factors, such as changes in coal types, fluctuations in combustion conditions, etc., which lead to deviations between the predicted results and the actual values, thereby affecting the reliability of intelligent monitoring and evaluation; on the other hand, the construction of the counter-balance model is relatively complex, and has high requirements on data quality and quantity. In actual applications, data collection is difficult and it is difficult to ensure the integrity and accuracy of the data, which makes this evaluation method face many challenges in actual operation and cannot effectively meet the needs of accurate evaluation of boiler combustion performance. Summary of the Invention

[0004] An embodiment of the present invention provides an intelligent monitoring and evaluation system for optimizing boiler combustion performance. The present invention can realize intelligent monitoring and evaluation of boiler combustion performance optimization strategies, ensure the monitoring and evaluation accuracy and evaluation efficiency of the boiler, thereby significantly improving the stability and economy of boiler operation and reducing energy waste.

[0005] To achieve the above objectives, the present invention provides an intelligent monitoring and evaluation system for optimizing boiler combustion performance, comprising: A set building module is used to collect boiler combustion performance feedback parameters based on multiple collection moments, and to combine the combustion performance feedback parameters corresponding to each collection moment into the same type to obtain multiple combustion performance feedback parameter sets; a parameter analysis module, configured to analyze each combustion performance feedback parameter set and determine a combustion feedback factor for each combustion performance feedback parameter in the combustion performance feedback parameter set; a factor calculation module, configured to extract all combustion feedback abnormality factors and determine characteristic combustion feedback abnormality factors, classify all combustion feedback abnormality factors based on the characteristic combustion feedback abnormality factors, and calculate the comprehensive combustion feedback factor of the boiler based on the classification results; The monitoring and evaluation module is used to extract all comprehensive combustion feedback factors, analyze all comprehensive combustion feedback factors, and calculate the monitoring and evaluation coefficient of the boiler based on the analysis results. According to the monitoring and evaluation coefficient and the preset monitoring and evaluation coefficient, it is judged whether the combustion performance optimization of the boiler meets the requirements.

[0006] Furthermore, the parameter analysis module is used to: The parameter analysis module is used to sort the combustion performance feedback parameter set based on the order of collection time, and randomly determine a combustion performance feedback parameter from the combustion performance feedback parameter set as the determined combustion performance feedback parameter; The parameter analysis module is configured to determine a median combustion performance feedback parameter from the combustion performance feedback parameter set, and calculate a difference between the determined combustion performance feedback parameter and the median combustion performance feedback parameter as a first abnormality factor; The parameter analysis module is configured to use all remaining combustion performance feedback parameters in the combustion performance feedback parameter set as comparative combustion performance feedback parameters, calculate a second difference between each comparative combustion performance feedback parameter and the determined combustion performance feedback parameter, and sum all the second differences to obtain a second abnormality factor; The parameter analysis module is used to determine the combustion feedback abnormality factor corresponding to the combustion performance feedback parameter according to the first abnormality factor and the second abnormality factor; The parameter analysis module is used to randomly extract the combustion performance feedback parameters in the combustion performance feedback parameter set and determine the corresponding combustion feedback factors.

[0007] Furthermore, the factor calculation module is used to: The factor calculation module is used to classify all combustion feedback abnormality factors based on the characteristic combustion feedback abnormality factor, and when the combustion feedback abnormality factor is less than or equal to the characteristic combustion feedback abnormality factor, the corresponding combustion feedback abnormality factor is classified into a first combustion feedback abnormality factor sequence; The factor calculation module is configured to classify the corresponding combustion feedback abnormality factor into a second combustion feedback abnormality factor sequence when the combustion feedback abnormality factor is greater than the characteristic combustion feedback abnormality factor; The factor calculation module is used to calculate a first sequence influence value and a second sequence influence value based on the first combustion feedback abnormality factor sequence and the second combustion feedback abnormality factor sequence; The factor calculation module is used to calculate the comprehensive combustion feedback factor of the boiler based on the first combustion feedback abnormality factor sequence, the second combustion feedback abnormality factor sequence, the first sequence influence value and the second sequence influence value.

