Global multi-source measurement variable adaptive conversion method based on high-precision beidou timing

Abstract

The application relates to the technical field of satellite navigation and application systems, and discloses a global multi-source measurement variable adaptive conversion method based on Beidou high-precision time service, which is a special instrument for time service in a satellite navigation and application system, and comprises the following steps: acquiring multi-source measurement variable original sampling data streams and extracting a time service signal to establish a global absolute time grid; analyzing sampling data bit field distribution to lock a least significant bit interval below physical measurement bottom noise; converting sampling time sequence deviation relative to the grid into a binary micro-time sequence; implementing phase reverse alignment correction according to physical causal time delay between associated variables; and calling a hardware bit shift instruction to overwrite the sequence into the least significant bit interval to generate a composite mapping variable; and the application establishes a bit field implicit reuse conversion mechanism, destroys asynchronous signal transmission delay to physical causal order under the premise of maintaining unchanged message topology and bus load.

Description

Technical Field

[0001] This invention relates to the field of satellite navigation and application system technology, and in particular to an adaptive conversion method for full-domain multi-source measurement variables based on BeiDou high-precision time synchronization. Background Technology

[0002] In the current distributed measurement scenarios of the BeiDou satellite navigation and application system, the timing, navigation and signal conversion of multi-source measurement variables need to be performed under a unified time base. Existing satellite navigation application system terminals or conversion devices usually generate global synchronization pulses by receiving high-precision timing signals from BeiDou satellites and map discrete asynchronous sampling data to preset time grid nodes. To ensure data consistency, the device usually sets a fixed conversion cycle and processing logic.

[0003] Under extreme conditions such as strong vibrations or signal blockage in special vehicles, the above processing logic faces physical constraints. The timing signal phase experiences transient drift under dynamic interference, and the communication link transmission rate exhibits nonlinear fluctuations. Traditional conversion devices using serial feedback mechanisms produce lag, causing data buffer queues within the conversion gateway to accumulate, leading to system peak power consumption exceeding safety thresholds. In addition to hardware physical constraints, existing synchronization alignment strategies at the software control and algorithm implementation levels are insufficient. Chinese invention patent CN119780585B discloses a power equipment status monitoring method and related equipment based on BeiDou high-precision timing. It improves timing accuracy and monitoring efficiency through dynamic compensation models and lightweight neural networks. However, when handling concurrent conversions of massive heterogeneous variables, it still relies on standard message blocking. The current technology approach for device and transmission architecture fails to address the phase loss problem caused by asynchronous signals being mapped to a synchronous grid. At edge devices with limited bandwidth or scarce computing resources, the inference overhead of complex models cannot meet the real-time requirements of nanosecond-level causal reconstruction. Furthermore, to achieve global synchronization of multi-source heterogeneous data, the device typically forces asynchronously arriving measurement variables to the nearest synchronous timescale point during coordinate mapping. This processing mode eliminates the inherent asynchronous phase characteristics between variables, making it impossible for subsequent processing units to restore the microscopic causal order between multi-source physical events. This results in irreversible information entropy loss in the signal conversion stage. While the industry has attempted to alleviate these contradictions by increasing cache depth or sampling frequency, the resulting computational overhead and storage pressure are unbearable at edge-side conversion nodes.

[0004] Therefore, the technical problem to be solved by this invention is how to provide an adaptive transformation method for full-domain multi-source measurement variables based on BeiDou high-precision time synchronization, so that it can maintain physical causality fidelity and reduce edge processing load in dynamic interference environment. Summary of the Invention

[0005] This invention addresses the problems existing in the current adaptive conversion method of global multi-source measurement variables based on BeiDou high-precision time synchronization.

[0006] Therefore, the problem to be solved by this invention is: loss of physical causal timing due to environmental interference during the conversion process of measurement variables and runaway power consumption of edge conversion gateway.

[0007] To address the aforementioned technical problems, this invention provides the following technical solution: a global multi-source measurement variable adaptive transformation method based on BeiDou high-precision time synchronization, comprising the following steps:

[0008] Step S1: Obtain the raw sampling data stream of multi-source measurement variables and extract the BeiDou high-precision timing signal to establish the global absolute time grid;

[0009] Step S2: Analyze the bit field distribution of the original sampled data stream in the underlying register and lock the lowest effective bit interval in the original sampled data stream where the numerical amplitude is lower than the physical measurement background noise envelope;

[0010] Step S3: Monitor the nanosecond-level deviation of the original sampled data stream relative to the global absolute time grid at the sampling time, and convert the nanosecond-level deviation value into a binary microtimescale sequence based on the mapping ratio between the nanosecond-level deviation value and the sampling frequency of the original sampled data stream.

[0011] Step S4: Establish a correlation variable topology matrix to identify the primary and secondary variables with native physical causal relationships in the original sampled data stream, and determine the asynchronous delay deviation of the secondary variables relative to the primary variables. Use the asynchronous delay deviation to perform phase reverse alignment correction on the binary micro-timescale sequence.

