Universal mixed signal acquisition and access system for ships and warships

Abstract

The invention belongs to the technical field of ship data acquisition and signal processing, and particularly relates to a mixed signal universal acquisition access system for a ship, which comprises a data acquisition conditioning module, a synchronization module, a data processing module and a communication interface module, the synchronization module automatically identifies and unifies signal formats, the data processing module completes verification and compression, and the communication interface module adapts to different upper-layer systems to form a closed-loop optimized mixed signal acquisition architecture, so that the compatibility, real-time performance and reliability of data acquisition in a ship complex environment are improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of ship data acquisition and signal processing, and in particular relates to a universal mixed signal acquisition and access system for ships. Background Art

[0002] Ship operations require the acquisition of a large number of heterogeneous signals, including analog sensor outputs, digital switching values, bus device data, and specialized interface signals. Traditional data acquisition systems typically employ a discrete design, deploying specialized acquisition equipment for different signal types. This results in a complex system structure, poor scalability, and difficult maintenance. The ship environment is subject to harsh conditions such as strong electromagnetic interference, mechanical vibration, and high humidity and salinity. Conventional data acquisition equipment lacks signal isolation and anti-interference capabilities, easily leading to data distortion or loss.

[0003] In existing technologies, signal conditioning circuits are mostly designed with fixed parameters, which cannot adapt to the output characteristics of different sensors. Gain and filter parameters need to be adjusted manually, which is cumbersome and error-prone. Protocol conversion usually relies on preset protocol libraries, and when faced with new or non-standard protocols, it is necessary to shut down and upgrade, which affects system continuity. Resource allocation mostly adopts static strategies and cannot be dynamically adjusted according to signal priority and system load. Critical data may be delayed due to resource competition. The data processing link lacks a unified time base, and the data of distributed acquisition nodes is difficult to synchronize accurately, affecting subsequent analysis and decision-making. Communication interfaces are usually bound to specific protocols, and additional conversion equipment is required when connecting to different upper-layer systems, increasing costs and failure points.

[0004] While existing patents address ship data acquisition, they often focus on a single signal type or local optimization, lacking systematic solutions for unified access, intelligent adaptation, and global resource scheduling of mixed signals. The International Maritime Organization (IMO) has placed higher demands on ship intelligence, necessitating a universal data acquisition system that can accommodate multiple signals, adapt to environmental changes, and dynamically optimize resources to support advanced applications such as condition monitoring and fault warning. This invention addresses these pain points by achieving full-process optimization through a modular architecture and intelligent algorithms, filling a technological gap in this field. Summary of the Invention

[0005] In view of the above shortcomings of the prior art, the purpose of the present invention is to provide a universal mixed signal acquisition and access system for ships, which is used to solve the problems of unified acquisition, adaptive processing and dynamic resource optimization of multi-source heterogeneous signals on ships.

[0006] The technical solutions for implementing the present invention are as follows:

[0007] A mixed signal universal acquisition and access system for ships, comprising:

[0008] The data acquisition and conditioning module is used to amplify and filter the external input signal to form a physical layer signal. The data acquisition and conditioning module includes a programmable gain amplifier circuit and an adaptive filter circuit;

[0009] A synchronization module is used to extract and classify features of the physical layer signal and form a standardized digital signal. The synchronization module has a built-in multi-protocol recognition algorithm and a signal feature extraction unit. The protocol recognition algorithm implements unsupervised classification of protocol types based on the signal time domain features and statistical features extracted by the signal feature extraction unit;

[0010] A data processing module is used to process the standardized digital signal to form an application layer data packet after receiving the optimization allocation instruction. The data processing module processes the data including data verification, time stamp alignment and data compression operations;

[0011] The communication interface module is used to analyze application layer data packets and form standard communication protocol data streams to be transmitted to the ship's upper system.

[0012] Among them, the programmable gain amplifier circuit of the data acquisition and conditioning module operates in a closed-loop control mode, and its gain parameter is dynamically adjusted by the synchronization module according to the amplitude of the input signal, forming an adaptive signal conditioning mechanism, which enables input signals of different amplitudes to be adjusted to a preset optimal processing range; the cutoff frequency of the adaptive filtering circuit is associated with the output of the signal feature extraction unit, and the filter passband and stopband range are dynamically adjusted by obtaining the frequency domain characteristic parameters of the signal in real time.

