Wireless intelligent acquisition system

Abstract

The application relates to a wireless intelligent acquisition system, which comprises a wireless intelligent acquisition transmission terminal, a sensor arranged on the wireless intelligent acquisition transmission terminal, a handheld terminal connected with the wireless intelligent acquisition transmission terminal, an inbuilt APP arranged in the handheld terminal, a cloud platform configured to the wireless intelligent acquisition transmission terminal, the wireless intelligent acquisition transmission terminal, real-time uploading of characteristic values to the cloud platform, automatic identification of the wireless intelligent acquisition transmission terminal on whether the sensor is connected, communication between a communication module and the handheld terminal, reading and configuration of data collected by the wireless intelligent acquisition transmission terminal by the handheld terminal, and compression algorithm of the data. Thus, communication with the handheld terminal can be realized, and the convenience of implementation and maintenance is improved. The sensor can be adapted to various devices on the market and can be used in different use environments. The cloud platform is additionally arranged, so that the data storage and planning management are facilitated. The wireless intelligent acquisition transmission terminal is independently arranged, so that the sensor data processing and docking are satisfied.

Description

Technical Field

[0001] This invention relates to a data acquisition system, and more particularly to a wireless intelligent data acquisition system. Background Technology

[0002] Wireless data acquisition and monitoring systems, unlike traditional wired data acquisition and monitoring systems, are based on wireless sensor network technology to achieve wireless acquisition and transmission of various environmental data.

[0003] Currently, conventional intelligent data acquisition systems are typically built using sensors and intelligent gateways. During implementation, a PC serves as the data processing and storage center, handling real-time display of collected data and storage of historical data. A microcontroller acts as the data acquisition terminal and core for transmission, primarily handling data acquisition and transmission. This model requires designing a communication protocol between the PC and the microcontroller to enable data interaction between them. This approach is costly, bulky, and inconvenient to carry. Furthermore, the PC requires the installation and design of necessary application software, and in open environments, the PC's power supply needs additional control, making it difficult to move.

[0004] At the same time, the data transmission is prone to errors due to its length, requiring appropriate data optimization or compression methods.

[0005] In view of the above-mentioned shortcomings, the designer has actively researched and innovated in order to create a wireless intelligent data acquisition system that has greater industrial application value. Summary of the Invention

[0006] To address the aforementioned technical problems, the purpose of this invention is to provide a wireless intelligent data acquisition system.

[0007] This invention discloses a wireless intelligent data acquisition system, comprising a wireless intelligent data acquisition and transmission terminal, wherein: the wireless intelligent data acquisition and transmission terminal is equipped with a sensor; the wireless intelligent data acquisition and transmission terminal is connected to a handheld terminal; the handheld terminal has a built-in APP; the wireless intelligent data acquisition and transmission terminal is configured with a cloud platform; the wireless intelligent data acquisition and transmission terminal uploads feature values ​​to the cloud platform in real time; and the wireless intelligent data acquisition and transmission terminal automatically identifies whether the sensor is connected.

[0008] The wireless intelligent data acquisition and transmission terminal includes a terminal body, which contains an integrated circuit module. The integrated circuit module includes an ADC module, an automatic identification module, an FPGA module, a CPU, a storage module, a power control module, an over-the-air wake-up identification module, a configuration module, and a communication module.

[0009] The communication module communicates with the handheld terminal, enabling the handheld terminal to read and configure the data collected by the wireless intelligent acquisition and transmission terminal. The data is compressed using a compression algorithm and then sent to the cloud platform. The cloud platform receives the data and decompresses it.

[0010] Furthermore, in the aforementioned wireless intelligent data acquisition system, the sensor is equipped with a digital interface. After being connected to the wireless intelligent data acquisition and transmission terminal, the wireless intelligent data acquisition and transmission terminal supplies power to the sensor, and the sensor automatically uploads its own information. The wireless intelligent data acquisition and transmission terminal identifies the sensor type through a digital protocol and initiates the corresponding feature value algorithm.

