Intelligent control method for a boiler sootblower
By monitoring the fouling coefficient and flue gas pressure difference under stable boiler operating conditions, and dynamically adjusting the soot blowing parameters and modes, the adaptability and accuracy of the boiler soot blower under load changes are solved, achieving efficient and safe soot blowing control.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- BEIJING HITECH TECH & ENVIRONMENT CO LTD
- Filing Date
- 2025-12-03
- Publication Date
- 2026-05-15
AI Technical Summary
Existing boiler sootblower control methods are poorly adaptable to changes in boiler load, lack flexibility, have insufficiently targeted sootblowing strategies, and are inaccurate in judging when sootblowing ends, resulting in energy waste and equipment wear.
By identifying stable operating conditions, monitoring the fouling coefficient and flue gas pressure differential growth rate, dynamically determining soot blowing requirements, matching appropriate purging pressure and duration, and selecting wide-area or fixed-point purging modes according to the type of ash accumulation distribution, the soot blowing process is monitored in real time to determine the timing of termination.
It improves the accuracy and efficiency of boiler soot blowing, reduces energy consumption and equipment wear, and enhances the safety and economy of system operation.
Smart Images
Figure CN121596729B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of boiler sootblower control, and specifically to an intelligent control method for boiler sootblowers. Background Technology
[0002] Boiler soot blowers are crucial equipment for removing ash from the heating surfaces of boilers. Their function is to maintain the boiler's heat exchange efficiency and ensure the safe and stable operation of the system. During boiler operation, ash produced by fuel combustion accumulates on the heating surfaces, forming an ash layer. This leads to decreased heat transfer efficiency, increased flue gas flow resistance, and consequently affects the overall performance of the boiler, even potentially causing safety accidents. Therefore, effective control of the soot blower is an important means to achieve efficient, energy-saving, and safe boiler operation.
[0003] Currently, the control methods for boiler soot blowers mainly include timed soot blowing, constant pressure differential soot blowing, and intelligent soot blowing methods based on simple threshold judgment. For example, there are existing soot blowing optimization control schemes based on expert system rules. For instance, the existing Chinese patent with authorization announcement number CN108829057B discloses a boiler heating surface monitoring system and method based on different characteristic parameters and logical relationships. Through the collaboration of virtual controller and real controller, the judgment of the fouling status of the boiler heating surface and soot blowing control are realized. However, such methods still have the following shortcomings: (1) Poor adaptability to boiler load changes: Existing methods are mostly based on fixed thresholds or single parameters for judgment, and do not fully consider the impact of boiler load fluctuations on monitoring parameters, resulting in a decrease in judgment accuracy under unstable operating conditions.
[0004] (2) The soot blowing strategy lacks flexibility and specificity: the soot blowing mode is not dynamically adjusted according to the type of ash accumulation, making it difficult to achieve differentiated treatment of uniform ash accumulation and concentrated ash accumulation.
[0005] (3) Inaccurate judgment of the end of soot blowing: The lack of dynamic monitoring of the changing trend of ash accumulation characteristic parameters during soot blowing can easily lead to insufficient or excessive soot blowing, resulting in energy waste or equipment wear.
[0006] Therefore, there is an urgent need for a control method that can adapt to changes in boiler operating conditions, accurately identify the ash accumulation status, and dynamically determine the end of soot blowing, so as to improve soot blowing efficiency and the economy and safety of system operation. Summary of the Invention
[0007] To address the above problems, this invention proposes an intelligent control method for a boiler sootblower. The specific technical solution is as follows: An intelligent control method for a boiler sootblower includes the following steps: Step S1: Determine whether the current operating condition is a stable operating condition based on boiler load data. Under stable operating conditions, monitor ash accumulation characteristic parameters, including the fouling coefficient and the flue gas pressure difference growth rate.
[0008] Step S2: Compare the dust accumulation characteristic parameters with the corresponding cleaning benchmark to determine whether dust blowing is required. If yes, start the dust blower and assess the dust blowing requirement. If no, return to step S1.
[0009] Step S3: Match the corresponding soot blowing parameters and adjust them adaptively according to the soot blowing demand. The soot blowing parameters include blowing pressure and blowing time.
