Valve terminal control box based on intelligent turbulence valve and pipe blockage early warning system in pneumatic ash conveying system

Abstract

The invention relates to the technical field of pneumatic conveying control, and discloses a valve terminal control box and pipe blockage early warning system based on an intelligent turbulence valve in a pneumatic ash conveying system, which comprises a physical parameter sensing module, a logic mapping processing module, a flow state attribute judgment module, an execution control driving module and an adjustment execution module, the physical parameter sensing module obtains a pressure pulsation high-frequency component generated by two-phase flow evolution in a material transmission channel, and the logic mapping processing module determines a high-frequency signal attenuation impedance ratio reflecting the fluid viscous damping evolution trend. The flow state attribute judgment module determines that a controlled object is in a flow state reconstruction state according to the impedance ratio offset characteristic and generates a feedforward early warning instruction, the execution control driving module drives the adjustment execution module to output high-pressure jet pulses, an agglomeration structure is destroyed, and the flow state is analyzed through flow state microcosmic evolution quantization. The mode of lagging macroscopic pressure judgment is converted into the mode of microcosmic feedforward early warning, powder bridging is avoided, and dynamic balance of a channel is maintained.

Description

Technical Field

[0001] This invention belongs to the field of pneumatic conveying control technology, and particularly relates to a valve island control box and a blockage early warning system based on an intelligent turbulence valve in a pneumatic ash conveying system. Background Technology

[0002] Currently, pneumatic ash conveying systems in thermal power plants typically employ a control method based on macroscopic pressure thresholds. This method utilizes pressure transmitters to acquire pipeline pressure signals, and the controller determines valve adjustment commands based on pressure change trends to achieve gas replenishment or ash discharge operations. Macroscopic pipeline pressure is essentially an integral representation of the local flow field physical resistance in the overall spatial topology. There is a physical lag in the signal generation and physical transmission process. When the sensor detects an abnormal pressure slope and triggers the adjustment action, the powder inside the pipeline has usually changed from a discrete phase to a dense agglomerated phase, causing the conventional gas replenishment action to fail due to fluid channel blockage, and the system enters a fault shutdown state.

[0003] Existing technologies attempt to optimize control accuracy by shortening the sampling cycle or increasing the number of pressure monitoring points. However, macroscopic pressure signals are difficult to separate from gas source fluctuation components and steady-state delivery pressure components, and cannot effectively capture the high-frequency energy attenuation characteristics caused by particle collisions with pipe walls. There is room for improvement in physical pipeline design and hardware topology. Pneumatic delivery control methods and early warning logic face bottlenecks such as insufficient sensing accuracy and significant response time delays. For example, Chinese invention patent CN208394362U discloses a static pressure dense-phase booster pneumatic delivery process test device, which detects pressure difference through segmented pressure transmitters. Using electrostatic induction electrodes to monitor the ash conveying status and adjust the supplementary air flow rate is a passive feedback mechanism after the state has been established. However, the electrostatic induction signal is affected by electromagnetic environment and material humidity under complex industrial conditions, making it difficult to accurately predict the microscopic flow state reconstruction process of powder. This linear improvement method based on macroscopic parameters is difficult to identify the initial microscopic process of powder agglomeration, resulting in the actuator being unable to intervene in situ before physical jamming occurs. At the same time, existing control boxes mostly use a single communication protocol, which limits the efficiency of acquiring multi-dimensional operating data under complex conditions and makes it difficult to support adjustment strategies with feedforward capabilities.

[0004] Therefore, how to achieve real-time monitoring of the micro-flow state of powder and construct a regulation loop with physical feedforward capability is the technical problem to be solved by this invention. Summary of the Invention

[0005] This invention provides a valve island control box and a blockage early warning system based on an intelligent turbulence valve in a pneumatic ash conveying system, comprising: The physical parameter sensing module is used to acquire the high-frequency components of pressure pulsation generated by the evolution of two-phase flow inside the material transfer channel in real time. The logic mapping processing module is used to determine the high-frequency signal attenuation impedance ratio, which reflects the evolution trend of fluid viscosity damping inside the material transport channel, based on the high-frequency component of pressure pulsation within a preset time sliding window. The flow state property determination module is used to perform a numerical comparison between the high-frequency signal attenuation impedance ratio and the preset flow state stability criterion. When the offset value of the high-frequency signal attenuation impedance ratio continues to exceed the preset phase change trigger threshold, it determines that the controlled object is in the flow state reconstruction state of the phase transition from discrete phase to dense agglomeration and generates a feedforward adjustment early warning command. The execution control drive module is used to generate a pulse width modulation command with an asymmetric duty cycle and controlled frequency in response to the feedforward adjustment warning command. The regulating execution module is used to output high-pressure jet pulses in response to pulse width modulation commands. The high-pressure jet pulses are used to perform shearing actions on the agglomeration structure generated in the flow state reconstruction state. Before the macroscopic characteristic parameters of the system increase by a step, the bridging structure is destroyed and the flow state of the material in the material transmission channel is restored.

