Shafting load analysis method based on real-time data monitoring

Abstract

The invention relates to the technical field of ship propulsion system monitoring, in particular to a shafting load analysis method based on real-time data monitoring, and the method comprises the following steps: S1, collecting a pressure parameter and a displacement parameter of a shafting; s2, performing timestamp alignment and data frame encapsulation to generate a synchronous data stream; s3, shafting natural vibration noise and real load signals are separated, and shafting real-time torque distribution is calculated; s4, if the torque distribution deviates from the correction threshold value, graded early warning is triggered; and S5, generating an interactive report according to the triggered early warning level and the torque distribution result. According to the invention, through multi-sensor synchronous acquisition, edge calculation data alignment, vibration noise decoupling, dynamic safety threshold adjustment and intelligent fault tracing analysis, high-precision monitoring, abnormity early warning and intelligent maintenance of the shafting load are realized, and the safety and operation and maintenance efficiency of ship operation are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of ship propulsion system monitoring, and in particular to a shafting load analysis method based on real-time data monitoring. Background Art

[0002] The ship's shafting is the core component of the ship's propulsion system, and its working condition directly affects the ship's operational safety and economic performance. During operation, the shafting will be affected by complex loads, including torque, pressure, vibration and other factors, which are coupled by multiple factors such as the ship's navigation status, propulsion system operating conditions, and environmental conditions.

[0003] Traditional shaft load monitoring methods mainly rely on regular manual inspections or local measurements based on a single sensor, which makes it difficult to obtain the shaft load status in real time and comprehensively. At the same time, due to the inherent vibration characteristics of the shaft system itself and the time synchronization error of multi-sensor data acquisition, the actual measurement data often has noise interference, resulting in a decrease in the accuracy of shaft torque calculation and affecting the reliability of load assessment. Therefore, a shaft load analysis method based on real-time data monitoring is urgently needed to solve the problem. Summary of the invention

[0004] Based on the above objectives, the present invention provides a shaft load analysis method based on real-time data monitoring to solve the problems of data synchronization error and noise interference in shaft load analysis.

[0005] A shaft system load analysis method based on real-time data monitoring comprises the following steps:

[0006] S1: The pressure and displacement parameters of the shaft system are synchronously collected through the piezoresistive pressure sensor and the optical fiber displacement sensor, and the sensor sampling frequency is dynamically adjusted based on the temperature and humidity data in the ship cabin to generate an original data set that is resistant to environmental interference;

[0007] S2: Through the deployed edge computing nodes, the original data set is timestamped and encapsulated, the timing error caused by asynchronous acquisition of multiple sensors is eliminated, and a synchronous data stream is generated;

[0008] S3: Based on the physical model of the ship shafting, the pressure and displacement parameters in the synchronous data stream are dynamically decoupled to separate the shafting inherent vibration noise and the real load signal, and the real-time torque distribution of the shafting is calculated through the decoupled real load signal;

[0009] S4: Based on the shaft system torque distribution results and combined with the ship's navigation status data, the safety threshold interval is dynamically corrected. If the torque distribution deviates from the correction threshold, a graded warning is triggered;

[0010] S5: Automatically generate an interactive report including load source tracing analysis, maintenance suggestions and data heat map based on the triggered warning level and torque distribution results.

[0011] Optionally, the S1 specifically includes:

[0012] S11: Use a piezoresistive pressure sensor to obtain the contact surface pressure of the shaft system, and use an optical fiber displacement sensor to detect the micro-displacement change of the shaft system. The two sensors are respectively arranged at the connection position between the bearing seat and the shaft system. The synchronous trigger signal is used to control the sampling, so that the pressure parameter and the displacement parameter complete the data collection at the same time point;

[0013] S12: Cache the collected pressure parameters and displacement parameters, and match them according to the timestamps to ensure that the sensor data in the same time window are aligned to form a complete raw data frame;

[0014] S13: Collect temperature and humidity data in the ship cabin, wherein the temperature data comes from the thermistor temperature sensor, and the humidity data comes from the humidity sensitive resistor sensor.

[0015] Optionally, the S1 further includes:

[0016] S14: Based on the fluctuation range of temperature and humidity data, a linear compensation algorithm is used to calculate the current environmental interference factor , the formula is: ,in, is the current temperature, Calibrate the sensor temperature, is the current humidity, Calibrate the sensor for humidity, is the empirical correction coefficient;

[0017] S15: Based on the calculated environmental interference factor , for the sampling frequency Dynamic adjustment is performed using the formula: ,in, is the standard sampling frequency, is the sampling frequency adjustment coefficient, is the adjusted sampling frequency;

[0018] S16: Perform a stability check on the adjusted data acquisition frequency. If the variation between two adjacent sampling frequencies is less than a set threshold, formal data acquisition is performed and an original data set resistant to environmental interference is generated.

