Wireless radio frequency data monitoring and distributing platform system and method based on data analysis

Abstract

The invention discloses a wireless radio frequency data monitoring and distribution platform system and method based on data analysis, and belongs to the technical field of wireless communication. Wireless radio frequency signal parameters are acquired, data processing is performed on the signal parameters, a signal evaluation model is constructed, and the signal parameters are imported into the signal evaluation model to evaluate the signal-to-noise ratio. Constructing a channel occupation and multipath time delay extension evaluation model, importing the channel occupation time and the power and time delay of the multipath channel into the channel occupation and multipath time delay extension evaluation model to evaluate the signal condition, and constructing an equipment interference model; the method comprises the following steps: importing signal parameters and position distances of field working equipment into an equipment interference model to evaluate the interference degree of the working equipment on a wireless radio frequency transmission signal, constructing an optimal frequency band scoring model, and importing a signal-to-noise ratio, a channel occupancy rate, multipath time delay extension and equipment interference conditions into the optimal frequency band scoring model to perform frequency band selection. And the reliability and the real-time performance of wireless communication in an industrial scene are improved.

Description

Technical Field

[0001] The present application belongs to the field of wireless communication technology, and specifically, is a wireless radio frequency data monitoring and distribution platform system and method based on data analysis. Background Art

[0002] With the continuous development of industrial automation and intelligent manufacturing, wireless radio frequency communication is widely used for short-distance data transmission between various terminal devices due to its flexible deployment and low cost. There are a large number of potential wireless interference sources in the industrial environment, such as motors, welding machines, inverters and other industrial equipment, which will generate complex electromagnetic interference signals in different frequency bands, affecting the reliable reception of radio frequency signals. At the same time, multiple communication systems share frequency bands, densely accessed devices, and dynamic changes in channel conditions make the communication channel have significant uncertainty in both space and time.

[0003] In the prior art, radio frequency communication systems mostly use fixed frequencies or preset frequency sets for data transmission, lacking the ability to perceive the communication environment in real time and dynamically optimize spectrum resources, resulting in reduced communication quality, increased bit error rate, and even data transmission interruption. They fail to make intelligent judgments based on the spectrum status and channel characteristics in the current environment, making it difficult to ensure the robustness and stability of communications in complex environments. Therefore, this application proposes a wireless radio frequency data monitoring and distribution platform system and method based on data analysis, combining multiple indicators such as signal power, signal-to-noise ratio, channel occupancy, multipath delay spread, and on-site interference equipment parameters to dynamically evaluate frequency band quality and select the best frequency band for transmission, thereby improving the reliability, real-time nature, and stability of wireless communications in industrial scenarios. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present application proposes a wireless radio frequency data monitoring and distribution platform system and method based on data analysis.

[0005] To achieve the above objectives, this application provides the following technical solutions: A wireless radio frequency data monitoring and distribution platform method based on data analysis includes the following specific steps: Obtaining wireless radio frequency signal parameters and performing data processing on the signal parameters; Construct a signal evaluation model, and import signal parameters into the signal evaluation model to evaluate the signal-to-noise ratio; Construct a channel occupancy and multipath delay spread evaluation model, and import the channel occupancy time, the power and delay of the multipath channel into the channel occupancy and multipath delay spread evaluation model to evaluate the signal situation; Construct a device interference model, import the signal parameters and location distance of the on-site working equipment into the device interference model to evaluate the degree of interference of the working equipment on the wireless RF transmission signal; Construct an optimal frequency band scoring model, and import the signal-to-noise ratio, channel occupancy, multipath delay spread and equipment interference into the optimal frequency band scoring model for frequency band selection.

[0006] Preferably, the obtaining of wireless radio frequency signal parameters and performing data processing on the signal parameters comprises the following specific steps: S11, receiving a signal through a wireless RF receiver, and sampling the signal through an analog-to-digital converter at the wireless RF front end to obtain signal parameters, frequency band parameters and on-site interference equipment parameters; S12, filtering the collected spectrum data to remove transient noise and abnormal data, obtaining a discrete signal sequence from the received continuous-time radio frequency signal, and converting the time domain signal into a power spectrum density through fast Fourier transform.

