IoT-based sensor acquisition device and its dynamic state control system

Abstract

This invention relates to the field of sensor technology, specifically to an IoT-based sensor acquisition device and its dynamic state control system. The device includes multiple sensors, a serial port module, a detection module, and a main control chip. The outputs of the various sensors are electrically connected to the inputs of the multiple serial port modules. The outputs of the serial port modules are communicatively connected to the inputs of the detection modules. The outputs of the detection modules are electrically connected to the input of the main control chip. When transmitting sensor data to the main control chip via the serial port module, the comparison module calculates the memory value of the converted data and then compresses the data based on the comparison result. This reduces the size of the transmitted data, facilitating rapid data transmission from the sensors to the main control chip. This allows workers to obtain sensor data promptly, enabling quick equipment operation and preventing operational errors.

Description

Technical Field

[0001] This invention relates to the field of sensor technology, and more specifically to a sensor acquisition device based on the Internet of Things and its dynamic state control system. Background Technology

[0002] In recent years, with the rapid development of science and technology, automation and intelligence have become an inevitable trend in social development. As we all know, signal acquisition technology is a key link in automation and intelligence. At present, signal acquisition is mainly accomplished by various sensors, such as temperature sensors for acquiring temperature signals, humidity sensors for acquiring humidity signals, pressure sensors for acquiring pressure signals, and so on.

[0003] A wireless sensor acquisition device based on the Internet of Things (IoT), as described in application number CN201420358047.0 and publication date 20141210, includes at least one sensor. Its features include: a serial port for connecting to the sensor to obtain the acquired signal; a JTAG adjustment interface for operating an independent, reference clock signal to test a chip; a CC2430 chip, the CC2430 chip including an 8-bit MCU, 128KB of programmable flash memory, 8KB of RAM, and a 2.4GHz RF transceiver; and a power supply module for providing power to the CC2430 chip; wherein: the sensor is electrically connected to the I / O input terminals of the CC2430 chip via the serial port; the JTAG adjustment interface is electrically connected to the CC2430 chip; and the power supply module is electrically connected to the power supply terminals of the CC2430 chip.

[0004] For example, patent application CN201610861671.6, published on April 6, 2018, describes a multi-channel sensor data acquisition device and data acquisition and export method. The device includes: a main control chip; a power module; a data storage module; an output serial port; a 3G module; and multiple sensor input interfaces, each connected to the main control chip. At least one input interface is connected to a temperature sensor via a data line, at least one to a vibration sensor via a data line, at least one to a tilt angle sensor via a data line, and at least one to an RFID module via a data line. A positioning module is also included, connected to a GPS positioning antenna via a GPS antenna. This patent offers rich data acquisition paths, allowing data acquisition via serial or CAN ports, compatibility with different interface sensors, and simultaneous acquisition of data from multiple sensors and GPS positioning data. The acquired data can be output in various ways, including via serial port or 3G network.

[0005] The sensors mentioned above and those in the prior art are mostly connected to the control equipment via cables. The sensors transmit the detected data to the control equipment through the cables. However, when the detected data is large, the data transmission speed is slow, which prevents the control equipment from receiving the equipment operation information in a timely manner. This affects the worker's judgment of the equipment and the worker's operation of the equipment, leading to problems in the equipment operation. Therefore, it is urgent to design a sensor acquisition device based on the Internet of Things and its dynamic state control system to solve the above problems. Summary of the Invention

[0006] The purpose of this invention is to provide an Internet of Things-based sensor acquisition device and its dynamic state control system to address the aforementioned shortcomings in the prior art.

[0007] To achieve the above objectives, the present invention provides the following technical solution:

[0008] The IoT-based sensor acquisition device includes multiple sensors, a serial port module, a detection module, and a main control chip. The output terminals of the multiple sensors are electrically connected to the input terminals of the multiple serial port modules. The output terminals of the serial port modules are communicatively connected to the input terminals of the detection modules. The output terminals of the detection modules are electrically connected to the input terminals of the main control chip. The output terminals of the main control chip are communicatively connected to the input terminals of the serial port modules. The output terminals of the serial port modules are communicatively connected to the input terminals of the multiple sensors.

[0009] The various sensors are arranged at the signal acquisition positions of the device under test to collect the operating data of the device under test;

[0010] The serial port module is used to connect the sensor to the main control chip and the detection module for communication.

