Intelligent regulation and control method for flue gas fan of gas-fired boiler

Abstract

The invention relates to the technical field of boiler energy conservation, in particular to a gas boiler flue gas fan intelligent regulation and control method which comprises the following steps: S1, collecting the temperature of gas and the wind speed parameter information of a fan inlet in real time, and smoothing the collected temperature parameter and wind speed parameter to obtain a temperature smooth value Tfilt and a wind speed smooth value vfilt; s2, calculating a total correction coefficient Ktotal according to a temperature smooth value and a wind speed smooth value by taking the temperature of the fuel gas and the inlet wind speed of the fan as influence items on the rotating speed of the fan; s3, correcting the reference rotating speed of the fan according to the total correction coefficient Ktotal to obtain a target rotating speed narget; and S4, smoothing the target rotating speed narget to obtain the output rotating speed of the fan. According to the method, through a multi-parameter cooperative regulation and control strategy, it can be ensured that the draught fan always operates near the optimal state under various working conditions, and the overall heat efficiency of the gas boiler and the operation efficiency of the draught fan are remarkably improved.

Description

Technical Field

[0001] This invention relates to the field of boiler energy-saving technology, specifically a method for intelligent control of flue gas fans in gas-fired boilers. Background Technology

[0002] The flue gas fan in a gas-fired boiler is a key device for collecting waste heat from the flue gas. The quality of the fan's operation directly affects the boiler's energy efficiency and equipment lifespan. Currently, traditional methods for controlling flue gas fans in gas-fired boilers are relatively simplistic, often employing feedback control strategies based on a single measurement parameter. For example, fixed-speed fans or simple frequency converters adjust the fan speed based solely on the airflow parameter, ignoring the synergistic effect of flue gas temperature and airflow velocity. When the flue gas temperature rises sharply, the fan motor is easily burned out due to high temperature. Relying solely on a single parameter for adjustment cannot comprehensively and accurately reflect the system's true needs, leading to deviations between the fan speed setpoint and the actual optimal operating point. Even small fluctuations in the system's sensors can cause frequent changes in fan speed. When the fan speed fluctuates, over-extraction due to a surge in resistance or under-extraction due to flue gas stagnation can occur, increasing energy consumption and increasing fan vibration amplitude and noise, accelerating component wear. Furthermore, these methods cannot adaptively and selectively adjust the fan speed according to the degree to which operating parameters deviate from the optimal value, thus requiring urgent solutions. Summary of the Invention

[0003] To avoid and overcome the technical problems existing in the prior art, this invention provides an intelligent control method for flue gas fans in gas-fired boilers. Through a multi-parameter coordinated control strategy, this invention ensures that the fan always operates near its optimal state under various operating conditions, significantly improving the overall thermal efficiency of the gas-fired boiler and the operating efficiency of the fan.

[0004] To achieve the above objectives, the present invention provides the following technical solution: A method for intelligent control of flue gas fans in gas-fired boilers includes the following steps: S1. Real-time acquisition of gas temperature and fan inlet velocity parameters, and smoothing of the acquired temperature and velocity parameters to obtain a smoothed temperature value. T filt and wind speed smoothing value v filt ; S2. Using the gas temperature and the inlet velocity of the fan as factors affecting the fan speed, calculate the total correction factor based on the temperature smoothing value and the velocity smoothing value. K total ; S3, with total correction factor K total The target speed is obtained by correcting the reference speed of the fan. n target; n target =clip ( × , , ); in, clip Represents the amplitude limiting function; This is the reference speed of the fan; This is the minimum speed of the fan; This is the maximum speed of the fan; S4, Target Rotation Speed n target Smoothing process yields the fan's output speed. .

[0005] As a further aspect of the present invention: in step S2, S21, Confirm T filt Calculate the temperature correction factor for the corresponding temperature range. ; when T filt ≤ hour, =1+[( - T filt ) / ( - )]× i ltr ; when <T filt ≤ hour, =1-[( T filt - ) / ( - )]× i htr ; in, This is the optimal operating temperature for the fan; To ensure the fan can withstand the lower limit of temperature; To ensure the fan can withstand the maximum temperature limit; iltr This is the adjustment range coefficient for low-temperature operating conditions, representing the temperature from... T min Rise to T opt hour, K t Increase in magnitude; i htr This is an adjustment range coefficient for high-temperature operating conditions, representing the temperature from... T opt Rise to T max hour, The extent of the reduction; S22, Confirm v filt Calculate the wind speed correction factor within the given wind speed range. ; when v f ≤ hour, =1+[( - v f ) / ( - )]× i lsr ; when < v filt ≤ hour, =1-[( v filt - ) / ( - )]× i hsr ; in, v opt The optimal operating wind speed for the fan; v min This is the minimum design operating wind speed for the fan; v max This refers to the maximum design operating wind speed of the fan. i lsr This is the adjustment factor for low-speed operation, indicating the wind speed from... v min Rise to v opt hour, Kv Increase in magnitude; i hsr This is the adjustment factor for high-speed operating conditions, representing the wind speed from... v opt Rise to v max hour, The extent of the reduction; S23. Calculate the total correction factor. K total : = ×K t + × ; in, This is the temperature correction factor; This is the wind speed correction factor; + = 1.