[0007] Preferably, constructing a signal evaluation model and importing signal parameters into the signal evaluation model to evaluate the signal-to-noise ratio comprises the following specific steps: S21. Generate a candidate frequency band set from the candidate frequency bands, where the candidate frequency band set is: ,in, is the i-th frequency band, with a total of frequency bands, substitute the signal parameters of the ith frequency band into the calculation formula of the signal power to calculate the signal power in the ith frequency band, where the calculation formula of the signal power in the ith frequency band is: ,in, is the power spectrum density, B is the signal frequency band bandwidth, is the spectral resolution, , f' is the sampling rate, N is the number of fast Fourier transform points, and the noise power spectrum width and signal bandwidth are substituted into the noise power calculation formula to calculate the noise power. The noise power calculation formula in the i-th frequency band is: ,in, is the noise power spectrum width, B is the signal bandwidth; S22. Substituting the signal power and the noise power into the signal-to-noise ratio calculation formula in the i-th frequency band to calculate the signal-to-noise ratio, wherein the signal-to-noise ratio calculation formula is: ,in, is the signal power, is the noise power.

[0008] Preferably, the constructing of the channel occupancy and multipath delay spread evaluation model, importing the channel occupancy time, the power and delay of the multipath channel into the channel occupancy and multipath delay spread evaluation model to evaluate the signal condition comprises the following specific steps: S31. Substituting the channel occupancy time into the channel occupancy rate calculation formula in the i-th frequency band to evaluate the channel occupancy situation, wherein the channel occupancy rate calculation formula is: , is the occupied time of the ith frequency band in the total monitoring period, is the total monitoring time of the ith frequency band, where when the received power is greater than the received power threshold, the channel is determined to be occupied; S32. Substituting the power and delay of the multipath channel into the multipath delay spread calculation formula in the i-th frequency band to evaluate the delay dispersion of the multipath channel, wherein the multipath delay spread calculation formula is: ,in, is the delay of the kth multipath component, is the power of the kth path, is the average delay, n is the number of index paths of all valid multipath components detected, where the calculation formula of the average delay is: ,Multipath delay spread reflects the delay dispersion of the multipath channel.

[0009] Preferably, the construction of the equipment interference model, importing the signal parameters and location distance of the on-site working equipment into the equipment interference model to evaluate the interference degree of the working equipment to the wireless radio frequency transmission signal includes the following specific steps: S41. Obtain the signal parameters of the factory on-site working equipment, and convert the time domain signal into power spectrum density through fast Fourier transform, and substitute the power spectrum density of the wireless spectrum transmission signal and the power spectrum density of the interference device into the spectrum similarity calculation formula to calculate the spectrum similarity, wherein the spectrum similarity calculation formula is: ,in, is the center frequency of the interfering device, is the power spectral density of the interference device; S42. The location distance of the factory site working equipment will affect the transmission of wireless RF signals. The distance between the signal receiver and the interference device is substituted into the logarithmic distance path loss calculation formula to evaluate the impact of the interference device location. The logarithmic distance path loss calculation formula is: ,in, is the path loss between the signal receiver and the interference device at distance d, The reference distance The path loss at , obtained through actual measurement, is the path loss exponent, is the environmental disturbance term. The interference power decays with distance. Substitute the logarithmic distance path loss into the interference power calculation formula to calculate the interference power. The interference power calculation formula is: , is the transmission power of the interference source.