[0011] Furthermore, in the aforementioned wireless intelligent acquisition system, the storage module has a built-in feature value algorithm for matching sensors. The feature values ​​and thresholds in the feature value algorithm are settable, and the validity of the current original waveform is determined by the relationship between the real-time feature values ​​and the thresholds.

[0012] Furthermore, in the aforementioned wireless intelligent data acquisition system, the sensor is one or more of the following: a vibration sensor, an ultrasonic sensor, a pressure sensor, a strain sensor, a temperature sensor, and a current sensor.

[0013] Furthermore, in the aforementioned wireless intelligent data acquisition system, the power control module receives sensor access information from the CPU and selects to turn on or off the acquisition modules of the ADC and FPGA. The air wake-up identification module listens for information from the cloud platform via broadcast mode.

[0014] Furthermore, in the aforementioned wireless intelligent data acquisition system, the wireless intelligent data acquisition and transmission terminal is equipped with a time synchronization function when the sensor acquires data, and the acquired data is timestamped.

[0015] Furthermore, in the aforementioned wireless intelligent acquisition system, when no sensor is connected, the detection interface voltage is 0V; when a sensor is connected, the detection interface voltage is aV, where a is a high level and its value ranges from 2.5V to 5V.

[0016] Furthermore, in the aforementioned wireless intelligent data acquisition system, the compression algorithm process is as follows:

[0017] Let the data sequence to be transmitted be A(i), i∈(1,n), where A is a data sequence of a continuous signal in nature, i is the sequence number, and ns is the total amount of the sequence;

[0018] Perform term-by-term difference calculation on the data sequence A(i) to obtain the data sequence B(i), i∈(1,n-1);

[0019] Perform a bitwise XOR operation on the preceding and following elements of the data sequence B(i) to obtain the data sequence C(i), where i∈(1,n-2);

[0020] Obtain the following new sequences: A(1), B(1), C(1), C(2), ..., C(n-2);

[0021] The new sequence is deduplicated and sorted in ascending order to obtain the data sequence D(i);

[0022] Starting from i = 0, search in the data sequence C for n consecutive data with a valid length between 0 and the data sequence D. If there are any, group the corresponding data in the data sequence C together and change the corresponding data in the data sequence D to -1, i = i + 1, until i = length(D). If there are no such data, set i = i + 1 directly and continue searching in the data sequence C until i = length(D).

[0023] After receiving the data containing feature values, the cloud platform decompresses the data. The decompression process is as follows:

[0024] Let the received data segment be S. Extract the first 4 bits of data segment S and convert them into a decimal number a, which is the effective number of bits of the original waveform data in data segment S after compression.

[0025] Extract the first 4 bits of data from data segment S and convert the remaining 8 bits into a decimal number b, which is the number of data points after the original waveform data in data segment S is compressed.

[0026] Extract the first 12 bits of data from data segment S and the next two 16 bits, and place them in the first position of array A and the first position of array B, i.e., A(1) and B(1);

[0027] Based on the number of significant digits a and the number of data b in this data segment S, extract all data into array C, i.e., C(i) = S(44 + a * i), until i = b, at which point the data extraction is complete;

[0028] The extracted data is XORed and then stored in array B, i.e., B(j+1) = B(j). ⊕ C(j), j = j + 1, until the XOR calculation is completed, i.e., j = length(C);

[0029] The extracted data is processed and put into array A, i.e., A(k+1)=A(k)+B(k), k=k+1, until the sum is calculated, i.e., k=length(B);

[0030] The resulting array A is the original data of the original waveform before compression.

[0031] Furthermore, in the aforementioned wireless intelligent data acquisition system, the cloud platform is equipped with a database for storing various types of data. The handheld terminal can access the data in the database for algorithmic data processing and page display. The database can be connected to a third-party platform via an API interface.

[0032] Furthermore, in the aforementioned wireless intelligent data acquisition system, the communication module includes a WiFi module, a Bluetooth module, and a 5G module.