[0011] The detection module is used to determine whether the data received by the serial port module is distorted or missing, and to repair the data.

[0012] The serial port module includes a comparison module, a conversion module, a compression module, a serial cable module, an antenna module, and a temporary storage module;

[0013] The serial cable module is connected to the sensor and detection module via a serial cable.

[0014] The antenna module is connected to the detection module via WiFi.

[0015] The conversion module is used to convert the data received by the serial cable module and the antenna module, and the conversion module adopts a data converter.

[0016] The comparison module is used to calculate the memory value of the data converted by the conversion module to obtain the comparison value S, and the formula for the comparison value S is as follows:

[0017]

[0018] Where N is the size of the data memory value after conversion by the conversion module, M is the optimal transmission rate of the serial cable module and the antenna module, and M is set according to the material of the serial cable module and the bandwidth of the antenna module.

[0019] It should be noted that the serial cable module uses Cat5e, Cat6, Cat6a, Cat7, and Cat8 cables, each with different transmission rates and frequency bandwidths.

[0020] 1) Cat5e network cable

[0021] Network cables are generally marked Cat.5E, with a frequency bandwidth of 100MHz and a transmission rate of 100Mbps. Cat 5e cables are an upgraded version of Cat 5 cables, generally used for 100Mbps networks, and support gigabit speeds over short distances.

[0022] 2) Category 6 network cable.

[0023] Network cables are generally marked Cat.6, with a frequency bandwidth of 250MHz and a transmission rate of 1000Mbps. Cat.6 cables are standard gigabit network cables, offering a significant performance improvement over Cat.5e cables because their internal copper cores are thicker, and a cross-shaped core is added to isolate the four twisted pairs, effectively reducing crosstalk.

[0024] 3) Cat6e network cable.

[0025] Network cables are typically marked Cat.6A, with a frequency bandwidth of 500MHz and a transmission rate of 10Gbps. They offer superior performance compared to Cat 6 cables and are considered 10 Gigabit Ethernet cables.

[0026] 4) Category 7 network cable.

[0027] Network cables are generally marked Cat7. They have a frequency bandwidth of 600MHz, a transmission rate of 10Gbps, and are double-shielded cables with both aluminum foil and aluminum-magnesium wire shielding. They are also 10 Gigabit Ethernet cables.

[0028] 5) Category 8 network cable.

[0029] Network cables are generally marked with Cat8, have a frequency bandwidth of 2000MHz, and a transmission rate of 40Gbps. They are currently considered high-grade network cables and are typically used in high-speed broadband environments.

[0030] Network cable quality:

[0031] Network cables are generally made of aluminum wire, copper-clad aluminum, or pure copper wire. When choosing a network cable, pay attention to the core material. The highest quality is copper core wire, which is suitable for PoE power supply and has strong conductivity. When testing a network cable, you can place it in an environment of 35℃ to 40℃ to see if the outer sheath softens. High-quality network cables have flame-retardant outer sheaths.

[0032] The antenna module uses WiFi; the theoretical WiFi speed is:

[0033] WiFi 4 single stream: 150Mbps, 4 streams: 600Mbps

[0034] WiFi 5 single stream: 433Mbps, 8 streams: 3466Mbps (wave2 version, 867Mbps, 8 streams: 6933Mbps)

[0035] WiFi 6 single stream: 1200Mbps, 8 streams: 9.6Gbps.

[0036] The compression module operates based on the comparison value calculated by the comparison module. When the comparison value S>1, the compression module starts; when the comparison value S≤1, the compression module does not run.

[0037] It should be noted that the compression module uses statistical compression, a common lossless compression algorithm that compresses data based on its statistical characteristics. The basic idea of ​​this algorithm is to use statistical information in the data to construct an encoding table, representing frequently occurring data patterns with shorter codes and less frequent patterns with longer codes, thereby achieving data compression.

[0038] The temporary storage module is used to temporarily store the data transmitted by the serial cable module and the antenna module for 7-15 days.

[0039] It should be noted that the temporary storage module uses a temporary storage device.

