A mixed signal universal acquisition access system for a ship

Abstract

The application belongs to the technical field of ship data acquisition and signal processing, and particularly relates to a mixed signal general acquisition access system for a ship, which comprises a data acquisition and conditioning module, a synchronization module, a data processing module and a communication interface module. The mixed signal general acquisition access system realizes adaptive conditioning of multiple types of signals through the data acquisition and conditioning module, automatically identifies and unifies signal formats through the synchronization module, completes verification and compression through the data processing module, and adapts to different upper-layer systems through the communication interface module, so as to form a closed-loop optimized mixed signal acquisition architecture and improve the compatibility, real-time performance and reliability of data acquisition under a complex environment of the ship.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of ship data acquisition and signal processing, and particularly relates to a mixed signal general acquisition access system for a ship. BACKGROUND

[0002] A large number of heterogeneous signals need to be collected during the operation of a ship, including analog sensor output, digital switching quantity, bus device data and special interface signals. Traditional acquisition systems usually adopt a discrete design, and special acquisition equipment is deployed for different signal types, resulting in complex system structure, poor expandability and difficult maintenance. The ship environment has strong electromagnetic interference, mechanical vibration, high humidity and high salt, and the signal isolation and anti-interference ability of conventional acquisition equipment is insufficient, which easily causes data distortion or loss.

[0003] In the prior art, the signal conditioning circuit is designed with fixed parameters, which cannot adapt to the output characteristics of different sensors, and the gain and filter parameters need to be adjusted manually, which is tedious and prone to errors. Protocol conversion usually relies on a pre-set protocol library, and when facing new or non-standard protocols, the system needs to be upgraded, which affects the continuity of the system. The resource allocation usually adopts a static strategy, which cannot be dynamically adjusted according to the signal priority and system load, and critical data may be delayed due to resource competition. The data processing link lacks a unified time reference, and the data of distributed acquisition nodes is difficult to accurately synchronize, which affects subsequent analysis and decision-making. The communication interface is usually bound to a specific protocol, and additional conversion equipment is needed when connecting with different upper-layer systems, which increases the cost and failure points.

[0004] Although the existing patents involve ship data acquisition, they mostly focus on a single signal type or local optimization, and lack a systematic solution to the unified access, intelligent adaptation and global resource scheduling of mixed signals. The International Maritime Organization has higher requirements for ship intelligence, and there is an urgent need for a general acquisition system that can be compatible with multiple signals, adapt to environmental changes and dynamically optimize resources, to support advanced applications such as state monitoring and fault warning. The present application addresses the above-mentioned pain points by implementing full-process optimization through modular architecture and intelligent algorithms, filling the technical gap in this field. SUMMARY

[0005] In view of the shortcomings of the prior art, the present application aims to provide a mixed signal general acquisition access system for a ship, which solves the problem of unified acquisition, adaptive processing and dynamic resource optimization of multiple source heterogeneous signals of a ship.

[0006] The technical scheme of the present application is as follows:

[0007] A mixed signal general acquisition access system for a ship, comprising:

[0008] The data acquisition and conditioning module is used for gain amplification and filtering processing of external input signals to form physical layer signals, and comprises a programmable gain amplification circuit and an adaptive filtering circuit.

[0009] The synchronization module is used for feature extraction and classification of the physical layer signals to form standardized digital signals, and comprises a multi-protocol identification algorithm and a signal feature extraction unit. The protocol identification algorithm realizes unsupervised classification of protocol types based on signal time domain features and statistical features extracted by the signal feature extraction unit.

[0010] The data processing module is used for processing the standardized digital signals to form application layer data packets after receiving an optimized allocation instruction, and the processing includes data verification, timestamp alignment and data compression operations.

[0011] The communication interface module is used for analyzing the application layer data packets to form standard communication protocol data streams and transmitting the data streams to a shipboard upper layer system.

[0012] The programmable gain amplification circuit of the data acquisition and conditioning module works 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 to form an adaptive signal conditioning mechanism. The mechanism 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. By real-time acquisition of the frequency domain feature parameters of the signal, the passband and stopband range of the filter is dynamically adjusted.

[0013] The adaptive filtering circuit further comprises a fine frequency response compensation. A reconfigurable filtering network is constructed at the hardware level, and a plurality of groups of switchable capacitors and inductors are used to form basic filtering units. In combination with a numerical control resistance array, programmable adjustment of filtering parameters is realized.

