A PLC Interactive Wireless Signal Conversion Method and System

Abstract

This invention discloses a PLC interactive wireless signal conversion method and system, relating to the field of PLC communication protocol conversion technology. The method includes: parsing a spatiotemporal pulse sequence, identifying and extracting core control elements to form triplet data; calculating chaotic state variables in real time based on the Lorentz differential equations and mapping them to carrier frequency offsets; injecting the triplet data into a carrier modulator, obtaining a dynamic carrier frequency through the carrier frequency offset and the fundamental frequency, and performing phase-shift keying modulation to generate a radio frequency signal; inputting the demodulated triplet data into a pulse neural network for decoding, reconstructing the original industrial protocol data stream, and outputting it to a second PLC via an Ethernet port to execute control commands. This improves the robustness and decoding accuracy of communication; enables the wireless signal to have adaptive frequency hopping capability and higher spectrum utilization, significantly enhancing communication stability and real-time response performance under multi-interference conditions in industrial environments.

Description

Technical Field

[0001] This invention relates to the field of PLC communication protocol conversion technology, and in particular to a PLC interactive wireless signal conversion method and system. Background Technology

[0002] With the continuous development of industrial automation systems, programmable logic controllers (PLCs), as core equipment in industrial control, are widely used in various intelligent manufacturing and process control systems. In recent years, with the rapid development of wireless communication technology, combining PLC control systems with wireless networks has become an important direction for improving the flexibility, scalability, and deployment efficiency of industrial systems.

[0003] Existing PLC wireless communication technologies still have limitations in terms of real-time performance, anti-interference capabilities, and protocol compatibility. Especially in complex industrial electromagnetic environments, fixed-frequency carrier communication is susceptible to interference, leading to increased data packet loss rates and affecting the stability and reliability of the control system. Traditional modulation methods lack adaptability to dynamic spectrum environments, making it difficult to meet the low-latency, high-precision communication requirements of industrial control scenarios. Summary of the Invention

[0004] In view of the aforementioned existing problems, the present invention is proposed.

[0005] Therefore, this invention provides a PLC interactive wireless signal conversion method to solve the problems of high latency and high packet loss rate in PLC control command transmission under complex industrial electromagnetic environments.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution:

[0007] In a first aspect, the present invention provides a PLC interactive wireless signal conversion method, comprising: acquiring raw control commands from the industrial Ethernet port of a first PLC, inputting them into a spiking neural network, and converting them into a spatiotemporal pulse sequence through a leakage integral ignition neuron layer and a protocol weight matrix; parsing the spatiotemporal pulse sequence, identifying and extracting core control elements, and forming triplet data; calculating chaotic state variables in real time based on the Lorentz differential equation system and mapping them to carrier frequency offsets; injecting the triplet data into a carrier modulator, obtaining a dynamic carrier frequency through the carrier frequency offset and the fundamental frequency, and performing phase shift keying modulation to generate a radio frequency signal; the PLC node capturing the radio frequency signal on the dynamic carrier frequency, obtaining the demodulated triplet data through a coherent demodulation method; inputting the demodulated triplet data into a spiking neural network for decoding, reconstructing the original industrial protocol data stream, and outputting it to a second PLC through the Ethernet port to execute control commands.

[0008] As a preferred embodiment of the PLC interactive wireless signal conversion method of the present invention, the steps of obtaining the original control command from the industrial Ethernet port of the first PLC, inputting it into a spiking neural network, and converting it into a spatiotemporal pulse sequence through a leakage integral ignition neuron layer and a protocol weight matrix are as follows:

[0009] The logical relationships between the fields of the original control instructions are analyzed, a protocol semantic topology graph is constructed, and a protocol weight matrix is ​​generated based on the node dependency strength of the protocol semantic topology graph.

[0010] The original control command is input into the spiking neural network to activate the neuromorphic encoding. The original control command is then subjected to nonlinear integral operation through the leakage integral ignition neuron layer to generate dynamic membrane potential changes. Semantic weighted fusion is then performed using the protocol weight matrix to obtain the postsynaptic potential distribution.

[0011] Historical control error data is collected to calculate the mean and standard deviation. The ignition threshold of the pulse neural network is dynamically set. The postsynaptic potential distribution is compared with the ignition threshold to trigger discrete pulse events and aggregate them to generate a spatiotemporal pulse sequence.

[0012] In a preferred embodiment of the PLC interactive wireless signal conversion method of the present invention, the steps for parsing the spatiotemporal pulse sequence, identifying and extracting core control elements, and forming triplet data are as follows:

[0013] The spatiotemporal pulse sequence is divided into time windows to generate spatiotemporal pulse distributions within multiple consecutive time periods;

[0014] Using the first spatiotemporal pulse distribution as the time reference, the effective window is screened by histogram correlation matching, and the time reference offset is calculated by combining the dynamic time warping algorithm. Timestamp translation compensation is performed on all effective windows to generate a time-aligned pulse sequence.

