An integrated data monitoring system and method for thermal sensing devices

Abstract

This invention relates to an integrated data monitoring system for thermal sensing devices. The system includes: a data acquisition card for acquiring various analog or digital signals, and uploading the acquired, filtered, and denoised data to a data acquisition device via a network port based on TCP and a private user protocol; a data acquisition device for controlling the data acquisition card according to instructions issued by the system monitoring center, and sending the data to an integrated network controller; an integrated network controller for converting communication protocol data from different data acquisition devices into a unified mode and sending it to the system monitoring center, and for converting received data or instructions into a communication format corresponding to the data acquisition device and sending it to the data acquisition device; a system monitoring center for classifying and recording the received data, comparing it, and triggering an alarm if the data exceeds the range or abnormal data is found, while simultaneously removing the abnormal data, obtaining a graph, and sending it to a cloud platform data center; and a cloud platform data center for converting the received data into images and displaying the data images and graphs.

Description

Technical Field

[0001] This invention relates to the field of thermal sensing equipment technology, and in particular to an integrated data monitoring system and method for thermal sensing equipment. Background Technology

[0002] Currently, with the rapid advancement of communication, network, and industrial control technologies, and the accelerating pace of social informatization, information is not only changing people's lifestyles and work methods but also rapidly and profoundly reshaping industrial production and traditional manufacturing. In industrial production, manual data recording, equipment monitoring, and problem-solving are no longer acceptable; instead, higher levels of intelligence, safety, and controllability are sought. Thermal induction equipment, primarily used for quenching and tempering industrial parts, has a high power output frequency (kHz level) and large current fluctuations. PLC scanning cycles (typically ≥10ms) cannot capture transient anomalies, leading to uneven workpiece quenching. Due to the large size of the equipment and the numerous components involved, malfunctions during processing require significant manpower and resources for troubleshooting. Furthermore, during production, the equipment cannot determine the normality of parameters for each component in real time, nor can it quickly assess the workpiece's process status; only after processing is complete can manual judgment be made regarding its quality. These problems have consistently existed in industrial production and manufacturing. With the widespread adoption of the Industrial Internet and intelligent manufacturing technologies, addressing these production process challenges has become increasingly urgent. Most existing data monitoring systems on the market currently monitor the parameter data of a specific equipment module and adjust the performance of the monitored equipment based on the parameter data, resulting in relatively limited functionality. Furthermore, these systems only monitor the equipment itself and do not perform status monitoring and data processing and analysis of the entire production process, making it difficult to achieve the goal of intelligent monitoring and control of the entire equipment. Summary of the Invention

[0003] In view of the above problems, the present invention provides an integrated data monitoring system and method for thermal sensing equipment to solve the technical problems of existing technologies, such as only being able to collect data in a fixed manner, being unable to supervise the entire production process and situation, having unidirectional data flow, and lacking bidirectional interactivity.

[0004] This invention provides an integrated data monitoring system for thermal sensing devices. The system includes: a data acquisition card for acquiring various analog or digital signals, and based on TCP and proprietary user protocols, uploading the acquired, filtered, and denoised data to a data acquisition device via a network port; a data acquisition device connected to the data acquisition card, used to control the data acquisition card according to instructions from the system monitoring center, and sending the acquired data to an integrated network controller through its respective interface protocols; and an integrated network controller connected to the data acquisition device, used to convert communication protocol data from different data acquisition devices into a unified mode, and send the acquired data to the system monitoring center through this unified mode, as well as convert received data or instructions into a communication format corresponding to the data acquisition device. The system transmits data or instructions to the data acquisition device via this communication format. The system monitoring center, connected to the integrated network controller, classifies and records the received data, compares it with pre-stored parameters and normal data ranges, and alarms are triggered if the data exceeds the range or abnormal data is detected. Abnormal data is removed, and normal data is smoothed to produce a graph. The processed data and graph are then sent to the cloud platform data center. The cloud platform data center, connected to the system monitoring center, analyzes and statistically processes the received data based on the type and model of the processed product, the operator, and the product's qualification status. Using a time synchronization algorithm, the time dimension of the data is unified, and the data is converted into an image. Based on user instructions, the data image and graph are displayed for remote monitoring.

[0005] Furthermore, the acquisition card includes: an analog input interface for acquiring workpiece parameters in real time and inputting them to an AD signal processing chip, the workpiece parameters including voltage and current; a digital input interface for acquiring operating status parameters of the thermal sensing equipment and inputting them to an FPGA chip, the operating status parameters including system master clock, drive output, and feedback input; an AD signal processing chip connected to the analog input interface for receiving workpiece parameters, performing analog-to-digital conversion, and sending them to the FPGA chip; and an FPGA chip connected to both the digital input interface and the AD signal processing chip for filtering and denoising the analog-to-digital converted workpiece parameters and operating status parameters, then packaging them in a structure defined by a private user protocol and uploading them to the data acquisition device via a network port based on the TCP protocol.