[0006] As a further aspect of the present invention: 0< i ltr ≤ ; < i htr ≤ ; 0< i lsr ≤ ; < i hsr ≤ .

[0007] As a further aspect of the present invention: in step S1, T filt =α×T 实时 + (1- α )× T filt ， 上 ; v filt=α×v 实时 + (1- α ) ×v filt ， 上 ; in, α These are the filter coefficients; T 实时 This refers to the real-time temperature of the gas. v 实时 This refers to the real-time wind speed at the fan inlet; T filt ， 上 This is the smoothed temperature value from the previous moment; v filt ， 上 This is the smoothed wind speed value from the previous moment.

[0008] As a further aspect of the present invention:

[0009] in, T The sampling period for collecting parameter information; This is the cutoff frequency.

[0010] As a further aspect of the present invention: in step S4, = β×n target +(1- β )× n 上 ; in, β For smoothing coefficients; β The value range is 0 to 1; n 上 This represents the output speed at the previous moment.

[0011] As a further aspect of the present invention: when T filt >1.1× T max or v filt >1.1× v max The system was determined to be in an abnormal state, and the fan's output speed was switched to [unclear]. n min; If the temperature sensor and / or wind speed sensor malfunctions, the fan output speed will switch to [unclear]. n base .

[0012] An electronic device includes a processor, an input device, an output device, and a memory, wherein the processor, the input device, the output device, and the memory are connected in sequence, the memory is used to store a computer program, the computer program includes program instructions, and the processor is configured to call the program instructions to execute the aforementioned intelligent control method for flue gas fans in a gas-fired boiler.

[0013] A readable storage medium storing a computer program, the computer program including program instructions that, when executed by a processor, cause the processor to perform the aforementioned intelligent control method for flue gas fans in a gas-fired boiler.

[0014] Compared with the prior art, the beneficial effects of the present invention are: 1. This invention couples the gas temperature with the inlet wind speed of the fan, calculates the temperature correction coefficient and the wind speed correction coefficient, and weights them to synthesize the total correction coefficient, thereby finely correcting the reference speed of the fan. Through a multi-parameter coordinated control strategy, it ensures that the fan always operates near its optimal state under various operating conditions, significantly improving the overall thermal efficiency of the gas boiler and the operating efficiency of the fan. By using a limiting function, the target speed is strictly limited between the minimum and maximum allowable speed of the fan, fundamentally preventing the operational risks caused by overspeed or excessively low speed.

[0015] 2. This invention uses a dual smoothing processing mechanism to filter the real-time collected temperature and wind speed signals, filtering out high-frequency fluctuations caused by sensor noise or instantaneous disturbances on site. It also smooths the calculated target speed, ensuring that the final output speed of the fan can transition smoothly rather than change abruptly. This prevents mechanical shocks and pressure fluctuations caused by rapid changes in speed to the fan itself, the transmission system, and the entire flue gas system, thus extending the service life of the equipment.

[0016] 3. This invention sets optimal operating ranges for temperature and wind speed respectively. By calculating correction coefficients in segments, when parameters deviate from the optimal value, the system can automatically and smoothly adjust the correction range to bring the fan speed back to the optimal value. The setting of the adjustment range coefficient ensures that the correction process is smooth and controllable, which not only ensures the sensitivity of the adjustment, but also avoids over-adjustment or oscillation, so that the fan can maintain efficient and stable operation under a wider range of operating conditions.

[0017] 4. The adaptive control algorithm of this invention dynamically adjusts the fan speed based on flue gas temperature and wind speed, reducing speed at high temperatures and appropriately increasing speed at low temperatures to avoid energy waste caused by over- or under-extraction. By processing sensor data through two-stage filtering, the system response time is reduced, motor speed fluctuations are minimized, and equipment impact caused by frequent start-stop cycles is avoided. The anomaly detection mechanism fundamentally prevents high-temperature flue gas from burning out the fan motor and high-speed airflow from impacting equipment, preventing potential safety hazards. Attached Figure Description

[0018] Figure 1 This is a diagram showing the effect of temperature data filtering in this invention.

[0019] Figure 2 This is a diagram illustrating the wind speed data filtering effect of the present invention.

[0020] Figure 3 This is a dynamic variation diagram of the temperature and wind speed correction coefficients of the present invention.

[0021] Figure 4 This is a diagram illustrating the fan speed control effect of the present invention. Detailed Implementation

[0022] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0023] Please see Figure 1~4 In this embodiment of the invention, a method for intelligent control of flue gas fans in a gas-fired boiler is provided. Includes the following steps: S1. Real-time acquisition of gas temperature and fan inlet velocity parameters, and smoothing of the acquired temperature and velocity parameters to obtain a smoothed temperature value. T filt and wind speed smoothing value v filt ; T filt =α×T 实时 + (1- α )× T filt ， 上 ; v filt =α×v 实时+ (1- α ) ×v filt ， 上 ; ; in, α These are the filter coefficients; T The sampling period for collecting parameter information; The cutoff frequency; T 实时 This refers to the real-time temperature of the gas. v 实时 This refers to the real-time wind speed at the fan inlet; T filt ， 上 This is the smoothed temperature value from the previous moment; v filt ， 上 This is the smoothed wind speed value from the previous moment.