[0006] Preferably, the physical parameter sensing module includes pressure distribution acquisition units distributed on the material conveying channel. The sampling frequency of the pressure distribution acquisition units is 1000Hz to 5000Hz, which are used to capture the pulsating energy absorption signal generated by the collision of material particles.

[0007] Preferably, the logic mapping processing module performs energy distribution mapping by the following steps: Step S1, extracting discrete pressure sample sequences within a preset time sliding window; Step S2, calculating the instantaneous dispersion of the discrete pressure sample sequences relative to the mean of the preset time sliding window; Step S3, determining the high-frequency signal attenuation impedance ratio based on the energy spectral density distribution of the instantaneous dispersion in the frequency domain.

[0008] Preferably, the high-frequency signal attenuation impedance ratio is determined by the following formula: ,in, For high-frequency signal attenuation impedance ratio, The root mean square value of the signal within a preset time sliding window. The system presets the pulsating energy baseline value under no-load conditions, where α is the energy absorption coefficient characterizing particle collision damping characteristics, and Δt is the characteristic evolution time step.

[0009] Preferably, the flow property determination module is also used to dynamically adjust the numerical comparison weights in the flow stability criterion based on the topological layout characteristics of the material transport channel and the property data of the controlled material.

[0010] Preferably, the frequency of the pulse width modulation command generated by the execution control drive module is adjusted to form a preset frequency difference with the inherent frequency of the material conveying channel.

[0011] Preferably, the asymmetric duty cycle of the pulse width modulation command is defined as a periodic pressure pulse with a rising edge width smaller than the falling edge width, used to apply a unidirectional pulse load to the aggregated structure.

[0012] Preferably, the system also includes a communication gateway module, which is used to integrate fieldbus protocols to enable operational data interaction between the system and an external monitoring center.

[0013] Preferably, the communication gateway module is also used to record historical evolution data of the high-frequency signal attenuation impedance ratio and to use a deep learning model to perform trend prediction on the deposition risk on the inner wall of the material transport channel.

[0014] Preferably, the physical parameter sensing module, logic mapping processing module, flow state attribute determination module, and execution control drive module are all integrated into the logic encapsulation module, and the regulation execution module adopts a turbulence regulation unit, forming a local feedback control closed loop with the logic encapsulation module.

[0015] Compared with existing technologies, the valve island control box and pipe blockage early warning system based on intelligent turbulence valve in the pneumatic ash conveying system of the present invention have the following advantages: 1. In the valve island control box of the intelligent turbulent flow valve, by integrating digital bandpass filter logic into the processor of the valve island control box, the high-frequency pressure perturbation component in the continuous pressure time series data array collected by the pressure sensor is continuously stripped away. A closed-loop feedback mechanism based on the change of micro-flow activity is constructed, so that the system's perception dimension of the evolution of powder flow in the conveying pipeline is reduced from the lagging macro-pressure slope judgment to the real-time quantification of the degree of absorption of high-frequency pulsating energy generated by particle collision with the pipe wall. Thus, before the powder in the pipe completes the irreversible physical reconstruction from discrete phase to dense agglomerate phase, a deterministic feedforward early warning signal is provided, avoiding the failure of gas injection intervention caused by physical transmission delay in traditional control logic.

[0016] 2. The valve island control box uses a preset time sliding window to calculate the root mean square value of the high-frequency pressure perturbation component and converts it into a high-frequency signal attenuation impedance ratio that reflects the change in viscosity damping inside the fluid. The change in this impedance ratio directly characterizes the degree of distortion of the virtual flow topology inside the pipeline network, enabling the system to bypass complex nonlinear two-phase flow modeling and transform the potential pipe blockage risk into a single-variable time-series attenuation feedback control problem. This improves the decision certainty of the control loop under complex operating conditions and ensures that the control system triggers intervention actions at the microscopic stage of the initial local bridging of powder, maintaining the dynamic balance of gas-solid two-phase flow in the pipeline.

[0017] 3. By generating pulse width modulation commands with asymmetric duty cycles through the drive circuit, the intelligent turbulence valve of the corresponding pipe section is driven to output high-pressure jet pulses of a specific frequency. Utilizing the physical intervention generated by the natural resonance frequency between the high-pressure jet pulses and the powder agglomeration structure inside the pipe, the initial powder bridging structure is destroyed by high-frequency physical shear force before the macroscopic conveying pressure increases dramatically, forcibly restoring the material's fluidity. This method not only significantly reduces the energy consumption of continuous air replenishment to deal with blockages, but also eliminates the physical basis for rigid jamming of the system by intervening in the microscopic phase change process, extending the service life of pneumatic components and conveying pipelines. Attached Figure Description

[0018] Figure 1 This is a flowchart of the micro-flow state sensing and feedforward regulation logic of the present invention; Figure 2 This is a functional module and logic architecture diagram of the valve island control box of the present invention. Detailed Implementation

[0019] The technical solutions of the embodiments of this application will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.

