Anti-blocking and high-precision metering control method for biomass feeding system

Abstract

The application discloses a biomass feeding system anti-blocking and high-precision metering control method, which adopts a double-stage feeding structure, and runs a quality-volume cascade control module, a moisture content online estimation and density correction module, a motor current spectrum analysis and blocking feature identification module and an anti-blocking action sequence generation module in parallel in a unified controller; the cascade control module is combined with a weighing signal differential outer ring and a speed and weighing differential observation fusion inner ring, and introduces a dynamic feedforward, so that the metering accuracy is less than or equal to ±1% and the load response is in seconds; the blocking feature identification module performs double-threshold diagnosis of the motor current FFT characteristic frequency amplitude and mean value to diagnose the blocking precursor, and triggers the reverse rotation material loosening and bin wall vibration arch breaking, and the total anti-blocking time is less than or equal to 2s.

Description

Technical Field

[0001] This invention relates to the field of fuel delivery control technology in biomass energy utilization, specifically to a biomass feeding control method that combines anti-clogging, high-precision metering, and rapid response capabilities. It is applicable to operating conditions such as biomass direct-fired boilers and gasifiers where feeding stability and metering accuracy are critical. Background Technology

[0002] Biomass fuels are mostly in the form of straw, rice husks, sawdust, etc., in the form of fragments or pellets. They generally have the physical characteristics of being highly hygroscopic, prone to clumping, and having poor flowability. During the operation of the silos and feeders in the biomass feeding system, the material is prone to bridging and overflow, which can cause blockages or material interruptions, seriously affecting the continuous operation of the system.

[0003] Meanwhile, the bulk density and flowability of biomass materials fluctuate significantly with changes in moisture content and particle size distribution. Traditional volumetric feeders control the feeding volume solely by rotation speed, which cannot offset the mass flow deviation caused by density fluctuations, and the metering accuracy is insufficient to meet combustion control requirements. While a simple weighing feeding scheme can achieve mass metering, it suffers from signal response lag and cannot adapt to the fuel supply requirements of rapid boiler load increases and decreases.

[0004] Currently, existing technologies have not yet formed a comprehensive control scheme that can simultaneously solve the problems of feed blockage, insufficient metering accuracy, and load response lag, which restricts the operational reliability and control accuracy of biomass feeding systems. Summary of the Invention

[0005] (a) Technical problems to be solved In view of the shortcomings of the prior art, the technical problem to be solved by the present invention is as follows: 1. Solve the problem of material bridging, blockage, and frequent material interruption during biomass feeding: Existing unblocking methods are mostly passive treatments after the blockage has formed, with delayed early warning and intervention, making it impossible to achieve early prevention and control; 2. Solve the problems of low metering accuracy and large influence of material moisture content and density fluctuations in volumetric feeding: eliminate metering drift caused by batch changes in materials and changes in environmental humidity, and improve long-term metering stability; 3. Solve the problem of slow response and inability to adapt to rapid load increases and decreases in simple weighing feeding: achieve second-level dynamic response of feeding rate to support rapid adjustment of boiler load; 4. Construct an integrated composite control architecture: Integrate anti-blocking control, high-precision metering control, and rapid load response functions into a unified controller to avoid the problems of poor coordination and fragmented control logic when multiple systems operate independently.

[0006] (II) Technical Solution To address the aforementioned technical problems, this invention, based on a two-stage feeding hardware structure, constructs a composite control architecture that integrates "mass flow rate closed-loop as the primary mechanism, volumetric flow rate closed-loop as a secondary mechanism, and intelligent early warning and active anti-blocking coordination for material blockage." This architecture combines online estimation of material moisture content with real-time density correction, integrating all control functions into a unified controller. The system as a whole adopts a parallel computing architecture, with each functional module interacting with data in real time. The specific technical solution is as follows: Step 1: Construct a two-stage feeding structure A first-stage steady-flow scraper feeder is installed at the outlet of the front-end silo. It adopts a scraper structure and relies on a large conveying cross section and forced scraping capacity to break up material bridging and slack at the silo outlet, providing a continuous and stable basic material flow for the subsequent equipment. The steady-flow scraper feeder discharges material at a rate higher than the feeding requirements of the subsequent equipment. A buffer hopper is set between the steady-flow scraper feeder and the subsequent feeding equipment to absorb front-end flow fluctuations and ensure the stability of the subsequent metering environment.

