Dynamic monitoring system for ship mooring cable tension based on exciting natural frequency analysis

Abstract

The application relates to the technical field of ship mooring equipment monitoring, and discloses a ship mooring cable tension dynamic monitoring system based on vibration excitation and natural frequency analysis. The system applies transient vibration to the cable through a vibration excitation device, acquires vibration response signals by using a dynamic response acquisition unit, eliminates interference through a signal pretreatment module, and identifies intrinsic frequency components related to the cable tension through a spectrum analysis and feature extraction module. Furthermore, the axial tension of the cable is accurately calculated through a tension calculation model integrated with cable structure parameters and boundary condition correction, so that dynamic monitoring and early warning of the tension are realized. The application effectively improves the safety and reliability of ship mooring operations.

Description

Technical Field

[0001] This invention relates to the field of ship mooring equipment monitoring technology, and discloses a dynamic monitoring system for ship mooring cable tension based on excitation natural frequency analysis. Background Technology

[0002] In ship mooring operations, the tension of the mooring lines is a critical parameter for ensuring the safe berthing of the vessel. Traditional monitoring methods mostly rely on manual measurement or static tension sensors, which have drawbacks such as inaccurate monitoring, poor real-time performance, and inability to reflect dynamic changes.

[0003] Especially in complex sea conditions, the swaying of ships and the noise from wind and waves significantly interfere with the monitoring results, leading to data distortion and making it difficult to meet the needs of modern ship safety management.

[0004] Therefore, it is particularly important to develop a dynamic monitoring system that can monitor the tension of ship mooring lines in real time and accurately. Summary of the Invention

[0005] To address the aforementioned technical shortcomings, the purpose of this invention is to provide a dynamic monitoring system for ship mooring cable tension based on excitation natural frequency analysis, thereby solving the problems of inaccurate and poor real-time performance in existing ship mooring cable tension monitoring.

[0006] To solve the above-mentioned technical problems, the present invention adopts the following technical solution: In a first aspect, the present invention provides a dynamic monitoring system for ship mooring cable tension based on excitation natural frequency analysis, comprising: A vibration excitation device is used to apply a transient vibration excitation to the mooring lines of a ship. The dynamic response acquisition unit, arranged in conjunction with the excitation device, is used to acquire the time-domain vibration response signal generated by the cable under excitation. The signal preprocessing module, connected to the dynamic response acquisition unit, is used to preprocess the time-domain vibration response signal to eliminate interference components introduced by the ship's own swaying and environmental wind and wave noise. The spectrum analysis and feature extraction module is connected to the signal preprocessing module. It is used to execute the cable vibration spectrum feature extraction algorithm, perform frequency domain transformation on the preprocessed time-domain vibration response signal, and identify the intrinsic frequency components related to cable tension. The tension calculation module connects to the spectrum analysis and feature extraction module, and integrates a tension calculation model that combines cable structure parameters and boundary condition corrections. This tension calculation model takes the intrinsic frequency components as input and outputs the tension calculation results. The dynamic monitoring and output unit is connected to the tension calculation module to receive and process continuous tension calculation results, generate a sequence of tension changes over time, and display and warn in real time.

[0007] Preferably, in one possible implementation of the first aspect, the excitation device includes an electromagnetic actuator and a force sensor; The electromagnetic exciter generates a pulsed magnetic field according to the control command, which drives the magnetic sheet fixed on the surface of the cable to generate a transient impact perpendicular to the cable axis. Force sensors measure the force value of each transient impact and feed it back to the control system; The control system adjusts the current parameters of the subsequent pulse magnetic field based on the difference between the feedback force value and the preset target excitation force.

[0008] Preferably, in one possible implementation of the first aspect, the dynamic response acquisition unit includes a vibration sensor, a signal conditioning circuit, and a synchronous acquisition module arranged on the surface of the cable. The vibration sensor uses a piezoelectric accelerometer with its sensing axis perpendicular to the cable axis, converting the cable's vibration acceleration into an analog electrical signal. The signal conditioning circuit performs impedance matching, amplification, and anti-aliasing filtering on analog electrical signals. The synchronous acquisition module receives the trigger signal from the excitation device and starts after the excitation device applies transient excitation. It performs synchronous analog-to-digital conversion on the conditioned analog electrical signal and outputs a time-domain vibration response signal that includes the free decay vibration process of the cable.

