Signal conversion method and device and terminal equipment

Abstract

The invention provides a signal conversion method and device and terminal equipment, and is suitable for the technical field of communication, and the method comprises the steps: generating a plurality of pieces of networking interaction signal time sequence information according to a plurality of pieces of networking interaction signal information; based on a preset networking interaction signal time sequence cutting model, according to the number information of the plurality of networking interaction signal time sequence cutting points, cutting the plurality of pieces of networking interaction signal time sequence information to obtain a plurality of pieces of networking interaction signal sub-time sequence information; and generating a plurality of pieces of signal conversion information according to the plurality of pieces of networking interaction signal sub-time sequence information based on a preset signal conversion model. The method and the device are used for guaranteeing the transmission flexibility and stability of the interaction signal of each node in the remote networking so as to realize cross-equipment and cross-network-segment efficient signal interaction, and the communication cooperation efficiency and the data transmission adaptability of the remote networking are greatly improved, so that the controllability and the fault tolerance of the remote networking signal transmission are enhanced.

Description

Technical Field

[0001] This application belongs to the field of communication technology, and in particular relates to signal conversion methods, devices and terminal equipment. Background Technology

[0002] In the field of remote networking communication, with the continuous growth of demand for distributed device collaboration and cross-regional data interaction, timing management and format conversion technology of networking interaction signals have become the core link to improve communication stability and adaptability.

[0003] In existing technologies, a multi-channel optical transceiver array and anti-jitter circuit are integrated through a hardware optical I / O synchronization module. Stable synchronization pulses are generated using phase-locked loop technology. A dedicated clock distribution network is used to achieve microsecond-level alignment between the local timing unit of each node and the global reference clock. The communication cycle is divided into a fixed time window and a flexible buffer window. The fixed window prioritizes the deterministic transmission of control signaling, while the flexible window uses a dynamic bandwidth allocation algorithm to adapt to burst traffic. At the same time, the priority preemption mechanism of the SRIO bus is supported to ensure the transmission priority of high-priority signals. Zero-copy technology is used to reduce protocol stack processing latency. Combined with dynamic multicast routing, secure isolation signal transmission links are constructed to meet the real-time communication requirements of multi-node networking.

[0004] However, existing technologies are insufficient in signal conversion compatibility and timing control when facing network interaction signals of multiple types and protocols. They are prone to packet loss and delay problems in the transmission of large segments of timing signals, and do not have the ability to customize signal conversion for different receiving ends. Summary of the Invention

[0005] In view of this, embodiments of this application provide a signal conversion method, apparatus, and terminal device, aiming to solve the problems in the prior art that make it difficult to adapt to the differences in signal processing capabilities of different node devices, insufficient compatibility of conversion of multi-protocol and multi-type network interaction signals, and the easy occurrence of delay and packet loss in the transmission of long-segment time-series signals.

[0006] A first aspect of this application provides a signal conversion method, including: Acquire information on multiple network interaction signals and the number of timing cut-off points for multiple network interaction signals; Based on the multiple network interaction signal information, multiple network interaction signal timing information is generated; Based on the preset network interaction signal timing segmentation model, the timing information of the multiple network interaction signals is segmented according to the number of timing segmentation points of the multiple network interaction signals to obtain multiple network interaction signal sub-timing information. Based on a preset signal conversion model, multiple signal conversion information is generated according to the timing information of the multiple network interaction signals.

[0007] A second aspect of this application provides a signal conversion apparatus, comprising: The information acquisition module is used to acquire information on multiple network interaction signals and the number of timing cut points for multiple network interaction signals. The network interaction signal timing information generation module is used to generate multiple network interaction signal timing information based on the multiple network interaction signal information. The sub-timing information generation module for network interaction signals is used to segment the timing information of multiple network interaction signals based on a preset timing segmentation model and according to the number of timing segmentation points of the multiple network interaction signals, to obtain multiple sub-timing information of network interaction signals. The signal conversion information generation module is used to generate multiple signal conversion information based on a preset signal conversion model and the timing information of the multiple network interaction signals.

[0008] A third aspect of this application provides a terminal device, the terminal device including a memory and a processor, the memory storing a computer program executable on the processor, and the processor executing the computer program to implement the steps of the signal conversion method described in the first aspect above.

[0009] A fourth aspect of this application provides a computer-readable storage medium, comprising: storing a computer program, wherein when executed by a processor, the computer program implements the steps of the signal conversion method as described in the first aspect above.

[0010] Compared with the prior art, the beneficial effects of this application are: this application effectively adapts to the differences in signal processing capabilities of different node devices in remote networking, significantly reduces the delay and packet loss risk of large-segment time-series signal transmission, ensures the transmission flexibility and stability of interactive signals of each node in remote networking, so as to realize efficient signal interaction across devices and network segments, and greatly improve the communication coordination efficiency and data transmission adaptability of remote networking, thereby enhancing the controllability and fault tolerance of remote networking signal transmission. Attached Figure Description

[0011] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0012] Figure 1 This is a schematic diagram illustrating the implementation process of the signal conversion method provided in Embodiment 1 of this application; Figure 2This is a schematic diagram illustrating the implementation flow of the signal conversion method provided in Embodiment 2 of this application; Figure 3 This is a schematic diagram illustrating the implementation flow of the signal conversion method provided in Embodiment 3 of this application; Figure 4 This is a schematic diagram illustrating the implementation flow of the signal conversion method provided in Embodiment 4 of this application; Figure 5 This is a schematic diagram illustrating the implementation flow of the signal conversion method provided in Embodiment 5 of this application; Figure 6 This is a schematic diagram illustrating the implementation flow of the signal conversion method provided in Embodiment Six of this application; Figure 7 This is a schematic diagram illustrating the implementation process of the signal conversion method provided in Embodiment 7 of this application; Figure 8 This is a schematic diagram of the signal conversion device provided in the embodiments of this application; Figure 9 This is a schematic diagram of the terminal device provided in the embodiments of this application. Detailed Implementation

[0013] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0014] To illustrate the technical solution described in this application, specific embodiments are provided below.