[0010] Preferably, the constructing of the optimal frequency band scoring model, importing the signal-to-noise ratio, channel occupancy, multipath delay spread and device interference into the optimal frequency band scoring model for frequency band selection comprises the following specific steps: S51. Substitute the signal-to-noise ratio, channel occupancy, multipath delay spread and device interference coefficient in the ith frequency band into a scoring formula to score the ith frequency band, wherein the scoring formula is: , in, is the maximum signal-to-noise ratio among all candidate frequency bands, is the signal-to-noise ratio weight, reflecting the importance of the signal-to-noise ratio in the scoring. is the frequency band idle rate. The larger the value, the less competition there is. is the channel occupancy weight, is the delay tolerance threshold. When the delay exceeds the threshold, the exponential decay decreases rapidly. is the multipath delay spread weight, is the device impact weight, is the reference power, is the distance weight; S52. If the spectrum similarity between the target frequency band and the interference device exceeds the threshold, it is marked as a highly similar frequency band. There is a significant overlap between the two in the frequency domain. The highly similar frequency band is added to the temporary blacklist and the scores are sorted. The highest score is the best frequency band. Switch to the best frequency band for transmission. Set an update cycle. Collect data of the current frequency band in real time during each cycle, calculate the indicators corresponding to all candidate frequency bands, execute the frequency band evaluation process, compare with the previously calculated scores, and determine whether the current frequency band is still suitable for transmission. If it is detected that the signal-to-noise ratio and score of the current frequency band are lower than the set threshold, the spectrum re-collection is triggered immediately, and it is dynamically switched to a frequency band with a higher score. Handshake confirmation is performed before switching to prevent interruption. After switching, the connection is re-established and data transmission continues.

[0011] A wireless radio frequency data monitoring and distribution platform system based on data analysis is implemented based on the wireless radio frequency data monitoring and distribution platform method based on data analysis described above, and specifically includes: The data acquisition and processing module is used to acquire the wireless radio frequency signal parameters and perform data processing on the signal parameters; A signal evaluation module, used for evaluating the signal-to-noise ratio during signal transmission by using signal parameters; Channel occupancy and multipath delay spread assessment module, used to assess signal conditions through channel occupancy time, power and delay of multipath channels; The device interference assessment module is used to assess the interference degree of the working equipment to the wireless radio frequency transmission signal through the signal parameters and location distance of the on-site working equipment; The optimal frequency band evaluation module is used to select the optimal frequency band by scoring the signal-to-noise ratio, channel occupancy, multipath delay spread and device interference.

[0012] An electronic device comprises: a processor and a memory, wherein the memory stores a computer program that can be called by the processor; The processor executes the above-mentioned wireless radio frequency data monitoring and distribution platform method based on data analysis by calling the computer program stored in the memory.

[0013] A computer-readable storage medium, characterized in that it stores instructions, which, when executed on a computer, enable the computer to execute the above-mentioned wireless radio frequency data monitoring and distribution platform method based on data analysis.

[0014] Compared with the prior art, the beneficial effects of this application are: The present application obtains wireless RF signal parameters, performs data processing on the signal parameters, constructs a signal evaluation model, imports the signal parameters into the signal evaluation model to evaluate the signal-to-noise ratio, constructs a channel occupancy and multipath delay spread evaluation model, imports the channel occupancy time, the power and delay of the multipath channel into the channel occupancy and multipath delay spread evaluation model to evaluate the signal condition, constructs an equipment interference model, imports the signal parameters and location distance of the on-site working equipment into the equipment interference model to evaluate the degree of interference of the working equipment to the wireless RF transmission signal, constructs an optimal frequency band scoring model, imports the signal-to-noise ratio, channel occupancy, multipath delay spread and equipment interference condition into the optimal frequency band scoring model for frequency band selection. The present application combines signal power, signal-to-noise ratio, channel occupancy and multipath delay spread parameters, as well as multiple indicators of factory site equipment interference, dynamically evaluates frequency band quality and selects the optimal frequency band for transmission, thereby improving the reliability and real-time performance of wireless communications in industrial scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 This is a schematic diagram of the overall process of a wireless radio frequency data monitoring and distribution platform method based on data analysis in this application; Figure 2 Flowchart of scoring calculation for this application; Figure 3 This is a schematic diagram of the overall framework of a wireless radio frequency data monitoring and distribution platform system based on data analysis in this application. DETAILED DESCRIPTION

[0016] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments.