[0019] Optionally, the S2 specifically includes:

[0020] S21: receiving the original data set generated by S1 in the edge computing node, and extracting the timestamp attached to each sensor data in the original data set;

[0021] S22: Based on a unified time reference, the original data of the piezoresistive pressure sensor and the optical fiber displacement sensor are resampled using a linear interpolation alignment method to eliminate the timing difference of the sampling points of the two sensors caused by the response delay;

[0022] S23: Based on the aligned unified timestamp, the resampled pressure parameters and displacement parameters are combined into a structured data frame, each of which contains a unified timestamp, a pressure parameter, and a displacement parameter data pair;

[0023] S24: using a data frame encapsulation protocol to perform standardized encapsulation on the combined data frame, each encapsulated data frame includes a data frame identification header, a unified timestamp, a sensor identification code, a pressure parameter value, a displacement parameter value, and a data frame check code;

[0024] S25: Perform a continuity check on the encapsulated data frames to confirm that the timestamps of the data frames are continuous and not missing. If there is a missing data frame or an abnormal timestamp, the abnormal data frame is discarded; and the data frames that pass the continuity check are spliced ​​into a continuous data stream in sequence, and then a synchronous data stream with a unified timestamp and no timing errors is output.

[0025] Optionally, the S3 specifically includes:

[0026] S31: Based on the geometric structure and material properties of the ship shaft system, a dynamic physical model of the shaft system is established, which includes the shaft system stiffness parameters, damping characteristic parameters and moment of inertia parameters;

[0027] S32: input the synchronous data stream obtained in S2 into the shaft system dynamics physical model, and determine the real-time excitation load in combination with the shaft system speed information, and calculate the theoretical vibration response value of the shaft system; and compare and analyze the theoretical vibration response value with the pressure parameters and displacement parameters measured by the synchronous data stream, and identify the noise component generated by the inherent vibration of the shaft system in the synchronous data stream;

[0028] S33: based on the identified shaft system inherent vibration noise component, deduct the noise component from the pressure parameter and displacement parameter measured by the synchronous data stream in the time domain and the frequency domain to obtain a decoupled real load signal;

[0029] S34: Calculate the real-time torque distribution at the shafting section using the decoupled real load signal.

[0030] Optionally, the S31 specifically includes:

[0031] S311: Collect the geometric structure parameters and mass distribution parameters of the shaft system, including the length, diameter, cross-sectional area and density of the shaft system;

[0032] S312: Obtain material mechanical characteristic parameters of the shaft system, including elastic modulus, Poisson's ratio and yield limit;

[0033] S313: Calculate the overall stiffness coefficient of the shaft system based on the geometric structure parameters and material mechanical property parameters of the shaft system , damping coefficient And the moment of inertia ;

[0034] S314: Based on stiffness coefficient , damping coefficient , moment of inertia , and the external excitation torque , construct the dynamic physical model of the shaft system, the expression is: ,in, is the angular displacement of the shaft system, is the external excitation torque.

[0035] Optionally, the S32 specifically includes:

[0036] S321: Based on the shaft system dynamics physical model constructed in S31, obtain the real-time speed of the shaft system under actual operating conditions , calculate the real-time excitation torque of the shaft system based on the speed , the formula is: ,in, Input power to the shaft system;

[0037] S322: Real-time excitation torque Substitute it into the shaft system dynamics physical model equation in S31 and solve the equation using the numerical integration method to obtain the theoretical angular displacement response of the shaft system. ;

[0038] S323: Using the theoretical angular displacement response Calculate the theoretical displacement response ;

[0039] S324: Using theoretical displacement response and shaft stiffness coefficient , calculate the theoretical contact pressure response of the shaft system ;

[0040] S325: The theoretical displacement response calculated by S323 and S324 Contact pressure response with theory , respectively, with the displacement parameters measured by the synchronous data stream in S2 and pressure parameters Compare and get the displacement error sequence and the pressure error series ;

[0041] S326: Displacement error sequence and the pressure error series A joint analysis in time and frequency domains is performed, and the characteristic spectrum of the error sequence is extracted using fast Fourier transform. The frequency component and amplitude corresponding to the natural vibration mode of the shaft system in the spectrum are determined, and the signal feature corresponding to the frequency component is identified as the natural vibration noise component of the shaft system in the synchronous data stream.

[0042] Optionally, the S34 specifically includes:

[0043] S341: Get the real load signal after S33 decoupling, including the real contact pressure at the shaft section and the true displacement ;

[0044] S342: Calculate the true shear stress at the cross section based on the geometric parameters of the shafting cross section , the formula is: ,in, is the shear stress at the shafting section, is the cross-sectional force area of ​​the shaft system, is the polar moment of inertia of the shafting section;

[0045] S343: Using shear stress Calculation of shear moments at the shafting section , the formula is: ;

[0046] S344: Based on the overall structural parameters of the shaft system, the calculated shear moment Interpolate the longitudinal position of the shaft system to obtain the real-time torque distribution at each section of the shaft system .