[0015] Figure 1 A flowchart illustrating the implementation of the signal conversion method provided in Embodiment 1 of this application is shown, and is described in detail below: Step S101: Obtain information on multiple network interaction signals and the number of timing cut-off points for multiple network interaction signals.

[0016] In this embodiment, network interaction signal information refers to various raw signal data generated by each node device in the remote network system during communication interaction. This data can include multi-dimensional information such as signal transmission protocol type data, signal amplitude parameters, signal frequency characteristics, signal transmission direction identifiers, and the node device identifiers corresponding to the signals. This information can be acquired by signal acquisition modules deployed at each key node of the network. It is understood that the acquisition module can capture all real-time communication signals of each node at a specific acquisition frequency, and integrate the communication logs and signal transmission status data of each node device as complete network interaction signal information. The number of network interaction signal timing segmentation points refers to the specific number of segmentation points used to divide the timing segments, which is pre-set to achieve accurate segmentation of the network interaction signal timing. This information can be obtained by directly retrieving the baseline values ​​of the number of network interaction signal timing segmentation points set manually in the system configuration library. Alternatively, it can be manually set by technicians after comprehensively evaluating the signal processing capabilities, transmission bandwidth limitations, and task priorities of the receiving device through the network communication demand analysis module, and then input into the computer.

[0017] Step S102: Generate multiple network interaction signal timing information based on the multiple network interaction signal information.

[0018] In this embodiment, the process of converting multiple discrete network interaction signal information without temporal correlation into an ordered time sequence with temporal order and timestamps based on the chronological order of acquisition is described. The converted time sequence information of multiple network interaction signals is used to fully present the time dimension characteristics of each network interaction signal, such as the generation time, transmission time, interaction time between nodes, and signal duration. Simultaneously, it can also establish the temporal correlation between different network interaction signals. The multiple network interaction signal information can be preprocessed first, extracting the clock information of the device at the timestamp node for each network interaction signal and the delay data of the signal transmission link. Then, the discrete network interaction signals are sorted according to chronological order, and the actual interaction timing of the signals is corrected based on the communication link delay data between nodes. A unified global time reference mark is then added to each network interaction signal. Finally, all processed signal time dimension data are integrated to generate multiple network interaction signal time sequence information with complete temporal logic and correlation.

[0019] Step S103: Based on the preset network interaction signal timing segmentation model, the timing information of the multiple network interaction signals is segmented according to the number of timing segmentation points of the multiple network interaction signals to obtain multiple network interaction signal sub-timing information.

[0020] In this embodiment, the preset network interaction signal timing segmentation model can be manually set, a greedy algorithm model, a long short-term memory network model based on a recurrent neural network, a temporal convolutional network model, or an attention-enhanced gated recurrent unit model. The process involves first importing the number of timing segmentation points and timing information of multiple network interaction signals into the preset model. Based on the number of timing segmentation points, the model uniformly or as needed delineates corresponding segmentation nodes on the global timing axis. Then, based on the delineated segmentation nodes, the timing information of multiple network interaction signals is segmented. During this process, integrity checks and boundary corrections are performed on network interaction signals crossing segmentation nodes to prevent signal timing breaks or repetitions. Finally, time interval labels and node association indexes are added to each segmented sub-timing segment to obtain the sub-timing information of multiple network interaction signals.

[0021] Step S104: Based on the preset signal conversion model, generate multiple signal conversion information according to the multiple network interaction signal sub-timing information.

[0022] In this embodiment, the preset signal conversion model can be manually set, a deep learning-based multi-protocol adaptation model, a traditional protocol parsing and conversion model, a rule-based signal format mapping model, or a hybrid conversion model integrating multiple signal adaptation algorithms. Multiple network interaction signal sub-timing information can be first imported into the preset signal conversion model. Then, feature extraction is performed on each network interaction signal sub-timing information, extracting core information such as signal transmission protocol type data, signal amplitude parameters, and signal frequency characteristics. Subsequently, targeted protocol adaptation and format adjustment are performed based on the network interaction signal sub-timing information with different characteristics. During the process, the integrity and validity of the converted signal data can be verified to avoid protocol incompatibility or format errors. Finally, corresponding conversion identifiers and adaptation node information are added to each converted sub-timing signal, thereby generating multiple signal conversion information that meets the needs of each receiving device in the remote network.

[0023] The signal conversion method provided in this application effectively adapts to the differences in signal processing capabilities of different node devices in a remote network, significantly reduces the delay and packet loss risk of large-segment time-series signal transmission, ensures the transmission flexibility and stability of interactive signals between various nodes in a remote network, realizes efficient signal interaction across devices and network segments, and greatly improves the communication coordination efficiency and data transmission adaptability of a remote network, thereby enhancing the controllability and fault tolerance of remote network signal transmission.

[0024] Figure 2The flowchart illustrating the implementation of the signal conversion method provided in Embodiment 2 of this application is shown. The difference between this method and Embodiment 1 described above is that: The information on the number of timing cut-off points for the multiple network interaction signals includes the information on the number of timing cut-off points for the first network interaction signal and the information on the number of timing cut-off points for the second network interaction signal. Step S103 specifically includes: Step S201: Based on the preset network interaction signal timing segmentation model, according to the number of timing segmentation points of the first network interaction signal, the timing information of the multiple network interaction signals is segmented to obtain multiple first network interaction signal sub-timing information.

[0025] In this embodiment, the preset network interaction signal timing segmentation model can be manually set, a greedy algorithm model, a long short-term memory network model based on a recurrent neural network, a temporal convolutional network model, or an attention-enhanced gated recurrent unit model. First, the number of timing segmentation points for the first network interaction signal and the timing information of multiple network interaction signals can be imported into the preset network interaction signal timing segmentation model. Then, the preset network interaction signal timing segmentation model, based on the number of timing segmentation points for the first network interaction signal, uniformly or as needed delineates corresponding first segmentation nodes on the global timing axis according to a first segmentation strategy. Then, based on the delineated first segmentation nodes, the timing information of multiple network interaction signals is segmented. During this process, integrity checks and boundary corrections are performed on network interaction signals crossing first segmentation nodes to avoid signal timing breaks or repetitions. Finally, a unique first time interval label and first node association index are added to each segmented first sub-timing segment, thereby obtaining multiple first network interaction signal sub-timing information.