[0008] Furthermore, the factor calculation module is used to: The factor calculation module is used to calculate the first sequence impact value corresponding to the first combustion feedback abnormality factor sequence according to the following formula: ; Wherein, a1 is the first sequence influence value corresponding to the first combustion feedback abnormality factor sequence, s1 is the first calculation weight, s2 is the second calculation weight, s2>s1, s1+s2=1, d1 is the mean corresponding to the first combustion feedback abnormality factor sequence, f1 is the number of combustion feedback abnormality factors in the first combustion feedback abnormality factor sequence, f2 is the number of combustion feedback abnormality factors in the second combustion feedback abnormality factor sequence, and d2 is the mean corresponding to the second combustion feedback abnormality factor sequence.

[0009] Furthermore, the factor calculation module is used to: The factor calculation module is used to determine a first initial combustion feedback abnormality factor and a first final combustion feedback abnormality factor of the first combustion feedback abnormality factor sequence; The factor calculation module is used to determine a second initial combustion feedback abnormality factor and a second final combustion feedback abnormality factor of the second combustion feedback abnormality factor sequence; The factor calculation module is used to mark the mean value of the first combustion feedback abnormality factor sequence in the first combustion feedback abnormality factor sequence as a first sequence mark; The factor calculation module is used to mark the mean value of the second combustion feedback abnormality factor sequence in the second combustion feedback abnormality factor sequence as a second sequence mark; The factor calculation module is used to count the number g1 of first combustion feedback abnormality factors from the first sequence mark to the first end combustion feedback abnormality factor; The factor calculation module is used to count the number g2 of second combustion feedback abnormality factors marked by the second sequence to the second initial combustion feedback abnormality factor; The factor calculation module is used to calculate the first combustion feedback abnormality factor ratio h1 according to the first combustion feedback abnormality factor quantity g1 and the second combustion feedback abnormality factor quantity g2, wherein: , j is the first combustion feedback abnormality factor sequence and the total number of combustion feedback abnormality factors corresponding to the first combustion feedback abnormality factor sequence; The factor calculation module is used to count the number g3 of third combustion feedback abnormality factors marked from the first sequence to the first initial combustion feedback abnormality factor; The factor calculation module is used to count the fourth combustion feedback abnormality factor number g4 from the second sequence mark to the second end combustion feedback abnormality factor; The factor calculation module is used to calculate the second combustion feedback abnormality factor ratio h2 according to the third combustion feedback abnormality factor quantity g3 and the fourth combustion feedback abnormality factor quantity g4, wherein, , a2 is the second sequence impact value.

[0010] Furthermore, the factor calculation module is used to: The factor calculation module is used to calculate the absolute value of the difference between the first combustion feedback abnormality factor ratio and the second combustion feedback abnormality factor ratio, and calculate the sum of the first combustion feedback abnormality factor ratio and the second combustion feedback abnormality factor ratio; The factor calculation module is used to use the ratio of the absolute value of the difference to the sum as the comprehensive combustion feedback factor of the boiler.

[0011] Furthermore, the monitoring and evaluation module is used to: The monitoring and evaluation module is used to randomly combine each k comprehensive combustion feedback factors to obtain multiple comprehensive combustion feedback factor groups; The monitoring and evaluation module is used to calculate the comprehensive combustion feedback factor and value of each comprehensive combustion feedback factor group, and extract the maximum comprehensive combustion feedback factor from all comprehensive combustion feedback factors; The monitoring and evaluation module is used to calculate the ratio of the maximum comprehensive combustion feedback factor to the sum of each comprehensive combustion feedback factor as a relative comprehensive combustion feedback factor; The monitoring and evaluation module is used to randomly match all relative comprehensive combustion feedback factors in pairs to obtain multiple relative comprehensive combustion feedback factor groups, and calculate the monitoring and evaluation coefficient of the boiler based on all relative comprehensive combustion feedback factor groups.

