Wireless temperature measurement system and wireless temperature measurement method

Abstract

The invention discloses a wireless temperature measurement system and a wireless temperature measurement method, and relates to the technical field of infrared wireless temperature measurement. According to the infrared temperature measuring sensor, the microcontroller unit MCU, the wireless transmission module and the data processing terminal, the infrared temperature measuring sensor is specifically an infrared temperature measuring probe, the infrared temperature measuring probe with high precision and high sensitivity is selected as the infrared temperature measuring sensor, the microcontroller unit is connected with the infrared temperature measuring sensor, and the wireless transmission module is connected with the data processing terminal. The microprocessor is responsible for receiving the electric signal transmitted by the sensor, performing preliminary data processing and conversion and converting an analog signal into a digital signal so as to facilitate subsequent transmission and analysis; the wireless transmission module analyzes the data obtained by the microcontroller unit and uploads the data to the data processing terminal; the infrared temperature measurement sensor adopts a high-precision and high-sensitivity infrared temperature measurement probe and is provided with a protection structure, so that the accuracy and the stability of temperature measurement can be guaranteed, and the influence of external factors on the sensor is reduced.

Description

Technical Field

[0001] The invention relates to the technical field of infrared wireless temperature measurement, in particular to a wireless temperature measurement system and a wireless temperature measurement method. Background Art

[0002] The infrared temperature sensor is a multi-purpose economical infrared temperature sensor that integrates signal processing circuit and ambient temperature compensation circuit. It is fully calibrated by the factory, which makes it multi-purpose; However, the signal transmission distance of some infrared temperature sensors is limited when they measure temperature wirelessly. Especially in complex industrial environments, the signal may be interfered or attenuated, affecting the accurate transmission of data. In addition, the data processing efficiency of the background terminal is poor, affecting the normal data reporting. At the same time, when the current infrared temperature probe is in use, the end of the probe is blocked by impurities or dust at some high temperatures, and measurement deviations are prone to occur after a period of time. The current processing requires staff to dismantle and clean the fixed infrared temperature probe and then install it to the measuring point before re-working. This process is inefficient and cannot be handled well.

[0003] In view of the above problems, the inventors propose a wireless temperature measurement system and a wireless temperature measurement method to solve the above problems. Summary of the invention

[0004] In order to solve the above problems, the purpose of the present invention is to provide a wireless temperature measurement system and a wireless temperature measurement method.

[0005] In order to solve the above technical problems, the present invention adopts the following technical solutions: a wireless temperature measurement system, including an infrared temperature measurement sensor, a microcontroller unit (MCU), a wireless transmission module and a data processing terminal; The infrared temperature sensor is specifically an infrared temperature probe, and the infrared temperature sensor uses a high-precision, high-sensitivity infrared temperature probe; A protective structure is provided outside the infrared temperature measuring probe; The microcontroller unit is connected to the infrared temperature sensor, responsible for receiving the electrical signal from the sensor, and performing preliminary data processing and conversion, converting the analog signal into a digital signal for subsequent transmission and analysis; The wireless transmission module analyzes the data obtained by the microcontroller unit and uploads it to the data processing terminal, specifically using wireless communication technology with strong anti-interference ability; The data processing terminal is composed of a large number of servers or high-performance computers, which are equipped with large-capacity memory and high-speed processors, which are sufficient to cope with the massive influx of data from numerous wireless temperature measurement nodes. They receive data from each node stably and efficiently through pre-configured network interfaces and in accordance with established communication protocols (such as specific application layer protocols in the TCP / IP protocol suite).

[0006] The microcontroller unit has a built-in intelligent algorithm, which performs multi-dimensional filtering processing on the original data collected by the sensor to remove noise interference and improve data stability.

[0007] The wireless transmission module also includes an automatic retransmission mechanism, which automatically resends data when data transmission errors or loss are detected to ensure data integrity. At the same time, adaptive power regulation technology is used to dynamically adjust the transmission power according to signal strength and transmission distance, reduce power consumption and reduce interference to other devices.