[0017] Example 1 See also Figure 1-2 , an embodiment provided by the present application: a wireless radio frequency data monitoring and distribution platform method based on data analysis, which includes the following specific steps: Obtaining wireless radio frequency signal parameters and performing data processing on the signal parameters; Construct a signal evaluation model, and import signal parameters into the signal evaluation model to evaluate the signal-to-noise ratio; Construct a channel occupancy and multipath delay spread evaluation model, and import the channel occupancy time, the power and delay of the multipath channel into the channel occupancy and multipath delay spread evaluation model to evaluate the signal situation; Construct a device interference model, import the signal parameters and location distance of the on-site working equipment into the device interference model to evaluate the degree of interference of the working equipment on the wireless RF transmission signal; Construct an optimal frequency band scoring model, and import the signal-to-noise ratio, channel occupancy, multipath delay spread and equipment interference into the optimal frequency band scoring model for frequency band selection.

[0018] It should be specifically explained in this embodiment that obtaining the wireless radio frequency signal parameters and performing data processing on the signal parameters include the following specific steps: S11, receiving a signal through a wireless RF receiver, and sampling the signal through an analog-to-digital converter at the wireless RF front end to obtain signal parameters, frequency band parameters and on-site interference equipment parameters; S12, filtering the collected spectrum data to remove transient noise and abnormal data, obtaining a discrete signal sequence by receiving a continuous-time radio frequency signal, and converting the time domain signal into a power spectrum density by fast Fourier transform; S121. When receiving the wireless radio frequency, the continuous time signal is sampled and converted into a discrete sequence, wherein the discrete sequence is: , where f' is the sampling rate and N is the number of fast Fourier transform points; S122, the discrete sequence is introduced into the fast Fourier transform formula to perform Fourier transform to generate a frequency domain complex spectrum, wherein the fast Fourier transform formula is: ,in, is the Fourier kernel; S123, substituting the frequency domain complex spectrum into the power spectrum density calculation formula to calculate the power spectrum density, wherein the power spectrum density calculation formula is: .

[0019] It should be specifically explained in this embodiment that constructing a signal evaluation model and importing signal parameters into the signal evaluation model to evaluate the signal-to-noise ratio includes the following specific steps: S21. Generate a candidate frequency band set from the candidate frequency bands, where the candidate frequency band set is: ,in, is the i-th frequency band, with a total of frequency bands, substitute the signal parameters of the ith frequency band into the calculation formula of the signal power to calculate the signal power in the ith frequency band, where the calculation formula of the signal power in the ith frequency band is: ,in, is the power spectrum density, B is the signal frequency band bandwidth, is the spectral resolution, , f' is the sampling rate, N is the number of fast Fourier transform points, and the noise power spectrum width and signal bandwidth are substituted into the noise power calculation formula to calculate the noise power. The noise power calculation formula in the i-th frequency band is: ,in, is the noise power spectrum width, B is the signal bandwidth, and the signal power is used to measure the energy intensity of the wireless signal in the frequency band; S22. Substituting the signal power and the noise power into the signal-to-noise ratio calculation formula in the i-th frequency band to calculate the signal-to-noise ratio, wherein the signal-to-noise ratio calculation formula is: ,in, is the signal power, The signal-to-noise ratio is the ratio of signal power to noise power and is used to evaluate channel quality. The larger the value, the more prominent the signal is in the noise and the lower the data bit error rate.