[0013] The adaptive filtering circuit also includes refined frequency response compensation, building a reconfigurable filtering network at the hardware level, with multiple groups of switchable capacitors and inductors forming the basic filtering unit, and cooperating with a digitally controlled resistor array to achieve programmable adjustment of the filtering parameters;

[0014] The specific process of programmable adjustment is as follows: taking the time domain waveform of the signal as the reference target, the compensation parameters are continuously optimized through iterative calculation. In each iteration, the system performs a correlation analysis between the compensated output signal and the reference signal, calculates the gradient direction of the error function, and dynamically adjusts the filter coefficient weight. In view of the time-varying interference characteristics unique to the ship environment, a frequency response compensation history database is established to record typical interference patterns under different working conditions. When similar working condition characteristics are detected, the historical optimal compensation parameters are preloaded. At the same time, the compensation process also includes a nonlinear distortion correction link, and pre-distortion processing is performed on the phase offset related to the signal amplitude through a polynomial fitting model.

[0015] Among them, the multi-protocol identification algorithm of the synchronization module adopts a multi-level classification strategy. First, it performs coarse classification based on the signal waveform characteristics, then performs fine classification based on statistical characteristics, and finally determines the specific protocol type through protocol feature library matching; the signal feature extraction unit of the synchronization module calculates the rise time, duty cycle and amplitude distribution characteristics of the signal in real time. The said characteristics serve as the basis for protocol identification. When encountering an unknown protocol type, it automatically records the characteristic parameters of the signal and prompts the user to define the protocol.

[0016] Among them, the multi-protocol identification algorithm adopts a three-level classification architecture.

[0017] In the first stage of coarse time-domain waveform classification, the input signal is preprocessed. After preprocessing, the signal enters the time-domain feature extraction stage. Key parameters calculated include the ratio of the signal's peak-to-peak value to the root mean square value, the minimum time interval between adjacent transition edges, the proportion of high-level duration, and zero-crossing rate statistics. Based on these key parameters, the system preliminarily divides the signal into four categories: continuous analog signals, discrete switching signals, pulse trains, and coded digital signals.

[0018] In the second-level statistical feature classification stage, for continuous analog signals, the skewness and kurtosis of the amplitude distribution histogram are calculated to distinguish linear signals from nonlinear logarithmic signals. For discrete switching signals, the time distribution entropy of state switching events is analyzed to determine whether they are random events or periodic events. For pulse sequences, the regularity of pulse intervals is detected through the autocorrelation function to identify fixed-frequency pulses and variable-frequency pulses. For coded digital signals, the Markov transition probability of 0 / 1 jumps in the bit stream is extracted to distinguish different coding rules.

[0019] In the third-level protocol feature library matching stage, the system inputs the feature vectors extracted in the first two levels into the protocol feature library for similarity matching; the feature library uses a graph database to store feature templates, each template contains a standard feature vector and an allowable deviation range; the matching algorithm uses an improved K-nearest neighbor classification method to assign dynamic weights to each feature dimension; when the matching degree exceeds the set upper threshold, the protocol type is directly output; if the matching degree is within the set range, the protocol conflict resolution mechanism is activated, and secondary confirmation is performed through auxiliary means such as check bit verification and frame length verification; for signals with a matching degree lower than the set lower threshold, the system automatically starts the unknown protocol learning mode: recording the complete time domain waveform, statistical characteristics and environmental context information of the signal, generating a temporary protocol identifier and prompting the user to intervene in the definition.

[0020] Among them, the data verification operation of the data processing module adopts a combination of cyclic redundancy check and parity check, the timestamp alignment function is achieved through clock synchronization, and the data compression operation selects lossless or lossy compression algorithm according to the data type.