[0040] The detection module includes a verification module, a repair module, a calibration module, and a fusion module;

[0041] The calibration module compensates and calibrates the data transmitted by the serial port module using a sensor compensation algorithm formula. The sensor compensation algorithm includes a zero-point deviation compensation formula and a sensitivity compensation formula. The zero-point deviation compensation formula is used to correct the zero-point drift of the sensor, and the sensitivity compensation formula is used to correct the sensitivity error of the sensor.

[0042] The zero-point deviation compensation formula is as follows:

[0043] V' out =V out -V0

[0044] Among them, V' out V is the corrected output value. out V0 is the actual output value of the sensor, and V0 is the zero-point deviation of the sensor.

[0045] The sensitivity compensation formula is as follows:

[0046] V' out =V out ×(1+K)

[0047] Where is the corrected output value, is the actual output value of the sensor, and k is the sensitivity compensation coefficient of the sensor;

[0048] The fusion module fuses the data calibrated by the calibration module using a target attribute fusion strategy.

[0049] It should be noted that the Target Attribute-Based Fusion Strategy (FSBTA) is a distributed data processing procedure in which each sensor extracts target parameters and identifies different targets to form a target list; multiple target lists are then fused to obtain reliable and accurate target information, avoiding false alarms and missed detections.

[0050] The verification module uses a data verification method to verify the data fused by the fusion module, and the repair module is built based on data repair technology to repair the data that the verification module has failed to verify.

[0051] It should be noted that the data verification method uses cumulative verification. The cumulative verification is achieved by adding a byte of verification data to the end of the communication data packet. This byte is the byte-by-byte sum of all data in the data packet, ignoring any carry.

[0052] Data recovery technology uses professional recovery tools for backup and recovery.

[0053] A dynamic control system for the status of sensor acquisition devices based on the Internet of Things, wherein the control system is installed on the main control chip;

[0054] The control system includes an identification unit, a storage unit, a comparison unit, a feedback unit, and a calculation unit. The identification unit is used to identify and determine which type of sensor the data transmitted by the detection module belongs to. The data identified by the identification unit is transmitted to the calculation unit. The identification unit includes multiple sensor verification tools that can verify which type of sensor the data detected by the detection module belongs to.

[0055] The computing unit can perform simulation processing on the data identified by the recognition unit. The computing unit is simulation software for the device under test, and after inputting data, it can simulate the operating status data of the device under test. The simulated status data of the device under test and the actual status data of the device under test are both the speed of the device under test.

[0056] The comparison unit can compare the operating status data of the device under test simulated by the computing unit with the actual status data sent by the device under test stored in the storage unit. The comparison unit compares the operating status data of the device under test simulated by the computing unit with the actual status data sent by the device under test stored in the storage unit using a fast-slow comparison formula. The fast-slow comparison formula is P, and the calculation formula is as follows:

[0057]

[0058] Where w represents the running speed of the device under test simulated by the computing unit, and W represents the actual running speed of the device under test stored in the storage unit. {P=1} indicates that the device under test is running normally, the sensor detection results match the actual running results of the device, and the sensor status is normal. {P<1, P>1} indicates that the device under test is running abnormally, the sensor detection results do not match the actual running results of the device, and the sensor status is abnormal.

[0059] The storage unit includes a memory module, an expansion module, and a cleanup module. The memory module is divided into a sensor detection data storage area and a device-to-operation data storage area. The memory module is a solid-state drive with a smart chip. The expansion module creates new folders to store data in the sensor detection data storage area and the device-to-operation data storage area using date and time. The cleanup module automatically cleans the data in the memory module using a data retrieval formula, G, as shown below:

[0060]

[0061] Where g is the actual number of times the corresponding data is called within a certain period of time, F is the minimum standard number of times the data is called within a certain period of time, G≥1, the cleanup module does not clean up the corresponding data in the memory module, and when G<1, the cleanup module cleans up the corresponding data in the memory module.

[0062] The feedback unit sends information to the worker based on the comparison result of the comparison unit, reminding the worker to replace, repair and adjust the sensor in a timely manner. The storage unit is used to store the data processed by the identification unit and the comparison unit.

[0063] In the above technical solution, the sensor acquisition device and its dynamic state control system based on the Internet of Things provided by the present invention have the following beneficial effects:

[0064] (1) The serial port module designed in this invention can calculate the memory value of the data converted by the conversion module when the sensor transmits the data to the main control chip through the serial port module. Then, the data is compressed by the comparison result, so that the memory value of the transmitted data is reduced, which makes it convenient for the serial port module to quickly transmit the data detected by the sensor to the main control chip. This allows the workers to obtain the sensor detection data in a timely manner, so as to quickly operate the equipment and avoid errors in the operation of the equipment.