[0020] It should be noted that all directional and positional terms used in this invention, such as: up, down, left, right, front, back, vertical, horizontal, inner, outer, top, bottom, transverse, longitudinal, center, etc., are only used to explain the relative positional relationship and connection between components in a specific state (as shown in the accompanying drawings). They are only for the convenience of describing this invention and do not require that this invention be constructed and operated in a specific orientation. Therefore, they should not be construed as limiting this invention. In addition, the descriptions of "first," "second," etc., in this invention are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated.

[0021] In the description of this invention, unless otherwise explicitly specified and limited, the terms installation, connection, and linking should be interpreted broadly. For example, they can refer to fixed connections, detachable connections, or integral connections; they can refer to mechanical connections; they can refer to direct connections or indirect connections through an intermediate medium; they can refer to the internal connection of two components. For those skilled in the art, the specific meaning of the above terms in this invention can be understood according to the specific circumstances.

[0022] In the description of this specification, references to the terms "an embodiment," "some embodiments," "illustrative embodiments," "examples," "specific examples," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example, and the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0023] A valve island control box and a blockage early warning system based on an intelligent turbulence valve in a pneumatic ash conveying system, comprising: The physical parameter sensing module is used to acquire the high-frequency components of pressure pulsation generated by the evolution of two-phase flow inside the material transfer channel in real time. The logic mapping processing module is used to determine the high-frequency signal attenuation impedance ratio, which reflects the evolution trend of fluid viscosity damping inside the material transport channel, based on the high-frequency component of pressure pulsation within a preset time sliding window. The flow state property determination module is used to perform a numerical comparison between the high-frequency signal attenuation impedance ratio and the preset flow state stability criterion. When the offset value of the high-frequency signal attenuation impedance ratio continues to exceed the preset phase change trigger threshold, it determines that the controlled object is in the flow state reconstruction state of the phase transition from discrete phase to dense agglomeration and generates a feedforward adjustment early warning command. The execution control drive module is used to generate a pulse width modulation command with an asymmetric duty cycle and controlled frequency in response to the feedforward adjustment warning command. The regulating execution module is used to output high-pressure jet pulses in response to pulse width modulation commands. The high-pressure jet pulses are used to perform shearing actions on the agglomeration structure generated in the flow state reconstruction state. Before the macroscopic characteristic parameters of the system increase by a step, the bridging structure is destroyed and the flow state of the material in the material transmission channel is restored.

[0024] Preferably, the physical parameter sensing module includes pressure distribution acquisition units distributed on the material conveying channel. The sampling frequency of the pressure distribution acquisition units is 1000Hz to 5000Hz, which are used to capture the pulsating energy absorption signal generated by the collision of material particles.

[0025] Preferably, the logic mapping processing module performs energy distribution mapping by the following steps: Step S1, extracting discrete pressure sample sequences within a preset time sliding window; Step S2, calculating the instantaneous dispersion of the discrete pressure sample sequences relative to the mean of the preset time sliding window; Step S3, determining the high-frequency signal attenuation impedance ratio based on the energy spectral density distribution of the instantaneous dispersion in the frequency domain.

[0026] Preferably, the high-frequency signal attenuation impedance ratio is determined by the following formula: ,in, For high-frequency signal attenuation impedance ratio, The root mean square value of the signal within a preset time sliding window. α is the preset pulsed energy reference value under no-load conditions of the system, α is the energy absorption coefficient characterizing the particle collision damping characteristics, and Δt is the characteristic evolution time step.

[0027] Preferably, the flow property determination module is also used to dynamically adjust the numerical comparison weights in the flow stability criterion based on the topological layout characteristics of the material transport channel and the property data of the controlled material.

[0028] Preferably, the frequency of the pulse width modulation command generated by the execution control drive module is adjusted to form a preset frequency difference with the inherent frequency of the material conveying channel.

[0029] Preferably, the asymmetric duty cycle of the pulse width modulation command is defined as a periodic pressure pulse with a rising edge width smaller than the falling edge width, used to apply a unidirectional pulse load to the aggregated structure.

[0030] Preferably, the system also includes a communication gateway module, which is used to integrate fieldbus protocols to enable operational data interaction between the system and an external monitoring center.

[0031] Preferably, the communication gateway module is also used to record historical evolution data of the high-frequency signal attenuation impedance ratio and to use a deep learning model to perform trend prediction on the deposition risk on the inner wall of the material transport channel.

[0032] Preferably, the physical parameter sensing module, logic mapping processing module, flow state attribute determination module, and execution control drive module are all integrated into the logic encapsulation module, and the regulation execution module adopts a turbulence regulation unit, forming a local feedback control closed loop with the logic encapsulation module.

