A multi-sensor high-frequency data synchronous acquisition method and system

Abstract

The present application relates to the technical field of intelligent sensor, in particular to a kind of multi-sensor high-frequency data synchronous acquisition method and system, comprising the following steps: analog voltage is converted into oscillation signal, and phase pulse is superimposed to form single electric signal, sampling generates mixed sequence, obtains environmental value by band-pass filtering analysis frequency, extracts phase marker to generate data packet, calculates time offset and shifts alignment output synchronous data.In the present application, the analog signal of sensor is converted into oscillation signal and superimposed with global phase reference pulse to form single composite electric signal, single-channel data is separated by frequency band and instantaneous frequency analysis based on global sampling and digital band-pass filtering, and time offset is shifted and aligned by extracting phase marker, and other technical means, realize the mixed acquisition and accurate digital reconstruction of multi-channel high-frequency sensing data under single physical channel, ensure the strict time synchronization of multi-source high-frequency signal, improve the reliability and transmission efficiency of multi-sensor data joint analysis.

Description

Technical Field

[0001] This invention relates to the field of intelligent sensor technology, and in particular to a method and system for synchronous acquisition of high-frequency data from multiple sensors. Background Technology

[0002] The field of intelligent sensor technology involves various detection devices with information acquisition, processing, and communication functions. Its main function is to sense external environmental parameters and convert them into recognizable digital signals for processing by terminal systems. It is widely used in industries such as industrial automation, autonomous driving, the Internet of Things (IoT), and aerospace. Among these, the synchronous acquisition of high-frequency data from multiple sensors refers to the process of time-aligning and parallel reading of high-sampling-frequency data generated by multiple sensing elements distributed within the same system. This is primarily used to aggregate sensor data streams from different physical locations with consistent time sequences, providing them to a processing center for multi-source data joint analysis. Existing technologies such as external hardware trigger circuits, network clock synchronization protocols, or multi-channel synchronous analog-to-digital converter chips are typically employed to perform the acquisition of multi-source time-aligned data.

[0003] In traditional multi-sensor high-frequency data synchronous acquisition processes, although existing methods such as external hardware trigger circuits, network clock synchronization protocols, or multi-channel synchronous analog-to-digital converter chips can be used to acquire multi-source time-aligned data, in complex system environments with numerous distributed nodes and the need to maintain high-frequency sampling, there are problems such as complex hardware connections, high cost of multi-channel devices, and time alignment accuracy limited by network communication delays. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of existing technologies and propose a method for synchronous acquisition of high-frequency data from multiple sensors.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: a method for synchronous acquisition of high-frequency data from multiple sensors, comprising the following steps: S1: Acquire an analog voltage signal and a global phase reference signal, process the analog voltage signal using voltage-controlled oscillation parameters to obtain a continuous oscillation signal, construct an additional voltage pulse based on the global phase reference signal and a preset voltage conversion ratio, superimpose the additional voltage pulse onto the polarity alternation position of the continuous oscillation signal to generate a phase marker signal, and merge multiple phase marker signals to generate a single composite electrical signal; S2: Obtain the global sampling frequency value, sample the single composite electrical signal based on the global sampling frequency value to extract the voltage digital amplitude, and splice them in chronological order to generate a mixed digital sequence; S3: Process the hybrid digital sequence according to the digital bandpass filter parameters to construct an independent frequency band digital sequence, extract the positive and negative alternation time interval of the independent frequency band digital sequence, and analyze the instantaneous frequency value by combining the frequency conversion constant. Analyze the offset of the instantaneous frequency value relative to the center frequency value of the frequency band to obtain the environmental change value sequence. S4: Compare the amplitude characteristics of the independent frequency band digital sequence with the pulse judgment threshold to extract the phase extraction pulse, restore the original phase mark value according to the phase extraction pulse and the phase conversion ratio parameter, and insert the original phase mark value into the starting data address of the environmental change value sequence to generate a sensor data mixture packet. S5: Based on the zero-phase reference value, extract the original phase marker value from the sensor data mixture package, perform a reference comparison to obtain the timing phase deviation, combine it with the phase-time conversion constant to obtain the time offset, and translate and align the sensor data mixture package with the time offset to output a multi-sensor synchronous sensing data set.

[0006] As a further aspect of the present invention, during the extraction of phase extraction pulses, if the amplitude feature is greater than the pulse judgment threshold, it is extracted as a phase extraction pulse; if the amplitude feature is less than or equal to the pulse judgment threshold, it is filtered out.

[0007] As a further aspect of the present invention, the polarity alternation position refers to the instant at which the voltage polarity of the continuous oscillation signal changes.

[0008] As a further aspect of the present invention, step S1 specifically comprises: S111: Obtain the system frequency band allocation protocol and analog voltage signal, collect the channel dynamic range constraint standard, analyze the frequency mapping relationship of the system frequency band allocation protocol to obtain the voltage-controlled oscillation parameters, extract the maximum voltage swing limit of the dynamic range constraint standard to set the preset voltage conversion ratio, and adjust the analog voltage signal to continuously oscillate and alternate based on the voltage-controlled oscillation parameters to generate a continuous oscillation signal; S112: Based on the continuous oscillation signal and the preset voltage conversion ratio, monitor the global phase reference signal, extract the voltage polarity alternation time point of the continuous oscillation signal to obtain the polarity alternation position, extract the phase offset for the global phase reference signal, and perform mapping conversion on the phase offset in combination with the preset voltage conversion ratio to obtain the additional voltage pulse; S113: The additional voltage pulse is shifted to the polarity alternation position at the corresponding time to perform amplitude superposition, thereby obtaining a signal carrying a phase mark. The internal spectral energy characteristics of the multiple signals carrying phase marks are extracted. Based on the spectral energy characteristics, the multiple signals carrying phase marks are subjected to frequency division multiplexing and merging processing to generate a single composite electrical signal.

[0009] As a further aspect of the present invention, step S2 specifically includes: S211: Extract the internal spectral energy distribution state of the single composite electrical signal, identify the highest frequency component index, perform frequency multiplication operation on the highest frequency component index to obtain the discretized rate value, and perform boundary rounding processing on the discretized rate value to obtain the global sampling frequency value. S212: Configure the sampling clock beat based on the global sampling frequency value, and sample the single composite electrical signal at equal intervals according to the clock beat to obtain a discrete voltage point set. Read the analog level index of each point in the discrete voltage point set, perform quantization encoding mapping on the analog level index, and extract the digital voltage amplitude. S213: Extract the time tag index associated with the multiple voltage digital amplitudes, sort the multiple voltage digital amplitudes according to the time tag to obtain a time sequence data set, and perform first-end connection combination on adjacent data elements in the time sequence data set to establish a hybrid digital sequence.

