A dust monitoring system and method based on underground WiFi6 communication network

Abstract

The present invention discloses a dust monitoring system and method based on an underground WiFi6 communication network, belonging to the field of dust monitoring technology, and the system includes a data acquisition module, a data processing module, a data analysis module, a data transmission module and an early warning module. By setting data acquisition terminals at different locations underground, the coal dust concentration in different areas within the underground range is obtained, the coal dust concentration is monitored and monitored, and a dust concentration change curve and a dust concentration gradient diagram with respect to time and position are generated to determine whether the dust concentration in the underground area exceeds the standard. If it exceeds the threshold, the LED lights up red and alarms at the same time, the monitoring center displays the alarm position, and the radiator works to increase air flow and reduce the dust concentration in the environment; the present invention further discloses a dust monitoring method used in the ESP8266WiFi module dust monitoring system.

Description

Technical Field

[0001] The present invention relates to the field of dust monitoring technology, and specifically to a dust monitoring system and method based on an underground WiFi6 communication network. Background Art

[0002] As an important energy resource, coal plays a very important role in promoting my country's economic development. Coal mining machines will generate a large amount of dust during the underground comprehensive mining operation. The dust will spread everywhere under the action of the underground airflow, which will not only lead to low visibility of the comprehensive mining surface and affect the efficiency and safety of the comprehensive mining operation, but also enter the lungs with the breathing of underground workers, causing "pneumoconiosis", which seriously affects the health of underground workers. When the dust accumulates to a certain concentration, it may even cause an explosion. Dust is one of the main causes of occupational diseases among underground workers. In recent years, the country has continuously attached importance to dust concentration monitoring technology, and the application of dust concentration sensors has become increasingly widespread.

[0003] At present, the main dust sensor used in coal mines is infrared dust sensor, which has the characteristics of easy installation, low cost, small size, etc. It has a wide measurement range, can distinguish smoke and dust in the measurement environment, and is stable and reliable, which is of great significance for feedback of air quality. Although infrared dust sensors have obvious advantages in cost, the detection accuracy of infrared dust sensors has large errors, which affects the detection accuracy and user experience. At the same time, most monitoring systems are based on traditional dust concentration sensors, but due to the backward control method used by this type of sensor, the monitoring range is small, the accuracy is low, and the reliability is insufficient, it can no longer meet the increasingly high requirements of coal comprehensive mining operations. Summary of the invention

[0004] The purpose of the present invention is to provide a dust monitoring system and method based on an underground WiFi6 communication network. The dust monitoring method and system have the advantages of high detection accuracy, small error, strong monitoring continuity and good monitoring effect. Users can view all stored data and realize networking function at the same time, which can solve the problem of online monitoring of dust concentration in the prior art.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] A dust monitoring system based on an underground WiFi6 communication network, comprising:

[0007] A data acquisition module is used to collect dust concentration signals and convert the dust concentration signals into dust concentration values;

[0008] A data processing module is used to analyze the dust concentration value and generate a dust concentration change curve and a dust concentration gradient diagram with respect to time and location;

[0009] The data analysis module is used to determine whether the dust concentration data exceeds the concentration threshold and whether the underground dust situation is normal;

[0010] Data transmission module, which sends the measured data to the PC for display through the ESP8266WiFi module, and stores the measured data in the database;

[0011] The early warning module determines the source of the underground alarm information and controls the underground dust situation.

[0012] As a further solution of the present invention: the data acquisition module includes:

[0013] A laser dust sensor, used to collect the dust concentration optical signal;

[0014] The filter amplifier circuit is used to amplify the collected dust concentration signal and convert it into a digital signal;

[0015] The A / D converter is used to convert the dust signal analog-to-digital into the dust concentration value and transmit it to the data processing module.

[0016] The photoelectric converter and laser diode in the data acquisition module laser dust sensor are the signal transmitting and receiving parts, the filter amplifier circuit amplifies the weak electrical signal and converts it into a digital signal, and inputs the signal into the single-chip processor, and the frequency signal output unit converts the collected dust concentration value into a corresponding frequency signal and outputs it.