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

[0015] The multi-protocol identification algorithm of the synchronization module adopts a multi-stage classification strategy, first performs coarse classification according to signal waveform characteristics, then performs fine classification in combination with statistical characteristics, and finally determines the specific protocol type through protocol characteristic 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, and the characteristics serve as the basis for protocol identification; when an unknown protocol type is encountered, the feature parameters of the signal are automatically recorded and the user is prompted to define the protocol.

[0016] The multi-protocol identification algorithm adopts a three-stage classification architecture,

[0017] In the first-stage time-domain waveform coarse classification stage, the input signal is first preprocessed, the preprocessed signal enters the time-domain feature extraction link, and the key parameters including the proportional relationship between the signal peak-to-peak value and the root mean square value, the minimum time interval of adjacent jump edges, the high-level duration ratio and the zero-crossing rate statistics are calculated; based on the key parameters, the system preliminarily divides the signal into four categories: continuous analog signal, discrete switching signal, pulse sequence and coded digital signal;

[0018] In the second-stage statistical feature fine classification stage, for the continuous analog signal, the skewness and kurtosis of the amplitude distribution histogram are calculated to distinguish linear signals from nonlinear logarithmic signals; for the discrete switching signal, the time distribution entropy value of the state switching event is analyzed to determine whether it is a random event or a periodic event; for the pulse sequence, the regularity of the pulse interval is detected through the autocorrelation function to identify fixed frequency pulses and variable frequency pulses; for the coded digital signal, the Markov transition probability of 0 / 1 transitions in the bit stream is extracted to distinguish different coding rules;

[0019] In the third-stage protocol characteristic library matching stage, the system inputs the feature vectors extracted in the previous two stages into the protocol characteristic library for similarity matching; the characteristic library stores feature templates in a graph database, each template containing a standard feature vector and an allowed deviation range; the matching algorithm adopts an improved K-nearest neighbor classification method, and assigns dynamic weights to each feature dimension; when the matching degree exceeds the upper limit of the set threshold, the protocol type is directly output; if the matching degree is in the set interval, the protocol conflict resolution mechanism is started, and secondary confirmation is performed through the auxiliary means of check bit verification and frame length verification; for the signal with a matching degree lower than the lower limit of the set threshold, the system automatically starts the unknown protocol learning mode: records the complete time-domain waveform, statistical characteristics and environmental context information of the signal, generates a temporary protocol identifier and prompts the user to intervene in the definition.

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

[0021] The communication interface module supports automatic conversion of multiple mainstream industrial communication protocols, dynamically adjusts the output protocol format according to the interface requirements of the shipboard upper system, the module is built-in protocol conversion mapping table, stores the field corresponding relationship between various protocols, when detecting the upper system protocol change, automatically reconfigures the data encapsulation mode, ensures the continuity of communication, at the same time, the module also has the communication quality monitoring function, real-time statistics data transmission error rate and delay time, provides the network state reference for the conditioning module.

[0022] The data acquisition conditioning module and the synchronization module adopt the isolation mode combining photoelectric isolation and magnetic isolation, the photoelectric isolation is used for blocking common mode interference, and the magnetic isolation is used for inhibiting noise, and the insulation material of the isolation barrier is selected from a high molecular composite material.

[0023] Beneficial effects:

[0024] The mixed signal universal acquisition access system for a ship provided by the application realizes adaptive conditioning of multiple types of signals through a data acquisition conditioning module, automatically identifies and unifies signal formats through a synchronization module, completes verification and compression through a data processing module, and adapts to different upper systems through a communication interface module, so that a closed-loop optimized mixed signal acquisition architecture is formed, and the compatibility, real-time performance and reliability of data acquisition in a complex environment of a ship are improved. BRIEF DESCRIPTION OF DRAWINGS

[0025] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments described in the present application, and other drawings can also be obtained by those skilled in the art based on these drawings.

[0026] Figure 1 The system structure block diagram provided by the embodiments of the present application. DETAILED DESCRIPTION

[0027] The embodiments of the present application will be described below through specific concrete examples, and those skilled in the art can easily understand other advantages and effects of the present application from the content disclosed in the present specification. The present application can also be implemented or applied through other different specific embodiments, and each detail in the present specification can be modified or changed based on different viewpoints and applications without departing from the spirit of the present application. It should be noted that the following embodiments and features in the embodiments can be combined with each other without conflict.

[0028] The mixed signal universal acquisition access system for a ship provided by the embodiments of the present application, the external device signals received by the system include analog sensor signals, digital switch signals, bus device data and special interface signals.

