Coal flow detection system and control method thereof

Abstract

The invention relates to a coal flow detection system and a control method thereof, and the system is characterized in that the system specifically comprises the following modules: a weighing detection module, a speed detection module, a temperature compensation module, a data processing module, a communication module, an alarm module, a power management module and a display module; the weighing detection module is connected with a differential input interface of the data processing module through a full-bridge strain circuit; the speed detection module is connected with a timer capture unit of the data processing module through an orthogonal encoder interface; the temperature compensation module is connected with a sensor interface of the data processing module through a digital bus; the data processing module communicates with the communication module and the display module through a high-speed serial interface; the alarm module is connected with the data processing module through an isolated digital output interface. The problem that an existing detection method only depends on single weighing or speed measurement, the actual situation of the coal flow cannot be comprehensively and accurately reflected, and consequently the measurement result error is large is solved.

Description

Technical Field

[0001] The present invention relates to, in particular to a coal flow detection system and a control method thereof. Background Art

[0002] Accurately measuring coal flow is crucial during coal production, transportation, and processing. Precise coal flow measurement not only helps optimize production processes and improve efficiency, but also ensures safe equipment operation, preventing equipment damage or production accidents caused by abnormal flow.

[0003] Traditional coal flow detection methods have many drawbacks. Some rely solely on single weighing or speed measurements, which cannot fully and accurately reflect the actual coal flow situation, resulting in large errors in the measurement results. Moreover, in complex industrial environments, factors such as temperature and vibration can significantly affect measurement accuracy, and traditional methods lack effective compensation and anti-interference measures. In addition, the data processing capabilities of traditional systems are limited, making it difficult to achieve real-time and efficient data analysis and processing, and unable to meet the high requirements of modern coal production for flow detection. Therefore, the development of a high-precision, high-reliability, multi-functional coal flow detection system that can adapt to complex environments is of great practical significance. Summary of the Invention

[0004] To address the challenges of the existing technology, the present invention provides a coal flow detection system and control method. This system primarily consists of a weighing detection module, a speed detection module, a temperature compensation module, a data processing module, a communication module, an alarm module, a power management module, and a display module. These modules work together through specific interfaces and connections to achieve precise detection, processing, transmission, and display of coal flow.

[0005] The weighing detection module includes a strain gauge load cell with a range of 0 to 50 tons to meet the needs of coal transportation scenarios of varying scales. Nonlinear error is strictly controlled to within ±0.05% of full scale, and creep error is within ±0.02% of full scale every 30 minutes, ensuring long-term measurement stability. The excitation voltage uses a DC range of 5V to 10V, providing stable operating conditions for the sensor and guaranteeing accurate and reliable output signals.

[0006] The signal amplifier features a gain adjustment capability of 100x to 1000x, allowing for flexible adjustments based on the actual measured signal strength to ensure the appropriate signal amplitude for subsequent processing. Its common-mode rejection ratio and bandwidth common-mode rejection ratio are both no less than 120dB, effectively suppressing common-mode interference signals and improving signal purity. Its bandwidth covers 0 to 200 Hz, accurately capturing the frequency range of weighing signals.

[0007] The overload protection structure has a mechanical bearing capacity of not less than 150% of the rated load, which can protect the sensor from damage in overload conditions and extend the service life of the sensor. It is equipped with an anti-lateral force guide device to avoid the influence of lateral force on weighing accuracy and ensure the accuracy of measurement results.

[0008] The speed detection module includes an incremental rotary encoder with an output pulse count of 500 to 1024 per revolution. The appropriate pulse count can be selected based on actual needs for more accurate speed measurement. The response frequency is no less than 100 kHz, enabling rapid response to changes in conveyor belt speed. The axial and radial load capacity is no less than 50 Newtons, adapting to various load conditions generated during conveyor belt operation and ensuring the encoder's proper operation.

[0009] The anti-vibration mounting bracket has a natural frequency of at least 200 Hz, effectively reducing the impact of vibration on the encoder and improving measurement stability. The IP67 protection rating ensures excellent dust and water resistance, making it suitable for harsh industrial environments. The speed conversion unit calculates the conveyor belt's linear speed using a pulse counting and time window method. By accurately measuring the number of pulses and the time interval, it calculates the actual linear speed of the conveyor belt. The minimum resolution reaches 0.001 meters per second, meeting the requirements of high-precision speed measurement.