[0021] Among them, the communication interface module supports automatic conversion of multiple mainstream industrial communication protocols, and dynamically adjusts the output protocol format according to the interface requirements of the ship's upper-level system. The module has a built-in protocol conversion mapping table that stores the field correspondence between various protocols. When a change in the upper-level system protocol is detected, the data encapsulation method is automatically reconfigured to ensure communication continuity. At the same time, the module also has a communication quality monitoring function, which records the bit error rate and delay time of statistical data transmission in real time, and provides a network status reference for the conditioning module.

[0022] Among them, the data acquisition and conditioning module and the synchronization module adopt an isolation method that combines optoelectronic isolation and magnetic isolation. Optoelectronic isolation is used to block common-mode interference, while magnetic isolation is used to suppress noise. The insulating material of the isolation barrier is made of polymer composite material.

[0023] Beneficial effects:

[0024] The hybrid signal universal acquisition access system for ships provided by the present invention realizes adaptive conditioning of multiple types of signals through a data acquisition and conditioning module, a synchronization module automatically identifies and unifies signal formats, a data processing module completes verification and compression, and a communication interface module adapts to different upper-layer systems, forming a closed-loop optimized hybrid signal acquisition architecture, thereby improving the compatibility, real-time performance and reliability of data acquisition in complex ship environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments described in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0026] Figure 1 This is a system structure block diagram provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0027] The following describes the embodiments of the present invention through specific examples. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments. The details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the following embodiments and features in the embodiments can be combined with each other unless they conflict.

[0028] An embodiment of the present application provides a mixed signal universal acquisition and access system for ships, wherein the external device signals received by the system include analog sensor signals, digital switch signals, bus device data, and dedicated interface signals.

[0029] A mixed signal universal acquisition and access system for ships, comprising:

[0030] The data acquisition and conditioning module is used to amplify and filter the external input signal to form a physical layer signal. The data acquisition and conditioning module includes a programmable gain amplifier circuit and an adaptive filter circuit;

[0031] A synchronization module is used to extract and classify features of the physical layer signal and form a standardized digital signal. The synchronization module has a built-in multi-protocol recognition algorithm and a signal feature extraction unit. The protocol recognition algorithm implements unsupervised classification of protocol types based on the signal time domain features and statistical features extracted by the signal feature extraction unit;

[0032] A data processing module is used to process the standardized digital signal to form an application layer data packet after receiving the optimization allocation instruction. The data processing module processes the data including data verification, time stamp alignment and data compression operations;

[0033] The communication interface module is used to analyze the application layer data packets and form a standard communication protocol data stream to be transmitted to the upper system of the ship. Figure 1 shown.

[0034] Under the conditions of high background noise and strong interference in the marine environment, it is very difficult to collect multi-channel and multi-type signals (especially weak signals) in parallel. Therefore, the following methods are used to achieve synchronization in the system:

[0035] Multiple data acquisition and conditioning modules are connected to the CPCI bus. The synchronization module sends the generated time synchronization trigger signal to each data acquisition and conditioning module via the CPCI bus. Upon receiving the synchronization trigger signal, each data acquisition and conditioning module performs synchronous acquisition at the same rising edge and sends the acquired data to the data processing module via the CPCI bus. The data processing module then receives the acquired data and processes it according to the time synchronization stamp, achieving synchronous acquisition and transmission. Multiple data acquisition and conditioning modules are connected to the CPCI bus and send various heterogeneous signals, such as CAN signals, 4mA-20mA, vibration signals, and digital input signals, to the data processing module via the CPCI bus. The acquired data from the data processing module is encapsulated into Ethernet packets according to the protocol and sent to the communication module for external data transmission.

[0036] CAN, switch inputs, and relay outputs do not require conditioning, while analog models such as 4mA-20mA and vibration signals require filtering, amplification, and noise conditioning.

[0037] Shielding is implemented at all levels of the signal chain to resist interference. Each signal cable is twisted into a pair, with the shield of each twisted pair grounded, and the shield of the entire signal cable is grounded.

