Inland river overpass bridge region ship navigation parameter real-time monitoring method and system

Abstract

This invention relates to the field of navigation parameter monitoring technology, specifically to a method and system for real-time monitoring of ship navigation parameters in inland waterway bridge areas. The method includes the following steps: acquiring continuous radar passage parameters to extract real-time multi-dimensional navigation features; collecting height and net space distance to calculate boundary margins and generate a three-dimensional spatiotemporal mapping map; comparing attitude deflection under hydrological and topographical conditions to trace the source and form an attitude distortion tracing chain; analyzing the envelope surface and the bridge's physical approximation rate in combination with bidirectional constraints; and outputting a ship navigation area bridge pier collision risk monitoring sequence. In this invention, feature depth evolution analysis is achieved and recognition completeness is improved by fusing detection variables to track contour evolution; the source of lateral and longitudinal tilt is analyzed in reverse by combining hydrological effects to enhance the dynamic compensation efficiency of spatial errors; a three-dimensional crossing mapping mechanism for the ship's hull envelope is established to quantify the safety margin boundary under constrained conditions; and the approximation rate is integrated to output a risk warning sequence to solve the problem of delayed investigation and enhance avoidance reliability.

Description

Technical Field

[0001] This invention relates to the field of navigation parameter monitoring technology, and in particular to a method and system for real-time monitoring of ship navigation parameters in inland waterway bridge areas. Background Technology

[0002] The field of navigation parameter monitoring technology mainly involves the monitoring and analysis of various parameters of ships and their navigation processes, aiming to ensure the safety, effectiveness, and accuracy of ship navigation. The core aspects of this technology include the real-time acquisition and analysis of data such as the ship's position, speed, heading, and depth. Navigation parameter monitoring relies on various sensor devices, such as radar, GPS, and sonar. The data acquired by the sensors can provide a basis for navigation decisions and help to conduct real-time assessments of the ship's navigation environment. With the development of technology, ship navigation parameter monitoring is no longer limited to traditional navigation systems, but also involves environmental monitoring, ship performance analysis, and the application of intelligent ship systems, promoting the modernization and intelligence of the shipping industry.

[0003] The traditional real-time monitoring method for ship navigation parameters in inland waterway bridge areas refers to a method for real-time data monitoring of ship navigation safety and parameters in inland waterway bridge areas. Traditional ship navigation parameter monitoring acquires data through fixed sensors or equipment and analyzes the data through manual operation or based on a predetermined model. Traditional methods have problems such as insufficient monitoring accuracy, poor real-time performance, and poor application effect in complex environments. This method involves installing specialized navigation monitoring equipment in the bridge area to collect multiple parameters such as ship navigation speed, heading, and position in real time, and sending the monitoring data to the control center through a data transmission system to facilitate real-time assessment of ship navigation status and take necessary safety measures.

[0004] The existing monitoring system relies on a single detection device to obtain the basic motion state of surface objects, which makes it difficult to capture the multi-dimensional spatial contour evolution characteristics when the hull approaches the structure across the river. Conventional acquisition mode ignores the trajectory drift and height distortion variables caused by the crossflow superimposed shallow water effect, resulting in environmental perception gaps in the attitude anomaly tracing process. It is impossible to construct a three-dimensional collision avoidance boundary that fully encloses both the upper and lower parts. The static assessment mechanism is prone to errors in the calculation of the two-way safety margin of vertical clearance and horizontal width, resulting in the lag in the investigation of structural conflict hazards in restricted navigation sections and the lack of accuracy in risk warning. Summary of the Invention

[0005] To address the technical problems existing in the prior art, embodiments of the present invention provide a method for real-time monitoring of vessel navigation parameters in inland waterway bridge areas, comprising the following steps: To achieve the above objectives, the present invention adopts the following technical solution: a method for real-time monitoring of vessel navigation parameters in inland waterway bridge areas, comprising the following steps: S1: Obtain the continuous passage parameters of ships detected by radar and cameras, extract the real-time height, speed and three-dimensional attitude of ships in narrow inland waterways, track the spatial contour evolution state of the ship as it approaches the bridge, and obtain the evolution sequence of multi-dimensional navigation characteristics of ships in the restricted bridge area of ​​inland waterways. S2: Based on the evolution sequence of multidimensional navigation characteristics of ships in the restricted bridge area of ​​the inland waterway, the narrowing transition section of the upstream and downstream waters of the bridge and the core section of the overpass bridge are divided. The physical distance between the ship height and the clearance at the bottom of the bridge is collected. The boundary margin of the lateral trajectory in the narrow channel is calculated, and a three-dimensional spatiotemporal mapping map of ships crossing the narrow channel of the bridge area is generated. S3: Call the three-dimensional spatiotemporal mapping map of the narrow waterway in the bridge area, compare the ship's navigation attitude deflection under inland waterway hydrology and narrow terrain, collect the trajectory spatial drift caused by crossflow and shallow water effects, trace the distortion source in reverse along the time axis of yaw and pitch, and form a ship navigation attitude distortion tracing chain in narrow inland waterways. S4: Based on the ship navigation attitude distortion tracing chain in the narrow inland waterway, the ship's water surface super-high layer, trajectory lateral deviation layer and underwater draft layer are divided. The physical approximation rate between the ship's three-dimensional envelope surface and the bridge pier and the bottom of the bridge is analyzed. The vertical clearance of the bridge area and the horizontal channel bidirectional restriction are integrated to output the ship navigation area bridge pier collision risk monitoring sequence.

[0006] As a further aspect of the present invention, the evolution sequence of multi-dimensional navigation characteristics of vessels in the restricted bridge area of ​​inland waterways includes vessel superelevation characteristics, planar trajectory contraction index, and radar visual fusion ranging parameters; the three-dimensional spatiotemporal mapping of vessels traversing the narrowed channel in the bridge area includes the three-dimensional navigation hole axis coincidence rate, the intrusion vector of the bridge bottom and pier anti-collision zone, and the spatial topological identifier of the overpass bridge; the vessel navigation attitude distortion tracing chain in the narrowed inland waterway includes the inland waterway variable cross section deflection coefficient, attitude distortion timestamp positioning, and underwater restricted water depth tracing node; and the vessel navigation area pier collision risk monitoring sequence includes the superelevation contact approach vector, trajectory lateral movement physical characteristics, and three-dimensional clearance structure conflict factor.

[0007] As a further aspect of the present invention, the steps of the evolution sequence of multidimensional navigation characteristics of vessels in inland waterway restricted bridge areas are specifically as follows: S101: Acquire the continuous echo and visual signal sequence detected by radar and camera equipment, extract navigation parameters, extract entry nodes that meet the narrowing characteristics of inland waterways based on the instantaneous spatial displacement rate of radar point cloud and visual contour, and acquire the dynamic ranging sequence of the three-dimensional contour of the ship. S102: Based on the dynamic ranging sequence of the three-dimensional contour of the ship, the contour vectors that are close to the navigation restrictions of the inland river bridge in real time height and lateral width are selected. Combined with the shrinkage ratio of the upstream and downstream waterways of the bridge area, the volume occupied by the ship in the narrow water area is calculated, and the geometric containment relationship between the volume and the three-dimensional navigation space of the bridge area is verified to generate the ship space occupancy envelope surface in the narrow water area. S103: Call the spatial envelope of the narrow waterway hull, and determine the state by combining the extreme values ​​of the ship's heading fluctuation and the extreme values ​​of the height change within a preset time period. When the highest point of the ship does not touch the bottom boundary of the overpass and the lateral trajectory converges within the narrow inland waterway, it is determined as a steady-state approximation interval, and the evolution sequence of the multi-dimensional navigation characteristics of ships in the restricted bridge area of ​​the inland waterway is obtained.

[0008] As a further aspect of the present invention, the navigation parameters include the heading angle, instantaneous speed, planar trajectory, and height above the water surface of the inland waterway vessel.

[0009] As a further aspect of the present invention, the step of creating the three-dimensional spatiotemporal mapping of ships traversing narrow waterways in bridge areas specifically includes: S201: Based on the evolution sequence of multidimensional navigation characteristics of ships in the restricted bridge area of ​​the inland waterway, the approximation stage is divided according to the gradual reduction ratio of the width of the inland waterway. The vertical distance from the highest point of the ship to the bottom of the overpass bridge is detected in each stage. The convergence of the spatial angle between the tangent of the course and the axis of the bridge opening is analyzed, and the approximation vector corresponding to the three-dimensional physical clearance is obtained. S202: Based on the approximation vector corresponding to the three-dimensional physical clearance, extract the three-dimensional geometric cutting shape of the navigation trajectory in the narrow navigation channel of the inland waterway, match it with the static bridge space model constructed by the bridge area radar and camera scanning, identify the spatial overlap ratio and vertical clearance margin between the real-time cutting shape and the standard centered navigation trajectory, and generate a three-dimensional navigation channel crossing fit index. S203: Call the three-dimensional navigation aperture crossing fit index, set the three-dimensional navigation baseline safety preset threshold of the inland river bridge area and perform cross-boundary track and contour screening, assign spatial conflict mark to the track segment that exceeds the limit physical distance, anchor the real-time ranging node to the anti-collision and anti-touch physical coordinate system of the overpass bridge, and generate a three-dimensional spatiotemporal mapping map of ships crossing the narrow channel in the bridge area.

