Intelligent pulse dust collector monitored by Internet of Things and control method

Abstract

The invention discloses an intelligent pulse dust collector monitored by Internet of Things and a control method, the intelligent pulse dust collector comprises a pulse dust filter main body and an Internet of Things monitoring system, the main body comprises a sealed upper box body, a lower box body, electromagnetic pulse valves arranged in groups, a dust filtering assembly and a scraper assembly; the Internet of Things monitoring system is composed of a sensing module, a control module, a communication module and a cloud Internet of Things platform. The sensing module is used for collecting operation parameters such as filter bag resistance and dust concentration and equipment states through multiple types of sensors; the control module adopts an edge calculation module and PLC dual-core architecture, operates a multi-parameter fused intelligent ash removal decision algorithm, and generates a targeted control instruction to drive an execution mechanism to act; the communication module realizes data interaction through wired and wireless dual modes, and the cloud platform supports remote monitoring, control, fault early warning and data analysis. The problems that traditional equipment is rigid in ash removal, inconvenient to operate and maintain and the like are solved, the dust removal efficiency and the equipment reliability are remarkably improved, and the energy consumption and the operation and maintenance cost are reduced.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of pulse bag type dust collectors, in particular to an intelligent pulse dust collector and a control method for Internet of Things monitoring. BACKGROUND

[0002] In industrial production, dust pollution is a common environmental problem. As the main treatment equipment, the traditional working mode of the pulse dust collector is mostly fixed time or fixed pressure difference cleaning. This mode has significant defects: fixed cycle cleaning cannot adapt to actual working conditions, which easily leads to cleaning not in time (filter bag resistance increases, efficiency decreases) or excessive cleaning (filter bag wear is intensified, energy waste). At the same time, the traditional equipment lacks effective state monitoring and remote management means, and the operation and maintenance personnel cannot real-time master the equipment health status, the fault response is lagging, and the maintenance cost is high.

[0003] With the development of industrial Internet of Things (IIoT), intelligent sensing and edge computing technology, intelligent upgrading of dust removal equipment is possible. Through real-time sensing, intelligent decision-making and remote linkage, precise cleaning on demand and preventive maintenance are realized, which is the key direction to improve the efficiency and reliability of the dust removal system. SUMMARY

[0004] Therefore, the application aims to provide an intelligent pulse dust collector and a control method for Internet of Things monitoring, which can avoid the problem of inaccurate cleaning strategy, lack of real-time state sensing and remote intelligent control ability of the traditional dust collector.

[0005] In order to solve the above technical problems, the application discloses an intelligent pulse dust collector for Internet of Things monitoring, comprising: A pulse dust collector main body, comprising a sealed upper box body provided with a dust filtering assembly, a lower box body connected below the upper box body to form a dust collecting cavity, an electromagnetic pulse valve arranged in the upper box body according to the dust filtering assembly, and a scraper assembly arranged in the lower box body; An Internet of Things monitoring system connected with the pulse dust collector main body, comprising: A sensing module comprising a plurality of sensor units arranged on the pulse dust collector main body, for collecting operating parameters and equipment state signals; A control module comprising an edge computing module and a PLC controller, respectively connected with the sensing module and the actuator of the pulse dust collector main body, for processing sensing data, generating control instructions and driving the actuator to act; A communication module for realizing data interaction between the control module and the cloud Internet of Things platform; A cloud Internet of Things platform for realizing remote monitoring, control and data analysis of the equipment; Wherein, the operating parameters collected by the perception module are analyzed and processed by the control module to generate control instructions, drive the electromagnetic pulse valve and the scraper assembly to act, and the operating parameters and the equipment state are uploaded to the cloud Internet of Things platform through the communication module; the remote instructions of the cloud Internet of Things platform are transmitted to the control module through the communication module and executed.

[0006] Further, the perception module comprises: The filter bag resistance monitoring unit is a differential pressure transmitter arranged at the inlet and outlet sides of the filter bag in the dust filtering assembly, used to collect the pressure difference between the two ends of the filter bag. The dust state monitoring unit comprises a laser scattering type dust concentration sensor arranged at the inlet and outlet pipes of the dust collector, and a high-frequency radar level sensor arranged at the bottom of the ash bucket of the lower box body. The equipment operation state monitoring unit comprises a pulse valve stroke switch corresponding to each electromagnetic pulse valve, a motor current sensor connected with the motor of the scraper assembly and the motor of the induced draft fan, and an electrostatic induction type filter bag breakage sensor arranged below the filter bag. The environmental parameter monitoring unit is a temperature and humidity sensor arranged at the top of the upper box body and the side wall of the lower box body.