[0010] Step S4: Based on the changing trend of ash accumulation characteristic parameters, identify whether the ash distribution type of the heated area is uniform or concentrated, and set the working mode of the soot blower to wide-area coverage blowing or fixed-point powerful blowing according to the ash accumulation distribution type.
[0011] Step S5: During the soot blowing process, when the rate of change of the ash accumulation characteristic parameters tends to level off or the blowing time is reached, stop the soot blowing and turn off the soot blower.
[0012] Step S6: After the soot blowing is completed, evaluate the soot blowing effect based on the recovery value of the ash accumulation characteristic parameters and provide feedback.
[0013] Compared with the prior art, the intelligent control method for boiler soot blowers described in this invention has the following advantages: 1. By identifying stable operating conditions and monitoring the fouling coefficient and flue gas pressure difference growth rate under stable operating conditions, this invention eliminates the influence of boiler load fluctuations on parameter monitoring, thereby providing a high-quality data foundation for intelligent decision-making and significantly improving the accuracy and reliability of system judgment.
[0014] 2. This invention identifies whether the ash on the heated surface is uniformly distributed or concentrated based on the temporal changes of ash accumulation characteristic parameters, and adopts a working mode of wide-area coverage purging or fixed-point powerful purging accordingly, thereby achieving precise response to different types of ash accumulation and improving the ash blowing effect.
[0015] 3. This invention dynamically determines the end of the ash blowing process by monitoring whether the rate of change of ash accumulation characteristic parameters tends to level off or whether the set blowing time has been reached, ensuring that unnecessary energy consumption and equipment damage are avoided while achieving the cleaning effect. Attached Figure Description
[0016] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0017] Figure 1 This is a schematic diagram of the method flow of the present invention.
[0018] Figure 2 This is a structural block diagram of the present invention.
[0019] Figure 3 This is a schematic diagram of the workflow of step S5 of the present invention. Detailed Implementation
[0020] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of an intelligent control method for a boiler sootblower according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.
[0021] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.
[0022] The specific scheme of the intelligent control method for a boiler soot blower provided by the present invention will be described in detail below with reference to the accompanying drawings.
[0023] Please see Figure 1 and Figure 2 As shown, the present invention provides an intelligent control method for a boiler soot blower, comprising the following steps: Step S1, determining whether the current operating condition is a stable operating condition based on boiler load data, and monitoring ash accumulation characteristic parameters under stable operating conditions, wherein the ash accumulation characteristic parameters include the fouling coefficient and the flue gas pressure difference growth rate.
[0024] In one embodiment of the present invention, the intelligent control process of the boiler sootblower begins with a judgment on the stability of the boiler's operating conditions. Only by performing sootblowing under stable operating conditions can the characteristic parameters of ash accumulation be accurately monitored and the sootblowing effect and operational safety be guaranteed. If sootblowing is carried out under conditions of large load fluctuations or low load, it will not only be difficult to effectively remove ash accumulation, but may also lead to safety hazards due to insufficient flue gas velocity or unstable parameters.
[0025] Based on this, the embodiments of the present invention collect actual evaporation data of the boiler, calculate the boiler load rate at each time point, and then evaluate the average load rate and the maximum fluctuation of the load rate, so as to scientifically determine whether the current condition is a stable condition suitable for soot blowing.
[0026] Based on this, in a preferred embodiment of the present invention, the method for determining whether the current operating condition is a stable operating condition includes: collecting the actual evaporation data of the boiler during the current monitoring period, calculating the ratio of the actual evaporation to the rated evaporation at each time point during the period, and obtaining the boiler load rate corresponding to each time point.
[0027] Based on the boiler load rate at each time point, calculate the average load rate and the maximum load rate fluctuation of the boiler.
[0028] If the average load rate is greater than the preset load rate threshold and the maximum fluctuation of the load rate is within the preset allowable fluctuation range, then the current operating condition is determined to be a stable operating condition; otherwise, it is determined to be an unstable operating condition.
[0029] It should be noted that when soot blowers are used to perform soot blowing operations on boilers, the boilers are typically required to operate at medium or higher loads and under stable conditions. Under low load conditions, the flue gas velocity is low, which may not be able to effectively carry away the blown-off ash; while under conditions of excessive load fluctuation, the boiler operating parameters become unstable, which not only affects the accurate judgment of the soot blowing effect, but may also cause safety hazards.