[0026] Step S202: Calculate the first network interaction signal sub-time sequence segmentation quality value based on the multiple first network interaction signal sub-time sequence information and the preset network interaction signal time sequence segmentation quality calculation weight.

[0027] In this embodiment, the preset weights for calculating the timing segmentation quality of the network interaction signal can be manually preset. First, core quality assessment parameters such as integrity parameters, independence parameters, and correlation parameters can be extracted from multiple first network interaction signal sub-timing information. Then, each core quality assessment parameter is weighted and calculated with its corresponding preset weights for calculating the timing segmentation quality of the network interaction signal. Finally, all weighted parameter values ​​are summarized, and the summarized values ​​are normalized to obtain a standardized quality value for the timing segmentation of the first network interaction signal sub-timing. This quality value directly reflects the overall effect of the segmentation process based on the number of timing segmentation points of the first network interaction signal.

[0028] Step S203: Based on the preset network interaction signal timing segmentation model, according to the number of timing segmentation points of the second network interaction signal, the timing information of the multiple network interaction signals is segmented to obtain multiple second network interaction signal sub-timing information.

[0029] In this embodiment, the preset network interaction signal timing segmentation model can be manually set. First, the number of timing segmentation points for the second network interaction signal and the timing information of multiple network interaction signals can be imported into the preset network interaction signal timing segmentation model. Then, the preset network interaction signal timing segmentation model, based on the number of timing segmentation points for the second network interaction signal, uniformly or as needed delineates corresponding second segmentation nodes on the global timing axis according to a second segmentation strategy. This second segmentation strategy may differ from the first segmentation strategy in terms of the distribution density of segmentation nodes. Then, based on the delineated second segmentation nodes, the timing information of multiple network interaction signals is segmented. During this process, integrity checks and boundary corrections are performed on network interaction signals crossing second segmentation nodes to avoid signal timing breaks or repetitions. Finally, a unique second time interval label and a second node association index are added to each segmented second sub-timing segment, thereby obtaining multiple second network interaction signal sub-timing information.

[0030] Step S204: Calculate the second network interaction signal sub-time sequence cutting quality value based on the multiple second network interaction signal sub-time sequence information and the preset network interaction signal time sequence cutting quality calculation weight.

[0031] In this embodiment, the preset weights for calculating the timing segmentation quality of the network interaction signal can be manually preset. First, core quality assessment parameters such as integrity parameters, independence parameters, and correlation parameters can be extracted from multiple second network interaction signal sub-timing information. Then, each core quality assessment parameter is weighted and calculated with its corresponding preset weights for calculating the timing segmentation quality of the network interaction signal. Finally, all weighted parameter values ​​are summarized, and the summarized values ​​are normalized to obtain a standardized second network interaction signal sub-timing segmentation quality value. This quality value directly reflects the overall effect of the segmentation process based on the number of timing segmentation points in the second network interaction signal.

[0032] Step S205: Based on the multiple first network interaction signal sub-timing information, multiple second network interaction signal sub-timing information, the first network interaction signal sub-timing segmentation quality value, the second network interaction signal sub-timing segmentation quality value, and a preset network interaction signal timing segmentation quality difference threshold, multiple network interaction signal sub-timing information are obtained.

[0033] In this embodiment, the preset threshold for the quality difference of timing segmentation of network interaction signals can be preset manually. First, the difference between the quality values ​​of the first and second network interaction signal sub-timing segments can be calculated. Then, this difference is compared with a preset threshold for the difference in network interaction signal timing segmentation quality. Based on the comparison result, the final segmentation result is determined. If the difference is less than or equal to the preset threshold, the corresponding sub-timing information with the higher quality value can be selected as multiple network interaction signal sub-timing information. If the two sets of quality values ​​are consistent, multiple first and second network interaction signal sub-timing information can be integrated to generate comprehensive sub-timing information. If the difference is greater than the preset threshold, the corresponding sub-timing information with the higher quality value is directly selected as multiple network interaction signal sub-timing information. Finally, the selected sub-timing information is subjected to final tag integration and index verification to obtain multiple network interaction signal sub-timing information that meets the requirements of high-precision segmentation for remote networking.

[0034] The signal conversion method provided in this application improves the accuracy and reliability of segmenting and processing the timing information of multiple network interaction signals, effectively avoids the problem of segmentation result deviation caused by a single segmentation parameter, enhances the quality controllability of the timing information of multiple network interaction signals, ensures the adaptability of the generation of subsequent multiple signal conversion information, thereby reducing the delay and packet loss risk of signal transmission in remote networking, improving the communication coordination efficiency and data transmission adaptability of remote networking, and enhancing the controllability and fault tolerance of remote networking signal transmission, providing more stable technical support for complex signal interaction in remote networking scenarios.

[0035] Figure 3 The flowchart illustrating the implementation of the signal conversion method provided in Embodiment 3 of this application is shown. The difference between this method and Embodiment 2 is that step S201 specifically includes: Step S301: Based on the number of timing cut points of the first network interaction signal, the timing information of multiple network interaction signals, and the preset timing cut model of the network interaction signal, generate the location information of multiple first network interaction signal sub-timing cut points.

[0036] In this embodiment, the preset network interaction signal timing segmentation model can be manually preset, a greedy algorithm model, a long short-term memory network model based on a recurrent neural network, a temporal convolutional network model, or an attention-enhanced gated recurrent unit model. First, the number of timing segmentation points for the first network interaction signal and the timing information of multiple network interaction signals can be imported into the preset network interaction signal timing segmentation model. Then, the preset network interaction signal timing segmentation model performs global timing feature extraction on the multiple network interaction signal timing information, obtaining key data such as signal timestamp distribution features, signal interaction interval features, and signal type switching features. Next, based on the number of timing segmentation points for the first network interaction signal, segmentation point distribution rules are set. Then, combined with the extracted key timing features, preliminary candidate segmentation point positions are marked on the global timing axis. Finally, the rationality of the candidate positions is verified, and abnormal candidate points that may cause signal timing breaks are eliminated, thereby generating multiple first network interaction signal sub-timing segmentation point position information with precise location identification.