[0038] The specific working process of each module is described in detail below;

[0039] Data acquisition and conditioning module:

[0040] The programmable gain amplifier circuit of the data acquisition and conditioning module uses a closed-loop feedback control mechanism. Its gain parameters are not fixed settings, but are dynamically adjusted by the synchronization module based on the real-time amplitude characteristics of the input signal, forming a cross-module collaborative optimization mechanism. When the data acquisition and conditioning module detects that the input signal amplitude exceeds the preset threshold, it sends signal status information to the synchronization module. The synchronization module analyzes the signal waveform characteristics and statistical distribution, calculates the optimal gain coefficient, and feeds it back to the data acquisition and conditioning module to achieve online adaptive adjustment of the gain parameters. This dynamic adjustment mechanism can effectively address the problem of large amplitude fluctuations in the output signal of ship sensors, such as the output differences of vibration sensors under different operating conditions of the main engine, ensuring that the signal is always within the optimal quantization range.

[0041] The design of the adaptive filter circuit in the data acquisition and conditioning module deeply integrates signal feature extraction technology. Its cutoff frequency is linked to the output of the signal feature extraction unit in the synchronization module. By acquiring the signal's frequency domain characteristic parameters in real time, the filter's passband and stopband ranges are dynamically adjusted. For example, when electromagnetic interference in a specific frequency band is detected in the input signal, the filter automatically generates a notch characteristic to suppress the interference component while maintaining a flat response within the signal's effective frequency band. In addition, the filter circuit adopts a hybrid filter structure, combining the real-time performance of analog filtering with the programmability of digital filtering. This achieves rapid noise suppression at the hardware level while performing refined frequency response compensation through software algorithms. The data acquisition and conditioning module can automatically filter out interference components in specific frequency bands. This design enables the system to adapt to the complex electromagnetic environment of ships and reliably access signals of various strengths.

[0042] Refined frequency response compensation is the core technology of the adaptive filter circuit in the data acquisition and conditioning module. Essentially, it dynamically adjusts the filter's frequency response to offset the distortion caused by the ship's complex electromagnetic environment. This technology first constructs a reconfigurable filter network at the hardware level. Multiple groups of switchable capacitors and inductors form the basic filter unit, which, combined with a digitally controlled resistor array, enables software-programmable adjustment of filter parameters (such as cutoff frequency and quality factor). When a signal enters the adaptive filter circuit, a real-time spectrum analysis unit simultaneously collects the signal's spectral distribution characteristics, extracts the amplitude and phase information of the main frequency components through a fast Fourier transform, and compares this information with a library of ideal signal models. If abnormal attenuation or gain is detected in a specific frequency band (such as the 50Hz-5kHz range, where power system harmonic interference is concentrated), a control algorithm generates a compensation parameter matrix to drive the filter network to reconstruct the frequency response curve. For example, if an 8dB attenuation is detected at 1.2kHz, the system generates an inverse gain peak near this frequency to compensate, while simultaneously suppressing the gain of adjacent frequency bands to prevent resonance. At the software level, the compensation algorithm utilizes a minimum mean square error adaptive algorithm, using the original signal's time-domain waveform as a reference target. Compensation parameters are continuously optimized through iterative calculations. During each iteration, the system performs a correlation analysis between the compensated output signal and the reference signal, calculates the gradient direction of the error function, and dynamically adjusts the coefficient weights in the digital filter. To address the unique time-varying interference characteristics of shipboard environments, the system also establishes a frequency response compensation history database, recording typical interference patterns under different operating conditions (such as engine startup and radar operation). When similar operating conditions are detected, the system preloads historically optimized compensation parameters, significantly improving response speed. The compensation process also includes nonlinear distortion correction, using a polynomial fitting model to pre-distort signal amplitude-dependent phase offsets, ensuring full-band fidelity for signals with a wide dynamic range. This compensation mechanism, combining hardware reconfigurability with software adaptability, enables the system to suppress interference in the sub-200 MHz band while keeping signal amplitude distortion within ±0.5 dB and phase offset below 2 degrees.

[0043] A composite isolation scheme combining optoelectronic and magnetic isolation is used between the data acquisition and conditioning module and the synchronization module. Optoelectronic isolation blocks low-frequency common-mode interference, while magnetic isolation suppresses high-frequency noise. The isolation barrier is made of corrosion-resistant polymer composite material to meet the long-term stability requirements of the high-humidity and high-salt fog environments of ships. Signal transmission between modules uses differential signaling to further reduce the impact of electromagnetic interference on signal quality.