[0015] The time-aligned sequence is converted into a structured tensor, the spatial dimension is divided according to the neuron address, the temporal dimension is divided according to a fixed interval, the pulse sequence intensity is quantized into the energy dimension, and a three-dimensional spatial-temporal-energy matrix is ​​constructed through a hardware counter.

[0016] In the space-time-energy three-dimensional matrix, the target device address is located from the spatial dimension, the urgency of the operation is identified from the time dimension, and the control parameter values ​​are quantified from the energy dimension and converted into triplet data.

[0017] As a preferred embodiment of the PLC interactive wireless signal conversion method of the present invention, the specific steps for calculating chaotic state variables in real time based on the Lorentz differential equations and mapping them to carrier frequency offsets are as follows.

[0018] The initial parameters of the chaotic state are set based on the triplet data, and after cryptographic hash transformation, they are loaded into the hardware solving engine and subjected to discrete iterative calculation to obtain the chaotic state variables. The chaotic variables are updated in real time using the Euler method to obtain the updated chaotic state variables.

[0019] The updated chaotic state variables are dynamically normalized, extreme values ​​are tracked through a sliding window and standardized eigenvalues ​​are calculated, and the standardized eigenvalues ​​are linearly mapped to carrier frequency offsets according to physical constraints.

[0020] In a preferred embodiment of the PLC interactive wireless signal conversion method of the present invention, the steps of injecting triplet data into a carrier modulator, obtaining a dynamic carrier frequency through the carrier frequency offset and the fundamental frequency, and performing phase shift keying modulation to generate a radio frequency signal are as follows.

[0021] The carrier frequency offset is superimposed on the fundamental frequency of the carrier modulator to synthesize a dynamic carrier frequency in real time.

[0022] The triplet data is encapsulated into a communication protocol frame structure, and a timestamp and quantum error correction code are added to obtain a phase-encoded sequence;

[0023] The phase-coded sequence is injected into the carrier modulator corresponding to the dynamic carrier frequency, and phase-shift keying is performed on the dynamic carrier frequency to generate a radio frequency signal.

[0024] In a preferred embodiment of the PLC interactive wireless signal conversion method of the present invention, the PLC node captures radio frequency signals on a dynamic carrier frequency and obtains demodulated triplet data through a coherent demodulation method. The specific steps are as follows.

[0025] The radio frequency signal is radiated outward through the ISM band antenna. The PLC node locks the dynamic carrier frequency through the adjustable radio frequency front-end to capture it. After the signal is amplified by low noise, it is mixed to downconvert the radio frequency signal to a fixed intermediate frequency to obtain the intermediate frequency signal.

[0026] An orthogonal demodulator is used to separate the intermediate frequency signal, and an error voltage is generated by phase detection to eliminate carrier phase offset, outputting two orthogonal baseband signals;

[0027] The instantaneous phase quadrant position of two orthogonal baseband signals is analyzed to obtain the current symbol information and perform differential phase mapping to generate a continuous differential coded bit stream, which is then segmented and mapped into demodulated triplet data.

[0028] In a preferred embodiment of the PLC interactive wireless signal conversion method of the present invention, the steps of inputting the demodulated triplet data into a pulse neural network decoder to reconstruct the original industrial protocol data stream and outputting it to a second PLC for execution of control instructions via an Ethernet port are as follows:

[0029] The demodulated triplet data is encoded as a neuron trigger density vector. The neuron trigger density vector is then processed by the leak integral ignition neuron layer of the spiking neural network to generate a reconstructed spatiotemporal pulse sequence.

[0030] The pattern distribution characteristics of the spatiotemporal pulse sequence are reconstructed by parsing the protocol weight matrix, and the industrial protocol data frame structure is reconstructed. A timestamp and check code are added to encapsulate the standard Ethernet frame, and the output is sent to the Ethernet port of the second PLC through the physical layer drive circuit.

[0031] Secondly, this invention provides a PLC interactive wireless signal conversion system, comprising: an encoding module for acquiring raw control commands from the industrial Ethernet port of a first PLC, inputting them into a spiking neural network, and converting them into a spatiotemporal pulse sequence through a leakage integral ignition neuron layer and a protocol weight matrix; a parsing module for parsing the spatiotemporal pulse sequence, identifying and extracting core control elements, and forming triplet data; a modulation module for calculating chaotic state variables in real time based on the Lorentz differential equations and mapping them to a carrier frequency offset; a wireless transmission module for injecting the triplet data into a carrier modulator, obtaining a dynamic carrier frequency through the carrier frequency offset and a fundamental frequency, and performing phase shift keying modulation to generate a radio frequency signal; a demodulation module for the PLC node to capture the radio frequency signal on the dynamic carrier frequency, and obtaining the demodulated triplet data through a coherent demodulation method; and a decoding module for inputting the demodulated triplet data into a spiking neural network decoder, reconstructing the original industrial protocol data stream, and outputting it to a second PLC through an Ethernet port to execute control commands.