[0037] Step S302: Based on the location information of the multiple first network interaction signal sub-timing cutting points, the multiple network interaction signal timing information is cut to obtain multiple first network interaction signal sub-timing information.

[0038] In this embodiment, the location information of multiple first network interaction signal sub-time sequence cutting points can be associated and mapped with multiple network interaction signal time sequence information to clarify the specific time node corresponding to each cutting point on the global time sequence axis. Then, according to the cutting point location information, the multiple network interaction signal time sequence information is divided into a corresponding number of time sequence intervals. The integrity of the network interaction signals in each time sequence interval is then verified, and the boundary correction and attribution confirmation are performed on the signals crossing cutting points. Subsequently, a unique first time interval label and first node association index are added to each divided time sequence interval. Then, all the divided time sequence interval data are integrated to obtain multiple first network interaction signal sub-time sequence information.

[0039] The signal conversion method provided in this application embodiment ensures the integrity and independence of the timing information of multiple first network interaction signal sub-sequences, enhances the controllability of the overall segmentation process, thereby optimizing the quality of the timing information of multiple network interaction signal sub-sequences, improving the refinement level of remote network signal timing processing, and enhancing the stability and adaptability of remote network signal transmission.

[0040] Figure 4 The flowchart illustrating the implementation of the signal conversion method provided in Embodiment 4 of this application is shown. The difference between this method and Embodiment 2 is that step S202 specifically includes: Step S401: Based on the multiple first network interaction signal sub-time sequence information, calculate the multiple first network interaction signal sub-time sequence length information, the multiple first network interaction signal sub-time sequence mean information, and the multiple first network interaction signal sub-time sequence variance information.

[0041] In this embodiment, the start and end timestamps of each first network interaction signal sub-timing information can be extracted firstly. The duration of each sub-timing is calculated using the timestamp difference, thereby generating multiple first network interaction signal sub-timing length information. Then, the values ​​of core data such as signal amplitude parameters and signal frequency characteristics within each first network interaction signal sub-timing information are statistically analyzed. The average level of the corresponding data for each sub-timing is obtained using the mean calculation method, thereby generating multiple first network interaction signal sub-timing mean information. Subsequently, the deviation between the core data and the corresponding mean within each first network interaction signal sub-timing information is calculated. The dispersion of each sub-timing data is obtained using the variance calculation method, thereby generating multiple first network interaction signal sub-timing variance information.

[0042] Step S402: Based on the mean information of the time series of the multiple first network interaction signals and the variance information of the time series of the multiple first network interaction signals, perform numerical normalization processing on the time series information of the multiple first network interaction signals and the length information of the multiple first network interaction signals to obtain normalized information of the time series of the multiple first network interaction signals and normalized information of the length of the multiple first network interaction signals.

[0043] In this embodiment, a normalized benchmark value can be first determined based on the mean information of multiple first group network interaction signal sub-time series. Then, the normalized fluctuation range can be determined by combining the variance information of multiple first group network interaction signal sub-time series. Next, the data of each dimension in the multiple first group network interaction signal sub-time series information is compared with the benchmark value. The normalized floating range is then transformed into a unified value by subtracting the mean information of multiple first group network interaction signal sub-time series information from the mean information of multiple first group network interaction signal sub-time series information and then dividing the subtraction result by the variance information of multiple first group network interaction signal sub-time series information. The standardized values ​​within a certain interval are used to generate multiple first-group network interaction signal sub-time sequence normalization information. Similarly, the numerical conversion of multiple first-group network interaction signal sub-time sequence length information can be performed by subtracting the mean of multiple first-group network interaction signal sub-time sequence length information from the numerical values ​​of multiple first-group network interaction signal sub-time sequence length information, and then dividing the result by the variance of multiple first-group network interaction signal sub-time sequence length information. This eliminates the difference in magnitude between different sub-time sequence lengths, thereby generating multiple first-group network interaction signal sub-time sequence length normalization information.

[0044] Step S403: Based on the preset network interaction signal timing segmentation quality calculation weights, the weighted summation of the mean information of the multiple first network interaction signal sub-timings, the variance information of the multiple first network interaction signal sub-timings, the normalized information of the multiple first network interaction signal sub-timings, and the normalized information of the length of the multiple first network interaction signals sub-timings is performed to calculate the first network interaction signal sub-timing segmentation quality value.

[0045] In this embodiment, the preset weights for calculating the timing segmentation quality of the network interaction signals can be manually preset. First, the mean information, variance information, normalized information, and length normalized information of multiple first network interaction signal sub-timing values ​​can be weighted by their respective weighting factors. Then, all weighted values ​​are summarized, and the summarized values ​​are calibrated as a whole to eliminate computational biases in different dimensions of the data, thereby obtaining standardized first network interaction signal sub-timing segmentation quality values.

[0046] The signal conversion method provided in this application improves the objectivity and accuracy of the quality assessment of the timing segmentation quality value of the first network interaction signal sub-sequence, and ensures the rationality of the segmentation quality comparison of the timing segmentation quality value of the first network interaction signal sub-sequence. This provides a more reliable basis for the selection of timing information of multiple network interaction signals, which can be used to subsequently optimize the overall quality of remote network signal timing segmentation, enhance the controllability and fault tolerance of remote network signal transmission, and improve the communication coordination efficiency and data transmission adaptability of remote network.

[0047] Figure 5 The flowchart illustrating the implementation of the signal conversion method provided in Embodiment 5 of this application is shown. The difference between this method and Embodiment 2 described above is that step S205 specifically includes: Step S501: Determine whether the difference between the quality value of the first network interaction signal sub-timing segmentation and the quality value of the second network interaction signal sub-timing segmentation is less than a preset threshold for the difference in network interaction signal timing segmentation quality. If yes, proceed to step S502; if no, proceed to step S503.