[0044] Synchronization module:

[0045] Technical details of the synchronization module's multi-protocol identification algorithm and signal feature extraction unit. The multi-protocol identification algorithm's three-level classification architecture forms the foundation for the protocol conversion module's intelligent analysis of mixed signals. Its core principle is to gradually narrow the protocol identification scope through a progressive analysis strategy, ultimately achieving accurate classification. In the first-level, coarse time-domain waveform classification phase, the algorithm preprocesses the input signal, including baseline calibration to eliminate DC offset and sliding window filtering to smooth glitches. The preprocessed signal then enters the time-domain feature extraction phase, where key parameters are calculated, including the ratio of the signal's peak-to-peak value to its RMS value (for analog / digital signal identification), the minimum time interval between adjacent transition edges (for pulse frequency identification), the proportion of high-level duration (for duty cycle calculation), and zero-crossing rate statistics (for distinguishing periodic from non-periodic signals). Based on these parameters, the system preliminarily classifies the signal into four categories: continuous analog signals (such as 4-20mA sensor output), discrete switching signals (such as relay status), pulse trains (such as speed sensor signals), and encoded digital signals (such as bus data). In the second-level, detailed statistical feature classification phase, further in-depth analysis is performed on each signal category. For continuous analog signals, the skewness and kurtosis of the amplitude distribution histogram are calculated to distinguish linear signals (skewness close to 0) from nonlinear logarithmic signals (such as decibel values). For discrete switching signals, the temporal entropy of state switching events is analyzed to determine whether they are random or periodic. For pulse trains, the regularity of pulse intervals is detected using the autocorrelation function to distinguish between fixed-frequency and variable-frequency pulses. For coded digital signals, the Markov transition probabilities of 0 / 1 transitions in the bitstream are extracted to distinguish between different encoding schemes such as Manchester and NRZ encoding. In the third-level protocol feature library matching stage, the system inputs the 42-dimensional feature vectors extracted from the first two stages into the protocol feature library for similarity matching. The feature library uses a graph database to store feature templates for thousands of protocols. Each template contains a standard feature vector and an allowable deviation range. The matching algorithm uses a modified K-nearest neighbor classification method, assigning dynamic weights to each feature dimension (for example, time-sensitive signals place greater emphasis on temporal features). When the matching degree exceeds 85%, the protocol type is directly output; if the matching degree is in the range of 60%-85%, the protocol conflict resolution mechanism is activated, and secondary confirmation is performed through auxiliary means such as check bit verification and frame length verification; for signals with a matching degree lower than 60%, the system automatically starts the unknown protocol learning mode: recording the complete time domain waveform, statistical characteristics and environmental context information of the signal, generating a temporary protocol identifier and prompting the user to intervene in the definition. After the new protocol is manually confirmed, its feature vector is automatically added to the protocol feature library, and online incremental training is triggered to update the classification model parameters. For new protocols that are not registered in the feature library, the system automatically starts the learning mode, records the time domain and statistical characteristics of the signal, and generates a temporary protocol identifier for the user to define later.

[0046] The signal feature extraction unit utilizes a parallel computing architecture, running multiple feature extraction threads simultaneously, each performing real-time calculations on different signal dimensions. For example, the time-domain analysis thread continuously monitors the signal's rise time and overshoot, the frequency-domain analysis thread calculates the primary frequency components and their harmonic distribution, and the statistics thread generates amplitude histograms and autocorrelation function curves. This feature data is not only used for protocol identification, but also for standardization in the synchronization module. The data reconstruction phase parses the original signal into valid data fields according to the protocol specification, while the format encapsulation phase adds metadata such as timestamps, protocol type identifiers, and checksums to create an intermediate standard format. This module also features protocol conversion anomaly detection. When data field checksum errors or protocol logic conflicts are detected, it automatically triggers a resampling mechanism or requests data retransmission from the upstream module to ensure the reliability of the conversion process. Furthermore, the synchronization module and the communication interface module share a protocol information library, which uses an object-oriented data structure to store protocol field definitions, encoding rules, and semantic interpretations, ensuring semantic consistency throughout the entire data acquisition and transmission process.