[0032] Thirdly, the present invention provides a computer device including a memory and a processor, wherein the memory stores a computer program, wherein when the computer program is executed by the processor, it implements any step of the PLC interactive wireless signal conversion method as described in the first aspect of the present invention.

[0033] Fourthly, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, it implements any step of the PLC interactive wireless signal conversion method as described in the first aspect of the present invention.

[0034] The beneficial effects of this invention are as follows: by introducing a pulse neural network to perform semantic weighted fusion and spatiotemporal pulse coding on the original control instructions of the PLC, efficient representation and anti-interference transmission of control data in complex electromagnetic environments are achieved, improving the robustness of communication and decoding accuracy; combined with the Lorentz chaotic system to generate dynamic carrier frequency offset, the wireless signal has adaptive frequency hopping capability and higher spectrum utilization, significantly enhancing the communication stability and real-time response performance under multiple interference conditions in industrial sites. Attached Figure Description

[0035] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0036] Figure 1 This is a flowchart of a PLC interactive wireless signal conversion method.

[0037] Figure 2 This is a schematic diagram of a PLC-interactive wireless signal conversion system.

[0038] Figure 3 This is a flowchart of the spiking neural network encoding and decoding process.

[0039] Figure 4 This is a flowchart of chaotic carrier modulation and demodulation. Detailed Implementation

[0040] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0041] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0042] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0043] Reference Figures 1-4 As one embodiment of the present invention, this embodiment provides a PLC interactive wireless signal conversion method, including the following steps:

[0044] S1. Obtain the original control command from the industrial Ethernet port of the first PLC, input it into the spiking neural network, and transform it into a spatiotemporal pulse sequence through the leakage integral ignition neuron layer and the protocol weight matrix.

[0045] The logical relationships between the fields of the original control instructions are parsed, a protocol semantic topology graph is constructed, and a protocol weight matrix is ​​generated based on the node dependency strength of the protocol semantic topology graph.

[0046] Specifically, the attributes and interrelationships of each field in the original control command are analyzed to identify logical connections between fields, such as dependency order or hierarchical structure. Based on the analysis results of the logical relationships between fields, a protocol semantic topology graph is constructed, where nodes in the protocol semantic topology graph represent fields of the original control command, and edges in the protocol semantic topology graph represent the interaction strength between fields. In the protocol semantic topology graph, the dependency strength of each node on other nodes is calculated, for example, by quantifying the node's influence by statistically analyzing the in-degree weight value, and a protocol weight matrix is ​​generated based on the dependency strength values ​​of the nodes in the protocol semantic topology graph.

[0047] It should be noted that the formula for calculating the node dependency strength of the semantic topology graph of the computation protocol is:

[0048]

[0049] in, Nodes representing the semantic topology graph of the protocol The dependence strength value, Represents all nodes that directly point to each other. The set of neighboring nodes, Indicates from node Pointing to node edge weight values, Indicates all direct to The node that sends information or instructions. The node index represents the semantic topology graph of the protocol.

[0050] The original control command is input into the spiking neural network to activate the neuromorphic encoding. The original control command is then subjected to nonlinear integral operation through the leakage integral ignition neuron layer to generate dynamic membrane potential changes. Semantic weighted fusion is then performed using the protocol weight matrix to obtain the postsynaptic potential distribution.

[0051] Specifically, the original control command is input into the spiking neural network, activating the neuromorphic encoding process. The original control command then enters the leakage integral ignition neuron layer, which performs nonlinear integral operations on the original control command. These nonlinear integral operations include the calculation of membrane potential decay based on the time constant and the integral superposition of the input current. During the nonlinear integral operation, the leakage integral ignition neuron layer performs semantic weighted fusion based on the protocol weight matrix. The weighting coefficients of the protocol weight matrix are associated with the protocol field types of the original control command. For example, the weighting coefficient for the function code field is 0.8, the weighting coefficient for the address field is 0.2, and the weighting coefficient for the parameter value field is 0.4. The result of the semantic weighted fusion is reflected in the dynamic membrane potential changes of the leakage integral ignition neuron layer, outputting the postsynaptic potential distribution.

[0052] It should be noted that, to train the spiking neural network, 100,000 control command samples were extracted from the historical database of industrial protocols. The protocol fields in the control command samples were normalized and aligned to a 10-millisecond time window. The normalized protocol fields were injected into the leakage integral ignition neuron layer for forward propagation. This process included superimposing the membrane potential decay of the time constant with the integral of the input current. A loss function of the sum of squared pulse time errors was constructed based on the standard pulse time labeled by the industrial protocol. The weight coefficients of the protocol weight matrix were optimized through the backpropagation algorithm. The backpropagation algorithm calculated the partial derivative of the loss function with respect to the weight coefficients and updated the weight coefficients using a gradient descent rule with a learning rate of 0.001. The training process adopted a batch training strategy with a batch size of 128 samples. After 5,000 iterations, the loss convergence was achieved, resulting in the trained spiking neural network.