[0033] By means of the above-described solution, the present invention has at least the following advantages:

[0034] 1. It can communicate with handheld terminals, improving the convenience of implementation and maintenance.

[0035] 2. The sensor is compatible with a variety of devices currently on the market and can be used in different application environments.

[0036] 3. Add a cloud platform to facilitate data storage and planning management.

[0037] 4. It is equipped with an independent wireless intelligent data acquisition and transmission terminal to meet the needs of sensor data processing and docking.

[0038] 5. The overall structure is simple, making it easy to lay out and implement.

[0039] The above description is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention and to implement it in accordance with the contents of the specification, the preferred embodiments of the present invention are described in detail below with reference to the accompanying drawings. Attached Figure Description

[0040] Figure 1 This is a schematic diagram of the structure of this wireless intelligent data acquisition system.

[0041] Figure 2 This is a schematic diagram showing the relationship between the CPU controlling the LDO to supply power to the sensor.

[0042] Figure 3 This is a schematic diagram of the I / O pin waveform for enabling the LDO pin of the CPU.

[0043] Figure 4 This is a flowchart illustrating the data compression algorithm.

[0044] Figure 5 This is a diagram illustrating data compression.

[0045] The meanings of the labels in the figures are as follows.

[0046] 1. Wireless intelligent data acquisition and transmission terminal; 2. Sensors

[0047] 3. Handheld terminal 4. Cloud platform

[0048] 5ADC module 6 Automatic identification module

[0049] 7 FPGA modules 8 CPUs

[0050] 9. Storage module 10. Power control module

[0051] 11. Air Wake-up Identification Module 12. Configuration Module

[0052] 13 Communication Module Detailed Implementation

[0053] The specific embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and examples. The following examples are for illustrative purposes only and are not intended to limit the scope of the invention.

[0054] like Figures 1 to 5 A wireless intelligent data acquisition system includes a wireless intelligent data acquisition and transmission terminal 1, which is unique in that: the wireless intelligent data acquisition and transmission terminal 1 is equipped with a sensor 2 to effectively acquire various data. Simultaneously, considering the convenience of backend maintenance and data viewing, a handheld terminal 3 is connected to the wireless intelligent data acquisition and transmission terminal 1, and the handheld terminal 3 has a built-in APP. Furthermore, to realize data uploading, backup, and retrieval, a cloud platform 4 is configured in the wireless intelligent data acquisition and transmission terminal 1, and the wireless intelligent data acquisition and transmission terminal 1 uploads feature values ​​to the cloud platform 4 in real time. During implementation, effective waveforms are uploaded during the intervals of feature value uploading, with interrupted transmission resumed. The wireless intelligent data acquisition and transmission terminal 1 automatically identifies whether the sensor 2 is connected. For ease of implementation, the wireless intelligent data acquisition and transmission terminal 1 includes a terminal body, which contains an integrated circuit module. The integrated circuit module includes an ADC module 5, an automatic identification module 6, an FPGA module 7, a CPU 8, a storage module 9, a power control module 10, an over-the-air wake-up identification module 11, a configuration module 12, and a communication module 13. Communication module 13 communicates with handheld terminal 3, enabling handheld terminal 3 to read and configure data collected by wireless intelligent data acquisition and transmission terminal 1. Furthermore, the data employs a compression algorithm to reduce data transmission volume and accelerate transmission speed. It should be noted that during actual implementation, data transmission primarily occurs directly between wireless intelligent data acquisition and transmission terminal 1 and cloud platform 4; handheld terminal 3 is mainly used for configuration and display.

[0055] In a preferred embodiment of the present invention, sensor 2 is equipped with a digital interface. After being connected to wireless intelligent data acquisition and transmission terminal 1, wireless intelligent data acquisition and transmission terminal 1 supplies power to sensor 2. As a result, sensor 2 automatically uploads its own information, and wireless intelligent data acquisition and transmission terminal 1 identifies the type of sensor 2 through a digital protocol and initiates the corresponding feature value algorithm. During implementation, different types of sensors 2 will correspond to different types of feature values. For example, the feature values ​​of vibration sensors include peak acceleration, RMS velocity, peak-to-peak displacement, envelope value, kurtosis, and margin; the feature values ​​of current sensors include current and power.