[0020] It should be specifically explained in this embodiment that constructing a channel occupancy and multipath delay spread evaluation model, and importing the channel occupancy time, the power and delay of the multipath channel into the channel occupancy and multipath delay spread evaluation model to evaluate the signal situation includes the following specific steps: S31. Substituting the channel occupancy time into the channel occupancy rate calculation formula in the i-th frequency band to evaluate the channel occupancy situation, wherein the channel occupancy rate calculation formula is: , is the occupied time of the ith frequency band in the total monitoring period, is the total monitoring time of the i-th frequency band, where when the received power is greater than the received power threshold, the channel is determined to be occupied. In a factory environment, competition will occur in the same frequency band, and the frequency band is occupied when the received power is higher than the threshold; S32. Substituting the power and delay of the multipath channel into the multipath delay spread calculation formula in the i-th frequency band to evaluate the delay dispersion of the multipath channel, wherein the multipath delay spread calculation formula is: ,in, is the delay of the kth multipath component, is the power of the kth path, is the average delay, n is the number of index paths of all valid multipath components detected, where the calculation formula of the average delay is: ,Multipath delay spread reflects the delay dispersion of the multipath channel. ,In the factory, wireless signals are prone to generate multiple reflection paths, ,which lead to different signal arrival times and increased ,interference between data symbols. The weighted variance is used to ,evaluate the degree of signal time spread and identify ,frequencies that are not suitable for use due to multipath.

[0021] In this embodiment, it should be specifically explained that constructing a device interference model, importing the signal parameters and location distance of the on-site working equipment into the device interference model to evaluate the interference degree of the working equipment to the wireless radio frequency transmission signal includes the following specific steps: S41. Obtain the signal parameters of the factory on-site working equipment, and convert the time domain signal into power spectrum density through fast Fourier transform, and substitute the power spectrum density of the wireless spectrum transmission signal and the power spectrum density of the interference device into the spectrum similarity calculation formula to calculate the spectrum similarity, wherein the spectrum similarity calculation formula is: ,in, is the center frequency of the interfering device, The power spectrum density of the interference device. Through the spectrum similarity, it can be judged whether the signal shape of the current frequency band is similar to the known interference signal, so as to avoid selecting the frequency of similar interference; S42. The location distance of the factory site working equipment will affect the transmission of wireless RF signals. The distance between the signal receiver and the interference device is substituted into the logarithmic distance path loss calculation formula to evaluate the impact of the interference device location. The logarithmic distance path loss calculation formula is: ,in, is the path loss between the signal receiver and the interference device at distance d, The reference distance The path loss at , obtained through actual measurement, is the path loss exponent, is the environmental disturbance term. The interference power decays with distance. Substitute the logarithmic distance path loss into the interference power calculation formula to calculate the interference power. The interference power calculation formula is: , The transmission power of the interference source. The power of the wireless signal does not decay linearly during the propagation process, but decreases in a logarithmic series. The path loss scores corresponding to different frequencies are quickly calculated and compared in the channel selection algorithm. The comprehensive calculation of the path loss at the reference distance, the signal propagation distance, the path loss index and the environmental disturbance term reflects the energy attenuation of the signal caused by obstacles, reflections and obstructions in actual industrial scenarios.

[0022] It should be specifically explained in this embodiment that constructing the best frequency band scoring model and importing the signal-to-noise ratio, channel occupancy, multipath delay spread and device interference into the best frequency band scoring model for frequency band selection includes the following specific steps: S51. Substitute the signal-to-noise ratio, channel occupancy, multipath delay spread and device interference coefficient in the ith frequency band into a scoring formula to score the ith frequency band, wherein the scoring formula is: , in, is the maximum signal-to-noise ratio among all candidate frequency bands, is the signal-to-noise ratio weight, reflecting the importance of the signal-to-noise ratio in the scoring. is the frequency band idle rate. The larger the value, the less competition there is. is the channel occupancy weight, is the delay tolerance threshold. When the delay exceeds the threshold, the exponential decay decreases rapidly. is the multipath delay spread weight, is the device impact weight, is the reference power, is the distance weight; S52. If the spectrum similarity between the target frequency band and the interference device exceeds the threshold, it is marked as a highly similar frequency band. There is a significant overlap between the two in the frequency domain. The highly similar frequency band is added to the temporary blacklist and the scores are sorted. The highest score is the best frequency band. Switch to the best frequency band for transmission. Set an update cycle. Collect data of the current frequency band in real time during each cycle, calculate the indicators corresponding to all candidate frequency bands, execute the frequency band evaluation process, compare with the previously calculated scores, and determine whether the current frequency band is still suitable for transmission. If it is detected that the signal-to-noise ratio and score of the current frequency band are lower than the set threshold, the spectrum re-collection is triggered immediately, and it is dynamically switched to a frequency band with a higher score. Handshake confirmation is performed before switching to prevent interruption. After switching, the connection is re-established and data transmission continues.