[0012] Furthermore, the monitoring and evaluation module is used to: The monitoring and evaluation module is used to calculate the monitoring and evaluation coefficient of the boiler according to the following formula: ; Among them, q is the monitoring evaluation coefficient of the boiler, n is the number of relative comprehensive combustion feedback factor groups, w1 y is a relative comprehensive combustion feedback factor in the yth relative comprehensive combustion feedback factor group, w2 y is another relative comprehensive combustion feedback factor in the yth relative comprehensive combustion feedback factor group, For all The minimum value of The maximum value of .

[0013] Furthermore, the monitoring and evaluation module is used to: The monitoring and evaluation module is configured to determine that the combustion performance optimization of the boiler does not meet the requirements when the monitoring and evaluation coefficient is less than the preset monitoring and evaluation coefficient; The monitoring and evaluation module is used to determine whether the combustion performance optimization of the boiler meets the requirements when the monitoring and evaluation coefficient is greater than or equal to the preset monitoring and evaluation coefficient.

[0014] Compared with the prior art, the present invention has the following beneficial effects: The present invention discloses an intelligent monitoring and evaluation system for optimizing boiler combustion performance. The set construction module collects combustion performance feedback parameters of the boiler based on multiple collection moments to obtain multiple combustion performance feedback parameter sets; the parameter analysis module analyzes each combustion performance feedback parameter set to determine the combustion feedback factor of each combustion performance feedback parameter; the factor calculation module divides all combustion feedback abnormality factors based on characteristic combustion feedback abnormality factors to calculate a comprehensive combustion feedback factor; the monitoring and evaluation module analyzes all comprehensive combustion feedback factors, calculates a monitoring and evaluation coefficient, and judges whether the combustion performance optimization of the boiler meets the requirements. The intelligent monitoring and evaluation of the boiler combustion performance optimization strategy can be realized, and the monitoring and evaluation accuracy and evaluation efficiency of the boiler can be guaranteed, thereby significantly improving the operating stability and economy of the boiler and reducing energy waste. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Various other advantages and benefits will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiment below. The accompanying drawings are for illustration purposes only and are not to be considered as limiting the present invention. The same reference symbols are used throughout the drawings to represent the same components. In the drawings: Figure 1 A structural diagram of an intelligent monitoring and evaluation system for optimizing boiler combustion performance in an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0016] The following embodiments of the present invention are described in further detail with reference to the accompanying drawings and examples. The following embodiments are used to illustrate the present invention but are not intended to limit the scope of the present invention.

[0017] In the description of this application, it should be understood that the terms "center", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating the orientation or position relationship, are based on the orientation or position relationship shown in the accompanying drawings, and are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on this application.

[0018] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of the technical features being referred to. Thus, a feature specified as "first" or "second" may explicitly or implicitly include one or more of such features. Throughout this application, unless otherwise specified, "plurality" means two or more.

[0019] In the description of this application, it should be noted that, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" should be understood in a broad sense. For example, they can refer to fixed, detachable, or integral connections; mechanical or electrical connections; direct or indirect connections through an intermediate medium; and internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in this application based on the specific circumstances.

[0020] The following is a description of preferred embodiments of the present invention with reference to the accompanying drawings.

[0021] like Figure 1 As shown, an embodiment of the present invention discloses an intelligent monitoring and evaluation system for optimizing boiler combustion performance, comprising: A set building module is used to collect boiler combustion performance feedback parameters based on multiple collection moments, and to combine the combustion performance feedback parameters corresponding to each collection moment into the same type to obtain multiple combustion performance feedback parameter sets; In this embodiment, the collection moment refers to a specific collection time. Here, the number of collection moments is preferably 30, which can be set according to actual conditions. 30 collection moments are set.

[0022] In this embodiment, the combustion performance feedback parameters include boiler load, boiler coking rate, coking temperature, coking thickness, boiler corrosion degree, etc.

[0023] In this embodiment, the boiler loads corresponding to each acquisition moment are combined to obtain a combustion performance feedback parameter set, which is a same-type combination.