[0012] Step S5: Call the hardware shift instruction to overwrite the binary microtimescale sequence after phase reversal alignment correction bit by bit into the least significant bit interval, generating a composite mapping variable encapsulating time-series causal characteristics.

[0013] Preferably, step S2 includes: obtaining the physical range and the number of effective bits of the analog-to-digital conversion of the current measurement channel, determining the unit quantization step corresponding to the original sampled data stream; extracting the standard deviation of the background thermal noise jitter amplitude in the underlying register, determining the number of consecutive bits within the uncertainty envelope interval, and defining the low-bit space corresponding to the number of consecutive bits as the least significant bit interval.

[0014] Preferably, step S4 includes: monitoring the concurrent mutation characteristics of the initial variable and the secondary variable, extracting the observation delay difference when the initial variable and the secondary variable reach the global absolute time grid; comparing the observation delay difference with the preset reference propagation delay constant, removing the queuing jitter error caused by the fluctuation of the underlying transmission bus, and adding the queuing jitter error as a correction component to the nanosecond-level deviation value.

[0015] Preferably, the bit width N of the binary microtimestamp sequence satisfies the following quantization constraint rules: Where ceil is the floor function. The maximum allowable asynchronous offset duration is preset for the original sampled data stream, and Δt is the timing accuracy step defined by the global absolute time grid.

[0016] Preferably, after step S5, the following adaptive control steps are also included: step S51, real-time monitoring of the accumulation rate of the composite mapping variable in the transmission link; step S52, when the accumulation rate exceeds the preset burst transmission peak power consumption safety threshold 1A, reducing the sampling frequency of the original sampled data stream in subsequent cycles, so that the accumulation rate is maintained within the burst transmission peak power consumption safety threshold, and simultaneously increasing the coverage bits of the least significant bit interval.

[0017] Preferably, the number of bits covered in the least significant bit interval is adjusted in real time according to the dynamic change rate of the background thermal noise jitter amplitude, and the number of bits used to overwrite the binary microtime stamp sequence is increased when the background thermal noise jitter amplitude increases.

[0018] Preferably, the composite mapping variable is output to the solution terminal so that the solution terminal can extract the binary microtimescale sequence through reverse shifting and restore the physical causal order of the multi-source measurement variables under the global absolute time grid.

[0019] Preferably, the global absolute time grid is phase-locked by the edge of the second pulse of the BeiDou high-precision time synchronization signal, and the second pulse interval is subdivided and filled by a high-frequency crystal oscillator with a local frequency of not less than 10MHz.

[0020] Preferably, the least significant bit interval is logically isolated from the significant amplitude bits carrying physical quantity information in the original sampled data stream by a preset number of protection isolation bits.

[0021] Preferably, the method completes the orthogonal composite recombination of amplitude information and micro-timescale information within the data bit width of a single measurement variable, and the hardware shift instruction is directly driven by the processor's register control word.

[0022] The beneficial effects of this invention are:

[0023] 1. In the adaptive transformation of multi-source measurement variables in the whole domain, a spatiotemporal perturbation factor is constructed by the pulse phase drift rate of the Beidou high-precision timing signal, and this factor is used as a feedforward source to drive the dimensionality reduction update of the transformation matrix. The microscopic physical characteristics of the timing signal are used to characterize the physical interference intensity of the space where the device is located. This allows the transformation device to complete the convergence of internal sampling logic and resource scheduling in advance before the communication link is substantially disconnected or the judgment is delayed. This eliminates the perception delay caused by the traditional device's reliance on network protocol stack feedback. Under extreme working conditions such as strong vibration or obstruction of special vehicles, it avoids data accumulation and power consumption exceeding the limit of the local transmission queue, ensuring the physical determinism of the multi-source heterogeneous variable transformation process.

[0024] 2. An adaptive mapping mechanism based on the transient gradient of measured variables is established. By comparing the transient gradient with the dynamic sensitivity threshold, computing resources are dynamically allocated during the conversion process. For variables with gradual changes, a zero-order hold mapping is used, directly attaching the variable value to the global absolute time grid node and disabling the corresponding floating-point arithmetic unit. For variables with drastic transient changes, linear phase compensation mapping is performed. This adaptive allocation logic breaks the one-size-fits-all high-order interpolation resampling mode in traditional synchronous conversion. Without adding additional hardware computing modules, it effectively reduces the static power consumption and peak computing power overhead of the edge conversion gateway when processing massive heterogeneous variables, and solves the technical contradiction between high-precision alignment and low-power operation in the large-scale deployment of industrial IoT.

