A scene generation method and system for a ship system

Abstract

The present invention relates to the technical field of scene generation, and specifically discloses a scene generation method and system for a ship system, comprising: obtaining navigation data within a fixed time period; calculating and obtaining the navigation coefficient of the fixed time period; evaluating the risk of the ship in the fixed time period, and generating a risk assessment signal; establishing a ship navigation model based on a high-risk signal; predicting the waves to be encountered, and obtaining predicted waves and prediction data; calculating and obtaining the navigation prediction coefficient of the ship within the fixed time period; evaluating the subsequent navigation environment of the ship, and generating a risk prediction signal; based on the still high-risk signal, sending the wave height, wave direction and wave period of the predicted waves to the front end; the present invention provides timely and comprehensive risk assessment for ship navigation, helps to improve navigation safety and reduce potential risks; provides a more comprehensive and forward-looking risk assessment and early warning system for ship navigation, and effectively improves the scientificity and safety of navigation decision-making.

Description

Technical Field

[0001] The present invention relates to the technical field of scene generation, and in particular to a scene generation method and system for a ship system. Background Art

[0002] Ship system is an important concept in the field of maritime science and technology. It covers various systems on the ship except the power system. These systems provide support for the ship's life, loading and unloading, safety and other aspects.

[0003] However, in the prior art, in the scenario generation of the ship system, the assessment of navigation risk is not comprehensively assessed from the two dimensions of risk degree coefficient and risk uniformity coefficient, which leads to inaccurate risk assessment. It is also not possible to predict subsequent waves when high risks are identified. When it is predicted that the risk is still high, the prediction result is sent to the manager, so that the manager can prepare for the subsequent waves in advance. Summary of the invention

[0004] The object of the present invention is to provide a scene generation method and system for a ship system to solve the technical problems in the above background.

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] In a first aspect, the present invention provides a method for generating a scene of a ship system, comprising the following steps:

[0007] Step 1: When the ship is sailing, the environment of the ship is detected to obtain the navigation data within a fixed period of time;

[0008] Among them, the navigation data includes: the wave height, wave direction and wave period of each wave of the ship in a fixed period of time;

[0009] Step 2: Based on the navigation data of the ship in a fixed period, the navigation coefficient of the fixed period is calculated;

[0010] Step 3: Based on the navigation coefficient of a fixed period, assess the risk of the ship in the fixed period, determine whether the ship is currently in a high-risk state, and generate a risk assessment signal;

[0011] Among them, the risk assessment signals include: high risk signals and low risk signals;

[0012] Step 4: Based on the high-risk signals, use the ship’s past navigation data to establish a ship navigation model;

[0013] Step 5: Based on the ship navigation model, the wave height, wave direction and wave period of the waves that the ship will encounter during the navigation process are predicted to obtain the predicted waves, thereby obtaining the predicted data;

[0014] Step 6: Based on the forecast data, calculate the navigation forecast coefficient of the ship within a fixed period of time;

[0015] Step 7: Based on the navigation prediction coefficient, evaluate the subsequent navigation environment of the ship, determine whether the subsequent navigation environment of the ship is still in a high-risk state, and generate a risk prediction signal;

[0016] Among them, risk prediction signals include: still high risk signal and high risk relief signal;

[0017] Step 8: Based on the still high risk signal, the predicted wave height, wave direction and wave period are sent to the front end.

[0018] As a further solution of the present invention: based on the navigation data of a ship in a fixed period of time, the process of calculating and obtaining the navigation coefficient of the fixed period of time is:

[0019] Based on the navigation data of the ship at a fixed time period, the risk factor of each wave is obtained;

[0020] Based on the risk coefficient of each wave, the risk degree coefficient and the risk uniformity coefficient are calculated respectively;

[0021] The navigation coefficient is obtained by multiplying the risk degree coefficient and the risk uniformity coefficient.

[0022] As a further solution of the present invention: the process of obtaining the risk coefficient is:

[0023] Based on the wave height, wave direction and wave period of a single wave, the risk coefficient FX is calculated by the formula: FX=f(H, X, T), where H is the wave height, X is the wave direction, T is the wave period, and f is the function.

[0024] As a further solution of the present invention: the process of obtaining the risk degree coefficient is:

[0025] Extract the risk deviation values ​​of all large deviation waves within a fixed period, and sum up the risk deviation values ​​of all large deviation waves to obtain the risk offset value;

[0026] The risk coefficient mean and the risk offset value are summed to obtain the risk degree value, and the risk degree value is ratioed with the risk degree threshold to obtain the risk degree coefficient.

[0027] As a further solution of the present invention: the process of obtaining the large deviation wave is:

[0028] Obtain the risk coefficients of all waves in a fixed period, calculate the average of all risk coefficients, and obtain the average risk coefficient;

[0029] Then, the difference between the risk coefficient of each wave and the mean risk coefficient is calculated to obtain the risk deviation value of each wave;

[0030] Compare and analyze the absolute value of the risk deviation value with the risk deviation threshold;

[0031] If the absolute value of the risk deviation value is less than the risk deviation threshold, a small deviation signal is generated and the wave is marked as a small deviation wave;

[0032] If the absolute value of the risk deviation value ≥ the risk deviation threshold, a large deviation signal is generated and the wave is marked as a large deviation wave.