[0030] Once the current operating condition is confirmed to be stable, key parameters reflecting the soot condition of the heated surface can be further monitored to provide a basis for subsequent soot blowing decisions.
[0031] Considering that the fouling coefficient and flue gas pressure difference growth rate can reflect the degree of ash accumulation from two dimensions, namely heat transfer efficiency and flue gas flow resistance, this embodiment of the invention calculates the fouling coefficient by comparing the actual heat transfer coefficient under the current operating conditions with the heat transfer coefficient under clean conditions; at the same time, it calculates the growth rate based on the historical data of flue gas pressure difference, thereby comprehensively assessing the ash accumulation status.
[0032] Based on this, in a preferred embodiment of the present invention, the method for monitoring ash accumulation characteristic parameters includes: extracting the clean state heat transfer coefficient corresponding to the boiler's stable operation at different load points from the database, and determining the clean state heat transfer coefficient corresponding to the current operating condition based on the current average load rate of the boiler.
[0033] Obtain the actual heat transfer coefficient of the current heated surface, calculate the difference between the reciprocal of the actual heat transfer coefficient and the reciprocal of the heat transfer coefficient in the clean state, and use this difference as the fouling coefficient.
[0034] Obtain the flue gas pressure difference of the current heating surface, retrieve the flue gas pressure difference of the heating surface after the last soot blowing and the corresponding soot blowing time point from the database, and calculate the interval time since the last soot blowing.
[0035] Calculate the difference between the current flue gas pressure difference on the heated surface and the flue gas pressure difference on the heated surface after the last soot blowing, and use the ratio of this difference to the interval length as the flue gas pressure difference growth rate.
[0036] It should be noted that the actual heat transfer coefficient and flue gas pressure difference data of the heated surface at each time point within the current monitoring period are obtained. The average value of the actual heat transfer coefficient and the average value of the flue gas pressure difference are calculated respectively. The average value of the actual heat transfer coefficient is taken as the actual heat transfer coefficient of the current heated surface, and the average value of the flue gas pressure difference is taken as the flue gas pressure difference of the current heated surface.
[0037] It should be noted that monitoring and analyzing the fouling coefficient of the heated surface and the growth rate of the flue gas pressure difference are existing mature technologies, and will not be elaborated on in this manual.
[0038] It should be noted that the fouling factor reflects the degree to which ash accumulation hinders the heat transfer process; the larger the fouling factor, the more severe the ash accumulation.
[0039] It should be noted that ash accumulation can cause blockage of the flue gas passage, reducing the flow cross-section and thus increasing the flue gas pressure difference. The faster the flue gas pressure difference increases, the higher the ash accumulation rate, the greater the amount of ash accumulated, and the more severe the ash accumulation.
[0040] After obtaining the dust accumulation characteristic parameters under the current operating conditions, it is necessary to further compare them with the cleaning baseline to determine whether soot blowing is required.
[0041] Step S2: Compare the dust accumulation characteristic parameters with the corresponding cleaning benchmark to determine whether dust blowing is required. If yes, start the dust blower and assess the dust blowing requirement. If no, return to step S1.
[0042] Soot blowing decision-making is a crucial aspect of intelligent control. Blindly blowing soot before the soot accumulation reaches the threshold will lead to energy waste and equipment wear; conversely, failing to blow soot when it severely impacts operation will reduce boiler efficiency and increase safety risks. Therefore, it is necessary to scientifically determine the timing of soot blowing based on real-time data of the fouling coefficient and flue gas pressure differential growth rate, compared with preset cleanliness benchmarks.
[0043] In this embodiment of the invention, the cleaning benchmarks for each ash accumulation characteristic parameter under the current load condition are retrieved from the database, and the real-time monitored fouling coefficient and flue gas pressure difference growth rate are compared with them. If any parameter exceeds the benchmark, it is determined that soot blowing needs to be started.
[0044] Based on this, in a preferred embodiment of the present invention, the method for determining whether soot blowing is required includes: retrieving from the database a cleaning benchmark corresponding to the soot accumulation characteristic parameters under the current operating load conditions.
[0045] If the fouling coefficient is greater than its corresponding cleaning benchmark or the flue gas pressure difference growth rate is greater than its corresponding cleaning benchmark, then it is determined that soot blowing is required; otherwise, it is determined that soot blowing is not required.