[0010] As a further aspect of the present invention, step S3 specifically comprises: S311: Based on the hybrid digital sequence, the frequency range is intercepted according to the channel bandwidth boundary delineation rule to obtain the digital bandpass filter parameters and the center frequency value of the frequency band. Based on the digital bandpass filter parameters, a weighted summation and convolution operation is performed on the frequency components of each order inside the hybrid digital sequence to filter the in-band data and extract the independent frequency band digital sequence. S312: Obtain the factory parameters of the oscillator, extract the voltage response slope attribute within the factory parameters to generate a frequency conversion constant, read the timestamps associated with adjacent positive and negative alternation points in the independent frequency band digital sequence, perform subtraction to obtain the positive and negative alternation time difference, and perform reciprocal product conversion on the positive and negative alternation time difference using the frequency conversion constant to obtain the instantaneous frequency value. S313: Extract multiple consecutive nodes and associate them with the instantaneous frequency values ​​to establish a frequency evolution trajectory set. Perform subtraction operations between each element in the frequency evolution trajectory set and the center frequency value of the frequency band to construct a frequency offset amplitude set. Arrange the values ​​according to the order of time nodes to generate an environmental change numerical sequence.

[0011] As a further aspect of the present invention, step S4 specifically comprises: S411: Obtain channel noise floor statistics, extract background noise peak superposition tolerance index to establish pulse judgment threshold, extract local extrema based on the independent frequency band digital sequence to obtain amplitude features, perform numerical comparison operation between the amplitude features and the pulse judgment threshold, filter out associated amplitude features that exceed the pulse judgment threshold, and generate phase extraction pulse; S412: Perform reverse calculation on the preset voltage conversion ratio to obtain the phase conversion ratio parameter, extract the amplitude variable inside the phase extraction pulse, and perform scaling multiplication calculation on the amplitude variable in combination with the phase conversion ratio parameter to recover the original phase mark value; S413: Traverse the storage space distribution within the environmental change numerical sequence, locate the memory offset position of the first data element in the environmental change numerical sequence to obtain the starting data address, write the original phase marker value to the starting data address according to the data encapsulation protocol, and perform header appending and assembly operations to generate a sensor data hybrid packet.

[0012] As a further aspect of the present invention, step S5 specifically comprises: S511: Obtain the synchronization clock initialization configuration and system master clock frequency specification, extract the start timestamp anchor variable inside the synchronization clock initialization configuration, assign a value to set the zero phase reference value, parse the oscillation period attribute inside the system master clock frequency specification to obtain the single beat duration variable, perform normalization proportional conversion on the single beat duration variable, and obtain the phase time conversion constant. S512: Based on the sensor data mixture packet, the zero-phase reference value and the phase-time conversion constant, read the header data of the sensor data mixture packet to extract the original phase marker value, perform a subtraction operation between the original phase marker value and the zero-phase reference value to obtain the timing phase difference value, and combine the phase-time conversion constant to extract the time offset from the timing phase difference value. S513: Obtain the global timeline template, take the origin of the global timeline template as the reference, and perform time-series alignment processing on the timestamp index in the multi-channel sensor data mixing package by combining the corresponding time offset, and integrate and output the multi-sensor synchronous sensing data set.

[0013] A multi-sensor high-frequency data synchronous acquisition system includes: The analog signal composite module acquires an analog voltage signal and a global phase reference signal, processes the analog voltage signal using voltage-controlled oscillation parameters to obtain a continuous oscillation signal, constructs an additional voltage pulse based on the global phase reference signal and a preset voltage conversion ratio, superimposes the additional voltage pulse onto the polarity alternation position of the continuous oscillation signal to generate a phase marker signal, and merges multiple phase marker signals to generate a single composite electrical signal. The centralized slicing sampling module obtains the global sampling frequency value, samples the single composite electrical signal based on the global sampling frequency value to extract the voltage digital amplitude, and splices them in chronological order to generate a mixed digital sequence. The frequency band separation and analysis module processes the mixed digital sequence according to the digital bandpass filter parameters to construct an independent frequency band digital sequence, extracts the positive and negative alternation time interval of the independent frequency band digital sequence, analyzes the instantaneous frequency value in combination with the frequency conversion constant, analyzes the offset of the instantaneous frequency value relative to the center frequency value of the frequency band, and obtains the environmental change value sequence. The phase analysis and packet assembly module compares the amplitude characteristics of the independent frequency band digital sequence with the pulse judgment threshold to extract the phase extraction pulse, restores the original phase mark value based on the phase extraction pulse and the phase conversion ratio parameter, and inserts the original phase mark value into the starting data address of the environmental change value sequence to generate a sensor data hybrid packet. The data timing alignment module extracts the original phase marker values ​​from the sensor data mixture based on the zero-phase reference value, performs a reference comparison to obtain the timing phase deviation, and maps the time offset by the phase-time conversion constant. The time offset is then used to shift and align the sensor data mixture to output a multi-sensor synchronous sensing data set.

[0014] Compared with the prior art, the advantages and positive effects of the present invention are as follows: In this invention, by converting the analog signals of the sensors into oscillating signals and superimposing them with global phase reference pulses to merge them into a single composite electrical signal, performing frequency band separation and instantaneous frequency analysis of single-channel data based on global sampling and digital bandpass filtering, and extracting phase markers for time offset translation and alignment, the invention achieves mixed acquisition and accurate digital reconstruction of multiple high-frequency sensor data in a single physical channel. This reduces the hardware wiring complexity of multi-sensor systems and eliminates the dependence on expensive multi-channel synchronization chips and complex external triggering circuits. Thus, while ensuring strict time synchronization of multi-source high-frequency signals, it improves the reliability and transmission efficiency of joint analysis of multi-sensor data. Attached Figure Description

[0015] Figure 1 This is a flowchart of the main steps of the present invention; Figure 2 This is a detailed flowchart of step S1 of the present invention; Figure 3 This is a flowchart of step S2 of the present invention; Figure 4 This is a detailed flowchart of step S3 of the present invention; Figure 5 This is a flowchart of step S4 of the present invention; Figure 6 This is a flowchart of step S5 of the present invention. Detailed Implementation