[0056] In practical implementation, the storage module 9 has a built-in feature value algorithm for matching sensor 2. The feature values ​​and thresholds in the feature value algorithm are settable, and the validity of the current original waveform is determined by the relationship between the real-time feature values ​​and the thresholds. Furthermore, considering the diversity of the data to be collected, and to have a wider range of applications, the sensor 2 involved in this invention can be one or more of the following: vibration sensor, ultrasonic sensor, pressure sensor, strain sensor, temperature sensor, and current sensor. Of course, with the expansion of functionality, other types of sensors 2 can also be used, which will not be elaborated here. During implementation, the feature values ​​of vibration sensors include peak acceleration, effective velocity, peak-to-peak displacement, frequency, envelope, kurtosis, and margin. The feature values ​​of ultrasonic sensors include frequency and peak acceleration. The feature values ​​of pressure sensors include pressure values. The feature values ​​of strain sensors include strain values. The feature values ​​of temperature sensors include temperature values. The feature values ​​of current sensors include current and power consumption. Therefore, different types of sensors 2 have their specific feature values, which will not be elaborated here.

[0057] Meanwhile, threshold values ​​are generally set according to national standards or actual application scenarios. For example, vibration sensors have the international standard ISO 10816, but this may not fully meet the needs. The characteristic value used as the threshold and the threshold value are selected based on the parameters of the equipment on which the sensor is actually installed. Furthermore, sensors are generally used to monitor whether there are problems with the equipment. Therefore, when the characteristic value is very small, the equipment itself is not faulty, and the waveform data collected is useless. When the characteristic value is large enough, it indicates that the equipment itself may have a problem. At this time, collecting the original waveform for analysis can help identify the specific location or component of the equipment that is malfunctioning.

[0058] Furthermore, during use, the power control module 10 receives information from the sensor 2 connected to the CPU 8 and selects to turn the ADC and FPGA acquisition modules on or off, thereby reducing power consumption. Simultaneously, relying on the over-the-air wake-up identification module 11, it can listen for information from the cloud platform 4 via broadcast mode, which also reduces power consumption.

[0059] During implementation, the wireless intelligent data acquisition and transmission terminal 1 has a time synchronization function when acquiring data from sensor 2, and the acquired data is timestamped. This allows for accurate identification of the data acquisition time, which is beneficial for comprehensive analysis of the device under test. For better connection and identification during time synchronization, the wireless intelligent acquisition interface voltage is 0V when sensor 2 is not connected; when sensor 2 is connected, the detection interface voltage is aV. During implementation, a is a high level, with a value ranging from 2.5V to 5V.

[0060] like Figure 4 As shown, to better implement this invention, the compression algorithm used is as follows: The data sequence to be transmitted is A(i), i∈(1,n), where A is a data sequence of a continuous signal in nature, i is the sequence number, and n is the total number of elements in the sequence. For example, if data sequence A is a vibration waveform, and A = {0.01, 0.03, 0.11, 0.15, 0.25, 0.36, 0.29, 0.24, 0.21, 0.15, 0.11, 0.04}, then this vibration waveform has 12 data points, the value range of i is 1 to 12, and n = 12.

[0061] Then, the data sequence A(i) is subtracted term by term to obtain the data sequence B(i), i∈(1,n-1);

[0062] Next, the preceding and following elements of the data sequence B(i) are XORed bitwise to obtain the data sequence C(i), where i∈(1,n-2). This reduces the number of valid values ​​without affecting the accuracy of transmission.

[0063] Subsequently, obtain each new sequence: A(1), B(1), C(1), C(2), ..., C(n-2).

[0064] Then, the new sequence is deduplicated and sorted in ascending order to obtain the data sequence D(i) (similarly, B, C, D, etc. all represent data sequences).