[0033] As a further solution of the present invention: the process of obtaining the risk uniformity coefficient is:

[0034] Extract the wave periods of all waves with large deviations within a fixed period, and sum up the wave periods of all waves with large deviations to obtain the total period with large deviations, and calculate the ratio of the total period with large deviations to the duration of the fixed period to obtain the duration ratio with large deviations;

[0035] At the same time, the risk coefficients of all waves in a fixed period are extracted, the risk coefficients of adjacent waves are calculated for difference, and the absolute values ​​are taken to obtain adjacent deviation values, and then all adjacent deviation values ​​are summed to obtain adjacent average values;

[0036] The risk average value is obtained by multiplying the adjacent average values ​​with the ratio of the large deviation duration, and the risk average value is calculated by ratioing the risk average value with the risk average threshold to obtain the risk average coefficient.

[0037] As a further solution of the present invention: the process of generating the risk assessment signal is:

[0038] Preset the navigation coefficient threshold, and compare and analyze the navigation coefficient with the navigation coefficient threshold;

[0039] If the navigation coefficient is less than the navigation coefficient threshold, a low risk signal is generated;

[0040] If the navigation coefficient ≥ the navigation coefficient threshold, a high-risk signal is generated.

[0041] As a further solution of the present invention: based on the ship navigation model, the wave height, wave direction and wave period of the waves that the ship will encounter during the navigation process are predicted to obtain the predicted waves, and the process of obtaining the predicted data is as follows:

[0042] Based on the current navigation data obtained, the first several waves among the fixed number of waves are eliminated, and the remaining waves are marked as wave groups to be analyzed;

[0043] Based on the wave group to be analyzed and the ship navigation model, the wave height, wave direction and wave period of multiple waves to be encountered are predicted to obtain multiple predicted waves;

[0044] In terms of time, multiple predicted waves are added to the back of the wave group to be analyzed, that is, a fixed number of waves are used to obtain the predicted data, thereby obtaining the predicted data.

[0045] As a further solution of the present invention: the process of generating the risk prediction signal is:

[0046] Compare and analyze the navigation prediction coefficient with the navigation coefficient threshold;

[0047] If the navigation prediction coefficient is less than the navigation coefficient threshold, a high-risk release signal is generated;

[0048] If the navigation prediction coefficient ≥ the navigation coefficient threshold, a high risk signal is generated.

[0049] In a second aspect, the present invention provides a scene generation system for a ship system, the system comprising:

[0050] Data acquisition module: When the ship is sailing, the environment of the ship is detected and the navigation data within a fixed period of time is obtained;

[0051] Among them, the navigation data includes: the wave height, wave direction and wave period of each wave of the ship in a fixed period of time;

[0052] Data processing module: based on the navigation data of the ship in a fixed period, calculate the navigation coefficient of the fixed period;

[0053] Risk assessment module: Based on the navigation coefficient of a fixed period, it assesses the risk of the ship in the fixed period, determines whether the ship is currently in a high-risk state, and generates a risk assessment signal;

[0054] Among them, the risk assessment signals include: high risk signals and low risk signals;

[0055] Model building module: Based on high-risk signals, the ship navigation model is established using the ship's past navigation data;

[0056] Data prediction module: Based on the ship navigation model, the wave height, wave direction and wave period of the waves that the ship will encounter during the navigation process are predicted to obtain the predicted waves and thus obtain the predicted data;

[0057] Prediction data processing module: based on the prediction data, calculate the navigation prediction coefficient of the ship in a fixed period of time;

[0058] Risk prediction module: Based on the navigation prediction coefficient, the subsequent navigation environment of the ship is evaluated to determine whether the subsequent navigation environment of the ship is still in a high-risk state, and generate a risk prediction signal;

[0059] Among them, risk prediction signals include: still high risk signal and high risk relief signal;

[0060] Display module: Based on the still high risk signal, the predicted wave height, wave direction and wave period are sent to the front end.

[0061] Beneficial effects of the present invention:

[0062] (1) The present invention firstly continuously monitors the environment of the ship during navigation and collects navigation data within a fixed period of time, including wave height, wave direction and wave period; then, the navigation data is used to calculate the risk coefficient of each wave, and further statistical analysis is performed to obtain the risk degree coefficient and the risk uniformity coefficient; the risk degree coefficient reflects the overall risk level, especially the contribution of those waves that significantly deviate from the average level (large deviation waves); while the risk uniformity coefficient takes into account the distribution of wave periods and the changes in the risk coefficients of adjacent waves, and evaluates the uniformity of the risk; the two are multiplied to obtain the navigation coefficient, which combines the overall risk level and risk of the navigation environment. distribution; finally, by comparing with the preset navigation coefficient threshold, the navigation risk of the ship is evaluated in real time, and a corresponding risk assessment signal is generated; the embodiment of the present invention can instantly evaluate the navigation risk of the ship by detecting the navigation data in real time; and comprehensively considers multiple factors such as wave height, wave direction, and wave period, and comprehensively evaluates the navigation risk through the two dimensions of risk degree coefficient and risk uniformity coefficient; by distinguishing between large deviation waves and small deviation waves, more accurately identify waves that have a significant impact on the overall risk, thereby improving the accuracy of risk assessment; provides timely and comprehensive risk assessment for ship navigation, helps to improve navigation safety and reduce potential risks;