[0047] Data processing module:

[0048] Data verification utilizes a layered verification mechanism, implementing a rapid parity check on basic data and applying a cyclic redundancy check (CRC) and Hamming code double check to critical control instruction data, forming a three-tiered verification protection system. Abnormal data detected during verification triggers a hierarchical processing mechanism: minor errors trigger a local error correction algorithm to attempt repair, while severe errors are marked as invalid data and initiate a data retransmission process. Timestamp alignment is implemented using a high-precision clock synchronization network. The master clock module utilizes a complementary clock source, combining satellite timing with atomic clocks, and broadcasts a time reference to all distributed collection nodes via the Precision Time Protocol. When receiving data, the data processing module calculates transmission delays and compensates for time deviations, ensuring that data collected from different physical locations has a unified time scale. Data compression utilizes an intelligent compression strategy. A lossy compression algorithm is used for continuous signals such as equipment status monitoring to minimize data volume within the allowable error range; a lossless compression algorithm is used for discrete signals such as control instructions to ensure data integrity. In addition, the data processing module has an adaptive degradation function. When it detects that system resources are close to saturation, it automatically reduces the processing accuracy of non-critical data to prioritize the normal operation of core functions. This elastic processing mechanism significantly improves the system's ability to resist overload.

[0049] Communication interface module:

[0050] The communication interface module features adaptive protocol conversion and communication quality assurance mechanisms. This module has a built-in protocol conversion engine that stores a library of mappings for hundreds of industrial communication protocols. It automatically parses the upper-layer system's protocol handshake signals and intelligently selects the optimal conversion solution. Upon detecting a protocol change in the upper-layer system, the conversion engine uses a protocol signature matching algorithm to complete the protocol switch within milliseconds, employing a data buffering mechanism to prevent communication interruptions. The protocol mapping table uses a tree-like structure to store protocol field correspondences and supports dynamic updates and user-defined extensions, ensuring rapid integration of new protocols. The communication quality monitoring unit analyzes link layer bit error rate, signal strength, and transmission delay parameters in real time to construct a communication quality assessment matrix, providing a basis for decision-making. Upon detecting communication quality degradation, the module automatically initiates a channel optimization process, including adjusting transmit power, switching to an alternate channel, or enabling forward error correction coding. The module also features a protocol conversion exception fuse mechanism. If protocol parsing errors exceed a set threshold, the module automatically falls back to safe communication mode to prevent erroneous data from spreading and impacting the upper-layer system. The physical layer design of the communication interface module adopts a hybrid interface of multi-mode optical fiber and shielded twisted pair, which can flexibly select the transmission medium according to the on-site environment. In areas with strong interference, optical fiber channels are given priority to ensure signal quality.

[0051] Furthermore, the data acquisition and conditioning module and the synchronization module are designed with composite isolation technology and environmental adaptability. The electrical isolation between the two modules utilizes a composite architecture combining optoelectronic coupling and magnetic isolation in series. The optoelectronic isolation unit blocks low-frequency common-mode interference, while the magnetic isolation unit suppresses high-frequency noise, forming a full-band interference protection system. The insulation material used in the isolation circuit is a polyimide-based composite material, which is resistant to high temperatures, moisture, and salt spray corrosion, ensuring long-term stable operation in the harsh ship environment. The isolation parameter design incorporates an adaptive adjustment mechanism that automatically reduces the isolation capacitance value to minimize signal distortion when transmitting high-frequency signals and improves the common-mode rejection ratio to enhance anti-interference capabilities when transmitting low-frequency signals. The signal transmission path utilizes differential balanced transmission technology, coupled with shielded twisted-pair connectors, to effectively suppress electromagnetic radiation interference. The feedback control channel between modules is designed with an isolated digital interface that uses Manchester encoding to transmit control commands, ensuring both signal integrity and electrical isolation. To address the unique vibration environments of ships, the connector features a locking, anti-vibration design, the internal circuit board is potted, and key components use military-grade anti-vibration components to ensure reliable connections even under continuous mechanical vibration. Furthermore, the module housing utilizes a sealed aluminum alloy structure with an anodized and conformal coating to meet IP67 protection requirements, effectively preventing seawater salt spray corrosion and condensation.