[0025] 3. A bit-domain implicit reuse conversion mechanism is established. The least significant bit interval of the measured variable in the data register, which is lower than the physical noise floor, carries the binary micro-timescale sequence converted from the asynchronous arrival time difference. After performing phase compensation calculation, the device uses hardware-level shift instructions to overwrite the micro-time phase information bit by bit into the corresponding least significant bit interval, generating a composite mapping variable that has both grid synchronization amplitude characteristics and native time residuals. Under the premise of maintaining the standardized communication message topology and bus load unchanged, the micro-time phase information that was originally discarded as entropy loss in the interpolation operation is retained, which improves the downstream system's ability to perform nanosecond-level time-series tracing and accurate reconstruction of causal chains for concurrent physical events. Attached Figure Description

[0026] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below. 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, wherein:

[0027] Figure 1 This is a flowchart of the adaptive conversion steps for multi-source measurement variables in BeiDou time synchronization according to the present invention.

[0028] Figure 2 This is a logical architecture diagram of the global multi-source measurement variable composite mapping and physical causal restoration of the present invention. Detailed Implementation

[0029] 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. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0030] 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.

[0031] Secondly, an embodiment or embodiment referred to herein refers to a specific feature, structure or characteristic that may be included in at least one implementation of the present invention. An 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.

[0032] This invention is described in detail with reference to the schematic diagrams. When describing the embodiments of this invention, for ease of explanation, the cross-sectional views of the device structure will be partially enlarged without adhering to the general scale. Moreover, the schematic diagrams are only examples and should not limit the scope of protection of this invention. In addition, in actual manufacturing, the three-dimensional spatial dimensions of length, width and depth should be included.

[0033] Furthermore, in the description of this invention, it should be noted that the terms such as "upper," "lower," "inner," and "outer" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or component referred to has a specific orientation, or is constructed and operated in a specific orientation. Therefore, they should not be construed as limiting this invention. In addition, the terms "first," "second," or "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0034] Unless otherwise explicitly specified and limited, the terms installation, connection, and linking in this invention should be interpreted broadly. For example, they can refer to fixed connection, detachable connection, or integrated connection; similarly, they can refer to mechanical connection, electrical connection, or direct connection, or indirect connection through an intermediate medium, or internal connection between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0035] An adaptive transformation method for full-domain multi-source measurement variables based on BeiDou high-precision time synchronization includes the following steps:

[0036] Step S1: Obtain the raw sampling data stream of multi-source measurement variables and extract the BeiDou high-precision timing signal to establish the global absolute time grid;

[0037] Step S2: Analyze the bit field distribution of the original sampled data stream in the underlying register and lock the lowest effective bit interval in the original sampled data stream where the numerical amplitude is lower than the physical measurement background noise envelope;

[0038] Step S3: Monitor the nanosecond-level deviation of the original sampled data stream relative to the global absolute time grid at the sampling time, and convert the nanosecond-level deviation value into a binary microtimescale sequence based on the mapping ratio between the nanosecond-level deviation value and the sampling frequency of the original sampled data stream.

[0039] Step S4: Establish a correlation variable topology matrix to identify the primary and secondary variables with native physical causal relationships in the original sampled data stream, and determine the asynchronous delay deviation of the secondary variables relative to the primary variables. Use the asynchronous delay deviation to perform phase reverse alignment correction on the binary micro-timescale sequence.

[0040] Step S5: Call the hardware shift instruction to overwrite the binary microtimescale sequence after phase reversal alignment correction bit by bit into the least significant bit interval, generating a composite mapping variable encapsulating time-series causal characteristics.

[0041] Preferably, step S2 includes: obtaining the physical range and the number of effective bits of the analog-to-digital conversion of the current measurement channel, determining the unit quantization step corresponding to the original sampled data stream; extracting the standard deviation of the background thermal noise jitter amplitude in the underlying register, determining the number of consecutive bits within the uncertainty envelope interval, and defining the low-bit space corresponding to the number of consecutive bits as the least significant bit interval.

[0042] Preferably, step S4 includes: monitoring the concurrent mutation characteristics of the initial variable and the secondary variable, extracting the observation delay difference when the initial variable and the secondary variable reach the global absolute time grid; comparing the observation delay difference with the preset reference propagation delay constant, removing the queuing jitter error caused by the fluctuation of the underlying transmission bus, and adding the queuing jitter error as a correction component to the nanosecond-level deviation value.

[0043] Preferably, the bit width N of the binary microtimestamp sequence satisfies the following quantization constraint rules: Where ceil is the floor function. The maximum allowable asynchronous offset duration is preset for the original sampled data stream, and Δt is the timing accuracy step defined by the global absolute time grid.

[0044] Preferably, after step S5, the following adaptive control steps are also included: step S51, real-time monitoring of the accumulation rate of the composite mapping variable in the transmission link; step S52, when the accumulation rate exceeds the preset burst transmission peak power consumption safety threshold 1A, reducing the sampling frequency of the original sampled data stream in subsequent cycles, so that the accumulation rate is maintained within the burst transmission peak power consumption safety threshold, and simultaneously increasing the coverage bits of the least significant bit interval.

[0045] Preferably, the number of bits covered in the least significant bit interval is adjusted in real time according to the dynamic change rate of the background thermal noise jitter amplitude, and the number of bits used to overwrite the binary microtime stamp sequence is increased when the background thermal noise jitter amplitude increases.

