Efficient filtering, dedusting and mortar mixing integrated production system

Abstract

The invention discloses a high-efficiency filtering and dedusting mixed mortar integrated production system, and relates to the technical field of mixed mortar production, the high-efficiency filtering and dedusting mixed mortar integrated production system comprises an intelligent pre-separation filtering unit, and the intelligent pre-separation filtering unit is used for carrying out primary pre-separation on large-particle impurities and solid particles in raw materials; a double-layer rotational flow filter element with a self-cleaning function is arranged in the intelligent pre-separation filter unit, the outer layer of the double-layer rotational flow filter element is a wear-resistant ceramic coating, and the inner layer of the double-layer rotational flow filter element is made of an elastic polymer material. By designing the double-layer self-cleaning rotational flow filter element, the differential pressure self-adaptive filter screen dust removal unit and the online regenerated energy recovery device, the functions of full-process efficient dust removal and energy recovery are realized, the problems of large traditional dust removal resistance and energy waste are solved, the pressure difference is effectively reduced, the energy consumption is reduced, and the continuous online operation time is prolonged.

Description

Technical Field

[0001] The invention relates to the technical field of mixed mortar production, and in particular to a high-efficiency filtration and dust removal integrated mixed mortar production system. Background Art

[0002] As modern construction demands higher quality mortar and higher production efficiency, traditional dust removal and mortar preparation processes face technical bottlenecks such as incomplete dust control, resulting in high energy consumption, unstable mixing ratios, and frequent equipment maintenance.

[0003] Patent CN107020702B discloses a dry-mix mortar production equipment and process. The above patent effectively reduces the amount of dust generated during the production of dry-mix mortar, improves the working environment, and has a scientific and reasonable setting.

[0004] The above patent solves the technical problem in the prior art that pulse bag dust collectors are prone to bag clogging or upper mouth damage, but there is still room for improvement in the high energy consumption, unstable ratio and frequent equipment maintenance caused by incomplete dust control.

[0005] To this end, this application proposes an integrated production system for high-efficiency filtration and dust removal of mixed mortar, which can achieve high-efficiency dust removal and energy recovery functions throughout the entire process. Summary of the Invention

[0006] The purpose of the present invention is to provide an integrated production system for mortar mixing with high efficiency filtration and dust removal, so as to solve the technical problems raised in the above background technology, such as high energy consumption, unstable mixing ratio and frequent equipment maintenance caused by incomplete dust control.

[0007] To achieve the above objectives, the present invention provides the following technical solutions: an integrated production system for mortar mixing with high-efficiency filtration and dust removal, comprising an intelligent pre-separation filtration unit for primary pre-separation of large impurities and solid particles in raw materials, wherein a double-layer cyclone filter element with a self-cleaning function is provided inside the intelligent pre-separation filtration unit, wherein the outer layer of the double-layer cyclone filter element is a wear-resistant ceramic coating, and the inner layer is an elastic polymer material;

[0008] The intelligent pre-separation filter unit is connected to the differential pressure adaptive filter dust removal unit in the air path. The differential pressure adaptive filter dust removal unit is used to monitor the pressure difference before and after the filter online, and automatically adjust the back-blowing valve to achieve filter cleaning through the built-in micro-pressure sensor and closed-loop PID control algorithm.

[0009] The differential pressure adaptive filter dust removal unit is connected to an online regenerative energy recovery device, which is used to recover high-pressure gas energy during the backblowing process and convert it into micro-electricity or low-pressure gas for resupply through a high-pressure energy storage tank with adjustable flow and a variable geometry DC turbine generator set.

[0010] Preferably, the production system also includes an intelligent batching and mixing unit, which uses a multi-channel mass flow meter, online sensors for particle size and moisture content, and a dynamic proportioning algorithm to automatically adjust the feeding rates of cement, sand, water, and additives according to real-time detection data, and achieves homogeneous mixing through a dual-axis variable speed mixer and a programmable speed curve;

[0011] The twin-shaft variable speed mixer includes:

[0012] A pair of counter-rotating helical blades with exponentially varying root and tip widths to optimize shear stress distribution;

[0013] Adopting variable frequency drive and torque feedback control, it can achieve stepless speed regulation in the range of 0-300rpm and automatically adjust the speed according to the real-time material viscosity;

[0014] Built-in fluid dynamics CFD simulation optimizes cavity shape to reduce dead zones and improve mixing uniformity.

[0015] Preferably, the production system further includes a central control and remote monitoring module, which further includes:

[0016] A fault self-diagnosis algorithm module based on a combination of convolutional neural networks and time-series LSTM performs multi-dimensional heterogeneous feature extraction and fault type prediction on differential pressure sensor, vibration sensor, and temperature sensor data;

[0017] Automatic pre-maintenance scheduling submodule: When the predicted failure probability exceeds the set threshold, it generates a maintenance work order with priority and pushes it through the device touch screen and mobile app;

[0018] The post-maintenance feedback learning mechanism compares the actual maintenance results with the algorithm prediction results, automatically updates the model parameters and stores them in the local edge database.