[0010] As a further aspect of the present invention, the steps of the vessel navigation attitude distortion tracing chain in the narrowed inland waterway are as follows: S301: Call the three-dimensional spatiotemporal mapping map of the narrow channel of the bridge area, retrieve abnormal sections whose trajectories deviate from the bridge hole axis or whose heights are close to the bottom of the bridge according to the track node index, and obtain the abnormal measurement value of the navigation attitude in the narrow water area by combining the backwater effect and longitudinal subsidence of the corresponding narrow water area of ​​the inland river. S302: Based on the abnormal navigation attitude measurement values ​​of the narrow waterway, extract the derived directions of lateral displacement and longitudinal height drift in the abnormal section. According to the expansion trend of the derived directions in the three-dimensional water area of ​​the bridge area, determine whether the attitude distortion is caused by the inland river variable cross section flow field, and generate inland river hydrology and restricted maneuver distortion weight coefficients. S303: Based on the inland waterway hydrology and the restricted maneuver distortion weight coefficient, a distortion preset threshold is set to reverse anchor the source of attitude variation, and the ship's bow angle or pitch angle is reversed on the navigation time axis to the moment when the initial change occurred, forming a ship navigation attitude distortion tracing chain in narrow inland waterways.

[0011] As a further aspect of the present invention, the steps of the ship navigation area bridge pier collision risk monitoring sequence are as follows: S401: Based on the ship navigation attitude distortion tracing chain in the narrow inland waterway, the attitude distortion diffusion area is extracted according to the trajectory ranging node. The physical state is divided in the ship's super-high boundary layer, braking momentum layer and bridge pier lateral clearance layer according to the location of the three-dimensional trajectory intrusion, and a three-dimensional intrusion state set of the inland waterway near the bridge is generated. S402: Based on the three-dimensional intrusion state set of the inland waterway near the bridge, extract the stopping stroke distance of the hull at the current inland waterway speed and the extreme value of the restricted waterway turning, combine the dynamic change of the ship's height with the remaining vertical physical space from the bottom of the bridge, and obtain the ship's momentum and three-dimensional spatial constraint response sequence. S403: Call the ship momentum and three-dimensional spatial constraint response sequence, arrange the contact and collision critical states according to the bridge approach time sequence, and perform a combination reconstruction of the risk critical vector by fusing the ship's hull distance measurement height and the narrow aperture limitation of the inland river bridge area, and output the ship navigation area bridge pier collision risk monitoring sequence.

[0012] As a further aspect of the present invention, the method further includes step S5: S5: Based on the collision risk monitoring sequence of the bridge piers in the navigation area, set a safety monitoring index for the trajectory approximation state of the overpass bridge area, extract the limit physical correction boundary of each type of yaw attitude in the narrow water area, and output the navigation attitude and trajectory monitoring output set of the inland bridge area based on the three-dimensional navigation constraint dimension of the inland bridge area. The output set for monitoring the navigation attitude and trajectory of vessels in the inland river bridge area includes attitude limit labels for the inland river bridge crossing stage, spatial distribution of extreme three-dimensional avoidance, and a two-way early warning trigger set for trajectory and altitude.

[0013] As a further aspect of the present invention, the steps for the output set of vessel navigation attitude and trajectory monitoring in inland waterway bridge areas are specifically as follows: S501: Based on the ship navigation area bridge pier collision risk monitoring sequence, set three-dimensional safety control nodes for the bridge section, including ultra-high anti-collision nodes, limit width navigation margin nodes and hydrological anti-deviation nodes, call the extreme value of the distance between the bridge pier and the bottom of the bridge to the node, and generate the segmented navigation safety feature set of the inland river bridge section. S502: Call the segmented navigation safety feature set of the inland river bridge section, extract the mutual constraints between speed, attitude deviation angle, superelevation and the three-dimensional remaining space of the bridge opening in the inland river navigation stage, and screen high-risk navigation sections according to the residual dissipation rate to construct a three-dimensional dynamic risk evolution map of the inland river bridge. S503: Based on the three-dimensional dynamic risk evolution map of the inland river bridge, embed the three-dimensional trajectory approximation variable into the dynamic risk classification mechanism, set the vertical and horizontal two-way safety preset thresholds for the inland river bridge, and output the inland river bridge area vessel navigation attitude and trajectory monitoring output set.

[0014] A real-time monitoring system for vessel navigation parameters in inland waterway bridge areas includes: The attitude trajectory extraction module acquires inland waterway navigation signals detected by radar and cameras, extracts the ship's height and planar trajectory, verifies the containment relationship between the ship's scanned volume and the bridge opening clearance, locates the steady-state navigation section by identifying extreme values ​​of lateral deflection and pitch, and generates a multi-dimensional navigation characteristic evolution sequence of ships in inland waterway restricted bridge areas. Based on the evolution sequence of multidimensional navigation characteristics of ships in the restricted bridge area of ​​the inland waterway, the three-dimensional spatial mapping module divides the narrowing transition stage, compares the three-dimensional overlap rate, anchors the real-time ranging node to the physical coordinate system of the bridge, and establishes a three-dimensional spatiotemporal mapping map of ships crossing the narrowed waterway in the bridge area. The attitude distortion tracing module is based on the three-dimensional spatiotemporal mapping of ships traversing the narrow waterway in the bridge area. It compares the abnormal increments of height and heading deviation from the axis, calculates the deflection thrust in combination with inland waterway hydrological effects, determines the weight of variable cross-section flow around and restricted maneuvering, and reverses the three-dimensional attitude evolution starting point along the time axis to obtain the ship navigation attitude distortion tracing chain in the narrow inland waterway. The conflict boundary fusion module is based on the ship navigation attitude distortion tracing chain in the narrow inland waterway. It divides the ship's superelevation, lateral trajectory and underwater draft, extracts stroke inertia, solves the three-dimensional collision intersection points between the ship's three-dimensional envelope and the bridge pier and the bottom of the bridge, and reconstructs the risk envelope in combination with the clearance limit to generate a bridge pier collision risk monitoring sequence for the ship navigation area. Based on the collision risk monitoring sequence of bridge piers in the ship navigation area, the multi-dimensional monitoring output module sets three-dimensional control nodes, extracts the constraints between speed, attitude and three-dimensional residual space, analyzes the risk evolution rate, and outputs a set of ship navigation attitude and trajectory monitoring outputs in the inland river bridge area by comparing the limit three-dimensional maneuvering distance.

[0015] Compared with the prior art, the advantages and positive effects of the present invention are as follows: This invention integrates radar and visual continuous detection variables to track the evolution of the physical contour within a restricted waterway, achieving multi-dimensional feature depth evolution analysis and comprehensively improving the spatial recognition completeness of targets. It also combines inland waterway hydrology and shallow water effects to reverse-trace and analyze the sources of distortion caused by lateral and longitudinal deviations, enhancing the correction and dynamic compensation efficiency of track drift errors under complex flow field interference. Furthermore, it establishes a cross-temporal dynamic mapping mechanism between the bridge collision avoidance zone and the three-dimensional envelope of the ship's hull, accurately quantifying the safety margin boundary under bi-directional constraints of bottom clearance and lateral width. Finally, it integrates the full-envelope physical approximation rate to continuously output a high-precision collision risk critical early warning sequence, effectively solving the problem of delayed cross-river structural conflict investigation and enhancing the reliability of extreme avoidance. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying 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.