[0017] As a further solution of the present invention: the data processing module includes:

[0018] A collection information acquisition unit, used to acquire the collection information sent by the dust monitoring equipment;

[0019] A collection information analysis unit, used to analyze the collection information, generate a dust concentration change curve and a dust concentration gradient diagram of dust concentration with respect to time and position, so as to determine the collection time, collection position and collection concentration of dust;

[0020] A preset comparison unit is used to compare the data in the collected information to determine whether the data representing the dust collection time, collection location and collection concentration conforms to a preset format;

[0021] The dust monitoring unit is used to set the dust monitoring model and determine the dust distribution.

[0022] As a further solution of the present invention: the dust concentration gradient map is to establish a three-dimensional coordinate system of dust concentration with respect to time and position, and generate a dust concentration change curve and a dust concentration gradient map with respect to time and position according to the dust concentration data, dust collection time and collection position obtained by each data collection terminal, and set a dust concentration threshold line in each dust concentration gradient map according to the set dust concentration threshold.

[0023] As a further solution of the present invention: the preset comparison unit is used to compare the data characterizing the dust collection time, collection location and collection concentration with the data of the dust collection time, collection location and collection concentration in the configuration information to determine whether the data characterizing the dust collection time, collection location and collection concentration conforms to the preset format.

[0024] As a further solution of the present invention: the dust monitoring model is obtained by the following method:

[0025] Taking a preset number of collected information as a training sample set, marking the training samples in the training sample set, and marking the distribution of dust at different locations at different times corresponding to the training samples;

[0026] Inputting the training samples in the training sample set into a preset neural network model, learning the training samples in the training sample set, and outputting the distribution status of dust at different locations at different times corresponding to the training samples;

[0027] When the difference between the distribution of dust at different positions at different times corresponding to the output training samples and the distribution of dust at different positions at different times corresponding to the labeled training samples is greater than a preset threshold, the parameters of the convolution layer of the neural network model are modified;

[0028] The above process is repeated until the difference between the distribution of dust at different positions at different times in the output training samples and the distribution of dust at different positions at different times in the labeled training samples is less than a preset threshold.

[0029] As a further solution of the present invention: the data analysis module is an STM32F103RCT6 embedded single chip microcomputer which performs logic processing on the converted dust data.

[0030] As a further solution of the present invention: the data analysis module uses the STM32F103RCT6 single-chip microcomputer to connect to ATK-ESP8266; configures the ATK-ESP8266 working mode, the serial port wireless mode, and the module acts as a wireless WIFISTA to connect to a wireless network to realize wireless data conversion and transmission between the serial port and other devices.

[0031] As a further solution of the present invention: the data analysis module determines whether the dust concentration data is greater than the set dust concentration threshold. When the dust concentration data is less than the set dust concentration threshold, the green light is on, and the data processing module transmits the dust concentration data to the PC for storage and displays the dust concentration distribution, indicating that the underground dust situation is normal; when it exceeds the threshold, the red light is on, an alarm is issued, and the radiator works, indicating that the underground dust situation exceeds the standard, and dust excess alarm information is generated, and the dust excess alarm information is sent to the early warning module.

[0032] As a further solution of the present invention: the early warning module includes:

[0033] A sorting unit is used to sort the dust concentrations obtained by all data collection terminal groups in descending order when receiving dust exceeding standard warning information;

[0034] A marking unit, used to obtain the locations of the top three data collection terminal groups and mark the locations of the two data collection terminal groups;

[0035] The positioning point sending unit is used to find the positioning point in the underground area and send the location of the positioning point to the monitoring center.