[0063] (2) After identifying the high-risk state, the present invention uses the historical navigation data of the ship to construct a navigation model, which captures the intrinsic relationship between wave characteristics (wave height, wave direction, wave period); then, based on the current navigation data, some old data are eliminated, and the remaining wave information is retained as the group to be analyzed, and the navigation model is used to predict the wave characteristics to be encountered to form prediction data; then, the prediction data is processed to calculate the navigation prediction coefficient to quantify the risk level of the future navigation period; by comparing the coefficient with the preset threshold, it can be quickly determined whether the subsequent navigation environment is still in a high-risk state; if it is not in a high-risk state, a high-risk release signal is generated, indicating that the navigation environment will tend to be stable; if it is still in a high-risk state, a high-risk signal is issued, and the predicted wave characteristic information is immediately pushed to the front end so that the management personnel can take countermeasures in advance to ensure navigation safety; the embodiment of the present invention combines historical data with real-time prediction, providing a more comprehensive and forward-looking risk assessment and early warning system for ship navigation, effectively improving the scientificity and safety of navigation decision-making. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] The present invention will be further described below in conjunction with the accompanying drawings.

[0065] Figure 1 It is a flowchart of the present invention;

[0066] Figure 2 It is a system block diagram of the present invention. DETAILED DESCRIPTION

[0067] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0068] Example 1: Please refer to Figure 1 As shown, a scene generation method for a ship system according to an embodiment of the present invention comprises the following steps:

[0069] Step 1: When the ship is sailing, the environment of the ship is detected, and the navigation data within a fixed time period (the fixed time period is divided according to a fixed number of waves, and the fixed number of waves can be 10 or 20) is obtained;

[0070] The navigation data includes: the wave height, wave direction (wave direction is the angle between the wave propagation direction and the ship's navigation direction) and wave period (wave period is the time from the crest of the previous wave to the crest of this wave) of each wave of the ship in a fixed period of time;

[0071] It should be explained that during the ship's voyage, the navigation data is constantly changing. Since the selected fixed time period is divided according to the number of waves, the navigation data will be updated every time the ship passes a wave.

[0072] For example, when a ship is sailing, the environment of the ship is detected to obtain the navigation data of 10 waves, specifically:

[0073] Wave 1: wave height 2.8 meters, wave direction 30°, wave period 7.0 seconds;

[0074] Wave 2: wave height 3.0 meters, wave direction 35°, wave period 7.2 seconds;

[0075] Wave 3: wave height 2.9 meters, wave direction 30°, wave period 7.1 seconds;

[0076] Wave 4: wave height 2.6 meters, wave direction 25°, wave period 6.9 seconds;

[0077] Wave 5: wave height 2.4 meters, wave direction 20°, wave period 6.8 seconds;

[0078] Wave 6: wave height 2.5 meters, wave direction 20°, wave period 6.8 seconds;

[0079] Wave 7: wave height 2.7 meters, wave direction 25°, wave period 7.0 seconds;

[0080] Wave 8: wave height 3.2 meters, wave direction 30°, wave period 7.5 seconds;

[0081] Wave 9: wave height 3.0 meters, wave direction 35 degrees, wave period 7.3 seconds;

[0082] Wave 10: wave height 2.8 meters, wave direction 30°, wave period 7.1 seconds;

[0083] Step 2: Based on the navigation data of the ship in a fixed period, the navigation coefficient of the fixed period is calculated;

[0084] In some embodiments, the risk factor of each wave is obtained based on the navigation data of the ship at a fixed time period;

[0085] Based on the risk coefficient of each wave, the risk degree coefficient and the risk uniformity coefficient are calculated respectively;

[0086] The risk degree coefficient is multiplied by the risk uniformity coefficient to obtain the navigation coefficient;

[0087] For example, the navigation coefficient HX = risk degree coefficient CD × risk uniformity coefficient JY = 3.33 × 1.34 = 4.46;

[0088] In a first exemplary embodiment, the process of obtaining the risk coefficient is as follows:

[0089] Based on the wave height, wave direction and wave period of a single wave, the risk factor FX is calculated by the formula: FX = f(H, X, T), where H is the wave height, X is the wave direction, T is the wave period, and f is the function;

[0090] It should be explained that the function f represents the relationship between the wave height, wave direction and wave period and the risk factor. The function f is obtained by technicians in this field based on actual application scenarios. That is, if factors such as ship type and navigation area change, the function f will change accordingly.

[0091] For example, by the formula: FX = a × H b ×cos 2 (X-θ)×T c , calculate the risk factor FX of each wave, specifically:

[0092] Among them, H is the wave height, X is the wave direction, T is the wave period, and θ is the best navigation direction for the ship (such as true north, i.e. 0° or 360°);

[0093] a, b, c are coefficients determined according to ship characteristics and navigation experience, and a, b, c are all greater than 0. These coefficients need to be adjusted according to actual conditions, for example, a = 0.5, b = 1.5, c = 0.3;

[0094] It needs to be explained that higher waves mean greater navigation risks, that is, the greater the wave height, the higher the risk;

[0095] cos 2 (X-θ) represents the impact of wave direction on navigation risk. The smaller the difference between X and θ, the higher the risk. When the wave direction is consistent with the best navigation direction of the ship (X=θ), the wave direction is parallel to the best navigation direction of the ship, cos 2 The value of (X-θ) reaches the maximum, which is 1;

[0096] The larger the wave cycle value, the longer the wave cycle. Longer waves mean greater energy and longer recovery time, and higher risks.