[0024] S2. Using the gas temperature and the inlet velocity of the fan as factors affecting the fan speed, calculate the total correction factor based on the temperature smoothing value and the velocity smoothing value. K total ; S21, Confirm T filt Calculate the temperature correction factor for the corresponding temperature range. ; when T filt ≤ hour, =1+[( - T filt ) / ( - )]× i ltr ; 0< i ltr ≤ ; when <T filt ≤ hour, =1-[(T filt - ) / ( - )]× i htr ; < i htr ≤ ; in, This is the optimal operating temperature for the fan; To ensure the fan can withstand the lower limit of temperature; To ensure the fan can withstand the maximum temperature limit; i ltr This is the adjustment range coefficient for low-temperature operating conditions, representing the temperature from... T min Rise to T opt hour, K t Increase in magnitude; i htr This is an adjustment range coefficient for high-temperature operating conditions, representing the temperature from... T opt Rise to T max hour, The extent of the reduction; S22, Confirm v filt Calculate the wind speed correction factor within the given wind speed range. ; when v f ≤ hour, =1+[( - v f ) / ( - )]× i lsr ; 0< i lsr ≤ ; when < v filt ≤ hour, =1-[( vfilt - ) / ( - )]× i hsr ; < i hsr ≤ ; in, v opt The optimal operating wind speed for the fan; v min This is the minimum design operating wind speed for the fan; v max This refers to the maximum design operating wind speed of the fan. i lsr This is the adjustment factor for low-speed operation, indicating the wind speed from... v min Rise to v opt hour, K v Increase in magnitude; i hsr This is the adjustment factor for high-speed operating conditions, representing the wind speed from... v opt Rise to v max hour, The extent of the reduction; S23. Calculate the total correction factor. K total : = ×K t + × ; in, This is the temperature correction factor; This is the wind speed correction factor; + = 1.

[0025] S3, with total correction factor K total The target speed is obtained by correcting the reference speed of the fan. ntarget ; n target =clip ( × , , ); in, clip Represents the amplitude limiting function; This is the reference speed of the fan; This is the minimum speed of the fan; This is the maximum speed of the fan; S4, Target Rotation Speed n target Dynamic smoothing is used to obtain the output speed of the fan. .

[0026] = β×n target +(1- β )× n 上 ; in, β For smoothing coefficients; β The value range is 0 to 1; n 上 The output speed at the previous moment During system operation, when T filt >1.1× T max or v filt >1.1× v max The system was determined to be in an abnormal state, and the fan's output speed was switched to [unclear]. n min ; If the temperature sensor and / or wind speed sensor malfunctions, the fan output speed will switch to [unclear]. n base .

[0027] Based on the optimal operating temperature, two ranges are defined, allowing the temperature correction factor to be calculated under two different operating conditions. The calculation process essentially involves multiplying the deviation percentage by the adjustment range coefficient, ensuring that the correction range is proportional to the deviation. To achieve more precise and controllable speed regulation, the temperature correction factor is made proportional to the actual operating condition deviation; the larger the deviation, the larger the temperature correction factor and the greater the adjustment range.

[0028] Calculate the temperature correction factor hour,( T filt ) / ( Essentially, it represents the proportion of the current deviation to the total deviation, and its core function is to convert the absolute temperature difference into a relative proportion between 0 and 1. molecular( This represents the absolute deviation between the current operating condition and the ideal state, and indicates the current filtered temperature ( ). T filt Distance from optimal operating temperature ( The larger the difference, the more serious the problem of insufficient heat recovery, and the more the rotation speed needs to be increased.

[0029] Denominator ( T filt This indicates the "maximum permissible deviation" of the operating condition, representing the temperature from the lowest temperature. To the optimal temperature The total deviation range is the adjustment range under low-temperature operating conditions.

[0030] This ratio ranges from 0 to 1, and directly reflects the severity of the current temperature deviation. when T filt = That is, the optimal temperature, the ratio = 0. K t =1, the speed remains at the reference value and no adjustment is required; when T filt = That is, the temperature is the lowest, and the ratio is 1. i ltr =0.2, K t =1+1×0.2=1.2, the speed is increased to 120% of the base value (maximum allowable increase). when < T filt < This means the deviation is moderate, the ratio is between 0 and 1, and the increase in speed is directly proportional to the deviation, with a ratio of 0.5. i ltr =0.2, K t =1.1, speed increased by 10%.

[0031] ( T filt - ) / ( - ), ( －v filt ) / ( － )and( v filt － ) / ( － The design meaning is the same as above.

[0032] In a specific embodiment: when T min = T filt =80℃, i ltr =0.2, T max =120 ℃, T opt =100 ℃, then , The fan speed can be increased by up to 20% to avoid excessive speed increase leading to a surge in resistance.

[0033] when T max = T filt =180℃, T min =80 ℃, T opt =100 ℃, i htr =0.5, then , The fan speed can be reduced to a minimum of 50% for forced cooling to protect the motor. The absolute value of 0.5 is greater than 0.2, prioritizing safety.