[0036] Another object of an embodiment of the present invention is to provide a dust monitoring method based on an underground WiFi6 communication network, comprising the following steps:

[0037] Collect dust concentration signals and convert the dust concentration signals into dust concentration values;

[0038] Analyze the dust concentration value to generate the dust concentration change curve with respect to time and location and the dust concentration gradient diagram;

[0039] Determine whether the dust concentration data exceeds the concentration threshold and whether the underground dust situation is normal;

[0040] Connect the device to the WiFi wireless network, send the measured data to the PC for display through the ESP8266WiFi module, and store the measured data in the database;

[0041] Determine the source of underground alarm information and control the underground dust situation.

[0042] As a further solution of the present invention: the step of converting the dust concentration signal into a dust concentration value comprises the following steps:

[0043] Collecting the dust concentration optical signal;

[0044] Amplify the collected dust concentration signal and convert it into a digital signal;

[0045] The dust signal analog-to-digital conversion is performed into the dust concentration value and transmitted to the data processing module.

[0046] As a further solution of the present invention: the analysis of the dust concentration value to generate a dust concentration change curve and a dust concentration gradient diagram with respect to time and position specifically includes the following steps:

[0047] Obtain the collected information sent by the dust monitoring equipment;

[0048] Analyze the collected information to generate a dust concentration change curve and a dust concentration gradient diagram of dust concentration with respect to time and location, so as to determine the dust collection time, collection location and collection concentration;

[0049] Compare the data in the collected information to determine whether the data representing the dust collection time, collection location and collection concentration conform to the preset format;

[0050] Taking a preset number of collected information as a training sample set, marking the training samples in the training sample set, and marking the distribution of dust at different locations at different times corresponding to the training samples;

[0051] Inputting the training samples in the training sample set into a preset neural network model, learning the training samples in the training sample set, and outputting the distribution status of dust at different locations at different times corresponding to the training samples;

[0052] When the difference between the distribution of dust at different positions at different times corresponding to the output training samples and the distribution of dust at different positions at different times corresponding to the labeled training samples is greater than a preset threshold, the parameters of the convolution layer of the neural network model are modified;

[0053] The above process is repeated until the difference between the distribution of dust at different positions at different times in the output training samples and the distribution of dust at different positions at different times in the labeled training samples is less than a preset threshold, and the dust distribution is obtained.

[0054] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention arranges dust monitoring equipment and dust sensors at dust monitoring points, and sets data acquisition terminals at different locations underground, thereby acquiring the coal dust concentration in different areas within the underground range, and completing the monitoring of the coal dust concentration; the collected dust data is input into a pre-set monitoring model to generate a dust concentration change curve with respect to time and position and a dust concentration gradient diagram; the use of a laser dust sensor has the advantages of high detection accuracy and small error, strong monitoring continuity and good monitoring effect; the monitoring center displays the alarm position, and the user can view all stored data, while realizing the networking function, which can solve the problem of online monitoring of dust concentration in the prior art. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 A flowchart of a dust monitoring method based on an underground WiFi6 communication network provided in an embodiment of the present invention.

[0056] Figure 2 for Figure 1 A flow chart of the step “converting the dust concentration signal into a dust concentration value” in FIG.

[0057] Figure 3 It is a flowchart of analyzing dust concentration values ​​in the dust monitoring method of the present invention.

[0058] Figure 4 This is a functional diagram of the ESP8266WiFi module in an embodiment of the present invention. DETAILED DESCRIPTION

[0059] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0060] It is understood that the terms "first", "second", etc. used in this application may be used herein to describe various elements, but unless otherwise specified, these elements are not limited by these terms. These terms are only used to distinguish a first element from another element. For example, without departing from the scope of this application, a first receiving unit may be referred to as a second receiving unit, and similarly, a second receiving unit may be referred to as a first receiving unit.

[0061] As an embodiment of the present invention, a dust monitoring system based on an underground WiFi6 communication network includes:

[0062] A data acquisition module is used to collect dust concentration signals and convert the dust concentration signals into dust concentration values;

[0063] A data processing module is used to analyze the dust concentration value and generate a dust concentration change curve and a dust concentration gradient diagram with respect to time and location;

[0064] The data analysis module is used to determine whether the dust concentration data exceeds the concentration threshold and whether the underground dust situation is normal;

[0065] Data transmission module, which sends the measured data to the PC for display through the ESP8266WiFi module, and stores the measured data in the database;

[0066] The early warning module determines the source of the underground alarm information and controls the underground dust situation.

