Efficient energy-saving pulverizer based on intelligent control and optimization

Abstract

The invention relates to the technical field of crushers, and particularly discloses an efficient energy-saving crusher based on intelligent control and optimization, which comprises a crusher body and a control and optimization system arranged based on the crusher body, the control and optimization system comprises a real-time monitoring and adaptive adjustment system, a big data analysis and optimization system, an automatic maintenance system and a fault diagnosis system; the real-time monitoring and self-adaptive adjusting system is used for monitoring and adjusting the running state of the crusher body in real time through a sensor; the big data analysis and optimization system is used for analyzing historical operation data of the crusher body and establishing an operation model and a material crushing model of the crusher body; the automatic maintenance system is used for ensuring that a transmission part and a bearing of the crusher body are well lubricated; and the fault diagnosis system is used for monitoring the change of running parts in the crusher body. The invention aims to solve the problems of low crushing efficiency, unstable crushing effect, high maintenance cost, low equipment running reliability and the like of equipment in the prior art.

Description

Technical Field

[0001] The present application relates to the technical field of pulverizers, and specifically discloses a high-efficiency and energy-saving pulverizer based on intelligent control and optimization. Background Art

[0002] Currently, agricultural waste, such as straw, branches, and weeds, is generated in large quantities. Improper disposal of these wastes can occupy land resources, create fire hazards, and negatively impact the environment. However, these wastes are rich in organic components such as cellulose, hemicellulose, and lignin, and possess high resource utilization value. Proper disposal can convert them into organic fertilizer, biomass fuel, or animal feed, achieving resource recycling.

[0003] As a key pretreatment device, pulverizers have been widely used in agricultural waste reduction and resource recovery. They can quickly pulverize large waste into smaller particles, significantly increasing the specific surface area and the contact area between the waste and microorganisms, creating favorable conditions for subsequent composting, fermentation, or energy utilization. For example, during the composting process, pulverized waste is more easily accessible to microorganisms, accelerating the decomposition of organic matter and shortening the composting cycle.

[0004] However, traditional pulverizers still face numerous challenges in practical application. For one thing, the complex composition and varying texture of agricultural waste can lead to inefficient pulverization and severe equipment wear. Furthermore, the pulverization process can generate dust and noise, adversely affecting the environment and operator health. Furthermore, for waste with a high moisture content (such as wet straw), direct pulverization can cause equipment clogging or increased energy consumption.

[0005] To overcome these challenges, researchers and companies have recently begun exploring new pulverization technologies and equipment. For example, improvements in blade design and optimized pulverization chamber structure can improve pulverizer adaptability to different waste textures. Enclosed pulverization systems can also reduce dust and noise emissions. Furthermore, developing pre-drying or pre-treatment devices to reduce waste moisture content can effectively improve pulverization efficiency.

[0006] Although pulverizers have made significant progress in agricultural waste treatment, current research has focused on optimizing equipment performance and improving processes, with less attention paid to the impact of the pulverization process on the subsequent utilization of waste. For example, how the size, shape, and surface characteristics of pulverized particles affect composting, fermentation efficiency, or energy conversion efficiency still requires further exploration.

[0007] In addition, how to reduce energy consumption and environmental impact during the crushing process, and how to synergistically optimize it with other treatment processes (such as composting, anaerobic fermentation, etc.) are also important directions for future research.

[0008] While existing pulverizers have made some progress in agricultural waste treatment, most still suffer from low pulverization efficiency, high energy consumption, high maintenance costs, and poor adaptability to complex materials. These issues limit their application in large-scale resource utilization. Therefore, a more efficient, energy-saving, and intelligent pulverizer is needed to address these issues. To address these issues, the present invention provides a highly efficient and energy-saving pulverizer based on intelligent control and optimization to address these issues. Summary of the Invention

[0009] The purpose of the present invention is to solve the problems of low crushing efficiency, unstable crushing effect, high maintenance cost and low equipment operation reliability in the prior art.