[0052] Specifically, the synchronization module and the communication interface module collaborate and implement a data semantics assurance mechanism. The two modules implement end-to-end data format conversion through a shared protocol description information library. This library uses an object-oriented data model to store the physical layer characteristics, data link layer format, and application layer semantic information of protocol fields. When converting signals to an intermediate standard format, the synchronization module adds semantic tags to each data field, mapping these tags to metadata in the protocol description information library. When converting the intermediate format to the upper-layer system protocol, the communication interface module reorganizes fields and performs encoding conversion based on the semantic tags to ensure unambiguous data meaning during the conversion process. For example, when converting an analog signal from an oil pressure sensor to the MODBUS protocol, the synchronization module annotates it with "pressure value_engineering unit," and the communication interface module uses this tag to match the register address and dimensional conversion coefficient of the target protocol. For protocol version upgrades or custom protocol extensions, the system provides a visual configuration tool that allows users to define the field structure of the new protocol using drag-and-drop functionality. This configuration information is automatically synchronized to the protocol description information library, and the corresponding conversion rules are generated. When detecting missing protocol fields or semantic conflicts, the system initiates a negotiation mechanism: first, it attempts adaptive repairs based on the compatibility rules of the protocol description database. If the repair fails, it triggers a security isolation process, temporarily storing the abnormal data in a buffer and sending an exception alert to the upper-level system. This layered conversion architecture not only ensures data format compatibility but, more importantly, maintains data semantic integrity, ensuring consistent interpretation of the same data item across different subsystems.

[0053] The above embodiments are merely illustrative of the principles and effects of the present invention and are not intended to limit the present invention. Anyone skilled in the art may modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or alterations made by one of ordinary skill in the art without departing from the spirit and technical principles disclosed herein are intended to be covered by the claims of the present invention.

Claims

1. A universal mixed signal acquisition and access system for ships, characterized in that: include: The data acquisition and conditioning module is used to amplify and filter the external input signal to form a physical layer signal. The data acquisition and conditioning module includes a programmable gain amplifier circuit and an adaptive filter circuit; A synchronization module is used to extract and classify features of the physical layer signal and form a standardized digital signal. The synchronization module has a built-in multi-protocol recognition algorithm and a signal feature extraction unit. The protocol recognition algorithm implements unsupervised classification of protocol types based on the signal time domain features and statistical features extracted by the signal feature extraction unit; A data processing module is used to process the standardized digital signal to form an application layer data packet after receiving the optimization allocation instruction. The data processing module processes the data including data verification, time stamp alignment and data compression operations; The communication interface module is used to analyze application layer data packets and form standard communication protocol data streams to be transmitted to the ship's upper system.

2. The hybrid signal universal acquisition and access system for ships according to claim 1, characterized in that: The programmable gain amplifier circuit of the data acquisition and conditioning module operates in a closed-loop control mode, and its gain parameter is dynamically adjusted by the synchronization module according to the amplitude of the input signal, forming an adaptive signal conditioning mechanism. This mechanism adjusts input signals of different amplitudes to a preset optimal processing range; the cutoff frequency of the adaptive filter circuit is associated with the output of the signal feature extraction unit, and the filter passband and stopband range are dynamically adjusted by obtaining the frequency domain characteristic parameters of the signal in real time.

3. The hybrid signal universal acquisition and access system for ships according to claim 2, characterized in that: The adaptive filtering circuit also includes refined frequency response compensation, building a reconfigurable filtering network at the hardware level, with multiple groups of switchable capacitors and inductors forming the basic filtering unit, and cooperating with a digitally controlled resistor array to achieve programmable adjustment of the filtering parameters; The specific process of programmable adjustment is as follows: using the time domain waveform of the signal as a reference target, the compensation parameters are continuously optimized through iterative calculation. In each iteration, the system performs a correlation analysis between the compensated output signal and the reference signal, calculates the gradient direction of the error function, and dynamically adjusts the filter coefficient weights; In view of the time-varying interference characteristics unique to ship environments, a frequency response compensation history database is established to record typical interference patterns under different working conditions. When similar working condition characteristics are detected, the historical optimal compensation parameters are preloaded. At the same time, the compensation process also includes a nonlinear distortion correction link, and pre-distortion processing is performed on the phase offset related to the signal amplitude through a polynomial fitting model.