[0019] Preferably, the intelligent pre-separation and filtration unit and the intelligent batching and mixing unit constitute an online raw material tracing and dynamic adjustment subsystem, including:

[0020] Optical particle size analysis sensor and moisture content sensor based on laser scattering principle are used to detect the particle size distribution and moisture content of sand and powder after pre-separation in real time;

[0021] RFID reader and QR code scanner, used to automatically obtain raw material batch, supplier and production date information, and establish a database associated with online inspection data;

[0022] The dynamic ratio adjustment algorithm adjusts the flow rate of each mass flow meter according to the deviation between real-time detection and target formula to achieve stable physical and chemical performance of the final mixture.

[0023] Preferably, the online regenerative energy recovery device includes:

[0024] A high-pressure accumulator tank with adjustable flow rate is used to store high-pressure gas during the back-blowing process;

[0025] A variable geometry DC turbine generator set connected to a high-pressure energy storage tank drives the turbine to generate electricity. The output electricity is fed back to the local microgrid or energy storage battery through a bidirectional inverter.

[0026] The energy management control module dynamically optimizes the venting timing and turbine speed curve according to the process load, high-pressure accumulator tank pressure and energy storage status, and automatically switches excess pressure to cooling or secondary dust removal cycles.

[0027] Preferably, the intelligent batching and mixing unit comprises:

[0028] Humidity detection module based on capacitive moisture sensor, used to monitor the moisture content of sand and powder in real time;

[0029] Humidity compensation control algorithm dynamically increases or decreases water injection volume according to the deviation between the detection value and the set value, and accurately injects water through a constant temperature water tank and a mass flow control valve;

[0030] The additive injection submodule includes a multi-channel peristaltic pump for injecting high-performance polymer modifiers or water reducers in proportion to formulation requirements.

[0031] Preferably, the central control and remote monitoring module further includes:

[0032] 10.1-inch industrial-grade touch screen HMI supports multiple user permissions, visual process flow charts, and real-time historical curve playback;

[0033] The cloud communication module based on the MQTT protocol securely encrypts production data and uploads it to the enterprise's private cloud big data platform for process optimization and quality traceability;

[0034] Mobile APP enables remote alarm push, production report viewing and online parameter modification.

[0035] Preferably, the PID control algorithm of the differential pressure adaptive filter dust removal unit includes:

[0036] An online estimation model based on the filter's accumulated dust load and operating time is used to calculate the optimal proportional, integral, and derivative gains in real time;

[0037] When filter performance degradation or inlet dust concentration fluctuations are detected, the gain scheduling module is automatically activated to achieve switching between fast response and smooth cleaning modes;

[0038] After the dust cleaning is completed, the historical operating data is used for self-calibration to eliminate model errors.

[0039] Preferably, the central control and remote monitoring module is equipped with an edge computing node and deploys a digital twin simulation platform. The edge computing node and the digital twin simulation platform include:

[0040] A real-time digital twin virtual machine built based on the system physical model and historical operating data is used to predict filter life, mixing quality and energy consumption;

[0041] The simulation engine, which runs in parallel with the actual system, performs "join-then" scenario simulations during production idle periods and feeds optimization suggestions back to the central control module.

[0042] Preferably, the production system further includes a safety interlock and emergency bypass subsystem, which includes:

[0043] Multiple level, temperature, pressure, and smoke safety sensors to monitor critical operating conditions;

[0044] Emergency bypass valve and bypass filter element, used to automatically switch the main filter path and switch to bypass mode when the safety threshold is exceeded to ensure the continuous operation of the production system;

[0045] The sound and light alarm and automatic shutdown program linked with the central control module are used to alert the operator and perform a safe shutdown in an emergency.

[0046] Compared with the prior art, the present invention has the following beneficial effects:

[0047] 1. This invention utilizes a double-layer self-cleaning cyclone filter, a differential pressure adaptive filter dust removal unit, and an online regenerative energy recovery device to achieve full-process efficient dust removal and energy recovery. This solves the problems of high resistance and energy waste in traditional dust removal, effectively reduces pressure differentials, reduces energy consumption, and extends continuous online operation time.

[0048] 2. This invention implements continuous health monitoring and intelligent maintenance functions by designing fault self-diagnosis and predictive maintenance, solving the problem of sudden failure and shutdown caused by many maintenance blind spots in traditional production systems, improving production reliability and reducing downtime;

[0049] 3. This invention is designed with online particle size and moisture content dual sensing detection, batch traceability and dynamic ratio compensation to achieve real-time raw material quality traceability and ratio stability, solve the problem of uneven finished product performance caused by large raw material fluctuations, ensure product consistency, and facilitate quality traceability;

[0050] 4. The present invention is designed with a dual-shaft variable-speed mixer to achieve intelligent mixing with high homogeneity and low dead zone, solving the problems of uneven mixing, multiple dead zones and overload risks, improving mixing uniformity, and reducing equipment wear and overload risks. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 This is a schematic diagram of the operation of the integrated production system of the present invention. DETAILED DESCRIPTION