[0009] Preferably, in one possible implementation of the first aspect, the signal preprocessing module performs the following operations in sequence: The time-domain vibration response signal output by the dynamic response acquisition unit is subjected to zero-mean processing to eliminate the DC offset component in the signal. Apply a time-domain windowing function to the zero-mean signal to suppress spectral leakage caused by truncation; The windowed signal is input into a digital bandpass filter. The lower cutoff frequency of the digital bandpass filter is higher than the frequency of low-frequency interference components introduced by ship motion, and the upper cutoff frequency of the digital bandpass filter is lower than the frequency of high-frequency noise components introduced by environmental factors. Interference components outside the frequency band are filtered out, and the preprocessed time-domain vibration response signal is output.

[0010] Preferably, in one possible implementation of the first aspect, the cable vibration spectrum feature extraction algorithm includes: The discrete spectrum is obtained by applying the rotationally invariant subspace method to the preprocessed time-domain vibration response signal; In the discrete spectrum, identify multiple spectral peaks whose amplitude exceeds the dynamic noise threshold and whose frequency spacing exhibits a harmonic relationship, and record their initial frequency values ​​as candidate intrinsic frequency sequences. Construct a signal model of superimposed sinusoidal harmonics using candidate intrinsic frequency sequences; In the time domain, the signal model is fitted with the preprocessed time-domain vibration response signal using nonlinear least squares, and the frequency, amplitude and phase parameters of each harmonic are iteratively adjusted. The stable frequency values ​​of each harmonic after the fitting convergence are taken as the intrinsic frequency components.

[0011] Preferably, in one possible implementation of the first aspect, the rotation-invariant subspace method is implemented through the following steps: Construct the autocorrelation matrix of the preprocessed time-domain vibration response signal; The autocorrelation matrix is ​​decomposed into eigenvalues, and the resulting eigenvectors are divided into signal subspace and noise subspace. Based on the rotational invariance of the signal subspace, a generalized eigenvalue problem is solved to obtain a discrete spectrum characterizing the frequency components of cable vibration.

[0012] Preferably, in one possible implementation of the first aspect, the signal model construction process includes: Each frequency value in the candidate intrinsic frequency sequence is taken as an integer multiple of the fundamental frequency to generate the sinusoidal harmonic basis function of the initial frequency; The preprocessed time-domain vibration response signal is linearly decomposed using sinusoidal harmonic basis functions to obtain the initial amplitude and phase estimates of each harmonic component. The initial frequency, initial amplitude, and initial phase are used as the initial values ​​for the nonlinear least squares fitting iteration. A signal model is constructed with the mathematical model of the superposition of harmonic components as the function to be fitted and the preprocessed time-domain vibration response signal as the fitting target.

[0013] Preferably, in one possible implementation of the first aspect, the tension calculation model comprises a physical model unit, a parameter mapping unit, and a numerical solution unit connected in sequence; The physical model unit is based on the dynamic principle of cable lateral vibration and establishes control equations to describe the mapping relationship between cable axial tension, cable structural parameters, boundary conditions and intrinsic frequency components. The parameter mapping unit integrates cable structure parameters and boundary conditions, and encodes the cable structure parameters and boundary conditions into an input parameter matrix of the control equation. The cable structure parameters include the linear density, bending stiffness and length of the cable, and the boundary conditions include boundary constraint coefficients. The numerical solution unit receives the intrinsic frequency components, uses the intrinsic frequency components as the target value, and performs iterative comparison and inversion operations with the frequency prediction value calculated by the control equation from the input parameter matrix and the tension assumption value until convergence, and outputs the axial tension value of the cable.

[0014] Preferably, in one possible implementation of the first aspect, the method for determining the boundary constraint coefficients includes: Excitation and frequency analysis are performed on a cable under a known reference tension state to obtain the set of measured intrinsic frequency components under the known reference tension state; By substituting the measured intrinsic frequency components, known reference tension values, and cable structural parameters into the control equations, boundary condition parameter inversion calculations are performed to obtain the boundary constraint coefficients that characterize the constraint conditions at both ends of the cable under actual installation conditions.

[0015] Preferably, in one possible implementation of the first aspect, the iterative comparison and inversion operation process includes: A frequency observation vector is constructed by using multiple intrinsic frequency components. Substitute the frequency observation vector, input parameter matrix and tension assumption value into the control equation to calculate the corresponding frequency prediction vector. The norm of the difference between the frequency observation vector and the frequency prediction vector is constructed as the objective function. The tension assumption value is adjusted through an iterative algorithm, and the tension value that minimizes the objective function value is output as the axial tension value of the cable.