[0048] In this embodiment, the preset threshold for the quality difference of network interaction signal timing segmentation can be set manually. First, the absolute difference between the quality values ​​of the first and second network interaction signal sub-timing segments can be calculated using a numerical calculation module. Then, this absolute difference is compared with the preset threshold for the quality difference of network interaction signal timing segmentation. If the absolute difference is less than the preset threshold, it indicates that the quality of the two segmentation results is similar, and the already segmented timing results can be directly filtered or integrated as multiple network interaction signal sub-timing information. If the absolute difference is greater than or equal to the preset threshold, it indicates that the segmentation quality difference is significant, and the parameters can be readjusted for re-segmentation.

[0049] Step S502: Based on the first group network interaction signal sub-timing segmentation quality value, the second group network interaction signal sub-timing segmentation quality value, multiple first group network interaction signal sub-timing information, and multiple second group network interaction signal sub-timing information, multiple group network interaction signal sub-timing information are obtained to obtain multiple group network interaction signal sub-timing information.

[0050] In this embodiment, a second comparison can be performed on the quality values ​​of the first group network interaction signal sub-timing segments and the second group network interaction signal sub-timing segments. If the quality value of the first group network interaction signal sub-timing segments is greater than that of the second group network interaction signal sub-timing segments, multiple first group network interaction signal sub-timing information can be selected as the basis, and higher-quality local segments from multiple second group network interaction signal sub-timing information can be integrated as supplements. If the quality value of the second group network interaction signal sub-timing segments is higher, multiple second group network interaction signal sub-timing information can be used as the main body, and advantageous segments from multiple first group network interaction signal sub-timing information can be integrated. If the two sets of quality values ​​are completely equal, a full-dimensional feature comparison is performed on multiple first group network interaction signal sub-timing information and multiple second group network interaction signal sub-timing information, and segments with better temporal integrity are selected for integration. Then, the integrated sub-timing information is labeled and boundary-verified to generate multiple network interaction signal sub-timing information that meets the requirements.

[0051] Step S503: Based on the preset network interaction signal timing segmentation point number adjustment variable, adjust and calculate the timing segmentation point number information of the first network interaction signal and the timing segmentation point number information of the second network interaction signal to obtain the adjusted timing segmentation point number information of the first network interaction signal and the adjusted timing segmentation point number information of the second network interaction signal.

[0052] In this embodiment, the preset adjustment variable for the number of timing segmentation points of the network interaction signal can be manually preset. First, the relationship between the quality values ​​of the first and second network interaction signal sub-timing segments can be determined. If the quality value of the first network interaction signal sub-timing segmentation is lower, the number of timing segmentation points for the first network interaction signal is increased according to the preset adjustment variable. If the quality value of the second network interaction signal sub-timing segmentation is lower, the number of timing segmentation points for the second network interaction signal is increased accordingly according to the preset adjustment variable. Specific numerical adjustments can be made in conjunction with the preset adjustment variable, and then the adjusted values ​​are verified for reasonableness to ensure they meet the length and transmission requirements of multiple network interaction signal timing information. This yields the adjusted number of timing segmentation points for the first and second network interaction signals.

[0053] Step S504: Use the adjusted first network interaction signal timing cut-off point quantity information as the first network interaction signal timing cut-off point quantity information, use the adjusted second network interaction signal timing cut-off point quantity information as the second network interaction signal timing cut-off point quantity information, and return to step S201.

[0054] In this embodiment, the adjusted number of timing cut points for the first group of network interaction signals can be used to overwrite the original number of timing cut points for the first group of network interaction signals. Then, the adjusted number of timing cut points for the second group of network interaction signals can replace the original number of timing cut points for the second group of network interaction signals. The cutting and quality evaluation process based on the new parameters can be re-executed, thereby achieving dynamic optimization and iteration of the cutting parameters.

[0055] The signal conversion method provided in this application effectively improves the quality and reliability of timing information of multiple network interaction signals, avoids poor segmentation effect caused by improper initial parameters, and enhances the adaptive ability to adapt and segment timing information of multiple network interaction signals, ensuring the adaptability of subsequent signal conversion information generation, thereby reducing the delay and packet loss risk of remote network signal transmission, improving the communication coordination efficiency and data transmission adaptability of remote network, and enhancing the controllability and fault tolerance of remote network signal transmission.

[0056] Figure 6 The flowchart illustrating the implementation of the signal conversion method provided in Embodiment Six of this application is shown. The difference between this method and Embodiment Five is that step S502 specifically includes: Step S601: Determine whether the quality value of the first group of network interaction signal sub-timing segmentation is greater than the quality value of the second group of network interaction signal sub-timing segmentation; if yes, proceed to step S602; if no, proceed to step S603.

[0057] In this embodiment, the quality values ​​of the first group of network interaction signal sub-timing segments and the second group of network interaction signal sub-timing segments can be directly compared. If the quality value of the first group of network interaction signal sub-timing segments is greater than that of the second group of network interaction signal sub-timing segments, it can be determined that the segmentation effect of multiple first group of network interaction signal sub-timing information is better; if the quality value of the first group of network interaction signal sub-timing segments is less than or equal to that of the second group of network interaction signal sub-timing segments, it can be determined that the segmentation effect of multiple second group of network interaction signal sub-timing information is better.

[0058] Step S602: The multiple first network interaction signal sub-timing information is used as multiple network interaction signal sub-timing information.

[0059] In this embodiment, the quality of multiple first-group network interaction signal sub-timing information can be re-checked first to confirm that the core indicators such as integrity parameters and independence parameters meet the signal processing requirements of remote networking. Then, the unique temporary tags in the multiple first-group network interaction signal sub-timing information are removed and uniformly replaced with standard time interval tags and node association indexes. Subsequently, the format is standardized to ensure that the storage structure and data format of each sub-timing segment are consistent. Finally, the processed multiple first-group network interaction signal sub-timing information is determined as multiple network interaction signal sub-timing information.