[0047] Optionally, the S4 specifically includes:

[0048] S41: Get the real-time torque distribution of the shaft system calculated by S35 , and extract the torque value at the shafting section ;

[0049] S42: Obtain ship navigation status data, including speed and draft , and calculate the theoretical torque of the shaft system under the current sailing state based on the ship propulsion theory ;

[0050] S43: Compare the actual torque obtained by S41 with the theoretical torque calculated by S42 to calculate the shaft torque deviation , the formula is: ;

[0051] S44: Calculate dynamic safety threshold interval based on historical operating data and shafting load capacity ;

[0052] S45: Comparison of actual torque and safety threshold interval ,like , the shaft load is within the safe range and there is no warning; if or , then the warning is triggered according to the following rules;

[0053] Rule 1: When When the alarm is triggered, the first level warning is triggered;

[0054] Rule 2: When When the alarm is triggered, the second level warning is triggered;

[0055] Rule 3: When When the alarm is triggered, the third level warning is triggered;

[0056] in, is the absolute value of the torque deviation, and is the warning threshold coefficient.

[0057] Optionally, the S5 specifically includes:

[0058] S51: Based on the warning level triggered by S4 and the real-time torque distribution results of the shaft system, determine the analysis level and data range of the report, and generate a report template;

[0059] S52: Call historical data, retrieve historical shaft load data similar to the current warning event, compare the change trend with characteristic parameters, identify the cause of the current shaft load abnormality, and generate load tracing analysis content;

[0060] S53: Based on the load tracing analysis results, the maintenance suggestions corresponding to the abnormalities are matched from the preset maintenance expert rule library to generate inspection items, treatment measures and operation instructions;

[0061] S54: normalizing the shaft system real-time torque distribution data calculated in S34, drawing a data heat map based on the shaft system longitudinal position and the real-time torque distribution, and marking the load abnormality area;

[0062] S55: embed load tracing analysis, maintenance suggestions and data heat maps into interactive report templates to generate complete interactive reports.

[0063] Beneficial effects of the present invention:

[0064] The present invention solves the problems of data synchronization error and noise interference in shaft load analysis through real-time data monitoring and multi-sensor fusion; uses piezoresistive pressure sensors and optical fiber displacement sensors to synchronously collect shaft pressure and displacement data, and dynamically adjusts the sampling frequency based on the temperature and humidity in the ship cabin to ensure the environmental adaptability of the data; combines edge computing technology to achieve timestamp alignment and data frame encapsulation of sensor data, eliminates timing errors caused by asynchronous acquisition, and improves the accuracy and stability of load monitoring.

[0065] The present invention, by combining the ship's navigation status data, establishes a dynamic safety threshold adjustment mechanism to ensure that the safety range can be modified in real time as the working conditions change, and triggers graded warnings based on the degree of shaft load deviation to improve the accuracy of abnormal detection; for warning events, historical data analysis and expert rule library matching are used to generate interactive reports of load tracing analysis, intelligent maintenance suggestions and data heat maps, thereby improving the efficiency of abnormal fault diagnosis and processing. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only for the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0067] Figure 1 Schematic diagram of a shafting load analysis method according to an embodiment of the present invention;

[0068] Figure 2 The figure is a schematic diagram of the process of calculating the real-time torque distribution of the shaft system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0069] The present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. At the same time, it is explained here that in order to make the embodiments more detailed, the following embodiments are the best and preferred embodiments, and those skilled in the art may also adopt other alternatives to implement some known technologies; and the accompanying drawings are only for more specific description of the embodiments, and are not intended to specifically limit the present invention.

[0070] It should be noted that the references to "one embodiment", "embodiment", "exemplary embodiments", "some embodiments" and the like in the specification indicate that the embodiments described may include specific features, structures or characteristics, but not every embodiment may include the specific features, structures or characteristics. In addition, when a specific feature, structure or characteristic is described in conjunction with an embodiment, it should be within the knowledge of a person skilled in the art to implement such feature, structure or characteristic in conjunction with other embodiments (whether or not explicitly described).

[0071] In general, a term can be understood, at least in part, from its use in context. For example, depending, at least in part, on the context, the term "one or more" as used herein can be used to describe any feature, structure, or characteristic in the singular sense, or can be used to describe a combination of features, structures, or characteristics in the plural sense. Additionally, the term "based on" can be understood as not necessarily intended to convey an exclusive set of factors, but can instead, depending, at least in part, on the context, allow for the presence of other factors that are not necessarily explicitly described.

[0072] like Figure 1-Figure 2 As shown, a shaft load analysis method based on real-time data monitoring includes the following steps:

[0073] S1: The pressure and displacement parameters of the shaft system are synchronously collected through the piezoresistive pressure sensor and the optical fiber displacement sensor, and the sensor sampling frequency is dynamically adjusted based on the temperature and humidity data in the ship cabin to generate an original data set that is resistant to environmental interference;

[0074] S2: Through the deployed edge computing nodes, the original data set is timestamped and encapsulated, the timing error caused by asynchronous acquisition of multiple sensors is eliminated, and a synchronous data stream is generated;

[0075] S3: Based on the physical model of the ship shafting, the pressure and displacement parameters in the synchronous data stream are dynamically decoupled to separate the shafting inherent vibration noise and the real load signal, and the real-time torque distribution of the shafting is calculated through the decoupled real load signal;

[0076] S4: According to the shaft torque distribution results, combined with the ship's navigation status data (speed, draft depth), the safety threshold interval is dynamically corrected. If the torque distribution deviates from the correction threshold, a graded warning is triggered;

[0077] S5: Automatically generate an interactive report including load source tracing analysis, maintenance suggestions and data heat map based on the triggered warning level and torque distribution results.