[0007] Further, the edge computing module of the control module is an embedded development board based on ARM architecture, carrying a Linux operating system, which has the following built-in functions: The data preprocessing module filters and removes outliers from the parameters collected by the perception module. The intelligent soot cleaning decision module runs an intelligent soot cleaning decision algorithm based on multi-parameter fusion. The local data storage module uses SQLite database to store historical operation data. The PLC controller is a programmable logic controller connected with the electromagnetic pulse valve, the scraper assembly, the induced draft fan frequency converter controller and the ash unloading valve, used to receive the control instructions of the edge computing module and drive the actuator to act, and collect the actuator state signal feedback to the edge computing module. The edge computing module and the PLC controller communicate through industrial Ethernet using Profinet protocol.

[0008] Further, the communication module adopts a dual communication mode combining wired and wireless communication; The sensors of the perception module and the edge computing module communicate locally through RS485 bus using Modbus-RTU protocol. The edge computing module integrates 4G / 5G communication module and WiFi module, supports dual-mode automatic switching, and transmits data to the cloud Internet of Things platform through MQTT protocol. The communication module encrypts the remote control instructions and records all remote operation logs.

[0009] Furthermore, the cloud-based IoT platform is based on a B / S architecture, supports access from both web and mobile devices, and includes the following functional modules: The data visualization module displays real-time and historical operating parameters in chart form and supports map-based device status monitoring. The remote control module supports remote equipment start / stop, manual ash removal, parameter adjustment, and ash discharge level setting. The fault management module receives fault information and implements multi-channel alarms, and supports closed-loop tracking of fault handling. The data analysis module is used for dust removal efficiency statistics, filter bag life prediction, energy consumption analysis, and report generation. The user management module supports role-based multi-level permission management.

[0010] Furthermore, the differential pressure transmitter has a measurement range of 0-5 kPa, an accuracy of ±0.5%FS, and a response time of ≤100ms; The laser scattering dust concentration sensor has a measurement range of 0-1000 mg / m³. 3 With an accuracy of ±2%FS, it features automatic calibration. The high-frequency radar level sensor has a measurement range of 0-5m and an accuracy of ±1%.

[0011] Furthermore, the algorithm logic for the intelligent dust removal decision module is as follows: The real-time resistance of the filter bag is the core indicator. When the resistance is greater than or equal to the first threshold P1, the dust removal program is started. Adjust the cleaning interval and pulse width based on the real-time inlet dust concentration; The risk of filter bag clogging is assessed by combining changes in gas flow rate, and the cleaning intensity is dynamically adjusted accordingly. The cleaning process stops when the resistance is less than or equal to the second threshold P2.

[0012] Furthermore, the electromagnetic pulse valve is of type DMF-Z, with a response time ≤50ms and an adjustable pulse width within the range of 0.1-0.5s; The induced draft fan is equipped with a frequency converter. The edge computing module dynamically controls the speed of the induced draft fan by adjusting the output of the frequency converter based on the gas flow sensor data and filter bag resistance data, thereby achieving energy-saving operation.

[0013] Furthermore, the PLC controller has a local manual control mode. When the IoT monitoring and control system malfunctions, it can perform basic start-up, shutdown, dust removal operations and parameter settings of the equipment through the local human-machine interface. The control module also includes an industrial touch screen, which communicates with the PLC controller via the MPI bus for local parameter setting, real-time status display, and fault information query.

[0014] This invention also discloses a control method for an IoT-monitored intelligent pulse dust collector, comprising the following steps: S1: Through the sensor network of the sensing module integrated on the main body of the pulse dust filter, real-time operational data including filter bag resistance, inlet and outlet dust concentration, ash hopper level, equipment status and environmental parameters are collected. S2: In the edge computing module, the running data is preprocessed and input into the intelligent dust removal decision model for analysis to generate a targeted dust removal control strategy; S3: The dust removal control strategy is executed through the PLC controller, which drives the corresponding electromagnetic pulse valve and scraper assembly to move, and coordinates the control of the induced draft fan speed; S4: Uploads operating data, device status, and operation logs to the cloud IoT platform via the communication module, and receives and executes remote commands from the platform; S5: Analyzes data at the edge or in the cloud to enable fault warnings and equipment health management.