[0010] In order to achieve the above object, the present invention provides the following basic scheme:

[0011] A high-efficiency and energy-saving pulverizer based on intelligent control and optimization, comprising a pulverizer body and a control and optimization system based on the pulverizer body;

[0012] The control and optimization system includes a real-time monitoring and adaptive adjustment system, a big data analysis and optimization system, an automatic maintenance system, and a fault diagnosis system;

[0013] Real-time monitoring and adaptive adjustment system: real-time monitoring and adjustment of the operating status of the crusher through sensors;

[0014] Big data analysis and optimization system: Analyze the historical operation data of the crusher itself and establish the crusher operation model and material crushing model;

[0015] Automatic maintenance system: adopts a timed and quantitative method to accurately deliver lubricating oil to each lubrication point through the oil pump to ensure that the transmission parts and bearings of the grinder body are well lubricated;

[0016] Fault diagnosis system: By monitoring the changes in the running parts in the crusher body, it can determine whether the running parts are overheating or overloading.

[0017] Furthermore, the pulverizer body includes a pulverizing chamber, a feed port connected to the pulverizing chamber, a variable frequency screw conveyor configured for use with the feed port, a conveying pipe connected to the pulverizing chamber, a motor for driving the variable frequency screw conveyor, and a blade rotating pulverizing assembly arranged in the pulverizing chamber.

[0018] Furthermore, it also includes a collecting cylinder arranged at the output end of the conveying pipeline.

[0019] Furthermore, the real-time monitoring and adaptive adjustment system includes an Adam optimizer, a first humidity sensor, a second humidity sensor, a first temperature sensor, a first vibration sensor, a first pressure sensor, a second temperature sensor and a material particle size sensor, the second temperature sensor is installed on the motor, the first humidity sensor and the second humidity sensor are installed in the feed port and the crushing chamber respectively, the first vibration sensor and the first pressure sensor and the first temperature sensor are installed in the crushing chamber, the Adam optimizer has a built-in learning rate optimization algorithm module, the learning rate optimization algorithm module can record the sensor data of all sensors and form a model, the material particle size sensor is arranged near the blade rotating crushing assembly to monitor the material crushing particle size of the blade rotating crushing assembly, and a second pressure sensor is also provided, and the second pressure sensor is arranged in the feed port.

[0020] Furthermore, the big data analysis and optimization system is used in conjunction with the Adam optimizer in the real-time monitoring and adaptive adjustment system. The big data analysis and optimization system includes a human-machine interface arranged outside the crushing chamber and a processing chip with a built-in human-machine interface. The processing chip processes the data in the Adam optimizer, and the data includes operating parameters, material characteristics, and energy consumption data.

[0021] Furthermore, the automatic maintenance system includes a first cleaning brush, a second cleaning brush, an oil pump and an oil pump conduit and an ultrasonic liquid level sensor. The ultrasonic liquid level sensor detects the oil level inside the oil pump. After the oil pump is connected to the oil pump conduit, it delivers the lubricating oil to the transmission components of the grinder body. The transmission components of the grinder body include a variable frequency screw conveyor and a motor and a drive in the blade rotation crushing assembly. The first cleaning brush and the second cleaning brush are respectively installed at the input end and the output end of the conveying pipeline. The first cleaning brush and the second cleaning brush are both electrically driven.

[0022] Furthermore, the automatic maintenance system further includes a timer and a controller electrically connected to the timer, and the controller is connected to the oil pump signal.

[0023] Furthermore, the fault diagnosis system includes a central controller and a diagnostic module and a data collection module connected to the central controller. The diagnostic module monitors the operating status of the equipment in real time and collects equipment operating data in real time through the data collection module. After the data collection module is connected to the real-time monitoring and adaptive adjustment system, it collects data from sensors in the real-time monitoring and adaptive adjustment system. The central controller has a built-in fault diagnosis model, which quickly identifies and locates the fault point and automatically adjusts the operating parameters according to the fault type.