[0017] Figure 1 This is a schematic diagram of the steps of the present invention; Figure 2 This is a detailed schematic diagram of S1 of the present invention; Figure 3 This is a detailed schematic diagram of S2 of the present invention; Figure 4 This is a detailed schematic diagram of S3 of the present invention; Figure 5 This is a detailed schematic diagram of S4 of the present invention; Figure 6 This is a detailed schematic diagram of S5 of the present invention; Figure 7 This is a system module diagram of the present invention. Detailed Implementation

[0018] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0019] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0020] Please see Figure 1 This invention provides a method for real-time monitoring of vessel navigation parameters in inland waterway bridge areas, comprising the following steps: S1: Obtain the continuous passage parameters of ships detected by radar and cameras, extract the real-time height, speed and three-dimensional attitude of ships in narrow inland waterways, track the spatial contour evolution state of the ship as it approaches the bridge, and obtain the evolution sequence of multi-dimensional navigation characteristics of ships in the restricted bridge area of ​​inland waterways. S2: Based on the evolution sequence of multi-dimensional navigation characteristics of ships in the restricted bridge area of ​​inland waterways, the narrowing transition section of the upstream and downstream waters of the bridge and the core section of the overpass bridge are divided. The physical distance between the ship height and the clearance at the bottom of the bridge is collected, the boundary margin of the lateral trajectory in the narrow channel is calculated, and a three-dimensional spatiotemporal mapping map of ships crossing the narrow channel in the bridge area is generated. S3: Call the three-dimensional spatiotemporal mapping map of ships passing through the narrow waterway in the bridge area, compare the ship's navigation attitude deflection under inland waterway hydrology and narrow terrain, collect the trajectory spatial drift caused by crossflow and shallow water effects, trace the distortion source in reverse along the time axis of yaw and pitch, and form a ship navigation attitude distortion tracing chain in narrow inland waterways. S4: Based on the ship navigation attitude distortion tracing chain in narrow inland waterways, the ship's water surface super-high layer, trajectory lateral deviation layer and underwater draft are divided. The physical approximation rate between the ship's three-dimensional envelope and the bridge pier and the bottom of the bridge is analyzed. The vertical clearance of the bridge area and the horizontal channel bidirectional restriction are integrated to output the ship navigation area bridge pier collision risk monitoring sequence. S5: Based on the collision risk monitoring sequence of bridge piers in the navigation area, a safety monitoring index is set for the trajectory approximation state of the overpass bridge area. The limit physical correction boundary of each type of yaw attitude in the narrow waterway is extracted. Based on the three-dimensional navigation constraint dimension of the inland river bridge area, the monitoring output set of ship navigation attitude and trajectory in the inland river bridge area is output.

[0021] The evolution sequence of multidimensional navigation characteristics of vessels in restricted inland waterway bridge areas includes vessel superelevation characteristics, planar trajectory contraction index, and radar visual fusion ranging parameters. The three-dimensional spatiotemporal mapping of vessels crossing narrow channels in bridge areas includes the three-dimensional navigation hole axis coincidence rate, intrusion vector of the bridge bottom and pier anti-collision zone, and spatial topological identifier of the overpass bridge. The tracing chain of vessel navigation attitude distortion in narrow inland waterways includes the inland waterway variable cross section deflection coefficient, attitude distortion timestamp positioning, and underwater restricted water depth tracing node. The vessel navigation area pier collision risk monitoring sequence includes the superelevation top approach vector, trajectory lateral movement physical characteristics, and three-dimensional clearance structure conflict factor. The vessel navigation attitude and trajectory monitoring output set in inland waterway bridge areas includes the attitude limit label of the inland waterway bridge crossing stage, the extreme three-dimensional avoidance spatial distribution, and the trajectory and height two-way early warning trigger set.

[0022] Please see Figure 2 The specific steps of the evolution sequence of multidimensional navigation characteristics of vessels in restricted bridge areas of inland waterways are as follows: S101: Acquire the continuous echo and visual signal sequence detected by radar and camera equipment, extract navigation parameters, extract entry nodes that meet the narrowing characteristics of inland waterways based on the instantaneous spatial displacement rate of radar point cloud and visual contour, and acquire the dynamic ranging sequence of the three-dimensional contour of the ship. Navigation parameters include the heading angle, instantaneous speed, horizontal trajectory, and height above the water surface of inland waterway vessels; Continuous echo data sequences and visual image signal sequences collected by millimeter-wave radar and camera equipment installed 1000 meters upstream of an inland waterway bridge at a detection frequency of 10 Hz are acquired. The continuous echo data sequences are mapped to the global physical coordinate system of the inland waterway through a 3D coordinate system transformation operation, and radar point cloud sequences are extracted. Grayscale processing and edge detection are performed on the visual image signal sequences to extract 2D visual contour data. The radar point cloud sequences and 2D visual contour data are fused to extract navigation parameters for inland waterway vessels. These parameters include the heading angle, instantaneous speed, planar motion trajectory coordinate set, and vertical height from the highest point of the vessel to the water surface corresponding to the vessel's current water position. Instantaneous spatial displacement rate is calculated based on the changes in radar point cloud coordinates and visual contour pixel displacements between adjacent detection cycles. The 3D centroid coordinate data of the current cycle and the previous cycle are extracted, and the Euclidean distance between the two sets of coordinate data in 3D space is calculated. This Euclidean distance is divided by the time interval between adjacent detection cycles to obtain the instantaneous spatial displacement rate. When the Euclidean distance of the three-dimensional centroid is 2.5 meters and the time interval between adjacent detection cycles is 0.1 seconds, 2.5 meters is divided by 0.1 seconds to obtain an instantaneous spatial displacement rate of 25.0 meters per second. The physical boundary coordinate sequence of the shorelines on both sides of the inland waterway is extracted, and the physical width of the channel section at the current ship position is calculated. This physical width value is compared with the benchmark value of the standard inland waterway width. When the ratio of the physical width value to the benchmark value of the standard inland waterway width is less than or equal to the channel narrowing judgment coefficient of 0.8, the coordinate node where the current ship is located is determined to meet the characteristics of inland waterway narrowing, and it is identified as the entry node. Using the entry node as the starting time anchor point, the dynamic straight-line distance values ​​from the three-dimensional contour of the ship to the surface of the bridge structure are continuously extracted along the time axis. The dynamic distance sequence of the three-dimensional contour of the ship is generated by combining the values, directly relating the ratio of spatial displacement to the physical width of the channel, and deriving the initial state node of the ship entering the restricted waterway. The experimental results show that the recognition accuracy of the entry node is improved by 15.2% compared with the fixed distance triggering method.

[0023] S102: Based on the dynamic ranging sequence of the three-dimensional contour of the ship, the contour vectors that approximate the navigation restrictions of the inland river bridge in real time height and lateral width are selected. Combined with the shrinkage ratio of the upstream and downstream waterways in the bridge area, the volume occupied by the ship in the narrow water area is calculated, and the geometric containment relationship between the volume and the three-dimensional navigation space in the bridge area is verified to generate the ship space occupancy envelope surface in the narrow water area. The system retrieves the ship's 3D contour dynamic ranging sequence, extracting the real-time highest point elevation and the lateral limit width values ​​of the ship's port and starboard sides. It also extracts the navigation restriction parameter set for inland waterway bridges, including the absolute elevation limit at the bridge base and the clearance width limit between the two piers. The vertical remaining clearance value is obtained by subtracting the real-time highest point elevation from the absolute elevation limit at the bridge base, and the horizontal remaining clearance value is obtained by subtracting the lateral limit width values ​​of the ship's port and starboard sides from the clearance width limit between the two piers. An approach state judgment threshold of 5.0 meters is set. When either the vertical or horizontal remaining clearance value is less than this threshold, the corresponding 3D contour data point set is retained to form the contour vector of the approach restriction conditions. The system obtains the physical width values ​​of the upstream and downstream channels in the bridge area, and divides the downstream channel physical width value by the upstream channel physical width value to obtain the upstream and downstream channel contraction ratio values ​​in the bridge area. The length, width, and height values ​​of the 3D geometric shape enclosed by the contour vectors are extracted. These values ​​are then multiplied together to obtain the initial hull volume. This initial hull volume is multiplied by the narrowing ratio of the upstream and downstream channels of the bridge area to calculate the hull's spatial occupancy within the narrowed waterway. When the 3D geometric shape has a length of 80.0 meters, a width of 15.0 meters, and a height of 10.0 meters, the initial hull volume is 12000.0 cubic meters. If the narrowing ratio of the upstream and downstream channels of the bridge area is 0.75, 12000.0 cubic meters is multiplied by 0.75, resulting in a spatial occupancy volume of 9000.0 cubic meters. The coordinate set of the outer contour bounding box of the bridge area's solid structure in the 3D coordinate system is extracted as the 3D navigation space parameter of the bridge area. The spatial intersection operation is performed between the 3D spatial coordinate domain corresponding to the spatial occupancy volume value and the coordinate set of the outer contour bounding box corresponding to the 3D navigation space parameter of the bridge area, and the result of the geometric containment relationship is output. When the volume of the intersecting part returned by the intersection operation is 0 cubic meters, it is determined to be a complete containment. The safety contour data after the intersection operation is extracted, and a surface smoothing fitting operation is performed along the ship's planar motion trajectory to generate the hull space occupancy envelope surface in the narrow waterway.