[0067] In this embodiment, the data acquisition module collects dust concentration signals and converts the dust concentration signals into dust concentration values. The data processing module analyzes the dust concentration values ​​to generate a dust concentration change curve with respect to time and position and a dust concentration gradient diagram, and determines the dust collection time, collection position and collection concentration. The data analysis module determines whether the dust concentration data exceeds the concentration threshold and whether the underground dust situation is normal. The data transmission module sends the measured data to the PC for display through the ESP8266WiFi module and stores the measured data in the database. The early warning module determines the source of the underground alarm information and controls the underground dust situation.

[0068] As a preferred embodiment of the present invention, the data acquisition module includes:

[0069] A laser dust sensor, used to collect the dust concentration optical signal;

[0070] The filter amplifier circuit is used to amplify the collected dust concentration signal and convert it into a digital signal;

[0071] The A / D converter is used to convert the dust signal analog-to-digital into the dust concentration value and transmit it to the data processing module.

[0072] The photoelectric converter and laser diode in the data acquisition module laser dust sensor are the signal transmitting and receiving parts, the filter amplifier circuit amplifies the weak electrical signal and converts it into a digital signal, and inputs the signal into the single-chip processor, and the frequency signal output unit converts the collected dust concentration value into a corresponding frequency signal and outputs it.

[0073] As a preferred embodiment of the present invention, the data processing module includes:

[0074] A collection information acquisition unit, used to acquire the collection information sent by the dust monitoring equipment;

[0075] A collection information analysis unit, used to analyze the collection information, generate a dust concentration change curve and a dust concentration gradient diagram of dust concentration with respect to time and position, so as to determine the collection time, collection position and collection concentration of dust;

[0076] A preset comparison unit is used to compare the data in the collected information to determine whether the data representing the dust collection time, collection location and collection concentration conforms to a preset format;

[0077] The dust monitoring unit is used to set the dust monitoring model and determine the dust distribution.

[0078] As a preferred embodiment of the present invention, the dust concentration gradient map is to establish a three-dimensional coordinate system of dust concentration with respect to time and position, and generate a dust concentration change curve and a dust concentration gradient map with respect to time and position according to the dust concentration data, dust collection time and collection position obtained by each data collection terminal, and set a dust concentration threshold line in each dust concentration gradient map according to the set dust concentration threshold.

[0079] As a preferred embodiment of the present invention, the preset comparison unit is used to compare the data characterizing the dust collection time, collection location and collection concentration with the data of the dust collection time, collection location and collection concentration in the configuration information to determine whether the data characterizing the dust collection time, collection location and collection concentration conforms to the preset format.

[0080] As a preferred embodiment of the present invention, the dust monitoring model is obtained by:

[0081] Taking a preset number of collected information as a training sample set, marking the training samples in the training sample set, and marking the distribution of dust at different locations at different times corresponding to the training samples;

[0082] Inputting the training samples in the training sample set into a preset neural network model, learning the training samples in the training sample set, and outputting the distribution status of dust at different locations at different times corresponding to the training samples;

[0083] When the difference between the distribution of dust at different positions at different times corresponding to the output training samples and the distribution of dust at different positions at different times corresponding to the labeled training samples is greater than a preset threshold, the parameters of the convolution layer of the neural network model are modified;

[0084] The above process is repeated until the difference between the distribution of dust at different positions at different times in the output training samples and the distribution of dust at different positions at different times in the labeled training samples is less than a preset threshold.

[0085] As a preferred embodiment of the present invention, the data analysis module is an STM32F103RCT6 embedded single chip microcomputer which performs logic processing on the converted dust data.

