A high-efficiency integrated production system for filtration and dust removal of mortar

Abstract

This invention discloses a high-efficiency integrated dust removal and filtration system for mixed mortar production, relating to the field of mixed mortar production technology. It includes an intelligent pre-separation filtration unit for primary pre-separation of large particulate impurities and solid particles in raw materials. The intelligent pre-separation filtration unit internally incorporates a self-cleaning double-layer cyclone filter element. The outer layer of the double-layer cyclone filter element has a wear-resistant ceramic coating, and the inner layer is made of an elastic polymer material. This invention, through the design of a double-layer self-cleaning cyclone filter element, a differential pressure adaptive filter dust removal unit, and an online regeneration energy recovery device, achieves high-efficiency dust removal and energy recovery throughout the entire process. It solves the problems of high resistance and energy waste in traditional dust removal systems, effectively reducing pressure differential, energy consumption, and extending continuous online operation time.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of mortar production, in particular to an efficient filtering and dedusting mortar integrated production system. BACKGROUND

[0002] With the continuous improvement of the requirements of modern building construction on mortar quality and production efficiency, the traditional dust removal and mortar preparation links have the technical bottlenecks of high energy consumption, unstable proportioning and frequent equipment maintenance caused by incomplete dust control.

[0003] Patent CN107020702B discloses a dry mortar production equipment and process, which effectively reduces the dust amount generated during dry mortar production, improves the working environment and is scientifically and reasonably arranged.

[0004] The above patent solves the technical problem of the phenomenon of bag blocking or upper opening damage of the pulse bag dust collector in the prior art, but there is still optimization space for the high energy consumption, unstable proportioning and frequent equipment maintenance caused by incomplete dust control.

[0005] Therefore, the application provides an efficient filtering and dedusting mortar integrated production system which can realize efficient dust removal and energy recovery functions in the whole process. SUMMARY

[0006] The application aims to provide an efficient filtering and dedusting mortar integrated production system to solve the technical problems of high energy consumption, unstable proportioning and frequent equipment maintenance caused by incomplete dust control in the background technology.

[0007] To achieve the above-mentioned purpose, the application provides the following technical scheme: an efficient filtering and dedusting mortar integrated production system, comprising an intelligent pre-separation filtering unit, the intelligent pre-separation filtering unit is used for primary pre-separation of large-particle impurities and solid particles in raw materials, a double-layer cyclone filter core with a self-cleaning function is arranged inside the intelligent pre-separation filtering unit, the outer layer of the double-layer cyclone filter core is a wear-resistant ceramic coating, and the inner layer is an elastic polymer material;

[0008] The intelligent pre-separation filtering unit is connected with a differential pressure self-adaptive filter screen dust removal unit in an air path, the differential pressure self-adaptive filter screen dust removal unit is used for online monitoring of the pressure difference before and after the filter screen, and the filter screen ash removal is realized through automatic adjustment of the back-blowing valve by the built-in micro-pressure sensor and the closed-loop PID control algorithm;

[0009] The differential pressure self-adaptive filter screen dust removal unit is connected with an online regeneration energy recovery device, the online regeneration energy recovery device is used for recovering the high-pressure gas energy in the back-blowing process, and the micro-electric energy or low-pressure gas is returned through the adjustable-flow high-pressure energy storage tank and the variable-geometry direct-current turbine generator set.

[0010] Preferably, the production system further comprises an intelligent batching and mixing unit, which adopts a multi-channel mass flow meter, an on-line particle size and moisture content sensor, and a dynamic proportioning algorithm to automatically adjust the feeding rate of cement, sand, water, and additives according to real-time detection data, and realizes homogeneous mixing through a dual-shaft variable-speed mixer and a programmable speed curve.

[0011] The dual-shaft variable-speed mixer comprises:

[0012] A pair of counter-rotating helical blades with an exponentially changing blade root width and end width to optimize shear stress distribution;

[0013] Variable frequency drive and torque feedback control are adopted to realize stepless speed regulation in the range of 0-300 rpm, and the speed is automatically adjusted according to the real-time material viscosity;

[0014] The cavity shape is optimized by built-in fluid mechanics CFD simulation to reduce dead zones and improve mixing uniformity.