[0015] Compared with the prior art, the present invention can achieve the following technical effects: ① Based on real-time intelligent decision-making using multiple parameters such as actual filter bag resistance and dust load, on-demand cleaning is achieved, which significantly extends filter bag life and reduces compressed air consumption while ensuring dust removal efficiency, breaking through the previous fixed-cycle cleaning mode.

[0016] ② By deploying multiple types of sensors at key nodes of the dust collector, a full-dimensional digital perception of filtration performance, dust status, equipment health, and operating environment is achieved, laying a data foundation for intelligent decision-making and preventive maintenance.

[0017] ③ The dual-core architecture of edge computing and PLC leverages the flexibility and intelligence of edge computing while retaining the high reliability of PLC in industrial control. The cloud-based IoT platform provides integrated services for centralized monitoring, remote control, fault alarms, and data analysis, greatly reducing the frequency of on-site inspections and the difficulty of operation and maintenance.

[0018] Of course, any product implementing this invention does not necessarily need to achieve all of the technical effects described above at the same time. Attached Figure Description

[0019] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this invention, illustrate exemplary embodiments of the invention and are used to explain the invention, but do not constitute an undue limitation of the invention. In the drawings: Figure 1 This is a schematic diagram of an intelligent pulse dust collector with IoT monitoring according to an embodiment of the present invention; Figure 2This is a logical flowchart of an intelligent dust removal decision algorithm provided in an embodiment of the present invention; Figure 3 This is a functional block diagram of a cloud-based Internet of Things (IoT) platform provided in an embodiment of the present invention; Figure 4 This is a flowchart of the control method provided in an embodiment of the present invention.

[0020] Figure label: 1. Pulse filter body; 2. Filter assembly; 3. Upper chamber; 4. Lower chamber; 5. Electromagnetic pulse valve; 6. Scraper assembly; 7. Pulse jet pipe; 8. Tube plate; 9. Filter bag; 10. Ash discharge valve. Detailed Implementation

[0021] The following will describe in detail the implementation of the present invention with reference to the accompanying drawings and embodiments, so that the process of how the present invention uses technical means to solve technical problems and achieve technical effects can be fully understood and implemented accordingly.

[0022] Example 1: An intelligent pulse dust collector with IoT monitoring like Figure 1 As shown, this embodiment provides a complete IoT-monitored intelligent pulse dust collector.

[0023] The pulse jet dust collector includes a main body 1, filter components 2, an upper housing 3, a lower housing 4, an electromagnetic pulse valve 5, and a scraper assembly 6. The upper housing 3 is a sealed welded structure, housing several sets of filter components 2, each containing multiple filter bags 9. The electromagnetic pulse valve 4 is a DMF-Z type, with a response time ≤50ms, configured in groups and installed on the air tank at the top or side of the upper housing 3. Its pulse width can be adjusted within the range of 0.1-0.5s by the control system. The lower housing 4 is connected to the upper housing 3 via a flange, and its bottom conical ash hopper forms the dust collection chamber. The scraper assembly 6 is installed at the center of the bottom of the ash hopper, driven by a motor, and is responsible for conveying the collected dust to the ash discharge valve 10.

[0024] In detail, the upper chamber 3 and the lower chamber 4 are separated by a tube sheet 8 into an upper clean air chamber and a lower filter chamber. The clean air chamber has a clean air outlet at the top, and an airflow regulating valve or silencer can be installed at the outlet as needed. An air tank is installed at the top of the upper chamber 3, and a dust-laden gas inlet is located on the side of the lower chamber 4. In another embodiment, a pressure relief valve can also be installed in the lower chamber 4 for safety protection. The output end of the electromagnetic pulse valve 4 is connected to a blowpipe 7, and a nozzle is installed at predetermined intervals at the bottom of the blowpipe. Each nozzle is precisely aligned with the venturi tube at the top of a filter bag 9 below. The filter bags 9 are installed under the tube sheet 8 using a circular carbon steel cage as a frame to achieve dust filtration.