[0078] S1 specifically includes:

[0079] S11: Use a piezoresistive pressure sensor to obtain the contact surface pressure of the shaft system, and use an optical fiber displacement sensor to detect the micro-displacement change of the shaft system. The two sensors are respectively arranged at the connection position between the bearing seat and the shaft system. The synchronous trigger signal is used to control the sampling, so that the pressure parameter and the displacement parameter complete the data collection at the same time point;

[0080] S12: Cache the collected pressure parameters and displacement parameters, and match them according to the timestamps to ensure that the sensor data in the same time window are aligned to form a complete raw data frame;

[0081] S13: Collect temperature and humidity data in the ship cabin, wherein the temperature data comes from the thermistor temperature sensor, and the humidity data comes from the humidity sensitive resistor sensor.

[0082] S1 also includes:

[0083] S14: Based on the fluctuation range of temperature and humidity data, a linear compensation algorithm is used to calculate the current environmental interference factor , the formula is: ,in, is the current temperature, Calibrate the sensor temperature, is the current humidity, Calibrate the sensor for humidity, is the empirical correction coefficient;

[0084] S15: Based on the calculated environmental interference factor , for the sampling frequency Dynamic adjustment is performed using the formula: ,in, is the standard sampling frequency, is the sampling frequency adjustment coefficient, is the adjusted sampling frequency;

[0085] S16: Perform a stability check on the adjusted data acquisition frequency. If the change in the sampling frequency between two adjacent times is less than the set threshold, perform formal data acquisition and generate an original data set that is resistant to environmental interference. The original data set includes timestamp, pressure parameters, displacement parameters, temperature and humidity data, and sampling frequency adjustment records. The above steps are used to synchronize the trigger signal to control data acquisition to ensure the consistency of pressure parameters and displacement parameters. At the same time, the sampling frequency is dynamically adjusted based on the temperature and humidity data, so that the sensor can adapt to environmental changes, improve the stability and accuracy of data acquisition, and provide high-quality basic data for subsequent shaft load analysis.

[0086] S2 specifically includes:

[0087] S21: receiving the original data set generated by S1 in the edge computing node, and extracting the timestamp attached to each sensor data in the original data set;

[0088] S22: Based on a unified time base, the linear interpolation alignment method is used to resample the raw data of the piezoresistive pressure sensor and the optical fiber displacement sensor to eliminate the timing difference of the sampling points caused by the response delay of the two sensors. The calculation formula of the linear interpolation alignment method is: ; In the formula, is the sensor data after interpolation calculation, Align timestamps for targets in a unified time base, and are the original data acquisition time before and after the target alignment timestamp, and Timestamp and The raw sensor data at the time

[0089] S23: Based on the aligned unified timestamp, the resampled pressure parameters and displacement parameters are combined into a structured data frame, each of which contains a unified timestamp, a pressure parameter, and a displacement parameter data pair;

[0090] S24: using a data frame encapsulation protocol to perform standardized encapsulation on the combined data frame, each encapsulated data frame includes a data frame identification header, a unified timestamp, a sensor identification code, a pressure parameter value, a displacement parameter value, and a data frame check code;

[0091] S25: Perform continuity check on the encapsulated data frames to confirm that the timestamps of the data frames are continuous and not missing. If there is a missing data frame or an abnormal timestamp, the abnormal data frame is discarded; and the data frames that pass the continuity check are spliced ​​into a continuous data stream in sequence, and then output a synchronous data stream with a unified timestamp and eliminated timing errors; the above steps eliminate the slight differences in acquisition time between multiple sensors through the linear interpolation alignment method, and use the data frame encapsulation protocol to form a structured data unit, ensuring the continuity and consistency of the data stream, thereby improving the data synchronization accuracy and providing an accurate data basis for the subsequent dynamic analysis of the shaft system load.