[0046] After determining that soot blowing is necessary, it is also necessary to further assess the degree of soot blowing requirement in order to provide a quantitative basis for the matching and adjustment of subsequent soot blowing parameters.
[0047] Considering that different levels of ash accumulation require different soot blowing strategies, this embodiment of the invention calculates the proportion by which the fouling coefficient and the flue gas pressure difference growth rate exceed their respective cleaning benchmarks, and performs linear weighted fusion to obtain a quantitative assessment value of the current soot blowing demand, providing a basis for setting the soot blowing intensity and duration.
[0048] Based on this, in a preferred embodiment of the present invention, the method for assessing the soot blowing requirement includes: comparing the dirt coefficient with its corresponding cleaning benchmark, calculating the amount by which the dirt coefficient exceeds its cleaning benchmark to obtain the excess amount of the dirt coefficient, and then calculating the ratio of the excess amount of the dirt coefficient to the cleaning benchmark corresponding to the dirt coefficient as the excess ratio of the dirt coefficient.
[0049] The excess ratio of flue gas pressure difference growth rate is calculated using the same calculation method as the above-mentioned excess ratio of fouling coefficient.
[0050] The proportion of the fouling coefficient exceeding the limit and the proportion of the flue gas pressure difference growth rate exceeding the limit are linearly weighted and fused to obtain a quantitative assessment value of the current soot blowing demand.
[0051] It should be noted that the specific weights of the fouling coefficient excess ratio and the flue gas pressure difference growth rate excess ratio are configured based on the actual operating conditions and ash accumulation characteristics of the boiler. When the boiler load is stable and the fuel ash content is low, the impact of decreased heat transfer performance on system efficiency is more significant. In this case, a higher weight should be assigned to the fouling coefficient excess ratio, for example, set to 0.7, while a lower weight should be assigned to the flue gas pressure difference growth rate excess ratio, at 0.3, to accurately reflect the dominant influence of fouling accumulation on heat transfer efficiency. Conversely, when the boiler load fluctuates frequently or the fuel ash content is high, the impact of flue gas flow resistance on system safety is more critical. In this case, the weight of the flue gas pressure difference growth rate excess ratio should be increased to 0.7, and the weight of the fouling coefficient excess ratio should be correspondingly decreased to 0.3, to more accurately characterize the impact of flue gas passage blockage on operational safety. When both heat transfer performance and flow resistance have a significant impact on system operation, a balanced weight allocation strategy should be adopted, for example, setting the weight of both to 0.5, to take into account the comprehensive requirements of thermal efficiency and flow stability. This dynamic weight adjustment mechanism can adapt to different operating conditions and ash accumulation characteristics, ensuring the accuracy and applicability of soot blowing demand assessment.
[0052] After determining the soot blowing requirements, appropriate soot blowing parameters need to be matched accordingly, and the soot blower needs to be adaptively adjusted to achieve precise and efficient soot blowing operations.
[0053] Step S3: Match the corresponding soot blowing parameters and adjust them adaptively according to the soot blowing demand. The soot blowing parameters include blowing pressure and blowing time.
[0054] The proper setting of soot blowing parameters directly affects the soot blowing effect and equipment lifespan. Insufficient soot blowing pressure or too short a duration may result in incomplete removal of accumulated ash; conversely, excessive pressure or duration can easily lead to energy waste and damage to the heated surfaces. Therefore, it is necessary to match appropriate soot blowing parameters according to the soot blowing requirements and to achieve dynamic adjustment.
[0055] This invention, through the pre-stored correspondence between different soot blowing demand ranges and soot blowing parameters, matches the recommended soot blowing parameters corresponding to the current demand and compares them with the currently set parameters to determine the adjustment direction and amount, thereby achieving adaptive optimization of soot blowing parameters.
[0056] Based on this, in a preferred embodiment of the present invention, the method of matching and adaptively adjusting the corresponding soot blowing parameters includes: matching the soot blowing parameters corresponding to the current soot blowing demand according to the correspondence between different soot blowing demand ranges and soot blowing parameters stored in the database, and using them as suitable soot blowing parameters, wherein the soot blowing parameters include blowing pressure and blowing time.