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

[0016] A fault self-diagnosis algorithm module based on the combination of convolutional neural network 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] An automatic preventive maintenance scheduling sub-module generates a maintenance work order with priority and pushes it through the device touch screen and mobile APP when the predicted failure probability exceeds the set threshold;

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

[0019] Preferably, the intelligent pre-separation filtering unit and the intelligent batching and mixing unit form an on-line raw material tracing and dynamic adjustment subsystem, which comprises:

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

[0021] An RFID reading device and a two-dimensional code scanning device are used to automatically obtain raw material batch, supplier, and production date information, and establish an associated database with on-line detection data;

[0022] A dynamic proportioning adjustment algorithm adjusts the flow rate of each mass flow meter to compensate for the deviation from the target formula based on real-time detection, so as to realize stable physical and chemical properties of the final mixture.

[0023] Preferably, the online regeneration energy recovery device comprises:

[0024] A high-pressure energy storage tank with adjustable flow rate for storing high-pressure gas during the back-blowing process;

[0025] A variable-geometry direct-current turbine generator set connected to the high-pressure energy storage tank, which drives the turbine to generate electricity, and the output power is fed back to the local micro-grid or energy storage battery through a bidirectional inverter;

[0026] An energy management control module that dynamically optimizes the gas release timing and turbine speed curve according to the process load, high-pressure energy storage tank pressure, and energy storage state, and automatically switches excess pressure to cooling or secondary dust removal circulation.

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

[0028] A humidity detection module based on a capacitance type moisture content sensor for real-time monitoring of sand and powder moisture content;

[0029] A humidity compensation control algorithm that dynamically increases or decreases the water injection amount according to the deviation between the detected value and the set value, and precisely injects through a thermostatic water tank and a mass flow control valve;

[0030] An additive injection sub-module, including a multi-channel peristaltic pump, for proportionally injecting high-performance polymer modifiers or water-reducing agents according to the formulation requirements.

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

[0032] A 10.1-inch industrial-grade touch screen HMI supporting multi-user permissions, visual process flowcharts, and real-time historical curve playback;

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

[0034] A mobile APP for remote alarm push, production report viewing, and online parameter modification.

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

[0036] An online estimation model based on the cumulative dust load of the filter and the running time for real-time calculation of the optimal proportional, integral, and derivative gains;

[0037] When the filter performance degradation or inlet dust concentration fluctuation is detected, the gain scheduling module is automatically started to realize the switching between fast response and smooth ash removal modes;

[0038] After the dust cleaning is completed, historical working condition 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, and the edge computing node and the digital twin simulation platform comprise:

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

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

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

[0043] Multi-point liquid level, temperature, pressure and smoke safety sensors for monitoring critical working conditions;

[0044] Emergency bypass valves and bypass filter cartridges for automatically switching the main filter path and switching to bypass mode when safety thresholds are exceeded to ensure continuous operation of the production system;

[0045] An audible and visual alarm and automatic shutdown program linked to the central control module for prompting operators and performing safety shutdown in emergency situations.

[0046] Compared with the prior art, the present application has the following advantages:

[0047] 1. The present application realizes efficient dust removal and energy recovery functions throughout the process by designing double-layer self-cleaning cyclone filter cartridges, differential pressure self-adaptive filter screen dust removal units and online regeneration energy recovery devices, solves the problems of high resistance and energy waste in traditional dust removal, effectively reduces the pressure difference and energy consumption, and prolongs the continuous online running time;

[0048] 2. The present application realizes continuous health monitoring and intelligent maintenance functions by designing fault self-diagnosis and preventive maintenance, solves the problem of sudden failure shutdown caused by many blind spots in traditional production system maintenance, improves production reliability and reduces downtime;

[0049] 3. The present application realizes real-time raw material quality traceability and stable proportioning by designing online particle size and moisture content double-sensing detection, batch traceability and dynamic proportioning compensation, solves the problem of uneven product performance caused by large raw material fluctuations, ensures product consistency and facilitates quality traceability;

[0050] 4. The application realizes intelligent stirring with high homogeneity and low dead zone by designing a double-shaft variable-speed mixer, solves uneven stirring, many dead zones and overload risk, improves mixing uniformity, and reduces equipment wear and overload risk. BRIEF DESCRIPTION OF DRAWINGS

[0051] Figure 1 It is an integrated production system operation schematic diagram of the application. DETAILED DESCRIPTION

[0052] The technical solutions in the embodiments of the application will be clearly and completely described below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are only part of the embodiments of the application, rather than all the embodiments of the application. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative work belong to the protection scope of the application.

