Coal pile temperature data supervision method and system based on Internet of Things

Abstract

The invention discloses a coal pile temperature data supervision method and system based on the Internet of Things, and relates to the technical field of coal pile stacking data management. The method comprises the following steps: monitoring internal, surface and environment temperatures of a coal pile, inflammable gas concentration, dust concentration and humidity; data transmission supports wired and wireless modes, and the edge computing device carries out primary processing on the data. The data processing and analysis module is responsible for centralized monitoring, data cleaning, fusion, trend analysis and anomaly detection. And the automatic control module starts spraying, mist spraying and ventilation systems and intelligent scheduling according to the monitoring data. And the alarm notification module comprises a real-time alarm mechanism and a graded alarm mechanism, and notifies management personnel in various modes. Through comprehensive monitoring, intelligent analysis and automatic control, spontaneous combustion of the coal pile is effectively prevented, safety is improved, it is ensured that abnormal conditions are handled in time, and safe, efficient and intelligent coal pile management is achieved.

Description

Technical Field

[0001] The present invention belongs to the technical field of coal pile storage data management, and in particular relates to a method and system for monitoring coal pile temperature data based on the Internet of Things. Background Art

[0002] Spontaneous combustion of coal piles threatens economic and environmental safety, and may cause fires, explosions, and release harmful gases and dust. Traditional prevention methods such as manual inspections and regular temperature measurements have limitations and are difficult to monitor the status of coal piles in a comprehensive and real-time manner.

[0003] With the development of technology, sensors, the Internet of Things and data analysis technologies have provided new solutions for preventing spontaneous combustion. These methods can monitor the temperature, gas, dust and humidity of coal piles in real time, improving the accuracy of early warning and the speed of response. Compared with traditional management that relies on manual experience, a complete data management system can realize real-time monitoring, data analysis and automatic control, improving the efficiency and accuracy of coal pile management.

[0004] Therefore, a coal pile data management method based on comprehensive monitoring, intelligent analysis and automatic control is proposed, aiming to effectively prevent spontaneous combustion and improve the safety and operation efficiency of coal yards. Summary of the invention

[0005] In order to overcome the shortcomings and deficiencies of the above-mentioned prior art, the first purpose of the present invention is to provide a coal pile temperature data monitoring method based on the Internet of Things; the second purpose of the present invention is to provide a coal pile temperature data monitoring system based on the Internet of Things.

[0006] The first object of the present invention adopts the following technical solution:

[0007] A method for monitoring coal pile temperature data based on the Internet of Things, the process is as follows:

[0008] Step 1: Install sensors, including selecting temperature sensors, gas sensors, dust sensors and humidity sensors, and deploying these sensors inside, on the surface, around and in the coal pile, to comprehensively monitor the temperature, flammable gas concentration, dust concentration and humidity of the coal pile;

[0009] Step 2: Transmit the data collected by the sensor to the data processing center via wired or wireless means, and deploy edge computing equipment on site in the coal shed for preliminary data processing and filtering;

[0010] Step 3: Centrally monitor all sensor data in the data processing center, perform data cleaning, fusion, trend analysis and anomaly detection, store the data in the selected database, and provide a data visualization interface;

[0011] Step 4: Automatically start corresponding control measures according to monitoring data, including sprinkler system, mist system, ventilation system, and set warning thresholds, and realize synchronous start of multiple control measures through linkage control mechanism;

[0012] Step 5: When abnormal situations are detected, timely alarms and notifications are issued through real-time alarms, and a hierarchical alarm mechanism is implemented;

[0013] Step 6: Store and query historical data and alarm records, provide data retrieval and analysis functions, and automatically generate and customize reports.

[0014] Preferably, in step one, the temperature sensors include an insertable thermometer and an infrared thermal imager, the gas sensor is used to detect the concentrations of carbon monoxide, carbon dioxide and methane, the dust sensor is used to monitor the dust concentration around the coal pile, and the humidity sensor is used to monitor the air humidity in the coal shed.