[0057] Obtain the currently set sootblowing parameters of the sootblower, compare them with the appropriate sootblowing parameters, determine the adjustment direction and amount of the sootblowing parameters, and adaptively adjust the sootblowing parameters of the sootblower accordingly.
[0058] It should be noted that the correspondence between the different soot blowing demand ranges and soot blowing parameters is established through the following steps: First, operational data is collected, and historical cases of soot blowing operations performed on the boiler under different ash accumulation conditions are collected. Each case includes the soot blowing demand assessment value, the actual soot blowing parameter configuration used, and the effect evaluation after soot blowing.
[0059] Then, the demand level is classified, and historical cases are divided into different demand ranges based on the numerical distribution of the soot blowing demand assessment values.
[0060] Next, parameter analysis is performed. For each demand interval, the distribution pattern of the soot blowing parameters used in all historical cases under that interval is statistically analyzed. The parameter configurations with an effect evaluation compliance rate higher than the preset threshold are summarized as the recommended soot blowing parameters for that interval.
[0061] Finally, a mapping relationship is generated, and the correspondence between the demand range and the recommended soot blowing parameters is stored in the database to form a soot blowing parameter configuration knowledge base.
[0062] It should be noted that the set purging time should be less than the maximum safe time for the sootblower to be inserted into the boiler, in order to avoid the sootblower burning out due to overheating.
[0063] After setting the soot blowing parameters, it is necessary to further select a suitable soot blowing mode based on the distribution characteristics of the soot on the heated surface, so as to improve the targeting and efficiency of soot blowing.
[0064] Step S4: Based on the changing trend of ash accumulation characteristic parameters, identify whether the ash distribution type of the heated area is uniform or concentrated, and set the working mode of the soot blower to wide-area coverage blowing or fixed-point powerful blowing according to the ash accumulation distribution type.
[0065] The ash on the heated surface may exhibit different forms, such as uniform or concentrated distribution, and the requirements for soot blowing strategies also vary. If only a single soot blowing mode is used, it will be difficult to cope with different types of ash distribution, affecting the soot blowing effect.
[0066] Based on this, embodiments of the present invention construct a time series of the fouling coefficient and the flue gas pressure difference growth rate, and calculate its coefficient of variation to identify the ash accumulation distribution type. If the coefficient of variation is small, it indicates that the ash accumulation distribution is uniform; otherwise, it is a concentrated distribution.
[0067] Based on this, in a preferred embodiment of the present invention, the method for identifying the ash distribution type of the heated area includes: calculating the fouling coefficient and flue gas pressure difference growth rate at each time point within the current monitoring period, and constructing a time series sequence of the fouling coefficient and a time series sequence of the flue gas pressure difference growth rate, respectively.
[0068] Calculate the coefficient of variation of the time series of the fouling coefficient and the time series of the flue gas pressure difference growth rate, and take the larger value of the two as the coefficient of variation of the time series of the ash accumulation characteristic parameters.
[0069] If the coefficient of variation of the time series of the ash accumulation characteristic parameters is less than or equal to the set coefficient of variation threshold, then the change of the ash accumulation characteristic parameters is determined to be stable, and the ash distribution type of the heated area is determined to be uniform distribution.
[0070] If the coefficient of variation of the time series of the ash accumulation characteristic parameters is greater than the set coefficient of variation threshold, it is determined that the ash accumulation characteristic parameters change drastically, and the ash distribution type of the heated surface is determined to be a concentrated distribution.
[0071] It should be noted that the influence patterns of uniform ash accumulation and non-uniform ash accumulation (concentrated ash accumulation) on ash accumulation characteristic parameters differ. When uniform ash accumulation occurs on the heating surface, the fouling coefficient shows a slow and stable upward trend, while the flue gas pressure difference growth rate maintains a synchronous and stable increase. However, in the case of non-uniform ash accumulation (concentrated ash accumulation), the fouling coefficient and the flue gas pressure difference growth rate may exhibit abrupt or step-like changes.
[0072] Once the type of ash distribution is identified, the working mode of the soot blower can be set accordingly to achieve more targeted soot blowing operations.
[0073] For uniformly accumulated dust, wide-area coverage purging can completely remove the dust; while for concentrated dust, a fixed-point powerful purging mode is required to concentrate the purging force to remove local dust and improve purging efficiency.