[0053] In the description of the application, it should be noted that the terms "upper", "lower", "inner", "outer", "front end", "rear end", "two ends", "one end", "the other end" and the like indicate the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the application and simplifying the description, and do not indicate or imply that the devices or elements referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as a limitation on the application. In addition, the terms "first" and "second" are only for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0054] In the description of the application, it should be noted that unless otherwise explicitly specified and limited, the terms "mounting", "provided with", "connection" and the like should be understood broadly, for example, "connection" can be fixed connection, can also be detachable connection, or integral connection; can be mechanical connection, can also be electrical connection; can be direct connection, can also be indirect connection through an intermediate medium, can be the communication inside two elements. For those skilled in the art, the specific meaning of the above terms in the application can be understood according to the specific circumstances.

[0055] Please refer to Figure 1 , the application provides an embodiment: an efficient filtering and dust removing sand mixing mortar integrated production system, comprising an intelligent pre-separation filtering unit, the intelligent pre-separation filtering unit is used for primary pre-separation of large particle impurities and solid particles in raw materials, a double-layer cyclone filter core with self-cleaning function is arranged in the intelligent pre-separation filtering unit, the outer layer of the double-layer cyclone filter core is wear-resistant ceramic coating, and the inner layer is elastic polymer material;

[0056] The intelligent pre-separation filter unit is connected with an air path of a differential pressure self-adaptive filter screen dust removal unit, the differential pressure self-adaptive filter screen dust removal unit is used for monitoring pressure difference before and after the filter screen online, and automatically adjusts a back blowing valve through a built-in micro pressure sensor and a closed loop PID control algorithm to realize filter screen ash removal;

[0057] The differential pressure self-adaptive filter screen dust removal unit is connected with an online regeneration energy recovery device, the online regeneration energy recovery device is used for recovering high pressure gas energy in the back blowing process, and converts micro electric energy or low pressure gas back supply through an adjustable flow high pressure energy storage tank and a variable geometry direct current turbine generator set;

[0058] The PID control algorithm of the differential pressure self-adaptive filter screen dust removal unit comprises:

[0059] An online estimation model based on accumulated dust load of the filter screen and running time is used for real-time calculation of optimal proportional, integral and differential gain;

[0060] When filter screen performance degradation or inlet dust concentration fluctuation is detected, a gain scheduling module is automatically started to realize switching between fast response and smooth ash removal modes;

[0061] After ash removal is completed, historical working condition data is used for self-calibration to eliminate model error;

[0062] Further, an operator sets formula parameters of the current production batch through an HMI interface, including cement, sand and additive proportions and target material moisture content, a central control module performs self-checking on each sensor and actuator in turn, and a fault self-diagnosis algorithm is called through vibration and temperature sensor data to confirm that the system state is normal, and then the system enters a material waiting state;

[0063] Bulk cement and sand material enter a feeding cylinder of the intelligent pre-separation filter unit from a feeding hopper, the material is high-speed rotated in a cyclone field, large particles and metal impurities are thrown to the outer wall and discharged from the bottom due to centrifugal effect, and pre-separation of large particles is completed; every 10 minutes, the system automatically triggers a filter core self-cleaning cycle: the surface of an outer ceramic coating filter core is stripped of adhered particles by means of short time high pressure gas back flushing; then an inner elastic polymer filter core vibrates under the action of air flow pulse to further clear fine particles, and low pressure drop under long-term operation is ensured;

[0064] The micro pressure sensor collects the pressure difference data before and after the filter screen in real time and uploads the central control module. The system calls the online estimation model based on the cumulative dust load and operation market of the filter screen, calculates the current optimal PID proportion (P), integral (I) and differential (D) gain; if the inlet dust concentration fluctuation leads to a sudden rise in pressure difference, the control algorithm automatically reduces the PID gain and switches to the "fast response mode", quickly opens the blowback valve; when the pressure difference rises smoothly within the safety range, switch to the "smooth ash removal mode" to reduce the impact of blowback on the downstream process; the closed-loop PID output controls the blowback valve opening degree and duration to complete the filter screen ash removal; after the ash removal cycle is completed, the system compares the pressure difference change curve before and after this ash removal with the historical model data, automatically corrects the estimation model parameters, and removes the model error;

[0065] The high-pressure gas generated during the blowback process enters the adjustable-flow high-pressure energy storage tank through the pipeline and maintains a set pressure inside; when the energy storage tank pressure reaches the preset upper limit or the system needs to supplement the low-pressure gas source and power supply, the variable-geometry direct-current turbogenerator set is started: high-pressure gas is introduced into the turbine through the variable-geometry throttling mechanism to drive the rotor to rotate at high speed to generate electricity; the generated electric energy is connected to the system micro-grid through the bidirectional inverter, or is transmitted to the local lithium battery energy storage device; the energy management control module monitors the energy storage tank pressure and system load, and if the turbine is not started, the exhaust residual pressure is automatically switched to the next stage of dust removal or the pipeline cooling circuit for repeated use.