[0010] The temperature compensation module includes a non-contact infrared temperature measurement unit with a spectral response range of 8 to 14 microns, capable of accurately measuring infrared radiation within this band. Within the temperature range of -40°C to +120°C, the temperature measurement accuracy is within ±1°C, providing accurate ambient temperature data for temperature compensation. With a sampling period of 100 milliseconds, it can quickly capture ambient temperature changes and promptly apply temperature compensation to measurement results.

[0011] The contact-type platinum resistance temperature measurement unit has a temperature measurement range of -50°C to +300°C, making it suitable for measuring device surface temperatures under various temperature conditions. With a thermal response time of less than 5 seconds, it can quickly respond to temperature changes. The multi-source data fusion unit uses a dynamic filtering algorithm to compensate for temperature drift in real time, fusing data from non-contact and contact temperature measurement units. It dynamically adjusts compensation parameters based on changes in ambient and device surface temperatures, improving measurement accuracy.

[0012] The data processing module includes an analog front-end circuit with an input impedance of no less than 1 gigaohm to minimize the impact on the input signal. The noise density does not exceed 10 nanovolts per square root hertz, reducing circuit noise interference and improving signal quality. The programmable gain amplifier supports dynamic adjustment from 1x to 1000x, automatically adjusting the gain based on the input signal strength to ensure that the signal remains within the appropriate range for subsequent processing. The high-precision analog-to-digital converter has a resolution of no less than 24 bits and an effective number of bits of no less than 21, accurately converting analog signals into digital signals. The integral nonlinearity error does not exceed plus or minus 2 microvolts per volt, ensuring the accuracy of the digital signal.

[0013] The embedded processor features a built-in hardware floating-point unit (FPU) for faster floating-point operations. It supports direct memory access (DMA) data transfer, reducing data transfer overhead. With an instruction execution efficiency of at least 1.25 million instructions per MHz, it can rapidly process large amounts of data and complex algorithms.

[0014] The communication module includes a 4G LTE communication unit, which supports the first-class communication standard. The operating frequency band covers 700 MHz to 2.6 GHz and can adapt to the network frequency bands of different regions and operators. The maximum transmission power is 23 dBm, ensuring the signal transmission quality over longer distances.

[0015] The industrial fieldbus interface complies with the RS-485 standard and supports networking of at least 256 nodes, making it suitable for communication between multiple devices in industrial sites. The transmission rate can be configured from 9.6 kilobits per second to 10 megabits per second, allowing for flexible adjustment based on actual communication needs. The protocol conversion unit enables bidirectional conversion between Modbus RTU and TCP / IP protocols, facilitating communication between devices with different protocols. Data verification uses a 32-bit cyclic redundancy check algorithm to ensure the accuracy and integrity of data transmission.

[0016] The alarm module includes a multi-level sound and light alarm unit. The sound alarm frequency range is 2 kHz to 4 kHz, which has strong penetration and can attract the attention of operators in noisy environments; the light alarm uses a red light-emitting diode with a wavelength of 625 nanometers and a flash intensity of not less than 2000 millicandela, which can be clearly seen at a long distance.

[0017] The safety interlock relay's contact switching time is less than 10 milliseconds, quickly disconnecting faulty circuits. Its electrical lifespan is at least one million cycles, ensuring long-term, reliable operation. An arc suppression circuit reduces arcing during contact switching, extending the relay's lifespan. Different alarm levels are triggered based on the percentage difference between the flow rate deviation and the set value. For example, a warning signal is issued when the deviation is within 10%, and an emergency alarm is issued when the deviation exceeds 20%, improving the accuracy and timeliness of alarms.

[0018] The power management module includes a wide-range input AC-DC conversion unit with an input voltage of 85V to 264V AC and a frequency adaptability of 47Hz to 63Hz, which can adapt to grid voltage and frequency fluctuations in different regions; the surge protection capability is not less than 4kV, effectively preventing surge voltage in the grid from damaging the system.

[0019] The multi-channel isolated DC-DC conversion unit features an output ripple peak-to-peak of less than 50 millivolts, providing stable DC power to each module. Load regulation is within ±0.5%, ensuring output voltage stability under varying loads. Overvoltage and undervoltage protection automatically cuts off power when the output voltage exceeds or falls below the set value, protecting the modules from damage. The dynamic power consumption monitoring unit, with a sampling rate of 1 kHz, generates real-time energy consumption curves for each module's current consumption, enabling managers to understand the system's energy consumption and implement energy-saving management.