[0016] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0017] Please see Figure 1 A method for synchronous acquisition of high-frequency data from multiple sensors includes the following steps: S1: Perform synchronous acquisition of high-frequency data from multiple sensors and concurrent monitoring of front-end physical signals; acquire analog voltage signals and global phase reference signals; process analog voltage signals using voltage-controlled oscillation parameters to obtain continuous oscillation signals; construct additional voltage pulses based on global phase reference signals and preset voltage conversion ratios; superimpose additional voltage pulses onto the polarity alternation position of continuous oscillation signals to generate phase-marked signals; and merge multiple phase-marked signals to generate a single composite electrical signal. Among them, the voltage-controlled oscillator parameters are obtained by analyzing the frequency mapping relationship of each channel in the system frequency band allocation protocol; the maximum voltage swing limit in the channel dynamic range constraint standard is obtained by analyzing the preset voltage conversion ratio. S2: Perform multi-sensor high-frequency data synchronous acquisition and electrical signal aggregation and transmission; obtain the global sampling frequency value through the Nyquist sampling theorem, extract the voltage digital amplitude of a single composite electrical signal based on the global sampling frequency value, and splice them in chronological order to generate a mixed digital sequence; S3: Perform multi-sensor high-frequency data synchronous acquisition backend digital signal frequency band separation and extraction; process the mixed digital sequence according to the digital bandpass filter parameters to construct independent frequency band digital sequences, extract the positive and negative alternation time intervals of the independent frequency band digital sequences, combine the frequency conversion constant to analyze and obtain the instantaneous frequency value, analyze the offset of the instantaneous frequency value relative to the center frequency value of the frequency band, and obtain the environmental change value sequence. Among them, the digital bandpass filter parameters and the center frequency of the frequency band are obtained by querying the channel bandwidth boundary delineation rules in the system frequency band allocation protocol and extracting the corresponding filter interval; the frequency conversion constant is obtained by reading the voltage-frequency response slope of the voltage-controlled oscillator factory specifications. S4: Perform multi-sensor high-frequency data synchronous acquisition and phase data parsing; compare the amplitude characteristics of the independent frequency band digital sequence with the pulse judgment threshold to extract the phase extraction pulse; restore the original phase mark value based on the phase extraction pulse and the phase conversion ratio parameter; insert the original phase mark value into the starting data address of the environmental change value sequence; and combine to generate a sensor data hybrid package. Among them, the pulse judgment threshold is obtained by extracting the background noise peak from the channel noise floor statistical evaluation record and adding a threshold margin; the phase conversion ratio parameter is obtained by inverting the voltage conversion inverse mapping relationship of the preset voltage conversion ratio. If the amplitude feature is greater than the pulse judgment threshold, it is extracted as a phase extraction pulse; if the amplitude feature is less than or equal to the pulse judgment threshold, it is filtered out. S5: Perform multi-sensor high-frequency data synchronous acquisition and time-series coordinate reconstruction; based on the zero-phase reference value, extract the original phase marker value from the sensor data mixture package, compare it with the reference to obtain the time-series phase deviation, combine it with the phase-time conversion constant to obtain the time offset, translate and align the sensor data mixture package with the time offset, and output the multi-sensor synchronous sensing data set. The zero-phase reference value is obtained by extracting the starting timestamp anchor point from the synchronous clock initialization configuration; the phase-time conversion constant is obtained by analyzing the clock cycle duration of the system master clock frequency specification.

[0018] Please see Figure 2 Step S1 is as follows: S111: Acquire the system frequency band allocation protocol and analog voltage signal, collect the channel dynamic range constraint standard, analyze the frequency mapping relationship of the system frequency band allocation protocol to obtain the voltage-controlled oscillation parameters, extract the maximum voltage swing limit of the dynamic range constraint standard, set the preset voltage conversion ratio, and adjust the analog voltage signal to continuously oscillate and alternate based on the voltage-controlled oscillation parameters to generate a continuous oscillation signal; In a multi-sensor high-frequency data synchronous acquisition architecture, multiple intelligent sensors configured at the front end receive the system's frequency band allocation protocol via a general-purpose data bus, synchronously read the level fluctuation data of the RF interface to acquire analog voltage signals, and extract the channel dynamic range constraint standard by reading the data payload fields within the protocol byte by byte. Based on the preset configuration, the correspondence between frequency values ​​and level values ​​within the system's frequency band allocation protocol is analyzed to obtain the frequency mapping relationship. Based on this, the tuning slope index and bias index are extracted to obtain the voltage-controlled oscillation parameters. The constraint standard is read to extract the controlled level swing threshold to obtain the maximum voltage swing limit. The calculation logic for the preset voltage conversion ratio is set as follows: extract the maximum voltage swing limit and the rated output peak value, perform a ratio division operation between the two to obtain the voltage drop factor, perform a multiplication operation between the voltage drop factor and the static gain constant to obtain the preliminary ratio, and finally perform an addition operation with the temperature compensation coefficient to obtain the preset voltage conversion ratio. For example, when the maximum voltage swing is limited to 3000 mV and the rated output peak is 5000 mV, the ratio calculation yields a step-down factor of 0.6, the static gain constant is set to 1.1, multiplication yields an initial ratio of 0.66, the temperature compensation coefficient is set to 0.04, and summation yields a preset voltage conversion ratio of 0.7. Each intelligent sensor efficiently completes this parameter configuration using its built-in logic operation unit. The instantaneous level values ​​of the analog voltage signal are multiplied by the ratio 0.7 to attenuate the amplitude. The attenuated voltage is linearly transformed using the tuning slope of the parameter to obtain the frequency offset. Based on this offset, the circuit is adjusted to generate an alternating continuous oscillation signal.

[0019] S112: Based on the continuous oscillation signal and the preset voltage conversion ratio, monitor the global phase reference signal, extract the voltage polarity alternation time point of the continuous oscillation signal to obtain the polarity alternation position, extract the phase offset for the global phase reference signal, and perform mapping conversion on the phase offset in combination with the preset voltage conversion ratio to obtain the additional voltage pulse; Based on the generated continuous oscillation signal and the calculated preset voltage conversion ratio of 0.7, the internal synchronous listening port is activated to monitor the global phase reference signal. Using a zero-crossing detection algorithm, the signal is advanced along the time axis to extract the polarity alternation position by identifying the zero-level penetration points where the instantaneous voltage value within the continuous oscillation signal transitions from positive to negative or vice versa. To meet the stringent requirements for phase consistency in multi-sensor high-frequency data synchronous acquisition, each intelligent sensor extracts the ideal zero-crossing point of the global phase reference signal. The time stamp of the polarity alternation position is compared with the time stamp of the ideal zero-crossing point to calculate the phase offset. This phase offset is then mapped and converted using the preset voltage conversion ratio of 0.7. The conversion logic involves extracting the current phase offset and the fundamental pulse amplitude constant, multiplying the phase offset by the preset voltage conversion ratio of 0.7 to obtain the equivalent offset time, and then multiplying the equivalent offset time by the fundamental pulse amplitude constant to obtain the initial amplitude of the additional voltage pulse. For example, if the phase offset is extracted to be 2.0 microseconds, multiply it by the ratio 0.7 to obtain an equivalent offset time of 1.4 microseconds. If the base pulse amplitude constant is set to 50 millivolts per microsecond, multiply 1.4 microseconds by 50 millivolts per microsecond to obtain an initial amplitude of 70 millivolts for the additional voltage pulse.