[0025] Furthermore, the IoT monitoring system includes a sensing module, a control module, a communication module, and a cloud-based IoT platform.

[0026] The perception module specifically includes: Filter bag resistance monitoring unit: It adopts a high-precision differential pressure transmitter (e.g., measurement range 0-5kPa, accuracy ±0.5%FS). One end is connected to the clean air side of the filter bag, and the other end is connected to the dust-laden air side of the compartment where the filter bag is located. It monitors the pressure difference before and after the filter bag in real time. This pressure difference directly reflects the dust adhesion and air permeability of the filter bag.

[0027] Dust monitoring unit: Laser scattering dust concentration sensors (e.g., measurement range 0-1000 mg / m³) are installed at the inlet and outlet pipes of the dust collector. 3 The inlet concentration (accuracy ±2%FS) is used to assess the processing load, and the outlet concentration is used to monitor dust removal efficiency in real time. A high-frequency radar level sensor (e.g., measurement range 0-5m, accuracy ±1%) is installed at the bottom of the ash hopper to monitor the dust accumulation height and trigger automatic ash unloading.

[0028] Equipment operation status monitoring unit: Each electromagnetic pulse valve 5 is equipped with a pulse valve limit switch to provide feedback on the actual opening and closing position of the valve core and diagnose whether the valve is stuck. Motor current sensors are provided for the scraper assembly motor and the induced draft fan motor to detect motor overload, stall, and other faults through abnormal current fluctuations. An electrostatic induction filter bag damage sensor is installed in the clean air chamber below the filter bag; when the filter bag is damaged, causing dust leakage, the sensor detects a change in electrostatic signal and triggers an alarm.

[0029] Environmental parameter monitoring unit: Temperature and humidity sensors are installed on the top of the upper chamber 3 and the side wall of the lower chamber 4 to monitor the internal gas environment and prevent filter bags from caking or dust from clumping due to high temperature and humidity.

[0030] The control module of the present invention includes an edge computing module and a PLC controller.

[0031] The edge computing module utilizes an industrial-grade embedded computer based on the ARM architecture (such as a Raspberry Pi CM4 core board with a customized carrier board) running a Linux operating system. Its software functions are modularized: The data preprocessing module performs digital filtering, jump suppression, and outlier removal on the raw data from various sensors via the RS485 bus to improve data quality. The intelligent dust removal decision module is the core of the algorithm. (Example...) Figure 2As shown, its decision-making logic uses real-time filter bag resistance as the core indicator, setting an upper threshold P1 (e.g., 1.2 kPa) and a lower threshold P2 (e.g., 0.5 kPa). When the resistance ≥ P1, a dust removal decision is triggered, and the target filter bag group, pulse width, and pulse interval are dynamically adjusted based on real-time inlet dust concentration (higher concentration requires more frequent or thorough dust removal) and gas flow data (abnormal flow rate drops may indicate blockage). When the resistance ≤ P2, dust removal is immediately terminated to avoid over-pulsing. The local data storage module uses a lightweight SQLite database, which can store all historical sensor data, alarm records, and operation logs according to a set period (e.g., configurable from 1 to 365 days). Data is ensured not to be lost during network interruptions and is automatically re-uploaded after network recovery.

[0032] The PLC controller uses a Siemens S7-1200 series PLC as the direct control layer. It communicates at high speed with the edge computing module via Profinet industrial Ethernet, receiving dust removal command packets (including valve group address, pulse width, etc.) and converting them into precise timing control signals to drive the corresponding solenoid pulse valve 5, scraper assembly 6 motor, and ash discharge valve 10. Simultaneously, the PLC collects feedback signals from all actuators in real time (such as limit switch status and inverter status) and uploads them to the edge computing module, forming a closed-loop control system.

[0033] The local HMI is equipped with a 7-inch industrial touchscreen, which connects to the PLC controller via an MPI bus. The touchscreen provides a field operation interface, enabling equipment start / stop, manual dust removal, parameter setting (such as P1 / P2 thresholds), real-time data display, historical curve query, and fault alarm confirmation. It also provides a reliable backup operation method in case of IoT system anomalies.