[0034] when T min =90℃, T filt =100℃, T opt =120℃, i ltr =0.25, then at this time The fan speed can be increased by up to 17%.

[0035] when Tmax =190℃, T filt =180℃, T opt =160℃, i htr =0.6, T min =120 ℃, then 67, at this time The fan speed can be reduced to as low as 60%.

[0036] when T min =70℃, T filt =80℃, T opt =110℃, i ltr =0.3, then at this time The engine speed can be increased by up to 23%.

[0037] when T max =200℃, T filt =190℃, T opt =150℃, i htr =0.55, T min =130 ℃ 8. At this time That is, the speed can be reduced to as low as 56%.

[0038] when T min =90℃, T filt =95℃, T opt =120℃, T max =140 ℃, i ltr =0.35, then at this time The engine speed can be increased by up to 29%.

[0039] when T max =180℃, T filt =170℃, T opt =140℃, i htr =0.3, T min =120 ℃ 75, at this time That is, the speed can be reduced to as low as 77.5%.

[0040] The core objective of the wind speed correction coefficient is to quantify the deviation between the current operating conditions and the ideal wind speed based on the filtered wind speed, so as to ensure the flow field is stable, avoid eddies, and ensure low drag.

[0041] First determine v opt , v min and v max Key wind speed parameters, v opt The balance point between stabilizing the flow field (avoiding eddies) and minimizing drag (avoiding excessively high wind speeds that could cause a surge in drag) is set at 12 m / s. v min This is the minimum wind speed. Below this speed, eddies are easily formed, and the speed needs to be increased appropriately to eliminate the eddies. It is set to 8m / s. v max The maximum safe wind speed is set at 18 m / s. Above this wind speed, the system resistance increases sharply, and the speed needs to be reduced appropriately to reduce energy consumption.

[0042] According to v filt The relationship with the ideal wind speed benchmark is calculated under two different operating conditions. K v The formula is essentially "percentage of deviation × adjustment range coefficient".

[0043] when v max =12m / s,v opt =10m / s , v filt = v min =8m / s, i lsr =0.15, then , The engine speed can be increased by up to 20%, avoiding excessive acceleration that could lead to a surge in resistance. when v min =8m / s,v opt =10m / s , v filt = v max =18m / s, i hsr =0.3, but That is, the speed can be reduced to a minimum of 70% to avoid excessive speed reduction affecting heat recovery.

[0044] when v max =12m / s,v min =8m / s, v filt =9m / s, v opt =12m / s, i lsr =0.2, then ,at this time The rotational speed can be increased by up to 15%.

[0045] when v max =18m / s, v min =11m / s,v filt =16m / s, v opt =15m / s, i hsr =0.35, then ,at this time That is, the speed can be reduced to as low as 89%.

[0046] when v min =10m / s, v filt =12m / s, v opt =15m / s, i lsr =0.1, then ,at this time The maximum speed can be increased by 6%.

[0047] when v min =10m / s, v max =20m / s, v filt =17m / s, v opt =16m / s, i hsr =0.3, then ,at this time That is, the speed can be reduced to as low as 93%.

[0048] when v max =15m / s, v min =7m / s, v filt =9m / s, v opt =13m / s, i lsr =0.23, then 67, at this time The rotational speed can be increased by up to 15%.

[0049] when v min =10m / s, v max =17m / s, v filt =15m / s, v opt =14m / s, i hsr =0.4, then ,at this time That is, the speed can be reduced to as low as 87%.

[0050] K v and temperature correction factor K t The value setting needs to be determined by combining the operating condition priority, equipment characteristics, and control objectives, through qualitative analysis of scenario requirements and quantitative derivation of parameter range. The specific process is as follows: 1. Qualitative setting based on the relationship between operating condition priority and correction direction: The values ​​of the two coefficients depend primarily on the weighting of temperature and wind speed on the system's influence, and must be qualitatively determined based on the core control objective. For example, in industrial boiler waste heat recovery scenarios, when heat recovery efficiency is the core objective... K t Higher weight: T opt The impact on heat recovery efficiency is more significant, such as when the temperature is below a certain level. T opt At that time, a 10°C decrease may lead to a 15% reduction in heat recovery. Therefore, a larger correction margin needs to be set, for example... i ltr =0.3, that is, at low temperature K t The maximum speed can be increased to 1.3, ensuring a rapid increase in rotational speed to enhance heat absorption. Wind speed correction factor. K vLower weighting: Wind speed mainly affects flue gas flow rate. In scenarios prioritizing heat recovery, as long as the wind speed does not exceed the safe range, the correction range can be relatively small, such as... i lsr =0.1, meaning at low wind speeds K v The maximum value is increased to 1.1 to avoid disrupting temperature stability due to excessive wind speed adjustment.

[0051] For example, in high-temperature flue gas fan scenarios, when equipment safety is the core objective: K t High temperature risks must be strictly limited: when the temperature approaches the upper limit. T max At that time, a larger cooling correction range needs to be set, such as i htr =0.6, meaning at high temperatures K t It can be reduced to 0.4, forcibly reducing the speed to reduce the intake of high-temperature flue gas.