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

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

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

[0032] The data processing module receives optimization allocation instructions and processes standardized digital signals to form application layer data packets. The data processing module performs operations including data verification, timestamp alignment, and data compression.

[0033] The communication interface module is used to analyze application layer data packets and form a standard communication protocol data stream for transmission to the ship's upper-level system. The system structure provided in this embodiment is as follows: Figure 1 As shown.

[0034] In marine environments with high background noise and strong interference, it is very difficult to achieve universal parallel synchronous acquisition of multiple channels and various types of signals (especially weak signals). Therefore, the following method is used in the system to achieve synchronization:

[0035] Multiple data acquisition and conditioning modules are connected to the CPCI bus. The synchronization module sends a 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 synchronously acquired data to the data processing module via the CPCI bus. The data processing module receives the acquired data and performs packet processing according to the time synchronization stamp to achieve synchronous acquisition and transmission. Multiple data acquisition and conditioning modules connected to the CPCI bus send various heterogeneous signals, such as CAN signals, 4mA-20mA signals, vibration signals, and switch input signals, to the data processing module via the CPCI bus. The data acquired by the data processing module is encapsulated into Ethernet data packets according to the protocol and sent to the communication module to achieve external data transmission.

[0036] CAN, digital input, and relay output do not require conditioning, while analog signals such as 4mA-20mA and vibration signals require filtering, amplification, and noise conditioning.

[0037] Shielding design is implemented on each level of the signal link to resist interference. Each signal cable is twisted-pair, each twisted pair is covered with a shield and grounded, and the entire signal cable is covered with a shield and grounded.

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

[0039] Data acquisition and conditioning module:

[0040] The programmable gain amplifier circuit of the data acquisition and conditioning module adopts a closed-loop feedback control mechanism. Its gain parameter is not fixed but 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 a 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, achieving online adaptive adjustment of the gain parameter. This dynamic adjustment mechanism effectively addresses the problem of large fluctuations in the output signal amplitude of shipboard 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 adaptive filtering circuit of the data acquisition and conditioning module deeply integrates signal feature extraction technology. Its cutoff frequency is correlated with the output of the signal feature extraction unit in the synchronization module. By acquiring the frequency domain characteristic parameters of the signal in real time, the passband and stopband range of the filter are dynamically adjusted. For example, when electromagnetic interference of 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 effective frequency band of the signal. In addition, the filtering circuit adopts a hybrid filter structure, combining the real-time performance of analog filtering with the programmability of digital filtering. This achieves fast noise suppression at the hardware level while performing fine-grained frequency response compensation through software algorithms. The data acquisition and conditioning module can automatically filter out interference components of specific frequency bands. This design enables the system to reliably access signals of various intensities in the complex electromagnetic environment of a ship.

[0042] Refined frequency response compensation is the core technology of the adaptive filtering circuit in the data acquisition and conditioning module. Essentially, it compensates for the distortion caused by the complex electromagnetic environment of the ship by dynamically adjusting the frequency response characteristics of the filter. This technology first constructs a reconfigurable filtering network at the hardware level. The basic filtering unit consists of multiple sets of switchable capacitors and inductors, combined with a numerically controlled resistor array to achieve software-programmable adjustment of filter parameters (such as cutoff frequency and quality factor). When a signal enters the adaptive filtering circuit, the real-time spectrum analysis unit synchronously acquires the signal's spectral distribution characteristics, extracts the amplitude and phase information of the main frequency components through fast Fourier transform, and compares it with an ideal signal model library. 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), the control algorithm generates a compensation parameter matrix to drive the filtering network to reconstruct the frequency response curve. For example, when an 8dB attenuation is detected at 1.2kHz, the system generates an inverse gain peak near that frequency for compensation, while suppressing the gain of adjacent frequency bands to avoid resonance. At the software level, the compensation algorithm employs a minimum mean square error adaptive algorithm, using the time-domain waveform of the original signal as a reference target and continuously optimizing the compensation parameters through iterative calculations. In each iteration, the system performs 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 time-varying interference characteristics unique to the ship environment, the system also establishes a frequency response compensation history database, recording typical interference patterns under different operating conditions (such as main engine startup and radar operation). When similar operating condition characteristics are detected, the system preloads the historically optimal compensation parameters, significantly improving response speed. The compensation process also includes a nonlinear distortion correction stage, using a polynomial fitting model to pre-distort the phase shift related to signal amplitude, ensuring full-band fidelity of the large dynamic range signal. This compensation mechanism, combining hardware reconfigurability and software adaptation, enables the system to suppress interference in frequency bands below 200MHz while controlling signal amplitude distortion within ±0.5dB and phase shift within 2 degrees.