[0086] As a preferred embodiment of the present invention, the data analysis module uses an STM32F103RCT6 single-chip microcomputer to connect to ATK-ESP8266; configures the ATK-ESP8266 working mode, the serial port wireless mode, and the module acts as a wireless WIFISTA to connect to a wireless network to achieve wireless data conversion and transmission between the serial port and other devices.

[0087] As a preferred embodiment of the present invention, the data analysis module determines whether the dust concentration data is greater than a set dust concentration threshold. When the dust concentration data is less than the set dust concentration threshold, the green light is on, and the data processing module transmits the dust concentration data to the PC for storage and displays the dust concentration distribution, indicating that the underground dust situation is normal; when it exceeds the threshold, the red light is on, an alarm is issued, and the radiator works, indicating that the underground dust situation exceeds the standard, and dust excess alarm information is generated, and the dust excess alarm information is sent to the early warning module.

[0088] As a preferred embodiment of the present invention, the early warning module includes:

[0089] A sorting unit is used to sort the dust concentrations obtained by all data collection terminal groups in descending order when receiving dust exceeding standard warning information;

[0090] A marking unit, used to obtain the locations of the top three data collection terminal groups and mark the locations of the two data collection terminal groups;

[0091] The positioning point sending unit is used to find the positioning point in the underground area and send the location of the positioning point to the monitoring center.

[0092] As an embodiment of the present invention, please refer to Figure 1 and Figure 4 , a dust monitoring method based on underground WiFi6 communication network, comprising the following steps:

[0093] Determine the number and location of dust monitoring equipment to be installed;

[0094] Set dust concentration threshold;

[0095] Collect dust concentration signals and convert the dust concentration signals into dust concentration values;

[0096] Analyze the dust concentration value to generate the dust concentration change curve with respect to time and location and the dust concentration gradient diagram;

[0097] Determine whether the dust concentration exceeds the concentration threshold and whether the underground dust situation is normal. When the dust concentration data is less than the set dust concentration threshold, the green light is on, and the data processing module transmits the dust concentration data to the PC for storage and displays the dust concentration distribution, indicating that the underground dust situation is normal. When the threshold is exceeded, the red light is on, an alarm is sounded, and the radiator works, indicating that the underground dust situation exceeds the standard. Dust exceeding standard alarm information is generated, and the dust exceeding standard alarm information is sent to the early warning module;

[0098] Connect the device to the WiFi wireless network, send the measured data to the PC for display through the ESP8266WiFi module, and store the measured data in the database;

[0099] Determine the source of underground alarm information and control the underground dust situation.

[0100] As an embodiment of the present invention, please refer to Figure 2 , the step of converting the dust concentration signal into a dust concentration value comprises the following steps:

[0101] Collecting the dust concentration optical signal;

[0102] Amplify the collected dust concentration signal and convert it into a digital signal;

[0103] The dust signal analog-to-digital conversion is performed into the dust concentration value and transmitted to the data processing module.

[0104] As an embodiment of the present invention, please refer to Figure 3 The analysis of the dust concentration value to generate a dust concentration change curve and a dust concentration gradient diagram with respect to time and location specifically includes the following steps:

[0105] Obtain the collected information sent by the dust monitoring equipment;

[0106] Analyze the collected information to generate a dust concentration change curve and a dust concentration gradient diagram of dust concentration with respect to time and location, so as to determine the collection time, collection location and collection concentration of dust;

[0107] Compare the data in the collected information to determine whether the data representing the dust collection time, collection location and collection concentration conform to the preset format;

[0108] Taking a preset number of collected information as a training sample set, marking the training samples in the training sample set, and marking the distribution of dust at different locations at different times corresponding to the training samples;

[0109] Inputting the training samples in the training sample set into a preset neural network model, learning the training samples in the training sample set, and outputting the distribution status of dust at different locations at different times corresponding to the training samples;

[0110] When the difference between the distribution of dust at different positions at different times corresponding to the output training samples and the distribution of dust at different positions at different times corresponding to the labeled training samples is greater than a preset threshold, the parameters of the convolution layer of the neural network model are modified;

[0111] The above process is repeated until the difference between the distribution of dust at different positions at different times in the output training samples and the distribution of dust at different positions at different times in the labeled training samples is less than a preset threshold, and the dust distribution is obtained.