[0006] Furthermore, the sampling rate of the acquisition card is not less than 100 kS / s to capture transient current / voltage fluctuations of the induced power supply.

[0007] Furthermore, the integrated network controller includes: an uplink conversion module connected to the system monitoring center, used to integrate OPC UA, Modbus TCP / RTU, TCP / IP, and MQTT industrial communication protocols, providing standardized APIs and data interaction specifications, converting communication protocol data from different data acquisition devices into a unified mode, and sending the acquired data to the system monitoring center through this unified mode; and a downlink conversion module connected to the data acquisition device, used to convert received data or instructions into a communication format corresponding to the data acquisition device, and sending the data or instructions to the data acquisition device through this communication format.

[0008] Furthermore, the system monitoring center includes: a data recording module, connected to the integrated controller, for receiving and classifying data, accessing the database, creating data tables in the database according to data type, and writing the classified data into the corresponding data tables; a data analysis module, connected to the data recording module, for storing the configuration parameters and normal data ranges of each equipment component in the database during equipment installation, comparing the data written to the database with the parameters and normal data ranges, and triggering an alarm if the data exceeds the range or abnormal data occurs, while removing abnormal data and smoothing normal data to obtain a curve graph; a data statistics module, connected to the data recording module, for classifying and statistically analyzing data according to product type, model, and operator, and generating data packets; and an interaction module, connected to the data analysis module and the data statistics module respectively, for uploading the curve graphs and data packets to the cloud platform data center, and receiving user instructions sent by the cloud platform data center.

[0009] Furthermore, the system monitoring center is also used to: trigger scheduled tasks, call log services and database services, and store the system's action status and process data through these services for system diagnosis and remote updates.

[0010] This invention provides an integrated data monitoring method for thermal sensing devices. The method includes: Step 1, acquiring various analog or digital signals, and uploading the acquired, filtered, and denoised data to the data acquisition device via a network port based on TCP and a private user protocol; Step 2, the cloud platform data center sends user commands to the integrated network controller through the system monitoring center; Step 3, the integrated network controller converts the commands into a communication format corresponding to the data acquisition device, and sends the data or commands to the data acquisition device through this communication format; Step 4, the data acquisition device acquires data during the production process according to the commands, and sends the acquired data to the integrated network controller through its respective interface protocol; Step 5, the integrated network controller processes different data acquisition signals... Step 6: The data from the collected devices' communication protocols is converted into a unified mode and sent to the system monitoring center through this unified mode. Step 7: The system monitoring center categorizes and records the received data, comparing it with pre-stored parameters and normal data ranges. If the data exceeds the range or abnormal data appears, an alarm is triggered. Abnormal data is removed, and normal data is smoothed to obtain a graph. The processed data and graph are then sent to the cloud platform data center. Step 8: After receiving the data, the cloud platform data center analyzes and statistically processes it based on the type and model of the processed product, the operator, and whether the product is qualified. Using a time synchronization algorithm, the time dimension of the data is unified, and the data is converted into an image. Based on user instructions, the data image and graph are displayed for remote monitoring.

[0011] Furthermore, step 1 includes: step 11, acquiring workpiece parameters in real time via the analog input interface and inputting them to the AD signal processing chip, the workpiece parameters including voltage and current; step 12, acquiring the operating status parameters of the thermal sensing device via the digital input interface and inputting them to the FPGA chip, the operating status parameters including system master clock, drive output, and feedback input; step 13, receiving the workpiece parameters via the AD signal processing chip, completing the analog-to-digital conversion, and sending them to the FPGA chip; step 14, filtering and denoising the workpiece parameters and operating status parameters after analog-to-digital conversion using a digital filtering algorithm, then packaging them in a structure defined by a private user protocol, and uploading them to the data acquisition device via the network port based on the TCP protocol.

[0012] Furthermore, step 5 includes: Step 51, during equipment installation, storing the parameter indicators and normal data ranges of each equipment component in the database; Step 52, receiving and classifying the data, calling the database, creating data tables in the database according to data type, and writing the classified data into the corresponding data tables; Step 53, comparing the data written to the database with the parameter indicators and normal data ranges, and if the data exceeds the range or abnormal data appears, an alarm is triggered, and abnormal data is removed while normal data is smoothed to obtain a curve; Step 54, classifying and statistically analyzing the data according to product type, model, and operator, generating data packets, and uploading the curve and data packets to the cloud platform data center.