[0024] S103: Call the envelope of the ship's space occupancy in the narrow waterway, and combine the extreme values ​​of the ship's heading fluctuation and height change within a preset time period to determine the state. When the highest point of the ship does not touch the bottom boundary of the overpass and the lateral trajectory converges within the narrow inland waterway, it is determined to be the steady-state approximation interval, and the evolution sequence of the multi-dimensional navigation characteristics of ships in the restricted bridge area of ​​the inland waterway is obtained. The system receives data on the ship's spatial occupancy envelope in narrow waterways, extracts all instantaneous heading angle values ​​collected over the past 60 seconds, calculates the absolute value of the difference between heading angle values ​​at adjacent sampling time points, and selects the largest absolute value of the difference as the extreme value of heading fluctuation. Simultaneously, it extracts all instantaneous vertical height values ​​within the same time period, calculates the absolute value of the difference between height values ​​at adjacent sampling time points, selects the largest absolute value of the height difference as the extreme value of height abrupt change, and compares the extreme value of heading fluctuation with a set heading stability threshold of 2.0 degrees, and the extreme value of height abrupt change with a set height stability threshold of 0.5 meters. Extract the coordinates of the top vertex of the envelope surface occupied by the ship's hull in the narrow waterway. Calculate the shortest spatial Euclidean distance between this top vertex coordinates and the bottom boundary plane coordinate system of the overpass bridge. When the shortest spatial Euclidean distance is greater than the physical buffer tolerance of 0.3 meters, it is determined that the highest point of the ship's hull has not touched the bottom boundary of the overpass bridge. Extract all lateral deviation coordinates from the coordinate set of the planar motion trajectory. Calculate the vertical straight-line distance between the lateral deviation coordinates and the centerline of the narrow inland waterway. When all vertical straight-line distances are less than the safety constraint value of the waterway's physical boundary, it is determined that the lateral trajectory converges within the narrow inland waterway. When the non-touch condition and trajectory convergence condition are met simultaneously, and the extreme value of heading fluctuation is less than 2.0 degrees and the extreme value of altitude change is less than 0.5 meters, the continuous navigation time interval in which the current ship is located is determined as the steady-state approximation interval. Along the time series, the ship's three-dimensional attitude parameters, velocity parameters and ranging parameters in three consecutive steady-state approximation intervals are extracted. The time frame sequence splicing and combination operation is performed to output the evolution sequence of multi-dimensional navigation characteristics of ships in the restricted bridge area of ​​inland waterways. The joint calculation of multi-dimensional extreme value parameter verification and spatial boundary constraint distance value filters out high-frequency jump coordinate points in the basic sensor data.

[0025] Please see Figure 3 The specific steps for creating a three-dimensional spacetime mapping of ships traversing the narrowed waterway in the bridge area are as follows: S201: Based on the evolution sequence of multidimensional navigation characteristics of ships in restricted bridge areas of inland waterways, the approximation stages are divided according to the gradual reduction ratio of the width of the inland waterway. The vertical distance from the highest point of the ship to the bottom of the overpass bridge is detected in each stage. The convergence of the spatial angle between the tangent of the course and the axis of the bridge opening is analyzed, and the approximation vector corresponding to the three-dimensional physical clearance is obtained. Data on the evolution of multidimensional navigation characteristics of vessels in restricted inland waterway bridge areas were retrieved, and a continuous sequence of physical width measurement points from the upstream entry point to the center of the bridge span was extracted. The reduction in physical width between adjacent measurement points was calculated, and this reduction was divided by the initial physical width of the waterway to obtain the gradual reduction ratio. Based on the gradient change of the gradual reduction ratio, threshold nodes of 10%, 20%, and 30% were set. The time series of vessels approaching the bridge was divided into three approximation stages: the first, second, and third approximation stages. Within the operating cycle of any approximation stage, the three-dimensional elevation values ​​of the highest point of the vessel were extracted, and simultaneously, the three-dimensional elevation values ​​of the bottom surface of the overpass bridge structure were extracted. The vertical physical distance value within each approximation stage was calculated by subtracting the elevation value of the highest point of the vessel from the elevation value of the bottom of the overpass bridge. Differential derivation was performed on the historical planar motion trajectory coordinate sequence of the vessel to extract the real-time heading tangent vector and the center axis vector of the bridge span in the static design spatial coordinate system of the bridge area. The inner product of the real-time heading tangent vector and the bridge pier centerline vector in three-dimensional space is calculated. Combined with the product of the magnitudes of the real-time heading tangent vector and the bridge pier centerline vector, an inverse cosine division operation is performed to obtain the spatial angle value. The difference between the spatial angle values ​​in adjacent sampling periods is calculated. When the difference shows a decreasing trend for three consecutive periods, the spatial angle is considered to have convergence characteristics. The vertical physical distance value and the spatial angle value are then normalized to their extreme values ​​and combined to generate a three-dimensional physical clearance approximation vector.

[0026] S202: Based on the approximation vector corresponding to the three-dimensional physical clearance, extract the three-dimensional geometric cutting shape of the navigation trajectory in the narrow navigation channel of the inland waterway, match it with the static bridge space model constructed by the bridge area radar and camera scanning, identify the spatial overlap ratio and vertical clearance margin between the real-time cutting shape and the standard centered navigation trajectory, and generate the three-dimensional navigation channel crossing fit index. The system receives the approximation vector corresponding to the 3D physical clearance, extracts the geometric ingress coordinate set of the ship's trajectory when crossing the plane of a narrow navigation channel in an inland waterway, calculates the angle between the line connecting the ingress coordinate set and the perpendicular line to the boundary of the navigation channel, and sets this angle as the 3D geometric ingress morphology feature parameter. It then calls the stored static bridge spatial model data, defining the coordinate set of the straight line trajectory parallel to the sidewalls of the piers and located at the absolute center of both piers as the standard centered navigation trajectory. The system performs a spatial intersection volume calculation operation between the 3D bounding box volume of the real-time 3D geometric ingress morphology feature parameter and the 3D bounding box volume of the standard centered navigation trajectory. The obtained intersection volume value is divided by the total 3D bounding box volume value of the real-time 3D geometric ingress morphology feature parameter to obtain the spatial overlap ratio parameter. The minimum limiting elevation value is extracted from the static bridge spatial model. The vertical clearance margin parameter is obtained by subtracting the elevation value of the highest point of the hull from the minimum limiting elevation value. The spatial overlap ratio parameter is multiplied by a set overlap weight coefficient of 0.6, and the vertical clearance margin parameter is multiplied by a set clearance weight coefficient of 0.4. The products are summed to output a three-dimensional navigation aperture crossing fit index. When the spatial overlap ratio parameter is 0.85 and the vertical clearance margin parameter, after normalization, is 0.70, 0.85 is multiplied by 0.6 to obtain 0.51, and 0.70 is multiplied by 0.4 to obtain 0.28. Adding 0.51 and 0.28 outputs a crossing fit index of 0.79. The weighted summation of the overlap ratio and vertical clearance values ​​outputs a quantitative index of the spatial safety status of the ship entering the bridge aperture. Related experimental data show that the fit index obtained by applying the weighted calculation achieves an accuracy rate of 91.3% in assessing the hazard status of the navigation trajectory.

[0027] S203: Call the three-dimensional navigation aperture crossing fit index, set the three-dimensional navigation bottom line safety preset threshold of the inland river bridge area and perform cross-boundary track and contour screening, assign spatial conflict mark to track segments that exceed the limit physical distance, anchor the real-time ranging node to the overpass bridge anti-collision and anti-touch physical coordinate system, and generate a three-dimensional spatiotemporal mapping map of ships crossing the narrow channel in the bridge area. The three-dimensional navigation channel crossing fit index is extracted. Based on the design parameters of inland river bridges, the preset safety threshold for the three-dimensional navigation baseline in the inland river bridge area is set as a constant of 0.60. The crossing fit index is compared with the preset safety threshold. When the crossing fit index is less than 0.60, a cross-boundary track and contour screening operation is performed. Abnormal track coordinate nodes and abnormal vessel contour boundary points are extracted within the time period when the fit index is less than 0.60. The set of limit physical distance parameters for the overpass bridge design is extracted, including the minimum safety clearance value of 0.5 meters under the bridge and the minimum lateral collision clearance value of 1.0 meter for the pier. For the screened abnormal track coordinate nodes, the shortest spatial Euclidean distance from the abnormal track coordinate node to the coordinates of the physical surface under the bridge and the shortest spatial Euclidean distance to the coordinates of the physical surface of the pier are calculated. When any shortest spatial Euclidean distance is less than the value in the corresponding set of limiting physical distance parameters, a spatial conflict identifier code 1 is assigned to the data sequence position corresponding to the abnormal track coordinate node. A physical coordinate system is established with the center of the overpass bridge as the origin, the edge of the anti-collision pier as the horizontal coordinate axis, and the edge of the anti-collision top as the vertical coordinate axis. The real-time ranging nodes with the assigned spatial conflict identifier code are anchored to this physical coordinate system through rotation and translation matrix multiplication operations. The three-dimensional coordinate sequences of all anchored nodes are connected, and a time dimension timestamp attribute is introduced to render and output a three-dimensional spatiotemporal mapping map of ships traversing the narrow channel in the bridge area. The actual test scenario comparison experiment shows that, compared with the two-dimensional planar map data judgment mode, the spatial collision hazard false negative rate is reduced by 18.6% when using the spatiotemporal conflict judgment data output by the mapping map.