[0033] Example 1: In the industrial operation of a thermal power plant's ash conveying system, where ash content fluctuations caused by coal blending lead to blockages in pneumatic conveying pipelines, conventional monitoring mechanisms based on the overall pressure integration of the pipeline network suffer from physical transmission delays. By the time the sensor detects the pressure slope shift and triggers the adjustment action, the powder inside the pipeline has already undergone an irreversible phase transition from a discrete state to a dense agglomeration state. In this technical solution, a pneumatic ash conveying system is configured with a distributed arrangement of a valve island control box based on an intelligent turbulence valve and a pipe blockage early warning system. A pressure distribution acquisition unit on the material conveying channel continuously acquires the high-frequency components of pressure pulsations generated by the evolution of two-phase flow inside the material conveying channel at a sampling frequency of 1000Hz to 5000Hz. This captures the pulsating energy absorption signal generated by the collision of material particles with the pipe wall, shifting the dimension of physical perception of blockage from the overall blockage result to the initial stage of local agglomeration phase transition of powder particles.

[0034] The logic mapping processing module within the valve island control box extracts the discrete pressure sample sequence within a preset time sliding window, calculates its instantaneous dispersion relative to the preset time sliding window mean, and determines the high-frequency signal attenuation impedance ratio, reflecting the evolution trend of fluid viscosity damping within the material transport channel, based on the energy spectral density distribution of the instantaneous dispersion in the frequency domain. This high-frequency signal attenuation impedance ratio is determined according to the formula... Confirmed, among which For high-frequency signal attenuation impedance ratio, The root mean square value of the signal within a preset time sliding window. The system uses a preset pulsating energy benchmark value under no-load conditions, where α is the energy absorption coefficient characterizing particle collision damping, and Δt is the characteristic evolution time step. The flow state property determination module compares the high-frequency signal attenuation impedance ratio with the preset flow state stability criterion. Based on the topological layout characteristics of the material transport channel and the attribute data of the controlled material, it dynamically adjusts the numerical comparison weights in the flow state stability criterion. When the calculation results within three consecutive characteristic evolution time steps show that the offset value of the high-frequency signal attenuation impedance ratio continuously exceeds the preset phase change trigger threshold, it determines that the controlled object is in a flow state reconstruction state of phase transition from discrete to dense agglomeration. Simultaneously, it outputs a feedforward adjustment early warning command, using the previously acquired high-frequency pressure pulsation component as the direct data input to trigger flow state reconstruction intervention.

[0035] In response to the feedforward adjustment warning command, the execution control drive module generates a pulse width modulation command with an asymmetric duty cycle and controlled frequency. The asymmetric duty cycle of this pulse width modulation command is defined as a periodic pressure pulse with a rise edge width shorter than a fall edge width. A unidirectional pulse load is applied to the agglomeration structure, and the frequency of the pulse width modulation command is adjusted to form a preset frequency difference with the inherent frequency of the material transport channel. The adjustment execution module outputs a high-pressure jet pulse according to the pulse width modulation command. This high-pressure jet pulse applies physical shear force to the agglomeration structure generated under the flow reconstruction state, disrupting the powder bridging structure before the overall system characteristic parameters experience a step increase, thus restoring the steady-state flow of the material within the material transport channel. High-frequency pulsed jet local instantaneous energy injection replaces continuous high-flow global air replenishment, reducing the overall consumption of the conveying air source while maintaining the safety of the material conveying channel against blockage. During the system's air purging phase, the execution control drive module outputs a randomly distributed pulse width excitation signal to the intelligent turbulence valve. The physical parameter sensing module collects the pressure disturbance sequence of the material conveying channel, and the logic processing unit calculates the power spectral density of the sequence, identifies the frequency component with the highest amplitude and determines it as the natural frequency of the material conveying channel. The algebraic sum of the offsets between the natural frequency and the preset frequency is calculated to obtain the pulse width modulation command center trigger frequency. The identification process of this natural frequency includes: under purging conditions with zero material load, the execution control drive module outputs a frequency to the intelligent turbulence valve. A sweep excitation signal, increasing in 1Hz increments between 10Hz and 500Hz, is used to synchronously acquire pressure sequences by the physical parameter sensing module. The frequency point corresponding to the maximum amplitude in the energy spectral density is used as the natural frequency reference value for the pipeline. This operation is automatically performed before the start of each conveying cycle. The measured frequency parameters are used to offset the impact of stress changes in the pipeline support structure on vibration characteristics. Addressing the signal transmission bottleneck and physical execution lag limitations at the hardware level of the pneumatic ash conveying system, the physical parameter sensing module in the valve island control box is configured with a direct memory access transmission architecture independent of the conventional polling bus. This architecture converts the acquired high-frequency components of pressure pulsations into discrete pressure sample sequences and directly maps them to the underlying hardware registers of the logic mapping processing module. To avoid frequency domain distortion caused by communication bandwidth, the built-in feedforward dead zone compensation circuit of the execution module is adjusted to extract the parasitic inductance parameter of the electromagnetic drive coil and the mass of the internal mechanical components of the intelligent turbulent valve. The mechanical hysteresis time constant of the valve action component overcoming static friction to reach the set opening stroke from a stationary state is calculated. Based on the mechanical hysteresis time constant, the advance displacement of the rising edge trigger phase execution time dimension of the pulse width modulation command with asymmetric duty cycle and controlled frequency is compensated, and a corrected drive signal superimposed with transient overvoltage is generated and output to the intelligent turbulent valve. While offsetting the physical compression of the asymmetric duty cycle time width by the mechanical inertia of the fluid valve, the timing consistency between the actual output high-pressure jet pulse and the intervention of the early warning judgment result is maintained.