[0024] a parameter analysis module, configured to analyze each combustion performance feedback parameter set and determine a combustion feedback factor for each combustion performance feedback parameter in the combustion performance feedback parameter set; In some embodiments of the present application, the parameter analysis module is used to: The parameter analysis module is used to sort the combustion performance feedback parameter set based on the order of collection time, and randomly determine a combustion performance feedback parameter from the combustion performance feedback parameter set as the determined combustion performance feedback parameter; The parameter analysis module is configured to determine a median combustion performance feedback parameter from the combustion performance feedback parameter set, and calculate a difference between the determined combustion performance feedback parameter and the median combustion performance feedback parameter as a first abnormality factor; The parameter analysis module is configured to use all remaining combustion performance feedback parameters in the combustion performance feedback parameter set as comparative combustion performance feedback parameters, calculate a second difference between each comparative combustion performance feedback parameter and the determined combustion performance feedback parameter, and sum all the second differences to obtain a second abnormality factor; The parameter analysis module is used to determine the combustion feedback abnormality factor corresponding to the combustion performance feedback parameter according to the first abnormality factor and the second abnormality factor; The parameter analysis module is used to randomly extract the combustion performance feedback parameters in the combustion performance feedback parameter set and determine the corresponding combustion feedback factors.

[0025] In this embodiment, the median combustion performance feedback parameter refers to the median of all combustion performance feedback parameters.

[0026] In this embodiment, the first abnormality factor is the absolute value of the difference.

[0027] In this embodiment, the second difference means first calculating the difference and then taking the absolute value.

[0028] In this embodiment, the sum of the first abnormality factor and the second abnormality factor is used as the combustion feedback abnormality factor corresponding to the combustion performance feedback parameter.

[0029] The beneficial effect of the above technical solution is: the present invention determines the combustion feedback abnormality factor corresponding to the combustion performance feedback parameter based on the first abnormality factor and the second abnormality factor. The combustion feedback abnormality factor can reflect the degree of discreteness of each combustion performance feedback parameter relative to all combustion performance feedback parameters, providing technical support for boiler monitoring and evaluation.

[0030] a factor calculation module, configured to extract all combustion feedback abnormality factors and determine characteristic combustion feedback abnormality factors, classify all combustion feedback abnormality factors based on the characteristic combustion feedback abnormality factors, and calculate the comprehensive combustion feedback factor of the boiler based on the classification results; In some embodiments of the present application, the factor calculation module is used to: The factor calculation module is used to classify all combustion feedback abnormality factors based on the characteristic combustion feedback abnormality factor, and when the combustion feedback abnormality factor is less than or equal to the characteristic combustion feedback abnormality factor, the corresponding combustion feedback abnormality factor is classified into a first combustion feedback abnormality factor sequence; The factor calculation module is configured to classify the corresponding combustion feedback abnormality factor into a second combustion feedback abnormality factor sequence when the combustion feedback abnormality factor is greater than the characteristic combustion feedback abnormality factor; The factor calculation module is used to calculate a first sequence influence value and a second sequence influence value based on the first combustion feedback abnormality factor sequence and the second combustion feedback abnormality factor sequence; The factor calculation module is used to calculate the comprehensive combustion feedback factor of the boiler based on the first combustion feedback abnormality factor sequence, the second combustion feedback abnormality factor sequence, the first sequence influence value and the second sequence influence value.

[0031] In this embodiment, the characteristic combustion feedback abnormality factor refers to the average value of all combustion feedback abnormality factors.

[0032] The beneficial effect of the above technical solution is: the present invention calculates the first sequence impact value and the second sequence impact value based on the first combustion feedback abnormality factor sequence and the second combustion feedback abnormality factor sequence, and the first sequence impact value and the second sequence impact value can further ensure the comprehensiveness and accuracy of the boiler monitoring evaluation.

[0033] In some embodiments of the present application, the factor calculation module is used to: The factor calculation module is used to calculate the first sequence impact value corresponding to the first combustion feedback abnormality factor sequence according to the following formula: ; Wherein, a1 is the first sequence influence value corresponding to the first combustion feedback abnormality factor sequence, s1 is the first calculation weight, s2 is the second calculation weight, s2>s1, s1+s2=1, d1 is the mean corresponding to the first combustion feedback abnormality factor sequence, f1 is the number of combustion feedback abnormality factors in the first combustion feedback abnormality factor sequence, f2 is the number of combustion feedback abnormality factors in the second combustion feedback abnormality factor sequence, and d2 is the mean corresponding to the second combustion feedback abnormality factor sequence.