[0097] Wave 1: FX1 = 0.5 × 2.8 1.5 ×cos 2 (30°-0°)×7.0 0.3 =3.15;

[0098] Wave 2: FX2 = 0.5 × 3 1.5 ×cos 2 (35°-0°)×7.2 0.3 =3.15;

[0099] Wave 3: FX3 = 0.5 × 2.9 1.5 ×cos 2 (30°-0°)×7.1 0.3 =3.33;

[0100] Wave 4: FX4 = 0.5 × 2.6 1.5 ×cos 2 (25°-0°)×6.9 0.3 =3.07;

[0101] Wave 5: FX5 = 0.5 × 2.4 1.5 ×cos 2 (20°-0°)×6.8 0.3 =2.92;

[0102] Wave 6: FX6 = 0.5 × 2.5 1.5 ×cos 2 (20°-0°)×6.8 0.3 =3.10;

[0103] Wave 7: FX7 = 0.5 × 2.7 1.5 ×cos 2 (25°-0°)×7.0 0.3 =3.27;

[0104] Wave 8: FX8 = 0.5 × 3.2 1.5 ×cos 2 (30°-0°)×7.5 0.3 =3.93;

[0105] Wave 9: FX9 = 0.5 × 3.0 1.5 ×cos 2 (35°-0°)×7.3 0.3 =3.17;

[0106] Wave 10: FX10 = 0.5 × 2.8 1.5 ×cos 2 (30°-0°)×7.1 0.3 =3.16;

[0107] In a second exemplary embodiment, the process of obtaining the risk degree coefficient is as follows:

[0108] Obtain the risk coefficients of all waves in a fixed period, calculate the average of all risk coefficients, and obtain the average risk coefficient;

[0109] Then, the difference between the risk coefficient of each wave and the mean risk coefficient is calculated to obtain the risk deviation value of each wave;

[0110] Compare and analyze the absolute value of the risk deviation value with the risk deviation threshold;

[0111] If the absolute value of the risk deviation value is less than the risk deviation threshold, it means that the risk coefficient of the wave is slightly different from the mean risk coefficient, that is, the risk coefficient of the wave has little influence on the calculation of the mean risk coefficient, that is, a small deviation signal is generated, and the wave is marked as a small deviation wave;

[0112] If the absolute value of the risk deviation value is ≥ the risk deviation threshold, it means that the risk coefficient of the wave is significantly different from the mean risk coefficient, that is, the risk coefficient of the wave has a greater impact on the calculation of the mean risk coefficient, that is, a large deviation signal is generated, and the wave is marked as a large deviation wave;

[0113] Extract the risk deviation values ​​of all large deviation waves within a fixed period, and sum up the risk deviation values ​​of all large deviation waves to obtain the risk offset value;

[0114] The mean value of the risk coefficient and the risk offset value are summed to obtain the risk degree value, and the risk degree value is ratioed to the risk degree threshold to obtain the risk degree coefficient;

[0115] It should be explained that the risk deviation value is obtained by summing up the risk deviation values ​​of all large deviation waves. The risk deviation value reflects the degree of deviation between the risk coefficient of a single wave and the overall average level. Therefore, the risk deviation value is a quantitative indicator to measure the additional risk deviation or contribution generated by waves that have a significant impact on the overall risk level (i.e. large deviation waves); the risk deviation value reflects the total difference between the risk coefficient of large deviation waves and the average value of the overall risk coefficient, thereby providing a measure of the amount of unstable or extreme parts in the overall risk; the risk degree value is calculated by adding the risk coefficient mean value to the risk deviation value. The risk degree value comprehensively considers the average level of the overall risk coefficient and the contribution of extreme risk events, thereby providing a more comprehensive risk level assessment;

[0116] Exemplarily, the risk coefficients of all waves in a fixed period are obtained, which are: FX1=3.15, FX2=3.15, FX3=3.33, FX4=3.07, FX5=2.29, FX6=3.10, FX7=3.27, FX8=3.93, FX9=3.17, FX10=3.16;

[0117] Calculate the mean of all risk factors to obtain the mean risk factor

[0118] Then, the difference between the risk coefficient of each wave and the mean risk coefficient is calculated to obtain the risk deviation value of each wave, which is:

[0119] The risk deviation value of the first wave is FP1 = 3.15-3.162 = -0.012;

[0120] The risk deviation value of the second wave FP2 = 3.15-3.162 = -0.012;

[0121] The risk deviation value of the third wave FP3 = 3.33-3.162 = 0.168;

[0122] The risk deviation value of the 4th wave FP4 = 3.07-3.162 = -0.092;

[0123] The risk deviation value of the 5th wave FP5 = 2.29-3.162 = -0.872;

[0124] The risk deviation value of the 6th wave is FP6 = 3.10-3.162 = -0.062;

[0125] The risk deviation value of the 7th wave FP7 = 3.27-3.162 = 0.108;

[0126] The risk deviation value of the 8th wave is FP8 = 3.93-3.162 = 0.768;

[0127] The risk deviation value of the 9th wave FP9 = 3.17-3.162 = 0.008;

[0128] The risk deviation value of the 10th wave FP10 = 3.16-3.162 = -0.002;

[0129] The absolute value of the risk deviation value is compared and analyzed with the risk deviation threshold FPY=0.1;

[0130] The absolute value of the risk deviation of the first wave is less than the risk deviation threshold, a small deviation signal is generated, and the wave is marked as a small deviation wave;