[0007] A second-stage high-precision weighing feeder is installed at the outlet of the buffer hopper. It can be a fully suspended weighing belt conveyor or a loss-in-weight screw feeder. The whole machine is installed on a high-precision weighing sensor to directly acquire the instantaneous weight signal of the material. The drive motor of the high-precision weighing feeder is equipped with a speed detection component to collect the actual speed of the motor.

[0008] Step 2: Configure the sensor acquisition system and controller Sensing and actuation components are deployed at various locations within the system, and all signals are connected to a unified controller. The specific configuration is as follows: A weighing sensor group is arranged on the weighing platform of the high-precision weighing feeder, which outputs a 4~20mA or 0~10V analog signal, and the weighing resolution is better than 1 / 10000. A photoelectric encoder is configured as a speed sensor on the shaft of the drive motor of the high-precision weighing feeder to detect the real-time speed of the motor. Hall current transformers are connected to the power distribution circuits of the drive motors of the steady flow scraper feeder and the high-precision weighing feeder to monitor the motor operating current in real time, and the current range covers the motor stall current. An online microwave moisture analyzer and a matching temperature probe are installed at the inlet of the buffer hopper or high-precision weighing feeder to detect the dielectric constant and temperature of the material. A silo wall vibrator is installed on the outside of the silo wall. Its start and stop are controlled by the output signal of the controller to help break up material bridging inside the silo.

[0009] The output signals of all the above sensors are connected to the same programmable logic controller (PLC) or embedded controller. The controller's operation and execution cycle is ≤10ms, and all control logic and operations are completed within the controller.

[0010] Step 3: Construct the parallel functional module of the composite controller Four parallel real-time computing functional modules are built inside the controller: mass flow rate-volume flow rate cascade control module, moisture content online estimation and density correction module, drive motor current spectrum analysis and blockage feature identification module, and anti-blockage action sequence generation module.

[0011] The overall control input of the system is the mass flow rate setpoint. The value is sent from the upper-level combustion optimization system to the controller as the core setpoint of the cascade control module; the other modules operate independently and exchange data in real time to jointly achieve integrated control of metering, anti-blocking and rapid response.

[0012] Step 4: The mass-volume cascade control module achieves high-precision measurement and rapid response. This module is the core of the metering and control system. It adopts a cascade control structure, using a mass flow closed loop as the outer loop to ensure long-term accuracy, and a volumetric flow closed loop as the inner loop to suppress instantaneous disturbances. The specific implementation process is as follows: (1) Calculation of mass flow feedback value Real-time weight signal acquired by weighing sensor A second-order Butterworth low-pass filter is applied, with a cutoff frequency set to 2Hz, to remove high-frequency noise caused by mechanical vibration, resulting in a smoothed weight signal. Instantaneous mass flow rate feedback value is calculated through real-time differential calculation:

[0013] In the formula: The filtered weight of the material at time t is in kg. This is the system sampling period, which is consistent with the controller's operation period, and its value is ≤10ms. The instantaneous mass flow rate feedback value at time t is expressed in kg / s.

[0014] The instantaneous mass flow rate feedback value is used as the process feedback value of the outer loop of the cascade control.

[0015] (2) Online correction of material bulk density The online moisture content estimation module outputs the current moisture content of the material in real time. This module corrects the bulk density of materials in real time based on the offline calibrated density-moisture content relationship. :

[0016] In the formula: The basic bulk density of the material under oven-dry conditions is expressed in kg / L and was obtained through offline experimental calibration. The influence coefficient of moisture content is dimensionless and obtained through offline experimental calibration. This represents the real-time moisture content of the material, dimensionless (expressed as a decimal).

[0017] The corrected bulk density is input in real time into the feedforward and volume conversion stages of the cascade control to offset the measurement deviation caused by density fluctuations.

[0018] (3) Calculation of outer loop mass flow PID controller Mass flow rate setting With mass flow feedback value deviation The input to the outer loop PID controller is used to calculate the correction amount for the volumetric flow rate setpoint. :

[0019] In the formula, , , These are the proportional coefficient, integral coefficient, and derivative coefficient of the outer loop mass flow PID controller, respectively, which are obtained through debugging and tuning.