[0020] The display module includes an industrial-grade thin-film transistor liquid crystal display with a brightness of no less than 400 candelas per square meter and a contrast ratio of no less than 800:1. It can clearly display data under different lighting conditions; the viewing angle is no less than 170 degrees, which is convenient for operators to view from multiple angles.

[0021] The capacitive touch screen supports simultaneous recognition of no less than 10 touch points, with a response time of no more than 15 milliseconds and sensitive operation; the surface hardness is no less than 7H level and is not easily scratched; the data visualization unit supports three-dimensional trend chart display and historical data playback functions, with a screen refresh rate of no less than 30 frames per second, which can intuitively display the changing trends and historical data of coal flow, facilitating analysis and decision-making by operators.

[0022] When the system is started up, each module performs a self-test to check whether the hardware circuits are functioning properly and whether the software programs are running normally. After the self-test is completed, the communication module reports a status code to the remote monitoring system and the local display module, informing the system of the working status of each module. The weighing detection module acquires the raw weight signal at a sampling rate of 200 Hz and transmits the weight signal to the data processing module via a full-bridge strain gauge circuit. The speed detection module counts pulses in real time using an incremental rotary encoder, calculates the real-time speed of the conveyor belt based on the number of pulses and time intervals, and transmits the speed data to the data processing module via the orthogonal encoder interface. The temperature compensation module simultaneously collects ambient temperature and equipment surface temperature data. The non-contact infrared temperature measurement unit and the contact platinum resistance temperature measurement unit transmit the temperature data to the data processing module via the digital bus.

[0023] The data processing module compensates for temperature drift in the received weight signal. Based on the temperature data provided by the temperature compensation module, a corresponding compensation algorithm is used to eliminate the effects of temperature on weight measurement. The weight signal is also digitally filtered to remove high-frequency interference. The instantaneous flow rate is calculated by multiplying the effective weight value by the conveyor belt speed, combined with the effective weighing section length. The calculation formula is: Instantaneous flow rate = Effective weight value × Conveyor belt speed / Effective weighing section length. A sliding average algorithm is used to generate a flow rate trend curve, averaging the instantaneous flow values ​​over a period of time to determine the flow rate trend, allowing operators to understand flow rate fluctuations.

[0024] The flow data is uploaded to the remote monitoring system through the communication module, which allows management personnel to remotely monitor the real-time situation of coal flow. When the system detects an abnormal state, such as flow deviation exceeding the set value or temperature abnormality, the alarm module triggers the corresponding alarm signal and generates an event log to record the time and type of the abnormality. The display module dynamically updates the real-time data interface, and displays data such as weight, speed, flow, and temperature to the operator in an intuitive manner, while displaying alarm information and flow change trend curves.

[0025] The system executes the above steps in a cycle of 100 milliseconds to ensure the real-time and continuity of the system and timely reflect the changes in coal flow.

[0026] The beneficial effects of this invention are as follows: Through the collaborative operation of various modules, this system achieves high-precision coal flow detection, real-time processing, reliable transmission, and intuitive display, and includes functions such as temperature compensation and alarm prompts. This effectively improves the accuracy and reliability of coal flow detection, reduces production accidents caused by flow anomalies, improves production efficiency, reduces production costs, and ensures safe and efficient coal production. Furthermore, the system's remote monitoring and data analysis capabilities help enterprises achieve intelligent management and enhance overall management capabilities. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The present invention will be further described below with reference to the accompanying drawings and examples.

[0028] Figure 1 This is a system structure diagram of the present invention.

[0029] Figure 2 It is the workflow diagram of the present invention.

[0030] In the figure: 101, weighing detection module; 102, speed detection module; 103, temperature compensation module; 104, data processing module; 105, communication module; 106, alarm module; 107, power management module; 108, display module. DETAILED DESCRIPTION

[0031] In order to make the technical means, creative features, objectives and effects achieved by the present invention easier to understand, the present invention is further described below in conjunction with specific implementation methods.

