Calculating ship roll period

Abstract

Portable sensing equipment may be provided to determine at least one stability assessment value for the vessel. The sensing equipment may include one or more motion sensors to sense motion of the vessel, one or more freeboard sensors to determine a freeboard of the vessel, and a computing system to process the motion data from the one or more motion sensors and the freeboard data from the one or more freeboard sensors to determine the at least one stability assessment value. The computing system may be programmed to convert the motion data from time domain motion data to frequency domain motion data and process the frequency domain motion data to determine the at least one stability assessment value for the vessel and the freeboard of the vessel.

Description

[Technical Field]

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS This application claims priority to U.S. Provisional Patent Application No. 63 / 016483, filed April 28, 2020, the entire contents of which are incorporated herein by reference.

[0002] FIELD OF THE INVENTION The present invention relates to an apparatus and method for determining the stability of a marine vessel. [Background technology]

[0003] Background of the Invention Clearly, vessel stability is a critical factor in maritime operations. Current ship modeling systems only use mathematics and blueprint dimensions to approximate stability. Figures 1A and 1B illustrate the theory behind ship stability. In Figure 1A, a vessel 110 floating in a body of water 120 has a center of gravity M 112, the point around which the vessel's center of buoyancy rotates like a pendulum as the vessel heels, as shown in Figure 1B. This is generally only true when the heel angle is less than 10 degrees. The vessel has a center of gravity G 114 and a center of buoyancy B 116. [Prior art document] [Patent Document 1] U.S. Patent No. 4,918,628 Summary of the Invention [Problem to be solved by the invention]

[0004] GM is the most important stability evaluation value for ship's navigators to evaluate the stability of a float. GM is the linear distance between the float's center of gravity (G) and center of roll (M), and reflects the float's initial static stability. GM is particularly important for ships where the center of gravity G changes frequently, such as merchant ships, fishing boats, and passenger ferries. GM is also crucial in the event of ship damage. Every ship has its own "safety range" of GM. If GM is too low, stability will be compromised, and if it is too high, "sudden" rolling movements may actually injure personnel.

[0005] There will be many situations in which it is desirable for a person to encounter a vessel and be able to quickly determine whether it is safe to remain on board and / or operate the vessel. For example, search and rescue or law enforcement operations may require a person to board a vessel whose design or loading conditions are not known in advance.

[0006] Current GM modeling systems are expensive, cumbersome, and require significant training. Furthermore, the systems require many inputs, making it virtually impossible to quickly obtain accurate assessments. For example, the U.S. Navy Flood Hazard Control System (FCCS) requires fuel and water tank levels, knowledge of cargo and personnel, often speculative or incomplete damage reports, and potentially inaccurate load plans. The systems are prohibitively expensive to purchase, making them unusable for small-scale operations.

[0007] What is needed are improved devices, systems, and methods for calculating vessel stability information.

[0008] Summary of one embodiment of the invention Advantages of One or More Embodiments of the Invention Various embodiments of the present invention may realize one or more, if not all, of the following advantages. Ability to calculate stability ratings for floating structures; Performing fast calculations of ship stability, The ability to obtain vessel stability ratings using real-time measurement data; Providing cost-effective equipment for determining vessel stability; Providing a portable instrument that can be quickly installed on a vessel to obtain vessel stability measurements; Providing low-cost equipment that can be owned by individuals or teams who move from ship to ship; Providing the ability to quickly assess the residual stability of a vessel which can be used in combination with roll period and / or centric height to quickly assess the safety of the vessel's current loading condition.

[0009] These and other advantages will be understood by reference to the following portions of the specification, claims, and abstract. [Means for solving the problem]

[0010] Brief Description of One Embodiment of the Invention In one aspect of the present invention, there is provided a portable sensing device for determining at least one stability measure of a vessel. The sensing device may include one or more motion sensors for sensing motion of the vessel, one or more freeboard sensors for determining freeboard of the vessel, and a computing system for processing motion data from the one or more motion sensors and freeboard data from the one or more freeboard sensors to determine the at least one stability measure. The computing system may be programmed to convert the motion data from time domain motion data to frequency domain motion data and process the frequency domain motion data to determine the at least one stability measure of the vessel and the freeboard of the vessel.