[0065] (2) The control system designed in this invention has a computing unit that can simulate the data identified by the identification unit, and then the comparison unit can compare the running status data of the device under test simulated by the computing unit with the actual status data sent by the device under test stored in the storage unit to determine whether the data detected by the sensor is consistent with the data during the operation of the device and whether the sensor is operating normally. Subsequently, the feedback unit will send information to the worker based on the comparison result of the comparison unit, so that the worker can quickly replace, repair and adjust the sensor to achieve control of the sensor. Attached Figure Description

[0066] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0067] Figure 1 This is a schematic diagram of the sensor acquisition device structure provided in an embodiment of the Internet of Things-based sensor acquisition device and its dynamic state control system of the present invention.

[0068] Figure 2 This is a schematic diagram of the serial port module structure provided in an embodiment of the IoT-based sensor acquisition device and its dynamic state control system of the present invention.

[0069] Figure 3 This is a schematic diagram of the detection module structure provided in an embodiment of the IoT-based sensor acquisition device and its dynamic state control system of the present invention.

[0070] Figure 4 This is a schematic diagram of the system structure of the sensor acquisition device and its dynamic state control system based on the Internet of Things according to the present invention.

[0071] Figure 5 This is a schematic diagram of the storage unit structure provided in an embodiment of the IoT-based sensor acquisition device and its dynamic state control system of the present invention. Detailed Implementation

[0072] To enable those skilled in the art to better understand the technical solution of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings.

[0073] like Figure 1-3 As shown in the figure, the IoT-based sensor acquisition device provided in this embodiment of the invention includes multiple sensors, a serial port module, a detection module, and a main control chip. The output terminals of the multiple sensors are electrically connected to the input terminals of the multiple serial port modules. The output terminals of the serial port modules are communicatively connected to the input terminals of the detection modules. The output terminals of the detection modules are electrically connected to the input terminals of the main control chip. The output terminals of the main control chip are communicatively connected to the input terminals of the serial port modules. The output terminals of the serial port modules are communicatively connected to the input terminals of the multiple sensors.

[0074] The various sensors are arranged at the signal acquisition positions of the device under test to collect the operating data of the device under test;

[0075] The serial port module is used to connect the sensor to the main control chip and the detection module for communication.

[0076] The detection module is used to determine whether the data received by the serial port module is distorted or missing, and to repair the data.

[0077] The serial port module includes a comparison module, a conversion module, a compression module, a serial cable module, an antenna module, and a temporary storage module;

[0078] The serial cable module is connected to the sensor and detection module via a serial cable.

[0079] The antenna module is connected to the detection module via WiFi.

[0080] The conversion module is used to convert the data received by the serial cable module and the antenna module, and the conversion module adopts a data converter.

[0081] The comparison module is used to calculate the memory value of the data converted by the conversion module to obtain the comparison value S, and the formula for the comparison value S is as follows:

[0082]

[0083] Where N is the size of the data memory value after conversion by the conversion module, M is the optimal transmission rate of the serial cable module and the antenna module, and M is set according to the material of the serial cable module and the bandwidth of the antenna module.

[0084] It should be noted that the serial cable module uses Cat5e, Cat6, Cat6a, Cat7, and Cat8 cables, each with different transmission rates and frequency bandwidths.

[0085] 1) Cat5e network cable

[0086] Network cables are generally marked Cat.5E, with a frequency bandwidth of 100MHz and a transmission rate of 100Mbps. Cat 5e cables are an upgraded version of Cat 5 cables, generally used for 100Mbps networks, and support gigabit speeds over short distances.

[0087] 2) Category 6 network cable.

[0088] Network cables are generally marked Cat.6, with a frequency bandwidth of 250MHz and a transmission rate of 1000Mbps. Cat.6 cables are standard gigabit network cables, offering a significant performance improvement over Cat.5e cables because their internal copper cores are thicker, and a cross-shaped core is added to isolate the four twisted pairs, effectively reducing crosstalk.

[0089] 3) Cat6e network cable.