[0023] It should be noted that the values ​​of various setting parameters in this embodiment are obtained by obtaining signal data from representative wireless radio frequency transmission data, obtaining historical transmission effects, hiring experts to manually evaluate the transmission effects, and substituting the obtained historical data into the calculation results and judgment results of each step in this embodiment into the fitting software, and outputting the values ​​of various setting parameters that meet the highest judgment accuracy; The advantages of this embodiment over the prior art are: The present application obtains wireless RF signal parameters, performs data processing on the signal parameters, constructs a signal evaluation model, imports the signal parameters into the signal evaluation model to evaluate the signal-to-noise ratio, constructs a channel occupancy and multipath delay spread evaluation model, imports the channel occupancy time, the power and delay of the multipath channel into the channel occupancy and multipath delay spread evaluation model to evaluate the signal condition, constructs an equipment interference model, imports the signal parameters and location distance of the on-site working equipment into the equipment interference model to evaluate the degree of interference of the working equipment to the wireless RF transmission signal, constructs an optimal frequency band scoring model, imports the signal-to-noise ratio, channel occupancy, multipath delay spread and equipment interference condition into the optimal frequency band scoring model for frequency band selection. The present application combines signal power, signal-to-noise ratio, channel occupancy and multipath delay spread parameters, as well as multiple indicators of factory site equipment interference, dynamically evaluates frequency band quality and selects the optimal frequency band for transmission, thereby improving the reliability and real-time performance of wireless communications in industrial scenarios.

[0024] Example 2 like Figure 3 As shown, a wireless RF data monitoring and distribution platform system based on data analysis is implemented based on the above-mentioned wireless RF data monitoring and distribution platform method based on data analysis, and specifically includes a data acquisition and processing module, a signal evaluation module, a channel occupancy and multipath delay spread evaluation module, an equipment interference evaluation module and an optimal frequency band evaluation module. The data acquisition and processing module is used to obtain wireless RF signal parameters and perform data processing on the signal parameters; the signal evaluation module is used to evaluate the signal-to-noise ratio during signal transmission through signal parameters; the channel occupancy and multipath delay spread evaluation module is used to evaluate the signal condition through channel occupancy time, multipath channel power and delay; the equipment interference evaluation module is used to evaluate the degree of interference of working equipment on wireless RF transmission signals through signal parameters and location distance of on-site working equipment; the optimal frequency band evaluation module is used to score through signal-to-noise ratio, channel occupancy, multipath delay spread and equipment interference condition to select the optimal frequency band.

[0025] Example 3 This embodiment provides an electronic device, including: a processor and a memory, wherein the memory stores a computer program that can be called by the processor; The processor executes the above-mentioned wireless radio frequency data monitoring and distribution platform method based on data analysis by calling the computer program stored in the memory.

[0026] The electronic device may have relatively large differences due to different configurations or performances, and may include one or more processors (Central Processing Units, CPU) and one or more memories, wherein the memory stores at least one computer program, and the computer program is loaded and executed by the processor to implement a wireless radio frequency data monitoring and distribution platform method based on data analysis provided by the above method embodiment. The electronic device may also include other components for realizing the functions of the device, for example, the electronic device may also have components such as a wired or wireless network interface and an input and output interface to input and output data. This embodiment will not be described in detail here.

[0027] Example 4 This embodiment provides a computer-readable storage medium having a rewritable computer program stored thereon; When the computer program runs on a computer device, the computer device executes the above-mentioned wireless radio frequency data monitoring and distribution platform method based on data analysis.

[0028] For example, the computer readable storage medium can be a read-only memory (ROM), a random access memory (RAM), a compact disc (CD-ROM), a magnetic tape, a floppy disk, and an optical data storage device, etc.