[0052] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0053] In the description of the present invention, it should be noted that the terms "upper," "lower," "inner," "outer," "front end," "rear end," "both ends," "one end," "the other end," and the like, indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings and are intended solely to facilitate and simplify the description of the present invention. They are not intended to indicate or imply that the devices or components referred to must have, be constructed, or operate in a specific orientation, and therefore should not be construed as limiting the present invention. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0054] In the description of the present invention, it should be noted that, unless otherwise expressly specified or limited, the terms "installed," "provided with," "connected," etc., should be understood in a broad sense. For example, "connected" may refer to a fixed connection, a detachable connection, or an integral connection; it may refer to a mechanical connection or an electrical connection; it may refer to a direct connection or an indirect connection through an intermediate medium; it may refer to internal communication between two components. Those skilled in the art will be able to understand the specific meanings of the above terms in the present invention based on specific circumstances.

[0055] See also Figure 1 , the present invention provides an embodiment: an integrated production system for high-efficiency filtration and dust removal of mixed mortar, including an intelligent pre-separation filter unit, the intelligent pre-separation filter unit is used to perform primary pre-separation of large-particle impurities and solid particles in raw materials, and a double-layer cyclone filter element with a self-cleaning function is provided inside the intelligent pre-separation filter unit, the outer layer of the double-layer cyclone filter element is a wear-resistant ceramic coating, and the inner layer is made of an elastic polymer material;

[0056] The intelligent pre-separation filter unit is connected to the differential pressure adaptive filter dust removal unit in the air path. The differential pressure adaptive filter dust removal unit is used to monitor the pressure difference before and after the filter online, and automatically adjust the back-blowing valve to achieve filter cleaning through the built-in micro-pressure sensor and closed-loop PID control algorithm.

[0057] The differential pressure adaptive filter dust removal unit is connected to an online regenerative energy recovery device, which is used to recover the high-pressure gas energy during the back-blowing process and convert it into micro-electricity or low-pressure gas for resupply through a high-pressure energy storage tank with adjustable flow and a variable geometry DC turbine generator set;

[0058] The PID control algorithm of the differential pressure adaptive filter dust removal unit includes:

[0059] An online estimation model based on the filter's accumulated dust load and operating time is used to calculate the optimal proportional, integral, and derivative gains in real time;

[0060] When filter performance degradation or inlet dust concentration fluctuations are detected, the gain scheduling module is automatically activated to achieve switching between fast response and smooth cleaning modes;

[0061] After the dust cleaning is completed, the historical operating data is used for self-calibration to eliminate the model error;

[0062] Furthermore, the operator sets the recipe parameters for this production batch through the HMI interface, including the ratio of cement, sand, additives, and the target material moisture content. The central control module performs self-checks on each sensor and actuator in turn, and after confirming that the system is in normal condition by calling the fault self-diagnosis algorithm based on the vibration and temperature sensor data, the system enters the waiting state.

[0063] Bulk cement and sand enter the feed barrel of the intelligent pre-separation filter unit from the upper hopper. The materials rotate at high speed in the cyclonic field. Larger particles and metallic impurities are centrifugally thrown toward the outer wall and discharged from the bottom, completing the pre-separation of large particles. Every 10 minutes, the system automatically triggers a filter element self-cleaning cycle: A short period of high-pressure gas backwash removes adhering particles from the outer ceramic-coated filter element. Then, the inner elastic polymer filter element vibrates under the action of airflow pulses, further removing fine particles and ensuring low pressure drop during long-term operation.

[0064] The micro-pressure sensor collects the pressure difference data before and after the filter in real time and uploads it to the central control module. Based on the accumulated dust load and operating conditions of the filter, the system calls the online estimation model to calculate the current optimal PID proportional (P), integral (I) and differential (D) gains. If the pressure difference fluctuates due to the inlet dust concentration, the control algorithm automatically reduces the PID gain and switches to the "fast response mode", quickly opening the back-blowing valve. When the pressure difference rises steadily within the safe range, it switches to the "stable cleaning mode" to reduce the impact of back-blowing on downstream processes. The closed-loop PID output controls the opening and duration of the back-blowing valve to complete the filter cleaning. After the cleaning cycle is completed, the system compares the pressure difference change curve before and after this cleaning with the historical model data, automatically corrects the estimated model parameters, and eliminates the model error.

[0065] The high-pressure gas generated during the backblowing process enters the high-pressure accumulator tank with adjustable flow through a pipeline and maintains the set pressure inside; when the pressure in the accumulator tank reaches the preset upper limit or the system needs to supplement the low-pressure gas source and power supply, the variable geometry DC turbine generator set is started: the high-pressure gas is introduced into the turbine through the variable geometry throttling mechanism, driving the rotor to rotate at high speed to generate electricity; the generated electricity is incorporated into the system microgrid through a bidirectional inverter, or transmitted to a local lithium battery energy storage device; the energy management control module monitors the accumulator tank pressure and system load. If the turbine is not started temporarily, the exhaust residual pressure will be automatically switched to the next level of dust removal or pipeline cooling circuit for reuse.