[0013] Furthermore, step 5 also includes: step 55, triggering a scheduled task, calling the log service and database service, and storing the system's action status and process data through these services for system diagnosis and remote updates.

[0014] This invention provides an integrated data monitoring system and method for thermal sensing equipment, mainly to solve the technical problems of existing technologies, such as being only adaptable to specific application scenarios, being unable to adapt to changes in the specific needs of production equipment, only monitoring equipment parameters without controlling the overall production situation and process status, having relatively simple data monitoring functions (only monitoring the status of equipment without monitoring and managing the entire production process), having unidirectional data flow, and lacking two-way interactivity. Attached Figure Description

[0015] Figure 1 This invention provides a schematic diagram of an integrated data monitoring system for thermal sensing devices. Figure 2 A flowchart of an integrated data monitoring method for thermal sensing devices provided by the present invention; Figure 3 This is a flowchart of the data processing method for the system monitoring center provided by the present invention. Detailed Implementation

[0016] The exemplary embodiments of this disclosure are described below with reference to the accompanying drawings, including various details of the embodiments to aid understanding, and should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this disclosure. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0017] Device Example: This invention provides an integrated data monitoring system for thermal sensing devices, which, as follows: Figure 1As shown, the system includes a data acquisition card, a data acquisition device, an integrated network controller, a system monitoring center, and a cloud platform data center.

[0018] A data acquisition card is used to acquire various analog or digital signals. Based on TCP and a proprietary user protocol, it uploads the acquired, filtered, and denoised data to the data acquisition device via a network port. The acquisition card includes: an analog input interface for real-time acquisition of workpiece parameters, which are input to an AD signal processing chip; the workpiece parameters include voltage and current; a digital input interface for acquiring operating status parameters of the thermal sensing equipment and inputting them to an FPGA chip; the operating status parameters include the system master clock, drive output, and feedback input; an AD signal processing chip connected to the analog input interface for receiving workpiece parameters, performing analog-to-digital conversion, and sending the data to the FPGA chip; and an FPGA chip connected to both the digital input interface and the AD signal processing chip for filtering and denoising the converted workpiece parameters and operating status parameters, then packaging them in a structure defined by the proprietary user protocol and uploading them to the data acquisition device via a network port based on the TCP protocol. Since most existing solutions treat data acquisition as merely a branch function of the thermal sensing device's main control, a failure in the main control itself, such as an abnormal output of the system's master clock, will affect the entire data acquisition function, preventing timely output of fault information. Furthermore, the resource requirements of the main control limit the scalability of its data acquisition section. However, by establishing a separate acquisition card, data acquisition is decoupled from the thermal sensing device's main control. Even if the main control itself fails, the acquisition card can still capture and send error information promptly. Additionally, a separate card provides more available resources, resulting in better scalability and increased stability and scalability of the data acquisition. Decoupling data acquisition from the thermal sensing device's main control allows it to be used not only for monitoring the production process but also for monitoring the operating status of the thermal sensing device and assisting in troubleshooting faults. FPGA chips (Field-Programmable Gate Arrays) are a special type of logic chip, belonging to semi-custom, programmable chips. AD signal processing chips (A / D converters) provide the function of converting analog signals into digital signals. The FPGA chip used in the acquisition card, along with data transmission based on TCP and proprietary user protocols, ensures the real-time performance, stability, and scalability of the data acquisition. FPGA chips are characterized by flexible configuration and support for parallel computing. This allows the acquisition card to reserve a sufficient number of data acquisition input interfaces, facilitating the expansion of signals under test, and ensuring that all data can be acquired, processed, and uploaded synchronously. A proprietary user protocol defines the type, length, and byte length of each field of the uploaded data, allowing the uploaded data to be easily and flexibly changed according to the actual number and type of signals under test. Network transmission based on the TCP protocol guarantees the real-time performance and reliability of data transmission.This invention presents a direct power data acquisition architecture that bypasses the PLC data processing and forwarding stages. Data acquisition, preprocessing, and transmission are completed directly through the power acquisition board, eliminating the accuracy loss and transmission delay caused by the PLC. The data transmission path is shortened by 70% (as shown in Table 1), and the number of fault points is reduced by 60%, achieving "high-fidelity, low-latency" data acquisition. This invention also constructs a scalable monitoring configuration platform, employing a modular and plug-in design. Users can independently add, delete, and combine any monitoring items without modifying the core code, expanding monitoring dimensions and breaking through the technical bottleneck of traditional monitoring systems being "fixed and difficult to expand."