[0043] The data acquisition and conditioning module and the synchronization module employ a composite isolation scheme combining opto-isolation and magnetic isolation. Opto-isolation blocks low-frequency common-mode interference, while magnetic isolation suppresses high-frequency noise. The insulation material of the isolation barrier is a corrosion-resistant polymer composite material, meeting the long-term stable operation requirements of the ship's high-humidity and high-salt-spray environment. Differential signal transmission is used between modules to further reduce the impact of electromagnetic interference on signal quality.

[0044] Synchronization module:

[0045] Technical details of the multi-protocol identification algorithm and signal feature extraction unit in the synchronization module. The three-level classification architecture of the multi-protocol identification algorithm is the basic framework for the protocol conversion module to achieve intelligent analysis of mixed signals. Its core lies in gradually narrowing the protocol identification range through a progressive analysis strategy, ultimately achieving accurate classification. In the first-level coarse classification stage of time-domain waveform, the algorithm first preprocesses the input signal, including baseline calibration to eliminate DC offset and sliding window filtering to smooth glitch noise. The preprocessed signal enters the time-domain feature extraction stage, calculating key parameters including: the ratio of signal peak-to-peak value to root mean square value (to determine analog / digital signals), the minimum time interval between adjacent transition edges (to identify the upper limit of pulse frequency), the proportion of high-level duration (to calculate duty cycle), and zero-crossing rate statistics (to distinguish periodic signals from aperiodic signals). Based on these parameters, the system initially classifies the signals into four categories: continuous analog signals (such as 4-20mA sensor output), discrete switching signals (such as relay status), pulse sequences (such as speed sensor signals), and coded digital signals (such as bus data). In the second-level detailed classification stage of statistical features, further in-depth analysis is performed on each type of signal. For continuous analog signals, the skewness and kurtosis of their 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 distribution entropy of state switching events is analyzed to determine whether they are random or periodic events. For pulse sequences, the regularity of pulse intervals is detected through autocorrelation functions to identify fixed-frequency pulses 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 rules such as Manchester encoding and NRZ encoding. In the third-level protocol feature library matching stage, the system inputs the 42-dimensional 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 for thousands of protocols, each template containing a standard feature vector and an allowable deviation range. The matching algorithm uses an improved K-nearest neighbor classification method, assigning dynamic weights to each feature dimension (e.g., time-sensitive signals pay more attention to time features). When the matching degree exceeds 85%, the protocol type is output directly. If the matching degree is between 60% and 85%, a protocol conflict resolution mechanism is activated, using auxiliary methods such as checksum verification and frame length verification for secondary confirmation. For signals with a matching degree below 60%, the system automatically activates 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 manual confirmation, the feature vector of a new protocol is automatically added to the protocol feature library, and online incremental training is triggered to update the classification model parameters. For new protocols not registered in the feature library, the system automatically activates 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 employs a parallel computing architecture, running multiple feature extraction threads simultaneously to perform real-time calculations on different dimensions of the signal's characteristics. For example, the time-domain analysis thread continuously monitors the signal's rise time and overshoot, the frequency-domain analysis thread calculates the main frequency components and their harmonic distributions, and the statistical thread generates amplitude histograms and autocorrelation function curves. This feature data is used not only for protocol identification. The standardization process of the synchronization module includes two stages: data reconstruction and format encapsulation. The data reconstruction stage parses the original signal into valid data fields according to the protocol specifications, while the format encapsulation stage adds metadata such as timestamps, protocol type identifiers, and checksums to form an intermediate standard format. This module also has a protocol conversion anomaly detection function. When a data field verification error or protocol logic conflict is detected, a resampling mechanism is automatically triggered or a data retransmission request is sent to the upstream module to ensure the reliability of the conversion process. In addition, the synchronization module and the communication interface module share a protocol information database. This database 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 employs a layered verification mechanism. Basic data undergoes rapid screening using parity checks, while critical control command data is subject to dual verification using cyclic redundancy check and Hamming code checks, forming a three-tiered verification and protection system. Abnormal data detected during verification triggers a tiered processing mechanism: minor errors are corrected using local error correction algorithms, while serious errors are marked as invalid and a data retransmission process is initiated. Timestamp alignment relies on a high-precision clock synchronization network. The master clock module uses a complementary clock source of satellite timing and atomic clocks, broadcasting the time reference to each distributed acquisition node via a precise time protocol. The data processing module calculates transmission delays and compensates for time deviations upon receiving data, ensuring a unified time stamp system for data collected from different physical locations. The data compression stage employs an intelligent compression strategy. Continuous signals such as equipment status monitoring utilize lossy compression algorithms to minimize data volume within permissible error ranges; discrete signals such as control commands use lossless compression algorithms to ensure data integrity. In addition, the data processing module has an adaptive degradation function. When the system resources are detected to be close to saturation, it automatically reduces the processing precision of non-critical data and prioritizes the normal operation of core functions. This elastic processing mechanism significantly improves the system's overload resistance.