[0008] The data processing center also includes a software platform setting. The software platform adopts an advanced layered architecture design. The bottom layer is the data storage layer. A high-performance distributed file system is selected, which can reliably store the received massive data on multiple storage nodes. The middle layer is the data management layer, which is responsible for indexing, classifying and retrieving the stored data, and using database management technology.

[0009] The data processing terminal has a real-time data visualization function. In terms of visualization, the software platform integrates professional drawing engines, such as Echarts or Plotly, which can display the temperature change trend of each monitoring point in a variety of charts, including line charts, bar charts, and thermal maps. The line graph is used to visually present the continuous temperature changes of a single monitoring point over a period of time (such as the past 24 hours, the past week, etc., the user can customize the time span as needed). By observing the trend of the line, operation and maintenance personnel can easily determine whether there is an abnormal trend of gradual increase or decrease in temperature; Histograms are often used to compare the temperature differences at different monitoring points at the same time, making it easy to quickly find areas with high or low temperatures. They are especially suitable for displaying temperature distribution in large factories or complex equipment groups. The thermal map perfectly integrates temperature data with spatial location information, using different shades of color to indicate the temperature of each area. When the operator stands in front of the large monitoring screen, he can clearly understand the temperature of the entire monitoring site, quickly locate the high-temperature hotspot area, and provide accurate guidance for timely cooling measures. The data processing terminal may use cluster analysis and anomaly detection algorithms in machine learning for data analysis; Using the clustering analysis algorithm in machine learning, the software platform can automatically divide many monitoring points into different categories according to the characteristics of historical temperature data (such as temperature value range, change frequency, etc.). Monitoring points in the same category often have similar temperature change patterns. The anomaly detection algorithm is built based on statistical principles and deep learning models (such as autoencoder neural networks). It establishes a normal distribution model for temperature data by learning from historical normal data. Once the real-time data deviates from the model by more than a certain threshold (such as three times the standard deviation), it immediately issues an abnormal temperature change warning.

[0010] The protective structure includes a protective head, a transparent protective lens is installed at the end of the protective head, the protective head is arranged at the end of the probe in the infrared temperature measuring probe, a mounting block is fixedly provided at one end of the infrared temperature measuring probe close to the detection head, mounting grooves are opened at the upper and lower ends of the mounting block on the side facing the protective head, a card block corresponding to the mounting groove is fixedly provided on the side of the protective head facing the mounting groove, and the card block is L-shaped as a whole and is installed obliquely; the top of one end of the card block inserted in the mounting groove passes through the mounting block, a fixed block is fixedly provided on the end of the mounting block close to the card block, a vertical pole is movably inserted at the top of the fixed block, a movable block is fixedly provided at the bottom of the vertical pole, and an extrusion block is fixedly provided at the bottom of the movable block, and a spring is sleeved on one end of the vertical pole located in the fixed block; the extrusion block is a hard and bendable ceramic material.

[0011] A wireless temperature measurement method comprises the following steps: S1, infrared temperature sensor collects infrared radiation signals of target objects in real time, and converts them into electrical signals and transmits them to MCU; S2, MCU processes and filters the sensor data and transmits the processed data to the wireless transmission module; S3, the wireless transmission module sends the data to the data processing center according to the set protocol and frequency; S4. The data processing center receives and stores data, performs real-time visualization and in-depth analysis, and determines whether to issue an alarm or provide optimization suggestions based on the analysis results.

[0012] Compared with the prior art, the present invention has the following beneficial effects: 1. The infrared temperature sensor uses a high-precision, high-sensitivity infrared temperature probe with a protective structure to ensure the accuracy and stability of temperature measurement and reduce the impact of external factors on the sensor.

[0013] 2. The wireless transmission module has an automatic retransmission mechanism. When data transmission errors or losses are detected, the data is automatically resent to ensure data integrity. At the same time, it adopts adaptive power regulation technology to dynamically adjust the transmission power according to signal strength and transmission distance, reduce power consumption and reduce interference to other devices, further ensuring stable data transmission in complex environments.