[0036] Example 2: Under the industrial operation conditions of pneumatic conveying of fly ash in a thermal power plant, to verify the system's stability in the face of drastic fluctuations in ash content and disturbances in the background environment of the pipeline network, a closed-loop pneumatic conveying physical verification platform was constructed. A horizontal material conveying channel with an inner diameter of 150mm and a conveying equivalent distance of 500m was configured. High-frequency dynamic pressure sensors with a range of 0 to 1.0MPa and a natural frequency lower limit of 10kHz were installed at equal intervals on the outer side of the pipe wall. At the air inlet of the material conveying channel, Gaussian white noise with a signal-to-noise ratio of 20dB and a fundamental frequency of 50Hz were actively injected via a mechanical vibrator. The power frequency harmonic signal of z is used to simulate the airflow pulsation and electromagnetic environment disturbance of the compressor in the field. The sampling frequency parameter of the pressure distribution acquisition unit is determined by dynamically and adaptively adjusting the sampling period based on the high frequency bandwidth extension rate of the pulsating energy spectrum when the fluid in the pipe changes from a dilute phase to a dense phase. When the high frequency component spectrum expands to a frequency band above 1000Hz, the sampling frequency approaches the upper limit of the value range and is set to 5000Hz to avoid signal aliasing under the Nyquist sampling theorem. Discrete pressure sample sequences characterizing the pulsating energy absorption signal of material particles colliding with the pipe wall are obtained under working conditions including environmental disturbances.

[0037] The verification platform was started and the initial gas-ash-solid-gas mass ratio was set to 15, with a reference airflow velocity of 12 m / s. Gradient disturbance conditions were constructed by increasing the feeder speed in a stepwise manner, causing ash concentration surges of 10%, 30%, and 50%, respectively. Discrete pressure sample sequences containing the aforementioned mixed noise were extracted during this period. The logic mapping processing module in the test group of this invention filtered out power frequency interference and extracted the root mean square value of the pulsating signal within a preset time sliding window of 0.5 s. This value was then combined with the set energy absorption coefficient and substituted into the formula. Continuous quantitative calculations are performed, in which For high-frequency signal attenuation impedance ratio, The root mean square value of the signal within a preset time sliding window. The system uses the preset pulsating energy benchmark value under no-load conditions, where α is the energy absorption coefficient characterizing particle collision damping, and Δt is the characteristic evolution time step. Test data indicates that under a 30% surge in ash concentration, the global pipeline pressure average only increases by 2.1%, while the high-frequency signal attenuation impedance ratio calculated according to the formula rapidly drops from a steady-state 1.02 to 0.47, reflecting the increase in frictional collision dissipation between powder particle layers. The flow property determination module compares this offset of 0.47 with the preset phase change trigger threshold of 0.60. After confirming that the value crosses the threshold boundary within three consecutive 10ms characteristic evolution time steps, it outputs the previous value. The feed-in adjustment warning command triggers the execution control drive module to generate a pulse width modulation command with a duty cycle of 30% to 70% and a frequency offset of 15Hz from the pipeline's natural frequency. This drives the adjustment execution module to inject a high-pressure jet pulse with a peak value of 0.65MPa into the flow reconstruction region. The control group, which removed the high-frequency impedance mapping calculation, received the action command 14.6s after the disturbance occurred, under the same ash content disturbance, relying on global pressure average monitoring. At this time, a dense agglomerate column with a measured length of 1.2m had formed in the material transfer channel. The conventional continuous gas replenishment action caused the upstream pressure of the channel to rise to the safety critical threshold of 0.89MPa due to the increased flow resistance.