[0090] Network cables are typically marked Cat.6A, with a frequency bandwidth of 500MHz and a transmission rate of 10Gbps. They offer superior performance compared to Cat 6 cables and are considered 10 Gigabit Ethernet cables.

[0091] 4) Category 7 network cable.

[0092] Network cables are generally marked Cat7. They have a frequency bandwidth of 600MHz, a transmission rate of 10Gbps, and are double-shielded cables with both aluminum foil and aluminum-magnesium wire shielding. They are also 10 Gigabit Ethernet cables.

[0093] 5) Category 8 network cable.

[0094] Network cables are generally marked with Cat8, have a frequency bandwidth of 2000MHz, and a transmission rate of 40Gbps. They are currently considered high-grade network cables and are typically used in high-speed broadband environments.

[0095] Network cable quality:

[0096] Network cables are generally made of aluminum wire, copper-clad aluminum, or pure copper wire. When choosing a network cable, pay attention to the core material. The highest quality is copper core wire, which is suitable for PoE power supply and has strong conductivity. When testing a network cable, you can place it in an environment of 35℃ to 40℃ to see if the outer sheath softens. High-quality network cables have flame-retardant outer sheaths.

[0097] The antenna module uses WiFi; the theoretical WiFi speed is:

[0098] WiFi 4 single stream: 150Mbps, 4 streams: 600Mbps

[0099] WiFi 5 single stream: 433Mbps, 8 streams: 3466Mbps (wave2 version, 867Mbps, 8 streams: 6933Mbps)

[0100] WiFi 6 single stream: 1200Mbps, 8 streams: 9.6Gbps.

[0101] The compression module operates based on the comparison value calculated by the comparison module. When the comparison value S>1, the compression module starts; when the comparison value S≤1, the compression module does not run.

[0102] It should be noted that the compression module uses statistical compression, a common lossless compression algorithm that compresses data based on its statistical characteristics. The basic idea of ​​this algorithm is to use statistical information in the data to construct an encoding table, representing frequently occurring data patterns with shorter codes and less frequent patterns with longer codes, thereby achieving data compression.

[0103] The temporary storage module is used to temporarily store the data transmitted by the serial cable module and the antenna module for 7-15 days.

[0104] It should be noted that the temporary storage module uses a temporary storage device.

[0105] The detection module includes a verification module, a repair module, a calibration module, and a fusion module;

[0106] The calibration module compensates and calibrates the data transmitted by the serial port module using a sensor compensation algorithm formula. The sensor compensation algorithm includes a zero-point deviation compensation formula and a sensitivity compensation formula. The zero-point deviation compensation formula is used to correct the zero-point drift of the sensor, and the sensitivity compensation formula is used to correct the sensitivity error of the sensor.

[0107] The zero-point deviation compensation formula is as follows:

[0108] V' out =V out -V0

[0109] Among them, V' out V is the corrected output value. out V0 is the actual output value of the sensor, and V0 is the zero-point deviation of the sensor.

[0110] The sensitivity compensation formula is as follows:

[0111] V' out =V out ×(1+K)

[0112] Where is the corrected output value, is the actual output value of the sensor, and k is the sensitivity compensation coefficient of the sensor;

[0113] It should be noted that the basic principle of zero-point deviation compensation is to introduce a small voltage value near zero level to maintain the output voltage at a certain level, thereby compensating for the output deviation of the error amplifier. Specifically, when the output of the error amplifier is negative, compensation is performed using a zero-point compensation circuit; when the output is positive, compensation is also performed using a zero-point compensation circuit.

[0114] The basic principle of the sensitivity compensation formula is to offset or reduce the impact of environmental changes (such as temperature changes) on sensor sensitivity by adjusting certain parameters in the circuit.

[0115] The fusion module fuses the data calibrated by the calibration module using a target attribute fusion strategy.

[0116] It should be noted that the Target Attribute-Based Fusion Strategy (FSBTA) is a distributed data processing procedure in which each sensor extracts target parameters and identifies different targets to form a target list; multiple target lists are then fused to obtain reliable and accurate target information, avoiding false alarms and missed detections.

[0117] The verification module uses a data verification method to verify the data fused by the fusion module, and the repair module is built based on data repair technology to repair the data that the verification module has failed to verify.