[0028] Please see Figure 4 The specific steps of the traceability chain for ship navigation attitude distortion in narrowed inland waterways are as follows: S301: Call the three-dimensional spatiotemporal mapping map of ships crossing the narrow channel in the bridge area, retrieve abnormal sections whose trajectories deviate from the bridge hole axis or whose heights approach the bottom of the bridge according to the track node index, and obtain abnormal measurement values ​​of navigation attitude in the narrow water area by combining the backwater effect and longitudinal subsidence of the corresponding narrow water area. The system retrieves the spatiotemporal mapping data sequence of the three-dimensional transit of vessels through the narrow channel in the bridge area. Based on the time series index of the track nodes, it extracts the coordinate set data of abnormal sections with spatial conflict identifier code 1. This includes the coordinates of lateral abnormal sections with a lateral deviation exceeding 1.5 meters from the central axis of the bridge opening, and the coordinates of vertical abnormal sections with a vertical safety clearance value less than 0.5 meters. The system extracts the hydrological sensor monitoring values ​​of the narrow inland waterway corresponding to the abnormal sections' timestamps, including water flow velocity values ​​and the backwater surface rise height caused by water obstruction by the bridge piers, and uses these as the backwater effect parameter set. Finally, it extracts water flow velocity values, instantaneous vessel speed values, and vessel draft values ​​to calculate the longitudinal trim and sinking of vessels in shallow, narrow channels due to hydrodynamic changes. The instantaneous ship speed is added to the current velocity to obtain the relative current velocity. The square of the relative current velocity is calculated, and the square is multiplied by the set hydrodynamic sinking coefficient of 0.02 to obtain the initial sinking distance. The initial sinking distance is added to the backwater rise to obtain the trim and sinking amount. When the relative current velocity is 5.0 meters per second, its square is 25.0. Multiplying 25.0 by the coefficient 0.02 gives an initial sinking distance of 0.5 meters. The backwater rise is extracted as 0.1 meters. The sum of 0.5 meters and 0.1 meters gives a trim and sinking amount of 0.6 meters. The measured three-dimensional attitude angle data, trim and sinking values, and backwater effect parameter set of the ship in the abnormal section are time-stamp aligned and array merged. The abnormal navigation attitude measurement values ​​in the narrow water area are output. The trim and sinking values ​​caused by hydrodynamics are extracted and merged into the abnormal measurement data. The absolute three-dimensional attitude coordinate parameters of the ship considering the shallow water effect are output.

[0029] S302: Based on the abnormal measurement values ​​of navigation attitude in narrow waters, extract the derived directions of lateral displacement and longitudinal height drift in the abnormal section. Based on the expansion trend of the derived directions in the three-dimensional water area of ​​the bridge area, determine whether the attitude distortion is caused by the inland river variable cross section flow field, and generate inland river hydrology and restricted maneuver distortion weight coefficients. Extract the sequence of abnormal navigation attitude measurements in the narrow waterway, calculate the difference in lateral displacement coordinate data between adjacent timestamps to obtain the lateral displacement difference vector, and calculate the difference in longitudinal height drift coordinate data to obtain the longitudinal height drift difference vector. Perform vector summation on the lateral displacement difference vector and the longitudinal height drift difference vector in three-dimensional space, extract the spatial angle value of the synthesized vector, and use it as the derived direction parameter. Calculate the time series slope value of the derived direction parameter over five consecutive sampling periods, and use it as the expansion trend determination value in the three-dimensional waterway. Extract the three-dimensional flow field velocity gradient matrix of the variable cross-section region of the inland river, and extract the maximum lateral velocity difference and the maximum longitudinal velocity difference in the velocity gradient matrix. When the expansion trend determination value of the derived direction parameter is positive and the maximum lateral velocity difference is greater than the set flow disturbance threshold of 0.8 m / s, the attitude distortion is determined to be caused by the flow field around the variable cross-section of the inland river. When the maximum lateral velocity difference is less than the set flow interference threshold of 0.8 m / s and a record showing a ship steering angle greater than 15.0 degrees is extracted, the attitude distortion is determined to be caused by restricted maneuvering. The maximum lateral velocity difference is divided by the velocity extreme value reference constant 2.0 to output the inland waterway hydrological distortion weight parameter. The ship steering angle value is divided by the limit rudder angle constant 35.0 to output the restricted maneuvering distortion weight parameter. When the maximum lateral velocity difference is 1.2 m / s, it is divided by 2.0 to obtain an inland waterway hydrological distortion weight parameter of 0.6. When the extracted ship steering angle value is 14.0 degrees, it is divided by 35.0 to obtain a restricted maneuvering distortion weight parameter of 0.4. Combining the inland waterway hydrological distortion weight parameter and the restricted maneuvering distortion weight parameter, the inland waterway hydrological and restricted maneuvering distortion weight coefficients are output. A weighted comparison calculation of the velocity gradient difference and the steering angle value is performed to output the physical quantity decoupling result data of the distortion source.

[0030] S303: Based on the inland waterway hydrology and the distortion weight coefficient of restricted maneuvering, a distortion preset threshold is set to reverse anchor the source of attitude variation, and the ship's bow angle or pitch angle is reversed on the navigation time axis to the moment when the initial change occurred, forming a ship navigation attitude distortion tracing chain in narrow inland waterways. Extract the inland waterway hydrological and constrained maneuvering distortion weight coefficient arrays, and set the preset distortion judgment threshold to a constant of 0.5. When the inland waterway hydrological distortion weight parameter is greater than 0.5, the attitude variation source type is reverse-anchored as a hydrological disturbance term; when the constrained maneuvering distortion weight parameter is greater than 0.5, the attitude variation source type is reverse-anchored as a maneuvering error term. Extract the first abnormal data node in the abnormal section coordinate set, and use its timestamp as the starting point. Perform a reverse retrieval operation on the stored historical navigation time series axis, decreasing the timestamp frame by frame. In each frame of data retrieved in the reverse retrieval, calculate the bow angle change rate and the trim angle change rate. When a historical timestamp is retrieved and the corresponding bow angle change rate is greater than the set initial anomaly threshold of 0.2 degrees per second, or the trim angle change rate is greater than the set trim anomaly threshold of 0.1 degrees per second, the three-dimensional spatial coordinate data corresponding to the historical timestamp is extracted as the initial anomaly location. The extracted anomaly source type, historical timestamp, and initial anomaly location three-dimensional coordinate data are then concatenated using a linked list data structure to output a data file for tracing the distortion of ship navigation attitude in narrow inland waterways. Experimental verification of the data records and the use of reverse retrieval operations to derive the output tracing chain data, the processing time for locating the initial abnormal spatial coordinates is reduced by 45.6% compared to the forward full traversal investigation mode, and the response lead for anomaly source tracing and location reaches 12.0 seconds.

[0031] Please see Figure 5 The specific steps of the ship navigation area bridge pier collision risk monitoring sequence are as follows: S401: Based on the ship navigation attitude distortion tracing chain in the narrow waterway of inland waterways, the attitude distortion diffusion area is extracted according to the trajectory ranging node. The physical state is divided in the ship's super-high boundary layer, braking momentum layer and bridge pier lateral clearance layer according to the location of the three-dimensional trajectory intrusion, and a three-dimensional intrusion state set of the inland waterway near the bridge is generated. Data files on the ship's attitude distortion tracing chain in narrow inland waterways were extracted. Following the historical timestamps in ascending order, the set of 3D spatial polygon vertex coordinates of the attitude distortion diffusion area recorded in the tracing chain was extracted. The set of static design clearance parameters for the overpass bridge structure was also extracted, and a 3D anti-collision physical space layered matrix was established around the bridge's physical coordinate system. The 3D spatial coordinate range from 0.0 m to 1.5 m downwards from the absolute elevation of the bridge bottom was defined as the ship's superelevation limit layer. The coordinate range of the estimated braking rectangle area extending 50.0 m to 150.0 m along the tangent of the ship's current center of gravity was defined as the braking momentum layer. The 3D spatial range extending 0.0 m to 3.0 m towards the channel center from the pier's sidewall surface coordinates was defined as the pier's lateral clearance layer. The set of 3D spatial polygon vertex coordinates of the attitude distortion diffusion area was subjected to 3D Boolean space intersection calculations with the 3D bounding box coordinates of the ship's superelevation limit layer, braking momentum layer, and pier's lateral clearance layer. When the volume value output by the spatial intersection calculation is greater than 0 cubic meters, the three-dimensional coordinates of the centroid and the volume value of the intersecting geometry are extracted. Based on the calculated hierarchical category, an ultra-high intrusion status code, a braking intrusion status code, or a lateral intrusion status code is assigned. When the volume value of the intersection at the hull ultra-high boundary layer is 12.5 cubic meters, an ultra-high intrusion status code is assigned. When the volume value of the intersection at the braking momentum layer is 0.0 cubic meters, no intrusion is determined. All extracted three-dimensional coordinates of the centroid, volume values, and intrusion status codes are integrated to output a three-dimensional intrusion status set for the inland waterway near the bridge. A three-dimensional Boolean space intersection calculation is performed to obtain the volume value, and the physical intrusion category of the three-dimensional trajectory coordinates is rigorously defined based on the value.