[0066] Please refer to Figure 1 An embodiment provided by the application: an efficient filter dust removal and sand slurry integrated production system, the production system further comprises an intelligent batching and mixing unit, adopts a multi-channel mass flowmeter, a particle size and moisture content online sensor and a dynamic proportioning algorithm, automatically adjusts the feeding rate of cement, sand, water and additives according to real-time detection data, and realizes homogeneous mixing through a dual-shaft variable-speed mixer and a programmable speed curve;

[0067] The dual-shaft variable-speed mixer comprises:

[0068] A pair of reverse helical blades, the blade root width and the end width change exponentially to optimize the shear stress distribution;

[0069] Frequency conversion driving and torque feedback control are adopted to realize stepless speed regulation in the range of 0-300 rpm, and the speed is automatically adjusted according to the real-time material viscosity;

[0070] The built-in fluid mechanics CFD simulation optimizes the cavity shape to reduce the dead zone and improve the mixing uniformity;

[0071] The intelligent batching and mixing unit comprises:

[0072] A humidity detection module based on a capacitive moisture content sensor is used to monitor the moisture content of sand and powder in real time;

[0073] The humidity compensation control algorithm dynamically increases or decreases the water injection amount according to the deviation of the detection value and the set value, and precisely injects water through the constant temperature water tank and the mass flow control valve;

[0074] The additive injection sub-module includes a multi-channel peristaltic pump for proportionally injecting high-performance polymer modifiers or water reducing agents according to the formulation requirements;

[0075] Further, the mass ratio of each component in the target formulation is R target =[r c ,r s ,r w ,r a ], respectively corresponding to cement, sand, water, and additives, the total cumulative flow of the current silo is detected online as M tot , and the current component quantities M c , M s , M w , and M a are measured in real time; the current actual proportioning vector is calculated as The deviation vector is ΔR=R target -R meas ; the dynamic correction coefficient K i =1+α·Δr i (i∈{c,s,w,a}) is defined, where α is the adjustment sensitivity; the nominal feeding rate is The real-time feeding rate after correction is determined according to the formulation setting The mass flow meter and the peristaltic pump are controlled at this rate in the PLC to achieve closed-loop flow control;

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

[0077] For each additive channel, let the formulation require additive mass ratio r a , then the current total output target M tot,targetThe amount of injection should be noted: Real-time monitoring of the amount of injection M a (t), control the peristaltic pump rate w a For Where w nom is the nominal speed of the pump, and the safety range is ensured by amplitude limiting;

[0078] Double-shaft variable-speed mixer control:

[0079] Screw blade parameters: root width w0, end width w L , exponential transition: w(x) = w0e -βx / L , where L is the length of the blade, and β controls the shrinkage rate; CFD optimization wall: according to the pre-established flow field simulation model, the optimal combination of cavity shrinkage angle and round corner radius is adopted to ensure that the dead volume is <2%; the online measured slurry viscosity is u meas , the target viscosity u nom , and the mixer speed N is adaptively powered by a power law: Where, N nom is the nominal speed, and 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, and if τ exceeds the threshold τ max , the speed is immediately reduced by a certain proportion: And trigger an alarm to prevent overload.

[0080] Please refer to Figure 1 , the present application provides an embodiment: a high-efficiency filtration and dust removal sand slurry integrated production system, the production system further comprises a central control and remote monitoring module, and the central control and remote monitoring module further comprises:

[0081] A fault self-diagnosis algorithm module based on convolutional neural network and time series LSTM is used to extract multi-dimensional heterogeneous features and predict fault types from differential pressure sensor, vibration sensor and temperature sensor data;

[0082] An automatic preventive maintenance scheduling sub-module generates a maintenance work order with priority when the predicted fault probability exceeds a certain threshold, and pushes it through the device touch screen and mobile APP;

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

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

[0085] 10.1-inch industrial-grade touch screen HMI, supporting multi-user permissions, visual process flowchart and real-time historical curve playback;

[0086] The cloud communication module based on the MQTT protocol uploads the production data to the enterprise private cloud big data platform after safe encryption, for process optimization and quality traceability.

[0087] The mobile APP realizes remote alarm push, production report viewing, and online parameter modification.

[0088] The central control and remote monitoring module is equipped with an edge computing node and a digital twin simulation platform, and the edge computing node and the digital twin simulation platform comprise:

[0089] The real-time digital twin virtual machine based on the system physical model and historical working condition data is used to predict the filter life, mixing quality, and energy consumption.