[0020] Simultaneously, based on the current mass flow rate setpoint and the real-time corrected bulk density, the volumetric flow rate feedforward value is calculated. To achieve rapid pre-response to changes in setpoints:

[0021] The feedforward value and the correction amount are added together to obtain the final setpoint for the inner loop of the volumetric flow rate:

[0022] In the formula, This is the inner loop setpoint for volumetric flow rate, in L / s.

[0023] (4) Rapid adjustment of inner ring volumetric flow rate Displacement coefficient per revolution of high-precision weighing feeder The theoretical conveying volume corresponding to each revolution of the motor is predetermined by the mechanical structure parameters; the actual motor speed is obtained by collecting data from the photoelectric encoder. The actual volumetric flow rate feedback value is obtained by conversion:

[0024] In the formula: This is the feeder's displacement coefficient per revolution, expressed in L / r. This represents the actual speed of the motor, in r / s (revolutions per second). This is the volumetric flow rate feedback value converted from rotational speed, in L / s.

[0025] To further enhance the anti-disturbance capability, dynamic correction is introduced based on the volumetric flow rate observation value of the weighing signal: the differential value of the weighing signal is divided by the real-time bulk density to obtain the observed volumetric flow rate. :

[0026] The volumetric flow rate feedback value converted from rotational speed is weighted and fused with the volumetric flow rate observed by weighing to obtain the final process value of the inner loop control. :

[0027] In the formula, The fusion weighting coefficient for the observations is dimensionless and has a value of 0.2.

[0028] The inner loop uses a PI controller, which calculates the speed increment based on the deviation between the volumetric flow rate setpoint and the process value, and outputs it to the speed control device.

[0029] In the formula: , These are the proportional and integral coefficients of the inner loop volumetric flow PI controller, which are obtained through debugging and tuning. This is the setpoint for the motor speed, in r / s.

[0030] Through the above cascade structure, the inner ring can quickly offset the measurement error caused by the instantaneous bulk density fluctuation of the material and the unevenness of the mechanical structure, while the outer ring eliminates long-term measurement drift and ensures that the overall measurement accuracy is ≤±1%.

[0031] (5) Dynamic load feedforward compensation When the mass flow rate setting value is issued by the higher-level unit When a step change occurs, multiply its rate of change by the feedforward gain. Directly superimposed on the speed setpoint This further accelerates the load response speed, achieving a feed rate response time within seconds:

[0032] In the formula, The dynamic load feedforward gain is obtained through tuning and adjustment.

[0033] Step 5: Intelligent Diagnosis and Active Anti-blocking Module for Material Blockage This module operates independently of the metering and control module, processing the motor current signals of the constant-flow scraper feeder and the high-precision weighing feeder separately, diagnosing early signs of material blockage and triggering active anti-blockage actions. Taking any feeder as an example, the diagnosis and anti-blockage process is as follows: Real-time acquisition of motor current signal A windowed Fast Fourier Transform (FFT) is performed with a window length of 1024 points, sliding 512 points at a time to calculate the current spectrum in real time.

[0034] The characteristic frequency is calculated based on the mechanical parameters of the feeder. For a scraper feeder, the characteristic frequency is... Determined by the motor speed and the number of sprocket teeth:

[0035] In the formula: This is the current motor speed, in rpm (revolutions per minute). The number of teeth on the feeder drive sprocket is dimensionless. The characteristic frequency of the current corresponding to the scraper movement is expressed in Hz.

[0036] Extract the maximum amplitude within a ±0.5 Hz frequency band near the characteristic frequency from the real-time spectrum. Simultaneously, the moving average value of the current signal within a 2-second time window is calculated. .

[0037] When both conditions are met and When the system detects signs of material blockage or scraper jamming, a blockage warning is triggered; among which... The characteristic frequency amplitude threshold, Both are average current thresholds, and are baseline thresholds obtained statistically under normal operating conditions of the equipment.

[0038] Upon triggering of the warning, the anti-blocking action sequence generator is immediately invoked to execute the following timing actions on the corresponding feeder that has been diagnosed with signs of material blockage: a. Control the feeder to stop rotating forward, with a delay of 0.2 seconds; b. Control the drive motor of the feeder to run in reverse for 0.5~1.5s to loosen the stuck material; c. Simultaneously start the vibrator on the silo wall and vibrate continuously for 1 second to help break up the bridging at the silo outlet; d. After another 0.3s delay, the feeder resumes normal speed regulation operation and returns to the metering control logic.