[0015] Preferably, in step 2, wired transmission is achieved through cables, and wireless transmission uses LoRa, Zigbee, and Wi-Fi wireless communication technologies, and the edge computing device performs preliminary processing and filtering of the data on site in the coal shed.

[0016] Preferably, in step three, data cleaning is performed to remove outliers, duplicate values, and missing values, data fusion is performed using weighted averaging, Kalman filtering, or machine learning fusion methods, trend analysis is performed using ARIMA, LSTM, or Prophet models, and anomaly detection uses rule-based, statistical, or machine learning methods.

[0017] Preferably, in step four, the linkage control mechanism includes intelligently scheduling the start-up time of the spraying, misting and ventilation systems according to the monitoring results of temperature, gas concentration, dust concentration and humidity to avoid energy waste.

[0018] Preferably, in step five, the real-time alarm includes alarm bell, visual alarm, mobile phone APP notification, text message and phone notification, and the graded alarm mechanism includes level one alarm, level two alarm and level three alarm, corresponding to different levels of abnormal situations respectively.

[0019] As a preferred embodiment, in step six, the data storage and query function supports users to view historical data and alarm records, the data tracing and analysis function helps users to find potential problems, and the automatic generation and customization of reports can meet the different needs of users.

[0020] The second object of the present invention adopts the following technical solution:

[0021] A coal pile temperature data monitoring system based on the Internet of Things is used to implement a coal pile temperature data monitoring method based on the Internet of Things. The system includes a sensor module, a data transmission module, a data processing and analysis module, an automatic control module, an alarm notification module, and a historical data and alarm recording module;

[0022] Sensor module: responsible for selecting and arranging temperature sensors, gas sensors, dust sensors and humidity sensors; temperature sensors monitor the internal, surface and ambient temperatures of the coal pile; gas sensors detect the concentration of flammable gases such as carbon monoxide, carbon dioxide and methane around the coal pile; dust sensors monitor the dust concentration around the coal pile; humidity sensors monitor the air humidity in the coal shed;

[0023] Data transmission module: responsible for transmitting the data collected by the sensor to the data processing center; supports both wired and wireless transmission; edge computing devices perform preliminary processing and filtering on the data;

[0024] Data processing and analysis module: responsible for centralized monitoring, data cleaning, data fusion, trend analysis and anomaly detection;

[0025] Automatic control module: responsible for automatically starting corresponding control measures according to monitoring data, including sprinkler system, mist system, ventilation system and intelligent scheduling; setting early warning thresholds, and starting control measures according to conditional triggers and linkage control mechanisms;

[0026] Alarm notification module: responsible for issuing alarms and notifications in a timely manner when abnormal situations are detected, including real-time alarms and graded alarm mechanisms; real-time alarms include alarm bells, visual alarms, mobile APP notifications, SMS and phone notifications;

[0027] Historical data and alarm record module: responsible for storing and querying historical data and alarm records; providing data tracing and analysis functions to help users discover potential problems; automatic generation and customization of report functions.

[0028] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0029] The present invention provides a strong guarantee for the safe, efficient and intelligent management of coal piles through comprehensive monitoring and intelligent prevention, real-time response and efficient control, timely and accurate alarm notification, traceable analysis of historical data, and efficient and intelligent overall system. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0031] Figure 1 A flow chart of a method for monitoring coal pile temperature data based on the Internet of Things is shown in the present invention. DETAILED DESCRIPTION

[0032] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0033] In addition, the described features, structures or characteristics may be combined in one or more example embodiments in any suitable manner. In the following description, many specific details are provided to provide a full understanding of the example embodiments of the present disclosure. However, those skilled in the art will appreciate that the technical solutions of the present disclosure may be practiced while omitting one or more of the specific details, or other methods, components, steps, etc. may be adopted. In other cases, well-known structures, methods, implementations or operations are not shown or described in detail to avoid obscuring various aspects of the present disclosure.