[0034] In this embodiment, the second sequence impact value corresponding to the second combustion feedback abnormality factor sequence is calculated according to the following formula: .

[0035] In some embodiments of the present application, the factor calculation module is used to: The factor calculation module is used to determine a first initial combustion feedback abnormality factor and a first final combustion feedback abnormality factor of the first combustion feedback abnormality factor sequence; The factor calculation module is used to determine a second initial combustion feedback abnormality factor and a second final combustion feedback abnormality factor of the second combustion feedback abnormality factor sequence; The factor calculation module is used to mark the mean value of the first combustion feedback abnormality factor sequence in the first combustion feedback abnormality factor sequence as a first sequence mark; The factor calculation module is used to mark the mean value of the second combustion feedback abnormality factor sequence in the second combustion feedback abnormality factor sequence as a second sequence mark; The factor calculation module is used to count the number g1 of first combustion feedback abnormality factors from the first sequence mark to the first end combustion feedback abnormality factor; The factor calculation module is used to count the number g2 of second combustion feedback abnormality factors marked by the second sequence to the second initial combustion feedback abnormality factor; The factor calculation module is used to calculate the first combustion feedback abnormality factor ratio h1 according to the first combustion feedback abnormality factor quantity g1 and the second combustion feedback abnormality factor quantity g2, wherein: , j is the first combustion feedback abnormality factor sequence and the total number of combustion feedback abnormality factors corresponding to the first combustion feedback abnormality factor sequence; The factor calculation module is used to count the number g3 of third combustion feedback abnormality factors marked from the first sequence to the first initial combustion feedback abnormality factor; The factor calculation module is used to count the fourth combustion feedback abnormality factor number g4 from the second sequence mark to the second end combustion feedback abnormality factor; The factor calculation module is used to calculate the second combustion feedback abnormality factor ratio h2 according to the third combustion feedback abnormality factor quantity g3 and the fourth combustion feedback abnormality factor quantity g4, wherein, , a2 is the second sequence impact value.

[0036] In this embodiment, when counting the number g1 of the first combustion feedback abnormality factors, the number of the first sequence marker and the first end combustion feedback abnormality factors are not counted; when counting the number g2 of the second combustion feedback abnormality factors, the number of the second sequence marker and the second initial combustion feedback abnormality factors are not counted; when counting the number g3 of the third combustion feedback abnormality factors, the number of the first sequence marker and the first initial combustion feedback abnormality factors are not counted; and when counting the number g4 of the fourth combustion feedback abnormality factors, the number of the second sequence marker and the second end combustion feedback abnormality factors are not counted.

[0037] In some embodiments of the present application, the factor calculation module is used to: The factor calculation module is used to calculate the absolute value of the difference between the first combustion feedback abnormality factor ratio and the second combustion feedback abnormality factor ratio, and calculate the sum of the first combustion feedback abnormality factor ratio and the second combustion feedback abnormality factor ratio; The factor calculation module is used to use the ratio of the absolute value of the difference to the sum as the comprehensive combustion feedback factor of the boiler.

[0038] The beneficial effect of the above technical solution is: the present invention divides all combustion feedback abnormality factors based on the characteristic combustion feedback abnormality factor, calculates the comprehensive combustion feedback factor of the boiler based on the division result, ensures the calculation accuracy and efficiency of the comprehensive combustion feedback factor, and realizes comprehensive analysis of the combustion performance of the boiler through the comprehensive combustion feedback factor.

[0039] The monitoring and evaluation module is used to extract all comprehensive combustion feedback factors, analyze all comprehensive combustion feedback factors, and calculate the monitoring and evaluation coefficient of the boiler based on the analysis results. According to the monitoring and evaluation coefficient and the preset monitoring and evaluation coefficient, it is judged whether the combustion performance optimization of the boiler meets the requirements.