[0032] like Figure 1-Figure 2 As shown, the coal flow detection system and control method described in the present invention utilizes a strain gauge load cell with a measuring range of 0 to 50 tons, a nonlinear error controlled within ±0.05% of the full scale, and a creep error within ±0.02% of the full scale per 30 minutes. The load cell is installed below the effective weighing section of the conveyor belt, ensuring that the sensor is perpendicular to the conveyor belt and that the mounting foundation is stable to prevent vibration or tilt from affecting measurement accuracy. A DC excitation voltage of 5 to 10 volts is used to power the sensor, provided by a stable power supply module to ensure the stability of the sensor output signal. The weak signal output by the load cell is connected to a signal amplifier with a gain adjustment capability of 100 to 1000 times. The gain potentiometer is adjusted based on the actual strength of the measured signal to keep the output signal amplitude within an appropriate range. At the same time, ensure the amplifier's common-mode rejection ratio is no less than 120 decibels, with a bandwidth covering 0 to 200 Hz, to effectively suppress common-mode interference signals and accurately capture weighing signals. Install overload protection structures around the load cell, such as cushions and limiters, with a mechanical load capacity of no less than 150% of the rated load. Configure a lateral force guide device, using a combination of guide grooves and rollers, to prevent lateral forces from affecting weighing accuracy.

[0033] Select an incremental rotary encoder with an output pulse count of 500 to 1024 pulses per revolution and a response frequency of at least 100 kHz. Mount it on the conveyor belt's drive roller shaft, tightly connecting it to the roller shaft via a coupling to ensure synchronous rotation between the encoder and the roller. The encoder's axial and radial load capacity must be at least 50 Newtons to accommodate the loads generated during conveyor belt operation. Secure the encoder with a vibration-resistant mounting bracket with a natural frequency of at least 200 Hz and IP67 protection. The bracket is connected to the mounting base via shock-absorbing rubber pads to minimize vibration. Calculate the conveyor belt's linear speed using the pulse counting and time window method. A microcontroller sets a timer interrupt to count encoder pulses within a fixed time window (e.g., 100 milliseconds). Based on the pulse count and time interval, calculate the actual conveyor belt's linear speed using the formula: Conveyor belt linear speed = (number of pulses × roller circumference) / (time window × number of encoder pulses per revolution), with a minimum resolution of 0.001 meters per second.

[0034] A non-contact infrared temperature measurement unit with a spectral response range of 8 to 14 microns and a temperature measurement accuracy of no more than ±1°C within the range of -40°C to +120°C was selected. It was installed above the conveyor belt at an appropriate height (e.g., 0.5 meters) to ensure accurate measurement of the coal temperature on the conveyor belt. A sampling period of 100 milliseconds was set to quickly capture ambient temperature changes. A contact platinum resistance temperature measurement unit with a temperature measurement range of -50°C to +300°C and a thermal response time of less than 5 seconds was used. This unit was mounted on the surface of the weighing sensor, tightly bonded with thermally conductive adhesive, to measure the surface temperature of the equipment. A dynamic filtering algorithm was implemented in the microcontroller to fuse the data from the non-contact and contact temperature measurement units. Compensation parameters were dynamically adjusted based on changes in ambient and equipment surface temperatures to compensate for temperature drift in the weight measurement results.

[0035] Design an analog front-end circuit with an input impedance of at least 1 gigaohm and a noise density of no more than 10 nanovolts per square root hertz. Use a programmable gain amplifier with dynamic gain adjustment from 1x to 1000x, automatically adjusting the gain based on the input signal strength. Select a high-precision analog-to-digital converter with a resolution of at least 24 bits, an effective number of bits of at least 21, and an integral nonlinearity error of no more than ±2 microvolts per volt. Connect the analog signal output from the analog front-end circuit to the analog-to-digital converter for precise digital conversion. Select an embedded processor with a built-in hardware floating-point unit, support for direct memory access data transfer, and an instruction execution efficiency of at least 1.25 million instructions per megahertz. Write a program to implement data acquisition, processing, and storage, including algorithms for temperature compensation and flow calculation.

[0036] Install a 4G LTE communication unit that supports Class I communication standards, operates in the 700 MHz to 2.6 GHz frequency band, and has a maximum transmit power of 23 dBm. Configure communication parameters, such as the access point (APN), username, and password, to ensure network access and enable data communication with the remote monitoring system. Use an industrial fieldbus interface that complies with the RS-485 standard, supports networking of at least 256 nodes, and has a configurable transmission rate of 9.6 kilobits per second to 10 megabits per second. Connect the weighing detection module, speed detection module, and temperature compensation module to the bus to enable data communication between devices. Implement a bidirectional conversion program between the Modbus RTU protocol and the TCP / IP protocol in the embedded processor. Use a 32-bit cyclic redundancy check algorithm to verify data transmission accuracy and integrity.