[0131] The absolute value of the risk deviation of the second wave is less than the risk deviation threshold, a small deviation signal is generated, and the wave is marked as a small deviation wave;

[0132] The absolute value of the risk deviation value of the third wave is ≥ the risk deviation threshold, a large deviation signal is generated, and the wave is marked as a large deviation wave;

[0133] The absolute value of the risk deviation of the fourth wave is less than the risk deviation threshold, a small deviation signal is generated, and the wave is marked as a small deviation wave;

[0134] The absolute value of the risk deviation value of the fifth wave is ≥ the risk deviation threshold, a large deviation signal is generated, and the wave is marked as a large deviation wave;

[0135] The absolute value of the risk deviation of the sixth wave is less than the risk deviation threshold, a small deviation signal is generated, and the wave is marked as a small deviation wave;

[0136] The absolute value of the risk deviation value of the 7th wave is ≥ the risk deviation threshold, a large deviation signal is generated, and the wave is marked as a large deviation wave;

[0137] The absolute value of the risk deviation value of the 8th wave is ≥ the risk deviation threshold, a large deviation signal is generated, and the wave is marked as a large deviation wave;

[0138] The absolute value of the risk deviation value of the 9th wave is less than the risk deviation threshold, a small deviation signal is generated, and the wave is marked as a small deviation wave;

[0139] The absolute value of the risk deviation value of the 10th wave is less than the risk deviation threshold, a small deviation signal is generated, and the wave is marked as a small deviation wave;

[0140] Extract the risk deviation values ​​of all large deviation waves in a fixed period, i.e., FP3=0.168, FP5=-0.872, FP7=0.108, FP8=0.768; and sum up the risk deviation values ​​of all large deviation waves to obtain the risk deviation value PY=FP3+FP5+FP7+FP8=0.172;

[0141] The risk coefficient mean and the risk offset value are summed to obtain the risk degree value FC, that is,

[0142] The risk level value FC is calculated by ratio with the risk level threshold FCY=1, and the risk level coefficient CD=3.33 is obtained;

[0143] In a third exemplary embodiment, the process of obtaining the risk uniformity coefficient is as follows:

[0144] Extract the wave periods of all waves with large deviations within a fixed period, and sum up the wave periods of all waves with large deviations to obtain the total period with large deviations, and calculate the ratio of the total period with large deviations to the duration of the fixed period to obtain the duration ratio with large deviations;

[0145] At the same time, the risk coefficients of all waves in a fixed period are extracted, the risk coefficients of adjacent waves are calculated for difference, and the absolute values ​​are taken to obtain adjacent deviation values, and then all adjacent deviation values ​​are summed to obtain adjacent average values;

[0146] The product of adjacent average values ​​and the ratio of large deviation duration is calculated to obtain the risk average value, and the ratio of the risk average value to the risk average threshold is calculated to obtain the risk average coefficient;

[0147] Exemplarily, the wave periods LZ of all waves with large deviations within a fixed time period are extracted, specifically: the wave period LZ3 of the third wave = 7.1s, the wave period LZ5 of the fifth wave = 6.8s, the wave period LZ7 of the seventh wave = 7.0s, and the wave period LZ8 of the eighth wave = 7.5s; and the wave periods of all waves with large deviations are summed up to obtain the total period LZZ with large deviations, that is, LZZ = LZ3 + LZ5 + LZ7 + LZ8 = 28.4s, and the ratio of the total period with large deviations to the duration of the fixed time period is calculated to obtain the large deviation duration ratio LZB, that is,

[0148] At the same time, the risk coefficients of all waves in a fixed period are extracted, the risk coefficients of adjacent waves are calculated by difference, and the absolute values ​​are taken to obtain adjacent deviation values, and then all adjacent deviation values ​​are summed to obtain the adjacent average value LJ, that is,

[0149] The adjacent average value and the large deviation duration ratio are multiplied to obtain the risk average value FJ, FJ = LZB × LJ = 1.344;

[0150] The risk average value is calculated by ratio with the risk average threshold FJY=1, and the risk average coefficient JY=1.34 is obtained;

[0151] Step 3: Based on the navigation coefficient of a fixed period, assess the risk of the ship in the fixed period, determine whether the ship is currently in a high-risk state, and generate a risk assessment signal;

[0152] Among them, the risk assessment signals include: high risk signals and low risk signals;

[0153] In some implementation schemes, a navigation coefficient threshold is preset, and the navigation coefficient is compared and analyzed with the navigation coefficient threshold;

[0154] If the navigation coefficient is less than the navigation coefficient threshold, it means that the navigation environment of the ship is good during the fixed period, and the waves are small and uniform, that is, the ship is not currently in a high-risk state, and a low-risk signal is generated;

[0155] If the navigation coefficient is ≥ the navigation coefficient threshold, it means that the navigation environment of the ship is poor during the fixed period, and the waves are large or uneven, that is, the ship is judged to be in a high-risk state and a high-risk signal is generated;

[0156] Exemplarily, the navigation coefficient threshold HXY=4 is preset, and the navigation coefficient HX is compared and analyzed with the navigation coefficient threshold HXY;

[0157] If HX≥HXY, it means that the navigation environment of the ship is poor during the fixed period, and the waves are large or uneven, which means that the ship is currently in a high-risk state and a high-risk signal is generated;