[0090] The simulation engine running in parallel with the actual system performs "join-then" scenario simulation during the idle production period and feeds back the optimization suggestions to the central control module.

[0091] Further, the differential pressure sensor, vibration sensor, and temperature sensor upload the original signals to the edge computing node through industrial Ethernet at a frequency of 100 Hz, and perform fast filtering and normalization at the edge node: 0.1-20 Hz band-pass filtering is performed on the vibration and temperature signals, the differential pressure signal is subjected to moving average, and is standardized to [-1, 1]; the vibration and temperature signals are spliced into a two-dimensional "amplitude-time" matrix, input into a 3-layer convolution network (Conv1-Conv3), the convolution kernel size of each layer is (3x1) and the step is 1, and the number of channels is 16, 32, and 64 in sequence, for extracting short-time waveform and local temperature fluctuation features; the Conv3 output is flattened into a sequence, input into two layers of LSTM (128 hidden units per layer), and the last time output of the LSTM is input into a fully connected layer and Softmax to give the probability distribution of N classes of faults (such as filter clogging, air valve jamming, sensor drift, etc.); when the probability of any fault category is greater than θ, the category alarm is determined, and the confidence at this moment and the fault trend in the next moment are output;

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

[0093] Air valve jamming (high priority), sensor drift (medium priority), and filter clogging (low priority), the work order content includes device ID, fault description, recommended maintenance action, and required spare parts list; a pop-up alarm is displayed on the HMI touch screen, and an MQTT client is called to push the work order in JSON format to the mobile APP subscription topic, the APP receives and displays it in the "to-be-processed work order" list, and reminds the maintenance personnel through local notification;

[0094] The maintenance personnel fill in the maintenance results and the used market, the actual fault reason and the like information in the APP, the APP returns the results to the edge database through the HTTPS interface, the edge node marks the maintenance results to the original sample in a time manner, forms a new training set, executes the small batch gradient descent fine tuning convolution and the LSTM network weight, and the updated model immediately replaces the old model without stopping; The 10.1-inch industrial-grade touch screen main interface displays a production flow chart, and the current unit state is highlighted in real time; any unit is clicked to expand the historical curve of the unit and support playback to any time point;

[0095] The same simulation environment as the physical system is deployed on the edge server, real-time working condition parameters are input, and the simulation state is updated at a frequency of 5Hz; predicted indexes are output, including filter core remaining life, mixing uniformity and unit energy consumption; the "if-then" simulation task is automatically triggered during the daily "shift interval" or "system standby": for example, "if the back blowing frequency is increased by 30% -> filter core life changes"; "if the mixing speed is reduced by 20% -> energy consumption and uniformity change"; a simulation report is generated, and optimization suggestions are issued through the HMI and the APP, such as adjusting the dust removal period or modifying the speed curve.

[0096] Please refer to Figure 1 An embodiment provided by the application: a high-efficiency filtering and dust-removing sand slurry integrated production system, the intelligent pre-separation filtering unit and the intelligent batching and mixing unit constitute an online raw material tracing and dynamic adjustment subsystem, including:

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

[0098] An RFID reading device and a two-dimensional code scanning device are used to automatically obtain raw material batch, supplier and production date information, and establish an associated database with the online detection data;

[0099] A dynamic proportioning adjustment algorithm is used to compensate for the flow rate of each through the mass flow meter according to the deviation of real-time detection and the target formula, so as to realize the stability of the final mixed physical and chemical properties;

[0100] Further, before production, the optical particle size analysis sensor is calibrated by a standard particle size sample, the calibration curve is stored in the edge database, the laser scattering water content sensor is calibrated by using deionized water and a known water content medium to generate a water content-scattering intensity mapping table; the RFID tag is attached to the raw material bag, the two-dimensional code is printed on the package, and the operator sequentially approaches the reading position before loading, and the system automatically collects: batch number, supplier code, production date, raw material type, and the above information is written into the raw material batch association table with a time stamp;

[0101] After the preliminary removal of large particles by the intelligent pre-separation filtering unit, the continuous flow is introduced to the detection cabin through the bypass sampling pipeline, the detection cabin is provided with a high-speed camera and a light source, the material passes through the narrow gap flow channel at a constant speed, the camera shoots 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] Wherein p represents the proportion of the number of particles in each interval;

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

[0105] The target particle size distribution Dtarget and the target moisture content Htarget of the current batch are obtained from the central controller, the particle size deviation is calculated: ΔD=Dtarget-D, the deviation vector of the four interval is obtained: ΔD=[Δp1,Δp2,Δp3,Δp4]; For the sand channel, the original nominal flow rate is According to the maximum deviation position, the compensation focus is determined: K s =1+β·max(|Δp i |), wherein β is a compensation factor; The same way is used to calculate the cement powder and additive channel, but when the moisture deviation ΔH=Htarget-Hmeas exceeds 1%, the water flow channel is adjusted through the humidity compensation algorithm first, and the particle size channel is not adjusted greatly; Every 5 minutes, the sampling detection is performed again, if the particle size and moisture deviation are both lower than the preset threshold value, it is considered that the adjustment is completed; Otherwise, the cycle is executed until the standard is reached.