[0053] Historical control error data is collected to calculate the mean and standard deviation. The ignition threshold of the pulse neural network is dynamically set. The postsynaptic potential distribution is compared with the ignition threshold to trigger discrete pulse events and aggregate them to generate a spatiotemporal pulse sequence.

[0054] Specifically, control error data is collected from the historical control command database, and the mean and standard deviation of the control error data are calculated; the ignition threshold of the leakage integral ignition neuron layer is dynamically set based on the mean and standard deviation.

[0055] The postsynaptic potential distribution output by the leaky integral ignition neuron layer is compared in real time with a dynamically set ignition threshold; when the value of the postsynaptic potential distribution exceeds the ignition threshold, a discrete pulse event is triggered; the discrete pulse event is timestamped and associated with the neuron identifier; all triggered discrete pulse events are aggregated to generate a spatiotemporal pulse sequence.

[0056] It should be noted that the expressions for calculating the mean and standard deviation are as follows:

[0057]

[0058] in, This represents the mean of historical control error data. This represents the total number of control error data samples recorded in the historical control command database. Indicates the first The control error value generated after the execution of the next control command. Indicates the index of control commands;

[0059]

[0060] in, This represents the standard deviation of historical control error data.

[0061] S2. Analyze the spatiotemporal pulse sequence, identify and extract the core control elements, and form triplet data.

[0062] The spatiotemporal pulse sequence is divided into time windows to generate spatiotemporal pulse distributions within multiple consecutive time periods.

[0063] Specifically, a time window segmentation operation is performed on the spatiotemporal pulse sequence, with the time window length set to a fixed value derived from the standard scanning cycle of industrial control. The timestamps of the spatiotemporal pulse sequence are segmented according to the time window length to generate multiple consecutive time window intervals. Within each time window interval, all pulse events triggered within the time period are extracted. The number and distribution characteristics of pulse events within each time window interval are statistically analyzed. The statistical results are then categorized and aggregated according to neuron identifiers to generate the spatiotemporal pulse distribution within multiple consecutive time periods.

[0064] Using the first spatiotemporal pulse distribution as a time reference, effective windows are selected through histogram correlation matching. The time reference offset is calculated by combining the dynamic time warping algorithm, and timestamp translation compensation is performed on all effective windows to generate time-aligned pulse sequences.

[0065] Specifically, the first spatiotemporal pulse distribution is used as the time reference distribution; the spatiotemporal pulse distributions of subsequent windows are correlated with the time reference distribution using histograms; a dynamic time warping algorithm is used to perform nonlinear time axis bending matching between the pulse interval sequence of each effective window and the pulse interval sequence of the time reference distribution to obtain the optimal path offset; based on the optimal path offset output by the dynamic time warping algorithm, a subtraction translation operation is performed on the timestamps of all pulses within the effective window; after completing the timestamp translation compensation for all effective windows, they are spliced ​​together in the original time window order to generate a time-aligned pulse sequence.

[0066] The time-aligned pulse sequence is converted into a structured tensor, the spatial dimension is divided according to the neuron address, the temporal dimension is divided according to a fixed interval, the pulse sequence intensity is quantized into the energy dimension, and a three-dimensional spatial-temporal-energy matrix is ​​constructed through a hardware counter.

[0067] Specifically, after the time-aligned pulse sequence is input, spatial dimension partitioning is performed: the neuron address carried by each pulse is used as a spatial index to establish spatial dimension coordinates; temporal dimension segmentation is performed: time slices are divided according to fixed time intervals (1ms in the example) to generate continuous time slice indices; pulse intensity quantization is performed: the pulse amplitude at each spatial location within each time slice is integrated using a hardware counter to obtain a normalized energy value; and a three-dimensional spatial-temporal-energy matrix is ​​constructed based on the spatial dimension coordinates, time slice indices, and normalized energy values.

[0068] In the space-time-energy three-dimensional matrix, the target device address is located from the spatial dimension, the urgency of the operation is identified from the time dimension, and the control parameter values ​​are quantified from the energy dimension and converted into triplet data.

[0069] Specifically, in the space-time-energy three-dimensional matrix, the spatial dimension operation involves: traversing all neuron address indices, locating the spatial coordinates of the maximum cumulative energy value, and using this as the target device address; the temporal dimension operation involves: statistically analyzing the pulse density of consecutive time slices at the time segment where the target device address is located, and mapping the pulse density to the urgency of the operation; and the energy dimension operation involves: taking the maximum energy value of the time slice where the target device address is located, quantifying the control parameter values ​​through a calibration curve; and integrating the target device address, the urgency of the operation, and the control parameter values ​​to obtain triplet data.

[0070] S3. Based on the Lorentz differential equations, calculate the chaotic state variables in real time and map them to the carrier frequency offset.