[0112] In summary: The present invention proposes a dust monitoring system and method based on an underground WiFi6 communication network. The system includes a data acquisition module, a data processing module, a data analysis module, a data transmission module and an early warning module. By setting data acquisition terminals at different locations underground, the coal dust concentration in different areas within the underground range is obtained, the coal dust concentration is monitored and monitored, and a dust concentration change curve and a dust concentration gradient diagram with respect to time and position are generated to determine whether the dust concentration in the underground area exceeds the standard. If the threshold is exceeded, the LED lights up red and an alarm is sounded at the same time, the monitoring center displays the alarm position, and the radiator works to increase air flow and reduce the dust concentration in the environment. At the same time, the device is connected to a WiFi wireless network, and then sent to the PC for display through the ESP8266WiFi module, and the measured data is stored in a database. The user can view all the stored data and realize the networking function at the same time. The present invention further discloses a dust monitoring method used in the ESP8266WiFi module dust monitoring system.

[0113] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0114] The above-mentioned embodiments only express several implementation methods of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

[0115] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A dust monitoring system based on underground WiFi6 communication network, characterized in that: include: A data acquisition module is used to collect dust concentration signals and convert the dust concentration signals into dust concentration values; A data processing module is used to analyze the dust concentration value and generate a dust concentration change curve and a dust concentration gradient diagram with respect to time and location; The data analysis module is used to determine whether the dust concentration data exceeds the concentration threshold and whether the underground dust situation is normal; Data transmission module, which sends the measured data to the PC for display through the ESP8266 WiFi module and stores the measured data in the database; The early warning module determines the source of underground alarm information and controls the underground dust situation; The data processing module comprises: A collection information acquisition unit, used to acquire the collection information sent by the dust monitoring equipment; A collection information analysis unit, used to analyze the collection information, generate a dust concentration change curve and a dust concentration gradient diagram of dust concentration with respect to time and position, so as to determine the collection time, collection position and collection concentration of dust; A preset comparison unit is used to compare the data in the collected information to determine whether the data representing the dust collection time, collection location and collection concentration conforms to a preset format; Dust monitoring unit, used to set the dust monitoring model and determine the dust distribution; The dust monitoring model is obtained by: Taking a preset number of collected information as a training sample set, marking the training samples in the training sample set, and marking the distribution of dust at different locations at different times corresponding to the training samples; Inputting the training samples in the training sample set into a preset neural network model, learning the training samples in the training sample set, and outputting the distribution status of dust at different locations at different times corresponding to the training samples; When the difference between the distribution of dust at different positions at different times corresponding to the output training samples and the distribution of dust at different positions at different times corresponding to the labeled training samples is greater than a preset threshold, the parameters of the convolution layer of the neural network model are modified; Repeat the correction step until the difference between the distribution of dust at different positions at different times in the output training sample and the distribution of dust at different positions at different times in the labeled training sample is less than a preset threshold; The dust concentration gradient diagram establishes a three-dimensional coordinate system of dust concentration with respect to time and position, generates a dust concentration change curve and a dust concentration gradient diagram with respect to time and position according to the dust concentration data, dust collection time and collection position obtained by each data collection terminal, and sets a dust concentration threshold line in each dust concentration gradient diagram according to the set dust concentration threshold.

2. A dust monitoring system based on underground WiFi6 communication network according to claim 1, characterized in that: The data acquisition module comprises: A laser dust sensor, used for collecting the dust concentration signal; The filter amplifier circuit is used to amplify the collected dust concentration signal and convert it into a digital signal; The A / D converter is used to convert the dust concentration signal into the dust concentration value and transmit it to the data processing module.