[0118] It should be noted that the data verification method uses cumulative verification. The cumulative verification is achieved by adding a byte of verification data to the end of the communication data packet. This byte is the byte-by-byte sum of all data in the data packet, ignoring any carry.

[0119] Data recovery technology uses professional recovery tools for backup and recovery.

[0120] A dynamic control system for the status of sensor acquisition devices based on the Internet of Things, wherein the control system is installed on the main control chip;

[0121] The control system includes an identification unit, a storage unit, a comparison unit, a feedback unit, and a calculation unit. The identification unit is used to identify and determine which type of sensor the data transmitted by the detection module belongs to. The data identified by the identification unit is transmitted to the calculation unit. The identification unit includes multiple sensor verification tools that can verify which type of sensor the data detected by the detection module belongs to.

[0122] The computing unit can perform simulation processing on the data identified by the recognition unit. The computing unit is simulation software for the device under test, and after inputting data, it can simulate the operating status data of the device under test. The simulated status data of the device under test and the actual status data of the device under test are both the speed of the device under test.

[0123] The comparison unit can compare the operating status data of the device under test simulated by the computing unit with the actual status data sent by the device under test stored in the storage unit. The comparison unit compares the operating status data of the device under test simulated by the computing unit with the actual status data sent by the device under test stored in the storage unit using a fast-slow comparison formula. The fast-slow comparison formula is P, and the calculation formula is as follows:

[0124]

[0125] Where w represents the running speed of the device under test simulated by the computing unit, and W represents the actual running speed of the device under test stored in the storage unit. {P=1} indicates that the device under test is running normally, the sensor detection results match the actual running results of the device, and the sensor status is normal. {P<1, P>1} indicates that the device under test is running abnormally, the sensor detection results do not match the actual running results of the device, and the sensor status is abnormal.

[0126] The storage unit includes a memory module, an expansion module, and a cleanup module. The memory module is divided into a sensor detection data storage area and a device-to-operation data storage area. The memory module is a solid-state drive with a smart chip. The expansion module creates new folders to store data in the sensor detection data storage area and the device-to-operation data storage area using date and time. The cleanup module automatically cleans the data in the memory module using a data retrieval formula, G, as shown below:

[0127]

[0128] Where g is the actual number of times the corresponding data is called within a certain period of time, F is the minimum standard number of times the data is called within a certain period of time, G≥1, the cleanup module does not clean up the corresponding data in the memory module, and when G<1, the cleanup module cleans up the corresponding data in the memory module.

[0129] The feedback unit sends information to the worker based on the comparison result of the comparison unit, reminding the worker to replace, repair and adjust the sensor in a timely manner. The storage unit is used to store the data processed by the identification unit and the comparison unit.

[0130] The foregoing has only described certain exemplary embodiments of the present invention by way of illustration. Undoubtedly, those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the foregoing drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

Claims

1. A sensor acquisition device based on the Internet of Things, comprising multiple sensors, multiple serial port modules, a detection module, and a main control chip, characterized in that: The output terminals of various sensors are electrically connected to the input terminals of multiple serial port modules. The output terminals of the serial port modules are connected to the input terminals of the detection modules. The output terminals of the detection modules are electrically connected to the input terminals of the main control chip. The output terminals of the main control chip are connected to the input terminals of the serial port modules. The output terminals of the serial port modules are connected to the input terminals of various sensors. The various sensors are arranged at the signal acquisition positions of the device under test to collect the operating data of the device under test; The serial port module is used to connect the sensor to the main control chip and the detection module for communication. The detection module is used to determine whether the data received by the serial port module is distorted or missing, and to repair the data. The serial port module includes a comparison module, a conversion module, a compression module, a serial cable module, an antenna module, and a temporary storage module; The serial cable module is connected to the sensor and detection module via a serial cable. The antenna module is connected to the detection module via WiFi. The conversion module is used to convert the data received by the serial cable module and the antenna module, and the conversion module adopts a data converter. The comparison module is used to calculate the memory value of the data converted by the conversion module to obtain the comparison value S, and the formula for the comparison value S is as follows: ； Where N is the size of the data memory value after conversion by the conversion module, M is the optimal transmission rate of the serial cable module and the antenna module, and M is set according to the material of the serial cable module and the bandwidth of the antenna module. The compression module operates based on the comparison value calculated by the comparison module. When the comparison value S>1, the compression module starts; when the comparison value S≤1, the compression module does not run. The temporary storage module is used to temporarily store the data transmitted by the serial cable module and the antenna module for 7-15 days. The detection module includes a verification module, a repair module, a calibration module, and a fusion module; The calibration module compensates and calibrates the data transmitted by the serial port module using a sensor compensation algorithm formula. The sensor compensation algorithm includes a zero-point deviation compensation formula and a sensitivity compensation formula. The zero-point deviation compensation formula is used to correct the zero-point drift of the sensor, and the sensitivity compensation formula is used to correct the sensitivity error of the sensor. The zero-point deviation compensation formula is as follows: ； in, The corrected output value. This is the actual output value of the sensor. This refers to the zero-point deviation of the sensor. The sensitivity compensation formula is as follows: ; Where is the corrected output value, is the actual output value of the sensor, and k is the sensor's sensitivity compensation coefficient; The fusion module fuses the data calibrated by the calibration module using a target attribute fusion strategy.