[0071] The initial parameters of the chaotic state are set based on the triplet data. After cryptographic hash transformation, the data is loaded into the hardware solving engine and subjected to discrete iterative calculation to obtain the chaotic state variables. The chaotic variables are then updated in real time using the Euler method to obtain the updated chaotic state variables.

[0072] Specifically, the target device address, operation urgency, and control parameter values ​​from the triplet data are concatenated into a string in a fixed order. The concatenated string is then input into the SHA-256 hash algorithm, which outputs a 256-bit digest, from which the first 128 bits are truncated. The 128-bit digest is then segmented into 32-bit segments and loaded into the initial state register of the hardware solver engine. The hardware solver engine performs discrete iterative calculations at time steps (50 μs in the example) and updates the chaotic state variables using the Euler method, outputting the updated chaotic state variables.

[0073] The updated chaotic state variables are normalized, extreme values ​​are tracked through a sliding window and standardized eigenvalues ​​are calculated, and the standardized eigenvalues ​​are linearly mapped to carrier frequency offsets according to physical constraints.

[0074] Specifically, the updated chaotic state variables are normalized by using a sliding window mechanism to track the maximum and minimum values ​​within a specified time window at continuous time points; based on the tracked extreme values, standardized eigenvalues ​​are calculated, and a normalization operation is performed to obtain a scalar value; the standardized eigenvalues ​​are then linearly mapped according to the range of physical constraint carrier frequency offset to obtain the carrier frequency offset.

[0075] S4. Inject the triplet data into the carrier modulator, obtain the dynamic carrier frequency through the carrier frequency offset and the fundamental frequency, and perform phase shift keying modulation to generate the radio frequency signal.

[0076] The carrier frequency offset is superimposed on the fundamental frequency of the carrier modulator to synthesize a dynamic carrier frequency in real time.

[0077] Specifically, after the carrier frequency offset is generated, the base frequency is used as a fixed reference frequency point. The base frequency and the carrier frequency offset are arithmetically added by a hardware adder, and the superimposed frequency value is output in real time as the dynamic carrier frequency. The arithmetic addition calculation is based on electronic circuits, such as the addition principle of digital adders or analog mixers. The carrier frequency offset value and the base frequency value are input into the adder unit, and instantaneous addition is performed to generate the dynamic carrier frequency.

[0078] The triplet data is encapsulated into a communication protocol frame structure, and a timestamp and quantum error correction code are added to obtain a phase-encoded sequence.

[0079] Specifically, the triplet data is first written into the field position of the communication protocol frame structure in byte alignment. The current absolute time value is extracted from the real-time clock circuit as a timestamp and filled into the specified address segment of the frame header. Then, the quantum error correction encoder is used to encode the complete payload containing the timestamp and triplet data. The output quantum error correction code is written into the frame tail check area to form a phase coding sequence.

[0080] The phase-coded sequence is injected into the carrier modulator corresponding to the dynamic carrier frequency, and phase-shift keying is performed on the dynamic carrier frequency to generate a radio frequency signal, which is then radiated outward through an ISM band antenna.

[0081] Specifically, the phase-coded sequence is input as a modulation source into a carrier modulator that is synchronized with the dynamic carrier frequency. Simultaneously, phase-shift keying modulation technology is used within the carrier modulator to dynamically adjust the phase state of the output signal based on the bit values ​​of the phase-coded sequence. A phase shift operation is performed based on the dynamic carrier frequency as a constant carrier frequency point to generate a radio frequency (RF) signal. The RF signal is then amplified and transmitted to an antenna element operating in the ISM band. The antenna element radiates the RF signal in the form of electromagnetic waves into free space.

[0082] The S5.PLC node captures radio frequency signals on a dynamic carrier frequency and obtains demodulated triplet data through coherent demodulation.

[0083] The PLC node locks the dynamic carrier frequency through an adjustable RF front-end, amplifies the signal with low noise, and then performs a mixing operation to downconvert the RF signal to a fixed intermediate frequency to obtain the intermediate frequency signal.

[0084] Specifically, the PLC node performs carrier frequency locking operation through an adjustable RF front-end driven by a voltage-controlled oscillator, configuring the local oscillator frequency to be synchronized with the dynamic carrier frequency; a low-noise amplifier is used to optimize the signal-to-noise ratio of the captured RF signal, with an example signal strength enhancement of 40 dB; the amplified RF signal is input to a mixer and simulated with the local oscillator frequency, and the output result is filtered by a bandpass filter to remove high-frequency components, downconverting the RF signal to a fixed intermediate frequency, for example, a fixed intermediate frequency set to 70 MHz, and outputting an intermediate frequency signal.

[0085] An orthogonal demodulator is used to separate the intermediate frequency signal, and an error voltage is generated by phase detection to eliminate carrier phase offset, outputting two orthogonal baseband signals.