[0016] The beneficial effects of this invention are as follows: This invention achieves real-time and accurate monitoring of the tension of ship mooring cables through excitation natural frequency analysis technology.

[0017] The system uses an electromagnetic exciter to apply transient excitation, combined with vibration sensors to collect response signals, and through signal processing and spectrum analysis algorithms, eliminates interference from ship swaying and environmental noise, and extracts the intrinsic frequency components that are closely related to cable tension.

[0018] By utilizing a tension calculation model that integrates cable structure parameters and boundary conditions, the axial tension of the cable is calculated, enabling dynamic monitoring and early warning of tension, thereby improving the safety and reliability of ship mooring operations. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This application provides a structural diagram of a ship mooring cable tension dynamic monitoring system based on excitation natural frequency analysis. Detailed Implementation

[0021] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0022] Example 1: As Figure 1 As shown, this invention provides a dynamic monitoring system for ship mooring cable tension based on excitation natural frequency analysis, comprising: A vibration excitation device is used to apply a transient vibration excitation to the mooring lines of a ship.

[0023] In this embodiment, the vibration excitation device includes an electromagnetic exciter, a force sensor, and a control system. The electromagnetic exciter generates a high-intensity pulsed magnetic field according to control commands issued by the control system. This pulsed magnetic field acts on a magnetically conductive sheet fixedly mounted on the surface of the cable, driving the sheet to generate a transient mechanical impact perpendicular to the cable axis, thus exciting the cable to produce transverse free damping vibration.

[0024] The force sensor is integrated inside the excitation structure to measure the actual force applied to the cable by each transient impact and transmits the measured force value as a feedback signal to the control system.

[0025] The control system has a preset target excitation force value. The control system compares the received measured force value feedback signal with the preset target excitation force value, calculates the difference between the two, and dynamically adjusts the current parameters in the control commands sent to the electromagnetic exciter based on the difference. This adjusts the intensity of the pulse magnetic field so that the transient impact force value generated subsequently approaches and stabilizes at the preset target excitation force value, ensuring the consistency of each excitation.

[0026] The dynamic response acquisition unit, arranged in conjunction with the excitation device, is used to acquire the time-domain vibration response signal generated by the cable under excitation.

[0027] In this embodiment, the dynamic response acquisition unit includes a vibration sensor fixedly arranged on the surface of the cable, a signal conditioning circuit electrically connected to the vibration sensor, and a synchronous acquisition module connected to the output of the signal conditioning circuit.

[0028] The vibration sensor employs a piezoelectric accelerometer, with its sensing axis installed perpendicular to the cable's axis. It converts the lateral vibration acceleration generated by the cable after excitation into a continuous analog electrical signal. The signal conditioning circuit receives this analog signal, first performing impedance matching to adapt to the sensor's output characteristics, then amplifying the signal to improve the signal-to-noise ratio and subsequent acquisition accuracy. Finally, it applies anti-aliasing filtering to the amplified signal, removing high-frequency noise components above the Nyquist frequency to prevent spectral aliasing during sampling.

[0029] The synchronous acquisition module receives a trigger signal from the excitation device control system. This trigger signal is synchronized with the action of the excitation device applying transient excitation. After receiving the trigger signal, the synchronous acquisition module starts and performs high-resolution analog-to-digital conversion on the analog electrical signal processed by the signal conditioning circuit. Finally, it outputs a discrete digital signal containing the complete process of the cable's free decay vibration after transient excitation, which is the time domain vibration response signal.

[0030] The signal preprocessing module, connected to the dynamic response acquisition unit, is used to preprocess the time-domain vibration response signal to eliminate interference components introduced by the ship's own swaying and environmental wind and wave noise.

[0031] In this embodiment, the signal preprocessing module receives the time-domain vibration response signal output by the synchronous acquisition module in the dynamic response acquisition unit. The time-domain vibration response signal is a discrete digital signal that includes the free decay vibration process of the cable.

[0032] The signal preprocessing module first performs zero-mean processing on the input discrete digital signal. Zero-mean processing calculates the arithmetic mean of all sampling points of the time-domain vibration response signal, and then subtracts the average value from the value of each sampling point to eliminate the DC offset component that may exist in the signal. These DC offsets may come from the zero-point drift of the sensor itself or the DC bias introduced by the signal conditioning circuit.