[0019]

[0020] Table 1 Data acquisition devices, connected to acquisition cards, are used to control the acquisition cards according to instructions issued by the system monitoring center, and send the acquired data to the integrated network controller through their respective interface protocols. Besides the acquisition cards, there are also marking devices, barcode scanners, etc., all of which are objects controlled by this system. These devices interact and communicate with the integrated network controller module through their respective interface protocols, and perform corresponding outputs and actions according to instructions issued by the system monitoring center.

[0021] An integrated network controller, connected to data acquisition equipment, integrates OPC UA, Modbus TCP / RTU, TCP / IP, and MQTT industrial communication protocols. It provides standardized APIs and data interaction specifications, converting communication protocol data from different data acquisition devices into a unified mode and sending the acquired data to the system monitoring center through this unified mode. It also converts received data or commands into a communication format corresponding to the data acquisition device and sends the data or commands to the data acquisition device through this communication format. The integrated network controller includes: an uplink conversion module, connected to the system monitoring center, used to convert communication protocol data from different data acquisition devices into a unified mode and send the acquired data to the system monitoring center through this unified mode; and a downlink conversion module, connected to the data acquisition device, used to convert received data or commands into a communication format corresponding to the data acquisition device and send the data or commands to the data acquisition device through this communication format. The integrated controller is typically an ADIN2299. This invention proposes a "unified kernel + configurable adaptation" architecture. By abstracting the common logic of machine tool equipment and encapsulating differentiated parameter interfaces, it enables a single core codebase to adapt to multiple models and types of machine tools, completely solving the pain point of repetitive development of similar software with "one version per machine," and significantly improving system scalability and maintainability. A multi-protocol compatible communication interface layer integrates mainstream industrial communication protocols such as OPC UA, Modbus TCP / RTU, TCP / IP, and MQTT, providing standardized APIs and data interaction specifications to achieve bidirectional data interface with the MES system. This supports core business functions such as production plan issuance, equipment status feedback, process parameter synchronization, and quality data uploading, constructing a complete digital production data flow.

[0022] The system monitoring center, connected to the integrated network controller, is used to classify and record the received data, and compare it with pre-stored parameters and normal data ranges. If the data exceeds the range or abnormal data occurs, an alarm is triggered. At the same time, abnormal data is removed, and normal data is smoothed to obtain a curve. The processed data and curve are then sent to the cloud platform data center. The system monitoring center includes: a data recording module, connected to the integrated controller, for receiving and classifying data, accessing the database, creating data tables in the database according to data type, and writing the classified data into the corresponding data tables; a data analysis module, connected to the data recording module, for storing the parameter indicators and normal data ranges of each equipment component in the database during equipment installation, comparing the data written to the database with the parameter indicators and normal data ranges, and triggering an alarm if the data exceeds the range or abnormal data is found, while removing abnormal data and smoothing normal data to obtain a curve graph; a data statistics module, connected to the data recording module, for classifying and statistically analyzing data according to product type, model, and operator, and generating data packets; and an interaction module, connected to the data analysis module and the data statistics module respectively, for uploading curve graphs and data packets to the cloud platform data center, and receiving user commands sent by the cloud platform data center. The system monitoring center is also used to: trigger scheduled tasks, access log services and database services, and store the system's action status and process data through these services for system diagnostics and remote updates. The system monitoring center serves as the data processing, management, display, and human-machine interaction hub for the entire system. It is primarily responsible for recording, analyzing, processing, and statistically analyzing data generated throughout the entire production process of the thermal sensing equipment. It connects to the integrated network controller module via a local area network (LAN) to acquire various system monitoring data and to the cloud platform data center module via a wide area network (WAN) to interact with the cloud platform. The system pre-stores quenching current-time curve templates corresponding to different steel grades. Based on the processed product type, process parameters, and quality standards, after scanning and identifying the workpiece material, the corresponding template is automatically loaded as the normal range. This achieves deep matching between the monitoring scheme and the processing technology, improving the targeting and effectiveness of process monitoring. When data is recorded in real-time during production, the system monitoring center compares the recorded data with reference data in real time. If the data exceeds the range or abnormal data occurs, an alarm will be issued. The range of the reference data is: I min (p),I max (p) = f(material, diameter, frequency), where p is the workpiece process parameter vector, and the function f can be looked up in a table or calculated using empirical formulas. For the recorded data, I min (p) is the lower limit of the range, I max(p) represents the upper limit of the range, the value of which is determined by the material, diameter, and recording rate of the workpiece. For example, power supply voltage and current are processed according to certain rules. Taking power supply voltage as an example, the rules are as follows: Power supply voltage has a calibrated value and a set fluctuation range during production. When the system receives new voltage data, if it is greater than 10 times the calibrated value, it is discarded as abnormal data. Otherwise, the data is normal. The average of the previous 10 data points is taken to eliminate collection fluctuations and smooth the data. If there are fewer than 10 preceding data points, the average of those data points is taken. A curve is plotted using the average value. If the curve is in the middle of the deviation curve above and below the calibrated value, it indicates that the voltage is normal during production; if it exceeds the deviation curve range, it is abnormal. For example, if the calibrated voltage value is 100 and the fluctuation range is 10%, if the collected voltage is greater than 1000, it is discarded; if it is less than 1000, it is considered normal. After processing, the data is displayed in real-time on the system monitoring center page using a curve plot.