[0034] Embodiment 1:

[0035] See also Figure 1 As shown, a method for monitoring coal pile temperature data based on the Internet of Things in this embodiment has the following process:

[0036] Step 1: Install the sensor.

[0037] S11. Select sensor type.

[0038] Temperature sensor: used to monitor the internal, surface and ambient temperature of the coal pile. You can choose to use insertion thermometers, infrared thermal imagers and other equipment to ensure comprehensive monitoring of temperatures at different depths and locations.

[0039] Gas sensor: used to detect the concentration of flammable gases such as carbon monoxide (CO), carbon dioxide (CO2), and methane (CH4) around coal piles. Changes in the concentration of these gases can serve as early warning signals for spontaneous combustion of coal piles.

[0040] Dust sensor: used to monitor dust concentration around coal piles. High dust concentration not only affects air quality, but also may cause explosion risks.

[0041] Humidity sensor: used to monitor the air humidity in the coal shed. Changes in humidity will affect the oxidation reaction rate of the coal pile, which in turn affects temperature changes.

[0042] S12. Sensor deployment.

[0043] Internal temperature sensor: Insertion-type thermometers are buried at certain intervals (such as 2 meters) inside the coal pile to form a multi-layer temperature monitoring network to ensure full coverage of the interior of the coal pile.

[0044] Surface temperature sensor: Install an infrared thermal imager on the top or side of the coal shed to monitor the surface temperature distribution of the coal pile in real time and identify high-temperature areas.

[0045] Gas Sensors: Gas sensors are installed at different heights and locations in the coal shed to ensure comprehensive monitoring of gas concentrations in the entire space.

[0046] Dust sensors: Dust sensors are installed at key locations such as the coal shed entrance, exit and vents to monitor dust concentration.

[0047] Humidity Sensors: Humidity sensors are installed at various locations in the coal shed to ensure comprehensive monitoring of air humidity.

[0048] Step 2: Data transmission and processing.

[0049] Data transmission method is as follows:

[0050] Wired transmission: Transmit sensor data to a local data collector or gateway device via a cable. Suitable for scenarios with convenient wiring, with stable and reliable transmission.

[0051] Wireless transmission: Use wireless communication technologies such as LoRa, Zigbee, and Wi-Fi to transmit sensor data to the IoT platform. It is suitable for large-scale coal piles or scenes with inconvenient wiring, and has the advantage of high flexibility.

[0052] Edge computing: Edge computing devices are deployed on-site at the coal shed to perform preliminary data processing and filtering, and only necessary data is uploaded to the cloud. This can reduce the amount of data transmission, reduce bandwidth pressure, and improve response speed.

[0053] Step 3: Data processing and analysis.

[0054] Centralized monitoring layer: All sensor data is centrally transmitted to the central control system (such as cloud server or local server) through the IoT platform. The central control system is responsible for unified management and analysis of the data.

[0055] Data cleaning: Remove outliers, duplicate values, and missing values ​​to ensure data quality. Use statistical methods or machine learning algorithms to detect and clean outliers.

[0056] Data fusion: The temperature, gas, dust and humidity data from different sensors are fused and processed. Common fusion methods include weighted average method, Kalman filter, machine learning fusion, etc. to improve the accuracy and reliability of monitoring.

[0057] Trend analysis: Establish a change trend model of temperature, gas concentration, etc. based on historical data to predict future change trends.

[0058] Anomaly detection: Detects abnormal conditions of temperature, gas concentration, dust concentration, and humidity by comparing them to normal ranges. You can use rule-based anomaly detection, statistics-based anomaly detection, or machine learning-based anomaly detection.

[0059] The data is stored as follows:

[0060] Database selection: You can choose a relational database or a non-relational database to store historical data. For real-time data, you can use a time series database to improve query efficiency.

[0061] Data backup: Back up the database regularly to ensure data security and recoverability.

[0062] Data visualization: Through the Web or mobile application, a real-time temperature, gas, dust and humidity monitoring interface is provided to display the status of the coal pile. Charts can be used to intuitively display data change trends.