[0024] Furthermore, it also includes a cloud platform, which is connected to the fault diagnosis system.

[0025] The principle and effect of this solution are:

[0026] 1. Compared to existing technologies, the present invention utilizes multiple high-precision sensors installed within the pulverizing chamber, including a first pressure sensor, a temperature sensor, and a first vibration sensor, to collect key operational data during the pulverizing process in real time. These sensors are able to keenly perceive changes in the material's physical properties and the equipment's operating status. Specifically, the system automatically reduces the feed rate and adjusts the pulverizing speed to restore the motor current to a reasonable range. This process not only ensures stable operation of the equipment but also achieves energy-saving operation by optimizing operating parameters. In this way, the intelligent control system monitors and adjusts the pulverizing process in real time, improving the equipment's operating efficiency and reliability while reducing energy consumption.

[0027] 2. Compared to existing technologies, this system, through in-depth mining and analysis of massive amounts of material pulverization data, automatically calculates and recommends the most appropriate pulverization process parameter combinations based on different material characteristics. These parameters, including key indicators such as pulverization speed, feed rate, and cutter clearance, are designed to achieve maximum pulverization efficiency and minimize energy consumption. After the system generates the recommended parameters, the operator simply confirms them and directly applies them to the actual pulverization process, significantly improving the equipment's operating efficiency and stability while reducing the time and effort required for manual commissioning.

[0028] 3. Compared to existing technologies, the automatic maintenance system's lubrication and cleaning functions achieve highly efficient, coordinated operation through intelligent control. The lubrication system employs a timed and quantitative lubrication strategy, utilizing a high-precision oil pump and intelligent control system to precisely deliver lubricant to critical lubrication points on the equipment, such as transmission components and bearings. The system automatically sets the lubrication cycle and lubrication volume based on the equipment's cumulative operating time and workload, ensuring even and appropriate distribution of lubricant to each lubrication point. Furthermore, the system is equipped with a lubricant level monitoring device. When the lubricant level falls below the set value, it automatically alerts the operator to replenish the lubricant promptly, ensuring the proper operation of the lubrication system. Furthermore, the cleaning system utilizes highly efficient cleaning brushes, specifically designed for the unique structure of the crushing chamber and discharge port. During breaks in the equipment's operation, the cleaning system automatically activates, penetrating deep into the crushing chamber and discharge port to remove any remaining material. Regular cleaning effectively prevents material accumulation and blockage, thereby preventing corrosion and performance degradation caused by residual material. The entire cleaning process is fully automated, requiring no human intervention, significantly reducing maintenance workload and operator workload.

[0029] 4. Compared to existing technologies, this invention analyzes multiple data sources, such as vibration, temperature, and current, generated during equipment operation in real time. When abnormal data is detected, the system can quickly and accurately identify the fault type and location and immediately issue an alarm. Furthermore, by monitoring changes in motor temperature and current, the system can predict whether the motor is at risk of overheating or overloading. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0031] Figure 1 A schematic structural diagram of a pulverizer body in a high-efficiency energy-saving pulverizer based on intelligent control and optimization proposed in an embodiment of the present application is shown;

[0032] Figure 2 A schematic diagram showing the basic principles of control and optimization in a high-efficiency energy-saving grinder based on intelligent control and optimization proposed in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0033] In order to further illustrate the technical means and effects adopted by the present invention to achieve the predetermined purpose of the invention, the specific implementation methods, structures, features and effects of the present invention are described in detail below in conjunction with the accompanying drawings and preferred embodiments.

[0034] The figure marks in the drawings of the specification include: feed port 1, first humidity sensor 2, first temperature sensor 3, second humidity sensor 4, blade rotation crushing assembly 5, first vibration sensor 6, human-machine interface 7, second temperature sensor 8, motor 9, current sensor 10, voltage sensor 11, second vibration sensor 12, second pressure sensor 13, first pressure sensor 14, first pressure sensor 15, first cleaning brush 16, material particle size sensor 17, variable frequency screw conveyor 18, conveying pipeline 19, discharge port 20, second cleaning brush 21, oil pump 22, ultrasonic liquid level sensor 23.