[0029] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When a computer instruction or computer program is loaded or executed on a computer, a process or function according to an embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network or other programmable device. Computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center through a wired network or / and a wireless network. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

Claims

1. A wireless radio frequency data monitoring and distribution platform method based on data analysis, characterized in that: It includes the following specific steps: Obtaining wireless radio frequency signal parameters and performing data processing on the signal parameters; Construct a signal evaluation model, and import signal parameters into the signal evaluation model to evaluate the signal-to-noise ratio; Construct a channel occupancy and multipath delay spread evaluation model, and import the channel occupancy time, the power and delay of the multipath channel into the channel occupancy and multipath delay spread evaluation model to evaluate the signal situation; Construct a device interference model, import the signal parameters and location distance of the on-site working equipment into the device interference model to evaluate the degree of interference of the working equipment on the wireless RF transmission signal; Construct an optimal frequency band scoring model, and import the signal-to-noise ratio, channel occupancy, multipath delay spread and equipment interference into the optimal frequency band scoring model for frequency band selection.

2. A wireless radio frequency data monitoring and distribution platform method based on data analysis as claimed in claim 1, characterized in that: The obtaining of wireless radio frequency signal parameters and data processing of the signal parameters comprises the following specific steps: S11, receiving a signal through a wireless RF receiver, and sampling the signal through an analog-to-digital converter at the wireless RF front end to obtain signal parameters, frequency band parameters and on-site interference equipment parameters; S12, filtering the collected spectrum data to remove transient noise and abnormal data, obtaining a discrete signal sequence from the received continuous-time radio frequency signal, and converting the time domain signal into a power spectrum density through fast Fourier transform.

3. A method for wireless radio frequency data monitoring and distribution platform based on data analysis as claimed in claim 2, characterized in that: The construction of the signal evaluation model and the importation of the signal parameters into the signal evaluation model to evaluate the signal-to-noise ratio include the following specific steps: S21. Generate a candidate frequency band set from the candidate frequency bands, where the candidate frequency band set is: ,in, is the i-th frequency band, with a total frequency bands, substitute the signal parameters of the ith frequency band into the calculation formula of the signal power to calculate the signal power in the ith frequency band, where the calculation formula of the signal power in the ith frequency band is: ,in, is the power spectrum density, B is the signal frequency band bandwidth, is the spectral resolution, , f' is the sampling rate, N is the number of fast Fourier transform points, and the noise power spectrum width and signal bandwidth are substituted into the noise power calculation formula to calculate the noise power. The noise power calculation formula in the i-th frequency band is: ,in, is the noise power spectrum width, B is the signal bandwidth; S22. Substituting the signal power and the noise power into the signal-to-noise ratio calculation formula in the i-th frequency band to calculate the signal-to-noise ratio, wherein the signal-to-noise ratio calculation formula is: ,in, is the signal power, is the noise power.

4. A method for wireless radio frequency data monitoring and distribution platform based on data analysis as claimed in claim 3, characterized in that: The construction of the channel occupancy and multipath delay spread evaluation model, importing the channel occupancy time, the power and delay of the multipath channel into the channel occupancy and multipath delay spread evaluation model to evaluate the signal situation comprises the following specific steps: S31. Substituting the channel occupancy time into the channel occupancy rate calculation formula in the i-th frequency band to evaluate the channel occupancy situation, wherein the channel occupancy rate calculation formula is: , is the occupied time of the ith frequency band in the total monitoring period, is the total monitoring time of the ith frequency band, where when the received power is greater than the received power threshold, the channel is determined to be occupied; S32. Substituting the power and delay of the multipath channel into the multipath delay spread calculation formula in the i-th frequency band to evaluate the delay dispersion of the multipath channel, wherein the multipath delay spread calculation formula is: ,in, is the delay of the kth multipath component, is the power of the kth path, is the average delay, n is the number of index paths of all valid multipath components detected, where the calculation formula of the average delay is: .