[0039] The above-mentioned anti-blocking process is automatically executed by the controller. The total time from the identification of blockage symptoms to the completion of the action is ≤2 seconds, realizing proactive intervention and early elimination of blockage.

[0040] Step 6: Online Moisture Content Estimation and Density Compensation Module This module operates in parallel and independently, using a microwave moisture analyzer inside the buffer hopper to collect the dielectric constant of the material in real time. With material temperature The moisture content of materials is calculated online using a pre-calibrated polynomial model. :

[0041] In the formula: Let be the relative permittivity of the material, which is dimensionless; The temperature of the material is expressed in °C. These are polynomial regression coefficients, obtained through regression calibration experiments on a static testing bench using various moisture content samples.

[0042] Real-time moisture content calculated Real-time input density correction model enables continuous self-correction of bulk density, eliminating metering drift caused by rainy season and material batch changes.

[0043] (III) Beneficial Effects Compared with the prior art, the present invention has the following significant technical effects: 1. Proactively predicts and prevents blockages, ensuring continuous and reliable operation. This invention identifies early signs of material blockage based on the characteristics of motor current spectrum, triggering an early warning before the blockage is fully formed. It also intervenes in advance through a timed proactive anti-blockage sequence of "feeder reversal to loosen material + bin wall vibration to break arches". The entire process is executed automatically with a total time of ≤2s, which can completely eliminate the blockage and interruption of biomass feeding systems and greatly improve the continuity of system operation.

[0044] 2. High measurement accuracy and strong anti-interference ability This invention employs a cascade control architecture of mass flow rate outer loop and volumetric flow rate inner loop, combined with online estimation of material moisture content and real-time correction of bulk density, which can offset the impact of density changes caused by fluctuations in material moisture content and batch differences; at the same time, by quickly suppressing instantaneous disturbances through the inner loop and eliminating long-term drift through the outer loop, the feeding metering accuracy is finally stably controlled within ±1%, which is significantly better than traditional volumetric feeding systems.

[0045] 3. Rapid load response, adaptable to dynamic operating conditions. This invention introduces a dynamic load feedforward mechanism on the basis of cascade control, which can directly correct the speed setpoint according to the rate of change of the mass flow rate setpoint. Combined with the rapid adjustment capability of the volume inner loop, it can achieve second-level following of the feeding rate and a load change response delay of ≤3s, which can fully adapt to the operation requirements of biomass boilers for rapid load increase and decrease.

[0046] 4. Integrated and highly intelligent This invention integrates all functions of metering control, density correction, blockage diagnosis and anti-blockage control into a single controller with a control cycle of ≤10ms. Each functional module operates in parallel and collaboratively without manual intervention, enabling maintenance-free operation of the system and comprehensively improving the reliability and intelligence level of the biomass fuel supply system. Attached Figure Description

[0047] Figure 1 This is a schematic diagram of the system structure of the present invention. Figure 2 This is a block diagram illustrating the principle of the mass-volume cascade composite control of the present invention. Detailed Implementation

[0048] The present invention will be further described in detail below with reference to specific embodiments. These embodiments are based on the technical solution of the present invention and provide detailed implementation methods and specific operation procedures. However, the scope of protection of the present invention is not limited to the following embodiments. Conventional substitutions and adjustments made by those skilled in the art within the scope of the core concept of the present invention should all fall within the scope of protection of the present invention.

[0049] This embodiment is applied to the fuel supply system of a biomass direct-fired boiler, implementing the anti-clogging and high-precision metering control method for the biomass feeding system described in this invention. The overall hardware architecture, sensor configuration, and control logic are completely consistent with the aforementioned invention. All functions are integrated into the same controller and run in parallel in real time. The controller's calculation and execution cycle is set to 10ms.

[0050] I. Specific Layout of System Hardware Structure This embodiment adopts a two-stage feeding hardware structure, with the hopper, first-stage feeding device, buffer hopper, and second-stage feeding device arranged sequentially from front to back. All supporting sensing and execution components are connected to a unified controller, as detailed below: 1. Two-stage feeding main structure A storage silo is set up at the front end, and a first-stage steady-flow scraper feeder is installed below the outlet of the storage silo. It adopts a scraper conveying structure and relies on a large conveying cross section and forced scraping capacity to break up material bridging and slack at the outlet of the silo, so as to provide a continuous and stable basic material flow for the downstream equipment. The maximum discharge rate of the steady-flow scraper feeder is higher than the maximum demand rate of the downstream feeder, so as to avoid insufficient material supply at the front end.