[0011] In one embodiment, the motion data can be converted into roll period data.

[0012] In one embodiment, the portable sensing device may include a housing removably attachable to the vessel, the housing housing one or more motion sensors and a computing system.

[0013] In one embodiment, the portable sensing device may include an interface for receiving input of the vessel's beam width.

[0014] In one embodiment, the computing system is programmed to convert the roll period into a vessel centering height.

[0015] In one embodiment, the portable sensing device may include a display that displays at least one of the vessel roll period and the vessel centering height.

[0016] In one aspect of the present invention, there is provided a method for determining at least one stability measure for a vessel. The method may include installing portable sensing equipment at a location on the vessel, the sensing equipment including one or more motion sensors that sense motion of the vessel, and a computing system that processes motion data from the one or more motion sensors to determine at least one stability measure for the vessel. The method may include operating the sensing equipment for a period of time to generate an initial indication of the roll period of the vessel, determining a freeboard of the vessel, and determining a stability state of the vessel from the roll period and the freeboard.

[0017] In one embodiment, the initial display occurs every 5 minutes or less.

[0018] In one aspect, there is provided a system that includes at least one device programmed to communicate directly or indirectly with a third party system for a vessel that includes one or more third party sensors that receive raw motion data and freeboard data from one or more third party sensors, convert the motion data into at least one stability estimate that includes at least one of a vessel roll period or a vessel centering height, and combine the stability estimate and the freeboard data to determine a stability state of the vessel.

[0019] In one aspect, a method for determining at least one stability assessment for a marine vessel is provided. The method may include installing a portable sensing device at a location on the marine vessel, the portable sensing device including one or more motion sensors that sense motion data for the marine vessel and a computing system that processes the motion data from the one or more motion sensors to determine a roll period for the marine vessel. The sensing device may be operated for a period of time to generate an indication of the roll period for the marine vessel. The method may further include verifying the accuracy or precision of the sensed roll period and determining at least one stability assessment for the marine vessel from the roll period.

[0020] In one aspect, there is provided a computer readable medium comprising instructions executable by at least one processor that, when executed, cause at least one processor to: communicate directly or indirectly with a third party system for a vessel including one or more third party sensors to receive raw motion data from the one or more third party sensors and freeboard data from the one or more third party sensors; convert the motion data into at least one stability assessment value comprising at least one of a roll period of the vessel or a centering height of the vessel; and combine the stability assessment value and the freeboard data to determine a stability state of the vessel.

[0021] The foregoing disclosure sets forth an outline of one embodiment of the present invention so that the detailed description that follows may be better understood, and so that the present contribution to the art may be better appreciated. Some embodiments of the present invention may not include all of the features or characteristics enumerated in the summary above. There are, of course, additional features of the present invention that will be described below and will form the subject matter of the claims. In this regard, before describing at least one preferred embodiment of the present invention in detail, it is to be understood that the invention is not limited in scope to the details of construction and the arrangement of elements set forth in the following description or illustrated in the drawings. The invention is capable of other embodiments and of being practiced and carried out in various ways. It is also to be understood that the phraseology and terminology employed herein is for the purpose of description only and should not be regarded as limiting the invention. [Brief explanation of the drawings]