[0020] S113: The additional voltage pulse is shifted to the polarity alternation position at the corresponding moment to perform amplitude superposition, resulting in a signal carrying phase mark. The internal spectral energy characteristics of the multiple signals carrying phase mark are extracted, and frequency division multiplexing and merging processing is performed on the multiple signals carrying phase mark based on the spectral energy characteristics to generate a single composite electrical signal. An additional voltage pulse with an amplitude of 70 millivolts is captured and shifted in the time dimension to the corresponding polarity alternation position. At this position, the amplitude of the original continuous oscillation signal and the shifted additional voltage pulse are superimposed. Specifically, the current amplitude of the continuous oscillation signal is summed with the amplitude of the additional voltage pulse (70 millivolts) to obtain a signal carrying a phase marker. For multiple signals carrying phase markers, a discrete Fourier algorithm is introduced to extract their internal spectral energy characteristics. This extraction process involves converting multiple signals into frequency domain sequences, reading the squared amplitude values ​​of each frequency point to construct a distribution vector, and extracting the peak energy of the main lobe and the average energy of the side lobes as spectral energy characteristics. Based on the spectral energy characteristics, frequency division multiplexing and merging processing is performed on the multiple signals carrying phase markers. The merging logic involves extracting the peak energy of the main lobe of each signal and the global energy reference constant, performing a ratio division operation between the peak energy of each main lobe and the global energy reference constant to obtain a dynamically allocated weight, and using the dynamically allocated weight to sum the signals to generate a single composite electrical signal. This signal will serve as the key carrier for the convergence of multiple source features within the intelligent sensor. For example, the peak energy of the main lobe of the first signal is 120 microwatts, and the peak energy of the main lobe of the second signal is 80 microwatts. With a global reference constant set to 200 microwatts, the weights are calculated to be 0.6 for the first signal and 0.4 for the second signal. The first and second signals are then weighted and summed using these weights to generate a single composite electrical signal. This optimizes the frequency band utilization during synchronous high-frequency data acquisition from multiple sensors.

[0021] Please see Figure 3 Step S2 is as follows: S211: Extract the internal spectral energy distribution state of a single composite electrical signal, identify the highest frequency component index, perform frequency multiplication operation on the highest frequency component index to obtain the discretized rate value, perform boundary rounding processing on the discretized rate value to obtain the global sampling frequency value. For the generated single composite electrical signal, a short-time spectral observation window with a windowing function is used to scan and extract its internal spectral energy distribution. After obtaining the complete frequency domain power spectral density, a peak search algorithm is used to traverse the entire frequency band array, identify the maximum point with the highest amplitude on the power spectral density curve, and record the frequency coordinates corresponding to this point to obtain the highest frequency component index. To meet the throughput requirements of massive parallel data during the synchronous acquisition of high-frequency data from multiple sensors, a frequency multiplication operation needs to be performed on the highest frequency component index to obtain the discretized rate value. The operation logic is to extract the highest frequency component index and the Nyquist frequency harmonic constant, directly multiply the highest frequency component index and the Nyquist frequency harmonic constant to obtain the reference rate, and then multiply the reference rate with the hardware reserved margin coefficient to derive the discretized rate value. For example, if the highest frequency component is identified as 20 MHz, and the Nyquist harmonic constant is strictly extracted as 2, multiplying these two values ​​yields a base rate of 40 MHz. Setting a hardware margin coefficient of 1.2, multiplying 40 MHz by 1.2 yields a discretized rate of 48 MHz. Boundary rounding is then applied to this 48 MHz discretized rate. Since the actual hardware crystal oscillator frequency is limited by a standard step value, an upward rounding algorithm is used to match 48 MHz to the closest standard clock level, resulting in a global sampling frequency of 50 MHz. This ensures that each front-end smart sensor can capture transient characteristics.

[0022] S212: Configure the sampling clock based on the global sampling frequency value, and obtain a discrete voltage point set by sampling a single composite electrical signal at equal intervals according to the clock clock. Read the analog level index of each point in the discrete voltage point set, perform quantization encoding mapping on the analog level index, and extract the digital voltage amplitude. Based on a predetermined global sampling frequency of 50 MHz, the high-frequency analog-to-digital converter within the intelligent sensor works in concert. Under the unified scheduling of multi-sensor high-frequency data synchronous acquisition tasks, the system is configured with a high-frequency sampling clock, establishing a hardware cycle that triggers once every 20 nanoseconds. According to the clock cycle, a single composite electrical signal is sampled at equal intervals to obtain a discrete voltage point set. The analog level index of each point within the discrete voltage point set is read sequentially, and quantization encoding mapping is performed to extract the digital voltage amplitude. The quantization encoding operation logic involves extracting the analog level index of the current sampling point and the system quantization step size constant. A ratio division operation is performed between the analog level index and the quantization step size constant to obtain a floating-point digital order. Finally, the floating-point digital order is truncated and rounded to obtain the corresponding digital voltage amplitude. For example, if the analog level index is read as 1235 mV and the quantization step size constant is configured as 5 mV, the ratio of 1235 mV to 5 mV yields a floating-point order of 247.0, which is then truncated and rounded to determine the digital voltage amplitude as 247. Through this process, the intelligent sensor achieves robust discretization of high-speed signals.

[0023] Table 1 Quantization Record of Discrete Sampling Points Sampling sequence number Analog Level Specifications Quantization step size constant Floating-point number exponent Digital voltage amplitude 1 1235 millivolts 5 millivolts 247.0 247 2 1241 millivolts 5 millivolts 248.2 248 3 1258 millivolts 5 millivolts 251.6 252 As shown in Table 1, by strictly performing ratio and rounding operations on each discrete sampling point, the system completely maps the analog waveform into a discrete digital sequence.

[0024] S213: Extract the time tag index associated with the digital amplitude of multiple voltage channels, sort the digital amplitude of multiple voltage channels according to the time tag to obtain a time sequence data set, and perform first-end connection and combination on adjacent data elements in the time sequence data set to establish a mixed digital sequence. Extracting the associated time stamp index of multiple voltage digital amplitudes from the system time counter built into the intelligent sensor node is a crucial prerequisite for accurately controlling the absolute time coordinates of each signal node and achieving synchronous acquisition of high-frequency data from multiple sensors. This time stamp index consists of an absolute timestamp and a microsecond offset, precisely marking the generation time of each voltage digital amplitude. Based on the time stamps corresponding to each data point, the multiple voltage digital amplitudes are sorted chronologically using a bubble sort algorithm, comparing the timestamps one by one to obtain the time-series data set. The internal storage area is traversed, and adjacent data elements are joined to create a hybrid digital sequence. The joining logic involves extracting the voltage digital amplitudes of the previous and subsequent sampling points, performing a left shift multiplication operation on the previous voltage digital amplitude to free up low-order bits, and then performing a bitwise logical summation operation with the subsequent voltage digital amplitude to complete the concatenation and fusion, forming a 2-word hybrid digital sequence. For example, under 8-bit environmental control, the amplitude of the preceding voltage digit is extracted to be 12, and the amplitude of the next adjacent voltage digit is 5. A left shift of the preceding value 12 by 8 bits is equivalent to multiplying by 256 to obtain the extended value 3072. Adding 3072 to the following value 5 yields the mixed digital sequence value 3077. This compact merging mechanism reduces the communication load on the local bus.