[0038] To define the boundaries of the asymmetric pulsed jet parameters, the duty cycle parameter of the pulse width modulation command was verified beyond its range under a disturbance condition with a 50% surge in ash concentration. The measured physical response showed that when the duty cycle rise edge width ratio was compressed to the lower limit of 12%, the shear kinetic energy of the jet output could not penetrate the outer boundary layer of the agglomerated material, and the local channel flow resistance remained within the range of 7.4 kPa / m. When the duty cycle rise edge width ratio exceeded the upper limit of 48%, the high-pressure jet changed from transient pulse hammering to continuous aerodynamic propulsion. Without physical cutting that causes powder bridging, excessive compression from the additional air source leads to a secondary compaction effect in the channel, inducing a secondary step rebound in the conveying back pressure with an amplitude of 0.15 MPa. This confirms that limiting the asymmetric duty cycle to the range of 20% to 40% is a suitable configuration for balancing the bridging penetration force and preventing the secondary compaction effect. In a 120-hour continuous variable working condition test, the particle group in the material conveying channel maintained a dynamic flow balance in the system with this parameter configuration. The measured air consumption per ton of ash conveyed was stable at 125.6 cubic meters, effectively blocking large-area blockage paths in the pipeline.

[0039] Example 3: In a thermal power plant's pneumatic conveying pipeline network, which includes variable-diameter bends and fluctuations in the median particle size of powder, a fixed phase change trigger threshold is used to intervene in the timing deviation of local flow regime evolution. The system performs an initial state extraction operation to establish a judgment benchmark, executes a control drive module to maintain a steady-state conveying airflow benchmark velocity, and the pressure distribution acquisition unit extracts the interference-free pressure pulsation signal within a preset benchmark time window. The logic mapping processing module calculates the high-frequency energy ratio of this pressure pulsation signal to determine the steady-state benchmark impedance ratio corresponding to the pure discrete phase. The ratio of the local radius of curvature of the material conveying channel bend to the current input median particle size of the powder is used to generate a spatial curvature compensation coefficient. The logic mapping processing module calculates the product of the steady-state benchmark impedance ratio and the spatial curvature compensation coefficient to determine the... The phase change trigger threshold is set to 0.60 in the test conditions. It is obtained by multiplying the measured steady-state reference impedance ratio of 0.85 and the spatial curvature compensation coefficient of 0.705. The parameter setting is anchored to the physical network characteristics and material properties, and adapts to the topological characteristics of the bends and diameter changes in the material transmission channel. The logic processing unit extracts the position curvature radius based on the spatial coordinates of the pressure distribution acquisition unit, calculates the ratio of curvature radius to pipe diameter to generate spatial distribution correction parameters, and multiplies the preset phase change trigger threshold with the correction parameters to obtain the local dynamic judgment threshold of a specific pipe section. Based on the physical characteristic that powder is easy to accumulate at bends, the sensitivity of the impedance ratio at a specific coordinate point is increased to trigger the execution control drive module, and the local agglomeration structure shear intervention is completed before the overall flow resistance of the channel changes.

[0040] Based on the phase transition trigger threshold, the logic mapping processing module extracts a discrete pressure sample sequence containing background environmental disturbances and dynamically corrects the judgment logic according to the local topological characteristics of the material transport channel: for bends with a curvature radius of less than 500mm, the weight allocation coefficient is increased from the default 1.0 to 1.5, thereby increasing the sensitivity of this region to impedance ratio decrease. The weight calculation formula is: base weight 1.0 plus a correction value of (the difference between 500mm and the current bend radius divided by 1000mm). The discrete pressure sample sequence is input into a digital bandpass filter with a lower limit cutoff frequency set to 1000Hz to remove low-frequency mechanical vibrations and power frequency harmonics. The root mean square value of the filtered discrete sequence is extracted, and the high-frequency signal attenuation impedance ratio is continuously output in combination with the set energy absorption coefficient. When the high-frequency signal attenuation impedance ratio falls below the phase transition trigger threshold and When the duration spans three characteristic evolution time steps, the flow attribute determination module extracts the spatial coordinate parameters of the pressure distribution acquisition unit that currently generates the alarm state. Based on the difference between the high-frequency signal attenuation impedance ratio and the phase change trigger threshold, the execution priority of the intervention action is allocated in combination with the spatial coordinate parameters. The execution control drive module generates a pulse width modulation command based on the execution priority, and drives the adjustment execution module to inject a high-pressure jet pulse with an asymmetric duty cycle into the material transport channel region in the early stage of dense phase change. The pneumatic ash conveying system integrates the pipeline topology parameters to correct the phase change trigger threshold and performs feature-level data filtering. The pipeline blockage prediction is transformed into signal tracking and spatial matrix mapping actions. Under the boundary conditions of variable diameter bends and coal ash content variations, the system outputs physical shear intervention to maintain the dynamic flow balance of the gas-solid two-phase flow inside the pipeline.