[0060] Step S603: The multiple second network interaction signal sub-timing information is used as multiple network interaction signal sub-timing information.

[0061] In this embodiment, the quality of multiple second-group network interaction signal sub-timing information can be re-checked first to confirm that the core indicators such as integrity parameters and independence parameters meet the signal processing requirements of remote networking. Then, the unique temporary tags in the multiple second-group network interaction signal sub-timing information are removed and uniformly replaced with standard time interval tags and node association indexes. Subsequently, the format is standardized to ensure that the storage structure and data format of each sub-timing segment are consistent. Finally, the processed multiple second-group network interaction signal sub-timing information is determined as multiple network interaction signal sub-timing information.

[0062] The signal conversion method provided in this application improves the accuracy, adaptability, and reliability of segmenting the timing information of multiple network interaction signals, laying the foundation for the efficient generation of multiple subsequent signal conversion information, thereby improving the overall efficiency of remote network signal processing, enhancing the stability and adaptability of remote network signal transmission, and reducing redundancy overhead in the communication coordination process.

[0063] Figure 7 The flowchart illustrating the implementation of the signal conversion method provided in Embodiment Seven of this application is shown. Its difference from Embodiment One described above lies in: The preset signal conversion model includes multiple preset signal conversion adaptation functions and multiple preset signal conversion sub-models; among them, the preset signal conversion adaptation functions and the preset signal conversion sub-models correspond one-to-one. Step S104 specifically includes: Step S701: Calculate the values ​​of multiple network interaction signal sub-timing adaptation functions based on the multiple network interaction signal sub-timing information and multiple preset signal conversion adaptation functions.

[0064] In this embodiment, the multiple preset signal conversion adaptation functions can be manually set or automatically generated by the preset signal conversion model during the training process before application. Each preset signal conversion adaptation function corresponds to a specific signal feature adaptation scenario and can be used to quantify the matching degree between multiple network interaction signal sub-timing information and the corresponding preset signal conversion sub-model. First, core adaptation features such as signal transmission protocol type data, signal amplitude parameters, and signal frequency characteristics can be extracted from each network interaction signal sub-timing information. Then, these core adaptation features are input into the multiple preset signal conversion adaptation functions. Each preset signal conversion adaptation function then processes the core adaptation features according to its own adaptation rules, outputting a value reflecting the degree of adaptation between the current network interaction signal sub-timing information and the preset signal conversion sub-model corresponding to that function. This yields multiple network interaction signal sub-timing adaptation function values ​​for each network interaction signal sub-timing information under different adaptation functions.

[0065] Step S702: Extract the maximum value of the multiple network interaction signal sub-timing adaptation function values ​​corresponding to the multiple network interaction signal sub-timing information to obtain the multiple network interaction signal conversion sub-model adaptation values.

[0066] In this embodiment, each network interaction signal sub-timing information can be categorized and organized into a set of network interaction signal sub-timing adaptation function values ​​to ensure that the adaptation function values ​​of each network interaction signal sub-timing information form an independent numerical set. Then, each numerical set is traversed one by one, and the maximum value is selected through the numerical comparison unit. This maximum value represents the degree of adaptation between the corresponding network interaction signal sub-timing information and the one with the highest matching degree among all preset signal conversion sub-models. Then, each selected maximum value is marked as the exclusive adaptation index of the corresponding network interaction signal sub-timing information, thereby obtaining multiple network interaction signal conversion sub-model adaptation values.

[0067] Step S703: Based on the multiple preset signal conversion sub-models corresponding to the multiple network interaction signal conversion sub-model adaptation values, generate multiple signal conversion information according to the multiple network interaction signal sub-timing information.

[0068] In this embodiment, the preset signal conversion sub-model can be manually preset and may include deep learning-based multi-protocol adaptation sub-models, traditional protocol parsing and conversion sub-models, etc., and each preset signal conversion sub-model has specific signal conversion capabilities. First, an index matching mechanism can be used to find the corresponding preset signal conversion sub-model based on the adaptation values ​​of multiple network interaction signal conversion sub-models, establishing a correlation between network interaction signal sub-timing information and the optimally adapted signal conversion sub-model. Then, each network interaction signal sub-timing information is input into its corresponding preset signal conversion sub-model. The corresponding signal conversion sub-model then performs targeted protocol adaptation, format adjustment, and data optimization on the input network interaction signal sub-timing information. During this process, the integrity and validity of the converted signal data are verified to avoid protocol incompatibility issues. Finally, corresponding conversion identifiers and adaptation node information are added to each converted network interaction signal sub-timing information, thereby generating multiple signal conversion information that meet the needs of each receiving end in the remote network.

[0069] The signal conversion method provided in this application ensures that the optimal signal conversion sub-model is matched for the timing information of each network interaction signal sub-model, thereby improving the pertinence and accuracy of signal conversion, avoiding the problem of insufficient adaptability of a single conversion model, ensuring high compatibility between multiple signal conversion information and receiving devices, thereby reducing the error rate of signal interaction in remote networking, improving the efficiency and stability of cross-device and cross-network segment signal transmission, and enhancing the communication coordination capability and data transmission adaptability of remote networking.

[0070] Corresponding to the method in the above embodiments, Figure 8 A structural block diagram of a signal conversion device provided in an embodiment of this application is shown. For ease of explanation, only the parts related to the embodiment of this application are shown. Figure 8 The example signal conversion device can be the execution subject of the signal conversion method provided in the aforementioned embodiment 1.

[0071] Reference Figure 8 The signal conversion device includes: The information acquisition module 810 is used to acquire information on multiple network interaction signals and the number of timing cut points for multiple network interaction signals. The network interaction signal timing information generation module 820 is used to generate multiple network interaction signal timing information based on the multiple network interaction signal information. The network interaction signal sub-timing information generation module 830 is used to cut the network interaction signal timing information according to the number of network interaction signal timing cutting points based on a preset network interaction signal timing cutting model, so as to obtain multiple network interaction signal sub-timing information. The signal conversion information generation module 840 is used to generate multiple signal conversion information based on a preset signal conversion model and according to the timing information of the multiple network interaction signal sub-sequences.