[0033] After zero-mean normalization, the signal preprocessing module applies a time-domain windowing function to the processed signal. In this embodiment, a Hanning window is used. The time-domain vibration response signal sequence is multiplied point-by-point with a Hanning window function sequence of the same length in the time domain. The Hanning window function smoothly decays to zero at both ends of the time domain. Time-domain windowing is used to suppress spectral leakage caused by signal truncation. Since the acquired cable free-attenuating vibration signal has a finite length in time, it is equivalent to truncating a theoretically infinitely long signal with a rectangular window, which will cause main lobe broadening and side lobes to appear in the frequency domain, i.e., spectral leakage. Windowing processing effectively reduces spectral leakage by making the signal smoothly transition to zero at the truncation edge.

[0034] Next, the signal preprocessing module inputs the windowed signal into a digital bandpass filter. In this embodiment, the digital bandpass filter is a linear phase finite-length unit impulse response filter. The digital bandpass filter has a passband frequency range. The lower cutoff frequency is set higher than the upper frequency limit of low-frequency interference components introduced by the ship's slow rolling, heave, and other motions; the upper cutoff frequency is set lower than the lower frequency limit of high-frequency noise components introduced by environmental wind-induced vibrations, wave impacts, etc. The determination of this frequency range depends on the prior analysis of the spectral characteristics of the actual mooring environment background noise.

[0035] The signal output after digital bandpass filtering is a preprocessed time-domain vibration response signal. This signal weakens the interference components of ship motion and environmental noise, and enhances the intrinsic vibration information of the cable.

[0036] The spectrum analysis and feature extraction module is connected to the signal preprocessing module. It is used to execute the cable vibration spectrum feature extraction algorithm, perform frequency domain transformation on the preprocessed time-domain vibration response signal, and identify the intrinsic frequency components related to cable tension.

[0037] In this embodiment, the spectrum analysis and feature extraction module first applies the rotation-invariant subspace method to the preprocessed time-domain vibration response signal to perform a high-resolution frequency domain transformation, obtaining its discrete spectrum. The rotation-invariant subspace method achieves higher frequency resolution accuracy through signal subspace analysis, and the implementation process is as follows: The autocorrelation matrix of the time-domain vibration response signal is constructed using the rotation-invariant subspace method. The dimension of the autocorrelation matrix is ​​determined by the predetermined dimension of the signal subspace, which is estimated based on prior knowledge or through information theory criteria such as the minimum description length criterion. Next, eigenvalue decomposition is performed on the constructed autocorrelation matrix. After eigenvalue decomposition, the resulting eigenvectors are distinguished according to the magnitude of their corresponding eigenvalues. The space spanned by eigenvectors corresponding to larger eigenvalues ​​is defined as the signal subspace, containing the main components of the cable vibration signal; the space spanned by eigenvectors corresponding to smaller eigenvalues ​​is defined as the noise subspace, mainly containing the noise component.

[0038] Based on the rotational invariance of the signal subspace, the algorithm solves a generalized eigenvalue problem. The solution to this problem is a set of complex exponents located on the unit circle, whose phases directly correspond to the frequency components of the signal. By calculating the phases of the complex exponents, a set of discrete spectrum estimates characterizing the frequency components of cable vibration is obtained.

[0039] After obtaining the high-resolution discrete spectrum, valid spectral peaks are identified within the discrete spectrum to obtain an initial frequency estimate. A dynamic noise threshold is set, calculated based on the statistical properties of the noise subspace eigenvalues, to distinguish the true signal spectral peaks from background noise fluctuations.

[0040] The entire discrete spectrum is scanned to identify all local maxima whose amplitudes exceed the dynamic noise threshold; these points are then designated as candidate spectral peaks. Subsequently, the relationships between the frequencies of these candidate peaks are analyzed. Since the transverse vibration mode frequencies of the cable are approximately integer multiples of the fundamental frequency under ideal conditions, exhibiting a harmonic relationship, multiple spectral peaks with frequency intervals showing approximately integer multiples or simple rational multiples are further selected. The initial frequency values ​​corresponding to the selected spectral peaks that satisfy the harmonic relationship are recorded, forming a candidate intrinsic frequency sequence.

[0041] Next, based on the candidate intrinsic frequency sequence, a signal model of multi-order sinusoidal harmonic superposition is constructed. The construction process is as follows: First, each frequency value in the candidate intrinsic frequency sequence is regarded as an integer multiple of a certain fundamental frequency. Based on these initial frequency values, a set of sinusoidal harmonic basis functions with corresponding initial frequencies are generated. Each basis function represents a possible vibration mode.