[0014] 3. The microcontroller unit has built-in intelligent algorithms, such as median filtering and mean filtering, which perform multi-dimensional filtering on the raw data collected by the sensor to remove noise interference, improve data stability, ensure the reliability of measurement data, and avoid the impact of inaccurate data on subsequent transmission and judgment.

[0015] 4. The protective head provided in the present invention can protect the infrared temperature measuring probe. When disassembling later, it is only necessary to press the vertical pole to pull out the protective head. The operation is very convenient and does not require too many steps and additional tools, thereby improving the overall processing efficiency and facilitating the staff to only operate. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] 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.

[0017] Figure 1 It is a schematic diagram of the system flow of the present invention.

[0018] Figure 2 It is a schematic diagram of the structure of the protective head of the present invention.

[0019] Figure 3 For the present invention Figure 2 Enlarged structural diagram at A in the middle.

[0020] In the figure: 1. Infrared temperature probe; 11. Mounting block; 12. Protective head; 13. Protective lens; 14. Mounting slot; 15. Block; 16. Fixed block; 17. Movable block; 18. Extrusion block; 19. Vertical pole; 2. Spring. DETAILED DESCRIPTION

[0021] 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.

[0022] like Figure 1-3 As shown, the present invention provides a wireless temperature measurement system, including an infrared temperature measurement sensor, a microcontroller unit, a wireless transmission module and a data processing terminal. The infrared temperature sensor is specifically an infrared temperature probe 1, and the infrared temperature sensor uses a high-precision, high-sensitivity infrared temperature probe 1; A protective structure is provided outside the infrared temperature measuring probe 1; The microcontroller unit is connected to the infrared temperature sensor, responsible for receiving the electrical signal from the sensor, and performing preliminary data processing and conversion, converting the analog signal into a digital signal for subsequent transmission and analysis; The wireless transmission module analyzes the data obtained by the microcontroller unit and uploads it to the data processing terminal. It adopts wireless communication technology with strong anti-interference ability, such as industrial-grade Wi-Fi6 or Bluetooth 5.0 or above standard protocols. Compared with traditional wireless modules, it has a longer transmission distance and stronger penetration ability, and can still ensure signal quality under the obstruction of obstacles in complex industrial environments; The data processing terminal is composed of a large number of servers or high-performance computers. These devices are equipped with large-capacity memory and high-speed processors, which are sufficient to cope with the massive influx of data from numerous wireless temperature measurement nodes. They receive data from each node stably and efficiently through pre-configured network interfaces and in accordance with established communication protocols (such as specific application layer protocols in the TCP / IP protocol suite).

[0023] The microcontroller unit has a built-in intelligent algorithm, which performs multi-dimensional filtering on the raw data collected by the sensor to remove noise interference and improve data stability. For example, algorithms such as median filtering and mean filtering are used to ensure the reliability of the measured data; control the working state of the wireless transmission module and coordinate the timing of data transmission and reception; first is the median filtering algorithm, which will sort the data from a set of continuously collected data (for example, 5 or 7 data samples are collected continuously, and the number of samples can be flexibly adjusted according to the actual noise situation) by size and select the middle value as the valid data output. This process can effectively eliminate the maximum or minimum noise caused by instantaneous pulse interference, making the output data closer to the actual temperature value.

[0024] The mean filter algorithm sums all the data within a certain time period (such as 10 data points collected in the past 1 second, the time window and sampling frequency can be configured as needed), and then divides it by the number of data points to obtain the average value as the filtered result. This algorithm can smooth out high-frequency random noise in the data and has a good suppression effect on the noise generated by the sensor due to slight environmental fluctuations. By alternating or switching these two filtering algorithms according to conditions, the MCU can fully cope with different types of noise interference and ensure the reliability of the measurement data.