[0074] Based on this, in a preferred embodiment of the present invention, the method for setting the working mode of the soot blower includes: when the soot distribution type of the heated area is identified as uniform distribution, the working mode of the soot blower is set to wide-area coverage purging.
[0075] When the ash distribution type of the heated area is identified as concentrated, the working mode of the soot blower is set to fixed-point powerful blowing.
[0076] After setting the soot blowing mode and starting soot blowing, the soot blowing process needs to be monitored in real time, and the soot blowing should be stopped at the appropriate time to avoid over-blowing or under-blowing.
[0077] Step S5: During the soot blowing process, when the rate of change of the ash accumulation characteristic parameters tends to level off or the blowing time is reached, stop the soot blowing and turn off the soot blower.
[0078] Determining when to end soot blowing is crucial for ensuring both its economic efficiency and safety. Ending soot blowing too early may result in incomplete removal of accumulated ash; while extending the blowing time excessively will lead to energy waste and equipment damage.
[0079] This invention monitors the rate of change of ash accumulation characteristic parameters during the soot blowing process. When the rate of change becomes gradual or the preset blowing time is reached, the soot blowing is terminated in a timely manner, ensuring that the soot blowing operation achieves the cleaning effect while avoiding resource waste.
[0080] Based on this, in a preferred embodiment of the present invention, see [reference]. Figure 3 As shown, the method for determining when to end soot blowing includes: during the soot blowing process, selecting a time point when the operating condition is stable, and monitoring the ash accumulation characteristic parameters at each time point.
[0081] The rate of change of ash accumulation characteristic parameters is calculated based on monitoring data at adjacent time points.
[0082] If the rate of change of the ash accumulation characteristic parameter at a certain time point is less than the set rate of change threshold, it is determined that the rate of change of the ash accumulation characteristic parameter tends to level off.
[0083] When it is determined that the rate of change tends to level off or the blowing time reaches the blowing time set in step S3, the blowing operation ends.
[0084] It should be noted that when the rate of change of the ash accumulation characteristic parameters tends to level off, it indicates that the heated surface has basically achieved a cleaning effect. At this point, the soot blowing operation should be stopped in time to avoid energy waste and equipment wear.
[0085] After the soot blowing operation is completed, the soot blowing effect needs to be evaluated in order to provide feedback for the optimization of subsequent soot blowing strategies.
[0086] S6. After the soot blowing is completed, the soot blowing effect is evaluated based on the recovery value of the ash accumulation characteristic parameters, and feedback is provided.
[0087] Evaluating the effectiveness of soot blowing is a crucial component of closed-loop control. By comparing changes in characteristic parameters of dust accumulation before and after soot blowing, the effectiveness of soot blowing can be quantified, and it can be determined whether the expected cleaning goals have been achieved.
[0088] This invention uses the ratio of the difference between the initial and recovered values of the ash accumulation characteristic parameters before and after soot blowing as a quantitative evaluation value of the soot blowing effect. If the effect is not as expected, soot blowing can be performed again after a set interval, thereby achieving continuous optimization of the soot blowing process.
[0089] Based on this, in a preferred embodiment of the present invention, the method for evaluating the soot blowing effect includes: after the soot blowing operation is completed, monitoring the ash accumulation characteristic parameters under stable operating conditions and using them as the recovery values of the ash accumulation characteristic parameters.
[0090] The ash accumulation characteristic parameters obtained in step S1 under stable operating conditions are used as the initial values of the ash accumulation characteristic parameters.
[0091] Calculate the difference between the initial value and the restored value of the ash accumulation characteristic parameter, and use the ratio of the difference to the initial value as a quantitative evaluation value of the ash blowing effect.
[0092] In this embodiment, the present invention achieves adaptive adjustment of soot blowing intensity by assessing the soot blowing demand and matching the corresponding soot blowing parameters, thereby avoiding insufficient or excessive soot blowing and improving soot blowing efficiency and equipment lifespan.
[0093] In this embodiment, after the soot blowing is completed, the present invention quantitatively evaluates the soot blowing effect by comparing the initial and recovered values of the ash accumulation characteristic parameters, and provides data support for the optimization of subsequent soot blowing strategies, forming a closed-loop control and continuously improving system performance.