[0072] For details on how each module in the signal conversion device provided in this application implements its respective function, please refer to the foregoing. Figure 1 The description of Embodiment 1 shown will not be repeated here.

[0073] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0074] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0075] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0076] As used in this application specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if detected [the described condition or event]" may be interpreted, depending on the context, as meaning "once determined," "in response to determination," "once detected [the described condition or event]," or "in response to detection [the described condition or event]."

[0077] Furthermore, in the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only for distinguishing descriptions and should not be construed as indicating or implying relative importance. It should also be understood that although the terms "first," "second," etc., are used in the text to describe various elements in some embodiments of this application, these elements should not be limited by these terms. These terms are merely used to distinguish one element from another. For example, a first table may be named a second table, and similarly, a second table may be named a first table, without departing from the scope of the various described embodiments. Both the first table and the second table are tables, but they are not the same table.

[0078] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0079] The signal conversion method provided in this application can be applied to terminal devices such as mobile phones, tablets, wearable devices, in-vehicle devices, augmented reality / virtual reality devices, laptops, super mobile personal computers, netbooks, and personal digital assistants. This application does not impose any restrictions on the specific type of terminal device.

[0080] For example, the terminal device may be a station in a WLAN, a cellular phone, a cordless phone, a session initiation protocol phone, a wireless local loop station, a personal digital processing device, a handheld device with wireless communication capabilities, a computing device or other processing device connected to a wireless modem, an in-vehicle device, a vehicle networking terminal, a computer, a laptop computer, a handheld communication device, a handheld computing device, a satellite wireless device, a wireless modem card, a set-top box, a user premises equipment, and / or other devices for communication over a wireless system, as well as next-generation communication systems, such as mobile terminals in 5G networks or mobile terminals in future evolved public terrestrial mobile networks, etc.

[0081] Figure 9 This is a schematic diagram of the structure of a terminal device provided in an embodiment of this application. For example... Figure 9 As shown, the terminal device 9 of this embodiment includes: at least one processor 90 ( Figure 9(Only one is shown in the image) a memory 91, which stores a computer program 92 that can run on the processor 90. When the processor 90 executes the computer program 92, it implements the steps in the various signal conversion method embodiments described above, for example... Figure 1 Steps S101 to S104 are shown. Alternatively, when the processor 90 executes the computer program 92, it implements the functions of each module / unit in the above-described device embodiments, for example... Figure 8 The functions of modules 810 to 840 are shown.

[0082] The terminal device 9 can be a desktop computer, laptop, handheld computer, or cloud server, etc. The terminal device may include, but is not limited to, a processor 90 and a memory 91. Those skilled in the art will understand that... Figure 9 This is merely an example of terminal device 9 and does not constitute a limitation on terminal device 9. It may include more or fewer components than shown, or combine certain components, or different components. For example, the terminal device may also include input transmission devices, network access devices, buses, etc.

[0083] The processor 90 may be a central processing unit, or it may be other general-purpose processors, digital signal processors, application-specific integrated circuits, off-the-shelf programmable gate arrays or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc.

[0084] In some embodiments, the memory 91 may be an internal storage unit of the terminal device 9, such as a hard disk or memory of the terminal device 9. The memory 91 may also be an external storage device of the terminal device 9, such as a plug-in hard disk, smart memory card, secure digital card, flash memory card, etc., equipped on the terminal device 9. Furthermore, the memory 91 may include both internal and external storage units of the terminal device 9. The memory 91 is used to store operating systems, applications, bootloaders, data, and other programs, such as the program code of computer programs. The memory 91 can also be used to temporarily store data that has been sent or will be sent.

[0085] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0086] This application also provides a terminal device, which includes at least one memory, at least one processor, and a computer program stored in the at least one memory and executable on the at least one processor. When the processor executes the computer program, it causes the terminal device to implement the steps in any of the above method embodiments.

[0087] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps described in the various method embodiments above.

[0088] This application provides a computer program product that, when run on a terminal device, enables the terminal device to implement the steps described in the various method embodiments above.

[0089] If the integrated module / unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory, a random access memory, an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.

[0090] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0091] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0092] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0093] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A signal conversion method, characterized in that, include: Acquire information on multiple network interaction signals and the number of timing cut-off points for multiple network interaction signals; Based on the multiple network interaction signal information, multiple network interaction signal timing information is generated; Based on the preset network interaction signal timing segmentation model, the timing information of the multiple network interaction signals is segmented according to the number of timing segmentation points of the multiple network interaction signals to obtain multiple network interaction signal sub-timing information. Based on a preset signal conversion model, multiple signal conversion information is generated according to the timing information of the multiple network interaction signals.

2. The signal conversion method as described in claim 1, characterized in that, The information on the number of timing cut-off points for the multiple network interaction signals includes the information on the number of timing cut-off points for the first network interaction signal and the information on the number of timing cut-off points for the second network interaction signal. The step of segmenting the timing information of multiple network interaction signals based on a preset network interaction signal timing segmentation model, and obtaining multiple network interaction signal sub-timing information according to the number of timing segmentation points of the multiple network interaction signals, specifically includes: Based on the preset network interaction signal timing segmentation model, the timing information of the multiple network interaction signals is segmented according to the number of timing segmentation points of the first network interaction signal to obtain multiple first network interaction signal sub-timing information. The first network interaction signal sub-timing quality value is calculated based on the multiple first network interaction signal sub-timing information and the preset network interaction signal timing segmentation quality calculation weight. Based on the preset network interaction signal timing segmentation model, the timing information of the multiple network interaction signals is segmented according to the number of timing segmentation points of the second network interaction signal to obtain multiple second network interaction signal sub-timing information. The second network interaction signal sub-timing quality value is calculated based on the multiple second network interaction signal sub-timing information and the preset network interaction signal timing segmentation quality calculation weight. Multiple network interaction signal sub-timing information is obtained based on the multiple first network interaction signal sub-timing information, multiple second network interaction signal sub-timing information, the first network interaction signal sub-timing segmentation quality value, the second network interaction signal sub-timing segmentation quality value, and the preset network interaction signal timing segmentation quality difference threshold.