[0065] Finally, starting from i=0, search in the data sequence C for n consecutive data with a valid length between 0 and the data sequence D. If there are any, group the corresponding data in the data sequence C together and change the corresponding data in the data sequence D to -1, i=i+1, until i=length(D); if there are none, directly set i=i+1 and continue searching in the data sequence C until i=length(D).

[0066] like Figure 5 As shown, after the cloud platform or handheld terminal receives the compressed raw waveform data (data segment S), the decompression process is as follows:

[0067] Step 1: Extract the first 4 bits of data from data segment S and convert them to a decimal number 'a'. This represents the number of significant bits in the compressed original waveform data within data segment S. This allows us to confirm the direct value of the significant bits, facilitating subsequent verification after decompression and preventing decompression errors.

[0068] Step 2: Extract the first 4 bits of data from data segment S and convert the remaining 8 bits into a decimal number 'b'. This represents the number of data points in the compressed original waveform data within data segment S. This clearly identifies the number of data points in a single frame, enabling effective annotation and restoration, and preventing decompression errors.

[0069] Step 3: Extract the first 12 bits of data from data segment S and the next two 16 bits, and place them in the first position of array A and the first position of array B, i.e., A(1) and B(1).

[0070] Step 4: Extract all data into array C based on the number of significant digits a and the number of data points b in this data segment S, i.e., C(i) = S(44 + a*i), until i = b, at which point the data extraction is complete.

[0071] Step 5: Perform an XOR operation on the extracted data and store it in array B, i.e., B(j+1) = B(j). ⊕ C(j), j = j + 1, until the XOR calculation is completed, i.e., j = length(C). Thus, the initial restoration of the data is performed.

[0072] Step 6: Perform summation on the extracted data and store it in array A, i.e., A(k+1)=A(k)+B(k), k=k+1, until the summation is complete, i.e., k=length(B).

[0073] Ultimately, the resulting array A is the original data of the original waveform before compression. In this way, the original data before compression can be effectively restored, and the decompression is guaranteed to be accurate.

[0074] For better description, the compressed data segment format used during the implementation of this invention is as follows:

[0075]

[0076] During implementation, to ensure that cloud platform 4 has appropriate data storage and expansion capabilities, it is equipped with a database for storing various types of data. Handheld terminal 3 can access data from the database for algorithmic data processing and page display. The database can be connected to third-party platforms via API interfaces. Furthermore, considering the common formats of various newsletters, the communication module 13 is equipped with a WiFi module, a Bluetooth module, and a 5G module.

[0077] During the implementation of this invention, the relationship between the CPU controlling the LDO to supply power to the sensor is as follows:

[0078] like Figure 2 As shown, the CPU controls the LDO enable pin through the I / O pins. When the LDO (Low Dropout Linear Regulator) enable pin is high, it enables the sensor and supplies power; when the enable pin is low, it disables the sensor and does not output voltage to supply power.

[0079] like Figure 3 As shown, when the CPU enables the LDO pin's I / O pin, the pin is high during time period T1, enabling the LDO to power the sensor. During time period T2, the pin is low, disabling the LDO and preventing it from powering the sensor.

[0080] Therefore, we can define T = T1 + T2 as one cycle, with a recommended cycle length of 1 second. During implementation, the ratio of T1 to T2 can preferably be 1:9.

[0081] During time T1, the LDO is enabled. If a sensor is connected during this time period, the sensor is powered on and inputs sensor information through the digital interface. The information format is as follows:

[0082]

[0083]

[0084] Furthermore, after the CPU receives and identifies the sensor information, it starts the ADC (Analog-to-Digital Converter) and FPGA (Field-Programmable Gate Array) to acquire data and save the data to the corresponding location.

[0085] Take a vibration sensor as an example:

[0086] When no vibration sensor is connected to the wireless intelligent data acquisition and transmission terminal, the terminal does not need to activate the vibration sensor characteristic value. In other words, unless set via the handheld terminal, the default algorithm for the effective speed value is used. During this period, the wireless intelligent data acquisition and transmission terminal does not include vibration sensor characteristic value information when communicating with the handheld terminal and the cloud platform.