[0158] The technical solution of the embodiment of the present invention is mainly as follows: first, by continuously monitoring the environment of the ship during navigation, the navigation data within a fixed period of time, including wave height, wave direction and wave period, is collected; then, the risk coefficient of each wave is calculated using the navigation data, and further statistical analysis is performed to obtain the risk degree coefficient and the risk uniformity coefficient; the risk degree coefficient reflects the overall risk level, especially the contribution of those waves that significantly deviate from the average level (large deviation waves); and the risk uniformity coefficient takes into account the distribution of wave periods and the changes in the risk coefficients of adjacent waves, and evaluates the uniformity of the risk; the two are multiplied to obtain the navigation coefficient, which combines the overall risk of the navigation environment. The distribution of wave levels and risks; finally, by comparing with the preset navigation coefficient threshold, the navigation risk of the ship is evaluated in real time, and a corresponding risk assessment signal is generated; the embodiment of the present invention can instantly evaluate the navigation risk of the ship by detecting navigation data in real time; and comprehensively considers multiple factors such as wave height, wave direction, and wave period, and comprehensively evaluates the navigation risk through the two dimensions of risk degree coefficient and risk uniformity coefficient; by distinguishing between waves with large deviations and waves with small deviations, waves that have a significant impact on the overall risk are more accurately identified, thereby improving the accuracy of risk assessment; it provides timely and comprehensive risk assessment for ship navigation, helps to improve navigation safety and reduce potential risks.

[0159] Example 2: Based on Example 1, please refer to Figure 1 As shown, the scene generation method of a ship system according to an embodiment of the present invention further includes the following steps:

[0160] Step 4: Based on the high-risk signals, use the ship’s past navigation data to establish a ship navigation model;

[0161] It should be explained that the ship navigation model is established based on the ship's past navigation data. The ship navigation model reflects the relationship between the wave height, wave direction and wave period of a fixed number of waves, so as to facilitate the prediction of waves based on the model in the later stage;

[0162] In some embodiments, when a high-risk signal is received, a ship navigation model is established using a model building method of a deep learning model based on the ship's past navigation data;

[0163] Step 5: Based on the ship navigation model, the wave height, wave direction and wave period of the waves that the ship will encounter during the navigation process are predicted to obtain the predicted waves, thereby obtaining the predicted data;

[0164] In some embodiments, based on the current navigation data that has been obtained, the first multiple waves among the fixed number of waves (the first multiple waves are waves that are earlier in time within a fixed period, and the multiple number may be 1 or 2; the number of the first multiple waves should not be too large, and the larger the number, the less accurate the subsequent prediction) are eliminated, and the remaining waves are marked as a wave group to be analyzed;

[0165] Based on the wave group to be analyzed and the ship navigation model, the wave height, wave direction and wave period of multiple waves to be encountered (the number of waves of the multiple waves to be encountered is the same as the number of waves of the previous multiple waves) are predicted to obtain multiple predicted waves;

[0166] In terms of time, multiple forecast waves are added to the back of the wave group to be analyzed, that is, a fixed number of waves for obtaining forecast data, thereby obtaining forecast data;

[0167] It should be explained that the predicted data is the navigation data corresponding to the multiple predicted waves and the wave group to be analyzed. The difference between the predicted data and the navigation data in step 1 is that the objects of analysis are different.

[0168] Exemplarily, the prediction data is specifically:

[0169] Wave 1 (formerly Wave 2): wave height 3.0 meters, wave direction 35°, wave period 7.2 seconds;

[0170] Wave 2 (formerly Wave 3): wave height 2.9 meters, wave direction 30°, wave period 7.1 seconds;

[0171] Wave 3 (formerly Wave 4): wave height 2.6 meters, wave direction 25°, wave period 6.9 seconds;

[0172] Wave 4 (formerly Wave 5): wave height 2.4 meters, wave direction 20°, wave period 6.8 seconds;

[0173] Wave 5 (formerly Wave 6): wave height 2.5 meters, wave direction 20°, wave period 6.8 seconds;

[0174] Wave 6 (formerly Wave 7): Wave height 2.7 meters, wave direction 25°, wave period 7.0 seconds;

[0175] Wave 7 (formerly Wave 8): Wave height 3.2 meters, wave direction 30°, wave period 7.5 seconds;

[0176] Wave 8 (formerly Wave 9): wave height 3.0 meters, wave direction 35°, wave period 7.3 seconds;

[0177] Wave 9 (formerly Wave 10): Wave height 2.8 meters, wave direction 30°, wave period 7.1 seconds;

[0178] Wave 10 (predicted wave): wave height 2.5 meters, wave direction 23°, wave period 6.9 seconds;

[0179] Step 6: Based on the predicted data, the navigation prediction coefficient of the ship in a fixed period is calculated (the method of calculating the navigation prediction coefficient based on the predicted data is the same as the method of calculating the navigation coefficient based on the navigation data, which will not be repeated here);

[0180] Exemplarily, based on the prediction data, the navigation prediction coefficient HYC=5.14 is calculated;

[0181] Step 7: Based on the navigation prediction coefficient, evaluate the subsequent navigation environment of the ship, determine whether the subsequent navigation environment of the ship is still in a high-risk state, and generate a risk prediction signal;

[0182] Among them, risk prediction signals include: still high risk signal and high risk relief signal;

[0183] In some real-time schemes, the navigation prediction coefficient is compared and analyzed with the navigation coefficient threshold;