[0094] In summary, this invention identifies stable operating conditions and monitors ash accumulation characteristic parameters, including the fouling coefficient and flue gas pressure differential growth rate, under these conditions. It compares these ash accumulation characteristic parameters with a cleanliness benchmark to determine if soot blowing is necessary. It assesses the soot blowing demand and matches soot blowing parameters accordingly. Based on the changing trends of the ash accumulation characteristic parameters, it identifies the ash distribution type and sets corresponding soot blowing modes. During soot blowing, it determines the end time of soot blowing based on the change rate of the ash accumulation characteristic parameters and the blowing duration. After soot blowing, it quantitatively evaluates the soot blowing effect by comparing the initial and recovered values of the ash accumulation characteristic parameters. This invention achieves precise control of the soot blowing process, effectively overcoming problems in existing technologies such as poor adaptability to load changes, a single soot blowing strategy, and inaccurate judgment of the end time, significantly improving soot blowing efficiency, boiler operating safety, and economy.
[0095] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.
[0096] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.
[0097] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, in the form of a computer program product.
[0098] Those skilled in the art will recognize that the modules and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.
[0099] In addition, the functional modules in the various embodiments of this application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module.
[0100] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.
[0101] Finally, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.
Claims
1. An intelligent control method for a boiler soot blower, characterized in that, Includes the following steps: S1. Determine whether the current operating condition is a stable operating condition based on the boiler load data. Under stable operating conditions, monitor the ash accumulation characteristic parameters, including the fouling coefficient and the flue gas pressure difference growth rate. S2. Compare the dust accumulation characteristic parameters with the corresponding cleaning benchmark to determine whether dust blowing is required. If yes, start the dust blower and assess the dust blowing requirement. If no, return to step S1. S3. Match the corresponding soot blowing parameters and adjust them adaptively according to the soot blowing demand. The soot blowing parameters include blowing pressure and blowing time. S4. Based on the changing trend of ash accumulation characteristic parameters, identify whether the ash distribution type of the heated area is uniform or concentrated, and set the working mode of the soot blower to wide-area coverage blowing or fixed-point powerful blowing according to the ash accumulation distribution type. The method for identifying the ash distribution type of the heated area includes: Under stable operating conditions, the fouling coefficient and flue gas pressure difference growth rate at each time point within the current monitoring period are calculated, and the time series sequences of the fouling coefficient and flue gas pressure difference growth rate are constructed respectively; the coefficients of variation of the time series sequences of the fouling coefficient and flue gas pressure difference growth rate are calculated, and the larger value of the two is taken as the coefficient of variation of the time series of ash accumulation characteristic parameters. If the coefficient of variation of the ash accumulation characteristic parameter over time is less than or equal to the set coefficient of variation threshold, then the change of the ash accumulation characteristic parameter is determined to be stable, and the ash distribution type of the heated area is determined to be uniform distribution. If the coefficient of variation of the time series of the ash accumulation characteristic parameters is greater than the set coefficient of variation threshold, it is determined that the ash accumulation characteristic parameters change drastically, and the ash distribution type of the heated surface is determined to be concentrated distribution. S5. During the soot blowing process, when the rate of change of the ash accumulation characteristic parameters tends to level off or the blowing time is reached, the soot blowing is stopped and the soot blower is turned off. S6. After the soot blowing is completed, the soot blowing effect is evaluated based on the recovery value of the ash accumulation characteristic parameters, and feedback is provided.
2. The intelligent control method for a boiler soot blower according to claim 1, characterized in that: The method for determining whether the current operating condition is a stable operating condition includes: Collect the actual evaporation data of the boiler during the current monitoring period, calculate the ratio of the actual evaporation to the rated evaporation at each time point during the period, and obtain the boiler load rate corresponding to each time point; Based on the boiler load rate at each time point, calculate the average load rate and the maximum load rate fluctuation of the boiler; If the average load rate is greater than the preset load rate threshold and the maximum fluctuation of the load rate is within the preset allowable fluctuation range, then the current operating condition is determined to be a stable operating condition; otherwise, it is determined to be an unstable operating condition.