[0022] BRIEF DESCRIPTION OF THE DRAWINGS [Figure 1A] The stability rating values ​​are shown for a vessel when the stability rating values ​​are aligned vertically. [Figure 1B] This shows the stability rating of a vessel when the vessel is heeled and the stability rating is not aligned vertically. [Figure 2] Schematic showing elements of the stability assessment system within the enclosure. [Figure 3] 1 shows a graph of motion data substantially in the time domain. [Figure 4]10 shows a graph of energy data versus period in the frequency domain. [Figure 5] 10 shows a process for generating roll period data in essence. [Figure 6] 10 shows a graph substantially illustrating the change in roll period calculation over time. [Figure 7] 1 shows essentially the main routine of the roll period calculation algorithm. [Figure 8] 10 shows a transformation routine of the roll period calculation algorithm that transforms time domain data into frequency domain data. [Figure 9] 1 shows a filter routine that essentially implements a Kalman filter for the calculation of roll period and centripetal height. [Figure 10] An example of a stability curve is shown. [Figure 11] 1 shows a schematic diagram of the freeboard of a vessel substantially; [Figure 12] 1 shows an example of a freeboard versus roll period diagram substantially; [Figure 13] 1 shows a table of the standard deviation of the measurements and the energy dispersion data. [Figure 14] 14 shows a graph of the data in the table of FIG. 13. DETAILED DESCRIPTION OF THE INVENTION

[0023] Description of Specific Embodiments of the Invention In the following detailed description of the preferred embodiments, reference is made to the accompanying drawings that form a part hereof. These drawings show, by way of illustration, specific embodiments in which the invention may be practiced. It is to be understood that structural changes may be made utilizing other embodiments without departing from the scope of the present invention.

[0024] Current ship modeling systems only use mathematics and blueprint dimensions to approximate stability. Embodiments of the present disclosure provide a device that can convert real-time measurements from various sensors into calculations of ship stability. By basing stability assessments on real-time data rather than historical information and incomplete or speculative reports, the accuracy and effectiveness of stability assessments can be improved.

[0025] FIG. 2 illustrates a stability assessment system 200 for assessing the stability of a vessel, according to one embodiment of the present application. The system 200 includes a housing 210 that houses one or more motion sensors 212. The motion sensors 212 may include any suitable motion sensors capable of detecting vibrations of a floating vessel and determining the vessel's roll rate. Computational elements forming a signal processing system receive the motion data from the sensors and process and convert the motion data into a roll period. The roll rate (usually in radians per second) is typically one of the outputs of a basic motion sensor and does not require any processing. Actual roll data (usually in radians) may require extensive processing. The roll rate, roll (as well as acceleration and magnetometer data) may all be used as estimates that can be converted into a roll period.

[0026] The roll period is related to the vessel's centric height (GM) by the following equation:

number

[0027] The "mould width" used to derive the k value is similar to the beam width, but provides a more precise measurement. The "mould width" is considered to be the longest beam, or width, of the ship measured inside the inner hull strake of the plating, which usually occurs amidships. In one embodiment, k can be derived from the beam width.

[0028] Users of varying levels of sophistication will know the beam, or mould width, or actual section radius of gyration of their vessel, and the calculation system may have an interface that allows the user to input any of the beam, mould width, or section radius of gyration for use in calculating the roll data time.

[0029] Equation 1 shows the inverse relationship between roll period and centering height. Therefore, roll period can be used as an indicator of a ship's stability. Importantly, changes in roll period due to changes in the ship's condition caused by load increases or decreases, shifts in the position of loads, damage to the hull, etc., can provide an indication that the ship is stabilizing or becoming unstable, and can be used as an indicator or predictor of serious instability before it occurs.

[0030] Equation 1 above utilizes the cross-sectional radius of gyration k in calculating the roll period. In an alternative embodiment, the roll period can be calculated from the following equation:

number

[0031] Equation 2 is generally coarser than Equation 1, but both can be used to perform meaningful centripetal height calculations.

[0032] In one embodiment, the motion sensor may be a simple pendulum with basic signal processing. In more advanced embodiments, the motion sensor may include one or more micro-electromechanical systems (MEMS) sensors incorporating one or more gyros and / or accelerometers. In certain embodiments, the MEMS sensor may include a sensor with three-axis, nine-degrees-of-freedom motion detection. The motion sensor may detect motion and provide an output signal to a signal processing system.