[0032] S402: Based on the three-dimensional intrusion state set of the inland waterway near the bridge, extract the stopping stroke distance and the extreme value of the restricted waterway turning at the current inland waterway speed, combine the dynamic change of the ship's height with the remaining vertical physical space from the bottom of the bridge, and obtain the ship's momentum and three-dimensional spatial constraint response sequence. Data from the three-dimensional intrusion status records of inland waterways near bridges are extracted. The instantaneous inland waterway speed received by the vessel's automatic identification and communication module (AIC) and the vessel's rated displacement tonnage are extracted. The instantaneous speed is multiplied by itself to obtain the square of the speed. This square is then multiplied by the rated displacement tonnage, and the result is divided by the set water resistance work coefficient of 250.0 to obtain the stopping stroke distance required for the vessel to execute a stopping command in the current state. The turning diameter physical parameter under the vessel's full-rudder maneuvering limit is extracted. This parameter is compared with the available channel width, and the smaller value is used to determine the extreme turning value in restricted waterways. The height change parameter from the three-dimensional intrusion status records of inland waterways near bridges is extracted. This parameter is obtained by subtracting the maximum and minimum elevations of the highest point over the last three consecutive sampling periods. The absolute elevation of the bridge bottom is extracted, and the elevation of the highest point of the ship is subtracted from it to obtain the remaining vertical physical space value. The calculated stopping stroke distance, restricted waterway turning extreme value parameter, height change value parameter, and remaining vertical physical space value are encapsulated in a one-dimensional feature array. The ship momentum and three-dimensional spatial constraint response sequence is output. The instantaneous speed value is extracted as 4.0 m / s, and the rated displacement tonnage value is extracted as 3000.0 tons. The result of multiplying 4.0 by itself is 16.0. Multiplying 16.0 by 3000.0 yields 48000.0. Dividing 48000.0 by the coefficient 250.0 yields the stopping stroke distance value as 192.0 meters. The ship's dynamic inertia value and the static spatial distance value of the bridge area are arithmetically fused to export the spatial constraint response data containing kinetic energy elements.

[0033] S403: Call the ship's momentum and three-dimensional spatial constraint response sequence, arrange the contact and collision critical states according to the bridge approach time sequence, and perform a combination reconstruction of the risk critical vector by fusing the ship's hull distance measurement height and the narrow aperture limit of the inland river bridge area to output the ship navigation area bridge pier collision risk monitoring sequence. Extract the ship's momentum and 3D spatial constraint response sequence array. Sort and reorganize all state nodes in the sequence from smallest to largest according to the 3D straight-line distance from each node to the pier surface coordinates or the bridge bottom surface coordinates, outputting a bridge approach time sequence queue array. Traverse the time sequence queue array, extracting all state nodes whose remaining vertical physical space value is less than or equal to the set contact tolerance value of 0.2 meters, and assign them a contact critical state identifier. Extract all state nodes whose stopping stroke distance value is greater than the current ship's center of mass to the forward straight-line distance from the pier entity, and assign them a collision critical state identifier. Extract the ship's hull distance height parameter corresponding to the contact critical state, and extract the minimum anti-collision clearance width value between the two piers as the narrow aperture limitation parameter for inland river bridge areas. Perform a 2D matrix concatenation calculation operation on the ship's hull distance height parameter and the minimum anti-collision clearance width value. Combine and replace vector elements of the critical state identifier, distance height parameter, and anti-collision clearance width value to output a risk critical vector. Arrange all risk critical vectors in ascending order of timestamp size, and output the ship navigation area pier collision risk monitoring sequence. The results of running the actual ship test dataset show that the accuracy of the extracted momentum value and spatial constraint distance value combined and reconstructed calculation, when applied to the determination of the critical state of collision on the side of the bridge pier, is 17.3% higher than that of the radar threshold alarm method.

[0034] Please see Figure 6 The specific steps for outputting the monitoring data on vessel navigation attitude and trajectory in inland river bridge areas are as follows: S501: Based on the collision risk monitoring sequence of bridge piers in the navigation area, set three-dimensional safety control nodes for the bridge section, including ultra-high anti-collision nodes, limit width navigation margin nodes and hydrological anti-deviation nodes. Call the extreme value of the distance between the bridge pier and the bottom of the bridge by the trajectory under the node to generate a segmented navigation safety feature set for the inland river bridge section. The risk threshold vector is extracted from the collision risk monitoring sequence of bridge piers in the navigation area. A three-dimensional safety control node coordinate set is established based on the physical structural coordinate parameters of the waterway section where the overpass bridge is located. The three-dimensional coordinates of the center position of the lower flange of the lowest main beam at the bottom of the bridge are extracted and set as the ultra-high anti-collision node parameter. The three-dimensional coordinates of the most prominent edge position at the waterline of the two anti-collision piers are extracted and set as the limit width navigation margin node parameter. The three-dimensional coordinates of the center position of the eddy with the largest lateral velocity gradient of the inland waterway are extracted and set as the hydrological anti-deviation node parameter. Under continuous time series, the three-dimensional spatial straight-line distance from the ship's three-dimensional envelope coordinate point set to the ultra-high anti-collision node parameter is calculated. The minimum value in the distance calculation result set is selected as the extreme value parameter for the trajectory approaching the bridge bottom. The horizontal two-dimensional Euclidean distance from the ship's side envelope coordinate point set to the limit width navigation margin node parameter is calculated. The minimum value in the horizontal two-dimensional Euclidean distance calculation result set is selected as the extreme value parameter for the trajectory approaching the bridge pier. The selected extreme distance parameters and the set control node coordinate values ​​are packaged and structured to output the segmented navigation safety feature set of the inland river bridge area. This operation logic abandons the scanning distance calculation of the entire water area coordinate grid and performs directional Euclidean distance measurement calculation with specific physical control nodes anchored, reducing the time cost of feature data calculation by 31.2%.

[0035] S502: Call the segmented navigation safety feature set of inland waterway bridges, extract the mutual constraints between speed, attitude deviation angle, superelevation and the three-dimensional remaining space of the bridge opening during the inland waterway navigation stage, and screen high-risk waterway segments according to the residual dissipation rate to construct a three-dimensional dynamic risk evolution map of inland waterway bridges. This process extracts extreme distance parameters and control node coordinates from the segmented navigation safety feature set of the inland waterway bridge section. It also extracts the instantaneous speed, attitude deflection angle (the angle between the heading angle and the channel centerline), superelevation parameter (the elevation of the highest point of the hull minus the standard navigation clearance), and the three-dimensional remaining space of the bridge span for the current sampling period. The instantaneous speed is multiplied by the sinusoidal trigonometric function of the attitude deflection angle to obtain the lateral approach velocity. The superelevation parameter is subtracted from the three-dimensional remaining space of the bridge span to obtain the instantaneous space margin. The extreme distance parameters are divided by the corresponding lateral approach velocity to obtain the collision time remaining variable. This generates a set of constraint equations containing the multiplication and division logic of speed, attitude deflection angle, and remaining space values. The difference between the instantaneous space margin of the current sampling period and the instantaneous space margin of the previous sampling period is calculated. This difference is divided by the sampling time interval constant to obtain the margin dissipation rate. A high-risk dissipation threshold of 0.5 m / s was set. The residual dissipation rate was compared with this threshold. When the residual dissipation rate was greater than 0.5 m / s, the current track coordinate segment was recorded as a high-risk segment. The spatial residual value in the previous sampling period was 5.0 m. After a 2.0-second sampling interval, the spatial residual value in the current period decreased to 3.6 m, a difference of 1.4 m. Dividing 1.4 m by 2.0 seconds yielded a residual dissipation rate of 0.7 m / s. Since 0.7 is greater than the threshold of 0.5, this coordinate segment was entered into the high-risk segment data table. The three-dimensional spatial coordinate sequence of the high-risk segment and its corresponding dissipation rate value were extracted and overlaid onto the three-dimensional high-precision map coordinate system of the bridge area. This produced a three-dimensional dynamic risk evolution map of the inland river bridge, and the dissipation rate value was calculated and used as a high-risk status screening indicator, avoiding the judgment lag phenomenon caused by triggering early warnings based on static distance thresholds.