3. The intelligent control method for a boiler soot blower according to claim 2, characterized in that: The method for monitoring the characteristic parameters of ash accumulation includes: Extract the clean state heat transfer coefficients corresponding to the boiler's stable operation at different load points from the database, and determine the clean state heat transfer coefficients corresponding to the current operating conditions based on the current average load rate of the boiler. Obtain the actual heat transfer coefficient of the current heated surface, calculate the difference between the reciprocal of the actual heat transfer coefficient and the reciprocal of the heat transfer coefficient in the clean state, and use this difference as the fouling coefficient; Obtain the flue gas pressure difference of the current heating surface, retrieve the flue gas pressure difference of the heating surface after the last soot blowing and the corresponding soot blowing time point from the database, and calculate the interval time since the last soot blowing. Calculate the difference between the current flue gas pressure difference on the heated surface and the flue gas pressure difference on the heated surface after the last soot blowing, and use the ratio of this difference to the interval length as the flue gas pressure difference growth rate.
4. The intelligent control method for a boiler soot blower according to claim 1, characterized in that: The methods for determining whether soot blowing is necessary include: Retrieve the cleaning baseline corresponding to the ash accumulation characteristic parameters under the current operating load conditions from the database; If the fouling coefficient is greater than its corresponding cleaning benchmark or the flue gas pressure difference growth rate is greater than its corresponding cleaning benchmark, then it is determined that soot blowing is required; otherwise, it is determined that soot blowing is not required.
5. The intelligent control method for a boiler soot blower according to claim 1, characterized in that: The method for assessing the soot blowing demand includes: The dirt coefficient is compared with its corresponding cleaning benchmark, and the amount by which the dirt coefficient exceeds its cleaning benchmark is calculated to obtain the excess amount of the dirt coefficient. Then, the ratio of the excess amount of the dirt coefficient to the cleaning benchmark corresponding to the dirt coefficient is calculated as the excess proportion of the dirt coefficient. Calculate the excess ratio of flue gas pressure difference growth rate using the same calculation method as the above-mentioned excess ratio of fouling coefficient; The proportion of the fouling coefficient exceeding the limit and the proportion of the flue gas pressure difference growth rate exceeding the limit are linearly weighted and fused to obtain a quantitative assessment value of the current soot blowing demand.
6. The intelligent control method for a boiler soot blower according to claim 1, characterized in that: The method for matching and adaptively adjusting the corresponding soot blowing parameters includes: Based on the pre-stored correspondence between different soot blowing demand ranges and soot blowing parameters in the database, the soot blowing parameters corresponding to the current soot blowing demand are matched and used as suitable soot blowing parameters. The soot blowing parameters include blowing pressure and blowing duration. Obtain the currently set sootblowing parameters of the sootblower, compare them with the appropriate sootblowing parameters, determine the adjustment direction and amount of the sootblowing parameters, and adaptively adjust the sootblowing parameters of the sootblower accordingly.
7. The intelligent control method for a boiler soot blower according to claim 1, characterized in that: The method for setting the working mode of the soot blower includes: When the ash distribution type of the heated area is identified as uniform distribution, the working mode of the soot blower is set to wide-area coverage purging. When the ash distribution type of the heated area is identified as concentrated, the working mode of the soot blower is set to fixed-point powerful blowing.
8. The intelligent control method for a boiler soot blower according to claim 1, characterized in that: The method for determining when to end soot blowing includes: During the soot blowing process, select time points under stable operating conditions and monitor the ash accumulation characteristic parameters at each time point; Based on monitoring data from adjacent time points, the rate of change of ash accumulation characteristic parameters is calculated. If the rate of change of the ash accumulation characteristic parameter at a certain time point is less than the set rate of change threshold, it is determined that the rate of change of the ash accumulation characteristic parameter tends to level off. When it is determined that the rate of change tends to level off or the blowing time reaches the blowing time set in step S3, the blowing operation ends.
9. The intelligent control method for a boiler soot blower according to claim 1, characterized in that: The method for evaluating the effectiveness of soot blowing includes: After the soot blowing operation is completed, the characteristic parameters of ash accumulation are monitored under stable operating conditions and used as the recovery values of the characteristic parameters of ash accumulation. The ash accumulation characteristic parameters obtained in step S1 under stable operating conditions are used as the initial values of the ash accumulation characteristic parameters. Calculate the difference between the initial value and the restored value of the ash accumulation characteristic parameter, and use the ratio of the difference to the initial value as a quantitative evaluation value of the ash blowing effect.