2. The sensor acquisition device based on the Internet of Things according to claim 1, characterized in that, The verification module uses a data verification method to verify the data fused by the fusion module, and the repair module is built based on data repair technology to repair the data that the verification module has failed to verify.

3. A dynamic control system for the status of an IoT-based sensor acquisition device, using the IoT-based sensor acquisition device as described in any one of claims 1-2, characterized in that, The control system is installed on the main control chip; The control system includes an identification unit, a storage unit, a comparison unit, a feedback unit, and a calculation unit. The identification unit is used to identify and determine which type of sensor the data transmitted by the detection module belongs to. The data identified by the identification unit is transmitted to the calculation unit, which can perform simulation processing on the data identified by the identification unit. The comparison unit can compare the operating status data of the device under test simulated by the calculation unit with the actual status data sent by the device under test stored in the storage unit. The feedback unit sends information to the worker based on the comparison result of the comparison unit, reminding the worker to replace, repair, and adjust the sensor in a timely manner. The storage unit is used to store the data processed by the identification unit and the comparison unit.

4. The IoT-based sensor acquisition device state dynamic control system according to claim 3, characterized in that, The identification unit includes multiple sensor verification tools to verify which sensor the data detected by the detection module belongs to.

5. The IoT-based sensor acquisition device state dynamic control system according to claim 3, characterized in that, The calculation unit is a simulation software for the device under test, and after inputting data, it simulates the operating status data of the device under test. The simulated status data and the actual status data of the device under test are both the speed at which the device under test operates.

6. The IoT-based sensor acquisition device state dynamic control system according to claim 3, characterized in that, The comparison unit compares the operating status data of the device under test simulated by the calculation unit with the actual status data sent by the device under test stored in the storage unit using a fast-slow comparison formula.

7. The IoT-based sensor acquisition device state dynamic control system according to claim 6, characterized in that, The fast-slow comparison formula is P, and the calculation formula is as follows: ； Where w represents the running speed of the device under test as simulated by the computing unit, and W represents the actual running speed of the device under test stored in the storage unit. {P=1} indicates that the device under test is running normally, the sensor detection results match the actual running results of the device, and the sensor status is normal. {P<1, P>1} indicates that the device under test is running abnormally, the sensor detection results do not match the actual running results of the device, and the sensor status is abnormal.

8. The IoT-based sensor acquisition device state dynamic control system according to claim 3, characterized in that, The storage unit includes a memory module, an expansion module, and a cleanup module. The memory module is divided into a sensor detection data storage area and a data storage area for the actual operation of the device under test. The memory module is a solid-state drive with a smart chip.

9. The IoT-based sensor acquisition device state dynamic control system according to claim 8, characterized in that, The extension module creates new folders to store data in the sensor detection data storage area and the actual operation data storage area of ​​the device under test, based on the date and time.

10. The IoT-based sensor acquisition device state dynamic control system according to claim 8, characterized in that, The cleanup module automatically cleans up the data in the memory module using a data call formula, and the data call formula G is as follows: ； Where g is the actual number of times the corresponding data is called within a certain period of time, F is the minimum standard number of times the data is called within a certain period of time, G≥1, the cleanup module does not clean up the corresponding data in the memory module, and when G<1, the cleanup module cleans up the corresponding data in the memory module.

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