[0033] The computing elements included in the signal processing system may be integrated, dedicated computers that include at least one processor 214 and at least one memory 216 operatively associated with the processor. The memory 216 may include storage memory, i.e., read-only memory, that may store programs, applications, libraries, and instruction sets executable by the processor(s). The memory 216 may also include random access memory (RAM) used to execute the programs, applications, instruction sets, etc.

[0034] In one embodiment, the computer system is programmed to receive input signals from one or more sensors 212, in particular roll rate data, accelerometer data, magnetometer data, or calculated roll data, and process and convert the signals into one or more parameters, estimates, or outputs that serve to provide an indication of the stability of the vessel.

[0035] In one embodiment, the sensor system and computational elements are housed in a single integrated unit, such as in a single housing 210. The single unit may have a power source 218, such as from a battery, or may have one or more power ports for connecting to an external power source, such as via a conventional power plug or via a Universal Serial Bus (USB) plug, for connection to the vessel's power supply.

[0036] The detector 200 may include a user interface 220 that allows a user to provide input data, including calibration data, run count, vessel beam, minimum known roll period, maximum known centering height, or any other information necessary to perform a stability assessment calculation. The detector 200 may include a display 222 that displays output, such as roll period, roll period over time, centering height, or other assessments that can be derived from motion sensor data. Additional assessments may include, without limitation, current pitch and roll values ​​(i.e., the vessel is currently rolling 8 degrees and pitching 6 degrees, and the maximum roll in the past 5 minutes was 9.2 and the maximum pitch was 7). Such assessments may be useful for vessels attempting stability-requiring maneuvers, such as launching or recovering a helicopter, since each vessel has pitch and roll limits. The detector 200 may also include a communications module 224 that allows data to be received from and / or transmitted to the detector 200 from external devices.

[0037] The housing 210 may have an attachment that removably secures the housing to the vessel. For example, the housing may have a keyhole that allows the sensing unit to be hooked onto a suitable plug, hook, screw, or similar protrusion on the vessel. In other embodiments, the housing 210 is engagable with a docking station, such as a cell phone docking station, installed on the vessel. The attachment may be positioned so that the housing is secured to the vessel in an orientation appropriate for measuring roll rate data. Orientation is important, and therefore the sensor unit 210 may be provided with one or more markings or markers that define a designated axis of the device housing (phone, tablet, etc.) that aligns with the longitudinal (fore-aft) axis of the vessel to ensure that pitch and roll are accurately detected. Location on the vessel is not critical, as meaningful measurements can be made almost anywhere on the vessel. Furthermore, if the sensor unit were permanently installed in a location, algorithms could be optimized for that specific location, but this is not necessary for basic operation.

[0038] In an alternative embodiment, the sensor unit may be separate from the computing element. The sensor unit may include a communications module that transmits output signals to the computer unit via a wired (e.g., USB or similar serial line) or wireless (e.g., Bluetooth, RF, WiFi, Internet) communications channel. The sensor unit may have its own internal power source, e.g., a battery, or a power port for receiving power from the vessel's power supply or from the computer unit, e.g., via a USB connection. The sensor unit 210 may include one or more freeboard sensors 226, the functions of which are described below. The freeboard sensors may be integrated into the sensor unit housing or distributed at desired locations on the vessel, depending on the particular type of freeboard sensor. When a distributed freeboard sensor is deployed, the freeboard sensor 226 may communicate with the sensor unit via wired or wireless means. The sensor unit 210 may also include an inclinometer 228, which can be used for various functions, including calibration functions such as roll drift calibration, as described below.