[0040] In some embodiments of the present application, the monitoring and evaluation module is used to: The monitoring and evaluation module is used to randomly combine each k comprehensive combustion feedback factors to obtain multiple comprehensive combustion feedback factor groups; The monitoring and evaluation module is used to calculate the comprehensive combustion feedback factor and value of each comprehensive combustion feedback factor group, and extract the maximum comprehensive combustion feedback factor from all comprehensive combustion feedback factors; The monitoring and evaluation module is used to calculate the ratio of the maximum comprehensive combustion feedback factor to the sum of each comprehensive combustion feedback factor as a relative comprehensive combustion feedback factor; The monitoring and evaluation module is used to randomly match all relative comprehensive combustion feedback factors in pairs to obtain multiple relative comprehensive combustion feedback factor groups, and calculate the monitoring and evaluation coefficient of the boiler based on all relative comprehensive combustion feedback factor groups.

[0041] In this embodiment, k is preferably 3, that is, every three comprehensive combustion feedback factors are combined.

[0042] The beneficial effect of the above technical solution is: the present invention randomly matches all relative comprehensive combustion feedback factors in pairs to obtain multiple relative comprehensive combustion feedback factor groups, and calculates the boiler's monitoring and evaluation coefficient based on all relative comprehensive combustion feedback factor groups, which can realize the intelligent monitoring and evaluation of the boiler combustion performance optimization strategy, ensure the boiler's monitoring and evaluation accuracy and evaluation efficiency, and thus significantly improve the boiler's operating stability and economy, reduce energy waste, and avoid the problems of complex construction, data quality, quantity requirements, etc. in existing model evaluation.

[0043] In some embodiments of the present application, the monitoring and evaluation module is used to: The monitoring and evaluation module is used to calculate the monitoring and evaluation coefficient of the boiler according to the following formula: ; Among them, q is the monitoring evaluation coefficient of the boiler, n is the number of relative comprehensive combustion feedback factor groups, w1 y is a relative comprehensive combustion feedback factor in the yth relative comprehensive combustion feedback factor group, w2 y is another relative comprehensive combustion feedback factor in the yth relative comprehensive combustion feedback factor group, For all The minimum value of The maximum value of .

[0044] In some embodiments of the present application, the monitoring and evaluation module is used to: The monitoring and evaluation module is configured to determine that the combustion performance optimization of the boiler does not meet the requirements when the monitoring and evaluation coefficient is less than the preset monitoring and evaluation coefficient; The monitoring and evaluation module is used to determine whether the combustion performance optimization of the boiler meets the requirements when the monitoring and evaluation coefficient is greater than or equal to the preset monitoring and evaluation coefficient.

[0045] In this embodiment, the preset monitoring evaluation coefficient is preferably 8, and can be adjusted according to actual conditions.

[0046] The beneficial effect of the above technical solution is that the present invention determines whether the combustion performance optimization of the boiler meets the requirements based on the monitoring evaluation coefficient and the preset monitoring evaluation coefficient, making the monitoring evaluation more convenient and accurate.

[0047] In the description of the above embodiments, specific features, structures, materials or characteristics may be combined in an appropriate manner in any one or more embodiments or examples.

[0048] While the present invention has been described above with reference to exemplary embodiments, various modifications may be made and equivalent components may be substituted without departing from the scope of the present invention. In particular, the various features of the disclosed embodiments may be combined with one another in any manner, provided no structural conflicts exist. These combinations are not fully described in this specification for reasons of space and resource conservation.

[0049] Those skilled in the art will understand that the above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art will still be able to modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein with equivalents. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. An intelligent monitoring and evaluation system for boiler combustion performance optimization, characterized in that: include: A set building module is used to collect boiler combustion performance feedback parameters based on multiple collection moments, and to combine the combustion performance feedback parameters corresponding to each collection moment into the same type to obtain multiple combustion performance feedback parameter sets; a parameter analysis module, configured to analyze each combustion performance feedback parameter set and determine a combustion feedback factor for each combustion performance feedback parameter in the combustion performance feedback parameter set; a factor calculation module, configured to extract all combustion feedback abnormality factors and determine characteristic combustion feedback abnormality factors, classify all combustion feedback abnormality factors based on the characteristic combustion feedback abnormality factors, and calculate the comprehensive combustion feedback factor of the boiler based on the classification results; The monitoring and evaluation module is used to extract all comprehensive combustion feedback factors, analyze all comprehensive combustion feedback factors, and calculate the monitoring and evaluation coefficient of the boiler based on the analysis results. According to the monitoring and evaluation coefficient and the preset monitoring and evaluation coefficient, it is judged whether the combustion performance optimization of the boiler meets the requirements.