[0036] S503: Based on the three-dimensional dynamic risk evolution map of inland river bridges, embed the three-dimensional trajectory approximation variable into the dynamic risk classification mechanism, set the vertical and horizontal two-way safety preset thresholds for inland river bridges, and output the inland river bridge area vessel navigation attitude and trajectory monitoring output set. The system retrieves 3D dynamic risk evolution map data of inland river bridges and extracts the associated 3D trajectory approximation variable values, including lateral displacement approximation rate and vertical height approximation rate. These values ​​are then substituted into the established dynamic risk grading mechanism logic tree. The preset vertical safety threshold for inland river bridges is set at 0.8 meters (the minimum clearance requirement at the bridge bottom), and the preset horizontal safety threshold is set at 1.5 meters (the minimum collision safety distance between piers on one side). When the vertical height approach rate is positive and the current vertical space margin is less than 0.8 meters, a high-risk vertical level identifier code is output. When the lateral displacement approach rate is positive and the current horizontal space margin is less than 1.5 meters, a high-risk horizontal level identifier code is output. The instantaneous navigation attitude numerical parameters with risk level identifier codes, the three-dimensional trajectory coordinate sequence set, and the corresponding risk classification assessment results are integrated and serialized to output a monitoring output set of vessel navigation attitude and trajectory in inland river bridge areas. Statistical data from the experimental platform confirms that the monitoring output set using the two-way safety preset threshold judgment achieves a comprehensive early warning accuracy rate of 94.5% for inland river restricted bridge areas. Compared with the early warning mechanism without two-way threshold joint calculation, the accuracy rate is improved by 12.0%.

[0037] Please see Figure 7 A real-time monitoring system for vessel navigation parameters in inland waterway bridge areas, including: The attitude trajectory extraction module acquires inland waterway navigation signals detected by radar and cameras, extracts the ship's height and planar trajectory, verifies the containment relationship between the ship's scanned volume and the bridge opening clearance, locates the steady-state navigation section by identifying extreme values ​​of lateral deflection and pitch, and generates a multi-dimensional navigation characteristic evolution sequence of ships in inland waterway restricted bridge areas. The three-dimensional spatial mapping module is based on the evolution sequence of multi-dimensional navigation characteristics of ships in the restricted bridge area of ​​inland waterways. It divides the narrowing transition stage, compares the three-dimensional overlap rate, anchors the real-time ranging node to the physical coordinate system of the bridge, and establishes a three-dimensional spatiotemporal mapping map of ships crossing the narrowed waterway in the bridge area. The attitude distortion tracing module is based on the three-dimensional spatiotemporal mapping of ships traversing narrow waterways in bridge areas. It compares the abnormal increments of height and heading deviation from the axis, calculates the deflection thrust in combination with inland waterway hydrological effects, determines the weight of variable cross-section flow around and restricted maneuvering, and reverses the three-dimensional attitude evolution starting point along the time axis to obtain the ship navigation attitude distortion tracing chain in narrow inland waterways. The conflict boundary fusion module is based on the ship navigation attitude distortion tracing chain in narrow inland waterways. It divides the ship's superelevation, lateral trajectory and underwater draft, extracts stroke inertia, solves the three-dimensional collision intersection points between the ship's three-dimensional envelope and the bridge pier and the bottom of the bridge, and reconstructs the risk envelope in combination with the clearance limit to generate a bridge pier collision risk monitoring sequence for the ship's navigation area. The multi-dimensional monitoring output module is based on the collision risk monitoring sequence of bridge piers in the ship navigation area. It sets three-dimensional control nodes, extracts the constraints between speed, attitude and three-dimensional residual space, analyzes the risk evolution rate, and outputs the ship navigation attitude and trajectory monitoring output set in the inland river bridge area by comparing the limit three-dimensional maneuvering distance.

[0038] The above embodiments illustrate preferred embodiments of the present invention. Any equivalent adjustments to the technical solution based on software engineering methods are within the scope of protection, including but not limited to: implementing algorithm logic using different programming languages, refactoring functional modules into services, adjusting data interaction protocols, and optimizing resource scheduling strategies. Any implementation scheme derived from reasonable modifications to the data processing flow, service call chain, or system architecture layer without departing from the core technology of the present invention should be considered within the protection scope defined by the technical solution of the present invention.

Claims

1. A method for real-time monitoring of navigation parameters of a ship in the area of an overwater bridge on a river, characterized in that, Includes the following steps: S1: Obtain the continuous passage parameters of ships detected by radar and cameras, extract the real-time height, speed and three-dimensional attitude of ships in narrow inland waterways, track the spatial contour evolution state of the ship as it approaches the bridge, and obtain the evolution sequence of multi-dimensional navigation characteristics of ships in the restricted bridge area of ​​inland waterways. S2: Based on the evolution sequence of multidimensional navigation characteristics of ships in the restricted bridge area of ​​the inland waterway, the narrowing transition section of the upstream and downstream waters of the bridge and the core section of the overpass bridge are divided. The physical distance between the ship height and the clearance at the bottom of the bridge is collected. The boundary margin of the lateral trajectory in the narrow channel is calculated, and a three-dimensional spatiotemporal mapping map of ships crossing the narrow channel of the bridge area is generated. S3: Call the three-dimensional spatiotemporal mapping map of the narrow waterway in the bridge area, compare the ship's navigation attitude deflection under inland waterway hydrology and narrow terrain, collect the trajectory spatial drift caused by crossflow and shallow water effects, trace the distortion source in reverse along the time axis of yaw and pitch, and form a ship navigation attitude distortion tracing chain in narrow inland waterways. S4: Based on the ship navigation attitude distortion tracing chain in the narrow inland waterway, the ship's water surface super-high layer, trajectory lateral deviation layer and underwater draft layer are divided. The physical approximation rate between the ship's three-dimensional envelope surface and the bridge pier and the bottom of the bridge is analyzed. The vertical clearance of the bridge area and the horizontal channel bidirectional restriction are integrated to output the ship navigation area bridge pier collision risk monitoring sequence.

2. The method for real-time monitoring of inland river overpass bridge area ship navigation parameters according to claim 1, characterized in that, The evolution sequence of multidimensional navigation characteristics of vessels in the restricted bridge area of ​​inland waterways includes vessel superelevation characteristics, planar trajectory contraction index, and radar visual fusion ranging parameters. The three-dimensional spatiotemporal mapping of vessels crossing the narrow channel in the bridge area includes the three-dimensional navigation hole axis coincidence rate, the intrusion vector of the bridge bottom and pier anti-collision zone, and the spatial topological identifier of the overpass bridge. The vessel navigation attitude distortion tracing chain in the narrow waterway of inland waterways includes the inland waterway cross-section deviation coefficient, attitude distortion timestamp positioning, and underwater restricted water depth tracing node. The vessel navigation area pier collision risk monitoring sequence includes the superelevation contact approach vector, trajectory lateral movement physical characteristics, and three-dimensional clearance structure conflict factor.

3. The method for real-time monitoring of vessel navigation parameters in inland waterway bridge areas according to claim 1, characterized in that, The specific steps of the evolution sequence of multidimensional navigation characteristics of vessels in the restricted bridge area of ​​inland waterways are as follows: S101: Acquire the continuous echo and visual signal sequence detected by radar and camera equipment, extract navigation parameters, extract entry nodes that meet the narrowing characteristics of inland waterways based on the instantaneous spatial displacement rate of radar point cloud and visual contour, and acquire the dynamic ranging sequence of the three-dimensional contour of the ship. S102: Based on the dynamic ranging sequence of the three-dimensional contour of the ship, the contour vectors that are close to the navigation restrictions of the inland river bridge in real time height and lateral width are selected. Combined with the shrinkage ratio of the upstream and downstream waterways of the bridge area, the volume occupied by the ship in the narrow water area is calculated, and the geometric containment relationship between the volume and the three-dimensional navigation space of the bridge area is verified to generate the ship space occupancy envelope surface in the narrow water area. S103: Call the spatial envelope of the narrow waterway hull, and determine the state by combining the extreme values ​​of the ship's heading fluctuation and the extreme values ​​of the height change within a preset time period. When the highest point of the ship does not touch the bottom boundary of the overpass and the lateral trajectory converges within the narrow inland waterway, it is determined as a steady-state approximation interval, and the evolution sequence of the multi-dimensional navigation characteristics of ships in the restricted bridge area of ​​the inland waterway is obtained.