[0052] Wind speed correction factor K v Risk of overspeed needs to be limited: Excessive wind speed may overload the fan, therefore, larger corrections are required at high wind speeds, such as... i hsr =0.4, meaning high wind speed K v It can be reduced to 0.6, prioritizing speed reduction to ensure mechanical safety.

[0053] For example, in the case of a balanced-type residential gas-fired boiler... Temperature and wind speed corrections are similar, such as i ltr = i lsr =0.2, through weight allocation, such as α T =0.5 , α V =0.5, to achieve a balanced influence of both on the rotational speed and avoid over-adjustment of a single parameter.

[0054] 2. Quantitative setting based on parameter derivation from the deviation-response model: After qualitatively determining the priority, the specific value of the correction coefficient needs to be quantitatively calculated using bench tests or simulation data (e.g., i ltr , i lsr (etc.), the core is to establish a mapping relationship between parameter deviation, speed regulation, and system output: (1) First, quantitative derivation K t: Step 1: Determine the temperature deviation range and set the optimal temperature. T opt =120℃, minimum effective temperature T min =80℃, then the maximum temperature deviation Δ T max = T opt - T min =40℃.

[0055] Step 2: Determine the allowable speed adjustment range:

[0056] If the engine speed needs to be increased from the base value (1200 r / min) to a maximum of 1500 r / min at low temperatures (i.e., the maximum adjustment Δ), then... n max =300r / min, corresponding correction factor K T =1.25); Step 3: Calculation i ltr : according to K t The expression, when T filt At 100℃, i ltr =0.5. That is, the correction amplitude coefficient is derived by back-calculating the maximum permissible speed adjustment.

[0057] i htr and i ltr The derivation principle and process are consistent.

[0058] (2) Quantitative derivation K V : The logic is consistent with temperature, for example: optimal wind speed. v opt =12m / s, minimum wind speed v min =8m / s, maximum wind speed deviation Δ v max =4m / s, when v filt =10m / s, if the speed needs to be increased from the reference value (1200r / min) to the maximum allowable speed of 1440r / min (i.e., the maximum adjustment Δ), n max =240r / min, corresponding correction factor KT =1.2), then i shr =0.4.

[0059] i hsr and i lsr The derivation principle and process are consistent.

[0060] (3) Weighting coefficients α T , α V Quantitative allocation

[0061] Orthogonal experiments were conducted to determine the impact of speed regulation on system objectives (such as thermal efficiency and equipment temperature) under different temperature and wind speed combinations, and the weights were calculated using contribution rates. For example: If the effect of a 10°C change in temperature on thermal efficiency is 1.5 times that of a 1 m / s change in wind speed, then α T =0.6、α V =0.4.

[0062] 3. Dynamic adjustment based on a self-correction mechanism using operating condition feedback: In practical applications, the values ​​of the coefficients can be dynamically optimized through PID closed-loop control: when the system output (such as heat recovery) is lower than expected, the weight of the temperature correction coefficient is automatically increased; when the fan vibration exceeds the limit, the weight of the wind speed correction coefficient is automatically increased; for example, a feedback coefficient γ is set and adjusted according to the real-time thermal efficiency η. α T : α T = α T0 + c ·( or target - or real );in α T0 As the initial weights, or target The target thermal efficiency.

[0063] The choice of the filter coefficient α plays a decisive role in the filtering effect. For different structures and operating conditions, the following method for calculating the optimal filter coefficient is proposed: Step 1: Determine the cutoff frequency f c The maximum frequency component of the signal to be retained is determined based on actual signal processing requirements. If the highest effective component in the signal is... f abc Hz, then fc =f abc ; Step 2: Determine the sampling period T The sampling frequency is determined by system hardware settings or sampling strategy. f s reciprocal ， Right now T =1 / f s ; Step 3: Calculate the time constant: time constant τ and cutoff frequency f c Related, ; Step 4: Filter Coefficients α With cutoff frequency f c and sampling period T The relationship is α= , Will Substitution , and thus .

[0064] When the system requires a cutoff frequency f c =8Hz, sampling frequency f s =120Hz, then the sampling period T The value is 0.0083s. Calculate the time constant. t The filter coefficient is 0.0199s. It is 0.294.

[0065] Smoothing coefficient β Used for first-order low-pass filtering, its core function is to weaken the instantaneous jumps in parameters through weighted averaging, so that control commands (such as fan speed) can be smoothly transitioned, avoiding mechanical shock.

[0066] In step S4 β The determination is based on the inertial characteristics of mechanical systems: equipment such as fans and guide vanes have rotational inertia. β The optimal parameters can be selected through actual operating conditions and equipment debugging process. First, compare different parameters with specific and reasonable reference values. β The impact of values ​​on the control effect is used to screen out reasonable values ​​through effect comparison. β value.

[0067] As shown in Table 1 below, βAt a value of 0.5, the response is fast but the jitter is large. By step 5, the target value of 1500 r / min is approaching, and the response is rapid. At the step of time step 1, the speed changes abruptly by 150 r / min. Since the typical control step size of the boiler fan is 0.1-0.5 s, this far exceeds the maximum allowable instantaneous change of 200 r / min by the fan's mechanical system. s, which can easily lead to shaft vibration.