3. A dust monitoring system based on underground WiFi6 communication network according to claim 1, characterized in that: The preset comparison unit is used to compare the data representing the dust collection time, collection position and collection concentration with the data of the dust collection time, collection position and collection concentration in the configuration information to determine whether the data representing the dust collection time, collection position and collection concentration conforms to the preset format.

4. A dust monitoring system based on underground WiFi6 communication network according to claim 1, characterized in that: The data analysis module is an STM32F103RCT6 embedded single chip microcomputer that performs logic processing on the converted dust data.

5. A dust monitoring system based on underground WiFi6 communication network according to claim 4, characterized in that: The data analysis module uses the STM32F103RCT6 microcontroller to connect to ATK-ESP8266; configures the ATK-ESP8266 working mode, the serial port wireless mode, and the module acts as a wireless WIFI STA to connect to a wireless network to achieve wireless data conversion and transmission between the serial port and other devices.

6. A dust monitoring system based on underground WiFi6 communication network according to claim 1, characterized in that: The data analysis module determines whether the dust concentration data is greater than the set dust concentration threshold. When the dust concentration data is less than the set dust concentration threshold, the green light is on, and the data processing module transmits the dust concentration data to the PC for storage and displays the dust concentration distribution, indicating that the underground dust situation is normal. If it exceeds the threshold, the red light is on, an alarm is issued, and the radiator works, indicating that the underground dust situation exceeds the standard, and dust excess alarm information is generated, and the dust excess alarm information is sent to the early warning module.

7. A dust monitoring system based on underground WiFi6 communication network according to claim 1, characterized in that: The early warning module comprises: A sorting unit is used to sort the dust concentrations obtained by all data collection terminal groups in descending order when receiving dust exceeding standard warning information; A marking unit, used to obtain the locations of the top three data collection terminal groups and mark the locations of the two data collection terminal groups; The positioning point sending unit is used to find the positioning point in the underground area and send the location of the positioning point to the monitoring center.

8. A dust monitoring method based on underground WiFi6 communication network, characterized in that: The following steps are involved: Collect dust concentration signals and convert the dust concentration signals into dust concentration values; Analyze the dust concentration value to generate the dust concentration change curve with respect to time and location and the dust concentration gradient diagram; Determine whether the dust concentration data exceeds the concentration threshold and whether the underground dust situation is normal; Connect the device to the WiFi wireless network, send the measured data to the PC for display through the ESP8266WiFi module, and store the measured data in the database; Determine the source of underground alarm information and control the underground dust situation; The analysis of the dust concentration value to generate a dust concentration variation curve and a dust concentration gradient diagram with respect to time and location specifically includes the following steps: Obtain the collected information sent by the dust monitoring equipment; Analyze the collected information to generate a dust concentration change curve and a dust concentration gradient diagram of dust concentration with respect to time and location, so as to determine the collection time, collection location and collection concentration of dust; Compare the data in the collected information to determine whether the data representing the dust collection time, collection location and collection concentration conform to the preset format; Taking a preset number of collected information as a training sample set, marking the training samples in the training sample set, and marking the distribution of dust at different locations at different times corresponding to the training samples; Inputting the training samples in the training sample set into a preset neural network model, learning the training samples in the training sample set, and outputting the distribution status of dust at different locations at different times corresponding to the training samples; When the difference between the distribution of dust at different positions at different times corresponding to the output training samples and the distribution of dust at different positions at different times corresponding to the labeled training samples is greater than a preset threshold, the parameters of the convolution layer of the neural network model are modified; Repeat the correction step until the difference between the distribution of dust at different positions at different times in the output training sample and the distribution of dust at different positions at different times in the labeled training sample is less than a preset threshold, and the dust distribution is obtained.

9. A dust monitoring method based on underground WiFi6 communication network according to claim 8, characterized in that: The step of converting the dust concentration signal into a dust concentration value comprises the following steps: collecting the dust concentration signal; Amplify the collected dust concentration signal and convert it into a digital signal; The dust concentration signal is converted into the dust concentration value and transmitted to the data processing module.

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