[0063] Step 4: Automatic control.

[0064] S41, linkage control mechanism.

[0065] Spraying system: When the internal temperature or surface temperature exceeds the preset threshold, the system automatically starts the spraying system to spray water on the coal pile to quickly cool it down. The activation of the spraying system can be judged based on comprehensive factors such as temperature change rate and temperature difference.

[0066] Spray system: The spray system can reduce dust concentration and improve air quality while cooling. The activation of the spray system can be determined based on dust concentration and humidity.

[0067] Ventilation system: When the monitored gas concentration (such as carbon monoxide, methane) exceeds the safety threshold, the system automatically starts the ventilation system to increase air circulation and reduce gas concentration. The activation of the ventilation system can be judged based on the gas concentration change rate and temperature change.

[0068] Intelligent Scheduling: The system can intelligently schedule the start-up time of the sprinkler, mist and ventilation systems based on the comprehensive evaluation results of temperature, gas, dust and humidity to avoid unnecessary energy waste.

[0069] S42, control logic.

[0070] Threshold setting: According to the safety requirements of the coal pile, set the warning thresholds for internal temperature, surface temperature, gas concentration, dust concentration and humidity. For example:

[0071] Internal temperature warning threshold: 60℃

[0072] Surface temperature warning threshold: 50℃

[0073] Carbon monoxide concentration warning threshold: 50ppm

[0074] Methane concentration warning threshold: 1% V / V

[0075] Dust concentration warning threshold: 10mg / m 3

[0076] Humidity warning threshold: 80%

[0077] Condition trigger: When any parameter exceeds the warning threshold, the system immediately initiates the corresponding control measures. For example, when the internal temperature exceeds 60°C, the sprinkler system is activated; when the carbon monoxide concentration exceeds 50ppm, the ventilation system is activated.

[0078] S43, linkage control: multiple control measures can be activated at the same time to form a linkage effect. For example, when the temperature and gas concentration exceed the standard at the same time, the system can activate the spray and ventilation system at the same time to quickly cool down and reduce the gas concentration.

[0079] Step 5: Alarm and notification.

[0080] S51, real-time alarm

[0081] Alarm: An alarm is installed in the coal shed. When any parameter is monitored to exceed the warning threshold, the alarm will be activated immediately to remind on-site personnel to pay attention to safety.

[0082] Visual alarm: LED display screens or indicator lights are installed at key locations such as the entrance and exit of the coal shed. When an abnormal situation is detected, a red warning message will be displayed to alert personnel.

[0083] Mobile APP notification: Push notifications via mobile APP to inform management personnel of abnormal situations in a timely manner. The APP can display detailed alarm information, including time, location, parameter values, etc.

[0084] SMS and phone notifications: When a serious abnormality is detected, the system can urgently notify managers via SMS or phone to ensure that they can take action at the first time.

[0085] S52. Hierarchical alarm mechanism.

[0086] Level 1 alarm: When a parameter approaches the warning threshold, the system will issue a level 1 alarm to alert management personnel. At this time, management personnel can increase the monitoring frequency and observe parameter changes.

[0087] Level 2 alarm: When a parameter exceeds the warning threshold, the system will issue a level 2 alarm, initiate corresponding control measures (such as spraying, ventilation), and notify management personnel to take further action.

[0088] Level 3 alarm: When multiple parameters exceed the warning threshold at the same time, or a parameter exceeds the warning threshold for a long time, the system will issue a level 3 alarm, activate the emergency plan, notify all relevant personnel, and initiate all available control measures.

[0089] Step 6: Historical data and alarm records.

[0090] S61. Data storage and query.

[0091] Historical data storage: The system has a data storage function that supports long-term storage of historical data on temperature, gas, dust and humidity. Users can view historical data through the Web or mobile applications to understand the temperature change trend of the coal pile, gas concentration changes, etc.

[0092] Alarm record storage: The system will automatically record the time, location, parameter value, treatment measures, etc. of each alarm. Users can query historical alarm records through the system, analyze the cause of the accident, and optimize management strategies.