[0068] β When the value is 0.1, the smoothness is good but the response is lagging. The speed changes gradually, increasing by only 20-30 r / min per step, with no mechanical shock. The target value is still not reached in the 10th step (only 1393 r / min), and the response lag is serious, which will lead to insufficient heat recovery at low temperature.

[0069] β At 0.2, the response is balanced and smooth, with a step increase of only 60 r / min (1200→1260 r / min), which is far below the mechanical shock threshold. By the 10th step, it is close to the target value (1478 r / min), and the response speed meets the heat recovery requirements. The rotational speed changes evenly throughout the process (increasing by 30-50 r / min per step), taking into account both "no shaking" and "no stalling".

[0070] When the target speed changes frequently due to fluctuations in operating conditions (e.g., 1200→1300→1250→1400 r / min). β The output speed changes when the target speed is 0.2 are as follows: When the target speed jumps by 100 r / min, the output speed only changes by 20-30 r / min; when the target speed returns, there is no reverse impact on the output speed (e.g., from 1300→1250, the output speed transitions smoothly from 1280→1274). This further verifies... β A smoothness coefficient of 0.2 can effectively suppress speed fluctuations caused by dynamic fluctuations, which meets the mechanical characteristics requirements of the fan and is the best smoothness coefficient under this operating condition.

[0071] Table 1 ; The specific control process of this application was simulated using MATLAB software to verify the effectiveness of the control logic based on "temperature / wind speed deviation proportional correction + smooth control". The entire process was simulated, including: data processing → preprocessing → correction calculation → speed control → anomaly protection. 1. Core parameter system design Set basic threshold parameters, including T opt , T min 、T max 、v opt , vmin 、v max Define the boundaries for normal system operation. In this embodiment, the boundaries are: temperature 80-180℃ and wind speed 8-18m / s.

[0072] Set the control parameters. α =0.3, β =0.2, correction amplitude coefficient i ltr、 i ltr、 i lsr and i lsr Control and adjust sensitivity, weighting coefficient α T =0.6, α V =0.4, used to allocate the weight of the influence of temperature and wind speed on rotational speed.

[0073] Reference speed n base 1200 rpm As the target speed under the ideal operating conditions set by the system, it forms a fixed reference benchmark. It is the theoretical speed when the temperature and wind speed are both at their optimal values, and it does not change with time or operating conditions.

[0074] The initial speed is the speed at which the simulation starts. At the initial moment, it is in an ideal working condition by default, so it has the same value as the reference speed, but they are different in essence. The initial speed is the starting point for dynamic adjustment, while the reference speed is a fixed reference anchor point.

[0075] Minimum / maximum safe speed, n min =300r / min, n max =1500r / min, used to limit the mechanical operating range of the fan.

[0076] 2. Operating condition data simulation

[0077] The system generates noisy real-time data and simulates the periodic fluctuations of temperature and wind speed using a sine function. Gaussian noise is superimposed to simulate sensor acquisition errors, such as temperature fluctuations of ±3℃ and wind speed fluctuations of ±0.8m / s, thus closely resembling the parameter fluctuations caused by combustion instability in actual working conditions.

[0078] Boundary correction ensures that the data does not fall below the minimum threshold, avoiding mathematical errors such as negative denominators in subsequent calculations. At the same time, a small range of random values ​​is used to simulate normal fluctuations close to the threshold, enhancing the authenticity of the data.

[0079] 3. Establish a data preprocessing mechanism

[0080] The smoothing value is calculated by using an exponentially weighted moving average operation. Historical data weights are used to reduce instantaneous noise, so that the temperature / wind speed curve changes from severe fluctuations to a smooth transition, providing a stable input for subsequent correction calculations.

[0081] 4. Calculation of correction factor

[0082] Adjustment of work condition ratio: Temperature correction factor ,exist T filt ≤ T opt In low-temperature operating conditions, through ( T opt - T filt ) / ( T opt - T min Calculate the deviation ratio and increase it proportionally. (Enhancing heat recovery by increasing rotational speed); T filt >T opt Under high-temperature operating conditions, reduce proportionally. Overheating can be avoided by reducing the rotation speed.

[0083] Wind speed correction factor Logic and Consistent, improved at low wind speeds This increases airflow and reduces airflow at high wind speeds. This reduces speed and limits traffic.

[0084] Total correction factor K total By integrating temperature and wind speed weights and It comprehensively reflects the operating conditions' requirements for speed.

[0085] 5. Establish a speed control and smoothing mechanism.

[0086] Firstly, through n target =n base × K total Calculate the target speed, obtain the theoretical speed based on the total correction factor, and then... clip The amplitude is limited to ensure that it does not exceed the mechanical safety range.

[0087] Then, the target speed is smoothed using an exponentially weighted moving average operation. βA low-weighted abrupt change of 0.2 is used to mitigate the impact. For example, when the target speed changes by 300 r / min, the output speed only changes by 60 r / min, thus avoiding mechanical shock.