3. The signal conversion method as described in claim 2, characterized in that, The step of segmenting the timing information of the multiple network interaction signals based on the preset network interaction signal timing segmentation model, and obtaining multiple first network interaction signal sub-timing information according to the number of timing segmentation points of the first network interaction signal, specifically includes: Based on the number of timing cut points of the first network interaction signal, the timing information of multiple network interaction signals, and the preset timing cut model of the network interaction signal, the location information of multiple first network interaction signal sub-timing cut points is generated. Based on the location information of the multiple first network interaction signal sub-timing cutting points, the multiple network interaction signal timing information is segmented to obtain multiple first network interaction signal sub-timing information.

4. The signal conversion method as described in claim 2, characterized in that, The step of calculating the quality value of the first network interaction signal sub-timing segment based on the plurality of first network interaction signal sub-timing information and the preset network interaction signal timing segmentation quality calculation weights specifically includes: Based on the time-series information of the multiple first network interaction signals, the time-series length information, the time-series mean information, and the time-series variance information of the multiple first network interaction signals are calculated. Based on the mean information of the time series of the multiple first network interaction signals and the variance information of the time series of the multiple first network interaction signals, the time series information of the multiple first network interaction signals and the length information of the multiple first network interaction signals are numerically normalized to obtain the normalized information of the time series of the multiple first network interaction signals and the normalized information of the length of the time series of the multiple first network interaction signals. Based on the preset weights for calculating the timing segmentation quality of the network interaction signals, the weighted summation of the mean information of the multiple first network interaction signal sub-timings, the variance information of the multiple first network interaction signal sub-timings, the normalized information of the multiple first network interaction signal sub-timings, and the normalized information of the length of the multiple first network interaction signal sub-timings is performed to calculate the timing segmentation quality value of the first network interaction signal sub-timings.

5. The signal conversion method as described in claim 2, characterized in that, The step of obtaining multiple network interaction signal sub-timing information based on the multiple first network interaction signal sub-timing information, multiple second network interaction signal sub-timing information, the first network interaction signal sub-timing segmentation quality value, the second network interaction signal sub-timing segmentation quality value, and a preset network interaction signal timing segmentation quality difference threshold specifically includes: Determine whether the difference between the quality value of the first network interaction signal sub-timing segmentation and the quality value of the second network interaction signal sub-timing segmentation is less than a preset threshold for the difference in network interaction signal timing segmentation quality. If so, then based on the first group network interaction signal sub-timing segmentation quality value, the second group network interaction signal sub-timing segmentation quality value, multiple first group network interaction signal sub-timing information and multiple second group network interaction signal sub-timing information, multiple group network interaction signal sub-timing information are obtained to obtain multiple group network interaction signal sub-timing information; If not, then based on the preset network interaction signal timing cut-off point number adjustment variable, the timing cut-off point number information of the first network interaction signal and the timing cut-off point number information of the second network interaction signal are adjusted and calculated to obtain the adjusted timing cut-off point number information of the first network interaction signal and the adjusted timing cut-off point number information of the second network interaction signal. The steps involve taking the adjusted number of timing segmentation points of the first network interaction signal as the first network interaction signal timing segmentation point number information, taking the adjusted number of timing segmentation points of the second network interaction signal as the second network interaction signal timing segmentation point number information, and returning to the preset network interaction signal timing segmentation model. Based on the first network interaction signal timing segmentation point number information, the steps involve segmenting the multiple network interaction signal timing information to obtain multiple first network interaction signal sub-timing information.

6. The signal conversion method as described in claim 5, characterized in that, The step of obtaining multiple network interaction signal sub-timing information based on the first network interaction signal sub-timing segmentation quality value, the second network interaction signal sub-timing segmentation quality value, multiple first network interaction signal sub-timing information, and multiple second network interaction signal sub-timing information specifically includes: Determine whether the quality value of the first group of network interaction signal sub-timing segmentation is greater than the quality value of the second group of network interaction signal sub-timing segmentation. If so, the multiple first network interaction signal sub-timing information shall be used as multiple network interaction signal sub-timing information; If not, then the multiple second network interaction signal sub-timing information shall be used as multiple network interaction signal sub-timing information.

7. The signal conversion method as described in claim 1, characterized in that, The preset signal conversion model includes multiple preset signal conversion adaptation functions and multiple preset signal conversion sub-models; among them, the preset signal conversion adaptation functions and the preset signal conversion sub-models correspond one-to-one. The step of generating multiple signal conversion information based on a preset signal conversion model and according to the multiple network interaction signal sub-timing information specifically includes: Based on the multiple network interaction signal sub-timing information and multiple preset signal conversion adaptation functions, the values ​​of multiple network interaction signal sub-timing adaptation functions are calculated. Extract the maximum value of the multiple network interaction signal sub-timing adaptation function values ​​corresponding to the multiple network interaction signal sub-timing information to obtain the multiple network interaction signal conversion sub-model adaptation values; Based on the multiple preset signal conversion sub-models corresponding to the multiple network interaction signal conversion sub-model adaptation values, multiple signal conversion information is generated according to the multiple network interaction signal sub-timing information.

8. A signal conversion device, characterized in that, include: The information acquisition module is used to acquire information on multiple network interaction signals and the number of timing cut points for multiple network interaction signals. The network interaction signal timing information generation module is used to generate multiple network interaction signal timing information based on the multiple network interaction signal information. The sub-timing information generation module for network interaction signals is used to segment the timing information of multiple network interaction signals based on a preset timing segmentation model and according to the number of timing segmentation points of the multiple network interaction signals, to obtain multiple sub-timing information of network interaction signals. The signal conversion information generation module is used to generate multiple signal conversion information based on a preset signal conversion model and the timing information of the multiple network interaction signals.

9. A terminal device, characterized in that, The terminal device includes a memory and a processor. The memory stores a computer program that can run on the processor. When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 7.

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