[0092] S3 specifically includes:

[0093] S31: Based on the geometric structure and material properties of the ship shaft system, a dynamic physical model of the shaft system is established, which includes the shaft system stiffness parameters, damping characteristic parameters and moment of inertia parameters;

[0094] S32: input the synchronous data stream obtained in S2 into the shaft system dynamics physical model, and determine the real-time excitation load in combination with the shaft system speed information, and calculate the theoretical vibration response value of the shaft system; and compare and analyze the theoretical vibration response value with the pressure parameters and displacement parameters measured by the synchronous data stream, identify the noise component generated by the shaft system inherent vibration in the synchronous data stream, and determine the time domain characteristics and spectrum distribution of the noise component;

[0095] S33: based on the identified shaft system inherent vibration noise component, deduct the noise component from the pressure parameter and displacement parameter measured by the synchronous data stream in the time domain and the frequency domain to obtain a decoupled real load signal;

[0096] S34: The real-time torque distribution at the shafting section is calculated using the decoupled real load signal. During the calculation process, the load state, geometric dimensions and material mechanical property parameters of the shafting are combined to first determine the real stress state of the shafting section, and then calculate the real-time torque distribution of the shafting at each stress point based on the stress state. The above steps establish an accurate shafting dynamics physical model, dynamically decouple the inherent vibration noise of the shafting, obtain a real and effective shafting load signal, and calculate the real-time torque distribution of the shafting based on the real load signal, thereby ensuring the accuracy and reliability of subsequent load analysis and safety warnings.

[0097] The dynamic physical model of the shaft system established in S31 specifically includes:

[0098] S311: Collect geometric structure parameters and mass distribution parameters of the shaft system, including the length, diameter, cross-sectional area and density of the shaft system, and form basic structural information of the shaft system based on actual measurement and drawing data;

[0099] S312: Obtain material mechanical characteristic parameters of the shaft system, including elastic modulus, Poisson's ratio and yield limit, and determine the deformation and strength characteristics of the shaft system under load by combining the test results and the standard material database;

[0100] S313: Calculate the overall stiffness coefficient of the shaft system based on the geometric structure parameters and material mechanical property parameters of the shaft system , damping coefficient And the moment of inertia , considering the shaft system as a rotating part with distributed mass, the above key coefficients are obtained based on vibration theory and material mechanics principles;

[0101] S314: Based on stiffness coefficient , damping coefficient , moment of inertia , and the external excitation torque , construct the dynamic physical model of the shaft system, the expression is: ,in, is the angular displacement of the shaft system, The external excitation torque is combined with the above dynamic physical model and the real working environment of the shaft system to verify the reliability of the model under different loads, and the final confirmed model parameters are stored in the dynamic analysis unit to provide accurate theoretical support for the subsequent vibration noise decoupling and torque distribution calculation.

[0102] S32 specifically includes:

[0103] S321: Based on the shaft system dynamics physical model constructed in S31, obtain the real-time speed of the shaft system under actual operating conditions , calculate the real-time excitation torque of the shaft system based on the speed , the formula is: ,in, Input power to the shaft system;

[0104] S322: Real-time excitation torque Substitute it into the shaft system dynamics physical model equation in S31 and solve the equation using the numerical integration method to obtain the theoretical angular displacement response of the shaft system. , theoretical angular velocity response and the theoretical angular acceleration response , the solution process uses the fourth-order Runge-Kutta integration method for numerical solution;

[0105] S323: Using the theoretical angular displacement response Calculate the theoretical displacement response , the formula is: ,in, is the theoretical linear displacement response of the shaft system, is the cross-sectional radius at the measuring point of the shaft system;

[0106] S324: Using theoretical displacement response and shaft stiffness coefficient , calculate the theoretical contact pressure response of the shaft system , the formula is: ,in, is the theoretical contact pressure response of the shaft system, is the overall stiffness coefficient of the shaft system;

[0107] S325: The theoretical displacement response calculated by S323 and S324 Contact pressure response with theory , respectively, with the displacement parameters measured by the synchronous data stream in S2 and pressure parameters Compare and get the displacement error sequence and the pressure error series , calculated as follows: ; ;in, is the displacement error, is the pressure error, is the measured displacement parameter, is the measured pressure parameter;

[0108] S326: Displacement error sequence and the pressure error series A joint analysis in the time and frequency domains is performed, and the characteristic spectrum of the error sequence is extracted using the fast Fourier transform (FFT). The frequency component and amplitude corresponding to the natural vibration mode of the shaft system in the spectrum are determined, and the signal feature corresponding to the frequency component is identified as the natural vibration noise component of the shaft system in the synchronous data stream. The above steps calculate the theoretical response value of the shaft system under real-time operating conditions, and perform detailed time and frequency domain comparative analysis with the measured parameters of the synchronous data stream to accurately identify and extract the natural vibration noise component of the shaft system, providing a theoretical basis for the subsequent precise decoupling of the real load signal.

[0109] S34 specifically includes:

[0110] S341: Get the real load signal after S33 decoupling, including the real contact pressure at the shaft section and the true displacement , ensure that the data has removed the inherent vibration noise of the shaft system;

[0111] S342: Calculate the true shear stress at the cross section based on the geometric parameters of the shafting cross section , the formula is: ,in, is the shear stress at the shafting section, is the cross-sectional force area of ​​the shaft system, is the polar moment of inertia of the shaft system section, Calculated by the following formula: ,in, is the cross-sectional diameter of the shaft system;

[0112] S343: Using shear stress Calculation of shear moments at the shafting section , the formula is: ;

[0113] S344: Based on the overall structural parameters of the shaft system, the calculated shear moment Interpolate the longitudinal position of the shaft system to obtain the real-time torque distribution at each section of the shaft system , the interpolation calculation formula is: ,in, is the longitudinal position of the axis The torque value at is the torque at the initial position of the shaft system, Calculated from the shaft load change; the above steps are based on the decoupled real load signal, and the real-time torque distribution at each section of the shaft is obtained by calculating the shear stress and shear moment and combining the longitudinal interpolation operation of the shaft, thereby ensuring the accuracy of the load analysis and providing a high-precision calculation basis for the subsequent safety threshold adjustment and early warning.