[0035] Implementation example Figure 1 and Figure 2 Shown: A high-efficiency and energy-saving pulverizer based on intelligent control and optimization, including a pulverizer body and a control and optimization system based on the pulverizer body;

[0036] The control and optimization system includes a real-time monitoring and adaptive adjustment system, a big data analysis and optimization system, an automatic maintenance system, and a fault diagnosis system;

[0037] Real-time monitoring and adaptive adjustment system: real-time monitoring and adjustment of the operating status of the crusher through sensors;

[0038] Big data analysis and optimization system: Analyze the historical operation data of the crusher itself and establish the crusher operation model and material crushing model;

[0039] Automatic maintenance system: adopts a timed and quantitative method to accurately deliver lubricating oil to each lubrication point through the oil pump 22, ensuring that the transmission parts and bearings of the grinder body are well lubricated;

[0040] Fault diagnosis system: By monitoring the changes in the running parts in the crusher body, it can determine whether the running parts are overheating or overloading.

[0041] About the crusher body, such as Figure 2 As shown, the pulverizer body includes a pulverizing chamber, a feed port 1 connected to the pulverizing chamber, a variable frequency screw conveyor 18 configured for use with the feed port 1, a conveying pipe 19 connected to the pulverizing chamber, a motor 9 for driving the variable frequency screw conveyor 18, and a blade rotating pulverizing assembly 5 provided in the pulverizing chamber;

[0042] It also includes a collecting cylinder arranged at the output end of the delivery pipeline 19.

[0043] Specifically: the variable frequency screw conveyor 18 is driven by the motor 9 to transport the material. The material is transported to the top of the feed port 1 and enters the crushing chamber. The blades in the crushing chamber rotate and the crushing assembly 5 crushes the material. The crushed material enters the conveying pipe 19 and enters the collection cylinder.

[0044] In order to realize the control and optimization of the pulverizer body, this case proposes a control and optimization system based on the pulverizer body settings;

[0045] The details are as follows:

[0046] The real-time monitoring and adaptive adjustment system includes an Adam optimizer, a first humidity sensor 2, a second humidity sensor 4, a first temperature sensor 3, a first vibration sensor 6, a first pressure sensor 14, a second temperature sensor 8 and a material particle size sensor 17. The second temperature sensor 8 is installed on the motor 9, the first humidity sensor 2 and the second humidity sensor 4 are respectively installed in the feed port 1 and the crushing chamber, the first vibration sensor 6, the first pressure sensor 14 and the first temperature sensor 3 are installed in the crushing chamber, the Adam optimizer has a built-in learning rate optimization algorithm module, the learning rate optimization algorithm module can record the sensor data of all sensors and form a model, the material particle size sensor 17 is arranged near the blade rotating crushing assembly 5 for monitoring the material crushing particle size of the blade rotating crushing assembly 5; a second pressure sensor 13 is also provided, and the second pressure sensor 13 is arranged in the feed port 1.

[0047] For example:

[0048] Among the sensor parameters, the first temperature sensor 3 and the second temperature sensor 8: the measuring range is -20℃~+150℃, the accuracy is ±0.5℃, and the response time is <1 second; the first humidity sensor 2 and the second humidity sensor 4: the measuring range is 0%~100%RH, the accuracy is ±2%RH, and the response time is <2 seconds; the material particle size sensor 17: the measuring range is 0.1mm~50mm, the accuracy is ±0.1mm, and the sampling frequency is 10 times / second; the first vibration sensor 6: the measuring range is 0~20g, the accuracy is ±0.1g, and the sampling frequency is 100 times / second; the first pressure sensor 14: the measuring range is 0~1 MPa, accuracy is ±0.5% FS, response time <1 second. In addition, among the adaptive adjustment parameters, speed adjustment: the speed adjustment range is 500rpm~3000rpm, the accuracy is ±1rpm, and the adjustment frequency is real-time based on the feedback of the material particle size sensor 17; feed amount adjustment: the feeding device is a variable frequency screw conveyor 18, the feed speed range is 0.1kg / s~5kg / s, the accuracy is ±0.01kg / s, and the adjustment frequency is real-time (based on temperature, humidity, and particle size sensor feedback); crushing time adjustment: the time range is 10 seconds to 300 seconds, the accuracy is ±0.1 second, and the adjustment frequency is real-time (based on particle size sensor feedback).