[0025] Please see Figure 4 Step S3 is as follows: S311: Based on the mixed digital sequence, the frequency range is intercepted according to the channel bandwidth boundary delineation rules to obtain the digital bandpass filter parameters and the center frequency value of the frequency band. Based on the digital bandpass filter parameters, a weighted summation and convolution operation is performed on the frequency components of each order inside the mixed digital sequence to filter the in-band data and extract the independent frequency band digital sequence. Based on the continuous data stream composed of a hybrid digital sequence value of 3077 generated by the terminal intelligent sensor during the multi-sensor high-frequency data synchronous acquisition and collaborative process, and according to the preset channel bandwidth boundary delineation rules, a specific frequency range is extracted to obtain the digital bandpass filter parameters and the center frequency value of the frequency band. A finite impulse response filtering model is configured based on the digital bandpass filter parameters. Weighted summation convolution operations are performed on each order frequency component within the hybrid digital sequence to filter in-band data and extract independent frequency band digital sequences. The execution process of this model is as follows: the input layer receives the hybrid digital sequence, the data enters the hidden layer of the fully connected structure via a delay linear array, each node in the hidden layer uses the set bandpass filter parameters as convolution kernel coefficients, and directly performs linear weighted processing of the data without an activation function. Finally, the output layer summarizes and outputs the results. The weighted summation logic involves extracting the continuous sampled values ​​in the hybrid digital sequence and the corresponding bandpass filter parameter weight constants, multiplying the current value and the previous value with the first and second weight constants respectively, and finally summing all the product results to obtain the output value of the independent frequency band digital sequence. For example, extracting consecutive sample values ​​of 3077 and 3080 corresponds to a first weight constant of 0.4 and a second weight constant of 0.6. Multiplying 3077 and 0.4 yields 1230.8, multiplying 3080 and 0.6 yields 1848, and summing 1230.8 and 1848 yields an output value of 3078.8.

[0026] S312: Obtain the factory parameters of the oscillator, extract the voltage response slope attribute within the factory parameters to generate a frequency conversion constant, read the timestamps associated with adjacent positive and negative alternation points in the independent frequency band digital sequence, perform subtraction to obtain the positive and negative alternation time difference, and perform reciprocal product conversion on the positive and negative alternation time difference using the frequency conversion constant to obtain the instantaneous frequency value. The system calls the hardware management interface within the intelligent sensor microprocessor unit to obtain the factory parameters of the oscillator. It parses the read parameter file, extracts the internally calibrated voltage response slope attribute, and performs a numerical conversion on this slope attribute to generate a frequency conversion constant. It then reads the filtered independent frequency band digital sequence from the memory buffer, locates adjacent positive and negative alternating points and obtains their associated timestamps, and performs a subtraction operation on the timestamps of adjacent alternating points to obtain the positive and negative alternating time difference. Combining this with the frequency conversion constant, it performs a reciprocal product of the positive and negative alternating time difference to obtain the instantaneous frequency value. Specifically, the calculation logic is as follows: extract the current positive and negative alternating time difference and the frequency conversion constant; perform a ratio division operation between the constant 1 and the positive and negative alternating time difference to obtain the preliminary alternating frequency; and perform continuous multiplication of the preliminary alternating frequency with the frequency conversion constant and the phase compensation coefficient to obtain the instantaneous frequency value. For example, if the extracted adjacent positive and negative alternating time difference is 0.02 seconds, performing a ratio operation with 1 yields a preliminary alternating frequency of 50 Hz. The system extracts a frequency conversion constant of 2.5 and a phase compensation coefficient of 0.96. Multiplying the initial alternating frequency of 50 Hz by the conversion constant 2.5 yields 125. Finally, multiplying 125 by the phase compensation coefficient 0.96 gives an instantaneous frequency of 120 Hz. Based on this underlying conversion, the system's internal nodes maintain excellent self-calibration capabilities in a multi-sensor high-frequency data synchronous acquisition network.

[0027] S313: Extract the instantaneous frequency values ​​associated with multiple consecutive nodes to establish a frequency evolution trajectory set. Perform subtraction operations between each element in the frequency evolution trajectory set and the center frequency value of the frequency band to construct a frequency offset amplitude set. Arrange the values ​​according to the order of time nodes to generate a sequence of environmental change values. Each intelligent sensor extracts instantaneous frequency values ​​(e.g., 120 Hz) associated at multiple consecutive nodes within the monitoring period. These values ​​are arranged and combined according to the order of acquisition to establish a complete set of frequency evolution trajectories. The center frequency value of the frequency band is extracted, and each time-series element within the frequency evolution trajectory set is subtracted one by one from the center frequency value to construct a set of frequency offset amplitudes. The data is then organized according to the chronological order of the time nodes to generate a sequence of environmental change values. This allows for all-weather monitoring of subtle disturbances and fluctuations faced by each physical node under the environment of simultaneous high-frequency data acquisition from multiple sensors. The subtraction operation logic involves extracting the instantaneous frequency value of the current node from the center frequency value of the frequency band, directly calculating the difference between the instantaneous frequency value and the center frequency value to obtain the absolute frequency offset, and then multiplying the absolute frequency offset by the environmental sensitivity coefficient to obtain the environmental change value. For example, if the instantaneous frequency value is extracted as 120 Hz and the preset center frequency value of the frequency band is 100 Hz, the difference between the two is calculated to obtain an absolute frequency deviation of 20 Hz. If the system environment sensitivity coefficient is set to 1.5, the 20 Hz value is multiplied by 1.5 to obtain an environmental change value of 30.

[0028] Table 2 Instantaneous Frequency Offset Quantization Evolution Table Time Node Instantaneous frequency value Center frequency value Absolute frequency offset Environmental change values Phase 1 120 Hz 100 Hz 20 Hz 30 Phase 2 125 Hz 100 Hz 25 Hz 37.5 Phase 3 118 Hz 100 Hz 18 Hz 27 As shown in Table 2, the frequency domain change was precisely quantified by performing difference and multiplication operations on the instantaneous frequency values ​​at each time point.

[0029] Please see Figure 5 Step S4 is as follows: S411: Obtain channel noise floor statistics, extract background noise peak superposition tolerance index to establish pulse judgment threshold, extract local extrema based on independent frequency band digital sequence to obtain amplitude features, perform numerical comparison operation between amplitude features and pulse judgment threshold, filter related amplitude features that exceed pulse judgment threshold, and generate phase extraction pulse; To mitigate potential background channel crosstalk during simultaneous high-frequency data acquisition by numerous devices, each smart sensor obtains current channel noise floor statistics by calling the underlying listening interface. The background noise peak value and a pre-set superposition tolerance index are extracted from the records to establish a pulse judgment threshold. Specifically, the background noise peak value and the superposition tolerance index are summed to obtain a baseline threshold. This baseline threshold is then multiplied by a fluctuation redundancy multiplier to arrive at the final pulse judgment threshold. For example, if the extracted background noise peak value is 15 dB and the superposition tolerance index is 5 dB, the sum yields a baseline threshold of 20 dB. With a fluctuation redundancy multiplier of 1.2, the product yields a pulse judgment threshold of 24 dB. Subsequently, based on the independent frequency band digital sequence, a sliding window first-order difference algorithm is used to extract its local extrema as amplitude features. The extracted amplitude features are compared with the calculated 24 dB pulse judgment threshold. If the amplitude feature is greater than the pulse judgment threshold, the corresponding feature data is directly retained, and the associated amplitude features are selected to generate a phase extraction pulse. For example, when a certain amplitude feature is extracted as 28 dB, since 28 dB is greater than 24 dB, the feature is determined to be an effective abrupt change and converted into a phase extraction pulse.