[0046] Preferably, the composite mapping variable is output to the solution terminal so that the solution terminal can extract the binary microtimescale sequence through reverse shifting and restore the physical causal order of the multi-source measurement variables under the global absolute time grid.

[0047] Preferably, the global absolute time grid is phase-locked by the edge of the second pulse of the BeiDou high-precision time synchronization signal, and the second pulse interval is subdivided and filled by a high-frequency crystal oscillator with a local frequency of not less than 10MHz.

[0048] Preferably, the least significant bit interval is logically isolated from the significant amplitude bits carrying physical quantity information in the original sampled data stream by a preset number of protection isolation bits.

[0049] Preferably, the method completes the orthogonal composite recombination of amplitude information and micro-timescale information within the data bit width of a single measurement variable, and the hardware shift instruction is directly driven by the processor's register control word.

[0050] Example 1: In industrial monitoring scenarios where special tracked vehicles traverse complex mountainous terrain with strong vibrations and weak communication signal blockages, a global multi-source measurement variable adaptive conversion method is deployed within an edge diagnostic gateway to address the overload and timing errors in the data conversion bus caused by the massive influx of heterogeneous sensor signals triggered by sudden physical impacts on the chassis. When the vehicle tracks suffer a drop impact, the vibration stress distributed in the suspension system and drive shaft, as well as the pressure variables in the hydraulic lines, experience high-frequency concurrent abrupt changes within a preset time window. Traditional synchronous conversion mechanisms utilize a unified high-precision resampling algorithm to absorb all asynchronously arriving data streams into a fixed local... The clock tick, which ignores the physical evolution of the measured variables, instantly exhausts the processor's floating-point unit, causing the system's burst transmission peak power consumption to exceed the 1A safety threshold. This is achieved through indiscriminate mathematical smoothing, which eliminates the actual timing deviation of the chassis impact transmitted to the hydraulic system. The burst transmission peak power consumption safety threshold, at the physical hardware level, is specifically manifested as the core power supply bus operating current of the edge diagnostic gateway not exceeding 1A. The accumulation rate of composite mapped variables in the transmission link is positively correlated with the continuous level switching frequency of the transceiver chip in the gateway's internal bus physical layer and the throughput load of the direct data access channel to memory. When the variables in the cache queue... When the accumulation rate exceeds the preset 5000 frames per second, the high-frequency continuous burst read / write and the continuous full-load power consumption of the bus driver level will directly cause the transient operating current on the power supply line to rise to over 1A. This invention indirectly and proactively constrains the transient current load of the underlying hardware by monitoring the accumulation rate of composite mapped variables on the link in real time at the software algorithm layer, and using 5000 frames per second as the scalar for triggering regulation, thus preventing it from exceeding the 1A operating current safety physical boundary. This technical solution changes the mapping triggering rules of the global absolute time grid, and the edge diagnostic gateway obtains asynchronously arriving multi-source measurement variables and calculates each measurement variable. The transient gradient within the current time window is compared with a preset dynamic sensitivity threshold. For smooth variables with transient gradients below the dynamic sensitivity threshold, the floating-point arithmetic unit is disabled and a zero-order hold-forward mapping is executed, directly overwriting the magnitude to the nearest global absolute time grid node. For abrupt variables with transient gradients greater than or equal to the dynamic sensitivity threshold, the computation unit is activated to execute a linear phase compensation mapping. This mechanism transforms the allocation condition of computing power from a fixed time period to a dynamic instruction derived from the abrupt intensity of the physical quantity itself. By defining the processing boundary, it avoids the depletion of computing resources caused by global high-order interpolation operations.

[0051] To address data arrival delays caused by random queuing and preemption on the underlying fieldtransmission bus under concurrent impact conditions, a pre-alignment benchmark at the physical layer is established using the correlation variable topology matrix before interpolation calculations. When the gateway detects concurrent out-of-bounds transient gradient changes of primary and secondary variables with native physical causal relationships, it extracts the observation delay difference between the actual arrival time of the secondary variable and the actual arrival time of the primary variable. This observation delay difference is compared with the benchmark causal delay constant preset in the correlation variable topology matrix. The deviation from the benchmark causal delay constant is used as the queuing jitter error caused by physical congestion on the underlying communication bus. The process involves stripping the data and backtracking the actual arrival time of secondary variables based on the deviation to generate a corrected arrival time. This is achieved by using the physical structure transmission law to pre-filter the non-deterministic transmission jitter of the underlying data link. This ensures that the physical correlation prior data provided by the correlation variable topology matrix complements the subsequent phase reversal correction based on nanosecond-level deviation values. This resolves the data structure contradiction between the out-of-order arrival of multi-source heterogeneous data and the requirement for causal time-series fidelity. After establishing the corrected arrival time and generating the baseline compensation amplitude, this technical solution performs a conversion operation on the remaining time-series deviation values ​​during the conversion process. The gateway parses the original sampled data stream at the bottom... The bit distribution in the layer register is determined by obtaining the physical range of the current measurement channel and the effective number of bits in the analog-to-digital conversion to determine the unit quantization step. Then, the standard deviation representing the amplitude of the background thermal noise jitter is extracted to lock the least significant bit interval where the numerical amplitude is lower than the envelope of the physical measurement background noise. Based on the mapping relationship between the nanosecond-level deviation of the original sampled data stream relative to the global absolute time grid at the sampling time and the sampling frequency, this nanosecond-level deviation value is converted into a binary micro-timescale sequence. Then, a hardware shift instruction driven by the processor register control word is invoked to overwrite the phase-reversed binary micro-timescale sequence bit by bit to the corresponding least significant bit interval. Within the effective bit interval, the amplitude characteristics and timing characteristics are orthogonally recombined using the data bit width of a single measurement variable. The output generates a composite mapping variable that encapsulates timing and causal characteristics. The composite mapping variable output to the solution terminal carries the timing residual information of concurrent physical events while maintaining the existing standardized communication message topology and bus transmission load. After receiving the composite mapping variable, the solution terminal extracts the binary micro-timescale sequence within the least effective bit interval through a reverse shift operation. Then, under the constraint of the global absolute time grid, the actual causal sequence of the entire chain from chassis impact to hydraulic system is restored.