[0039] The MEMS sensors can process the recorded motion and convert it into roll data expressed in degrees per second, degrees, or equivalent dimensions. In one embodiment, multiple sensors record roll velocity every half second. FIG. 3 shows an example graph 310 of roll velocity 320 versus time 330. This data can be converted from the time domain to the frequency domain using a mathematical transformation operation to represent energy per recorded time. Transformations may include, but are not limited to, Fourier transform, fast Fourier transform (FFT), fast discrete Fourier transform, optimal Fourier transform, discrete Fourier transform, Welch's method, autocorrelation, etc. In one embodiment, quarter-minute blocks of data are transformed using a fast Fourier transform process. FIG. 4 shows an example graph 410 of period 430 versus energy 420 derived from an FFT of the roll velocity versus time graph of FIG. 3. The raw data can be filtered to provide a smoothed output 440. In one embodiment, the filtered data 440 may include a simple moving average filter, a weighted moving average filter, a linear regression model, exponential smoothing, Kalman, or similar filters. The roll period is the time 450 with the highest energy in the frequency domain. The plausibility of a signal can be confirmed in many different ways. In one embodiment, the signal spread can be evaluated, and the variance or standard deviation of the periods of the strongest signals obtained provides an indication of the signal's plausibility. A high level of signal spread would indicate a low plausibility of the signal, while a low level of signal spread would indicate a high plausibility of the signal. In another embodiment, the energy spread is evaluated, and the variance or standard deviation of the energy of the strongest signals can be used. A high level of energy spread indicates a high plausibility of the signal, while a low level of energy spread indicates a low plausibility of the signal. In the case of energy spread, the plausibility value can be normalized by dividing the energy spread by the energy of the strongest signal. In one embodiment, the top 10 signals can be evaluated to determine the signal spread or energy spread.

[0040] A specific system 500 illustrating the signal processing capabilities of a computer system is shown in FIG. 5. Signals generated by a MEMS sensor 502 are received by a signal processing computer, which performs an initial windowing / filtering operation 504 on the data to select data of interest; these operations occur in the time domain 520. The filtered signal then undergoes a Fourier (or other similar) transform 506, which converts the data from the time domain to the frequency domain 530. The transformed data may then be subjected to an energy analysis 508, which calculates the vessel's roll period 512, and a Kalman filter 510. The Kalman filter "intelligently" processes the data over time. Specific parameters in the Kalman filter can set the rate of change of the roll period and the boundaries of the roll period. This provides an optimal data output, taking into account the validity of the signal (in the energy analysis 508) and determining the probability that each data input is accurate. While a Kalman filter is described, other data processing techniques can be used to augment the final result. For example, a weighted moving average filter or a linear regression model could be used. With input estimates of the vessel's beam and type that can be used to approximate the k value required in Equation 1, or the C value in Equation 2, the roll period data can be further processed for use in calculating the vessel's centering height GM and other health data 514. The health value may be derived from the signal validity described above or generated by a Kalman filter and provides an indication to the user of the quality of the data being generated, i.e., the level of confidence that accurate roll period data is being generated. The health data may be presented as one or more visual representations of the data, one or more audible alarms, and / or one or more emergency notifications.

[0041] In effect, signal validity assessment is a probabilistic assessment of measurement accuracy versus normalized energy variance (NEV). Signal validity is important for user experience, but also for processing due to the large amount of spurious data that can be recorded. In various embodiments, a Kalman filter (or equivalent) is the backbone of the post-FFT algorithm, requiring a probabilistic validity value 514 for each new data point. For example, if the FFT indicates a roll period of 7 seconds, then the NEV would be 0.3. Signal validity assessment can utilize a table describing the probability (in the form of a standard deviation over a large sample set of measurements at NEV=0.3) that a measurement taken with NEV=0.3 is truly 7 seconds. An example table is shown in Figure 13. The table data from Figure 13 is graphed in Figure 14 as a plot of standard deviation versus NEV. The NEV informs the Kalman filter how much to weight a new roll period relative to previous measurements. The normalized energy variance provides a probabilistic validity value that can be translated between different vessels.

[0042] Very small amounts of motion can result in falsely high NEV values. To address this, an EV (energy variance) cutoff can be used. If EV<0.009, the measurement is treated as if it had NEV<0.1 (very low accuracy), as shown in the table in Figure 13. Note that in the table in Figure 13, StDev has increased from 0.3 to 0.4. This appears to be an anomaly and will likely improve with more data acquisition.