[0106] Please refer to Figure 1 , the application provides an embodiment: an efficient filtering and dust-removing sand mixing slurry integrated production system, the online regeneration energy recovery device comprises:

[0107] The adjustable flow high-pressure energy storage tank is used for storing high-pressure gas in the back blowing process;

[0108] The variable geometry direct current turbine generator set connected with the high-pressure energy storage tank drives the turbine to generate electricity, and the output electric energy is fed back to the local micro-grid or energy storage battery through the bidirectional inverter;

[0109] Energy management control module, according to the process load, high pressure energy storage tank pressure and energy storage state, dynamic optimization of gas release time and turbine speed curve, and the excess pressure is automatically switched to cooling or secondary dust removal cycle;

[0110] Further, after the differential pressure dust removal unit completes back blowing, high pressure gas is introduced to the high pressure energy storage tank through the pipeline, the inlet valve is opened at a speed of 0.5 m 3 / min until the pressure in the tank reaches 0.9 MPa or the back blowing gas source is finished; when the tank pressure reaches 0.9 MPa, the inlet valve is automatically fine-tuned to maintain constant pressure; if the pressure exceeds 1.1 MPa, the safety relief valve is opened to discharge to the secondary dust removal loop; when the pressure is lower than 0.7 MPa, the system stops gas release to the generator, and the pressure is preferentially reserved for the next back blowing; the EMCM evaluates every 10 s: if the tank pressure is greater than or equal to 0.85 MPa and the local micro-grid load is greater than or equal to 5 kW, or the battery SOC is less than or equal to 80%, the power generation is started; otherwise, the energy storage is kept standby, waiting for a better opportunity; when generating power, the EMCM calculates the optimal nozzle opening angle θ according to the real-time tank pressure P tank and the target power generation P req ; the optimal nozzle opening angle θ is calculated as follows: θ = θ min +(θ max -θ min )×P req / P rated ; wherein θ min 10°, θ max = 70°, P rated = 50 kW, and the target rotor speed N req = P req / k r P tank , wherein k r is an empirical torque coefficient;

[0111] The turbine guide gas drives the generator to reach N req ; the generator output power is transmitted through a bidirectional inverter: if the local load demand is higher than the current power generation, the excess power is preferentially used for battery charging; if the local load is lower than the power generation, the excess power is fed into the local micro-grid; when the tank pressure drops to 0.75 MPa, the EMCM judges whether to continue power generation: if the tank pressure will be reduced to the lower limit if the power generation continues, the power generation is stopped; after the power generation is stopped, if there is still excess pressure in the pipeline, the bypass valve is automatically opened to introduce high pressure gas into the cooling coil or the secondary dust removal unit, realizing the secondary use of excess pressure.

[0112] Please refer to Figure 1 , the present application provides an embodiment: a high-efficiency filtering and dust-removing mixed sand slurry integrated production system, the production system further comprises a safety interlock and emergency bypass subsystem, the safety interlock and emergency bypass subsystem comprises:

[0113] Multi-point liquid level, temperature, pressure and smoke safety sensors for monitoring critical operating conditions;

[0114] Emergency bypass valve and bypass filter for automatically switching main filtration path and switching to bypass mode when safety threshold is exceeded, to ensure continuous operation of production system;

[0115] Acoustic and light alarm and automatic shutdown program linked to central control module for prompting operator and executing safety shutdown in emergency situation;

[0116] Further, capacitive liquid level sensors are selected and installed inside high-pressure accumulator tank and constant-temperature water tank, PT100 platinum resistance temperature probe is arranged on the outlet pipeline of differential pressure dust removal unit and the outer wall of mixer cavity, intelligent differential pressure transmitter is used for pressure difference before and after filter screen, high-pressure absolute pressure sensor is used for accumulator tank, and photoelectric smoke alarm is installed at the top of main machine room and near inlet and outlet air duct;

[0117] Operation flow and switching sequence:

[0118] The central controller scans the signals of the above-mentioned sensors at a frequency of 1 Hz to evaluate the safety state, and if any safety parameter exceeds the alarm threshold, the controller issues a bypass switching command: 1, close the main filter valve, 2, delay 100 ms to ensure that the main valve is closed, 3, open the bypass valve, 4, the bypass filter starts to work to ensure that the gas continues to be dusted; at the same time, the audible and light alarm is started and the "emergency bypass started" prompt is popped up on the HMI screen;

[0119] If a serious new sensor, 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 audible and light alarm and lock the operation interface;

[0124] After the emergency state is eliminated, the operator executes the "bypass reset" instruction on the HMI:

[0125] Close the bypass valve; open the main filter valve; the system automatically performs 30s self-check 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: record sensor type, measurement value, trigger time and action sequence;

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

[0128] The safety threshold and interlocking logic are shown in Table 1 below

[0129] Table 1 Logic Table

[0130]

[0131] Working principle: The principle passes through the intelligent pre-separation filter unit, uses double-layer cyclone filter element to throw out large particles and foreign matters, and periodically blows back and vibrates the filter element to clean ash and keep low resistance.

[0132] The differential pressure before and after the filter screen is detected in real time by a micro-pressure sensor, and the gain is adjusted by a closed-loop PID according to the dust load and time length, and the ash is cleaned quickly or stably; the back-blowing waste gas enters a high-pressure storage tank, and then is generated by a variable-geometry turbine, and the excess pressure can be supplied back to cooling or secondary dust removal.

[0133] Multi-channel mass flow meters, particle size and moisture content sensors are used for online detection, and dynamic proportioning algorithms are used for real-time compensation of feeding proportions; a double-shaft variable-speed mixer is combined with CFD-optimized cavities and viscosity-adaptive rotating speeds to realize high-homogeneous mixing; a central control module integrates fault self-diagnosis, preventive maintenance, digital twin simulation and remote monitoring, and realizes closed-loop optimization of the whole process.

[0134] It is apparent to those skilled in the art that the application is not limited to the details of the foregoing exemplary embodiments, and that the application can be implemented in other concrete forms without departing from the spirit or essential characteristics of the application. Therefore, the embodiments should be considered as exemplary and non-limiting, and the scope of the application is defined by the appended claims rather than the foregoing description, and all changes falling within the meaning and range of equivalent elements of the claims are intended to be encompassed by the application. Any reference signs in the claims should not be considered as limiting the claims involved.

Claims

1. A high-efficiency filtration and dust removal integrated production system of sand slurry, comprising an intelligent pre-separation filtration unit, characterized in that: The intelligent pre-separation filter unit is used for primary pre-separation of large-particle impurities and solid particles in raw materials, and a double-layer cyclone filter core with a self-cleaning function is arranged in the intelligent pre-separation filter unit, the outer layer of the double-layer cyclone filter core is a wear-resistant ceramic coating, and the inner layer is an elastic polymer material; ​ The intelligent pre-separation filter unit is connected with a differential pressure self-adaptive filter screen dust removal unit in an air path, the differential pressure self-adaptive filter screen dust removal unit is used for online monitoring of pressure differences before and after a filter screen, and automatically adjusts a back-blowing valve to realize dust removal of the filter screen through a built-in micro-pressure sensor and a closed-loop PID control algorithm; The differential pressure self-adaptive filter screen dust removal unit is connected with an online regeneration energy recovery device, the online regeneration energy recovery device is used for recovering high-pressure gas energy in a back-blowing process, and converts micro-electric energy or low-pressure gas back supply through an adjustable-flow high-pressure energy storage tank and a direct-current turbine generator set; The production system further includes an intelligent batching and mixing unit, adopts a multi-channel mass flowmeter, a particle size and moisture content online sensor and a dynamic proportioning algorithm, automatically adjusts the feeding rates of cement, sand, water and additives according to real-time detection data, and realizes homogeneous mixing through a double-shaft variable-speed mixer and a programmable speed curve; The double-shaft variable-speed mixer comprises: A pair of reverse helical blades, the blade root width and the blade end width change exponentially to optimize the shear stress distribution; Frequency conversion driving and torque feedback control are adopted to realize stepless speed regulation in the range of 0-300 rpm, and the speed is automatically adjusted according to the real-time material viscosity; A built-in fluid mechanics CFD simulation optimization cavity shape is used to reduce the dead zone and improve the mixing uniformity; The online regeneration energy recovery device comprises: An adjustable-flow high-pressure energy storage tank is used for storing high-pressure gas in the back-blowing process; A direct-current turbine generator set connected with the high-pressure energy storage tank drives the turbine to generate electricity, and the output electric energy is fed back to the local micro-grid or energy storage battery through a bidirectional inverter; An energy management control module dynamically optimizes the gas discharge time and turbine speed curve according to the process load, high-pressure energy storage tank pressure and energy storage state, and automatically switches the excess pressure to the cooling or secondary dust removal cycle.