[0042] Then, the preprocessed time-domain vibration response signal is linearly decomposed using this set of sinusoidal harmonic basis functions. This is accomplished by solving a least-squares problem to obtain the initial amplitude and initial phase estimates of each harmonic component at the initial frequency. The initial estimates, including the initial frequency, initial amplitude, and initial phase, together constitute a complete initial vector of signal model parameters. Finally, a signal model is constructed with the mathematical model of the superposition of each harmonic component as the function to be fitted, and the preprocessed time-domain vibration response signal as the fitting target.

[0043] After the signal model is constructed, the constructed signal model is fitted with the preprocessed time-domain vibration response signal in the time domain using nonlinear least squares fitting to find a set of optimal model parameters that minimize the sum of squared errors between the model output signal and the measured signal. The initial frequency, initial amplitude, and initial phase are used as the initial values ​​for the iteration of the nonlinear least squares fitting algorithm.

[0044] The fitting process adjusts the three parameters of each harmonic in the signal model—frequency, amplitude, and phase—using an iterative algorithm. In each iteration, the model signal is calculated based on the current parameters and compared with the actual observed signal. The residuals are calculated, and then the parameter estimates are updated according to a preset optimization algorithm, including but not limited to the Gauss-Newton method or the Levin-Begg-Marquardt method. The iterative process continues until a preset convergence condition is met. The convergence condition is set as either the parameter change between two consecutive iterations being less than a threshold, or the decrease in the sum of squared residuals of the objective function being less than another threshold.

[0045] Once the nonlinear least squares fitting process converges, the parameters of each harmonic stabilize at their optimal estimates. At this point, the stable frequency values ​​of each harmonic after fitting convergence are extracted. These extracted stable frequency values ​​are the intrinsic frequency components. These intrinsic frequency components directly reflect the physical properties of the cable, including axial tension, linear density, bending stiffness, and boundary conditions.

[0046] The tension calculation module connects to the spectrum analysis and feature extraction module, integrating a tension calculation model that combines cable structure parameters and boundary condition corrections. This tension calculation model takes the intrinsic frequency components as input and outputs the tension calculation results.

[0047] In this embodiment, the tension calculation model includes a physical model unit, a parameter mapping unit, and a numerical solution unit. The physical model unit, based on the dynamic principles of cable lateral vibration, establishes governing equations describing the mapping relationship between cable axial tension, cable structural parameters, boundary conditions, and intrinsic frequency components. These governing equations originate from solving the differential equations of the lateral free vibration of a flexible cable or beam subjected to axial tension. For a uniform cable, considering the combined effects of its bending stiffness and axial tension, a definite nonlinear functional relationship exists between the natural frequencies of its lateral vibration and the axial tension.

[0048] The physical model unit realizes the nonlinear functional relationship as a governing equation. The input variables of the equation include the axial tension of the cable, the structural mechanical parameters of the cable, and the boundary constraints at both ends of the cable. The output variable is the set of theoretical vibration eigenfrequency of the cable under the corresponding input conditions.

[0049] The parameter mapping unit integrates the inherent structural parameters of the cable and the boundary conditions under actual installation conditions. The cable structural parameters include the cable's linear density, bending stiffness, and effective length between two measurement points or excitation response acquisition points. These parameters are obtained through measurement and calibration. The boundary conditions refer to the actual constraints at the connection points between the cable's ends and structures such as mooring bollards and ship's side guide holes. The parameter mapping unit uses boundary constraint coefficients to characterize the stiffness characteristics of this elastic constraint.

[0050] The parameter mapping unit encodes the cable structure parameters and boundary constraint coefficients into a unified input parameter matrix, which serves as the fixed coefficient term in the governing equations. First, a complete excitation and frequency analysis process is performed on the cable under test under a known reference tension state to obtain the set of measured intrinsic frequency components in this steady state. Then, the set of measured intrinsic frequency components, the known reference tension value, and the cable's linear density, bending stiffness, length, and other structural parameters are substituted into the governing equations of the physical model unit.

[0051] At this point, only the boundary constraint coefficients are unknowns in the equation. By solving this inverse problem with the boundary constraint coefficients as variables, the boundary condition parameters are inverted and calculated. A set of boundary constraint coefficient values ​​that best match the theoretically calculated frequency with the measured frequency is obtained. This set of coefficients characterizes the actual constraint situation at both ends of the cable under specific installation conditions.