[0114] S4 specifically includes:

[0115] S41: Get the real-time torque distribution of the shaft system calculated by S35 , and extract the torque value at the shafting section ,in Represents the torque of the shaft system at a specified position;

[0116] S42: Obtain ship navigation status data, including speed and draft , and calculate the theoretical torque of the shaft system under the current sailing state based on the ship propulsion theory , the calculation formula is as follows: ,in, is the torque coefficient of the ship propulsion system, which is determined by the ship design parameters;

[0117] S43: Compare the actual torque obtained by S41 with the theoretical torque calculated by S42 to calculate the shaft torque deviation , the formula is: ;

[0118] S44: Calculate dynamic safety threshold interval based on historical operating data and shafting load capacity , the formula is: ; ,in, and They are respectively the upper and lower limits of the safe torque after dynamic correction, and It is the safety factor related to the navigation status, which is determined based on the historical data of the ship and the safety of the structure;

[0119] S45: Comparison of actual torque and safety threshold interval ,like , the shaft load is within the safe range and there is no warning; if or , then the warning is triggered according to the following rules;

[0120] Rule 1: When When the alarm is triggered, the first level warning is triggered;

[0121] Rule 2: When When the alarm is triggered, the second level warning is triggered;

[0122] Rule 3: When When the alarm is triggered, the third level warning is triggered;

[0123] in, is the absolute value of the torque deviation, and is the warning threshold coefficient, which is set based on the shafting structure safety standard. The above steps calculate the dynamic safety threshold interval by combining the real-time torque distribution of the shafting with the ship's navigation status data, and trigger graded warnings based on the degree of torque deviation, thereby realizing the intelligent monitoring of shafting load safety and improving the safety and reliability of ship operation.

[0124] S5 specifically includes:

[0125] S51: Based on the warning level triggered by S4 and the real-time torque distribution results of the shaft system, determine the analysis level and data range of the report, and generate a report template;

[0126] S52: Call historical data, retrieve historical shaft load data similar to the current warning event, compare the change trend with characteristic parameters, identify the cause of the current shaft load abnormality, and generate load tracing analysis content;

[0127] S53: Based on the load tracing analysis results, the maintenance suggestions corresponding to the abnormalities are matched from the preset maintenance expert rule library to generate inspection items, treatment measures and operation instructions;

[0128] The above maintenance expert rule base specifically includes the following rules:

[0129] When the measured torque of the shaft system deviates from the dynamic threshold range, perform coupling tightness detection and oil monitoring, check the connection between the seal and the bolt, and confirm whether the load abnormality is caused by coupling looseness or lubrication failure;

[0130] When the amplitude of the shaft system's natural vibration frequency exceeds the set threshold, perform bearing seat stiffness verification and lubrication system inspection to eliminate additional vibration caused by bearing wear or improper lubrication;

[0131] When the shaft system torque distribution shows gradient fluctuations in the longitudinal position, the overall shaft system straightening and clearance detection should be carried out, and maintenance plans should be formulated for potential shaft system deformation or flange connection loosening;

[0132] When the shaft system operating temperature exceeds the limit, start the joint inspection of the cooling water circuit and ventilation system to check whether the cooling efficiency is reduced or the shaft system is affected by external heat sources, and adjust the cooling water flow and fan speed if necessary;

[0133] When the high-frequency vibration of the shaft system produces an impact peak, immediately check the shaft system surface fatigue cracks and bolt fatigue damage. If cracks or loose bolts are found, take replacement or reinforcement measures;

[0134] When it is monitored that the torque fluctuation is negatively correlated with the ship's draft and the amplitude exceeds the predetermined ratio, the ship's draft database is combined to determine whether there is additional bending moment caused by uneven loading of the hull, and re-balancing suggestions are made for the loading problem.

[0135] S54: normalizing the shaft system real-time torque distribution data calculated in S34, drawing a data heat map based on the shaft system longitudinal position and the real-time torque distribution, and marking the load abnormality area;

[0136] S55: Load tracing analysis, maintenance suggestions and data heat maps are embedded in the interactive report template to generate a complete interactive report. The above steps automatically associate historical data, expert rule base and visualization algorithm to quickly generate accurate, intuitive and easy-to-understand interactive reports, so that abnormal shaft load problems can be traced and analyzed and maintenance decisions can be made in a timely and effective manner, ensuring the efficiency and safety of shaft operation and maintenance.