[0051] A buffer hopper is installed below the discharge port of the steady-flow scraper feeder. Its effective volume can accommodate the feed rate for 30 seconds under rated operating conditions. This is used to absorb the flow fluctuations of the front-end feed and ensure a stable feeding environment for the downstream metering equipment.

[0052] A second-stage high-precision weighing feeder is installed below the outlet of the buffer hopper. In this embodiment, a fully suspended weighing belt feeder is used. The whole machine is suspended by a high-precision weighing sensor group, which can directly obtain the instantaneous weight signal of the material on the belt. A photoelectric encoder is installed at the tail of the drive motor of the high-precision weighing feeder to collect the actual speed of the motor in real time.

[0053] Vibrators are symmetrically installed on the outer side of the upper wall of the storage silo. Their start and stop are controlled by the output signal of the controller to help break up material bridging in the silo.

[0054] 2. Sensor Acquisition System Configuration Various sensing components are deployed at corresponding locations within the system, and all output signals are connected to the same programmable logic controller (PLC). The specific configuration is as follows: Weighing sensor group: arranged at the suspension support point of the high-precision weighing feeder, outputting 4~20mA analog signal, with a weighing resolution better than 1 / 10000; Speed ​​sensor: It adopts a photoelectric encoder, which is installed on the rotating shaft of the drive motor of the high-precision weighing feeder and outputs pulse signals to detect the real-time speed of the motor; Hall effect current transformers are connected in series in the power distribution circuits of the drive motors of the constant current scraper feeder and the high-precision weighing feeder to monitor the motor operating current in real time, with the current range covering the motor stall current. Online detection unit: An online microwave moisture analyzer and a matching temperature probe are installed at the material discharge position at the outlet of the buffer hopper to detect the relative permittivity and temperature of the material in real time.

[0055] All sensor signals are synchronously connected to the controller. The system sampling period is consistent with the controller's operation period, both being 10ms. All control logic and operations are completed within this controller.

[0056] II. Specific Implementation Process of Control Methods The controller internally comprises four parallel real-time computational modules: a mass flow rate-volume flow rate cascade control module, a moisture content online estimation and density correction module, a drive motor current spectrum analysis and blockage feature identification module, and an anti-blockage action sequence generation module. The module descriptions below are for functional convenience only; in actual operation, each module synchronously updates and interacts with data every control cycle, and there is no sequential execution order. The overall control input of the system is the mass flow rate setpoint issued by the host combustion optimization system. The modules work together to achieve integrated control of anti-blocking, high-precision metering and rapid load response.

[0057] 1. Online moisture content estimation and density correction module This module runs independently and in parallel, reading the relative permittivity of the material collected by the microwave moisture analyzer each control cycle. With material temperature The system uses a pre-calibrated polynomial model to calculate the real-time moisture content of materials online. The calculation formula is:

[0058] In the formula, These are polynomial regression coefficients, obtained through regression calibration experiments on a static testing bench using material samples with various moisture contents.

[0059] Real-time moisture content calculated The output is sent to the cascade control module in real time, and substituted into the bulk density correction formula to correct the bulk density of the material in real time. :

[0060] In the formula, The basic bulk density of the material under absolutely dry conditions, expressed in kg / L; The moisture content influence coefficient is dimensionless; both were obtained through offline experimental calibration. The corrected bulk density is input in real time into the feedforward calculation and volume conversion stages of the cascade control to offset the measurement deviation caused by material density fluctuations.

[0061] 2. Mass flow rate - volumetric flow rate cascade control module This module is the core of the metering control system. It adopts a cascade control structure, using a mass flow closed loop as the outer loop to ensure long-term metering accuracy, and a volumetric flow closed loop as the inner loop to suppress instantaneous disturbances. The specific implementation process is as follows: (1) Calculation of mass flow feedback value The real-time weight signal collected by the weighing sensor is read each control cycle. First, the signal is processed by a second-order Butterworth low-pass filter with a cutoff frequency of 2Hz to remove high-frequency noise caused by mechanical vibration, resulting in a smoothed weight signal. Instantaneous mass flow rate feedback value is calculated through real-time differential calculation:

[0062] In the formula, This is the system sampling period, which is consistent with the controller's operation period and has a value of 10ms. This is the instantaneous mass flow rate feedback value at time t, in kg / s. This value serves as the process feedback value for the outer loop of the cascade control.