[0052] The numerical solution unit receives the eigenfrequency components from the spectrum analysis and feature extraction module to solve for the real-time axial tension of the cable. The specific process is as follows: First, the acquired multiple eigenfrequency components are arranged according to their order to form a frequency observation vector. This vector contains the vibration characteristic information of the cable under the current unknown tension state. Then, the control equations of the physical model unit and the input parameter matrix provided by the parameter mapping unit are called, and an initial tension assumption value is preset. The frequency observation vector, the input parameter matrix, and the tension assumption value are substituted into the control equation to calculate a set of corresponding theoretical frequency prediction values. These prediction values ​​are arranged according to the same order to form a frequency prediction vector.

[0053] Next, an objective function is constructed to measure the degree of difference between the observed frequency vector and the predicted frequency vector, using the sum of squares of the frequency residuals of each order as the objective function. The smaller the value of the objective function, the closer the theoretical frequency calculated after substituting the current tension assumption value into the governing equation is to the measured frequency, meaning the tension assumption value is closer to the true tension.

[0054] The numerical solution unit employs an iterative optimization algorithm to find the tension value that minimizes the objective function. Starting with an initial tension hypothesis, the algorithm calculates the current objective function value and its gradient. Based on the gradient, the algorithm determines the adjustment direction and step size of the tension hypothesis, updates it using the Gauss-Newton method, and obtains a new, better tension hypothesis. The frequency prediction vector and the new objective function value are then recalculated using this new tension hypothesis. This process iterates repeatedly, with each iteration attempting to decrease the objective function value.

[0055] The iterative process is configured with convergence criteria. The calculation is considered convergent when the change in the assumed tension value between two consecutive iterations is less than a preset minimum threshold, or when the change in the objective function value is less than another preset threshold. At this point, the assumed tension value used in the final iteration is the optimal cable axial tension estimate obtained through inversion, and the numerical solution unit outputs this tension calculation result.

[0056] The dynamic monitoring and output unit is connected to the tension calculation module to receive and process continuous tension calculation results, generate a sequence of tension changes over time, and display and warn in real time.

[0057] In this embodiment, the dynamic monitoring and output unit includes a data interface module, a data buffer, a sequence generation module, a display driver module, and an early warning judgment module.

[0058] The data interface module reads the latest calculated axial tension value of the cable at fixed intervals and timestamps the tension value. The data buffer adopts a first-in-first-out queue structure to store the timestamped tension data input by the data interface module. The queue length is set according to the monitoring time range requirements.

[0059] The sequence generation module extracts tension data from the data buffer in chronological order. First, it performs time alignment processing on the discrete tension data. Then, it applies a moving average filtering algorithm, which calculates the arithmetic mean of all tension data within the previous fixed time window and uses this mean as the tension sequence value at the current moment, generating a smooth continuous sequence of tension changes over time.

[0060] The display driver module connects to the display screen, which is divided into a real-time data display area and a historical trend curve display area. The real-time data display area dynamically refreshes and displays the current tension value in digital form after processing by the sequence generation module; the historical trend curve display area dynamically plots and updates the tension time series curve output by the sequence generation module, with time as the horizontal axis and tension value as the vertical axis.

[0061] The early warning judgment module has preset safety tension thresholds and early warning tension thresholds. It continuously compares the current tension value in the real-time display area with these preset thresholds. When the tension value consistently exceeds the early warning tension threshold for a preset duration, the module determines it to be a yellow warning state, triggering an early warning signal to the display driver module. This causes the early warning status indicator on the display screen to flash yellow, and the warning text information is output in a designated area of ​​the screen. When the tension value exceeds the safety tension threshold, the module determines it to be a red alarm state, triggering an alarm signal. This causes the early warning status indicator to turn solid red and the buzzer to emit a continuous alarm sound. Simultaneously, the time, tension value, and type of this alarm event are recorded in the early warning log file.

[0062] Example 2: The present invention provides a dynamic monitoring system for ship mooring cable tension based on excitation natural frequency analysis, and also includes a highly integrated field monitoring terminal.

[0063] The on-site monitoring terminal integrates the core algorithms of the signal preprocessing module, spectrum analysis and feature extraction module, and tension calculation module into an industrial-grade embedded processor, and is packaged together with the display touch screen of the dynamic monitoring and output unit in a waterproof and corrosion-resistant chassis. The chassis is connected to the field excitation device and dynamic response acquisition unit via waterproof connectors, forming an independent monitoring node.