[0049] The data source of the learning rate optimization algorithm module in the Adam optimizer is historical operation data (temperature, humidity, particle size, energy consumption). The learning cycle is to automatically update the model after each run. The optimization goal is to minimize energy consumption and maximize crushing efficiency.

[0050] The big data analysis and optimization system is used in conjunction with the Adam optimizer in the real-time monitoring and adaptive adjustment system. The big data analysis and optimization system includes a human-machine interface 7 arranged outside the crushing chamber and a processing chip with a built-in human-machine interface 7. The processing chip processes the data in the Adam optimizer, and the data includes operating parameters, material characteristics, and energy consumption data.

[0051] Specifically:

[0052] The system collects and analyzes a large amount of operating data, including equipment operating parameters, material characteristics, energy consumption data, etc., and uses advanced data analysis algorithms and machine learning models to conduct in-depth analysis and optimization of the equipment's operating status. The system can identify potential performance bottlenecks and energy waste points and provide optimization suggestions. For example, by analyzing historical data, if the system finds that energy consumption is high during a certain period of time, it will automatically adjust the crusher's operating mode, optimize the feed speed and crushing parameters, and thus reduce energy consumption. In addition, the system also supports remote monitoring and data analysis. Users can view the equipment's operating data in real time through the cloud platform and make remote adjustments based on the analysis results to achieve intelligent management and optimization;

[0053] The automatic maintenance system includes a first cleaning brush 16, a second cleaning brush 21, an oil pump 22, an oil pump 22 conduit and an ultrasonic liquid level sensor 23. The ultrasonic liquid level sensor 23 detects the oil level inside the oil pump 22. After the oil pump 22 is connected to the oil pump 22 conduit, the lubricating oil is transported to the transmission components of the grinder body. The transmission components of the grinder body include a variable frequency screw conveyor 18, a motor 9 and a drive in the blade rotation crushing assembly 5. The first cleaning brush 16 and the second cleaning brush 21 are respectively installed at the input and output ends of the conveying pipe 19. The first cleaning brush 16 and the second cleaning brush 21 are both electrically driven.

[0054] Specifically:

[0055] It is mainly divided into wear detection module, automatic lubrication module and automatic cleaning module. Set the wear monitoring module parameters: the blade wear threshold is 0.5mm, the bearing vibration threshold is ≥5g, the transmission component displacement threshold is ≥0.3mm, the real-time monitoring frequency is 10 samples per second, and the data update frequency is once per minute; set the automatic lubrication module parameters: the initial setting is automatic lubrication once every 8 hours of operation, and it is automatically adjusted according to the operating time and ambient temperature. The lubrication amount each time is 0.5ml (blade position) and 1.0ml (bearing position). The oil pump 22 type is a micro gear pump, the oil pump 22 flow rate is 0.5mL / s, the oil pump 22 pressure is 0.5MPa, and the lubricating oil level monitoring device is an ultrasonic level monitoring device. Sensor 23, the liquid level alarm threshold is to alarm when it is lower than 10% of the liquid level, the response time is <1 second, and the lubrication accuracy is ±0.1ml; set the self-cleaning module parameters: the initial setting is to automatically clean once every 12 hours of operation, the cleaning intensity is adjustable, the cleaning time is 3 minutes each time, the cleaning brush is driven by a micro motor 9 (power: 50W, speed: 1000rpm), the cleaning brush stroke is to cover the inside of the crushing chamber and the discharge port 20, the cleaning monitoring is to monitor the cleaning effect through a photoelectric sensor, and the response time is <2 seconds; the automatic maintenance system also includes a timer and a controller electrically connected to the timer, and the controller is connected to the oil pump 22 signal.