[0088] 6. Activate the anomaly protection design

[0089] When the temperature / wind speed exceeds 1.1 times the upper limit, it is determined to be a dangerous operating condition, and the output speed is forcibly reduced to a lower limit. n min =300r / min and mark abnormal points, and protect the fan from overload and high temperature damage by emergency speed reduction.

[0090] To verify the regulatory effect of this application, such as Figure 1~Figure 2 As shown, the real-time temperature and wind speed curves exhibit high-frequency fluctuations due to superimposed noise, such as drastic temperature fluctuations between 85-125℃ and wind speed jumps between 9-15 m / s. However, after filtering, the smoothed temperature and wind speed curves become significantly smoother, preserving the trend while eliminating spikes. For example, the temperature fluctuation range is reduced from ±5℃ to ±2℃, demonstrating that the filtering mechanism effectively suppresses noise interference and provides reliable input for subsequent control. The optimal temperature and wind speed in the figure serve as baselines, clearly showing the deviation between the current smoothed values ​​and ideal operating conditions; for example, when the temperature is below 120℃, the engine speed needs to be increased.

[0091] like Figure 3 As shown, K t and K v It changes synchronously with temperature / wind speed deviation, while K total Fusion K t and K v Changes, such as when the temperature is low and the wind speed is low. K total A significant increase in temperature leads to a substantial acceleration; when both temperature and wind speed are high. K total This significantly reduces speed, resulting in a substantial decrease, and enables comprehensive multi-parameter regulation.

[0092] like Figure 4 The fan speed is adjusted as shown. Target speed follow K totalRapid changes, such as a sudden increase from 1200 r / min to 1500 r / min, cause drastic fluctuations, reflecting the theoretically achievable speed. However, after smoothing, the output speed curve is gentler and lags behind the target speed. For example, when the target speed jumps by 300 r / min, the output speed only changes by 60 r / min per step, effectively avoiding mechanical shock through the smoothing mechanism. In the set abnormal operating conditions, the output speed is forcibly reduced to 300 r / min, while the target speed is still calculated according to the theoretical value, verifying the effectiveness of the abnormal protection mechanism and prioritizing equipment safety.

[0093] In summary, the fluctuation range of the smoothed temperature and wind speed values ​​is significantly smaller than that of the original data, proving the effectiveness of the filtering. Simultaneously, the output speed fluctuation range is strictly controlled within the safety threshold, and the number of abnormal operating conditions is consistent with the preset values, verifying the reliability of the control logic. Through a complete process design encompassing simulation, filtering, correction, smoothing, and protection, the intelligent control logic of the gas boiler fan is accurately reproduced. Furthermore, simulation results demonstrate that this application can suppress noise and avoid mechanical shock while dynamically responding to changes in operating conditions and triggering protection in abnormal situations, achieving a balance between high efficiency and energy saving and equipment safety.

[0094] Another embodiment of this application is an electronic device.

[0095] The electronic device can be the mobile device itself, or a standalone device that can communicate with the mobile device to receive the collected input signals from it and send the selected target decision behavior to it.

[0096] Electronic devices include one or more processors and memory.

[0097] A processor can be a central processing unit (CPU) or other form of processing unit with data processing and / or instruction execution capabilities, and can control other components in an electronic device to perform desired functions.

[0098] The memory may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory. The non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and the processor may execute the program instructions to implement the intelligent control method for flue gas fans of a gas-fired boiler described in the various embodiments of this application above.

[0099] In one example, the electronic device may also include input and output devices, which are interconnected via a bus system and / or other forms of connection. For example, the input device may include various devices such as on-board diagnostics (OBD), cameras, industrial cameras, etc. The input device may also include, for example, a keyboard, a mouse, etc. The output device may include, for example, a monitor, speakers, a printer, and communication networks and their connected remote output devices, etc.

[0100] In addition, depending on the specific application, electronic devices may include any other suitable components.

[0101] Another embodiment of this application may be a computer program product, which includes computer program instructions that, when executed by a processor, cause the processor to perform the calculation steps described in the above-described intelligent control method for flue gas fans of a gas-fired boiler according to various embodiments of this application.

[0102] The computer program product can be written in any combination of one or more programming languages ​​to perform the operations of the embodiments of this application. The programming languages ​​include object-oriented programming languages ​​such as Java and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computing device, partially on the user's computing device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0103] Furthermore, embodiments of this application may also be computer-readable storage media storing computer program instructions thereon, which, when executed by a processor, cause the processor to execute a method for intelligent control of flue gas fans in a gas-fired boiler as described in this specification.

[0104] The computer-readable storage medium may be any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may, for example, include, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatuses, or devices, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: electrical connections having one or more wires, portable disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0105] The basic principles of this application have been described above with reference to specific embodiments. However, it should be noted that the advantages, benefits, and effects mentioned in this application are merely examples and not limitations, and should not be considered as essential features of each embodiment of this application. Furthermore, the specific details disclosed above are for illustrative and facilitative purposes only, and are not limitations. These details do not limit the application to the necessity of employing the aforementioned specific details for implementation.