[0052] Example 2: In a closed electrical metrology verification environment equipped with a high-frequency dynamic analog signal source and an industrial-grade bus transmission network, the timing reconstruction accuracy and data fidelity of the adaptive conversion method for multi-source measurement variables across the entire domain were verified. The test platform consisted of a programmable signal generator with nanosecond-level trigger response, a clock synchronization source simulating a BeiDou time receiver, an edge diagnostic gateway prototype running the method of this invention, and a calculation terminal. The signal generator was set to output two analog voltage signals with fixed physical causal delays, representing the initial variable of chassis vibration at a frequency of 1kHz and the secondary variable of hydraulic pressure at a frequency of 1kHz, respectively. A physical propagation delay of 5.00ms was preset between the two signals. At the same time, an interference module that generates random transmission jitter from 0 to 500μs was inserted into the signal link to simulate nondeterministic bus congestion. Gaussian white noise with a signal-to-noise ratio of 40.0dB was superimposed at the analog input to reproduce the electromagnetic environment of the industrial site.

[0053] Based on the initial state definition procedure, the physical boundary of the data conversion is locked. The analog input terminal of the edge diagnostic gateway is short-circuited to ground, and 10,000 sampling points of background data are continuously collected. The standard deviation σ of the data sequence is calculated to be 0.85mV. According to the 3σ criterion, the background noise envelope of the physical measurement is determined to be ±2.55mV. This envelope value corresponds to the lowest 3 bits of a 16-bit analog-to-digital converter with a range of ±10V. Based on this, the least significant bit interval is fixed in the hardware level as the D2 to D0 bit field of the register. This physical boundary setting ensures that the timing feature overwrite operation is located within the invalid noise space of the physical measurement. The trigger signal generator generates a step pulse excitation, and the edge diagnostic gateway connects to... The system receives the data stream and monitors the nanosecond-level deviation of the sampling time relative to the global absolute time grid. The measured deviation at the current time is 126 ns. Based on the preset mapping ratio, it is converted into a 3-bit binary two's complement sequence. At the same time, the correlation variable topology matrix identifies that the actual arrival time of the secondary variable lags behind the initial variable by 5.38 ms. The difference between this lag value and the preset physical propagation delay of 5.00 ms is calculated to be 0.38 ms. This difference is determined to be the deviation caused by bus transmission jitter. Based on this, the system performs phase reverse alignment correction on the binary microtimescale sequence of the secondary variable and calls the hardware shift instruction to overwrite the corrected sequence bit by bit into the D2 to D0 bit fields.

[0054] A three-dimensional comparative observation group was set up to quantitatively evaluate the technical effect. The control group adopted a marking method based on network arrival timestamps, while the sample group of this invention adopted the method claimed in this invention. The partially missing control group only performed bit field overwriting after removing the phase reversal alignment correction step. The output data of the solution terminal showed that when the control group restored the causal relationship between the two signals, the measured physical delay fluctuated between 4.78ms and 5.32ms due to random transmission jitter, with a standard deviation of 145μs. The causal logic under high-frequency impact caused timing inversion. The sample group of this invention analyzed... The physical delay converged within the range of 4.99ms to 5.01ms, the timing reconstruction error was controlled within 12μs, and the calculated analog waveform signal-to-noise ratio was 39.8dB, remaining within the tolerance range of 40.0dB Gaussian white noise of the original input signal. Data from the partially missing control group showed that the time resolution of single-point sampling was improved, but due to the failure to utilize the correlation variable topology matrix to remove bus queuing jitter error, a systematic bias of an average of 122μs remained in the timing error. This comparative data empirically demonstrates that the phase reversal alignment correction step is effective in eliminating nondeterminism. To address the engineering necessity of transmission delay, gradient stress testing was performed on the dynamic sensitivity threshold to verify the stability of the computing power allocation mechanism. The input signal frequency was linearly scanned from 100Hz to 5kHz, and three transient change gradient thresholds were set as comparison items for the sample group of this invention. The measured data shows that when the signal frequency is in the low-frequency flat range of 100Hz to 2kHz, the total harmonic distortion of the zero-order hold mapping output without activating the linear phase compensation mapping is maintained between 0.5% and 0.7%, and the power consumption of a single conversion is 12mW. When the signal frequency exceeds 2kHz... When the Hz inflection point and the transient gradient is higher than the threshold, if the zero-order hold mapping is continuously used, the phase distortion of the reconstructed waveform increases, and the total harmonic distortion (THD) measurement reaches 5.4%. After activating the linear phase compensation mapping, the THD measurement drops back and stabilizes at 0.8% at the 5kHz frequency. At this time, the conversion power consumption rises to 45mW, which confirms that the dynamic switching mapping algorithm based on the transient gradient can suppress the phase distortion of high-frequency abrupt signals under the condition of limiting the power consumption boundary of the edge diagnostic gateway, and establishes the correlation function law between the intensity of physical quantity abrupt changes and the allocation of computing resources.