[0056] The fault diagnosis system includes a central controller and a diagnostic module and a data collection module connected to the central controller. The diagnostic module monitors the operating status of the equipment in real time and collects equipment operating data in real time through the data collection module. After the data collection module is connected to the real-time monitoring and adaptive adjustment system, it collects data from sensors in the real-time monitoring and adaptive adjustment system. The central controller has a built-in fault diagnosis model, which can quickly identify and locate the fault point and automatically adjust the operating parameters according to the fault type.

[0057] Specifically, the system monitors the equipment's operating status in real time through a variety of sensors and diagnostic modules. These sensors collect real-time operating data, including temperature, pressure, vibration, current, and voltage. Current sensor 10 and a second vibration sensor 12 are positioned on motor 9. A fault diagnosis model is constructed using a deep learning algorithm, enabling rapid identification and location of fault points. This model automatically adjusts operating parameters based on the fault type, such as reducing speed and feed rate. Furthermore, the system connects to a remote technical support team via a cloud platform, enabling users to quickly access professional technical support in the event of complex faults, ensuring rapid recovery and normal operation of the equipment. Sensor parameters include: Current sensor 10: measurement range 0-50A, accuracy ±0.1A, sampling frequency 10 times / second; Voltage sensor 11: measurement range 0-400V, accuracy ±0.5V, sampling frequency 10 times / second.

[0058] The material enters the grinding chamber from the feed port 1. The material is gradually crushed by the grinding device, and the particle size gradually decreases. The material then enters the big data analysis and optimization system for further processing parameter adjustment to ensure the best grinding effect. The crushed material is cleaned and screened by the automatic maintenance system, and the solid material is discharged through the conveying pipe 19. The end of the conveying pipe 19 is provided with a discharge port 20. The exterior of the grinder body, the interior walls, and all interfaces are coated with a wear-resistant and anti-corrosion coating to ensure the long-term stable operation of the equipment.

[0059] After the material enters the crushing chamber, the real-time monitoring and adaptive adjustment system monitors the material status and automatically adjusts the parameters. After entering the crushing chamber, the data analysis and optimization system establishes the most suitable crushing model based on big data to ensure crushing efficiency and smooth material discharge. At the same time, the automatic maintenance system lubricates and cleans the various components in the crusher to ensure the normal and efficient operation of the equipment. If the equipment fails during the later operation, the fault diagnosis system will feedback the fault problem to the human-machine interface7.

[0060] The present invention solves the problems of low crushing efficiency, unstable crushing effect, high maintenance cost and low equipment operation reliability in the prior art.

[0061] The above description is merely a preferred embodiment of the present invention and does not constitute any form of limitation to the present invention. Although the present invention has been disclosed as a preferred embodiment as above, it is not intended to limit the present invention. Any person skilled in the art can make some changes or modifications to equivalent embodiments using the technical contents disclosed above without departing from the scope of the technical solution of the present invention. However, any simple modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention are still within the scope of the technical solution of the present invention.

Claims

1. A high-efficiency and energy-saving pulverizer based on intelligent control and optimization, characterized in that: It includes a crusher body and a control and optimization system based on the crusher body; The control and optimization system includes a real-time monitoring and adaptive adjustment system, a big data analysis and optimization system, an automatic maintenance system, and a fault diagnosis system; Real-time monitoring and adaptive adjustment system: real-time monitoring and adjustment of the operating status of the crusher through sensors; Big data analysis and optimization system: Analyze the historical operation data of the crusher itself and establish the crusher operation model and material crushing model; Automatic maintenance system: adopts a timed and quantitative method to accurately deliver lubricating oil to each lubrication point through the oil pump to ensure that the transmission parts and bearings of the grinder body are well lubricated; Fault diagnosis system: By monitoring the changes in the running parts in the crusher body, it can determine whether the running parts are overheating or overloading.