[0037] Install a multi-level audible and visual alarm unit with an audible alarm frequency range of 2 kHz to 4 kHz and a visual alarm using a red light-emitting diode (LED) with a wavelength of 625 nm and a flash intensity of at least 2000 millicandela. Connect the alarm unit to an embedded processor to trigger the corresponding audible and visual alarms based on the alarm signal. Install a safety interlock relay with a contact switching time of no more than 10 milliseconds, an electrical life of at least one million cycles, and an arc suppression circuit. Connect the relay to the conveyor belt's control circuit to cut off power to the conveyor belt in the event of a critical alarm, ensuring safety. Program intelligent tiered logic in the embedded processor to trigger different levels of alarm based on the percentage difference between the flow rate deviation and the set value. For example, a pre-alarm signal is issued when the deviation is within 10%, controlling the audible and visual alarm unit to sound an intermittent alarm. A critical alarm signal is issued when the deviation exceeds 20%, controlling the audible and visual alarm unit to sound a continuous alarm and triggering the safety interlock relay to cut power.

[0038] A wide-range AC-DC converter unit with an input voltage range of 85 V to 264 V AC, a frequency range of 47 Hz to 63 Hz, and surge protection of at least 4 kilovolts was installed. The AC power supply was connected to the converter unit, which outputs a stable DC voltage to power the system. A multi-channel isolated DC-DC converter unit was used, with a peak-to-peak output ripple of no more than 50 mV, a load regulation of no more than ±0.5%, and overvoltage and undervoltage protection. The DC voltage output from the wide-range AC-DC converter unit was further converted to provide DC power at different voltage levels for each module. A dynamic power consumption monitoring program was implemented in the microcontroller, sampling at a 1 kHz sampling rate in real time for each module's current consumption. This generated an energy consumption curve, which was then uploaded to the remote monitoring system via the communication module.

[0039] Install an industrial-grade thin-film transistor liquid crystal display (TFT-LCD) with a brightness of at least 400 candelas per square meter, a contrast ratio of at least 800:1, and a viewing angle of at least 170 degrees. Connect the display to the embedded processor to display various system data and alarm information. Install a capacitive touch screen that supports simultaneous recognition of at least 10 touch points, a response time of no more than 15 milliseconds, and a surface hardness of at least 7H. Human-computer interaction is achieved through the touch screen, allowing operators to set parameters and view historical data. A data visualization program is written in the embedded processor to support 3D trend charting and historical data playback, with a refresh rate of at least 30 frames per second. Flow data is displayed on the display in an intuitive graphical format, facilitating operator analysis and decision-making.

[0040] When the system starts, each module performs a self-test, checking the hardware circuits for proper function by reading the hardware status register and running the test program to verify the proper functioning of the software. After the self-test is complete, the communication module reports a status code to the remote monitoring system and the local display module, informing the system of the operating status of each module.

[0041] Write data acquisition programs for the weight detection module, speed detection module, and temperature compensation module, acquiring measurement data from each module according to the specified sampling rate and communication protocol. For example, the weight detection module acquires raw weight signals at a sampling rate of 200 Hz, the speed detection module counts pulses and calculates speed in real time, and the temperature compensation module periodically collects ambient temperature and device surface temperature data.

[0042] Implement a temperature compensation algorithm to compensate for temperature drift in the weight signal based on the temperature data provided by the temperature compensation module. Use a digital filtering algorithm to filter the weight signal and remove high-frequency interference. Calculate instantaneous flow using the flow calculation formula, and use a sliding average algorithm to generate a flow trend curve.

[0043] Write a communication program to upload flow data to the remote monitoring system via the communication module. Implement an alarm logic program to trigger corresponding alarm signals and generate event logs when the system detects an abnormal condition. Write a display program to dynamically update the real-time data interface of the display module, displaying weight, speed, flow rate, temperature, and other data in an intuitive manner for operators.

[0044] Data acquisition, data processing, control output and other programs are executed cyclically with a period of 100 milliseconds to ensure the real-time and continuity of the system.