[0025] The wireless transmission module also includes an automatic retransmission mechanism. When a data transmission error or loss is detected, the data is automatically resent to ensure the integrity of the data. At the same time, the adaptive power regulation technology is used to dynamically adjust the transmission power according to the signal strength and transmission distance, reduce power consumption and reduce interference to other devices; an advanced error detection and feedback system is built into the wireless transmission module. When the data is transmitted from the MCU, the module will immediately verify the data and use algorithms such as CRC (cyclic redundancy check) to generate a specific check code for each data packet. After receiving the data packet, the data processing center at the receiving end also verifies the data according to the CRC algorithm and compares the check code attached to the sending end. Once the two are found to be mismatched, it is determined that an error has occurred in the data transmission, and the receiving end will quickly send a retransmission request signal to the sending end (wireless transmission module). The wireless transmission module will re-extract the error data packet from the local cache in a very short time (usually less than 10 milliseconds) after receiving the signal, and send it again. At the same time, in order to avoid network congestion due to frequent retransmission, the module is also set with an upper limit on the number of retransmissions, which is generally set to 5-10 times. If the upper limit is exceeded and the transmission is still unsuccessful, a transmission failure alarm will be sent to the MCU for subsequent troubleshooting.

[0026] The data processing center also includes software platform settings. The software platform adopts an advanced layered architecture design. The bottom layer is the data storage layer. It uses a high-performance distributed file system (such as Ceph or GlusterFS) to reliably store the received massive data on multiple storage nodes, which not only ensures the persistence of the data, but also prevents data loss due to single point failures through data redundancy strategies. The middle layer is the data management layer, which is responsible for indexing, classifying and retrieving the stored data, and using database management technology (such as the hybrid architecture of relational database MySQL combined with NoSQL database MongoDB) to quickly locate and extract the required data fragments and improve data query efficiency. The upper layer is the data analysis and visualization layer.

[0027] The data processing terminal displays real-time data visualization. In terms of visualization, the software platform integrates professional drawing engines, such as Echarts or Plotly, which can display the temperature change trend of each monitoring point in a variety of charts, including line charts, bar charts, and thermal maps. The line graph is used to visually present the continuous temperature changes of a single monitoring point over a period of time (such as the past 24 hours, the past week, etc., the user can customize the time span as needed). By observing the trend of the line, operation and maintenance personnel can easily determine whether there is an abnormal trend of gradual increase or decrease in temperature; Histograms are often used to compare the temperature differences at different monitoring points at the same time, making it easy to quickly find areas with high or low temperatures. They are especially suitable for displaying temperature distribution in large factories or complex equipment groups. The heat map perfectly integrates temperature data with spatial location information, using different shades of color to indicate the temperature of each area. Operators standing in front of the large monitoring screen can grasp the overall temperature of the entire monitoring site at a glance, quickly locate high-temperature hotspots, and provide accurate guidance for timely cooling measures.

[0028] In data processing terminals, cluster analysis and anomaly detection algorithms in machine learning can be used for data analysis; Using the clustering analysis algorithm in machine learning, the software platform can automatically classify many monitoring points into different categories based on the characteristics of historical temperature data (such as temperature value range, change frequency, etc.). Monitoring points in the same category often have similar temperature change patterns, which helps operation and maintenance personnel understand the temperature distribution pattern of the entire monitoring system from a macro level and discover potential systemic temperature anomalies in advance; The anomaly detection algorithm is built based on statistical principles and deep learning models (such as autoencoder neural networks). It establishes a normal distribution model for temperature data by learning from historical normal data. Once the real-time data deviates from the model by more than a certain threshold (such as three times the standard deviation), it immediately issues an abnormal temperature change warning. At the same time, it analyzes the source of the abnormal data and the associated monitoring points in detail, providing accurate clues for equipment maintenance personnel to troubleshoot, helping to optimize production processes and reduce equipment downtime and production losses caused by abnormal temperatures.

[0029] The protective structure includes a protective head 12, a transparent protective lens 13 is installed at the end of the protective head 12, the protective head 12 is arranged at the end of the probe in the infrared temperature measuring probe 1, a mounting block 11 is fixedly provided at one end of the infrared temperature measuring probe 1 close to the detection head, a mounting groove 14 is opened at the upper and lower ends of the mounting block 11 facing the protective head 12, a card block 15 corresponding to the mounting groove 14 is fixedly provided on the side of the protective head 12 facing the mounting groove 14, and the card block 15 is L-shaped as a whole and is installed obliquely; the top of one end of the card block 15 inserted in the mounting groove 14 passes through the mounting block 11, and a fixed block 16 is fixedly provided on the end of the mounting block 11 close to the card block 15 passing through, a vertical rod 19 is movably inserted at the top of the fixed block 16, a movable block 17 is fixedly provided at the bottom of the vertical rod 19, and an extrusion block 18 is fixedly provided at the bottom of the movable block 17, and a spring 2 is sleeved on one end of the vertical rod 19 located in the fixed block 16.