[0086] Specifically, the quadrature demodulator receives the intermediate frequency (IF) signal and performs calculations with the in-phase reference signal and quadrature reference signal generated by the local oscillator through two internal mixers, respectively, decomposing the IF signal into in-phase and quadrature components. The calculation results are input to a low-pass filter to remove high-frequency residual components, separating two initial versions of the quadrature baseband signal. A phase detector is used to compare the phase difference of the two initial versions of the quadrature baseband signal in real time, generating an error voltage reflecting the phase deviation. The error voltage is input to a voltage-controlled oscillator to adjust the phase angle of the local oscillator, eliminating the carrier phase offset between the local oscillator output signal and the received carrier, aligning the local reference signal with the received signal, and outputting two phase-compensated quadrature baseband signals, which are represented as the in-phase channel baseband signal and the quadrature channel baseband signal, respectively.

[0087] The instantaneous phase quadrant position of two orthogonal baseband signals is analyzed to obtain the current symbol information and perform differential phase mapping to generate a continuous differential coded bit stream, which is then segmented and mapped into demodulated triplet data.

[0088] Specifically, the two orthogonal baseband signals are referred to as the in-phase channel baseband signal and the orthogonal channel baseband signal, respectively. The in-phase channel baseband signal and the orthogonal channel baseband signal values ​​at each time point are input into the phase calculator to obtain the instantaneous phase angle. The quadrant position of the instantaneous phase angle is determined by the quadrant division standard (e.g., the first quadrant corresponds to the angle range of 0° to 90°). The current symbol information is decoded according to the quadrant position (for example, in phase shift keying modulation, each quadrant maps to a discrete symbol). The phase angle difference between the current symbol information and the symbol at the previous time point is compared to perform differential phase mapping (e.g., a phase difference of 90° maps to bit "10") to generate a binary bit sequence, i.e., a differentially encoded bit stream. Data is segmented according to the fixed bit length defined by the communication protocol frame structure (for example, segmented into 8-bit blocks). The segmented bit blocks are converted and reassembled into demodulated triplet data according to the triplet data format specification.

[0089] S6. Input the demodulated triplet data into the spiking neural network decoder to reconstruct the original industrial protocol data stream, and output it to the second PLC through the Ethernet port to execute control instructions.

[0090] The demodulated triplet data is encoded into a neuron trigger density vector. The neuron trigger density vector is then processed by the leak integral ignition neuron layer of the spiking neural network to generate a reconstructed spatiotemporal pulse sequence.

[0091] Specifically, the demodulated triplet data is assigned to neuron index positions, and the control parameter values ​​are scaled proportionally to convert them into trigger frequency values ​​to fill the corresponding index positions, resulting in a neuron trigger density vector. The neuron trigger density vector is input to the leakage integral ignition neuron layer of the spiking neural network, and the membrane potential integral calculation is performed for continuous time steps. The ignition threshold is obtained based on the standard deviation of the collected historical control errors and the safety margin coefficient of the reliability requirements of the industrial scenario. When the membrane potential exceeds the ignition threshold, a pulse event is emitted. After the pulse event is accumulated in the time domain, a reconstructed spatiotemporal pulse sequence with spatial dimension (neuron address) and temporal dimension (pulse occurrence time) is output.

[0092] It should be noted that the expression for calculating the membrane potential integral over a continuous time step is:

[0093]

[0094] in, Indicates the membrane time constant. Represents membrane potential Over time rate of change, It represents a small change in membrane potential. Represents tiny intervals of time. This represents the membrane potential value at the current moment. This represents the resting potential reference value. Indicates time The synaptic input current, This indicates a very small change or difference. Indicates time.

[0095] The pattern distribution characteristics of the spatiotemporal pulse sequence are reconstructed by parsing the protocol weight matrix, and the industrial protocol data frame structure is reconstructed. A timestamp and check code are added to encapsulate the standard Ethernet frame, and the output is sent to the Ethernet port of the second PLC through the physical layer drive circuit.

[0096] Specifically, matrix multiplication is performed using the protocol weight matrix to analyze and reconstruct the pulse triggering pattern distribution characteristics of each neuron node in the spatiotemporal pulse sequence. A weighted summation formula is used to calculate the field weight distribution vector. Based on this vector, the activation strength of the device address field and control command field is located, and the industrial protocol data frame structure is reconstructed: the device address field uses the address code corresponding to the maximum weight index, and the control command field is decoded from the pulse time interval of consecutive neuron clusters. Original timestamp information (derived from the first pulse time stamp of the reconstructed spatiotemporal pulse sequence) is embedded in the header of the reconstructed industrial protocol data frame, and a CRC-32 cyclic redundancy check code is appended to the tail. After encapsulation, the signal level is converted by a Manchester encoder in the physical layer driver circuit and output to the Ethernet port of the second PLC via an RJ45 interface.

[0097] It should be noted that the weighted summation formula is as follows:

[0098]

[0099] in, Represents the field weight distribution vector. Represents the protocol weight matrix. This represents the pulse triggering mode distribution vector.