[0043] The system in Figure 2 provides a portable system that can be quickly installed on a vessel and is operational to provide an initial assessment of a vessel's stability and health within approximately four minutes. The combination of advanced motion sensors, digital signal processing, and nautical engineering results in an accurate and empirical stability monitoring system that improves vessel safety. Lifesaving real-time analysis can be performed by validating predictive calculations, providing early warning of unknown stability issues and accurate and immediate stability calculations after damage. These initial stability assessments can protect military, rescue, and law enforcement boarding teams when operating on vessels whose structure and stability are unknown. Other users include captains who travel between vessels and desire an initial and rapid assessment of an unfamiliar vessel. While the system is portable, it may also be permanently installed on a vessel.

[0044] In addition to the initial assessment, the system can quickly calculate any changes in vessel health due to dynamic conditions, such as boarding, ongoing damage, flooding, loading or unloading the vessel, changing sea conditions and weather, and ice accumulation, providing real-time, evolving operational data so that action can be taken, if necessary, before catastrophic events occur. In one embodiment, continuous roll periods can be calculated and displayed over time. FIG. 6 shows a graph 610 of time 630 versus roll period 620, including a filtered output 640. In one embodiment, the filtered output may include a 13-minute weighted moving average. A 13-minute average period is considered long enough to smooth out short-term effects, yet short enough to prevent potential adverse conditions from being buried in the average. Alternatively or additionally, a Kalman filter may be implemented. The roll period may be replaced with centripetal height GM or other health data, if desired.

[0045] The system may be programmed to generate notifications, alerts, warnings, etc. when a roll period or centering height threshold is detected. The threshold level may be vessel dependent rather than fixed or absolute, and may be based on a user's comfort level. Monitoring the roll period or centering height may include not only monitoring current values, but also detecting changes over time and using trend data to predict stability issues before they occur.

[0046] As described above, the system described herein can be used to rapidly assess the stability and health of a vessel. No prior knowledge of the vessel is required during search and rescue and / or law enforcement operations. The system, therefore, protects vulnerable boarding team personnel on vessels with questionable stability. During periods of significant damage, immediate stability reports can be obtained while the assessment crew searches for the damage. Any vessel may have unknown damage or immeasurable ice accumulation that cannot be addressed with current technology. Therefore, all vessels can benefit from roll cycle detection equipment as described herein. A particular advantage is that the low cost of construction of roll cycle detection equipment makes it accessible to many smaller vessels and / or for specific use by individuals or teams, such as captains and similar maritime personnel, who may move from vessel to vessel.

[0047] The systems described herein can be implemented in a variety of forms. In a basic implementation, ideal for small vessels, onboard teams, and the like, the roll period detection device can be completely contained within a box measuring approximately 6" x 2" x 3". The box may include a motion sensor, at least one processor and memory, associated electronics, and power source. In an alternative embodiment, the detection device may be a smartphone such as an iPhone / iPad or Android phone or tablet that utilizes the device's built-in motion sensor, processing power, and memory. Power may be an internal battery or connection to the vessel's power source via USB or other power source. The memory may store application software that performs the functions of the roll period detection device described herein. The box may include an interface and input devices that allow a user to input the necessary data, including calibration data. In particular, the user may input the minimum design roll period (or maximum design GM) as well as the beam width of the target vessel to be used in the centering height calculation. Other vessel-specific parameters that can be input via the interface may include, but are not limited to, roll constant, rolling coefficient, vessel type, estimated initialization roll period, expected day-to-day variation in GM or roll period due to fuel consumption, cross-sectional radius of gyration, form width, pitch, roll, GM, or roll period alarm parameters, etc.