[0184] If the navigation prediction coefficient is less than the navigation coefficient threshold, it means that the navigation environment of the ship in the subsequent period is good, the waves are small and more uniform, that is, it is predicted that the ship will leave the high-risk state in the future, and a high-risk release signal will be generated;

[0185] If the navigation prediction coefficient is ≥ the navigation coefficient threshold, it means that the navigation environment of the ship in the subsequent period is poor, the waves are large or uneven, that is, it is predicted that the ship will still be in a high-risk state in the future, and a high-risk signal is generated;

[0186] Exemplarily, the navigation prediction coefficient HYC is compared and analyzed with the navigation coefficient threshold HXY;

[0187] If HYC≥HXY, it means that the navigation environment of the ship in the subsequent period is poor, the waves are large or uneven, that is, it is predicted that the ship will still be in a high-risk state in the future, and a high-risk signal will be generated;

[0188] Step 8: Based on the high risk signal, the predicted wave height, wave direction and wave period are sent to the front end, so that managers can respond to subsequent waves in advance;

[0189] For example, the predicted waves: wave height 2.5 meters, wave direction 23°, wave period 6.9 seconds, are sent to the front end;

[0190] The technical solution of the embodiment of the present invention is mainly as follows: after identifying the high-risk state, a navigation model is constructed using the historical navigation data of the ship, and the model captures the intrinsic connection between wave characteristics (wave height, wave direction, wave period); then, based on the current navigation data, some old data are eliminated, and the remaining wave information is retained as a group to be analyzed, and the navigation model is used to predict the wave characteristics to be encountered to form prediction data; then, the prediction data is processed to calculate the navigation prediction coefficient to quantify the risk level of the future navigation period; by comparing the coefficient with the preset threshold, it can be quickly determined whether the subsequent navigation environment is still in a high-risk state; if it is not in a high-risk state, a high-risk release signal is generated, indicating that the navigation environment will tend to be stable; if it is still in a high-risk state, a high-risk signal is issued, and the predicted wave characteristic information is immediately pushed to the front end so that the management personnel can take countermeasures in advance to ensure navigation safety; the embodiment of the present invention combines historical data with real-time predictions to provide a more comprehensive and forward-looking risk assessment and early warning system for ship navigation, effectively improving the scientificity and safety of navigation decisions.

[0191] Example 3: Based on Example 1 and Example 2, please refer to Figure 2 As shown, a scene generation system for a ship system according to an embodiment of the present invention includes:

[0192] Data acquisition module: When the ship is sailing, the environment of the ship is detected and the navigation data within a fixed period of time is obtained;

[0193] Among them, the navigation data includes: the wave height, wave direction and wave period of each wave of the ship in a fixed period of time;

[0194] Data processing module: based on the navigation data of the ship in a fixed period, calculate the navigation coefficient of the fixed period;

[0195] Risk assessment module: Based on the navigation coefficient of a fixed period, it assesses the risk of the ship in the fixed period, determines whether the ship is currently in a high-risk state, and generates a risk assessment signal;

[0196] Among them, the risk assessment signals include: high risk signals and low risk signals;

[0197] Model building module: Based on high-risk signals, the ship navigation model is established using the ship's past navigation data;

[0198] Data prediction module: Based on the ship navigation model, the wave height, wave direction and wave period of the waves that the ship will encounter during the navigation process are predicted to obtain the predicted waves and thus obtain the predicted data;

[0199] Prediction data processing module: based on the prediction data, calculate the navigation prediction coefficient of the ship in a fixed period of time;

[0200] Risk prediction module: Based on the navigation prediction coefficient, the subsequent navigation environment of the ship is evaluated to determine whether the subsequent navigation environment of the ship is still in a high-risk state, and generate a risk prediction signal;

[0201] Among them, risk prediction signals include: still high risk signal and high risk relief signal;

[0202] Display module: Based on the still high risk signal, the predicted wave height, wave direction and wave period are sent to the front end.

[0203] The above thresholds are set for the convenience of comparison. The thresholds depend on the amount of sample data and the number of bases set by technicians in this field for each set of sample data.

[0204] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A method for generating a scene of a ship system, characterized in that: The following steps are involved: Step 1: When the ship is sailing, the environment of the ship is detected to obtain the navigation data within a fixed period of time; Among them, the navigation data includes: the wave height, wave direction and wave period of each wave of the ship in a fixed period of time; Step 2: Based on the navigation data of the ship in a fixed period, the navigation coefficient of the fixed period is calculated. The process is as follows: Based on the navigation data of the ship at a fixed time period, the risk factor of each wave is obtained; Based on the risk coefficient of each wave, the risk degree coefficient and the risk uniformity coefficient are calculated respectively; The process of obtaining the risk uniformity coefficient is as follows: Extract the wave periods of all waves with large deviations within a fixed period, and sum up the wave periods of all waves with large deviations to obtain the total period with large deviations, and calculate the ratio of the total period with large deviations to the duration of the fixed period to obtain the duration ratio with large deviations; At the same time, the risk coefficients of all waves in a fixed period are extracted, the risk coefficients of adjacent waves are calculated for difference, and the absolute values ​​are taken to obtain adjacent deviation values, and then all adjacent deviation values ​​are summed to obtain adjacent average values; The product of adjacent average values ​​and the ratio of large deviation duration is calculated to obtain the risk average value, and the ratio of the risk average value to the risk average threshold is calculated to obtain the risk average coefficient; The risk degree coefficient is multiplied by the risk uniformity coefficient to obtain the navigation coefficient; Step 3: Based on the navigation coefficient of a fixed period, assess the risk of the ship in the fixed period, determine whether the ship is currently in a high-risk state, and generate a risk assessment signal; Among them, the risk assessment signals include: high risk signals and low risk signals; Step 4: Based on the high-risk signals, use the ship’s past navigation data to establish a ship navigation model; Step 5: Based on the ship navigation model, the wave height, wave direction and wave period of the waves that the ship will encounter during the navigation process are predicted to obtain the predicted waves, thereby obtaining the predicted data; Step 6: Based on the forecast data, calculate the navigation forecast coefficient of the ship within a fixed period of time; Step 7: Based on the navigation prediction coefficient, evaluate the subsequent navigation environment of the ship, determine whether the subsequent navigation environment of the ship is still in a high-risk state, and generate a risk prediction signal; Among them, risk prediction signals include: still high risk signal and high risk relief signal; Step 8: Based on the still high risk signal, the predicted wave height, wave direction and wave period are sent to the front end.