[0049] Communication interface module:

[0050] The communication interface module features an adaptive protocol conversion and communication quality assurance mechanism. This module has a built-in protocol conversion engine that stores a mapping library containing hundreds of industrial communication protocols. It can automatically parse the protocol handshake signals of the upper-layer system and intelligently match the optimal conversion scheme. When a protocol change is detected in the upper-layer system, the conversion engine completes the protocol switching within milliseconds using a protocol feature matching algorithm, employing a data buffering mechanism to avoid communication interruption. The protocol mapping table uses a tree structure to store the correspondence between protocol fields, supporting dynamic updates and user-defined expansions to ensure rapid access to new protocols. The communication quality monitoring unit analyzes the bit error rate, signal strength, and transmission delay parameters of the link layer in real time, constructing a communication quality evaluation matrix to provide decision-making support. When communication quality degradation is detected, a channel optimization program is automatically initiated, including adjusting transmit power, switching to a backup channel, or enabling forward error correction coding. The module also features a protocol conversion anomaly circuit breaker mechanism. When consecutive protocol parsing errors exceed a set threshold, it automatically falls back to a safe communication mode to prevent the spread of erroneous data from affecting the upper-layer system. The physical layer design of the communication interface module adopts a hybrid interface of multimode fiber and shielded twisted pair, which can flexibly select the transmission medium according to the field environment. In areas with strong interference, fiber optic channels are given priority to ensure signal quality.

[0051] Furthermore, the data acquisition and conditioning module and the synchronization module employ composite isolation technology and environmental adaptability design. Electrical isolation between the two modules utilizes a composite architecture of optocoupler and magnetic isolation in series. The optocoupler 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 for the isolation circuit is a polyimide-based composite material, possessing high-temperature resistance, moisture resistance, and salt spray corrosion resistance, ensuring long-term stable operation in the harsh environment of a ship. The isolation parameter design incorporates an adaptive adjustment mechanism, automatically reducing the isolation capacitance value to minimize signal distortion when transmitting high-frequency signals and increasing the common-mode rejection ratio to enhance anti-interference capabilities when transmitting low-frequency signals. The signal transmission path employs differential balanced transmission technology, coupled with shielded twisted-pair connectors, effectively suppressing electromagnetic radiation interference. The feedback control channel between modules is designed with an isolated digital interface, using Manchester encoding to transmit control commands, ensuring both signal integrity and maintaining electrical isolation characteristics. To address the unique vibration environment of ships, the connectors feature a locking shock-resistant design, internal circuit boards are potted, and key components utilize military-grade vibration-resistant devices to ensure reliable connections even under continuous mechanical vibration. Furthermore, the module housing employs an aluminum alloy sealed structure with anodized and conformal coating, meeting IP67 protection requirements and effectively preventing seawater salt spray corrosion and condensation.

[0052] Specifically, the system employs a collaborative working mode and a data semantic guarantee mechanism between the synchronization module and the communication interface module. The two modules achieve 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 intermediate standard formats, the synchronization module adds semantic tags to each data field, establishing a mapping relationship between these tags and metadata in the protocol description information library. When converting intermediate formats to upper-layer system protocols, the communication interface module reorganizes and encodes fields based on semantic tags, ensuring that the data meaning remains unambiguous during the conversion process. For example, when converting the analog signal from a hydraulic pressure sensor to the MODBUS protocol, the synchronization module labels it with "pressure value_engineering units," and the communication interface module matches the register address and unit conversion coefficient of the target protocol based on this tag. For protocol version upgrades or custom protocol extensions, the system provides a visual configuration tool, allowing users to define the field structure of new protocols through drag-and-drop. The configuration information is automatically synchronized to the protocol description information library and generates corresponding conversion rules. Regarding anomaly handling, when a missing protocol field or semantic conflict is detected, the system initiates a negotiation mechanism: first, it attempts to adaptively repair the data using the compatibility rules of the protocol description information base; if the repair fails, a security isolation process is triggered, temporarily storing the abnormal data in a buffer and sending an anomaly alarm to the upper-layer system. This layered transformation architecture not only ensures data format compatibility but, more importantly, maintains the integrity of data semantics, ensuring that different subsystems always interpret the same data item consistently.