[0066] See also Figure 1 The present invention provides an embodiment of an integrated production system for mortar mixing with high-efficiency filtration and dust removal, which also includes an intelligent batching and mixing unit. The system uses a multi-channel mass flow meter, online sensors for particle size and moisture content, and a dynamic proportioning algorithm to automatically adjust the feed rates of cement, sand, water, and additives based on real-time detection data, and achieves homogeneous mixing through a dual-axis variable-speed mixer and a programmable speed curve.

[0067] The twin-shaft variable speed mixer includes:

[0068] A pair of counter-rotating helical blades with exponentially varying root and tip widths to optimize shear stress distribution;

[0069] Adopting variable frequency drive and torque feedback control, it can achieve stepless speed regulation in the range of 0-300rpm and automatically adjust the speed according to the real-time material viscosity;

[0070] Built-in fluid dynamics CFD simulation optimizes cavity shape to reduce dead zones and improve mixing uniformity;

[0071] The intelligent batching and mixing unit includes:

[0072] Humidity detection module based on capacitive moisture sensor, used to monitor the moisture content of sand and powder in real time;

[0073] Humidity compensation control algorithm dynamically increases or decreases water injection volume according to the deviation between the detection value and the set value, and accurately injects water through a constant temperature water tank and a mass flow control valve;

[0074] Additive injection submodule, including a multi-channel peristaltic pump, used to inject high-performance polymer modifiers or water reducers in proportion to formulation requirements;

[0075] Furthermore, let the mass ratio of each component in the target formula be R target =[r c ,r s ,r w ,r a ], corresponding to cement, sand, water, and additives respectively. The total cumulative flow of the current silo detected online is M tot , and measure the current dosage of each component in real time M=[M c ,M s ,M w ,M a ]; Calculate the current actual ratio vector Deviation vector: ΔR = R target -R meas ; Define dynamic correction coefficient: K i =1+α·Δr i (i∈{c, s, w, a}), where α is the adjustment sensitivity; nominal feeding rate Set by the recipe, real-time feeding rate after correction The PLC controls the mass flow meter and peristaltic pump at this rate to achieve closed-loop flow control;

[0076] Assume that the real-time measured moisture content of sand / powder is H meas , target moisture content H target To compensate for the difference, additional water needs to be injected Among them, M dry =M c +M s +M a , ΔM w That is, additional water needs to be injected, and the PI controller is used to fine-tune the water injection rate: where e(t) = H target -H meas (t), K p , K i are proportional and integral gains respectively, and the control quantity u(t) is mapped to the mass flow valve opening to ensure the stable output of the constant temperature water tank;

[0077] For each additive channel, let the formula require the additive mass ratio r a , then at the current total output target M tot,targetNext, quality should be injected: Real-time monitoring of injected volume M a (t), controls the peristaltic pump speed w a for where w nom The nominal speed of the pump is limited to ensure a safe range;

[0078] Dual-Shaft Variable Speed Mixer Control:

[0079] Spiral blade parameters: root width w0, end width w L , transition exponentially: w(x) = w0e -βx / L , where L is the blade length and β controls the contraction rate; CFD wall optimization: according to the pre-established flow field simulation model, the cavity contraction angle and fillet radius are optimally combined to ensure that the dead zone volume is less than 2%; assuming that the slurry viscosity measured online is u meas , target viscosity u nom , the mixer speed N adopts power law adaptation: Among them, N nom is the nominal speed, γ is the viscosity sensitivity index; a torque sensor is installed on the mixer drive motor to measure the output torque τ in real time. If τ exceeds the threshold τ max , immediately reduce the speed proportionally: And trigger an alarm to prevent overload.

[0080] See also Figure 1 The present invention provides an embodiment of a high-efficiency filtration and dust removal integrated mortar production system, wherein the production system further includes a central control and remote monitoring module, which further includes:

[0081] A fault self-diagnosis algorithm module based on a combination of convolutional neural networks and time-series LSTM performs multi-dimensional heterogeneous feature extraction and fault type prediction on differential pressure sensor, vibration sensor, and temperature sensor data;

[0082] Automatic pre-maintenance scheduling submodule: When the predicted failure probability exceeds the set threshold, it generates a maintenance work order with priority and pushes it through the device touch screen and mobile app;

[0083] A post-maintenance feedback learning mechanism compares actual maintenance results with algorithm predictions, automatically updates model parameters, and stores them in the local edge database;

[0084] The central control and remote monitoring module further includes:

[0085] 10.1-inch industrial-grade touch screen HMI supports multiple user permissions, visual process flow charts, and real-time historical curve playback;