[0023] The cloud platform data center, connected to the system monitoring center, receives data and analyzes and statistically processes it based on the type and model of the processed product, the operator, and the product's qualification status. This data is then converted into images and displayed as graphs and curves according to user commands for remote monitoring. The cloud platform data center communicates with the system monitoring center using the HTTPS protocol. By default, the system monitoring center automatically uploads production data to the cloud platform, which displays it in statistical graphs. Users can also issue specific commands, such as requesting to view the alarm status of a particular device over the past month. After the command is issued, the monitoring center uploads the corresponding data, displaying it clearly and concisely on the cloud platform data center. The cloud platform data center serves as the system's remote data management dashboard, enabling users to view the operating status and production conditions of the thermal sensing equipment anytime, anywhere, and to promptly issue commands to the system monitoring center. It achieves real-time dynamic visualization of the processing process, employing high-speed data acquisition and real-time rendering technology to simultaneously plot dynamic curves for multiple monitoring items. This intuitively reflects the fluctuation patterns of indicators during processing, providing real-time, intuitive, and traceable data support for processing status analysis, anomaly warnings, and process iteration. Meanwhile, the cloud-based remote diagnostic system enables real-time data interaction and command issuance between the device and the remote operation and maintenance center through encrypted VPN / private network channels. It supports remote real-time monitoring, fault code parsing, log tracing, online parameter debugging and firmware upgrades, enabling "remote troubleshooting without leaving home", significantly reducing operation and maintenance costs and downtime losses, and improving the level of intelligent operation and maintenance of equipment.

[0024] This invention discloses an integrated data monitoring system for thermal sensing equipment, primarily targeting industrial production scenarios involving thermal sensing equipment. The data acquisition equipment should be flexibly configured according to the actual application scenario, and the communication protocols of different devices are unified through an integrated network controller. The data monitoring system is more diversified in function, adding modules such as production process management and system authorization management. Users can also customize scheduled task services. A cloud platform data center module has been added, which allows remote viewing of equipment production status and operating status at any time, and also enables command interaction.

[0025] Method Example: This invention provides a method for an integrated data monitoring system for thermal sensing devices, such as... Figure 2 As shown, the method includes the following steps.

[0026] Step 1: The cloud platform data center sends user commands to the integrated network controller through the system monitoring center; The cloud platform data center is primarily used for remote monitoring of equipment status and production operations, as well as for interacting with specific commands. Typically, it utilizes Windows 10 systems, PHP programming language, and corresponding graphics frameworks to develop web applications, employing HTTPS protocol for communication with the system monitoring center. Once developed, the application is deployed to a wide area network server, allowing users to access it via computers or mobile devices.

[0027] Step 2: The integrated network controller converts the instructions into a communication format corresponding to the data acquisition device, and sends the data or instructions to the data acquisition device through this communication format; The integrated network controller can comprehensively process data from various communication protocols, flexibly converting and processing both uplink and downlink data. For uplink, the integrated network control module can convert data from different communication protocols into a unified format for interaction with the system monitoring center module. For downlink, the integrated network control module converts data or commands into the appropriate communication format based on the target acquisition device. Typically, to facilitate future system expansion, the ADIN2299, an industrial Ethernet solution product capable of integrating multiple protocols, is used.

[0028] Step 3: The data acquisition device collects data during the production process according to the instructions, and sends the collected data to the integrated network controller through its respective interface protocol; The thermal sensing equipment requires marking and scanning of workpieces during production, therefore it is equipped with a marking device and a barcode scanner, both of which transmit data using the TCP protocol. For the various power parameters of the system, due to the high requirements for latency and accuracy, a data acquisition card is configured. Other process parameters such as liquid spraying and cooling are acquired through a PLC (Programmable Logic Controller), typically a Siemens S7-1500 model PLC.