2. The intelligent monitoring and evaluation system for boiler combustion performance optimization according to claim 1 is characterized in that: The parameter analysis module is used to: The parameter analysis module is used to sort the combustion performance feedback parameter set based on the order of collection time, and randomly determine a combustion performance feedback parameter from the combustion performance feedback parameter set as the determined combustion performance feedback parameter; The parameter analysis module is configured to determine a median combustion performance feedback parameter from the combustion performance feedback parameter set, and calculate a difference between the determined combustion performance feedback parameter and the median combustion performance feedback parameter as a first abnormality factor; The parameter analysis module is configured to use all remaining combustion performance feedback parameters in the combustion performance feedback parameter set as comparative combustion performance feedback parameters, calculate a second difference between each comparative combustion performance feedback parameter and the determined combustion performance feedback parameter, and sum all the second differences to obtain a second abnormality factor; The parameter analysis module is used to determine the combustion feedback abnormality factor corresponding to the combustion performance feedback parameter according to the first abnormality factor and the second abnormality factor; The parameter analysis module is used to randomly extract the combustion performance feedback parameters in the combustion performance feedback parameter set and determine the corresponding combustion feedback factors.

3. The intelligent monitoring and evaluation system for boiler combustion performance optimization according to claim 1 is characterized in that: The factor calculation module is used to: The factor calculation module is used to classify all combustion feedback abnormality factors based on the characteristic combustion feedback abnormality factor, and when the combustion feedback abnormality factor is less than or equal to the characteristic combustion feedback abnormality factor, the corresponding combustion feedback abnormality factor is classified into a first combustion feedback abnormality factor sequence; The factor calculation module is configured to classify the corresponding combustion feedback abnormality factor into a second combustion feedback abnormality factor sequence when the combustion feedback abnormality factor is greater than the characteristic combustion feedback abnormality factor; The factor calculation module is used to calculate a first sequence influence value and a second sequence influence value based on the first combustion feedback abnormality factor sequence and the second combustion feedback abnormality factor sequence; The factor calculation module is used to calculate the comprehensive combustion feedback factor of the boiler based on the first combustion feedback abnormality factor sequence, the second combustion feedback abnormality factor sequence, the first sequence influence value and the second sequence influence value.

4. The intelligent monitoring and evaluation system for optimizing boiler combustion performance according to claim 3 is characterized in that: The factor calculation module is used to: The factor calculation module is used to calculate the first sequence impact value corresponding to the first combustion feedback abnormality factor sequence according to the following formula: ； Wherein, a1 is the first sequence influence value corresponding to the first combustion feedback abnormality factor sequence, s1 is the first calculation weight, s2 is the second calculation weight, s2>s1, s1+s2=1, d1 is the mean corresponding to the first combustion feedback abnormality factor sequence, f1 is the number of combustion feedback abnormality factors in the first combustion feedback abnormality factor sequence, f2 is the number of combustion feedback abnormality factors in the second combustion feedback abnormality factor sequence, and d2 is the mean corresponding to the second combustion feedback abnormality factor sequence.