[0093] S62. Data tracing and analysis.

[0094] Data recall: Users can set the time range and parameter type to query historical data and alarm records within a specific time period.

[0095] Data analysis: The system provides data analysis tools to help users analyze the patterns and trends in historical data. For example, it can generate temperature trend graphs, gas concentration fluctuation graphs, etc., to help managers identify potential problems and take preventive measures in advance.

[0096] Automatically generate reports: The system can regularly generate reports on temperature, gas, dust and humidity according to user needs, including historical data, alarm records, treatment measures, etc.

[0097] Customized reports: Users can customize the content and format of reports according to their needs to highlight key data of concern.

[0098] The beneficial effects of this embodiment are: through comprehensive monitoring, intelligent analysis and automatic control, it can effectively prevent the spontaneous combustion of coal piles and improve safety. At the same time, the real-time alarm and graded response mechanism ensure that abnormal situations are handled in a timely manner, and the historical data recording and analysis help optimize management and achieve safe, efficient and intelligent coal pile management.

[0099] Embodiment 2:

[0100] A coal pile temperature data monitoring system based on the Internet of Things in this embodiment includes a sensor module, a data transmission module, a data processing and analysis module, an automatic control module, an alarm notification module, and a historical data and alarm recording module.

[0101] Sensor module: responsible for selecting and arranging temperature sensors, gas sensors, dust sensors and humidity sensors; temperature sensors monitor the internal, surface and ambient temperatures of the coal pile; gas sensors detect the concentrations of flammable gases such as carbon monoxide, carbon dioxide and methane around the coal pile; dust sensors monitor the dust concentration around the coal pile; humidity sensors monitor the air humidity in the coal shed.

[0102] Data transmission module: responsible for transmitting the data collected by the sensor to the data processing center; supports both wired and wireless transmission; edge computing devices perform preliminary processing and filtering on the data.

[0103] Data processing and analysis module: responsible for centralized monitoring, data cleaning, data fusion, trend analysis and anomaly detection.

[0104] Automatic control module: responsible for automatically starting corresponding control measures according to monitoring data, including sprinkler system, mist system, ventilation system and intelligent scheduling; setting early warning thresholds, and starting control measures according to conditional triggers and linkage control mechanisms.

[0105] Alarm notification module: responsible for issuing alarms and notifications in a timely manner when abnormal situations are detected, including real-time alarms and graded alarm mechanisms; real-time alarms include alarm bells, visual alarms, mobile phone APP notifications, text messages and phone notifications.

[0106] Historical data and alarm record module: responsible for storing and querying historical data and alarm records; providing data tracing and analysis functions to help users discover potential problems; automatic generation and customization of report functions.

[0107] The beneficial effects of this embodiment are as follows: through comprehensive monitoring and intelligent control, spontaneous combustion is effectively prevented and the safety of coal piles is improved. Real-time data transmission and analysis ensure rapid response to abnormalities. Alarm notifications are timely and accurate, and historical data can be traced and analyzed to help optimize management. The overall system is efficient and intelligent, ensuring the safe and stable operation of coal piles.

[0108] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

[0109] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A method for monitoring coal pile temperature data based on the Internet of Things, characterized in that: The method flow is as follows: Step 1: Install sensors, including selecting temperature sensors, gas sensors, dust sensors and humidity sensors, and deploying these sensors inside, on the surface, around and in the coal pile, to comprehensively monitor the temperature, flammable gas concentration, dust concentration and humidity of the coal pile; Step 2: Transmit the data collected by the sensor to the data processing center via wired or wireless means, and deploy edge computing equipment on site at the coal shed for preliminary data processing and filtering; Step 3: Centrally monitor all sensor data in the data processing center, perform data cleaning, fusion, trend analysis and anomaly detection, store the data in the selected database, and provide a data visualization interface; Step 4: Automatically start corresponding control measures according to monitoring data, including sprinkler system, mist system, ventilation system, and set warning thresholds, and realize synchronous start of multiple control measures through linkage control mechanism; Step 5: When abnormal situations are detected, timely alarms and notifications are issued through real-time alarms, and a hierarchical alarm mechanism is implemented; Step 6: Store and query historical data and alarm records, provide data retrieval and analysis functions, and automatically generate and customize reports.