[0034] Furthermore, the communication module adopts a layered hybrid communication strategy.

[0035] Local wired communication: All sensors are connected to the edge computing module via RS485 bus, using the standard Modbus-RTU protocol, which is simple to wire and has strong anti-interference ability.

[0036] Remote wireless communication: The edge computing module integrates a 4G / 5G module and a Wi-Fi module. When there is stable Wi-Fi coverage in the factory area, Wi-Fi is prioritized for data transmission to reduce costs; in weak signal or mobile scenarios, it automatically and seamlessly switches to 4G / 5G networks to ensure continuous connectivity. Data transmission with the cloud-based IoT platform uses the lightweight MQTT protocol, and control command channels are encrypted with TLS to ensure communication security. All remote operations are logged for easy auditing.

[0037] Cloud-based IoT platforms such as Figure 3As shown, the platform is developed based on a B / S architecture, supporting access from PC browsers and mobile apps / mini-programs. Its main functional modules include: Data visualization module: Visually displays the real-time operating parameters of one or more dust collectors using dashboards, trend curves, bar charts, etc. It can be combined with an electronic map to provide a global view of the distribution and online status of all equipment.

[0038] Remote control module: Authorized users can remotely start and stop the equipment, force dust removal, modify parameters (such as dust removal threshold and alarm limit), and set the ash discharge level.

[0039] Fault Management Module: Receives alarm information uploaded by the equipment (such as filter bag damage, pulse valve failure, and excessive material level), and immediately notifies the preset maintenance personnel through multiple channels such as the platform interface, SMS, and APP push, and tracks the closed loop of alarm handling.

[0040] Data analysis module: Mines massive amounts of historical data to automatically generate daily / monthly dust removal efficiency reports, filter bag remaining life predictions, system energy consumption analysis reports, etc., providing decision support for equipment optimization and scientific operation and maintenance.

[0041] User management module: Enables fine-grained access control, allowing users to set up different roles such as system administrator, regional operations manager, and field operator, and assign different data viewing and device operation permissions.

[0042] The collaborative workflow of this invention is as follows: After the equipment starts up, the sensing module continuously collects data. The intelligent algorithm in the edge computing module determines whether dust removal is needed and how to remove it based on real-time filter bag resistance, dust concentration, and other factors. When dust removal is required, a command is sent to the PLC controller. The PLC controls the opening of a specific group of electromagnetic pulse valves 5, instantly injecting compressed air into the filter bags, causing them to expand and shake off the dust. The scraper assembly 6 automatically operates according to the ash hopper level. Simultaneously, the frequency converter controller of the induced draft fan receives commands from the edge computing module and dynamically adjusts its speed based on system resistance to maintain optimal airflow. All data throughout the process is synchronously uploaded to the cloud platform for transparent monitoring.

[0043] Example 2: A control method like Figure 4 As shown, this embodiment provides a control method applied to the above-mentioned dust collector, including the following steps: S1: Comprehensive Data Sensing. After the system is powered on, all sensors in the sensing module start working, synchronously collecting data such as filter bag differential pressure, inlet and outlet dust concentration, temperature and humidity at various locations, ash hopper level, motor current, and pulse valve position signals at a configurable frequency of 1-10Hz.

[0044] S2: Edge-side data processing and intelligent decision-making. The edge computing module filters and calibrates the collected raw data. Subsequently, the intelligent dust removal decision model is activated. Its core process is as follows: read the current filter bag resistance value and compare it with the dynamic threshold (P1, P2). If the resistance ≥ P1, it is determined that dust removal is required; then, the current inlet dust concentration is queried. If the concentration is high, the pulse width is appropriately increased or the dust removal interval of the same filter bag group is reduced in this round of dust removal strategy; at the same time, it checks whether the gas flow rate is abnormally reduced. If so, it may be determined that there is a risk of blockage, triggering an enhanced dust removal mode or an alarm. Finally, a dust removal instruction package containing "target filter bag group number, pulse width, and blowing sequence" is generated. If the resistance ≤ P2, a "stop dust removal" instruction is generated.