[0029] Step 4: The acquisition card acquires various analog or digital signals. Based on TCP and private user protocols, the acquired data, after filtering and noise reduction, is uploaded to the data acquisition device via the network port. Step 4 includes: Step 41: The analog input interface acquires the workpiece parameters in real time and inputs them into the AD signal processing chip. The workpiece parameters include voltage and current. Step 42: The digital input interface acquires the operating status parameters of the thermal sensing device and inputs them into the FPGA chip. The operating status parameters include the system master clock, drive output, and feedback input. Step 43: The AD signal processing chip receives the workpiece parameters, completes the analog-to-digital conversion, and then sends them to the FPGA chip. Step 44: The workpiece parameters and operating status parameters after analog-to-digital conversion are filtered and denoised using a digital filtering algorithm, and then packaged in a structure defined by a private user protocol and uploaded to the data acquisition device via the network port based on the TCP protocol.

[0030] Because industrially acquired data such as power supply, temperature, and humidity are susceptible to electromagnetic interference and noise, digital filtering algorithms such as Kalman filtering (dynamic data noise reduction, suitable for power parameters with high real-time requirements), moving average filtering (simple and efficient, suitable for slowly changing data such as temperature, humidity, and air pressure), and median filtering (removing pulse interference, suitable for data prone to sudden anomalies such as flow rate) are needed to eliminate interference and ensure data accuracy. Real-world testing shows that Kalman filtering can reduce voltage acquisition noise from ±30 mV to ±8 mV while maintaining a rise time of <100 μs.

[0031] Step 5: The integrated network controller converts different data signal communication protocol data into a unified mode, and sends the collected data to the system monitoring center through this unified mode; As mentioned earlier, for the uplink side, the integrated network control module can convert various communication protocol data into a unified format, thereby interacting with the system monitoring center module.

[0032] Step 6: The system monitoring center will classify and record the received data, and compare it with the pre-stored parameter indicators and normal data range. If the data exceeds the range or abnormal data appears, an alarm will be triggered. At the same time, the abnormal data will be removed, and the normal data will be smoothed to obtain a curve. The processed data and curve will be sent to the cloud platform data center. The system monitoring center analyzes and processes parameter data uploaded from data acquisition devices, including real-time parameter monitoring, parameter process verification, and parameter early warning. Simultaneously, it uploads the collected and processed workpiece processing data to the cloud platform data center, presenting it to users in an easily accessible manner through information classification and statistical analysis. The system monitoring center also integrates many functions, such as production management, product management, configuration management, and authorization management. Furthermore, it can trigger scheduled tasks, call log services and database services, storing system action status and process data for system diagnostics and remote updates. The system monitoring center is developed using the C++ programming language and QT framework on a Windows 10 system and uses an SQLite database for data storage. Figure 3 As shown, step 6 includes the following steps.

[0033] Step 61: During equipment installation, store the parameter indicators and normal data ranges of each equipment component in the database. During the entire equipment installation process, the database stores the parameter specifications and normal data ranges for each equipment component.

[0034] Step 62: Receive and classify the data, call the database, create data tables in the database according to data types, and write the classified data into the corresponding data tables; The system will classify and record the various types of data collected from the acquisition devices. The system monitoring center will call the database, create data tables in the database according to data types, and continuously write the data into each data table.

[0035] Step 63: Compare the data written to the database with the parameter indicators and the normal range of data. If the data exceeds the range or abnormal data appears, an alarm is triggered. At the same time, the abnormal data is removed and the normal data is smoothed to obtain a curve. When data is recorded in real time during production, the system monitoring center compares the recorded data with reference data in real time. If the data exceeds the range or is abnormal, an alarm will be issued. For certain types of recorded data, such as power supply voltage and current, the data is processed according to certain rules. Taking power supply voltage as an example, the rules are as follows: The power supply voltage has a calibrated value and a set fluctuation range during production. When the system receives new voltage data, if it is greater than 10 times the calibrated value, it is discarded as abnormal data. Otherwise, the data is normal. The average of the previous 10 data points is taken to eliminate the sampling fluctuation and smooth the data. If there are fewer than 10 data points, the average of those data points is taken. The average value is used to plot a curve. If the curve is in the middle of the deviation curve of the calibrated value, it means that the voltage is normal during production; if it exceeds the deviation curve range, it is abnormal. For example, if the calibrated voltage value is 100 and the fluctuation range is 10%, if the collected voltage is greater than 1000, it is discarded; if it is less than 1000, it is considered normal. After processing, the data is displayed in real time on the system monitoring center page through curve plotting.

[0036] Step 64: Classify and statistically analyze the data according to product type, model, and operator, generate a data package, and upload the graph and data package to the cloud platform data center.

[0037] Data from the entire production process is categorized and statistically analyzed based on factors such as product type, model, and operator, generating data packages, which are then uploaded to the cloud platform data center and presented graphically.

[0038] Step 65 triggers a scheduled task, calls the log service and database service, and stores the system's action status and process data through these services for system diagnosis and remote updates.