[0064] The on-site monitoring terminal has a built-in embedded operating system, independently completing the entire process from data acquisition, signal processing, tension calculation to local display and early warning. It is suitable for distributed deployment at monitoring points on multiple mooring lines of a ship. Simultaneously, the terminal also integrates a wireless transmission unit, encrypting the processed tension data, spectral characteristics, and early warning status before uploading them to a remote cloud server, enabling centralized data storage, historical data review, and ship-shore collaborative monitoring.

[0065] Example 3: This invention provides a dynamic monitoring system for ship mooring cable tension based on excitation natural frequency analysis, and also includes a portable calibration and rapid evaluation kit for rapid on-site deployment and calibration of the system. The kit includes a handheld excitation and data acquisition unit, and a mobile terminal pre-installed with dedicated software.

[0066] The handheld all-in-one device integrates a miniaturized electromagnetic vibrator, force sensor, vibration sensor, and data acquisition circuitry. It can be quickly and temporarily clamped onto the cable under test using a fixture. The mobile terminal communicates with the all-in-one device via Bluetooth or Wi-Fi, and its software includes a built-in system calibration wizard to guide operators through the on-site calibration process of boundary constraint coefficients.

[0067] In rapid assessment mode, based on a pre-set library of typical cable parameters and a simplified rapid calculation model, the system provides an estimated range of tension and a safety status indication within seconds of completing a single excitation measurement. This is suitable for rapid inspection and preliminary safety screening of multiple cables.

[0068] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A dynamic monitoring system for ship mooring cable tension based on excitation natural frequency analysis, characterized in that, include: A vibration excitation device is used to apply a transient vibration excitation to the mooring lines of a ship. The dynamic response acquisition unit, arranged in conjunction with the excitation device, is used to acquire the time-domain vibration response signal generated by the cable under excitation. The signal preprocessing module, connected to the dynamic response acquisition unit, is used to preprocess the time-domain vibration response signal to eliminate interference components introduced by the ship's own swaying and environmental wind and wave noise. The spectrum analysis and feature extraction module is connected to the signal preprocessing module. It is used to execute the cable vibration spectrum feature extraction algorithm, perform frequency domain transformation on the preprocessed time-domain vibration response signal, and identify the intrinsic frequency components related to cable tension. The cable vibration spectrum feature extraction algorithm includes: The discrete spectrum is obtained by applying the rotationally invariant subspace method to the preprocessed time-domain vibration response signal; In the discrete spectrum, identify multiple spectral peaks whose amplitude exceeds the dynamic noise threshold and whose frequency spacing exhibits a harmonic relationship, and record their initial frequency values ​​as candidate intrinsic frequency sequences. Construct a signal model of superimposed sinusoidal harmonics using candidate intrinsic frequency sequences; In the time domain, the signal model is fitted with the preprocessed time-domain vibration response signal using nonlinear least squares, and the frequency, amplitude and phase parameters of each harmonic are iteratively adjusted. The stable frequency values ​​of each harmonic after the fitting convergence are taken as the intrinsic frequency components. The tension calculation module connects to the spectrum analysis and feature extraction module, and integrates a tension calculation model that combines cable structure parameters and boundary condition corrections. This tension calculation model takes the intrinsic frequency components as input and outputs the tension calculation results. The tension calculation model comprises a physical model unit, a parameter mapping unit, and a numerical solution unit connected in sequence. The physical model unit is based on the dynamic principle of cable lateral vibration and establishes control equations to describe the mapping relationship between cable axial tension, cable structural parameters, boundary conditions and intrinsic frequency components. The parameter mapping unit integrates cable structure parameters and boundary conditions, and encodes the cable structure parameters and boundary conditions into an input parameter matrix of the control equation. The cable structure parameters include the linear density, bending stiffness and length of the cable, and the boundary conditions include boundary constraint coefficients. The method for determining the boundary constraint coefficients includes: Excitation and frequency analysis are performed on a cable under a known reference tension state to obtain the set of measured intrinsic frequency components under the known reference tension state; Substitute the measured intrinsic frequency component set, the known reference tension value, and the cable structure parameters into the control equation to perform boundary condition parameter inversion calculation, and solve for the boundary constraint coefficients that characterize the constraint situation at both ends of the cable under actual installation conditions. The numerical solution unit receives the intrinsic frequency components, uses the intrinsic frequency components as the target value, and performs iterative comparison and inversion operations with the frequency prediction value calculated by the control equation from the input parameter matrix and the tension assumption value until convergence, and outputs the axial tension value of the cable. The dynamic monitoring and output unit is connected to the tension calculation module to receive and process continuous tension calculation results, generate a sequence of tension changes over time, and display and warn in real time.