[0045] Check the hardware connections of each module for correctness. Measure parameters such as power supply voltage and signal voltage to ensure they are within normal ranges. Debug sensors, encoders, and other devices individually to ensure their output signals are normal. Use debugging tools to single-step debug the software program to verify program logic and accurate data processing. Debug the communication program to ensure the system can communicate properly with the remote monitoring system and local display module.

[0046] Use standard weights to calibrate the load cell, adjusting the gain and zero point to ensure accurate weight measurement. Use a standard speed source to calibrate the speed detection module, adjusting the pulse count and time parameters to ensure accurate speed measurement. Calibrate the temperature compensation module by comparing the actual temperature with the measured temperature and adjusting the compensation parameters to improve temperature measurement accuracy.

[0047] Through the implementation of the above specific implementation methods and details, this coal flow detection system is capable of high-precision detection, real-time processing, reliable transmission, and intuitive display of coal flow. In practical applications, the system accurately measures coal flow, promptly detects flow anomalies, and issues alarms, effectively improving the safety and efficiency of coal production. Furthermore, the system's temperature compensation function eliminates the effects of temperature on measurement results, improving measurement accuracy. The remote monitoring function allows managers to monitor the real-time status of coal flow at any time, enabling remote management of the coal production process.

[0048] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above and that the invention can be embodied in other specific forms without departing from the spirit or essential characteristics of the invention. Therefore, the embodiments should be considered in all respects as illustrative and non-restrictive, and the scope of the invention is defined by the appended claims, not the foregoing description, and all variations within the meaning and range of equivalents of the claims are intended to be included therein. Any reference sign in a claim should not be construed as limiting the claim to which it relates.

[0049] In addition, it should be understood that although this specification is described in terms of implementation methods, not every implementation method contains only one independent technical solution. This narrative method of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment can also be appropriately combined to form other implementation methods that can be understood by those skilled in the art.

Claims

1. A coal flow detection system and control method thereof, characterized in that: Specifically, it includes the following modules: a weighing detection module (101), a speed detection module (102), a temperature compensation module (103), a data processing module (104), a communication module (105), an alarm module (106), a power management module (107) and a display module (108); The weighing detection module (101) is connected to the differential input interface of the data processing module (104) through a full-bridge strain gauge circuit; the speed detection module (102) is connected to the timer capture unit of the data processing module (104) through an orthogonal encoder interface; the temperature compensation module (103) is connected to the sensor interface of the data processing module (104) through a digital bus; the data processing module (104) communicates with the communication module (105) and the display module (108) through a high-speed serial interface; the alarm module (106) is connected to the data processing module (104) through an isolated digital output interface; and the power management module (107) provides independent power supply for each module through a multi-level isolated power supply network.

2. A coal flow detection system according to claim 1, characterized in that: The weighing detection module (101) comprises: a strain gauge weighing sensor with a measuring range of 0 to 50 tons, a nonlinear error of no more than plus or minus 0.05% of the full scale, a creep error of no more than plus or minus 0.02% of the full scale per 30 minutes, and an excitation voltage of 5 volts to 10 volts DC; a signal amplifier with a gain adjustment range of 100 times to 1000 times, a common mode rejection ratio of no less than 120 decibels, and a bandwidth covering 0 to 200 Hz; an overload protection structure with a mechanical bearing capacity of no less than 150% of the rated load and equipped with an anti-lateral force guide device.

3. A coal flow detection system according to claim 1, characterized in that: The speed detection module (102) includes: an incremental rotary encoder, the number of output pulses per revolution is 500 to 1024, the response frequency is not less than 100 kHz, and the axial and radial load bearing capacity is not less than 50 Newtons; an anti-vibration mounting bracket, the natural frequency is not less than 200 Hz, and the protection level meets the IP67 standard; a speed conversion unit, which calculates the linear speed of the conveyor belt based on the pulse counting and time window method, and the minimum resolution reaches 0.001 meters per second.

4. The coal flow detection system according to claim 1, characterized in that: The temperature compensation module (103) comprises: a non-contact infrared temperature measurement unit, with a spectral response range of 8 to 14 microns, a temperature measurement accuracy error of no more than plus or minus 1 degree Celsius within the range of -40 degrees Celsius to +120 degrees Celsius, and a sampling period of 100 milliseconds; a contact platinum resistance temperature measurement unit, with a temperature measurement range covering -50 degrees Celsius to +300 degrees Celsius, and a thermal response time of less than 5 seconds; and a multi-source data fusion unit, which uses a dynamic filtering algorithm to perform real-time compensation for temperature drift.