[0053] The above embodiments are merely illustrative of the principles and effects of the present invention and are not intended to limit the invention. Any person skilled in the art can 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 those skilled in the art without departing from the spirit and technical concept disclosed in the present invention should still be covered by the claims of the present invention.

Claims

1. A hybrid signal universal acquisition and access system for ships, characterized in that, include: The data acquisition and conditioning module is used to amplify and filter external input signals to form physical layer signals. The data acquisition and conditioning module includes a programmable gain amplifier circuit and an adaptive filter circuit. The synchronization module is used to extract and classify the physical layer signals and form standardized digital signals. The synchronization module has a built-in multi-protocol identification algorithm and a signal feature extraction unit. The protocol identification algorithm realizes unsupervised classification of protocol types based on the signal time-domain features and statistical features extracted by the signal feature extraction unit. The data processing module receives optimization allocation instructions and processes standardized digital signals to form application layer data packets. The data processing module performs operations including data verification, timestamp alignment, and data compression. 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-level systems. The multi-protocol identification algorithm of the synchronization module adopts a multi-level classification strategy. First, it performs coarse classification based on signal waveform characteristics, then performs fine classification by combining statistical characteristics, and finally determines the specific protocol type by matching the protocol feature library. 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. These characteristics serve as the basis for protocol identification. When an unknown protocol type is encountered, the feature parameters of the signal are automatically recorded and the user is prompted to define the protocol. The multi-protocol identification algorithm adopts a three-level classification architecture. In the first-level time-domain waveform coarse classification stage, the input signal is preprocessed. The preprocessed signal enters the time-domain feature extraction stage, and the key parameters are calculated, including: the ratio of signal peak-to-peak value to 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 the key parameters, the system initially divides the signal into four categories: continuous analog signal, discrete switching signal, pulse sequence, and coded digital signal. In the second-level statistical feature classification stage, for continuous analog signals, the skewness and kurtosis of their amplitude distribution histogram are calculated to distinguish between linear and nonlinear logarithmic signals; for discrete switching signals, the time distribution entropy value of state switching events is analyzed to determine whether they are random 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 probabilities of 0 / 1 transitions in the bit stream are 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 containing a standard feature vector and an allowable deviation range. The matching algorithm uses an improved K-nearest neighbor classification method, assigning dynamic weights to each feature dimension. When the matching degree exceeds the upper limit of the set 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 lower limit of the set threshold, the system automatically activates the unknown protocol learning mode: recording the complete time-domain waveform, statistical features, and environmental context information of the signal, generating a temporary protocol identifier, and prompting the user to intervene in the definition.

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. 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 ensures that input signals of different amplitudes are adjusted to the preset optimal processing range. The cutoff frequency of the adaptive filter circuit is related to the output of the signal feature extraction unit. By acquiring the frequency domain feature parameters of the signal in real time, the passband and stopband range of the filter are dynamically adjusted.

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, constructing a reconfigurable filtering network at the hardware level, consisting of multiple sets of switchable capacitors and inductors forming a basic filtering unit, and using a numerically controlled resistor array to achieve programmable adjustment of filtering parameters; The specific process of the programmable adjustment is as follows: taking 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 correlation analysis between the compensated output signal and the reference signal, calculates the gradient direction of the error function, and dynamically adjusts the weight of the filter coefficients. To address the unique time-varying interference characteristics of the ship environment, a historical database of frequency response compensation is established to record typical interference patterns under different operating conditions. When similar operating condition characteristics are detected, the historically optimal compensation parameters are preloaded. Simultaneously, the compensation process also includes a nonlinear distortion correction stage, which uses a polynomial fitting model to pre-distort the phase shift related to the signal amplitude.

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

5. 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 various 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 statistically analyzes the bit error rate and latency of data transmission in real time, providing network status reference for the conditioning module.

6. 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 opto-isolation and magnetic isolation. Opto-isolation is used to block common-mode interference, while magnetic isolation is used to suppress noise. The insulating material of the isolation barrier is a polymer composite material.

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