5. The intelligent monitoring and evaluation system for optimizing boiler combustion performance according to claim 4 is characterized in that: The factor calculation module is used to: The factor calculation module is used to determine a first initial combustion feedback abnormality factor and a first final combustion feedback abnormality factor of the first combustion feedback abnormality factor sequence; The factor calculation module is used to determine a second initial combustion feedback abnormality factor and a second final combustion feedback abnormality factor of the second combustion feedback abnormality factor sequence; The factor calculation module is used to mark the mean value of the first combustion feedback abnormality factor sequence in the first combustion feedback abnormality factor sequence as a first sequence mark; The factor calculation module is used to mark the mean value of the second combustion feedback abnormality factor sequence in the second combustion feedback abnormality factor sequence as a second sequence mark; The factor calculation module is used to count the number g1 of first combustion feedback abnormality factors from the first sequence mark to the first end combustion feedback abnormality factor; The factor calculation module is used to count the number g2 of second combustion feedback abnormality factors marked by the second sequence to the second initial combustion feedback abnormality factor; The factor calculation module is used to calculate the first combustion feedback abnormality factor ratio h1 according to the first combustion feedback abnormality factor quantity g1 and the second combustion feedback abnormality factor quantity g2, wherein: , j is the first combustion feedback abnormality factor sequence and the total number of combustion feedback abnormality factors corresponding to the first combustion feedback abnormality factor sequence; The factor calculation module is used to count the number g3 of third combustion feedback abnormality factors marked from the first sequence to the first initial combustion feedback abnormality factor; The factor calculation module is used to count the fourth combustion feedback abnormality factor number g4 from the second sequence mark to the second end combustion feedback abnormality factor; The factor calculation module is used to calculate the second combustion feedback abnormality factor ratio h2 according to the third combustion feedback abnormality factor quantity g3 and the fourth combustion feedback abnormality factor quantity g4, wherein, , a2 is the second sequence impact value.

6. The intelligent monitoring and evaluation system for optimizing boiler combustion performance according to claim 5, characterized in that: The factor calculation module is used to: The factor calculation module is used to calculate the absolute value of the difference between the first combustion feedback abnormality factor ratio and the second combustion feedback abnormality factor ratio, and calculate the sum of the first combustion feedback abnormality factor ratio and the second combustion feedback abnormality factor ratio; The factor calculation module is used to use the ratio of the absolute value of the difference to the sum as the comprehensive combustion feedback factor of the boiler.

7. The intelligent monitoring and evaluation system for optimizing boiler combustion performance according to claim 1, characterized in that: The monitoring and evaluation module is used to: The monitoring and evaluation module is used to randomly combine each k comprehensive combustion feedback factors to obtain multiple comprehensive combustion feedback factor groups; The monitoring and evaluation module is used to calculate the comprehensive combustion feedback factor and value of each comprehensive combustion feedback factor group, and extract the maximum comprehensive combustion feedback factor from all comprehensive combustion feedback factors; The monitoring and evaluation module is used to calculate the ratio of the maximum comprehensive combustion feedback factor to the sum of each comprehensive combustion feedback factor as a relative comprehensive combustion feedback factor; The monitoring and evaluation module is used to randomly match all relative comprehensive combustion feedback factors in pairs to obtain multiple relative comprehensive combustion feedback factor groups, and calculate the monitoring and evaluation coefficient of the boiler based on all relative comprehensive combustion feedback factor groups.

8. The intelligent monitoring and evaluation system for optimizing boiler combustion performance according to claim 7, characterized in that: The monitoring and evaluation module is used to: The monitoring and evaluation module is used to calculate the monitoring and evaluation coefficient of the boiler according to the following formula: ； Among them, q is the monitoring evaluation coefficient of the boiler, n is the number of relative comprehensive combustion feedback factor groups, w1 y is a relative comprehensive combustion feedback factor in the yth relative comprehensive combustion feedback factor group, w2 y is another relative comprehensive combustion feedback factor in the yth relative comprehensive combustion feedback factor group, For all The minimum value of The maximum value of .

9. The intelligent monitoring and evaluation system for optimizing boiler combustion performance according to claim 1, characterized in that: The monitoring and evaluation module is used to: The monitoring and evaluation module is configured to determine that the combustion performance optimization of the boiler does not meet the requirements when the monitoring and evaluation coefficient is less than the preset monitoring and evaluation coefficient; The monitoring and evaluation module is used to determine whether the combustion performance optimization of the boiler meets the requirements when the monitoring and evaluation coefficient is greater than or equal to the preset monitoring and evaluation coefficient.

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