2. The ship mooring cable tension dynamic monitoring system based on excitation natural frequency analysis according to claim 1, characterized in that, The excitation device includes an electromagnetic exciter and a force sensor; The electromagnetic exciter generates a pulsed magnetic field according to the control command, which drives the magnetic sheet fixed on the surface of the cable to generate a transient impact perpendicular to the cable axis. Force sensors measure the force value of each transient impact and feed it back to the control system; The control system adjusts the current parameters of the subsequent pulse magnetic field based on the difference between the feedback force value and the preset target excitation force.

3. The ship mooring cable tension dynamic monitoring system based on excitation natural frequency analysis according to claim 1, characterized in that, The dynamic response acquisition unit includes a vibration sensor, a signal conditioning circuit, and a synchronous acquisition module arranged on the surface of the cable. The vibration sensor uses a piezoelectric accelerometer with its sensing axis perpendicular to the cable axis, converting the cable's vibration acceleration into an analog electrical signal. The signal conditioning circuit performs impedance matching, amplification, and anti-aliasing filtering on analog electrical signals. The synchronous acquisition module receives the trigger signal from the excitation device and starts after the excitation device applies transient excitation. It performs synchronous analog-to-digital conversion on the conditioned analog electrical signal and outputs a time-domain vibration response signal that includes the free decay vibration process of the cable.

4. The ship mooring cable tension dynamic monitoring system based on excitation natural frequency analysis according to claim 1, characterized in that, The signal preprocessing module performs the following operations in sequence: The time-domain vibration response signal output by the dynamic response acquisition unit is subjected to zero-mean processing to eliminate the DC offset component in the signal. Apply a time-domain windowing function to the zero-mean signal to suppress spectral leakage caused by truncation; The windowed signal is input into a digital bandpass filter. The lower cutoff frequency of the digital bandpass filter is higher than the frequency of low-frequency interference components introduced by ship motion, and the upper cutoff frequency of the digital bandpass filter is lower than the frequency of high-frequency noise components introduced by environmental factors. Interference components outside the frequency band are filtered out, and the preprocessed time-domain vibration response signal is output.

5. The ship mooring cable tension dynamic monitoring system based on excitation natural frequency analysis according to claim 1, characterized in that, The rotation-invariant subspace method is implemented through the following steps: Construct the autocorrelation matrix of the preprocessed time-domain vibration response signal; The autocorrelation matrix is ​​decomposed into eigenvalues, and the resulting eigenvectors are divided into signal subspace and noise subspace. Based on the rotational invariance of the signal subspace, a generalized eigenvalue problem is solved to obtain a discrete spectrum characterizing the frequency components of cable vibration.

6. The ship mooring cable tension dynamic monitoring system based on excitation natural frequency analysis according to claim 1, characterized in that, The signal model construction process includes: Each frequency value in the candidate intrinsic frequency sequence is taken as an integer multiple of the fundamental frequency to generate the sinusoidal harmonic basis function of the initial frequency; The preprocessed time-domain vibration response signal is linearly decomposed using sinusoidal harmonic basis functions to obtain the initial amplitude and phase estimates of each harmonic component. The initial frequency, initial amplitude, and initial phase are used as the initial values ​​for the nonlinear least squares fitting iteration. A signal model is constructed with the mathematical model of the superposition of harmonic components as the function to be fitted and the preprocessed time-domain vibration response signal as the fitting target.

7. The ship mooring cable tension dynamic monitoring system based on excitation natural frequency analysis according to claim 1, characterized in that, The iterative comparison and inversion process includes: A frequency observation vector is constructed by using multiple intrinsic frequency components. Substitute the frequency observation vector, input parameter matrix and tension assumption value into the control equation to calculate the corresponding frequency prediction vector. The norm of the difference between the frequency observation vector and the frequency prediction vector is constructed as the objective function. The tension assumption value is adjusted through an iterative algorithm, and the tension value that minimizes the objective function value is output as the axial tension value of the cable.

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