[0063] (2) Calculation of outer loop mass flow PID controller Mass flow rate setting With mass flow feedback value The difference is calculated to obtain the mass flow rate deviation. The input is given to the outer loop PID controller, which calculates the correction amount for the volumetric flow rate setpoint. :

[0064] In the formula, , , These are the proportional coefficient, integral coefficient, and derivative coefficient of the outer loop mass flow PID controller, respectively, obtained through on-site debugging and tuning.

[0065] Simultaneously, based on the current mass flow rate setpoint and the real-time corrected bulk density, the volumetric flow rate feedforward value is calculated. To achieve rapid pre-response to changes in setpoints:

[0066] The feedforward value and the correction amount are added together to obtain the final setpoint for the inner loop of the volumetric flow rate:

[0067] In the formula, This is the inner loop setpoint for volumetric flow rate, in L / s.

[0068] (3) Rapid adjustment of inner ring volumetric flow rate Based on the actual motor speed collected by the photoelectric encoder Combined with the pre-determined displacement coefficient per revolution of the feeder The actual volumetric flow rate feedback value is obtained by conversion:

[0069] In the formula, The feeder's displacement coefficient per revolution, in L / r, is predetermined by the mechanical structure parameters; This represents the actual speed of the motor, expressed in r / s.

[0070] To improve the ability to withstand disturbances, dynamic correction is introduced based on the observed volumetric flow rate from the weighing signal: the differential value of the weighing signal is divided by the real-time bulk density to obtain the observed volumetric flow rate. :

[0071] The volumetric flow rate feedback value converted from rotational speed is weighted and fused with the volumetric flow rate observed by weighing to obtain the final process value of the inner loop control. :

[0072] In the formula, The fusion weighting coefficient for the observations is dimensionless and has a value of 0.2.

[0073] The inner loop uses a PI controller, which calculates the speed increment based on the deviation between the volumetric flow rate setpoint and the process value, and outputs it to the speed control device.

[0074] In the formula, , These are the proportional and integral coefficients of the inner loop volumetric flow PI controller, which are obtained through debugging and tuning. This is the setpoint for the motor speed, in r / s.

[0075] (4) Dynamic load feedforward compensation When the mass flow rate setting value is issued by the higher-level unit When a step change occurs, calculate its rate of change and multiply it by the feedforward gain. This is directly superimposed on the setpoint speed to obtain the final speed command:

[0076] In the formula, The dynamic load feedforward gain is obtained through tuning and adjustment. Feedforward compensation further accelerates the load response speed, achieving a feed rate response within seconds.

[0077] Through the above cascade control architecture, the inner loop can quickly offset the metering error caused by the instantaneous bulk density fluctuation of materials and the unevenness of mechanical structure, while the outer loop eliminates long-term metering drift, ultimately ensuring that the overall metering accuracy is ≤±1%.

[0078] 3. Drive motor current spectrum analysis and blockage feature identification module This module operates independently and in parallel with the metering control module, processing the motor current signals of the constant-flow scraper feeder and the high-precision weighing feeder independently to diagnose early signs of material blockage. Taking any feeder as an example, the specific diagnostic process is as follows: Real-time current signal of the motor is collected during each control cycle. The current signal is subjected to a windowed Fast Fourier Transform (FFT) with a window length of 1024 points, and 512 points are slid in each step to calculate and update the current spectrum in real time.

[0079] The characteristic frequency of the current is calculated based on the mechanical parameters of the feeder. For a scraper feeder, the characteristic frequency is... Determined by the motor speed and the number of sprocket teeth:

[0080] In the formula, The current motor speed, in rpm; The number of teeth on the feeder drive sprocket is dimensionless. The characteristic frequency of the current corresponding to the scraper movement is expressed in Hz.