5. A method for wireless radio frequency data monitoring and distribution platform based on data analysis as claimed in claim 4, characterized in that: The construction of the equipment interference model and the importation of the signal parameters and location distance of the on-site working equipment into the equipment interference model to evaluate the interference degree of the working equipment to the wireless radio frequency transmission signal include the following specific steps: S41. Obtain the signal parameters of the factory on-site working equipment, and convert the time domain signal into power spectrum density through fast Fourier transform, and substitute the power spectrum density of the wireless spectrum transmission signal and the power spectrum density of the interference device into the spectrum similarity calculation formula to calculate the spectrum similarity, wherein the spectrum similarity calculation formula is: ,in, is the center frequency of the interfering device, is the power spectral density of the interference device; S42. Substitute the distance between the signal receiver and the interference device into the logarithmic distance path loss calculation formula to evaluate the impact of the interference device location, where the logarithmic distance path loss calculation formula is: ,in, is the path loss between the signal receiver and the interference device at distance d, The reference distance The path loss at is the path loss exponent, is the environmental disturbance term, and the logarithmic distance path loss is substituted into the interference power calculation formula to calculate the interference power. The interference power calculation formula is: , is the transmission power of the interference source.

6. A method for wireless radio frequency data monitoring and distribution platform based on data analysis as claimed in claim 5, characterized in that: The construction of the optimal frequency band scoring model and importing the signal-to-noise ratio, channel occupancy, multipath delay spread and device interference into the optimal frequency band scoring model for frequency band selection includes the following specific steps: S51. Substitute the signal-to-noise ratio, channel occupancy, multipath delay spread and device interference coefficient in the ith frequency band into a scoring formula to score the ith frequency band, wherein the scoring formula is: , in, is the maximum signal-to-noise ratio among all candidate frequency bands, is the signal-to-noise ratio weight, is the frequency band idle rate, is the channel occupancy weight, is the delay tolerance threshold, is the multipath delay spread weight, is the device impact weight, is the reference power, is the distance weight; S52. If the spectrum similarity between the target frequency band and the interference device exceeds the threshold, it is marked as a highly similar frequency band, added to a temporary blacklist, and sorted. The frequency band with the highest score is the best frequency band. The transmission is switched to the best frequency band, and an update cycle is set. The data of the current frequency band is collected in real time during each cycle, and the indicators corresponding to all candidate frequency bands are calculated. The frequency band evaluation process is executed, and the scores are compared with the previously calculated scores to determine whether the current frequency band is still suitable for transmission. If the signal-to-noise ratio and score of the current frequency band are detected to be lower than the set threshold, the spectrum re-collection is triggered immediately, and the frequency band with a higher score is dynamically switched.

7. A wireless radio frequency data monitoring and distribution platform system based on data analysis, which is implemented based on the wireless radio frequency data monitoring and distribution platform method based on data analysis as claimed in any one of claims 1 to 6, characterized in that: Specifically include: The data acquisition and processing module is used to acquire the wireless radio frequency signal parameters and perform data processing on the signal parameters; A signal evaluation module, used for evaluating the signal-to-noise ratio during signal transmission by using signal parameters; Channel occupancy and multipath delay spread assessment module, used to assess signal conditions through channel occupancy time, power and delay of multipath channels; The device interference assessment module is used to assess the interference degree of the working equipment to the wireless radio frequency transmission signal through the signal parameters and location distance of the on-site working equipment; The optimal frequency band evaluation module is used to select the optimal frequency band by scoring the signal-to-noise ratio, channel occupancy, multipath delay spread and device interference.

8. An electronic device comprising: A processor and a memory, wherein the memory stores a computer program that can be called by the processor; It is characterized in that the processor executes the wireless radio frequency data monitoring and distribution platform method based on data analysis as described in any one of claims 1 to 6 by calling the computer program stored in the memory.

9. A computer-readable storage medium, characterized in that: Instructions are stored, and when the instructions are executed on a computer, the computer executes a wireless radio frequency data monitoring and distribution platform method based on data analysis as described in any one of claims 1-6.

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