5. A coal flow detection system according to claim 1, characterized in that: The data processing module (104) includes: an analog front-end circuit, with an input impedance of not less than 1 gigaohm, a noise density of not more than 10 nanovolts per square root hertz, and a programmable gain amplifier supporting dynamic adjustment from 1 to 1000 times; a high-precision analog-to-digital converter, with a resolution of not less than 24 bits, an effective number of bits of not less than 21 bits, and an integral nonlinear error of not more than plus or minus 2 microvolts per volt; an embedded processor, with a built-in hardware floating-point operation unit, supporting direct memory access data transmission, and an instruction execution efficiency of not less than 1.25 million instructions per megahertz.

6. A coal flow detection system and control method thereof according to claim 1, characterized in that: The communication module (105) includes: a 4G LTE communication unit, supporting the first type of communication standards, with an operating frequency band covering 700 MHz to 2.6 GHz and a maximum transmission power of 23 dBm; an industrial field bus interface, complying with the RS-485 standard, supporting networking of not less than 256 nodes, and a transmission rate configurable to 9.6 kilobits per second to 10 megabits per second; and a protocol conversion unit, realizing bidirectional conversion between the Modbus RTU protocol and the TCP / IP protocol, with data verification using a 32-bit cyclic redundancy check algorithm.

7. A coal flow detection system and control method thereof according to claim 1, characterized in that: The alarm module (106) includes: a multi-level sound and light alarm unit, the sound alarm frequency range is 2 kHz to 4 kHz, the light alarm uses a red light emitting diode with a wavelength of 625 nanometers and a flash intensity of not less than 2000 millicandela; a safety interlock relay, the contact switching time does not exceed 10 milliseconds, the electrical life is not less than one million times, and an arc suppression circuit is configured; and an intelligent grading logic, which triggers different levels of alarms according to the percentage difference between the flow deviation value and the set value.

8. A coal flow detection system and control method thereof according to claim 1, characterized in that: The power management module (107) includes: a wide-range input AC-DC conversion unit, with an input voltage of 85V to 264V AC, a frequency adaption of 47Hz to 63Hz, and a surge protection capability of not less than 4kV; a multi-channel isolated DC-DC conversion unit, with an output ripple peak-to-peak value not exceeding 50mV, a load adjustment rate not exceeding plus or minus 0.5%, and having overvoltage and undervoltage protection functions; and a dynamic power consumption monitoring unit, with a sampling rate of 1kHz, which generates an energy consumption curve of the current consumption of each module in real time.

9. A coal flow detection system and control method thereof according to claim 1, characterized in that: The display module (108) includes: an industrial-grade thin-film transistor liquid crystal display screen with a brightness of not less than 400 candelas per square meter, a contrast ratio of not less than 800 to 1, and a viewing angle of not less than 170 degrees; a capacitive touch screen that supports simultaneous recognition of not less than 10 touch points, a response time of not more than 15 milliseconds, and a surface hardness of not less than 7H level; a data visualization unit that supports three-dimensional trend chart display and historical data playback functions, and a screen refresh rate of not less than 30 frames per second.

10. The coal flow detection system according to any one of claims 1 to 9, characterized in that: The control method includes the following specific stages: S1: Initialization phase: Each module performs self-test and reports status code via the communication module (105); S2: Data collection phase: a. The weighing detection module (101) obtains the original weight signal at a sampling rate of 200 Hz; b. The speed detection module (102) calculates the real-time speed of the conveyor belt by counting the encoder pulses; c. The temperature compensation module (103) synchronously collects ambient temperature and device surface temperature data; S3: Data processing stage: a. Perform temperature drift compensation and digital filtering on the weight signal to eliminate high-frequency interference; b. Calculate the instantaneous flow rate by multiplying the effective weight value by the conveyor belt speed and combining it with the effective weighing section length; c. Use sliding average algorithm to generate flow change trend curve; S4: Control output stage: a. The flow data is uploaded to the remote monitoring system via the communication module (105); b. The abnormal state triggers the alarm module (106) and generates an event log; c. Display module (108) dynamically updates the real-time data interface; S5: The system executes steps (2) to (4) in a loop with a period of 100 milliseconds.

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