[0081] Extract the maximum amplitude within a ±0.5 Hz frequency band near the characteristic frequency from the real-time spectrum. Simultaneously, the moving average value of the current signal within a 2-second time window is calculated. When both conditions are met and When the feeder shows signs of material blockage or jamming, a blockage warning is triggered; among which... The characteristic frequency amplitude threshold, Both are average current thresholds, and are baseline thresholds obtained statistically under normal operating conditions of the equipment.

[0082] 4. Anti-blocking action sequence generation module This module operates in parallel. Upon receiving an early warning signal from the blockage feature recognition module, it immediately executes a timed anti-blockage action on the corresponding feeder that shows signs of impending blockage. The specific action sequence is as follows: a. Control the feeder to stop rotating forward, with a delay of 0.2 seconds; b. Control the drive motor of the feeder to run in reverse for 0.5~1.5s to loosen the stuck material; c. Simultaneously start the vibrator on the silo wall and vibrate continuously for 1 second to help break up the bridging at the silo outlet; d. After another 0.3s delay, the feeder resumes normal speed regulation operation and returns to the metering control logic.

[0083] The above-mentioned anti-blocking process is automatically executed by the controller. The total time from the identification of blockage symptoms to the completion of the action is ≤2s, realizing proactive intervention and early elimination of blockage, without having to wait for the material to completely block the blockage before passive handling.

[0084] III. Verification of the Technical Effects of this Embodiment Through the complete implementation of the above hardware structure and parallel control architecture, this system can simultaneously solve the three core problems of existing technologies: easy clogging of feed, low metering accuracy, and lag in load response, and has significant technical advantages: 1. Proactive anti-blocking, continuous and reliable operation: Based on the current spectrum characteristics, the system identifies the signs of material blockage and triggers intervention before the material is completely blocked. Combined with the timed reverse loosening and vibration arch breaking action, the total anti-blocking time is ≤2s, which can effectively avoid material blockage and material interruption failures and improve the continuous operation capability of the system. 2. High-precision metering and strong anti-interference ability: Through mass-volume cascade control combined with density compensation with online moisture content correction, the influence of density fluctuation caused by material moisture content and batch differences can be offset, and the metering accuracy is stably controlled within ±1%, which is significantly better than the traditional volumetric feeding scheme. 3. Rapid load response, adaptable to dynamic operating conditions: The rapid adjustment capability of the cascade inner loop, combined with the dynamic load feedforward mechanism, enables the feeding rate to follow within seconds, and the load change response delay is ≤3s, which can fully adapt to the operating requirements of biomass boilers for rapid load increases and decreases. 4. Integrated and highly intelligent: All functions are integrated into the same controller, with parallel operation in 10ms cycle and real-time data interaction between modules. No need for multi-system collaboration, avoiding the fragmentation of control logic, and enabling maintenance-free automatic operation of the system.

[0085] The above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for preventing blockage and achieving high-precision metering control in a biomass feeding system, characterized in that, Includes the following steps: A flow-stabilizing scraper feeder is installed at the outlet of the silo, a buffer hopper is installed downstream of the flow-stabilizing scraper feeder, and a weighing feeder is installed at the outlet of the buffer hopper. The weighing feeder is supported by a weighing sensor group and is equipped with a speed sensor for detecting the speed of its drive motor. Hall current transformers are connected to the motor power distribution circuits of the constant flow scraper feeder and the weighing feeder respectively. An online microwave moisture analyzer and a temperature probe are installed at the inlet of the weighing feeder. A bin wall vibrator is installed on the bin. Connect the weighing sensor group, speed sensor, Hall current transformer, online microwave moisture analyzer, temperature probe and bin vibrator to the same controller. The following control modules are constructed within the controller and operate in parallel: Mass flow rate-volume flow rate cascade control module: Receives the mass flow rate setpoint from the upper-level unit, obtains the mass flow rate feedback value based on the weight signal collected by the weighing sensor group, generates the volume flow rate inner loop setpoint based on the deviation between the mass flow rate setpoint and the mass flow rate feedback value, and the real-time bulk density provided by the online moisture content estimation and density correction module, performs inner loop control calculations based on the rotational speed signal collected by the rotational speed sensor, the weight signal, and the real-time bulk density to obtain the basic rotational speed setpoint, and then superimposes the feedforward quantity related to the rate of change of the mass flow rate setpoint to generate the final rotational speed setpoint, thereby controlling the drive motor of the weighing feeder; Online moisture content estimation and density correction module: Calculates the real-time moisture content of the material based on the dielectric constant collected by the online microwave moisture analyzer and the temperature collected by the temperature probe, and obtains the real-time bulk density based on the pre-calibrated density-moisture content relationship; Drive motor current spectrum analysis and blockage feature identification module: Perform spectrum analysis on the motor current signal collected by the Hall current transformer, extract the amplitude of the characteristic frequency corresponding to the mechanical structure of the feeder, and calculate the mean value of the current signal; When the amplitude is greater than the first threshold and the average current is greater than the second threshold, a blockage precursor signal is output. Anti-blocking action sequence generation module: After receiving the pre-blocking signal, it controls the corresponding feeder to stop rotating in the forward direction and in the reverse direction, and starts the bin wall vibrator. After a delay, the feeder resumes normal operation.