[0048] The box may include a simple display showing real-time roll period and / or centering height. Under all conditions, roll period is a useful quantity for the vessel operator. GM varies with roll period and is similarly useful, but can be easily derived from roll period only under smaller roll amplitudes (typically <10 degrees). The software may be programmed to include a cutoff value so that if the algorithm detects a roll greater than 10 degrees, it will stop updating the GM but will always provide a roll period. The cutoff value may be a user-configurable parameter, or a default cutoff may be programmed into the system.

[0049] The display may be programmed to display the stability rating in other useful representations or formats, including, but not limited to, one or more of the average or maximum pitch and roll amplitude over time.

[0050] The box may include an internal power source and associated electronics, including replaceable and / or rechargeable batteries, to power the motion sensors, computational elements, and display. Alternatively, the box may include a power port for connecting to an external power source. The sensor unit may include mounting components for easy installation on the vessel. These mounting components may include clips, brackets, adhesives, Velcro, etc. In use, a user attaches the roll cycle detection device box to the vessel and operates the device for approximately 5 to 15 minutes to obtain initial results. This provides the user with real-time data to make informed decisions following risk analysis. For example, ship captains (and engineers) are typically highly trained in stability and roll cycle. An example of risk management is a vessel operating with a high roll cycle (low GM). The captain may accept this situation if the vessel is entering port in good weather that day. If the vessel is three days away from entering port and there is a potential for a dangerous storm, the captain may decide to add ballast to the tanks to improve stability.

[0051] For larger systems, such as larger military and commercial vessels, the roll period detection equipment may include a communications module capable of receiving raw data from existing onboard motion sensors and converting it into useful roll period data, and / or transmitting motion sensor data and / or roll period analysis data to an external computing system. The external computing system may be located on the vessel. Alternatively, the data may be transmitted to a land-based processing station. Increased computing power, either onboard or onshore, may allow for more intensive calculations and have more stringent power requirements, providing users with more sophisticated motion analysis, including higher health roll periods and centering heights, particularly for larger vessels where roll periods can vary significantly based on loading conditions, such as from 2 to 40 seconds. Shorter roll periods require higher sample frequencies, while longer roll periods require larger sample sizes, increasing the time required to perform updates within these ranges.

[0052] Coached tilt experiment Listing experiments are crucial tests that determine a vessel's initial stability, or general helix (GM). Listing experiments are performed in port with slack dock lines and observe the vessel's precise heel as a weight of known value (W) is added, removed, or moved a specific distance (d) alongside the vessel. The vessel's displacement is known from freeboard measurements and / or draft observations. Since the distance (d) moved by a known weight W is known and the vessel's displacement is also known, the GM can be determined. Typically, the weight is moved multiple times (usually eight times) to verify results and correlate multiple observations of heel change with multiple changes in the weight's position.

[0053] By determining the roll period by rocking the vessel whilst determining the GM by employing a heeling experiment, the user can know the value of the roll coefficient C for that particular loading condition. This can be extremely useful when attempting to later correlate GM with roll period, possibly while the vessel is underway. The roll coefficient has a variety of uses, for example as the value "C" in Equation 2 above.

[0054] Freeboard Measurement Initial stability is determined by the center of gravity (G) of the vessel, which is the distance between the vessel's center of gravity (G) and the center of heel (M). The righting arm is the stabilizing moment that keeps the vessel upright against the heel arm caused by wind, sea conditions, etc. An exemplary vessel stability curve 1000 (Figure 10) illustrates residual stability, which is the "residual" righting energy that allows the vessel to overcome heel forces. An important consideration with residual stability is the vessel's freeboard (f) 1102 (Figure 11), which directly affects the amount of residual stability the vessel enjoys. Freeboard is represented by the vessel's displacement (d) 1104. As displacement increases, freeboard decreases. Also, as the vessel heels, freeboard decreases on one side (and increases on the other side) (Figure 1B). As weight increases, displacement increases, and initial stability (GM) increases or decreases depending on the position of the vessel where the weight is added. However, in either case, increasing weight decreases the vessel's freeboard. While a reduction in freeboard may or may not affect initial stability, it generally has a negative effect on residual stability, allowing seawater to more easily infiltrate the deck or interior of the ship, thereby reducing the righting arm at various heel angles. It is possible to generate a graph showing roll period (or centric height) on one axis and freeboard on the other. Typically, such a chart will be provided by the shipbuilder or generated or capable of being generated by the naval architect.