[0100] This embodiment also provides a PLC interactive wireless signal conversion system, including: an encoding module, a parsing module, a modulation module, a wireless transmission module, a demodulation module, and a decoding module; the encoding module is used to obtain the original control commands from the industrial Ethernet port of the first PLC, input them into a spiking neural network, and convert them into a spatiotemporal pulse sequence through leakage integral ignition neuron layers and protocol weight matrices; the parsing module is used to parse the spatiotemporal pulse sequence, identify and extract core control elements, and form triplet data; the modulation module is used to calculate chaotic state variables in real time based on the Lorentz differential equation system and map them to carrier frequency offsets; the wireless transmission module is used to inject the triplet data into a carrier modulator, obtain a dynamic carrier frequency through the carrier frequency offset and the fundamental frequency, and perform phase shift keying modulation to generate a radio frequency signal; the demodulation module is used for the PLC node to capture the radio frequency signal on the dynamic carrier frequency, and obtain the demodulated triplet data through a coherent demodulation method; the decoding module is used to input the demodulated triplet data into a spiking neural network decoder, reconstruct the original industrial protocol data stream, and output it to the second PLC to execute control commands through the Ethernet port.

[0101] This embodiment also provides a computer device applicable to the PLC interactive wireless signal conversion method, including: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to implement the PLC interactive wireless signal conversion method proposed in the above embodiment.

[0102] The computer device can be a terminal, comprising a processor, memory, communication interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, carrier networks, NFC (Near Field Communication), or other technologies. The display screen can be an LCD screen or an e-ink screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad on the computer device's casing, or an external keyboard, touchpad, or mouse.

[0103] This embodiment also provides a storage medium storing a computer program, which, when executed by a processor, implements the PLC interactive wireless signal conversion method proposed in the above embodiments. The storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read Only Memory (EPROM), Programmable Red-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0104] In summary, this invention achieves efficient representation and anti-interference transmission of control data in complex electromagnetic environments by introducing a pulse neural network to perform semantic weighted fusion and spatiotemporal pulse coding of the original PLC control instructions, thereby improving the robustness of communication and decoding accuracy. Furthermore, by combining this with a Lorentz chaotic system to generate dynamic carrier frequency offsets, the wireless signal acquires adaptive frequency hopping capability and higher spectrum utilization, significantly enhancing communication stability and real-time response performance under multi-interference conditions in industrial settings.

[0105] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A PLC interactive wireless signal conversion method, characterized by: The application relates to a method for realizing industrial protocol conversion between PLCs, and belongs to the technical field of industrial communication. The original control instruction is obtained from an industrial Ethernet port of a first PLC, input into a pulse neural network, converted into a time-space pulse sequence through a leaky integral firing neuron layer and a protocol weight matrix, and the specific steps are as follows. The field logical relationship of the original control instruction is analyzed, a protocol semantic topology graph is constructed, and a protocol weight matrix is generated based on the node dependency strength of the protocol semantic topology graph. The original control instruction is input into the pulse neural network, the neural morphological coding is activated, the original control instruction is subjected to nonlinear integral operation through the leaky integral firing neuron layer, the dynamic membrane potential change is generated, the protocol weight matrix is used for semantic weighted fusion, and the postsynaptic potential distribution is obtained. The historical control error data are collected to calculate the mean value and standard deviation, the firing threshold of the pulse neural network is dynamically set, the postsynaptic potential distribution is compared with the firing threshold, the discrete pulse events are triggered and aggregated, and the time-space pulse sequence is generated. The time-space pulse sequence is analyzed, core control elements are identified and extracted, and triple data are formed. The chaotic state variables are calculated in real time based on the Lorenz differential equation set, and are mapped into carrier frequency offsets. The triple data are injected into a carrier modulator, the dynamic carrier frequency is obtained through the carrier frequency offset and the basic frequency, phase shift keying modulation is carried out, and a radio frequency signal is generated. The PLC node captures the radio frequency signal on the dynamic carrier frequency, and obtains the demodulated triple data through coherent demodulation. The demodulated triple data are input into the pulse neural network for decoding, the original industrial protocol data stream is reconstructed, and the control instruction is output to a second PLC through an Ethernet port.

2. The PLC interactive wireless signal conversion method of claim 1, wherein: The time-space pulse sequence is analyzed, core control elements are identified and extracted, and triple data are formed, and the specific steps are as follows. The time-space pulse sequence is divided into time windows, and time-space pulse distributions in multiple continuous time periods are generated. The first time-space pulse distribution is taken as a time reference, effective windows are screened through histogram correlation matching, the time reference offset is calculated by combining a dynamic time warping algorithm, all the effective windows are time stamp shifted and compensated, and a time-aligned pulse sequence is generated. The time-aligned pulse sequence is converted into a structured tensor, the spatial dimension is divided according to the neuron address, the time dimension is cut at a fixed interval, the time-aligned pulse sequence is quantized into an energy dimension, and a space-time-energy three-dimensional matrix is constructed through a hardware counter. In the space-time-energy three-dimensional matrix, the target device address is located from the spatial dimension, the operation urgency is identified from the time dimension, the control parameter value is quantified from the energy dimension, and the triple data are converted.