[0137] The present invention covers any substitution, modification, equivalent method and scheme made on the essence and scope of the present invention. In order to make the public have a thorough understanding of the present invention, specific details are described in detail in the following preferred embodiments of the present invention, but those skilled in the art can fully understand the present invention without the description of these details. In addition, in order to avoid unnecessary confusion about the essence of the present invention, well-known methods, processes, procedures, components and circuits are not described in detail.

[0138] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A shaft load analysis method based on real-time data monitoring, characterized in that: The following steps are involved: S1: The pressure and displacement parameters of the shaft system are synchronously collected through the piezoresistive pressure sensor and the optical fiber displacement sensor, and the sensor sampling frequency is dynamically adjusted based on the temperature and humidity data in the ship cabin to generate an original data set that is resistant to environmental interference; S2: Through the deployed edge computing nodes, the original data set is timestamped and encapsulated, the timing error caused by asynchronous acquisition of multiple sensors is eliminated, and a synchronous data stream is generated; S3: Based on the physical model of the ship shafting, the pressure and displacement parameters in the synchronous data stream are dynamically decoupled to separate the shafting inherent vibration noise and the real load signal, and the real-time torque distribution of the shafting is calculated through the decoupled real load signal; S4: Based on the shaft system torque distribution results and combined with the ship's navigation status data, the safety threshold interval is dynamically corrected. If the torque distribution deviates from the correction threshold, a graded warning is triggered; S5: Automatically generate an interactive report including load source tracing analysis, maintenance suggestions and data heat map based on the triggered warning level and torque distribution results.

2. The shafting load analysis method based on real-time data monitoring according to claim 1 is characterized in that: The S1 specifically includes: S11: Use a piezoresistive pressure sensor to obtain the contact surface pressure of the shaft system, and use an optical fiber displacement sensor to detect the micro-displacement change of the shaft system. The two sensors are respectively arranged at the connection position between the bearing seat and the shaft system. The synchronous trigger signal is used to control the sampling, so that the pressure parameter and the displacement parameter complete the data collection at the same time point; S12: Cache the collected pressure parameters and displacement parameters, and match them according to the timestamps to ensure that the sensor data in the same time window are aligned to form a complete raw data frame; S13: Collect temperature and humidity data in the ship cabin, wherein the temperature data comes from the thermistor temperature sensor, and the humidity data comes from the humidity sensitive resistor sensor.

3. The shafting load analysis method based on real-time data monitoring according to claim 2 is characterized in that: The S1 further comprises: S14: Based on the fluctuation range of temperature and humidity data, a linear compensation algorithm is used to calculate the current environmental interference factor , the formula is: ,in, is the current temperature, Calibrate the sensor temperature, is the current humidity, Calibrate the humidity for the sensor, is the empirical correction coefficient; S15: Based on the calculated environmental interference factor , for the sampling frequency Dynamic adjustment is performed using the formula: ,in, is the standard sampling frequency, is the sampling frequency adjustment coefficient, is the adjusted sampling frequency; S16: Perform a stability check on the adjusted data acquisition frequency. If the variation between two adjacent sampling frequencies is less than a set threshold, formal data acquisition is performed and an original data set resistant to environmental interference is generated.

4. The shafting load analysis method based on real-time data monitoring according to claim 1 is characterized in that: The S2 specifically includes: S21: receiving the original data set generated by S1 in the edge computing node, and extracting the timestamp attached to each sensor data in the original data set; S22: Based on a unified time reference, the original data of the piezoresistive pressure sensor and the optical fiber displacement sensor are resampled using a linear interpolation alignment method to eliminate the timing difference of the sampling points of the two sensors caused by the response delay; S23: Based on the aligned unified timestamp, the resampled pressure parameters and displacement parameters are combined into a structured data frame, each of which contains a unified timestamp, a pressure parameter, and a displacement parameter data pair; S24: using a data frame encapsulation protocol to perform standardized encapsulation on the combined data frame, each encapsulated data frame includes a data frame identification header, a unified timestamp, a sensor identification code, a pressure parameter value, a displacement parameter value, and a data frame check code; S25: Perform a continuity check on the encapsulated data frames to confirm that the timestamps of the data frames are continuous and not missing. If there is a missing data frame or an abnormal timestamp, the abnormal data frame is discarded; and the data frames that pass the continuity check are spliced ​​into a continuous data stream in sequence, and then a synchronous data stream with a unified timestamp and no timing errors is output.

5. The shafting load analysis method based on real-time data monitoring according to claim 1 is characterized in that: The S3 specifically includes: S31: Based on the geometric structure and material properties of the ship shaft system, a dynamic physical model of the shaft system is established, which includes the shaft system stiffness parameters, damping characteristic parameters and moment of inertia parameters; S32: input the synchronous data stream obtained in S2 into the shaft system dynamics physical model, and determine the real-time excitation load in combination with the shaft system speed information, and calculate the theoretical vibration response value of the shaft system; and compare and analyze the theoretical vibration response value with the pressure parameters and displacement parameters measured by the synchronous data stream, and identify the noise component generated by the inherent vibration of the shaft system in the synchronous data stream; S33: based on the identified shaft system inherent vibration noise component, deduct the noise component from the pressure parameter and displacement parameter measured by the synchronous data stream in the time domain and the frequency domain to obtain a decoupled real load signal; S34: Calculate the real-time torque distribution at the shafting section using the decoupled real load signal.