2. The method for monitoring coal pile temperature data based on the Internet of Things according to claim 1, characterized in that: In step 1, the temperature sensors include an insertion thermometer and an infrared thermal imager, the gas sensor is used to detect the concentrations of carbon monoxide, carbon dioxide and methane, the dust sensor is used to monitor the dust concentration around the coal pile, and the humidity sensor is used to monitor the air humidity in the coal shed.

3. The method for monitoring coal pile temperature data based on the Internet of Things according to claim 1, characterized in that: In step 2, wired transmission is achieved through cables, and wireless transmission uses LoRa, Zigbee, and Wi-Fi wireless communication technologies. The edge computing device performs preliminary processing and filtering of the data on site in the coal shed.

4. The method for monitoring coal pile temperature data based on the Internet of Things according to claim 1, characterized in that: In step three, data cleaning is performed to remove outliers, duplicate values, and missing values, data fusion is performed using weighted averaging, Kalman filtering, or machine learning fusion methods, trend analysis is performed using ARIMA, LSTM, or Prophet models, and anomaly detection uses rule-based, statistical, or machine learning methods.

5. The method for monitoring coal pile temperature data based on the Internet of Things according to claim 1 is characterized in that: In step 4, the linkage control mechanism includes intelligently scheduling the start-up time of the spraying, misting and ventilation systems according to the monitoring results of temperature, gas concentration, dust concentration and humidity to avoid energy waste.

6. The method for monitoring coal pile temperature data based on the Internet of Things according to claim 1, characterized in that: In step five, the real-time alarm includes alarm bell, visual alarm, mobile phone APP notification, SMS and phone notification, and the graded alarm mechanism includes level one alarm, level two alarm and level three alarm, which correspond to different levels of abnormal situations respectively.

7. The method for monitoring coal pile temperature data based on the Internet of Things according to claim 1, characterized in that: In step six, the data storage and query function supports users to view historical data and alarm records, the data tracing and analysis function helps users to find potential problems, and the automatic generation and customization of reports can meet the different needs of users.

8. A coal pile temperature data monitoring system based on the Internet of Things, used to implement the coal pile temperature data monitoring method based on the Internet of Things as claimed in claim 1, characterized in that: The system includes a sensor module, a data transmission module, a data processing and analysis module, an automatic control module, an alarm notification module, and a historical data and alarm recording module; Sensor module: responsible for selecting and arranging temperature sensors, gas sensors, dust sensors and humidity sensors; temperature sensors monitor the internal, surface and ambient temperatures of the coal pile; gas sensors detect the concentration of flammable gases such as carbon monoxide, carbon dioxide and methane around the coal pile; dust sensors monitor the dust concentration around the coal pile; humidity sensors monitor the air humidity in the coal shed; Data transmission module: responsible for transmitting the data collected by the sensor to the data processing center; supports both wired and wireless transmission; edge computing devices perform preliminary processing and filtering on the data; Data processing and analysis module: responsible for centralized monitoring, data cleaning, data fusion, trend analysis and anomaly detection; Automatic control module: responsible for automatically starting corresponding control measures according to monitoring data, including sprinkler system, spray system, ventilation system and intelligent scheduling; Set early warning thresholds and initiate control measures based on conditional triggers and linkage control mechanisms; Alarm notification module: responsible for issuing alarms and notifications in a timely manner when abnormal situations are detected, including real-time alarms and graded alarm mechanisms; real-time alarms include alarm bells, visual alarms, mobile APP notifications, SMS and phone notifications; Historical data and alarm record module: responsible for storing and querying historical data and alarm records, providing data tracing and analysis functions to help users discover potential problems; automatic generation and customized report functions.

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