3. The PLC interactive wireless signal conversion method of claim 2, wherein: The chaotic state variables are calculated in real time based on the Lorenz differential equation set, and are mapped into carrier frequency offsets, and the specific steps are as follows. The chaotic state initial parameters are set according to the triple data, are converted through a cryptography hash after being loaded into a hardware solving engine and are subjected to discrete iterative operation, the chaotic state variables are obtained, the chaotic variables are updated in real time by adopting an Euler method, and the updated chaotic state variables are obtained. The updated chaotic state variables are subjected to dynamic range normalization processing, extreme values are tracked through a sliding window and a standardized characteristic value is calculated, the standardized characteristic value is linearly mapped into a carrier frequency offset according to physical constraints.

4. The PLC interactive wireless signal conversion method of claim 3, wherein: The ternary data is injected into a carrier modulator, a dynamic carrier frequency is obtained through a carrier frequency offset and a base frequency, and phase shift keying modulation is performed to generate a radio frequency signal, and the specific steps are as follows, The carrier frequency offset is superimposed on the base frequency of the carrier modulator to synthesize a dynamic carrier frequency in real time. The ternary data is encapsulated into a communication protocol frame structure, a timestamp and a quantum error correction code are added, and a phase encoding sequence is obtained. The phase encoding sequence is injected into the carrier modulator corresponding to the dynamic carrier frequency, and phase shift keying is performed on the dynamic carrier frequency to generate a radio frequency signal.

5. The PLC interactive wireless signal conversion method of claim 4, wherein: The PLC node captures the radio frequency signal on the dynamic carrier frequency, and obtains the demodulated ternary data through a coherent demodulation method, and the specific steps are as follows, The radio frequency signal is radiated outward through an ISM frequency band antenna, and the PLC node locks the dynamic carrier frequency through an adjustable radio frequency front end, performs mixing operation after signal enhancement through low noise amplification, and down-converts the radio frequency signal to a fixed intermediate frequency to obtain an intermediate frequency signal; An orthogonal demodulator is used to separate the intermediate frequency signal, an error voltage is generated through phase detection to eliminate the carrier phase offset, and two channels of quadrature baseband signals are output; The instantaneous phase quadrant position of the two channels of quadrature baseband signals is analyzed to obtain the current symbol information and perform differential phase mapping to generate a continuous differential encoding bit stream, and the continuous differential encoding bit stream is cut and mapped into demodulated ternary data.

6. The PLC interactive wireless signal conversion method of claim 5, wherein: The demodulated ternary data is input into a pulse neural network decoder to reconstruct the original industrial protocol data stream, and the original industrial protocol data stream is output to a second PLC through an Ethernet port to execute control instructions, and the specific steps are as follows, The demodulated ternary data is encoded into a neuron trigger density vector, the neuron trigger density vector is processed through a leaky integration firing neuron layer of a pulse neural network to generate a reconstructed spatiotemporal pulse sequence; The mode distribution characteristics of the reconstructed spatiotemporal pulse sequence are analyzed using a protocol weight matrix, and the industrial protocol data frame structure is reconstructed, a timestamp and a check code are added, and a standard Ethernet frame is encapsulated, and the standard Ethernet frame is output to the Ethernet port of the second PLC through a physical layer driving circuit.

7. A PLC interactive wireless signal conversion system based on the PLC interactive wireless signal conversion method according to any one of claims 1 to 6, characterized in that: It comprises, An encoding module is configured to obtain original control instructions from an industrial Ethernet port of a first PLC, input a pulse neural network, and convert the original control instructions into a spatiotemporal pulse sequence through a leaky integration firing neuron layer and a protocol weight matrix; An analysis module is configured to analyze the spatiotemporal pulse sequence, identify and extract core control elements, and form ternary data; A modulation module is configured to calculate chaotic state variables in real time based on a set of Lorenz differential equations, and map the chaotic state variables into a carrier frequency offset; A wireless transmission module is configured to inject the ternary data into a carrier modulator, obtain a dynamic carrier frequency through a carrier frequency offset and a base frequency, and perform phase shift keying modulation to generate a radio frequency signal; A demodulation module is configured to capture a radio frequency signal on a dynamic carrier frequency by a PLC node, and obtain demodulated ternary data through a coherent demodulation method; A decoding module is configured to input the demodulated ternary data into a pulse neural network decoder to reconstruct an original industrial protocol data stream, and output the original industrial protocol data stream to a second PLC through an Ethernet port to execute control instructions.

8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that: The computer program is executed by the processor to realize the steps of the PLC interactive wireless signal conversion method in any one of claims 1-6.

9. A computer readable storage medium having stored thereon a computer program, characterized in that: The computer program is executed by the processor to realize the steps of the PLC interactive wireless signal conversion method in any one of claims 1-6.

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