[0087] When the vibration sensor is connected to the wireless intelligent data acquisition and transmission terminal, the wireless intelligent data acquisition and transmission terminal detects that the analog interface voltage is not 0V (2.5V~5V), and then opens the corresponding digital interface to receive its own information transmitted from the vibration sensor.

[0088] Subsequently, the wireless intelligent data acquisition and transmission terminal detects the vibration sensor input and activates the algorithm for the vibration sensor characteristic value (the default effective speed value when not set via the handheld terminal). The wireless intelligent data acquisition and transmission terminal includes the vibration sensor characteristic value information when communicating with the handheld terminal and the cloud platform.

[0089] When not set via a handheld terminal, the vibration sensor characteristic value defaults to the effective velocity value, and the threshold is set to 2.3 mm / s according to the international standard ISO10816.

[0090] When the wireless intelligent acquisition and transmission terminal calculates the acquired waveform and finds that the effective value of the characteristic velocity is less than or equal to 2.3 mm / s, the terminal will not save the original vibration waveform. Instead, it will upload the vibration characteristic value along with the frame format of all characteristic values ​​to the cloud platform and the handheld terminal. When the calculated characteristic value is greater than 2.3 mm / s, the terminal will save the original vibration waveform and upload it to the cloud platform at the intervals during characteristic value transmission.

[0091] When the raw waveform is uploaded, the data is compressed first to reduce the amount of data transmitted and the transmission time. After the cloud platform receives the data, it decompresses it.

[0092] As can be seen from the above description and the accompanying drawings, the present invention has the following advantages:

[0093] 1. It can communicate with handheld terminals, improving the convenience of implementation and maintenance.

[0094] 2. The sensor is compatible with a variety of devices currently on the market and can be used in different application environments.

[0095] 3. Add a cloud platform to facilitate data storage and planning management.

[0096] 4. It is equipped with an independent wireless intelligent data acquisition and transmission terminal to meet the needs of sensor data processing and docking.

[0097] 5. The overall structure is simple, making it easy to lay out and implement.

[0098] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the technical principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A wireless intelligent data acquisition system, comprising a wireless intelligent data acquisition and transmission terminal, characterized in that: The wireless intelligent data acquisition and transmission terminal is equipped with a sensor and is connected to a handheld terminal. The handheld terminal has a built-in APP and is configured with a cloud platform. The wireless intelligent data acquisition and transmission terminal uploads feature values ​​to the cloud platform in real time. The wireless intelligent data acquisition and transmission terminal automatically identifies whether the sensor is connected. When the wireless intelligent data acquisition and transmission terminal uploads data, the effective waveform is uploaded during the interval of feature value upload, and the transmission can resume from the point of interruption. The data transmission is a direct transmission between the wireless intelligent data acquisition and transmission terminal and the cloud platform. The handheld terminal is used to configure and display the data. The wireless intelligent data acquisition and transmission terminal includes a terminal body, which contains an integrated circuit module. The integrated circuit module includes an ADC module, an automatic identification module, an FPGA module, a CPU, a storage module, a power control module, an over-the-air wake-up identification module, a configuration module, and a communication module. The ADC module is an analog-to-digital converter, and the FPGA module is a field-programmable gate array module. The communication module communicates with the handheld terminal, enabling the handheld terminal to read and configure the data collected by the wireless intelligent acquisition and transmission terminal. The data is compressed using a compression algorithm and then sent to the cloud platform. The cloud platform receives the data and decompresses it.

2. The wireless intelligent data acquisition system according to claim 1, characterized in that: The sensor is equipped with a digital interface. After being connected to a wireless intelligent data acquisition and transmission terminal, the wireless intelligent data acquisition and transmission terminal supplies power to the sensor, and the sensor automatically uploads its own information. The wireless intelligent data acquisition and transmission terminal identifies the sensor type through a digital protocol and starts the corresponding feature value algorithm.