[0030] S412: Read the mapping transformation equation, substitute the preset voltage conversion ratio into the mapping transformation equation to perform the inverse solution operation to obtain the phase conversion ratio parameter, extract the amplitude variable inside the phase extraction pulse, and perform scaling multiplication calculation on the amplitude variable in combination with the phase conversion ratio parameter to recover the original phase mark value. The mapping transformation equation is read from the parameter storage unit. The preset voltage conversion ratio of 0.7 obtained in the previous steps is substituted into the mapping transformation equation to perform a reverse solution operation, deriving the phase conversion ratio parameter. The reverse solution logic involves extracting a fixed normalized constant and the preset voltage conversion ratio, performing a ratio division operation between the fixed normalized constant and the preset voltage conversion ratio to obtain the basic inverter coefficient, and then performing a subtraction operation between the basic inverter coefficient and the hardware phase shift compensation constant to obtain the phase conversion ratio parameter. For example, if the extracted fixed normalized constant is 1.4, substituting it into the preset voltage conversion ratio of 0.7, the ratio operation yields a basic inverter coefficient of 2.0. The calibrated hardware phase shift compensation constant is read as 0.1, and the subtraction operation between 2.0 and 0.1 yields a phase conversion ratio parameter of 1.9. Subsequently, the specific amplitude variables within the phase extraction pulse are extracted, and the amplitude variables are multiplied using the phase conversion ratio parameter 1.9 to numerically recover the original phase marker value. For example, if the amplitude variable within the phase extraction pulse is 45 degrees, multiplying it by the phase conversion ratio parameter 1.9 yields a magnified and restored original phase marker value of 85.5 degrees. This reverse recovery logic ensures that each smart sensor possesses robust phase adaptive tracking capabilities during multi-sensor high-frequency data synchronous acquisition.

[0031] S413: Traverse the storage space distribution within the environmental change numerical sequence, locate the memory offset position of the first data element in the environmental change numerical sequence to obtain the starting data address, write the original phase marker value to the starting data address according to the data encapsulation protocol, and perform header appending and assembly operations to generate a sensor data hybrid packet. The system memory controller traverses the storage space distribution of the environmental change numerical sequence in main memory, locates the memory offset of the first data element of the environmental change numerical sequence according to the paging mapping table, and obtains the starting data address of the continuous data block. This mechanism greatly ensures seamless data injection for different edge nodes under the overall architecture of multi-sensor high-frequency data synchronous acquisition. Each intelligent sensor in the communication process, according to the IoT data encapsulation protocol, writes the calculated 85.5-degree and other original phase marker values ​​to the starting data address via the bus, and performs a header appending and assembly operation at the end of the data packet to generate a mixed sensor data packet. The appending and assembly operation logic involves extracting the byte length of the original phase marker values ​​and the total byte length of the environmental change numerical sequence, performing an addition operation on these two byte lengths to obtain the basic length of the data packet, and then performing an addition operation on the basic length of the data packet and the protocol check bit fixed-length constant to allocate the total packet memory space. For example, the extracted original phase marker value occupies a length of 4 bytes, the environmental change value sequence occupies a length of 128 bytes, the sum of the two gives a base length of 132 bytes, the protocol configuration check bit fixed length constant is 8 bytes, the sum of 132 and 8 is performed, and finally the system allocates a total packet memory space of 140 bytes to store the sensor data mixed packet.

[0032] Please see Figure 6 The S5 steps are as follows: S511: Obtain the synchronization clock initialization configuration and system master clock frequency specification, extract the start timestamp anchor variable inside the synchronization clock initialization configuration, assign a value to set the zero phase reference value, parse the oscillation period attribute inside the system master clock frequency specification to obtain the single beat duration variable, perform normalization proportional conversion on the single beat duration variable, and obtain the phase time conversion constant. As a prerequisite for the orderly advancement of multi-sensor high-frequency data synchronous acquisition tasks, the cluster management platform obtains the synchronization clock initialization configuration file and system master clock frequency specification parameters through the system management bus with each underlying intelligent sensor group. It reads the start timestamp anchor variable within the initialization configuration file and assigns this variable to the reference clock register, setting it as the zero-phase reference value. The oscillation period attribute within the system master clock frequency specification is analyzed to obtain the 1-cycle duration variable. A normalized proportional conversion is performed on this 1-cycle duration variable to derive the phase-time conversion constant. The conversion logic involves extracting the 1-cycle duration variable and the reference phase circumference constant, performing a ratio division operation between the cycle duration variable and the reference phase circumference constant to obtain a preliminary conversion base, and then performing an addition operation between the preliminary conversion base and the clock network propagation delay coefficient to obtain the phase-time conversion constant. For example, the duration of one beat is extracted as 360 nanoseconds, the preset reference phase circumference constant is 360 degrees, the ratio of the two is calculated to obtain the initial conversion base of 1 nanosecond per degree, the network propagation delay coefficient is obtained as 0.2 nanoseconds per degree, and the summation of 1 and 0.2 is performed to obtain the final phase time conversion constant of 1.2 nanoseconds per degree.

[0033] Table 3 Clock Conversion Parameter Configuration Table Beat duration variable Phase circumferential angle constant Preliminary conversion base Delay coefficient Transformation constant 360 nanoseconds 360 degrees 1 nanosecond per degree 0.2 nanoseconds per degree 1.2 nanoseconds per degree 360 nanoseconds 360 degrees 1 nanosecond per degree 0.5 nanoseconds per degree 1.5 nanoseconds per degree As shown in Table 3, a high-precision conversion ratio is generated by summing and compensating multiple sets of delay coefficients.

[0034] S512: Based on the sensor data mixture packet, the zero-phase reference value and the phase-time conversion constant, read the header data of the sensor data mixture packet to extract the original phase marker value, perform a subtraction operation between the original phase marker value and the zero-phase reference value to obtain the timing phase difference, and combine the phase-time conversion constant to extract the time offset from the timing phase difference. The receiving node in the central control hub initiates the unpacking and restoration process based on the assembled sensor data hybrid packet, the set zero-phase reference value, and the calculated 1.2 nanosecond phase-time conversion constant per degree. This parsing step fundamentally reduces the reference error caused by the drift of the local clock of the remote intelligent sensor during the synchronous acquisition of high-frequency data from multiple sensors. The sensor data hybrid packet is parsed to read the header data block and extract the original phase marker value, such as 85.5 degrees. The extracted original phase marker value is subtracted from the zero-phase reference value to obtain the timing phase difference relative to the initial origin. This timing phase difference is then multiplied using the 1.2 nanosecond phase-time conversion constant per degree to extract the time offset. The derivation logic is as follows: extract the original phase marker value and the zero-phase reference value obtained from the unpacking; subtract the zero-phase reference value from the original phase marker value to obtain the absolute phase deviation; finally, multiply the absolute phase deviation by the phase-time conversion constant to obtain the time offset. For example, if the original phase marker value is extracted as 85.5 degrees and the zero-phase reference value is set as 10.5 degrees, the absolute phase deviation is calculated by subtracting the two values, resulting in 75.0 degrees. Multiplying this 75.0 degrees by the conversion constant of 1.2 nanoseconds per degree yields a corresponding time offset of 90.0 nanoseconds. Using this calculation logic, the time offset calculation takes 15 milliseconds. This 15-millisecond time will be incorporated into the system clock drift correction parameters for secondary calibration.