4. The hybrid signal universal acquisition and access system for ships according to claim 1, characterized in that: The synchronization module's multi-protocol identification algorithm adopts a multi-level classification strategy. It first performs coarse classification based on signal waveform characteristics, then performs fine classification based on statistical characteristics, and finally determines the specific protocol type through protocol feature library matching. The synchronization module's signal feature extraction unit calculates the signal's rise time, duty cycle, and amplitude distribution characteristics in real time. These characteristics serve as the basis for protocol identification. When encountering an unknown protocol type, it automatically records the signal's characteristic parameters and prompts the user to define the protocol.

5. The hybrid signal universal acquisition and access system for ships according to claim 4, characterized in that: The multi-protocol identification algorithm adopts a three-level classification architecture. In the first stage of coarse time-domain waveform classification, the input signal is preprocessed. After preprocessing, the signal enters the time-domain feature extraction stage. Key parameters calculated include the ratio of the signal's peak-to-peak value to the root mean square value, the minimum time interval between adjacent transition edges, the proportion of high-level duration, and zero-crossing rate statistics. Based on these key parameters, the system preliminarily divides the signal into four categories: continuous analog signals, discrete switching signals, pulse trains, and coded digital signals. In the second-level statistical feature classification stage, for continuous analog signals, the skewness and kurtosis of the amplitude distribution histogram are calculated to distinguish linear signals from nonlinear logarithmic signals. For discrete switching signals, the time distribution entropy of state switching events is analyzed to determine whether they are random events or periodic events. For pulse sequences, the regularity of pulse intervals is detected through the autocorrelation function to identify fixed-frequency pulses and variable-frequency pulses. For coded digital signals, the Markov transition probability of 0 / 1 jumps in the bit stream is extracted to distinguish different coding rules. In the third-level protocol feature library matching stage, the system inputs the feature vectors extracted in the first two levels into the protocol feature library for similarity matching; the feature library uses a graph database to store feature templates, each template contains a standard feature vector and an allowable deviation range; the matching algorithm uses an improved K-nearest neighbor classification method to assign dynamic weights to each feature dimension; when the matching degree exceeds the set upper threshold, the protocol type is directly output; if the matching degree is within the set range, the protocol conflict resolution mechanism is activated, and secondary confirmation is performed through auxiliary means such as check bit verification and frame length verification; for signals with a matching degree lower than the set lower threshold, the system automatically starts the unknown protocol learning mode: recording the complete time domain waveform, statistical characteristics and environmental context information of the signal, generating a temporary protocol identifier and prompting the user to intervene in the definition.

6. The hybrid signal universal acquisition and access system for ships according to claim 1, characterized in that: The data processing module's data verification operation uses a combination of cyclic redundancy check and parity check. The timestamp alignment function is achieved through clock synchronization. The data compression operation selects lossless or lossy compression algorithm according to the data type.

7. The hybrid signal universal acquisition and access system for ships according to claim 1, characterized in that: The communication interface module supports automatic conversion of multiple mainstream industrial communication protocols and dynamically adjusts the output protocol format according to the interface requirements of the ship's upper-level system. The module has a built-in protocol conversion mapping table that stores the field correspondence between various protocols. When a change in the upper-level system protocol is detected, the module automatically reconfigures the data encapsulation method to ensure communication continuity. At the same time, the module also has a communication quality monitoring function, which records the bit error rate and delay time of statistical data transmission in real time, providing a network status reference for the conditioning module.

8. The hybrid signal universal acquisition and access system for ships according to claim 1, characterized in that: The data acquisition and conditioning module and the synchronization module are isolated by a combination of photoelectric isolation and magnetic isolation. Photoelectric isolation is used to block common-mode interference, while magnetic isolation is used to suppress noise. The insulating material of the isolation barrier is made of polymer composite material.

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