[0055] Example 3: In the initial off-line calibration of a special vehicle using a full-domain multi-source measurement variable adaptive transformation method, the edge diagnostic gateway initiates the system initialization program to define the quantification boundary between normal fluctuations and sudden impacts, and extracts the baseline causal delay constant. Under normal test conditions with the vehicle statically started and the engine idling, the edge diagnostic gateway locks the physical evolution range of the multi-source measurement variables and calls the underlying construction instructions for the correlation variable topology matrix. The edge diagnostic gateway synchronously activates the front axle vibration sensor and the rear axle hydraulic pressure sensor through the underlying data bus to acquire a continuous raw sampling data stream lasting 600 seconds. The processor reads the chassis structure map pre-written in the underlying configuration file and extracts the physical metal transmission distance of 4.50m between the front axle vibration sensor and the rear axle hydraulic pressure sensor. The transmission distance parameter is used, and a preset reference propagation velocity parameter of 5000 m / s for mechanical stress waves in this special steel is called. The theoretical acoustic delay lower limit of 0.90 ms is calculated by dividing the physical metal transmission distance by the reference propagation velocity. Based on the above lower limit, the processor calculates the sliding cross-correlation between the vibration variable sequence belonging to the front axle and the pressure variable sequence belonging to the rear axle in the original sampled data stream, extracts the time offset corresponding to the peak value of the cross-correlation function, and when the time offset is detected to be greater than the theoretical acoustic delay lower limit and maintained at an extreme deviation envelope of 1.25 ms within a 30s time window, 1.25 ms is extracted as the reference causal time delay constant and memory-bound to the corresponding measurement channel physical address to complete the parameter solidification of the basic node of the correlation variable topology matrix.

[0056] While establishing the baseline causal delay constant, the edge diagnostic gateway initiates the quantization calibration program for the dynamic sensitivity threshold. The processor intercepts a 10-second raw sampling data stream under the current shock-free operating condition, uses a first-order forward differential algorithm to calculate the voltage amplitude increment between adjacent sampling points, and divides it by the current sampling period to obtain the discrete rate of change sequence of each measured variable under the baseline operating condition. The root mean square value of this discrete rate of change sequence is extracted and defined as the baseline dynamic envelope representing the normal fluctuation of the system. Based on the normal distribution confidence interval requirements, constant coefficient 3 is called to calculate the product of the baseline dynamic envelope and constant coefficient 3, and the result is... The result is written into the controller's comparison register as a dynamic sensitivity threshold. The threshold boundary is constructed by extracting actual physical background noise to establish the computing power allocation logic. When a special vehicle faces a sudden physical impact on its chassis in a specific operating environment, the edge diagnostic gateway calls the calibration-generated correlation variable topology matrix and the dynamic sensitivity threshold. When the processor receives asynchronously arriving abruptly changing data, it acquires the transient gradient and compares it with the dynamic sensitivity threshold in the comparison register, activates the linear phase compensation mapping operation unit, and simultaneously reads the 1.25ms constant bound to the correlation variable topology matrix to calculate the actual arrival time of the secondary variable and the initial variable. The observed delay difference, which is the actual arrival time, is used to extract the deviation between this difference and the 1.25ms constant. This deviation is then used to correct the phase reversal of the binary micro-timescale sequence of the secondary variable. This sequence alignment and computing power scheduling logic rely on the physical indicators extracted from the pre-calibration. Under high-frequency overload conditions on the data bus, it outputs a composite mapping variable carrying the causal characteristics of the time sequence. The observed delay difference includes the original mechanical stress transmission delay and the random queuing jitter error of the underlying field transmission bus. Since the reference causal delay constant is an inherent rigid boundary determined by the physical metal transmission distance and the solid mechanical wave velocity, the secondary... The actual evolution time difference between variables and initial variables at the physical level is always equal to the baseline causal delay constant. Therefore, at the network data flow level, the observed delay difference, which includes network transmission delay, is directly subtracted from the fixed baseline causal delay constant. The resulting positive or negative residual value logically corresponds to the communication layer's nondeterministic jitter caused by bus conflicts, message queuing, and gateway scheduling fluctuations. Thus, through this differential mapping between mechanical prior delay and network transmission delay, a signal conversion closed loop that accurately isolates queuing jitter error from the mixed bus delay is achieved without relying on deep analysis of the hardware protocol stack.