[0041] Example 4: When the system faces the initial deployment conditions of a completely new material transfer channel and an unknown conveying medium, the logic mapping processing module initiates the pre-baseline calibration procedure to establish calculation parameters. The execution control drive module controls the system to operate continuously under a pure airflow purging state with zero material load. The pressure distribution acquisition unit extracts the discrete pressure sample sequence under this state. The logic mapping processing module integrates this sequence to calculate the steady-state background energy to determine the formula. The required pulsating energy reference value under no-load conditions The specific values ​​are as follows: the feeding system injects the current batch of powder sample into the channel at a constant flow rate; the pressure distribution acquisition unit records the transient pressure perturbation components during the flow transition process; the logic mapping processing module calculates the energy absorption coefficient α, which characterizes the particle collision damping characteristics, based on the ratio of energy dissipated in the flow field; in the high-frequency signal attenuation impedance ratio quantization stage, the system acquires 1,000 cycles of pressure components under zero material load conditions, calculates the root mean square value of the sample sequence, and sets it as the reference value of the pulsating energy under no-load conditions. To characterize the background energy noise without particle collision interference, a powder sample with a known mass flow rate is introduced into the channel, and the energy decay curve is recorded after the flow stabilizes. The least squares method is used to nonlinearly fit the curve to determine the energy absorption coefficient α that reflects the particle collision characteristics. This value is recorded in the memory of the logic encapsulation module. When the material type is changed, the model is resampled and the fitting is updated to achieve matching between the calculation model and the actual material properties.

[0042] The logic mapping processing module will acquire the pulsed energy reference value under no-load conditions. The energy absorption coefficient α is fixed as a low-level configuration file and written to the storage area. The flow property determination module calls the parameters in this file to calculate the high-frequency signal attenuation impedance ratio of the continuously acquired sample sequences during the real-time monitoring cycle. The flow property determination module compares the attenuation impedance ratio of the high-frequency signal with the preset phase change trigger threshold and outputs the execution priority of the intervention action. The execution control drive module generates a pulse width modulation command based on the execution priority and drives the adjustment execution module to release a high-pressure jet pulse into the channel. Under the environmental constraints of changes in the pipeline physical architecture and fluctuations in medium properties, the system completes the self-calibration of the underlying parameters and maintains the dynamic flow balance of the powder in the channel.

[0043] Example 5: In the case of continuous operation of the pneumatic ash conveying system in a thermal power plant, and the signal baseline drift caused by the aging of the pressure distribution acquisition unit hardware and the fluctuation of fluid velocity, in order to eliminate the zero-point drift error of physical components and reconstruct the underlying extraction parameters, the logic mapping processing module embedded in the system performs online adaptive calibration and fault-tolerant compensation procedures. The logic mapping processing module extracts the discrete pressure sample sequence within the current operating cycle, uses the fast Fourier transform algorithm to transform the discrete pressure sample sequence from the time domain to the frequency domain to isolate the low-frequency components generated by drift, extracts the effective pressure frequency band after removing the low-frequency components, and calculates the first zero-crossing time of its autocorrelation function. Based on this and the current conveying airflow reference velocity, the dominant time scale of the flow field fluctuation is calculated, and the length of the preset time sliding window is dynamically tuned to a specified multiple of the dominant time scale.

[0044] Based on the dynamically tuned time sliding window, the logic mapping processing module extracts multiple sets of blank pressure data during the system's purge flow phase. It then uses the least squares method to fit the baseline offset slope of the blank pressure data. Based on this slope, it constructs a time-varying baseline compensation function. The measured discrete pressure sample sequence is subtracted from the real-time compensation value output by the baseline compensation function to obtain the purified zero-mean pulsating sequence. This sequence is then input into a digital bandpass filter with a lower cutoff frequency set to 1000Hz. The root mean square value of the filtered signal is updated using a formula. The reference value of pulsating energy under no-load conditions indicated in the figure. The specific values, among which For high-frequency signal attenuation impedance ratio, The root mean square value of the signal within the time sliding window. α is the reference value of the pulsating energy under no-load conditions, α is the energy absorption coefficient characterizing the particle collision damping characteristics, and Δt is the characteristic evolution time step.

[0045] The flow property determination module calls the updated time sliding window length and the pulsating energy benchmark value under no-load conditions, recalculates the real-time high-frequency signal attenuation impedance ratio, compares the high-frequency signal attenuation impedance ratio with the phase change trigger threshold, and outputs the execution priority of the intervention action when the crossing condition is met for three consecutive characteristic evolution time steps. It drives the adjustment execution module to release a high-pressure jet pulse with an asymmetric duty cycle into the material conveying channel. The system transforms the data preprocessing steps into closed-loop tracking adjustment actions under changes in physical boundary conditions based on the time scale matching and baseline slope fitting compensation mechanism of the autocorrelation function, maintaining the anti-interference ability of the pneumatic ash conveying system to perceive and calculate the phase change evolution process of the powder two-phase flow.

[0046] The embodiments of this application have been described above with reference to the accompanying drawings. Unless otherwise specified, the embodiments and features in the embodiments of this application can be combined with each other. This application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit of this application and the scope of protection of this invention, and all of these forms are within the protection scope of this application.