[0045] S3: Precise Execution and Feedback. The PLC controller parses and executes instruction packets from the edge computing module, outputs drive signals to the designated solenoid pulse valve 5, and monitors the feedback of its limit switch to ensure proper operation. Simultaneously, it automatically controls the scraper assembly 6 and the ash discharge valve 10 based on the ash hopper level signal, and adjusts the induced draft fan speed according to the total system resistance.

[0046] S4: Data Upload to Cloud and Command Download. The edge computing module packages pre-processed operational data, device status, generated command records, alarm information, etc., via the MQTT protocol and uploads them to the cloud-based IoT platform for persistent storage and display via 4G / 5G / Wi-Fi networks. Remote control commands issued by the platform also travel down to the edge computing module through this path, and are executed by the PLC after verification.

[0047] S5: Intelligent Analysis and Early Warning. Data analysis is conducted simultaneously at the edge and in the cloud. At the edge, simple threshold exceedance alerts (such as current overruns) can be triggered instantly. The cloud utilizes greater computing power for in-depth analysis, such as using machine learning models to analyze the rate of increase in filter bag resistance over time, predicting its remaining lifespan, and generating replacement recommendations in advance; or using correlation analysis to diagnose the root causes of complex faults.

[0048] The foregoing description illustrates and describes several preferred embodiments of the present invention. However, as previously stated, it should be understood that the present invention is not limited to the forms disclosed herein and should not be construed as excluding other embodiments. It can be used in various other combinations, modifications, and environments, and can be altered within the scope of the inventive concept described herein through the foregoing teachings or techniques or knowledge in related fields. Any modifications and variations made by those skilled in the art that do not depart from the spirit and scope of the present invention should be within the protection scope of the appended claims.

Claims

1. An intelligent pulse dust collector with Internet of Things (IoT) monitoring, characterized in that, include: The main body of the pulse dust filter includes a sealed upper chamber equipped with dust filter components, a lower chamber connected below the upper chamber to form a dust collection chamber, electromagnetic pulse valves arranged in groups according to the dust filter components in the upper chamber, and a scraper assembly disposed in the lower chamber. An Internet of Things (IoT) monitoring system, connected to the main body of the pulse dust filter, includes: The sensing module includes multiple sensor units correspondingly arranged on the main body of the pulse dust filter, used to collect operating parameters and equipment status signals; The control module, including an edge computing module and a PLC controller, is connected to the sensing module and the actuator of the pulse dust filter body, respectively, and is used to process sensing data, generate control commands and drive the actuator to move. A communication module enables data interaction between the control module and the cloud-based IoT platform; A cloud-based IoT platform enables remote monitoring, control, and data analysis of devices; The operating parameters collected by the sensing module are analyzed and processed by the control module to generate control commands, which drive the electromagnetic pulse valve and scraper assembly to move. At the same time, the operating parameters and equipment status are uploaded to the cloud IoT platform via the communication module. The remote commands from the cloud IoT platform are transmitted to the control module and executed through the communication module.

2. The intelligent pulse dust collector with IoT monitoring according to claim 1, characterized in that, The sensing module includes: The filter bag resistance monitoring unit is a differential pressure transmitter arranged on the air inlet and outlet sides of the filter bag in the dust filtration assembly, used to collect the pressure difference between the two ends of the filter bag. The dust status monitoring unit includes laser scattering dust concentration sensors installed in the inlet and outlet pipes of the dust collector, and a high-frequency radar level sensor located at the bottom of the ash hopper in the lower box. The equipment operation status monitoring unit includes pulse valve limit switches that are connected one-to-one with each electromagnetic pulse valve, motor current sensors connected to scraper assembly motor and induced draft fan motor, and electrostatic induction filter bag damage sensors arranged below the filter bags. The environmental parameter monitoring unit consists of temperature and humidity sensors located on the top of the upper chamber and the side walls of the lower chamber.

3. The intelligent pulse dust collector with IoT monitoring according to claim 1, characterized in that, The edge computing module of the control module is an ARM-based embedded development board running a Linux operating system, and it has the following built-in features: The data preprocessing module filters and removes outliers from the parameters collected by the sensing module. The intelligent dust removal decision module runs an intelligent dust removal decision algorithm based on multi-parameter fusion; The local data storage module uses an SQLite database to store historical runtime data; The PLC controller is a programmable logic controller, which is connected to the electromagnetic pulse valve, scraper assembly, induced draft fan frequency converter and ash discharge valve respectively. It is used to receive control commands from the edge computing module and drive the actuator to move, while collecting the status signal of the actuator and feeding it back to the edge computing module. The edge computing module communicates with the PLC controller via Industrial Ethernet using the Profinet protocol.