[0106] The block diagrams of devices, apparatuses, devices, and systems involved in this application are merely illustrative examples and are not intended to require or imply that they must be connected, arranged, or configured in the manner shown in the block diagrams. As those skilled in the art will recognize, these devices, apparatuses, devices, and systems can be connected, arranged, and configured in any manner. Words such as “comprising,” “including,” “having,” etc., are open-ended terms meaning “including but not limited to,” and are used interchangeably with them. The terms “or” and “and” as used herein refer to the terms “and / or,” and are used interchangeably with them unless the context clearly indicates otherwise. The term “such as” as used herein refers to the phrase “such as but not limited to,” and is used interchangeably with it.

Claims

1. A method for intelligent control of flue gas fans in gas-fired boilers, characterized in that, Includes the following steps: S1. Real-time acquisition of gas temperature and fan inlet velocity parameters, and smoothing of the acquired temperature and velocity parameters to obtain a smoothed temperature value. T filt and wind speed smoothing value v filt ; S2. Using the gas temperature and the inlet velocity of the fan as factors affecting the fan speed, calculate the total correction factor based on the temperature smoothing value and the velocity smoothing value. K total ; S3, with total correction factor K total The target speed is obtained by correcting the reference speed of the fan. n target ; n target =clip ( × ， ， )； in, clip Represents the amplitude limiting function; This is the reference speed of the fan; This is the minimum speed of the fan; This is the maximum speed of the fan; S4, Target Rotation Speed n target Smoothing process yields the fan's output speed. .

2. The intelligent control method for flue gas fans in a gas-fired boiler according to claim 1, characterized in that, In step S2, S21, Confirm T filt Calculate the temperature correction factor for the corresponding temperature range. ; when T filt ≤ hour, =1+[( - T filt ) / ( - )]× θ ltr ; when <T filt ≤ hour, =1-[( T filt - ) / ( - )]× θ htr ; in, This is the optimal operating temperature for the fan; To ensure the fan can withstand the lower limit of temperature; To ensure the fan can withstand the maximum temperature limit; θ ltr This is the adjustment range coefficient for low-temperature operating conditions, representing the temperature from... T min Rise to T opt hour, K t Increase in magnitude; θ htr This is an adjustment range coefficient for high-temperature operating conditions, representing the temperature from... T opt Rise to T max hour, The extent of the reduction; S22, Confirm v filt Calculate the wind speed correction factor within the given wind speed range. ; when v f ≤ hour, =1+[( - v f ) / ( - )]× θ lsr ; when < v filt ≤ hour, =1-[( v filt - ) / ( - )]× θ hsr ; in, v opt The optimal operating wind speed for the fan; v min This is the minimum design operating wind speed for the fan; v max This refers to the maximum design operating wind speed of the fan. θ lsr This is the adjustment factor for low-speed operation, indicating the wind speed from... v min Rise to v opt hour, K v Increase in magnitude; θ hsr This is the adjustment factor for high-speed operating conditions, representing the wind speed from... v opt Rise to v max hour, The extent of the reduction; S23. Calculate the total correction factor. K total : = ×K t + × ； in, This is the temperature correction factor; This is the wind speed correction factor; + = 1。 3. The intelligent control method for flue gas fans in a gas-fired boiler according to claim 2, characterized in that, 0< θ ltr ≤ ； < θ htr ≤ ； 0< θ lsr ≤ ； < θ hsr ≤ 。 4. A method for intelligent control of flue gas fan in a gas-fired boiler according to any one of claims 1 to 3, characterized in that, In step S1, T filt =α×T 实时 + (1－ α )× T filt ， 上 ； v filt =α×v 实时 + (1－ α ) ×v filt ， 上 ； in, α These are the filter coefficients; T 实时 This refers to the real-time temperature of the gas. v 实时 This refers to the real-time wind speed at the fan inlet; T filt ， 上 This is the smoothed temperature value from the previous moment; v filt ， 上 This is the smoothed wind speed value from the previous moment.

5. The intelligent control method for flue gas fan of a gas-fired boiler according to claim 4, characterized in that, in, T The sampling period for collecting parameter information; This is the cutoff frequency.

6. A method for intelligent control of flue gas fan in a gas-fired boiler according to any one of claims 1 to 3, characterized in that, In step S4, = β×n target +(1－ β )× n 上 ； in, β For smoothing coefficients; β The value range is 0 to 1; n 上 This represents the output speed at the previous moment.

7. A method for intelligent control of flue gas fan in a gas-fired boiler according to any one of claims 1 to 3, characterized in that, when T filt >1.1× T max or v filt >1.1× v max The system was determined to be in an abnormal state, and the fan's output speed was switched to [unclear]. n min ; If the temperature sensor and / or wind speed sensor malfunctions, the fan output speed will switch to [unclear]. n base .

8. An electronic device, characterized in that, The system includes a processor, an input device, an output device, and a memory, which are connected in sequence. The memory is used to store a computer program, which includes program instructions. The processor is configured to call the program instructions to execute the intelligent control method for flue gas fans of a gas-fired boiler as described in any one of claims 1 to 3.

9. A readable storage medium, characterized in that, The storage medium stores a computer program, which includes program instructions that, when executed by a processor, cause the processor to perform a method for intelligent control of flue gas fans in a gas-fired boiler as described in any one of claims 1 to 3.

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