2. The high-efficiency energy-saving pulverizer based on intelligent control and optimization according to claim 1 is characterized in that: The pulverizer body includes a pulverizing chamber, a feed port connected to the pulverizing chamber, a variable frequency screw conveyor configured for use with the feed port, a conveying pipe connected to the pulverizing chamber, a motor for driving the variable frequency screw conveyor, and a blade rotating pulverizing assembly arranged in the pulverizing chamber.

3. The high-efficiency energy-saving pulverizer based on intelligent control and optimization according to claim 2 is characterized in that: The device also includes a collecting cylinder arranged at the output end of the conveying pipeline.

4. The high-efficiency energy-saving pulverizer based on intelligent control and optimization according to claim 2 is characterized in that: The real-time monitoring and adaptive adjustment system includes an Adam optimizer, a first humidity sensor, a second humidity sensor, a first temperature sensor, a first vibration sensor, a first pressure sensor, a second temperature sensor and a material particle size sensor, wherein the second temperature sensor is installed on the motor, the first humidity sensor and the second humidity sensor are installed in the feed port and the crushing chamber respectively, the first vibration sensor, the first pressure sensor and the first temperature sensor are installed in the crushing chamber, the Adam optimizer is equipped with a built-in learning rate optimization algorithm module, the learning rate optimization algorithm module can record the sensor data of all sensors and form a model, and the material particle size sensor is arranged close to the blade rotating crushing assembly to monitor the material crushing particle size of the blade rotating crushing assembly.

5. The high-efficiency energy-saving pulverizer based on intelligent control and optimization according to claim 4 is characterized in that: The big data analysis and optimization system is used in conjunction with the Adam optimizer in the real-time monitoring and adaptive adjustment system. The big data analysis and optimization system includes a human-machine interface arranged outside the crushing chamber and a processing chip with a built-in human-machine interface. The processing chip processes the data in the Adam optimizer, and the data includes operating parameters, material characteristics, and energy consumption data.

6. The high-efficiency energy-saving pulverizer based on intelligent control and optimization according to claim 5, characterized in that: The automatic maintenance system includes a first cleaning brush, a second cleaning brush, an oil pump, an oil pump conduit, and an ultrasonic liquid level sensor. The ultrasonic liquid level sensor detects the oil level inside the oil pump. After the oil pump is connected to the oil pump conduit, it delivers lubricating oil to the transmission component of the pulverizer body. The transmission component of the pulverizer body includes a variable frequency screw conveyor and a drive in the motor and blade rotation pulverizing assembly. The first cleaning brush and the second cleaning brush are respectively installed at the input end and the output end of the conveying pipeline. The first cleaning brush and the second cleaning brush are both electrically driven.

7. The high-efficiency energy-saving pulverizer based on intelligent control and optimization according to claim 6, characterized in that: The automatic maintenance system further includes a timer and a controller electrically connected to the timer, and the controller is connected to the oil pump signal.

8. The high-efficiency energy-saving pulverizer based on intelligent control and optimization according to claim 7, characterized in that: The fault diagnosis system includes a central controller and a diagnostic module and a data collection module connected to the central controller. The diagnostic module monitors the operating status of the equipment in real time and collects equipment operating data in real time through the data collection module. The data collection module is connected to the real-time monitoring and adaptive adjustment system to collect data from sensors in the real-time monitoring and adaptive adjustment system. The central controller has a built-in fault diagnosis model, which quickly identifies and locates the fault point and automatically adjusts the operating parameters according to the fault type.

9. The high-efficiency energy-saving pulverizer based on intelligent control and optimization according to claim 8, characterized in that: It also includes a cloud platform, which is connected to the fault diagnosis system.

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