[0039] Step 7: After receiving the data, the cloud platform data center analyzes and statistically processes it according to the type and model of the processed products, the operators, and whether the products are qualified. Through a time synchronization algorithm, the time dimension of the data is unified and converted into images. According to user instructions, the data images and graphs are displayed for remote monitoring by the user.

[0040] Because data from multiple devices and multiple data collection points (power boards, PLCs) requires a unified time dimension, time synchronization algorithms such as NTP (Network Time Protocol) and PTP (Precision Time Protocol) are used to ensure millisecond-level time alignment, avoiding deviations in curve plotting and fault tracing caused by time differences. The processing data uploaded from the system monitoring center is in JSON format. After receiving the data, the cloud platform parses the JSON data and performs data analysis and statistics based on factors such as the type and model of the processed product, the operator, and whether the product is qualified. Depending on the different display needs, the data is converted into an appropriate format. For example, if a bar chart is to be drawn, the data needs to be converted into a bar chart format; if a pie chart is to be drawn, the data also needs to be processed and modified accordingly.

[0041] In summary, the beneficial effects of this invention are that it provides an integrated data management and monitoring solution for thermal sensing equipment. It connects various data acquisition devices to a system monitoring center via an integrated network controller module. Through the system monitoring center and cloud platform data center, process monitoring and unified management of the thermal sensing equipment can be conveniently achieved. The data acquisition devices can be flexibly configured according to actual needs, making this integrated data monitoring system more flexible. The system monitoring center module includes functions such as authorization management and user management, which greatly enhances the security and reliability of the entire system. Users can view the production status and operating condition of the entire thermal sensing equipment at any time through the cloud platform and interact with the system monitoring center, improving the efficiency of equipment production management. The entire data monitoring system is integrated, flexibly configurable, and features unified management, security, efficiency, and ease of operation. Combined with other industrial automation technologies, it will bring significant commercial value to industrial production.

[0042] The specific embodiments described above do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.

Claims

1. An integrated data monitoring system for thermal sensing equipment, characterized in that, The system includes: The data acquisition card is directly connected to the output of the inductive power supply and is used to acquire various analog or digital signals. Based on TCP and private user protocols, the acquired data, after filtering and noise reduction, is uploaded to the data acquisition device through the network port. The data acquisition device, connected to the acquisition card, is used to control the acquisition card according to the instructions issued by the system monitoring center, and to send the acquired data to the integrated network controller through their respective interface protocols; An integrated network controller is connected to the data acquisition device to convert communication protocol data from different data acquisition devices into a unified mode and send the acquired data to the system monitoring center through this unified mode. It also converts received data or instructions into a communication format corresponding to the data acquisition device and sends the data or instructions to the data acquisition device through this communication format. The system monitoring center, connected to the integrated network controller, is used to classify and record the received data and compare it with the pre-stored parameters and normal data range. If the data exceeds the range or abnormal data occurs, an alarm is triggered. At the same time, the abnormal data is removed, and the normal data is smoothed to obtain a curve. The processed data and curve are then sent to the cloud platform data center. The cloud platform data center, connected to the system monitoring center, is used to analyze and statistically process data after receiving it, based on the type and model of the processed products, the operators, and whether the products are qualified. Through a time synchronization algorithm, the time dimension of the data is unified, and then the data is converted into images. According to user instructions, the data images and graphs are displayed for remote monitoring by the user.

2. The integrated data monitoring system for thermal sensing equipment according to claim 1, characterized in that, The acquisition card includes: An analog input interface is used to acquire workpiece parameters in real time and input them to an AD signal processing chip. The workpiece parameters include voltage and current. A digital input interface is used to acquire the operating status parameters of the thermal sensing device and input them into the FPGA chip. The operating status parameters include the system master clock, drive output, and feedback input. The AD signal processing chip is connected to the analog input interface to receive workpiece parameters, complete the analog-to-digital conversion, and send them to the FPGA chip. The FPGA chip is connected to the digital input interface and the AD signal processing chip respectively. It is used to filter and denoise the workpiece parameters and operating status parameters after analog-to-digital conversion. Then, it is packaged in a structure defined by a private user protocol and uploaded to the data acquisition device through the network port based on the TCP protocol.

3. An integrated data monitoring system for thermal sensing devices according to claim 1 or 2, characterized in that, The sampling rate of the acquisition card is not less than 100 kS / s to capture transient current / voltage fluctuations of the induced power supply.