[0086] The cloud communication module based on the MQTT protocol securely encrypts production data and uploads it to the enterprise's private cloud big data platform for process optimization and quality traceability;

[0087] Mobile APP enables remote alarm push, production report viewing and online parameter modification;

[0088] The central control and remote monitoring module is equipped with edge computing nodes and deploys a digital twin simulation platform. The edge computing nodes and digital twin simulation platform include:

[0089] A real-time digital twin virtual machine built based on the system physical model and historical operating data is used to predict filter life, mixing quality and energy consumption;

[0090] A simulation engine running in parallel with the actual system performs "add-then" scenario simulations during production idle periods and feeds optimization suggestions back to the central control module;

[0091] Furthermore, the differential pressure sensor, vibration sensor, and temperature sensor upload their raw signals to the edge computing node via industrial Ethernet at a frequency of 100Hz. Fast filtering and normalization are performed at the edge node: 0.1-20Hz bandpass filtering is performed on the vibration and temperature signals, and a sliding average is performed on the differential pressure signal, which is then normalized to [-1, 1]. The vibration and temperature signals are concatenated into a two-dimensional "amplitude-time" matrix and input into a three-layer convolutional network (Conv1-Conv3). Each layer has a convolution kernel size of (3×1), a step size of 1, and 16, 32, and 64 channels, respectively, to extract short-term waveforms and local temperature fluctuation features. The Conv3 output is flattened into a sequence and input into two layers of LSTM (128 hidden units per layer). The output of the LSTM at the last moment passes through a fully connected layer and softmax to give the probability distribution of N types of faults (such as filter blockage, air valve stuck, sensor drift, etc.). θ is set to 0.7. When the probability of any fault category is greater than θ, an alarm for that category is determined, and the confidence level at that moment and the fault trend at the next moment are also output.

[0092] After receiving the fault category and trend, the scheduling submodule generates a maintenance work order according to the priority mapping table:

[0093] For example, a stuck damper (high priority), sensor drift (medium priority), or clogged filter (low priority), the work order includes the device ID, fault description, recommended maintenance action, and a list of required spare parts. This process triggers a pop-up alert on the HMI touch screen and simultaneously calls the MQTT client to push the work order in JSON format to a subscribed topic on the mobile app. The app then displays the work order in the "pending work order" list and alerts maintenance personnel via local notifications.

[0094] Maintenance personnel fill in maintenance results, the market used, the actual cause of the fault, and other information in the app. The app then transmits the results back to the edge database via the HTTPS interface. The edge node regularly annotates the maintenance results to the original samples to form a new training set. It then performs small-batch gradient descent to fine-tune the convolution and LSTM network weights. The updated model immediately replaces the old one without downtime. The 10.1-inch industrial-grade touch screen main interface displays the production flow chart, with real-time scrolling and highlighting of the current unit status. Clicking on any unit expands the unit's historical curve and supports playback to any point in time.

[0095] A simulation environment identical to the physical system is deployed on the edge server, real-time operating parameters are input, and the simulation status is updated at a frequency of 5Hz. Predictive indicators are output, including remaining filter life, mixing uniformity, and energy consumption per unit of output. "What if" simulation tasks are automatically triggered during daily "shift intervals" or "system standby": for example, "Increasing backflush frequency by 30% will result in a change in filter life"; "Reducing mixing speed by 20% will result in a change in energy consumption and uniformity"; a simulation report is generated, and optimization suggestions are issued through the HMI and app, such as adjusting the cleaning cycle or modifying the speed curve.

[0096] See also Figure 1 The present invention provides an embodiment of an integrated production system for high-efficiency filtration and dust removal of mortar, wherein the intelligent pre-separation and filtration unit and the intelligent batching and mixing unit constitute an online raw material tracing and dynamic adjustment subsystem, including:

[0097] Optical particle size analysis sensor and moisture content sensor based on laser scattering principle are used to detect the particle size distribution and moisture content of sand and powder after pre-separation in real time;

[0098] RFID reader and QR code scanner, used to automatically obtain raw material batch, supplier and production date information, and establish a database associated with online inspection data;

[0099] Dynamic ratio adjustment algorithm, based on real-time detection and target formula deviation, adjusts the flow rate of each mass flow meter to compensate, achieving stable final mixed physical and chemical performance;

[0100] Furthermore, before production, the optical particle size analysis sensor is calibrated using standard particle size samples, and the calibration curve is stored in the edge database. The laser heat dissipation moisture content sensor is calibrated using deionized water and a medium with a known moisture content to generate a moisture content-scattering intensity mapping table. RFID tags are affixed to the outside of the raw material bag, and the QR code is printed on the packaging. Before loading, the operator brings both tags close to the reading position. The system automatically collects the batch number, supplier code, production date, and raw material type. This information, along with a timestamp, is written into the raw material batch association table.