[0057] Example 4: In special industrial environments, before connecting to sensors, the edge diagnostic gateway initiates a scale image calibration program to lock the quantization boundary of the micro-timescale sequence. The processor obtains the sampling frequency of the physical channel, calculates the maximum theoretical time delay span between consecutive sampling points based on its reciprocal, and simultaneously reads the number of available bits in the least significant bit interval and calculates the maximum binary threshold that can be accommodated. The maximum theoretical time delay span is divided by the maximum binary threshold to obtain the unit timescale quantization step, which is then written to the control register. This procedure ensures that the subsequently acquired nanosecond-level deviation values ​​are discretized and divided according to this quantization step, limiting the generated binary micro-timescale sequence values ​​to within the capacity of the least significant bit interval and suppressing the risk of residual overflow contaminating the effective physical amplitude data.

[0058] To address the background noise expansion caused by hardware heat accumulation during long-term operation of equipment, the edge diagnostic gateway triggers a dynamic reconstruction logic. The system monitors the real-time temperature parameter of the analog-to-digital converter. When the drift of this parameter relative to the initial state reaches a preset temperature gradient threshold, the controller suspends the acquisition service and switches the front-end link to the internal reference ground. It then re-extracts the standard deviation of the background thermal noise under the current thermal equilibrium state and dynamically adjusts the number of bits included in the least significant bit interval accordingly. After synchronously refreshing the unit time scale quantization step, the signal conversion is resumed. This control path uses objective physical environmental variables as the reconstruction trigger source to maintain a tight isolation boundary between the timing feature overwriting action and the physical measurement background noise blind zone under dynamic operating conditions.

[0059] Example 5: In scenarios where special tracked vehicles operate deep in underground mines or long tunnels, the adaptive conversion method for global multi-source measurement variables faces the challenge of intermittent interruptions in the BeiDou high-precision timing signal. The previously established global absolute time grid loses the periodic forced alignment from the external absolute clock source, and the controller hardware timer generates cumulative drift under free oscillation, causing the extracted nanosecond-level deviation value to deviate from the physical timing sequence. The edge diagnostic gateway embeds a pre-deployment calibration and online timekeeping fault-tolerant procedure based on local clock dynamic modeling in the hardware abstraction layer, switching the maintenance benchmark of the absolute time grid to internal and external clocks. The adaptive phase-locked loop output with dual clock sources deploys a pre-calibration procedure to perform local clock calibration in areas where BeiDou high-precision timing signals are normally received. The processor of the edge diagnostic gateway uses the standard second pulse of the BeiDou signal output as the reference time window, counts the actual oscillation count value of the local analog-to-digital converter driven clock within this physical time span, divides it by the theoretical oscillation count value to obtain the clock frequency offset ratio factor, and stores the time series of this factor in the memory circular buffer. The clock frequency offset ratio factor within 100 consecutive second pulse periods is extracted to calculate the mean and slope to construct the dynamic drift model of the local crystal oscillator.

[0060] When the carrier-to-noise ratio of the BeiDou high-precision timing signal is detected to be lower than the preset locking threshold and a signal interruption is determined, the processor blocks the external second pulse synchronization interrupt and activates the internal clock keep-alive mode. It calls the last locked frequency offset scaling factor in the dynamic drift model and the current temperature gradient rate collected by the ambient temperature sensor. Based on the preset temperature-frequency compensation mapping table, it calculates the equivalent second pulse trigger command and uses the internally generated equivalent second pulse to maintain the node update of the global absolute time grid. Simultaneously, when extracting the nanosecond-level deviation value of the original sampled data stream, it multiplies the relative deviation time captured by the local hardware counter by the frequency offset scaling factor to perform scaling. The mathematical expression is as follows: ,in, The calibration nanosecond deviation is expressed in nanoseconds (ns). The relative deviation time is measured in nanoseconds (ns). The dimensionless frequency offset scaling factor is used to generate the calibration nanosecond bias. After generating the calibration nanosecond bias, the system performs a conversion of the binary microtimescale sequence and an overwrite operation of the least significant bit interval. When the communication link is restored, the system re-acquires the BeiDou high-precision timing signal and calculates the cumulative time residual. The cumulative time residual is offset by adjusting the equivalent second pulse step size within the subsequent 10 standard second pulse periods. This online timekeeping fault-tolerant procedure limits the parameter constraint path of the conversion device under the condition of losing external timing excitation, and maintains the timing accuracy of the composite mapping variable and the continuity of the measurement data stream in the weak communication signal blockage area.