3. The wireless intelligent data acquisition system according to claim 1, characterized in that: The storage module has a built-in feature value algorithm for matching sensors. The feature values ​​and thresholds in the feature value algorithm are settable. The validity of the current original waveform is determined by the relationship between the real-time feature values ​​and the thresholds.

4. The wireless intelligent data acquisition system according to claim 1, characterized in that: The sensor is one or more of the following: vibration sensor, ultrasonic sensor, pressure sensor, strain sensor, temperature sensor, and current sensor.

5. The wireless intelligent data acquisition system according to claim 1, characterized in that: The power control module receives sensor access information from the CPU and selects to turn the ADC and FPGA acquisition modules on or off to reduce power consumption. The over-the-air wake-up identification module listens for information from the cloud platform in broadcast mode to reduce power consumption.

6. The wireless intelligent data acquisition system according to claim 1, characterized in that: The wireless intelligent data acquisition and transmission terminal is equipped with a time synchronization function when collecting data from the sensor, and the collected data is timestamped.

7. The wireless intelligent data acquisition system according to claim 1, characterized in that: When no sensor is connected, the wireless intelligent acquisition interface voltage is 0V; when the sensor is connected, the detection interface voltage is aV, where a is a high level and the value range is 2.5V to 5V.

8. The wireless intelligent data acquisition system according to claim 1, characterized in that: The compression algorithm process is as follows: The data sequence to be transmitted is A(i), i∈(1,n), where A is a data sequence of a continuous signal in nature, i is the sequence number, and n is the total amount of the sequence; Perform term-by-term difference calculation on the data sequence A(i) to obtain the data sequence B(i), i∈(1,n-1); Perform a bitwise XOR operation on the preceding and following elements of the data sequence B(i) to obtain the data sequence C(i), where i∈(1,n-2); Obtain the following new sequences: A(1), B(1), C(1), C(2), ..., C(n-2); The new sequence is deduplicated and sorted in ascending order to obtain the data sequence D(i); Starting from i=0, search in the data sequence C for n consecutive valid data with lengths between 0 and D. If they exist, group the corresponding data in the data sequence C together and change the corresponding data in the data sequence D to -1, i=i+1, until i=length(D); if they do not exist, set i=i+1 directly and continue searching in the data sequence C until i=length(D). After receiving the data containing feature values, the cloud platform decompresses the data. The decompression process is as follows: Let the received data segment be S. Extract the first 4 bits of data segment S and convert them into a decimal number a, which is the effective number of bits of the original waveform data in data segment S after compression. Extract the first 4 bits of data from data segment S and convert the remaining 8 bits into a decimal number b, which is the number of data points after the original waveform data in data segment S is compressed. Extract the first 12 bits of data from data segment S and the next two 16 bits, and place them in the first position of array A and the first position of array B, i.e., A(1) and B(1); Based on the significant number of digits *a* and the number of data points *b* in this data segment *S*, extract all data into array *C*, i.e., *C(i) = S(44 + a)*. i), until i=b, the data extraction is complete; Perform an XOR operation on the extracted data and store it in array B, i.e., B(j+1)=B(j)⊕C(j), j=j+1, until the XOR operation is completed, i.e., j=length(C); The extracted data is processed by summation and placed into array A, i.e., A(k+1)=A(k)+B(k), k=k+1, until the summation is completed, i.e., k=length(B); The resulting array A is the original data of the original waveform before compression; The compression algorithm uses the following compressed data segment format: a) the number of effective compression bits for 4-bit data, b) the number of compressed data for 8-bit data, A(1) the first data of the original 16-bit data, B(1) the first data after the difference of the 16-bit data, and a Compressed data of b-bit data.

9. The wireless intelligent data acquisition system according to claim 1, characterized in that: The cloud platform is equipped with a database for storing various types of data. The handheld terminal can call the data in the database for algorithm data processing and page display. The database can be connected to third-party platforms through API interfaces.

10. A wireless intelligent data acquisition system according to claim 1, characterized in that: The communication module is equipped with a WiFi module, a Bluetooth module, and a 5G module.

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