[0030] The extrusion block 18 is made of a hard and bendable ceramic material.

[0031] A wireless temperature measurement method comprises the following steps: S1, infrared temperature sensor collects infrared radiation signals of target objects in real time, and converts them into electrical signals and transmits them to MCU; S2, MCU processes and filters the sensor data and transmits the processed data to the wireless transmission module; S3, the wireless transmission module sends the data to the data processing center according to the set protocol and frequency; S4. The data processing center receives and stores data, performs real-time visualization and in-depth analysis, and determines whether to issue an alarm or provide optimization suggestions based on the analysis results.

[0032] Working principle: During the temperature measurement process using the infrared temperature measuring probe 1, when a certain amount of dust and impurities accumulate at the end of the probe, the staff does not need to disassemble the infrared temperature measuring probe 1 as a whole. The staff only needs to press the vertical poles 19 arranged up and down. At this time, the vertical poles 19 will drive the movable block 17 and the extrusion block 18 to move downward. At this time, the extrusion block 18 will squeeze one end of the penetrating mounting block 11 to move it into the mounting groove 14. At this time, the staff only needs to pull the protective head 12 to complete the disassembly of the protective head 12. Since the protective head 12 covers the end of the infrared temperature measuring probe 1, impurities and dust will not adhere to the infrared temperature measuring probe 1. On the temperature probe 1, the protective head 12 can be removed very quickly through the above operation, and a new protective head 12 can be directly replaced later or it can be cleaned and reinstalled. During installation, the staff only needs to align the end of the protective head 12 with the installation slot 14 and insert it. During the insertion process, the block 15 will be squeezed until the end of the block 15 is close to the fixed block 16. At this time, the end of the block 15 will protrude through the installation block 11. At this time, the installation between the protective head 12 and the infrared temperature measuring probe 1 will be completed. The operation is very convenient, without too many steps and additional tools, so that the overall processing efficiency is improved, and it is convenient for the staff to only operate.

[0033] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A wireless temperature measurement system, comprising an infrared temperature measurement sensor, a microcontroller unit (MCU), a wireless transmission module and a data processing terminal, characterized in that: The infrared temperature sensor is specifically an infrared temperature probe (1), and the infrared temperature sensor uses a high-precision, high-sensitivity infrared temperature probe (1); The infrared temperature measuring probe (1) is provided with a protective structure on the outside; The microcontroller unit is connected to the infrared temperature sensor, responsible for receiving the electrical signal from the sensor, and performing preliminary data processing and conversion, converting the analog signal into a digital signal for subsequent transmission and analysis; The wireless transmission module analyzes the data obtained by the microcontroller unit and uploads it to the data processing terminal, specifically using wireless communication technology with strong anti-interference ability; The data processing terminal is composed of a large number of servers or high-performance computers, which are equipped with large-capacity memory and high-speed processors, which are sufficient to cope with the massive influx of data from numerous wireless temperature measurement nodes. They receive data from each node stably and efficiently through pre-configured network interfaces and in accordance with established communication protocols (such as specific application layer protocols in the TCP / IP protocol suite).

2. A wireless temperature measurement system as claimed in claim 1, characterized in that: The microcontroller unit has a built-in intelligent algorithm, which performs multi-dimensional filtering processing on the original data collected by the sensor to remove noise interference and improve data stability.

3. A wireless temperature measurement system as claimed in claim 1, characterized in that: The wireless transmission module also includes an automatic retransmission mechanism, which automatically resends data when data transmission errors or loss are detected to ensure data integrity. At the same time, adaptive power regulation technology is used to dynamically adjust the transmission power according to signal strength and transmission distance, reduce power consumption and reduce interference to other devices.