[0061] 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 protection scope of the present invention.

Claims

1. A global multi-source measurement variable adaptive transformation method based on BeiDou high-precision time synchronization, characterized in that, Includes the following steps: Step S1: Obtain the raw sampling data stream of multi-source measurement variables and extract the BeiDou high-precision timing signal to establish the global absolute time grid; Step S2: Analyze the bit field distribution of the original sampled data stream in the underlying register and lock the lowest effective bit interval in the original sampled data stream where the numerical amplitude is lower than the physical measurement background noise envelope; Step S3: Monitor the nanosecond-level deviation of the original sampled data stream relative to the global absolute time grid at the sampling time, and convert the nanosecond-level deviation value into a binary microtimescale sequence based on the mapping ratio between the nanosecond-level deviation value and the sampling frequency of the original sampled data stream. Step S4: Establish a correlation variable topology matrix to identify the primary and secondary variables with native physical causal relationships in the original sampled data stream, and determine the asynchronous delay deviation of the secondary variables relative to the primary variables. Use the asynchronous delay deviation to perform phase reverse alignment correction on the binary micro-timescale sequence. Step S5: Call the hardware shift instruction to overwrite the binary microtimescale sequence after phase reversal alignment correction bit by bit into the least significant bit interval, generating a composite mapping variable encapsulating time-series causal characteristics.

2. The adaptive transformation method for full-domain multi-source measurement variables based on BeiDou high-precision time synchronization according to claim 1, characterized in that, Step S2 includes: obtaining the physical range and effective number of bits of the analog-to-digital conversion of the current measurement channel, determining the unit quantization step corresponding to the original sampled data stream; extracting the standard deviation of the background thermal noise jitter amplitude in the underlying register, determining the number of consecutive bits within the uncertainty envelope interval, and defining the low-bit space corresponding to the number of consecutive bits as the least significant bit interval.

3. The adaptive transformation method for full-domain multi-source measurement variables based on BeiDou high-precision time synchronization according to claim 1, characterized in that, Step S4 includes: monitoring the concurrent mutation characteristics of the initial variable and the secondary variable, extracting the observation delay difference when the initial variable and the secondary variable reach the global absolute time grid; comparing the observation delay difference with the preset reference propagation delay constant, removing the queuing jitter error caused by the fluctuation of the underlying transmission bus, and adding the queuing jitter error as a correction component to the nanosecond-level deviation value.

4. The adaptive transformation method for full-domain multi-source measurement variables based on BeiDou high-precision time synchronization according to claim 1, characterized in that, The bit width N of the binary microtimescale sequence satisfies the following quantization constraint rule: Where ceil is the floor function. The maximum allowable asynchronous offset duration is preset for the original sampled data stream, and Δt is the timing accuracy step defined by the global absolute time grid.

5. The adaptive transformation method for full-domain multi-source measurement variables based on BeiDou high-precision time synchronization according to claim 1, characterized in that, Step S5 is followed by the following adaptive control steps: Step S51, real-time monitoring of the accumulation rate of composite mapping variables in the transmission link; Step S52: When the stacking rate exceeds the preset burst transmission peak power consumption safety threshold 1A, reduce the sampling frequency of the original sampled data stream in subsequent cycles to keep the stacking rate within the burst transmission peak power consumption safety threshold, and simultaneously increase the coverage bits of the least significant bit interval.

6. The adaptive transformation method for full-domain multi-source measurement variables based on BeiDou high-precision time synchronization according to claim 2, characterized in that, The number of bits covered in the least significant bit interval is adjusted in real time according to the dynamic change rate of the background thermal noise jitter amplitude, and the number of bits used to overwrite the binary microtime stamp sequence is increased when the background thermal noise jitter amplitude increases.

7. The adaptive transformation method for full-domain multi-source measurement variables based on BeiDou high-precision time synchronization according to claim 1, characterized in that, The composite mapping variable is output to the solution terminal, which then extracts the binary microtimescale sequence through reverse shifting and restores the physical causal order of the multi-source measurement variables under the global absolute time grid.

8. The adaptive transformation method for full-domain multi-source measurement variables based on BeiDou high-precision time synchronization according to claim 1, characterized in that, The global absolute time grid is phase-locked by the edge of the second pulse of the BeiDou high-precision time signal, and the second pulse interval is subdivided and filled by a high-frequency crystal oscillator with a local frequency of not less than 10MHz.

9. The adaptive transformation method for full-domain multi-source measurement variables based on BeiDou high-precision time synchronization according to claim 1, characterized in that, The least significant bit interval is logically isolated from the effective amplitude bits carrying physical quantity information in the original sampled data stream by a preset number of protection isolation bits.

10. The adaptive transformation method for full-domain multi-source measurement variables based on BeiDou high-precision time synchronization according to claim 1, characterized in that, The method completes the orthogonal composite recombination of amplitude information and micro-timescale information within the data bit width of a single measurement variable, and the hardware shift instruction is directly driven by the processor's register control word.

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