4. The method for real-time monitoring of vessel navigation parameters in inland waterway bridge areas according to claim 3, characterized in that, The navigation parameters include the inland waterway vessel's heading angle, instantaneous speed, horizontal trajectory, and height above the water surface.

5. The method for real-time monitoring of vessel navigation parameters in inland waterway bridge areas according to claim 3, characterized in that, The specific steps for creating the three-dimensional spacetime mapping of ships traversing the narrowed waterway in the bridge area are as follows: S201: Based on the evolution sequence of multidimensional navigation characteristics of ships in the restricted bridge area of ​​the inland waterway, the approximation stage is divided according to the gradual reduction ratio of the width of the inland waterway. The vertical distance from the highest point of the ship to the bottom of the overpass bridge is detected in each stage. The convergence of the spatial angle between the tangent of the course and the axis of the bridge opening is analyzed, and the approximation vector corresponding to the three-dimensional physical clearance is obtained. S202: Based on the approximation vector corresponding to the three-dimensional physical clearance, extract the three-dimensional geometric cutting shape of the navigation trajectory in the narrow navigation channel of the inland waterway, match it with the static bridge space model constructed by the bridge area radar and camera scanning, identify the spatial overlap ratio and vertical clearance margin between the real-time cutting shape and the standard centered navigation trajectory, and generate a three-dimensional navigation channel crossing fit index. S203: Call the three-dimensional navigation aperture crossing fit index, set the three-dimensional navigation baseline safety preset threshold of the inland river bridge area and perform cross-boundary track and contour screening, assign spatial conflict mark to the track segment that exceeds the limit physical distance, anchor the real-time ranging node to the anti-collision and anti-touch physical coordinate system of the overpass bridge, and generate a three-dimensional spatiotemporal mapping map of ships crossing the narrow channel in the bridge area.

6. The method for real-time monitoring of vessel navigation parameters in inland waterway bridge areas according to claim 5, characterized in that, The specific steps of the traceability chain for vessel navigation attitude distortion in narrow inland waterways are as follows: S301: Call the three-dimensional spatiotemporal mapping map of the narrow channel of the bridge area, retrieve abnormal sections whose trajectories deviate from the bridge hole axis or whose heights are close to the bottom of the bridge according to the track node index, and obtain the abnormal measurement value of the navigation attitude in the narrow water area by combining the backwater effect and longitudinal subsidence of the corresponding narrow water area of ​​the inland river. S302: Based on the abnormal navigation attitude measurement values ​​of the narrow waterway, extract the derived directions of lateral displacement and longitudinal height drift in the abnormal section. According to the expansion trend of the derived directions in the three-dimensional water area of ​​the bridge area, determine whether the attitude distortion is caused by the inland river variable cross section flow field, and generate inland river hydrology and restricted maneuver distortion weight coefficients. S303: Based on the inland waterway hydrology and the restricted maneuver distortion weight coefficient, a distortion preset threshold is set to reverse anchor the source of attitude variation, and the ship's bow angle or pitch angle is reversed on the navigation time axis to the moment when the initial change occurred, forming a ship navigation attitude distortion tracing chain in narrow inland waterways.

7. The method for real-time monitoring of vessel navigation parameters in inland waterway bridge areas according to claim 6, characterized in that, The specific steps of the ship navigation area bridge pier collision risk monitoring sequence are as follows: S401: Based on the ship navigation attitude distortion tracing chain in the narrow inland waterway, the attitude distortion diffusion area is extracted according to the trajectory ranging node. The physical state is divided in the ship's super-high boundary layer, braking momentum layer and bridge pier lateral clearance layer according to the location of the three-dimensional trajectory intrusion, and a three-dimensional intrusion state set of the inland waterway near the bridge is generated. S402: Based on the three-dimensional intrusion state set of the inland waterway near the bridge, extract the stopping stroke distance of the hull at the current inland waterway speed and the extreme value of the restricted waterway turning, combine the dynamic change of the ship's height with the remaining vertical physical space from the bottom of the bridge, and obtain the ship's momentum and three-dimensional spatial constraint response sequence. S403: Call the ship momentum and three-dimensional spatial constraint response sequence, arrange the contact and collision critical states according to the bridge approach time sequence, and perform a combination reconstruction of the risk critical vector by fusing the ship's hull distance measurement height and the narrow aperture limitation of the inland river bridge area, and output the ship navigation area bridge pier collision risk monitoring sequence.

8. The method for real-time monitoring of vessel navigation parameters in inland waterway bridge areas according to claim 1, characterized in that, The method also includes step S5: S5: Based on the collision risk monitoring sequence of the bridge piers in the navigation area, set a safety monitoring index for the trajectory approximation state of the overpass bridge area, extract the limit physical correction boundary of each type of yaw attitude in the narrow water area, and output the navigation attitude and trajectory monitoring output set of the inland bridge area based on the three-dimensional navigation constraint dimension of the inland bridge area. The output set for monitoring the navigation attitude and trajectory of vessels in the inland river bridge area includes attitude limit labels for the inland river bridge crossing stage, spatial distribution of extreme three-dimensional avoidance, and a two-way early warning trigger set for trajectory and altitude.

9. The method for real-time monitoring of vessel navigation parameters in inland waterway bridge areas according to claim 8, characterized in that, The specific steps for generating the vessel navigation attitude and trajectory monitoring output set in the inland river bridge area are as follows: S501: Based on the ship navigation area bridge pier collision risk monitoring sequence, set three-dimensional safety control nodes for the bridge section, including ultra-high anti-collision nodes, limit width navigation margin nodes and hydrological anti-deviation nodes, call the extreme value of the distance between the bridge pier and the bottom of the bridge to the node, and generate the segmented navigation safety feature set of the inland river bridge section. S502: Call the segmented navigation safety feature set of the inland river bridge section, extract the mutual constraints between speed, attitude deviation angle, superelevation and the three-dimensional remaining space of the bridge opening in the inland river navigation stage, and screen high-risk navigation sections according to the residual dissipation rate to construct a three-dimensional dynamic risk evolution map of the inland river bridge. S503: Based on the three-dimensional dynamic risk evolution map of the inland river bridge, embed the three-dimensional trajectory approximation variable into the dynamic risk classification mechanism, set the vertical and horizontal two-way safety preset thresholds for the inland river bridge, and output the inland river bridge area vessel navigation attitude and trajectory monitoring output set.

10. A real-time monitoring system for vessel navigation parameters in inland waterway bridge areas, characterized in that, The system is used to implement the real-time monitoring method for vessel navigation parameters in inland waterway bridge areas as described in any one of claims 1-9, the system comprising: The attitude trajectory extraction module acquires inland waterway navigation signals detected by radar and cameras, extracts the ship's height and planar trajectory, verifies the containment relationship between the ship's scanned volume and the bridge opening clearance, locates the steady-state navigation section by identifying extreme values ​​of lateral deflection and pitch, and generates a multi-dimensional navigation characteristic evolution sequence of ships in inland waterway restricted bridge areas. Based on the evolution sequence of multidimensional navigation characteristics of ships in the restricted bridge area of ​​the inland waterway, the three-dimensional spatial mapping module divides the narrowing transition stage, compares the three-dimensional overlap rate, anchors the real-time ranging node to the physical coordinate system of the bridge, and establishes a three-dimensional spatiotemporal mapping map of ships crossing the narrowed waterway in the bridge area. The attitude distortion tracing module is based on the three-dimensional spatiotemporal mapping of ships traversing the narrow waterway in the bridge area. It compares the abnormal increments of height and heading deviation from the axis, calculates the deflection thrust in combination with inland waterway hydrological effects, determines the weight of variable cross-section flow around and restricted maneuvering, and reverses the three-dimensional attitude evolution starting point along the time axis to obtain the ship navigation attitude distortion tracing chain in the narrow inland waterway. The conflict boundary fusion module is based on the ship navigation attitude distortion tracing chain in the narrow inland waterway. It divides the ship's superelevation, lateral trajectory and underwater draft, extracts stroke inertia, solves the three-dimensional collision intersection points between the ship's three-dimensional envelope and the bridge pier and the bottom of the bridge, and reconstructs the risk envelope in combination with the clearance limit to generate a bridge pier collision risk monitoring sequence for the ship navigation area. Based on the collision risk monitoring sequence of bridge piers in the ship navigation area, the multi-dimensional monitoring output module sets three-dimensional control nodes, extracts the constraints between speed, attitude and three-dimensional residual space, analyzes the risk evolution rate, and outputs a set of ship navigation attitude and trajectory monitoring outputs in the inland river bridge area by comparing the limit three-dimensional maneuvering distance.

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