[0035] S513: Obtain the global timeline template, use the origin of the global timeline template as a reference, combine the corresponding time offset to perform compensation and translation calculations on the timestamp indicators in the multi-sensor data mixture package for time sequence alignment, and integrate and output a multi-sensor synchronous sensing data set. The dispatch center retrieves a pre-calibrated global timeline template from the central database, using the origin of the global timeline template as the reference for multi-dimensional data alignment. Combining the 90.0 nanosecond time offset calculated in the previous step, it performs compensation and shift calculations on the timestamps contained within the mixed data packets uploaded and aggregated from various terminal smart sensors via multiple routes to achieve time-series alignment. This results in a highly rigorous global multi-sensor high-frequency synchronous acquisition multi-dimensional sensor data set. The compensation and shift calculation logic involves extracting the inherent arrival timestamp of the current mixed packet and the calculated time offset, subtracting the inherent arrival timestamp from the time offset to obtain the backoff compensation time, and then adding the backoff compensation time to the system clock drift correction parameter to obtain the final aligned absolute timestamp. For example, a single-channel sensor data packet might have an inherent arrival timestamp of 1000.0 nanoseconds. The corresponding time offset is extracted to be 90.0 nanoseconds. Subtracting these two values ​​yields a backoff compensation time of 910.0 nanoseconds. The current system clock drift correction parameter is then sent, which is 5.0 nanoseconds. Adding 910.0 nanoseconds to 5.0 nanoseconds gives the final aligned absolute timestamp of 915.0 nanoseconds. Finally, the system enters the final synchronization data output state, integrating and outputting a multi-sensor synchronized sensing data set.

[0036] A multi-sensor high-frequency data synchronous acquisition system includes: The analog signal composite module is used to perform S1: acquire analog voltage signal and global phase reference signal, process analog voltage signal using voltage-controlled oscillation parameters to obtain continuous oscillation signal, construct additional voltage pulse according to global phase reference signal and preset voltage conversion ratio, superimpose additional voltage pulse onto the polarity alternation position of continuous oscillation signal to generate phase mark signal, and merge multiple phase mark signals to generate a single composite electrical signal; The centralized slice sampling module is used to perform S2: obtain the global sampling frequency value, sample a single composite electrical signal based on the global sampling frequency value to extract the voltage digital amplitude, and splice them in chronological order to generate a mixed digital sequence; The frequency band separation and analysis module is used to execute S3: process the mixed digital sequence according to the digital bandpass filter parameters to construct an independent frequency band digital sequence, extract the positive and negative alternation time interval of the independent frequency band digital sequence, analyze the instantaneous frequency value in combination with the frequency conversion constant, analyze the offset of the instantaneous frequency value relative to the center frequency value of the frequency band, and obtain the environmental change numerical sequence. The phase analysis package module is used to execute S4: compare the amplitude characteristics of the independent frequency band digital sequence with the pulse judgment threshold to extract the phase extraction pulse, restore the original phase mark value based on the phase extraction pulse and the phase conversion ratio parameter, insert the original phase mark value into the starting data address of the environmental change value sequence, and combine to generate a sensor data mixture package; The data timing alignment module is used to execute S5: Based on the zero-phase reference value, the original phase marker value is extracted from the sensor data mixture package and compared with the reference to obtain the timing phase deviation. Combined with the phase-time conversion constant, the time offset is obtained. The time offset is used to shift and align the sensor data mixture package, and output a multi-sensor synchronous sensing data set.

[0037] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments that can be applied to other fields. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A method for synchronous acquisition of high-frequency data from multiple sensors, characterized in that, Includes the following steps: S1: Acquire an analog voltage signal and a global phase reference signal, process the analog voltage signal using voltage-controlled oscillation parameters to obtain a continuous oscillation signal, construct an additional voltage pulse based on the global phase reference signal and a preset voltage conversion ratio, superimpose the additional voltage pulse onto the polarity alternation position of the continuous oscillation signal to generate a phase marker signal, and merge multiple phase marker signals to generate a single composite electrical signal; S2: Obtain the global sampling frequency value, sample the single composite electrical signal based on the global sampling frequency value to extract the voltage digital amplitude, and splice them in chronological order to generate a mixed digital sequence; S3: Process the hybrid digital sequence according to the digital bandpass filter parameters to construct an independent frequency band digital sequence, extract the positive and negative alternation time interval of the independent frequency band digital sequence, and analyze the instantaneous frequency value by combining the frequency conversion constant. Analyze the offset of the instantaneous frequency value relative to the center frequency value of the frequency band to obtain the environmental change value sequence. S4: Compare the amplitude characteristics of the independent frequency band digital sequence with the pulse judgment threshold to extract the phase extraction pulse, restore the original phase mark value according to the phase extraction pulse and the phase conversion ratio parameter, and insert the original phase mark value into the starting data address of the environmental change value sequence to generate a sensor data mixture packet. S5: Based on the zero-phase reference value, extract the original phase marker value from the sensor data mixture package, perform a reference comparison to obtain the timing phase deviation, combine it with the phase-time conversion constant to obtain the time offset, and translate and align the sensor data mixture package with the time offset to output a multi-sensor synchronous sensing data set.

2. The method for synchronous acquisition of high-frequency data from multiple sensors according to claim 1, characterized in that: During the phase extraction pulse process, if the amplitude feature is greater than the pulse judgment threshold, it is extracted as a phase extraction pulse; if the amplitude feature is less than or equal to the pulse judgment threshold, it is filtered out.

3. The method for synchronous acquisition of high-frequency data from multiple sensors according to claim 1, characterized in that, The polarity alternation position refers to the instant when the voltage polarity of the continuous oscillation signal changes.