2. The method according to claim 1, characterized in that, The constant flow scraper feeder discharges material at a rate higher than the maximum feeding requirement of the weighing feeder; the buffer hopper has a volume that can accommodate the feeding amount for 30 seconds under rated operating conditions; the weighing feeder is a fully suspended weighing belt conveyor or a loss-in-weight screw feeder; the speed sensor is a photoelectric encoder.

3. The method according to claim 1, characterized in that, The resolution of the weighing sensor group is better than Output or Analog signal; the controller is a programmable logic controller or an embedded controller, and the controller's operation execution cycle... The online microwave moisture analyzer is a capacitive dielectric constant sensor; the temperature probe is a platinum resistance thermometer; the system sampling period and the controller operation period are consistent. .

4. The method according to claim 1, characterized in that, The step of obtaining the mass flow feedback value includes: processing the weight signal. Perform a second-order Butterworth low-pass filter, with the filter cutoff frequency set to... To obtain a smooth weight Instantaneous mass flow feedback value is calculated through real-time differential calculation. : in The sampling period is [percentage], and the value is [value]. .

5. The method according to claim 4, characterized in that, The outer loop control calculation for generating the inner loop setpoint of the volumetric flow rate based on the deviation is PID control: ,in ; Volumetric flow feedforward Volumetric flow rate inner loop setpoint , The real-time packing density; The inner loop control operation includes: obtaining the actual volumetric flow rate feedback value based on the rotation speed signal. , The displacement coefficient per revolution of the weighing feeder is given. The motor speed is used; the observed volumetric flow rate is obtained based on the weight signal and real-time bulk density. ; Will and Weighted fusion yields the inner loop process value Weight The basic speed setpoint is obtained by using PI control to determine the deviation between the inner loop setpoint and the process value. ; The feedforward amount is The final speed setpoint is obtained by superimposing the values. , This is the feedforward gain.

6. The method according to claim 1, characterized in that, The real-time moisture content of the material Calculate using the following formula: in Let be the relative permittivity of the material. For material temperature ( ), The regression coefficients are pre-calibrated experimentally; the density-moisture content relationship is: in The basic bulk density of the oven-dry material ( ), This is the influence coefficient of moisture content.

7. The method according to claim 1, characterized in that, The spectrum analysis is for current signals. Perform a windowed Fast Fourier Transform, with the window length set to... Dot, each swipe Point; for the aforementioned constant-flow scraper feeder, its characteristic frequency Determined by the following formula: in Motor speed ( ), The number of sprocket teeth; in Extracting the maximum amplitude within the frequency band The average current is Moving average within a second window The first threshold is The second threshold is All of these are thresholds obtained from statistics during normal operation.

8. The method according to claim 1, characterized in that, The anti-blocking action sequence executed by the anti-blocking action sequence generation module is as follows: a) Control the corresponding feeder to stop rotating forward, with a delay. ; b) Control the feeder drive motor to rotate in reverse. ; c) Synchronously start the bin wall vibrator for continuous vibration ; d) Delay again The feeder was then restored to normal operation. Total time from the output of the warning signal for material blockage to the completion of the action .

9. The method according to claim 1, characterized in that, The four control modules synchronously complete data updates and interactions within each controller's operation cycle.

10. The method according to claim 2, characterized in that, The weighing feeder is a fully suspended weighing belt conveyor; the online microwave moisture analyzer is installed at the material discharge position of the buffer hopper outlet; the controller is a programmable logic controller.

Images