[0101] After the large particles are initially removed by the intelligent pre-separation filtration unit, the continuous material flow is led to the detection chamber through the bypass sampling pipe. The detection chamber is equipped with a high-speed camera and light source. The material passes through the narrow flow channel at a constant speed. The camera captures 1000fps video frames. The image processing unit extracts the particle outline in real time, calculates the particle diameter distribution, and outputs the particle size distribution vector:

[0102] d=[p<75um,p75-150um,p150-300um,p>300um]

[0103] Where p represents the proportion of particles in each interval;

[0104] The laser scattering probe is connected in parallel to the flow channel outlet to measure the backscattered light intensity I, which is converted into the moisture content H according to the pre-calibrated mapping table. meas Each test result {D,} is associated with the current sampling time and the corresponding batch information through BatchID and written into the "online test log table";

[0105] Obtain the target particle size distribution Dtarget and target moisture content Htarget of this batch from the central controller, calculate the particle size deviation: ΔD=Dtarget-D, and obtain the deviation vector ΔD=[Δp1,Δp2,Δp3,Δp4] in the four-speed interval; for the sand channel, assume the original nominal flow rate is Determine the compensation focus based on the maximum deviation gear: K s =1+β·max(|Δp i |), where β is the compensation factor. The cement powder and additive channels are calculated in the same way. However, when the moisture content deviation ΔH = Htarget - Hmeas exceeds 1%, the water flow channel is adjusted preferentially using the humidity compensation algorithm, and no major adjustments are made to the particle size channel. Sampling is performed again every 5 minutes. If both the particle size and moisture content deviations are below the preset thresholds, the adjustment is considered complete. Otherwise, the cycle is repeated until the target is met.

[0106] See also Figure 1 The present invention provides an embodiment of a high-efficiency filtration and dust removal integrated mortar production system, wherein the online regenerative energy recovery device comprises:

[0107] A high-pressure accumulator tank with adjustable flow rate is used to store high-pressure gas during the back-blowing process;

[0108] A variable geometry DC turbine generator set connected to a high-pressure energy storage tank drives the turbine to generate electricity. The output electricity is fed back to the local microgrid or energy storage battery through a bidirectional inverter.

[0109] The energy management control module dynamically optimizes the bleed timing and turbine speed curve based on process load, high-pressure accumulator tank pressure, and energy storage status, and automatically switches excess pressure to cooling or secondary dust removal cycles;

[0110] Furthermore, after the differential pressure dust removal unit completes the backflush, the high-pressure gas is led to the high-pressure energy storage tank through the pipeline, and the air inlet valve is adjusted to 0.5m 3 / min rate until the tank pressure reaches 0.9MPa or the back-blowing gas source ends; when the tank pressure reaches 0.9MPa, the air inlet valve automatically adjusts to maintain constant pressure; if the pressure exceeds 1.1MPa, the safety relief valve opens and discharges to the secondary dust removal circuit; when the pressure is lower than 0.7MPa, the system stops discharging air to the generator and prioritizes retaining the pressure for the next back-blowing; EMCM evaluates every 10s: if the tank pressure is ≥0.85MPa and the local microgrid load is ≥5kW, or the battery SOC is ≤80%, then power generation is started; otherwise, energy storage is maintained on standby, waiting for a better opportunity; when generating electricity, EMCM is based on the real-time tank pressure P tank and target power generation P req Calculate the optimal nozzle opening angle θ: θ = θ min +(θ max -θ min )×P req / P rated ; where =θ min 10°, θ max =70°, P rated =50kW, and set the rotor target speed N at the same time req =P req / k r P tank , where k r is the empirical torque coefficient;

[0111] The turbine guide air drives the generator to reach N req The generator outputs electrical energy through a bidirectional inverter: if the local load demand is higher than the current generated power, the excess energy is used to charge the battery first; if the local load is lower than the generated power, the excess energy is fed into the local microgrid at full power; when the tank pressure drops to 0.75MPa, the EMCM determines whether to continue generating electricity: if continuing to generate electricity will reduce the tank pressure to the lower limit, then power generation will be stopped; after power generation stops, if there is still residual pressure in the pipeline, the bypass valve will automatically open to introduce high-pressure gas into the cooling coil or secondary dust removal unit to achieve secondary utilization of the residual pressure.

[0112] See also Figure 1 The present invention provides an embodiment of a high-efficiency filtration and dust removal integrated mortar production system, wherein the production system further includes a safety interlock and emergency bypass subsystem, the safety interlock and emergency bypass subsystem including:

[0113] Multiple level, temperature, pressure, and smoke safety sensors to monitor critical operating conditions;

[0114] Emergency bypass valve and bypass filter element, used to automatically switch the main filter path and switch to bypass mode when the safety threshold is exceeded to ensure the continuous operation of the production system;

[0115] Sound and light alarms and automatic shutdown procedures linked to the central control module are used to alert operators and perform safe shutdowns in emergency situations;

[0116] Furthermore, capacitive liquid level sensors were selected and installed inside the high-pressure accumulator tank and the constant temperature water tank respectively. PT100 platinum resistance temperature probes were placed on the outlet pipe of the differential pressure dust removal unit and on the outer wall of the mixer cavity. An intelligent differential pressure transmitter was used to measure the pressure difference before and after the filter. A high-pressure absolute pressure sensor was used for the accumulator tank. Photoelectric smoke alarms were installed on the top of the main engine room and near the inlet and outlet air ducts.