4. A wireless temperature measurement system as claimed in claim 1, characterized in that: The data processing center also includes a software platform setting. The software platform adopts an advanced layered architecture design. The bottom layer is the data storage layer. A high-performance distributed file system is selected, which can reliably store the received massive data on multiple storage nodes. The middle layer is the data management layer, which is responsible for indexing, classifying and retrieving the stored data, and using database management technology.

5. A wireless temperature measurement system as claimed in claim 4, characterized in that: The data processing terminal has a real-time data visualization function. In terms of visualization, the software platform integrates professional drawing engines, such as Echarts or Plotly, which can display the temperature change trend of each monitoring point in a variety of charts, including line charts, bar charts, and thermal maps. The line graph is used to visually present the continuous temperature changes of a single monitoring point over a period of time (such as the past 24 hours, the past week, etc., the user can customize the time span as needed). By observing the trend of the line, operation and maintenance personnel can easily determine whether there is an abnormal trend of gradual increase or decrease in temperature; Histograms are often used to compare the temperature differences at different monitoring points at the same time, making it easy to quickly find areas with high or low temperatures. They are especially suitable for displaying temperature distribution in large factories or complex equipment groups. The heat map perfectly integrates temperature data with spatial location information, using different shades of color to indicate the temperature of each area. Operators standing in front of the large monitoring screen can grasp the overall temperature of the entire monitoring site at a glance, quickly locate high-temperature hotspots, and provide accurate guidance for timely cooling measures.

6. A wireless temperature measurement system as claimed in claim 1, characterized in that: The data processing terminal may use cluster analysis and anomaly detection algorithms in machine learning for data analysis; Using the clustering analysis algorithm in machine learning, the software platform can automatically divide many monitoring points into different categories according to the characteristics of historical temperature data (such as temperature value range, change frequency, etc.). Monitoring points in the same category often have similar temperature change patterns. The anomaly detection algorithm is built based on statistical principles and deep learning models (such as autoencoder neural networks). It establishes a normal distribution model for temperature data by learning from historical normal data. Once the real-time data deviates from the model by more than a certain threshold (such as three times the standard deviation), it immediately issues an abnormal temperature change warning.

7. A wireless temperature measurement system as claimed in claim 1, characterized in that: The protective structure comprises a protective head (12), an end of the protective head (12) being provided with a transparent protective lens (13), the protective head (12) being arranged at the end of a probe in an infrared temperature measuring probe (1), an end of the infrared temperature measuring probe (1) close to the detection head being fixedly provided with a mounting block (11), a side of the mounting block (11) facing the protective head (12) having mounting grooves (14) formed at the upper and lower ends thereof, a side of the protective head (12) facing the mounting groove (14) being fixedly provided with a clamping block (15) arranged corresponding thereto, the clamping block (15) being arranged in an L-shape as a whole and being installed at an angle.

8. A wireless temperature measurement system as claimed in claim 7, characterized in that: The top of one end of the clamping block (15) inserted in the mounting groove (14) passes through the mounting block (11); a fixed block (16) is fixedly provided on the mounting block (11) at one end close to the clamping block (15) passing through; a vertical rod (19) is movably inserted at the top of the fixed block (16); a movable block (17) is fixedly provided at the bottom of the vertical rod (19); and an extrusion block (18) is fixedly provided at the bottom of the movable block (17); and a spring (2) is sleeved on one end of the vertical rod (19) located in the fixed block (16).

9. A wireless temperature measurement system as claimed in claim 8, characterized in that: The extrusion block (18) is made of a hard and bendable ceramic material.

10. A wireless temperature measurement method, characterized in that: The method comprises the following steps: S1, infrared temperature sensor collects infrared radiation signals of target objects in real time, and converts them into electrical signals and transmits them to MCU; S2, MCU processes and filters the sensor data and transmits the processed data to the wireless transmission module; S3, the wireless transmission module sends the data to the data processing center according to the set protocol and frequency; S4. The data processing center receives and stores data, performs real-time visualization and in-depth analysis, and determines whether to issue an alarm or provide optimization suggestions based on the analysis results.

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