4. The integrated data monitoring system for thermal sensing equipment according to claim 1, characterized in that, The integrated network controller includes: The uplink conversion module, connected to the system monitoring center, is used to integrate OPC UA, Modbus TCP / RTU, TCP / IP, and MQTT industrial communication protocols. It provides standardized APIs and data interaction specifications, converts communication protocol data from different data acquisition devices into a unified mode, and sends the acquired data to the system monitoring center through this unified mode. The downlink conversion module, connected to the data acquisition device, is used to convert the received data or instructions into a communication format corresponding to the data acquisition device, and then send the data or instructions to the data acquisition device through this communication format.

5. The integrated data monitoring system for thermal sensing equipment according to claim 1, characterized in that, The system monitoring center includes: The data recording module, connected to the integrated controller, is used to receive and classify data, call the database, create data tables in the database according to data types, and write the classified data into the corresponding data tables. The data analysis module and the data recording module are used to store the parameter indicators and normal data range of each equipment component in the database during equipment installation. The data written to the database is compared with the parameter indicators and normal data range. If the data exceeds the range or abnormal data occurs, an alarm is triggered. At the same time, abnormal data is removed and normal data is smoothed to obtain a curve. The data statistics module, connected to the data recording module, is used to classify and statistically analyze data according to product type, model, and operator, and generate data packages. The interaction module is connected to the data analysis module and the data statistics module, respectively. It is used to upload graphs and data packets to the cloud platform data center and to receive user instructions sent by the cloud platform data center.

6. The integrated data monitoring system for thermal sensing equipment according to claim 1, characterized in that, The system monitoring center is also used to: trigger scheduled tasks, call log services and database services, and store the system's action status and process data through these services for system diagnosis and remote updates.

7. A method for using an integrated data monitoring system for thermal sensing devices as described in any one of claims 1-6, characterized in that, The method includes: Step 1: The cloud platform data center sends user commands to the integrated network controller through the system monitoring center; Step 2: The integrated network controller converts the instructions into a communication format corresponding to the data acquisition device, and sends the data or instructions to the data acquisition device through this communication format; Step 3: The data acquisition device collects data during the production process according to the instructions, and sends the collected data to the integrated network controller through its respective interface protocol; Step 4: The acquisition card acquires various analog or digital signals. Based on TCP and private user protocols, the acquired data, after filtering and noise reduction, is uploaded to the data acquisition device via the network port. Step 5: The integrated network controller converts different data signal communication protocol data into a unified mode, and sends the collected data to the system monitoring center through this unified mode; Step 6: The system monitoring center will classify and record the received data, and compare it with the pre-stored parameter indicators and normal data range. If the data exceeds the range or abnormal data appears, an alarm will be triggered. At the same time, the abnormal data will be removed, and the normal data will be smoothed to obtain a curve. The processed data and curve will be sent to the cloud platform data center. Step 7: After receiving the data, the cloud platform data center analyzes and statistically processes it according to the type and model of the processed products, the operators, and whether the products are qualified. Through a time synchronization algorithm, the time dimension of the data is unified and converted into images. According to user instructions, the data images and graphs are displayed for remote monitoring by the user.

8. The integrated data monitoring method for thermal sensing devices according to claim 7, characterized in that, Step 4 includes: Step 41: The analog input interface acquires the workpiece parameters in real time and inputs them into the AD signal processing chip. The workpiece parameters include voltage and current. Step 42: The digital input interface acquires the operating status parameters of the thermal sensing device and inputs them into the FPGA chip. The operating status parameters include the system master clock, drive output, and feedback input. Step 43: The AD signal processing chip receives the workpiece parameters, completes the analog-to-digital conversion, and then sends them to the FPGA chip. Step 44: The workpiece parameters and operating status parameters after analog-to-digital conversion are filtered and denoised using a digital filtering algorithm, and then packaged in a structure defined by a private user protocol and uploaded to the data acquisition device via the network port based on the TCP protocol.

9. The integrated data monitoring method for thermal sensing devices according to claim 7, characterized in that, Step 6 includes: Step 61: During equipment installation, store the parameter indicators and normal data ranges of each equipment component in the database. Step 62: Receive and classify the data, call the database, create data tables in the database according to data types, and write the classified data into the corresponding data tables; Step 63: Compare the data written to the database with the parameter indicators and the normal range of data. If the data exceeds the range or abnormal data appears, an alarm is triggered. At the same time, the abnormal data is removed and the normal data is smoothed to obtain a curve. Step 64: Classify and statistically analyze the data according to product type, model, and operator, generate a data package, and upload the graph and data package to the cloud platform data center.

10. The integrated data monitoring method for thermal sensing devices according to claim 9, characterized in that, Step 6 further includes: Step 65, triggering a scheduled task, calling the log service and database service, and storing the system's action status and process data through these services for system diagnosis and remote updates.

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