[0117] Operation process and switching sequence:

[0118] The central controller scans the signals from each of the above sensors at a frequency of 1Hz to assess the safety status. If any safety parameter exceeds the alarm threshold, the controller issues a bypass switching command: 1. Close the main filter valve; 2. Delay 100ms to ensure the main valve is closed; 3. Open the bypass valve; 4. The bypass filter element starts working to ensure that the gas continues to remove dust; At the same time, the audible and visual alarms are activated, and the "Emergency Bypass Activated" prompt pops up on the HMI screen;

[0119] If a serious new sensor is detected, the controller immediately:

[0120] Close all feed valves;

[0121] Disconnect the backflush and mixer drive;

[0122] Keep the bypass open to prevent overpressure inside the equipment;

[0123] Issue the highest level of sound and light alarm and lock the operation interface;

[0124] After the emergency is eliminated, the operator executes the "bypass homing" command on the HMI:

[0125] Close the bypass valve; open the main filter valve; the system automatically performs a 30-second self-test to confirm that the differential pressure, water level, temperature, and smoke are normal; resume normal production and automatically clear the alarm record;

[0126] Data recording and subsequent analysis: recording sensor type, measurement value, trigger time and action sequence;

[0127] The system status is automatically captured each time the bypass is switched, including the remaining life and energy consumption predicted by the model; the operation and maintenance team initiates a simulated accident every quarter to verify the response time of the bypass valve and the effectiveness of the shutdown procedure.

[0128] The safety threshold and interlock logic are shown in the following table 1 logic table

[0129] Table 1 Logic table

[0130]

[0131] Working principle: Through the intelligent pre-separation filter unit, the double-layer cyclone filter element is used to remove large particles and foreign matter. The filter element is periodically backflushed and vibrated to clean the dust to maintain low resistance.

[0132] The differential pressure before and after the filter is detected in real time by a micro-pressure sensor. The closed-loop PID adaptively adjusts the gain according to the dust load and duration, ensuring fast or smooth dust removal. The back-blown exhaust gas enters the high-pressure accumulator tank, and then generates electricity through the variable geometry turbine. The excess pressure can be returned to the cooling system or for secondary dust removal.

[0133] Multi-channel mass flow meters and particle size and moisture content sensors are used for online detection, and a dynamic proportioning algorithm compensates the feed ratio in real time. The dual-axis variable-speed mixer combines CFD-optimized cavity and viscosity-adaptive speed to achieve highly homogeneous mixing. The central control module integrates fault self-diagnosis, predictive maintenance, digital twin simulation, and remote monitoring, achieving closed-loop optimization of the entire process.

[0134] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above and that the invention can be embodied in other specific forms without departing from the spirit or essential characteristics of the invention. Therefore, the embodiments should be considered in all respects as illustrative and non-restrictive, and the scope of the invention is defined by the appended claims, not the foregoing description, and all variations within the meaning and range of equivalents of the claims are intended to be included therein. Any reference sign in a claim should not be construed as limiting the claim to which it relates.

Claims

1. An integrated production system for high-efficiency filtration and dust removal of mixed mortar, including an intelligent pre-separation filtration unit, characterized by: The intelligent pre-separation filter unit is used to perform primary pre-separation of large impurities and solid particles in the raw materials. A double-layer cyclone filter element with a self-cleaning function is provided inside the intelligent pre-separation filter unit. The outer layer of the double-layer cyclone filter element is a wear-resistant ceramic coating, and the inner layer is an elastic polymer material; The intelligent pre-separation filter unit is connected to the differential pressure adaptive filter dust removal unit in the air path. The differential pressure adaptive filter dust removal unit is used to monitor the pressure difference before and after the filter online, and automatically adjust the back-blowing valve to achieve filter cleaning through the built-in micro-pressure sensor and closed-loop PID control algorithm. The differential pressure adaptive filter dust removal unit is connected to an online regenerative energy recovery device, which is used to recover high-pressure gas energy during the backblowing process and convert it into micro-electricity or low-pressure gas for resupply through a high-pressure energy storage tank with adjustable flow and a variable geometry DC turbine generator set.

2. The high-efficiency filtration and dust removal integrated mortar production system according to claim 1 is characterized in that: The production system also includes an intelligent batching and mixing unit, which uses a multi-channel mass flow meter, online sensors for particle size and moisture content, and a dynamic proportioning algorithm to automatically adjust the feed rates of cement, sand, water, and additives based on real-time detection data, and achieves homogeneous mixing through a dual-shaft variable-speed mixer and a programmable speed curve. The twin-shaft variable speed mixer includes: A pair of counter-rotating helical blades with exponentially varying root and tip widths to optimize shear stress distribution; Adopting variable frequency drive and torque feedback control, it can achieve stepless speed regulation in the range of 0-300rpm and automatically adjust the speed according to the real-time material viscosity; Built-in fluid dynamics CFD simulation optimizes cavity shape to reduce dead zones and improve mixing uniformity.