2. A method for generating a scene of a ship system according to claim 1, characterized in that: The process of obtaining the risk factor is: Based on the wave height, wave direction and wave period of a single wave, the risk coefficient FX is calculated by the formula: FX=f(H, X, T), where H is the wave height, X is the wave direction, T is the wave period, and f is the function.

3. A method for generating a scene of a ship system according to claim 2, characterized in that: The process of obtaining the risk degree coefficient is as follows: Extract the risk deviation values ​​of all large deviation waves within a fixed period, and sum up the risk deviation values ​​of all large deviation waves to obtain the risk offset value; The risk coefficient mean and the risk offset value are summed to obtain the risk degree value, and the risk degree value is ratioed with the risk degree threshold to obtain the risk degree coefficient.

4. A method for generating a scene of a ship system according to claim 3, characterized in that: The process of obtaining large deviation waves is: Obtain the risk coefficients of all waves in a fixed period, calculate the average of all risk coefficients, and obtain the average risk coefficient; Then, the difference between the risk coefficient of each wave and the mean risk coefficient is calculated to obtain the risk deviation value of each wave; Compare and analyze the absolute value of the risk deviation value with the risk deviation threshold; If the absolute value of the risk deviation value is less than the risk deviation threshold, a small deviation signal is generated and the wave is marked as a small deviation wave; If the absolute value of the risk deviation value ≥ the risk deviation threshold, a large deviation signal is generated and the wave is marked as a large deviation wave.

5. The scene generation method of a ship system according to claim 1, characterized in that: The process of generating a risk assessment signal is: Preset the navigation coefficient threshold, and compare and analyze the navigation coefficient with the navigation coefficient threshold; If the navigation coefficient is less than the navigation coefficient threshold, a low risk signal is generated; If the navigation coefficient ≥ the navigation coefficient threshold, a high-risk signal is generated.

6. The scene generation method of a ship system according to claim 1, characterized in that: Based on the ship navigation model, the wave height, wave direction and wave period of the waves that the ship will encounter during the navigation process are predicted to obtain the predicted waves, and the process of obtaining the predicted data is as follows: Based on the current navigation data obtained, the first several waves among the fixed number of waves are eliminated, and the remaining waves are marked as wave groups to be analyzed; Based on the wave group to be analyzed and the ship navigation model, the wave height, wave direction and wave period of multiple waves to be encountered are predicted to obtain multiple predicted waves; In terms of time, multiple predicted waves are added to the back of the wave group to be analyzed, that is, a fixed number of waves are used to obtain the predicted data, thereby obtaining the predicted data.

7. The scene generation method of a ship system according to claim 1, characterized in that: The process of generating risk prediction signals is: Compare and analyze the navigation prediction coefficient with the navigation coefficient threshold; If the navigation prediction coefficient is less than the navigation coefficient threshold, a high-risk release signal is generated; If the navigation prediction coefficient is ≥ the navigation coefficient threshold, a high risk signal is generated.

8. A scene generation system for a ship system, characterized in that: The system is used to execute the method described in any one of claims 1 to 7, and the system comprises: Data acquisition module: When the ship is sailing, the environment of the ship is detected and the navigation data within a fixed period of time is obtained; Among them, the navigation data includes: the wave height, wave direction and wave period of each wave of the ship in a fixed period of time; Data processing module: based on the navigation data of the ship in a fixed period, calculate the navigation coefficient of the fixed period; Risk assessment module: Based on the navigation coefficient of a fixed period, it assesses the risk of the ship in the fixed period, determines whether the ship is currently in a high-risk state, and generates a risk assessment signal; Among them, the risk assessment signals include: high risk signals and low risk signals; Model building module: Based on high-risk signals, the ship's navigation model is established using the ship's past navigation data; Data prediction module: Based on the ship navigation model, the wave height, wave direction and wave period of the waves that the ship will encounter during the navigation process are predicted to obtain the predicted waves and thus obtain the predicted data; Prediction data processing module: based on the prediction data, calculate the navigation prediction coefficient of the ship in a fixed period of time; Risk prediction module: Based on the navigation prediction coefficient, the subsequent navigation environment of the ship is evaluated to determine whether the subsequent navigation environment of the ship is still in a high-risk state, and generate a risk prediction signal; Among them, risk prediction signals include: still high risk signal and high risk relief signal; Display module: Based on the still high risk signal, the predicted wave height, wave direction and wave period are sent to the front end.

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