Claims

1. A valve island control box and pipe blockage early warning system based on an intelligent turbulence valve in a pneumatic ash conveying system, characterized in that, include: The physical parameter sensing module is used to acquire the high-frequency components of pressure pulsation generated by the evolution of two-phase flow inside the material transfer channel in real time. The logic mapping processing module is used to determine the high-frequency signal attenuation impedance ratio, which reflects the evolution trend of fluid viscosity damping inside the material transport channel, based on the high-frequency component of pressure pulsation within a preset time sliding window. The flow state property determination module is used to perform a numerical comparison between the high-frequency signal attenuation impedance ratio and the preset flow state stability criterion. When the offset value of the high-frequency signal attenuation impedance ratio continues to exceed the preset phase change trigger threshold, it determines that the controlled object is in the flow state reconstruction state of the phase transition from discrete phase to dense agglomeration and generates a feedforward adjustment early warning command. The execution control drive module is used to generate a pulse width modulation command with an asymmetric duty cycle and controlled frequency in response to the feedforward adjustment warning command. The regulating execution module is used to output high-pressure jet pulses in response to pulse width modulation commands. The high-pressure jet pulses are used to perform shearing actions on the agglomeration structure generated in the flow state reconstruction state. Before the macroscopic characteristic parameters of the system increase by a step, the bridging structure is destroyed and the flow state of the material in the material transmission channel is restored.

2. The valve island control box and pipe blockage early warning system based on an intelligent turbulence valve in a pneumatic ash conveying system according to claim 1, characterized in that, The physical parameter sensing module includes pressure distribution acquisition units distributed along the material conveying channel. The sampling frequency of the pressure distribution acquisition units is 1000Hz to 5000Hz, which are used to capture the pulsating energy absorption signal generated by the collision of material particles.

3. The valve island control box and pipe blockage early warning system based on an intelligent turbulence valve in a pneumatic ash conveying system according to claim 1, characterized in that, The logic mapping processing module performs energy distribution mapping by the following steps: Step S1, extracting the discrete pressure sample sequence within a preset time sliding window; Step S2, calculating the instantaneous dispersion of the discrete pressure sample sequence relative to the mean of the preset time sliding window; Step S3, determining the high-frequency signal attenuation impedance ratio based on the energy spectral density distribution of the instantaneous dispersion in the frequency domain.

4. The valve island control box and pipe blockage early warning system based on an intelligent turbulence valve in a pneumatic ash conveying system according to claim 3, characterized in that, The attenuation impedance ratio of high-frequency signals is determined by the following formula: ,in, For high-frequency signal attenuation impedance ratio, The root mean square value of the signal within a preset time sliding window. α is the preset pulsed energy reference value under no-load conditions of the system, α is the energy absorption coefficient characterizing the particle collision damping characteristics, and Δt is the characteristic evolution time step.

5. The valve island control box and pipe blockage early warning system based on an intelligent turbulence valve in a pneumatic ash conveying system according to claim 1, characterized in that, The flow property determination module is also used to dynamically adjust the numerical comparison weights in the flow stability criterion based on the topological layout characteristics of the material transport channel and the property data of the controlled material.

6. The valve island control box and pipe blockage early warning system based on an intelligent turbulence valve in a pneumatic ash conveying system according to claim 1, characterized in that, The frequency of the pulse width modulation command generated by the execution control drive module is adjusted to form a preset frequency difference with the inherent frequency of the material conveying channel.

7. The valve island control box and pipe blockage early warning system based on an intelligent turbulence valve in a pneumatic ash conveying system according to claim 1, characterized in that, The asymmetric duty cycle of the pulse width modulation command is defined as a periodic pressure pulse with a rising edge width smaller than the falling edge width, used to apply a unidirectional pulse load to the aggregated structure.

8. The valve island control box and pipe blockage early warning system based on an intelligent turbulence valve in a pneumatic ash conveying system according to claim 1, characterized in that, The system also includes a communication gateway module, which integrates fieldbus protocols to enable operational data exchange between the system and an external monitoring center.

9. A valve island control box and pipe blockage early warning system based on an intelligent turbulence valve in a pneumatic ash conveying system according to claim 8, characterized in that, The communication gateway module is also used to record historical evolution data of the attenuation impedance ratio of high-frequency signals and to perform trend prediction of the deposition risk on the inner wall of the material transport channel using a deep learning model.

10. The valve island control box and pipe blockage early warning system based on an intelligent turbulence valve in a pneumatic ash conveying system according to claim 1, characterized in that, The physical parameter sensing module, logic mapping processing module, flow state attribute determination module, and execution control drive module are all integrated into the logic encapsulation module. The regulation execution module adopts a turbulence regulation unit and forms a local feedback control closed loop with the logic encapsulation module.

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