3. The high-efficiency filtration and dust removal integrated mortar production system according to claim 1 is characterized in that: The production system further includes a central control and remote monitoring module, which further includes: A fault self-diagnosis algorithm module based on a combination of convolutional neural networks and time-series LSTM performs multi-dimensional heterogeneous feature extraction and fault type prediction on differential pressure sensor, vibration sensor, and temperature sensor data; Automatic pre-maintenance scheduling submodule: When the predicted failure probability exceeds the set threshold, it generates a maintenance work order with priority and pushes it through the device touch screen and mobile app; The post-maintenance feedback learning mechanism compares the actual maintenance results with the algorithm prediction results, automatically updates the model parameters and stores them in the local edge database.

4. The high-efficiency filtration and dust removal integrated mortar production system according to claim 1 is characterized in that: The intelligent pre-separation and filtration unit and the intelligent batching and mixing unit constitute an online raw material traceability and dynamic adjustment subsystem, including: Optical particle size analysis sensor and moisture content sensor based on laser scattering principle are used to detect the particle size distribution and moisture content of sand and powder after pre-separation in real time; RFID reader and QR code scanner, used to automatically obtain raw material batch, supplier and production date information, and establish a database associated with online inspection data; The dynamic ratio adjustment algorithm adjusts the flow rate of each mass flow meter according to the deviation between real-time detection and target formula to achieve stable physical and chemical performance of the final mixture.

5. The high-efficiency filtration and dust removal integrated mortar production system according to claim 1 is characterized in that: The online regenerative energy recovery device comprises: A high-pressure accumulator tank with adjustable flow rate is used to store high-pressure gas during the back-blowing process; A variable geometry DC turbine generator set connected to a high-pressure energy storage tank drives the turbine to generate electricity. The output electricity is fed back to the local microgrid or energy storage battery through a bidirectional inverter. The energy management control module dynamically optimizes the venting timing and turbine speed curve according to the process load, high-pressure accumulator tank pressure and energy storage status, and automatically switches excess pressure to cooling or secondary dust removal cycles.

6. The high-efficiency filtration and dust removal integrated mortar production system according to claim 2, characterized in that: The intelligent batching and mixing unit includes: Humidity detection module based on capacitive moisture sensor, used to monitor the moisture content of sand and powder in real time; Humidity compensation control algorithm dynamically increases or decreases water injection volume according to the deviation between the detection value and the set value, and accurately injects water through a constant temperature water tank and a mass flow control valve; The additive injection submodule includes a multi-channel peristaltic pump for injecting high-performance polymer modifiers or water reducers in proportion to formulation requirements.

7. The high-efficiency filtration and dust removal integrated mortar production system according to claim 3 is characterized by: The central control and remote monitoring module further includes: 10.1-inch industrial-grade touch screen HMI supports multiple user permissions, visual process flow charts, and real-time historical curve playback; The cloud communication module based on the MQTT protocol securely encrypts production data and uploads it to the enterprise's private cloud big data platform for process optimization and quality traceability; Mobile APP enables remote alarm push, production report viewing and online parameter modification.

8. The high-efficiency filtration and dust removal integrated mortar production system according to claim 1 is characterized in that: The PID control algorithm of the differential pressure adaptive filter dust removal unit includes: An online estimation model based on the filter's accumulated dust load and operating time is used to calculate the optimal proportional, integral, and derivative gains in real time; When filter performance degradation or inlet dust concentration fluctuations are detected, the gain scheduling module is automatically activated to achieve switching between fast response and smooth cleaning modes; After the dust cleaning is completed, the historical operating data is used for self-calibration to eliminate model errors.

9. The high-efficiency filtration and dust removal integrated mortar production system according to claim 3, characterized in that: The central control and remote monitoring module is equipped with edge computing nodes and deploys a digital twin simulation platform. The edge computing nodes and digital twin simulation platform include: A real-time digital twin virtual machine built based on the system physical model and historical operating data is used to predict filter life, mixing quality and energy consumption; The simulation engine, running in parallel with the actual system, performs "add-then" scenario simulations during production idle periods and feeds optimization suggestions back to the central control module.

10. The high-efficiency filtration and dust removal integrated mortar production system according to claim 1, characterized in that: The production system further includes a safety interlock and emergency bypass subsystem, which includes: Multiple level, temperature, pressure, and smoke safety sensors to monitor critical operating conditions; Emergency bypass valve and bypass filter element, used to automatically switch the main filter path and switch to bypass mode when the safety threshold is exceeded to ensure the continuous operation of the production system; The sound and light alarm and automatic shutdown program linked with the central control module are used to alert the operator and perform a safe shutdown in an emergency.

Images