4. The method for synchronous acquisition of high-frequency data from multiple sensors according to claim 1, characterized in that, The specific steps of S1 are as follows: S111: Obtain the system frequency band allocation protocol and analog voltage signal, collect the channel dynamic range constraint standard, analyze the frequency mapping relationship of the system frequency band allocation protocol to obtain the voltage-controlled oscillation parameters, extract the maximum voltage swing limit of the dynamic range constraint standard to set the preset voltage conversion ratio, and adjust the analog voltage signal to continuously oscillate and alternate based on the voltage-controlled oscillation parameters to generate a continuous oscillation signal; S112: Based on the continuous oscillation signal and the preset voltage conversion ratio, monitor the global phase reference signal, extract the voltage polarity alternation time point of the continuous oscillation signal to obtain the polarity alternation position, extract the phase offset for the global phase reference signal, and perform mapping conversion on the phase offset in combination with the preset voltage conversion ratio to obtain the additional voltage pulse; S113: The additional voltage pulse is shifted to the polarity alternation position at the corresponding time to perform amplitude superposition, thereby obtaining a signal carrying a phase mark. The internal spectral energy characteristics of the multiple signals carrying phase marks are extracted. Based on the spectral energy characteristics, the multiple signals carrying phase marks are subjected to frequency division multiplexing and merging processing to generate a single composite electrical signal.

5. The method for synchronous acquisition of high-frequency data from multiple sensors according to claim 1, characterized in that, The specific steps of S2 are as follows: S211: Extract the internal spectral energy distribution state of the single composite electrical signal, identify the highest frequency component index, perform frequency multiplication operation on the highest frequency component index to obtain the discretized rate value, and perform boundary rounding processing on the discretized rate value to obtain the global sampling frequency value. S212: Configure the sampling clock beat based on the global sampling frequency value, and sample the single composite electrical signal at equal intervals according to the clock beat to obtain a discrete voltage point set. Read the analog level index of each point in the discrete voltage point set, perform quantization encoding mapping on the analog level index, and extract the digital voltage amplitude. S213: Extract the time tag index associated with the multiple voltage digital amplitudes, sort the multiple voltage digital amplitudes according to the time tag to obtain a time sequence data set, and perform first-end connection combination on adjacent data elements in the time sequence data set to establish a hybrid digital sequence.

6. The method for synchronous acquisition of high-frequency data from multiple sensors according to claim 1, characterized in that, The specific steps of S3 are as follows: S311: Based on the hybrid digital sequence, the frequency range is intercepted according to the channel bandwidth boundary delineation rule to obtain the digital bandpass filter parameters and the center frequency value of the frequency band. Based on the digital bandpass filter parameters, a weighted summation and convolution operation is performed on the frequency components of each order inside the hybrid digital sequence to filter the in-band data and extract the independent frequency band digital sequence. S312: Obtain the factory parameters of the oscillator, extract the voltage response slope attribute within the factory parameters to generate a frequency conversion constant, read the timestamps associated with adjacent positive and negative alternation points in the independent frequency band digital sequence, perform subtraction to obtain the positive and negative alternation time difference, and perform reciprocal product conversion on the positive and negative alternation time difference using the frequency conversion constant to obtain the instantaneous frequency value. S313: Extract multiple consecutive nodes and associate them with the instantaneous frequency values ​​to establish a frequency evolution trajectory set. Perform subtraction operations between each element in the frequency evolution trajectory set and the center frequency value of the frequency band to construct a frequency offset amplitude set. Arrange the values ​​according to the order of time nodes to generate an environmental change numerical sequence.

7. The method for synchronous acquisition of high-frequency data from multiple sensors according to claim 1, characterized in that, The specific steps of S4 are as follows: S411: Obtain channel noise floor statistics, extract background noise peak superposition tolerance index to establish pulse judgment threshold, extract local extrema based on the independent frequency band digital sequence to obtain amplitude features, perform numerical comparison operation between the amplitude features and the pulse judgment threshold, filter out associated amplitude features that exceed the pulse judgment threshold, and generate phase extraction pulse; S412: Perform reverse calculation on the preset voltage conversion ratio to obtain the phase conversion ratio parameter, extract the amplitude variable inside the phase extraction pulse, and perform scaling multiplication calculation on the amplitude variable in combination with the phase conversion ratio parameter to recover the original phase mark value; S413: Traverse the storage space distribution within the environmental change numerical sequence, locate the memory offset position of the first data element in the environmental change numerical sequence to obtain the starting data address, write the original phase marker value to the starting data address according to the data encapsulation protocol, and perform header appending and assembly operations to generate a sensor data hybrid packet.

8. The method for synchronous acquisition of high-frequency data from multiple sensors according to claim 1, characterized in that, The specific steps of S5 are as follows: S511: Obtain the synchronization clock initialization configuration and system master clock frequency specification, extract the start timestamp anchor variable inside the synchronization clock initialization configuration, assign a value to set the zero phase reference value, parse the oscillation period attribute inside the system master clock frequency specification to obtain the single beat duration variable, perform normalization proportional conversion on the single beat duration variable, and obtain the phase time conversion constant. S512: Based on the sensor data mixture packet, the zero-phase reference value and the phase-time conversion constant, read the header data of the sensor data mixture packet to extract the original phase marker value, perform a subtraction operation between the original phase marker value and the zero-phase reference value to obtain the timing phase difference value, and combine the phase-time conversion constant to extract the time offset from the timing phase difference value. S513: Obtain the global timeline template, take the origin of the global timeline template as the reference, and perform time-series alignment processing on the timestamp index in the multi-channel sensor data mixing package by combining the corresponding time offset, and integrate and output the multi-sensor synchronous sensing data set.

9. A synchronous acquisition system for high-frequency data from multiple sensors, characterized in that, The system is used to implement the method according to any one of claims 1-8, comprising: The analog signal composite module acquires an analog voltage signal and a global phase reference signal, processes the analog voltage signal using voltage-controlled oscillation parameters to obtain a continuous oscillation signal, constructs an additional voltage pulse based on the global phase reference signal and a preset voltage conversion ratio, superimposes the additional voltage pulse onto the polarity alternation position of the continuous oscillation signal to generate a phase marker signal, and merges multiple phase marker signals to generate a single composite electrical signal. The centralized slicing sampling module obtains the global sampling frequency value, samples the single composite electrical signal based on the global sampling frequency value to extract the voltage digital amplitude, and splices them in chronological order to generate a mixed digital sequence. The frequency band separation and analysis module processes the mixed digital sequence according to the digital bandpass filter parameters to construct an independent frequency band digital sequence, extracts the positive and negative alternation time interval of the independent frequency band digital sequence, analyzes the instantaneous frequency value in combination with the frequency conversion constant, analyzes the offset of the instantaneous frequency value relative to the center frequency value of the frequency band, and obtains the environmental change value sequence. The phase analysis and packet assembly module compares the amplitude characteristics of the independent frequency band digital sequence with the pulse judgment threshold to extract the phase extraction pulse, restores the original phase mark value based on the phase extraction pulse and the phase conversion ratio parameter, and inserts the original phase mark value into the starting data address of the environmental change value sequence to generate a sensor data hybrid packet. The data timing alignment module extracts the original phase marker values ​​from the sensor data mixture based on the zero-phase reference value, performs a reference comparison to obtain the timing phase deviation, and maps the time offset by the phase-time conversion constant. The time offset is then used to shift and align the sensor data mixture to output a multi-sensor synchronous sensing data set.

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