2. The integrated production system for high-efficiency filtering and dust-removing sand slurry according to claim 1, characterized in that: The production system further includes a central control and remote monitoring module, and the central control and remote monitoring module further comprises: A fault self-diagnosis algorithm module based on convolutional neural network and time series LSTM is used for multi-dimensional heterogeneous feature extraction and fault type prediction of differential pressure sensor, vibration sensor and temperature sensor data; An automatic preventive maintenance scheduling sub-module generates a maintenance work order with priority and pushes it through a device touch screen and a mobile terminal APP when the predicted fault probability exceeds a set threshold; A maintenance feedback learning mechanism compares the actual maintenance result with the algorithm prediction result, automatically updates the model parameters and stores them in a local edge database.

3. The integrated production system for high-efficiency filtering and dust-removing sand slurry according to claim 1, characterized in that: The intelligent pre-separation filter unit and the intelligent batching and mixing unit form an online raw material tracing and dynamic adjustment subsystem, comprising: An optical particle size analysis sensor and a moisture content sensor based on the laser scattering principle are used for real-time detection of the particle size distribution and moisture content of sand and powder after pre-separation; RFID reading device and two-dimensional code scanning device are used to automatically obtain raw material batch, supplier and production date information, and establish a correlation database with online detection data; A dynamic proportioning adjustment algorithm is used to compensate for the flow rate of each through the mass flow meter according to the deviation of real-time detection and target formula, so as to realize stable physical and chemical properties of final mixing.

4. The integrated production system for high-efficiency filtering and dust-removing sand slurry according to claim 1, characterized in that: The intelligent proportioning and mixing unit comprises: A humidity detection module based on a capacitive moisture content sensor is used to monitor the moisture content of sand and powder in real time; A humidity compensation control algorithm is used to dynamically increase or decrease the water injection amount according to the deviation of the detection value and the set value, and to accurately inject water through a constant temperature water tank and a mass flow control valve; An additive injection sub-module comprising a multi-channel peristaltic pump is used to inject high-performance polymer modifier or water reducing agent in proportion according to the formula requirements.

5. The integrated production system for high-efficiency filtering and dust-removing sand slurry according to claim 2, characterized in that: The central control and remote monitoring module further comprises: A 10.1-inch industrial touch screen HMI supports multi-user permissions, visual process flowcharts and real-time historical curve playback; A cloud communication module based on MQTT protocol is used to upload the production data to the enterprise private cloud big data platform after safe encryption, for process optimization and quality traceability; A mobile APP is used to realize remote alarm pushing, production report viewing and online parameter modification.

6. The integrated production system for high-efficiency filtration and dust removal of the sand slurry according to claim 1, characterized in that: The PID control algorithm of the differential pressure self-adaptive filter screen dust removal unit comprises: An online estimation model based on the cumulative dust load of the filter screen and the running time is used to calculate the optimal proportional, integral and differential gain in real time; When the performance degradation of the filter screen or the fluctuation of the inlet dust concentration is detected, the gain scheduling module is automatically started to realize the switching between fast response and smooth ash removal modes; After ash removal is completed, self-calibration is performed using historical working condition data to eliminate model errors.

7. The integrated production system for high-efficiency filtering and dust-removing sand slurry according to claim 2, characterized in that: The central control and remote monitoring module is equipped with an edge computing node and a digital twin simulation platform, and the edge computing node and the digital twin simulation platform comprise: A real-time digital twin virtual machine based on the system physical model and historical working condition data is used to predict the filter core life, mixing quality and energy consumption; An simulation engine running in parallel with the actual system performs "join-then" scenario simulation during idle production periods and feeds back optimization suggestions to the central control module.

8. The integrated production system for high-efficiency filtration and dust removal of the sand slurry according to claim 1, characterized in that it comprises: The production system further comprises a safety interlock and emergency bypass subsystem, and the safety interlock and emergency bypass subsystem comprises: Multiple point liquid level, temperature, pressure and smoke safety sensors are used to monitor critical working conditions; An emergency bypass valve and a bypass filter core are used to automatically switch the main filter path and switch to bypass mode when the safety threshold is exceeded, to ensure continuous operation of the production system; An audible and visual alarm and automatic shutdown program linked with the central control module is used to prompt the operator and execute safety shutdown in emergency situations.

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