6. The shafting load analysis method based on real-time data monitoring according to claim 5 is characterized in that: The S31 specifically includes: S311: Collect the geometric structure parameters and mass distribution parameters of the shaft system, including the length, diameter, cross-sectional area and density of the shaft system; S312: Obtain material mechanical characteristic parameters of the shaft system, including elastic modulus, Poisson's ratio and yield limit; S313: Calculate the overall stiffness coefficient of the shaft system based on the geometric structure parameters and material mechanical property parameters of the shaft system , damping coefficient And the moment of inertia ; S314: Based on stiffness coefficient , damping coefficient , moment of inertia , and the external excitation torque , construct the dynamic physical model of the shaft system, the expression is: ,in, is the angular displacement of the shaft system, is the external excitation torque.

7. The shafting load analysis method based on real-time data monitoring according to claim 6 is characterized in that: The S32 specifically includes: S321: Based on the shaft system dynamics physical model constructed in S31, obtain the real-time speed of the shaft system under actual operating conditions , calculate the real-time excitation torque of the shaft system based on the speed , the formula is: ,in, Input power to the shaft system; S322: Real-time excitation torque Substitute it into the shaft system dynamics physical model equation in S31 and solve the equation using the numerical integration method to obtain the theoretical angular displacement response of the shaft system. ; S323: Using the theoretical angular displacement response Calculate the theoretical displacement response ; S324: Using theoretical displacement response and shaft stiffness coefficient , calculate the theoretical contact pressure response of the shaft system ; S325: The theoretical displacement response calculated by S323 and S324 Contact pressure response with theory , respectively, with the displacement parameters measured by the synchronous data stream in S2 and pressure parameters Compare and get the displacement error sequence and the pressure error series ; S326: Displacement error sequence and the pressure error series A joint analysis in time and frequency domains is performed, and the characteristic spectrum of the error sequence is extracted using fast Fourier transform. The frequency component and amplitude corresponding to the natural vibration mode of the shaft system in the spectrum are determined, and the signal feature corresponding to the frequency component is identified as the natural vibration noise component of the shaft system in the synchronous data stream.

8. The shafting load analysis method based on real-time data monitoring according to claim 7 is characterized in that: The S34 specifically includes: S341: Get the real load signal after S33 decoupling, including the real contact pressure at the shaft section and the true displacement ; S342: Calculate the true shear stress at the cross section based on the geometric parameters of the shafting cross section , the formula is: ,in, is the shear stress at the shafting section, is the cross-sectional force area of ​​the shaft system, is the polar moment of inertia of the shafting section; S343: Using shear stress Calculation of shear moments at shafting sections , the formula is: ; S344: Based on the overall structural parameters of the shaft system, the calculated shear moment Interpolate the longitudinal position of the shaft system to obtain the real-time torque distribution at each section of the shaft system .

9. The shafting load analysis method based on real-time data monitoring according to claim 1 is characterized in that: The S4 specifically includes: S41: Get the real-time torque distribution of the shaft system calculated by S35 , and extract the torque value at the shafting section ; S42: Obtain ship navigation status data, including speed and draft , and calculate the theoretical torque of the shaft system under the current sailing state based on the ship propulsion theory ; S43: Compare the actual torque obtained by S41 with the theoretical torque calculated by S42 to calculate the shaft torque deviation , the formula is: ; S44: Calculate dynamic safety threshold interval based on historical operating data and shafting load capacity ; S45: Comparison of actual torque and safety threshold interval ,like , the shaft load is within the safe range and there is no warning; if or , then the warning is triggered according to the following rules; Rule 1: When When the alarm is triggered, the first level warning is triggered; Rule 2: When When the alarm is triggered, the second level warning is triggered; Rule 3, when When the alarm is triggered, the third level warning is triggered; in, is the absolute value of the torque deviation, and is the warning threshold coefficient.

10. The shafting load analysis method based on real-time data monitoring according to claim 1 is characterized in that: The S5 specifically includes: S51: Based on the warning level triggered by S4 and the real-time torque distribution results of the shaft system, determine the analysis level and data range of the report, and generate a report template; S52: Call historical data, retrieve historical shaft load data similar to the current warning event, compare the change trend with characteristic parameters, identify the cause of the current shaft load abnormality, and generate load tracing analysis content; S53: Based on the load tracing analysis results, the maintenance suggestions corresponding to the abnormalities are matched from the preset maintenance expert rule library to generate inspection items, treatment measures and operation instructions; S54: normalizing the shaft system real-time torque distribution data calculated in S34, drawing a data heat map based on the shaft system longitudinal position and the real-time torque distribution, and marking the load abnormality area; S55: embed load tracing analysis, maintenance suggestions and data heat maps into interactive report templates to generate complete interactive reports.

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