4. The intelligent pulse dust collector with IoT monitoring according to claim 1, characterized in that, The communication module adopts a dual communication mode combining wired and wireless communication. Each sensor in the sensing module communicates locally with the edge computing module via an RS485 bus using the Modbus-RTU protocol. The edge computing module integrates a 4G / 5G communication module and a WiFi module, supports automatic switching between dual modes, and transmits data with the cloud IoT platform via the MQTT protocol. The communication module encrypts remote control commands and records all remote operation logs.

5. The intelligent pulse dust collector with IoT monitoring according to claim 1, characterized in that, The cloud-based IoT platform is based on a B / S architecture, supports access from both web and mobile devices, and includes the following functional modules: The data visualization module displays real-time and historical operating parameters in chart form and supports map-based device status monitoring. The remote control module supports remote equipment start / stop, manual ash removal, parameter adjustment, and ash discharge level setting. The fault management module receives fault information and implements multi-channel alarms, and supports closed-loop tracking of fault handling. The data analysis module is used for dust removal efficiency statistics, filter bag life prediction, energy consumption analysis, and report generation. The user management module supports role-based multi-level permission management.

6. The intelligent pulse dust collector with IoT monitoring according to claim 2, characterized in that: The differential pressure transmitter has a measurement range of 0-5 kPa, an accuracy of ±0.5%FS, and a response time of ≤100ms. The laser scattering dust concentration sensor has a measurement range of 0-1000 mg / m³. 3 With an accuracy of ±2%FS, it features automatic calibration. The high-frequency radar level sensor has a measurement range of 0-5m and an accuracy of ±1%.

7. The intelligent pulse dust collector with IoT monitoring according to claim 3, characterized in that, The algorithm logic of the intelligent dust removal decision module is as follows: The real-time resistance of the filter bag is the core indicator. When the resistance is greater than or equal to the first threshold P1, the dust removal program is started. Adjust the cleaning interval and pulse width based on the real-time inlet dust concentration; The risk of filter bag clogging is assessed by combining changes in gas flow rate, and the cleaning intensity is dynamically adjusted accordingly. The cleaning process stops when the resistance is less than or equal to the second threshold P2.

8. The intelligent pulse dust collector with IoT monitoring according to claim 1, characterized in that: The electromagnetic pulse valve is of type DMF-Z, with a response time ≤50ms and an adjustable pulse width within the range of 0.1-0.5s; The induced draft fan is equipped with a frequency converter. The edge computing module dynamically controls the speed of the induced draft fan by adjusting the output of the frequency converter based on the gas flow sensor data and filter bag resistance data, thereby achieving energy-saving operation.

9. The intelligent pulse dust collector with IoT monitoring according to claim 3, characterized in that: The PLC controller has a local manual control mode. When the IoT monitoring and control system fails, it can perform basic start-up, shutdown, dust removal operations and parameter settings of the equipment through the local human-machine interface. The control module also includes an industrial touch screen, which communicates with the PLC controller via an MPI bus for local parameter setting, real-time status display, and fault information query.

10. A control method for an intelligent pulse dust collector monitored by the Internet of Things as described in any one of claims 1-9, characterized in that, Includes the following steps: S1: Through the sensor network of the sensing module integrated on the main body of the pulse dust filter, real-time operational data including filter bag resistance, inlet and outlet dust concentration, ash hopper level, equipment status and environmental parameters are collected. S2: In the edge computing module, the running data is preprocessed and input into the intelligent dust removal decision model for analysis to generate a targeted dust removal control strategy; S3: The dust removal control strategy is executed by the PLC controller, driving the corresponding electromagnetic pulse valve and scraper assembly to move, and coordinating the control of the induced draft fan speed; S4: Uploads operating data, device status, and operation logs to the cloud IoT platform via the communication module, and receives and executes remote commands from the platform; S5: Analyzes data at the edge or in the cloud to enable fault warnings and equipment health management.

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