[0055] A chart of the exemplary form shown in Figure 12 then shows acceptable and unacceptable stability regions given freeboard and roll period (or centric height) for different loading conditions of the vessel. Different loading conditions may arise, for example, based on changes in fuel levels during operation, loading of a trawler's fishing bay, addition of new equipment, shifts in loads within the vessel, etc. For example, Figure 12 shows three separate plots. Plot (a) may show safe and unsafe combinations of freeboard and roll period for a vessel with full tanks, plot (b) may show safe and unsafe regions for a vessel with half full tanks (e.g., half the tanks are completely empty), and plot (c) may show a situation where all tanks are nearly empty.

[0056] In one aspect of the present invention, a sensing device is provided for determining freeboard. The sensing device may include one or more distance meters that measure the distance from the vessel's main deck to the water level 1108 outside the vessel. The sensor may be a distance sensor mounted on the main deck or one or more linear fluid sensors mounted on the vessel's exterior. Alternatively, the sensor may be one or more sensors mounted inside the vessel's hull that can detect the presence of liquid on the opposite side of the vessel. Alternatively, the sensor may be a pressure sensor mounted on the vessel's exterior at a specific location below the waterline, which detects pressure and can therefore be used to determine the depth below the waterline at that specific location on the vessel. The pressure information can be manipulated to determine freeboard. The determined vessel freeboard, or residual stability, can then be used in conjunction with the roll period and centering height to quickly assess the safety of the vessel's current loading condition.

[0057] In one embodiment, the processor 214 of the sensing portion 210 is programmed with the freeboard versus roll period relationship of Figure 12 and can receive ongoing displacement related data such as fuel load, fishing level, passenger level, etc. As the roll period is calculated, the processor 214 incorporates the freeboard calculation and outputs an indication of the vessel's current stability state. The stability state can be indicated, for example, as a position on the chart of Figure 12 that can be displayed on the display 222, a binary indication of sufficient or insufficient stability (e.g., indicated by a status light or an audible alarm), a status bar that can include a number of lights that provide an indication of stability in the form of the number of lights illuminated, etc.

[0058] Roll Drift There are technical challenges associated with resolving drifting roll or heel when using "isolated" sensor packages that do not have absolute external measurements as input. An example of an isolated sensor package is a typical 9-DOF sensor package. This situation can have a variety of causes, ranging from disturbances in the vessel's motion to magnetic or electromagnetic interference. One possible solution to this situation is to implement a dedicated pendulum or modified hydrodynamic inclinometer that periodically performs the external calibration required to determine the roll / heel solution.

[0059] In one embodiment, the sensor section 210 may include an inclinometer 228 of a type that can be used to calibrate and recalibrate roll drift. In one specific embodiment, a conventional fluid-filled inclinometer is fitted with two electrodes, and when a conductive weight passes the centerline, it closes a circuit, informing the system that the vessel was vertical at that moment. A similar configuration is possible, with a conventional fluid-filled inclinometer mounted on the camera lens of a cell phone. As the vessel passes vertically, the weight blocks the light from the camera, indicating to the system that the vessel was vertical at that moment. A pendulum with a magnet may also be implemented. As the vessel passes vertically, the magnet passes a magnetic pickup, closing a circuit and indicating to the system that the vessel is vertical. Finally, an electrometer is attached to the pendulum's pivot point to provide complete roll and heel information to the system at all times.

[0060] Figures 7-9 show flow diagrams of algorithmic subroutines that perform the roll period or centricity calculations. The algorithm labeled RPSD receives raw motion data from the vessel's internal motion sensors or third-party sensors. The RPSD algorithm converts the raw motion data (of multiple different types) into a Kalman-fused roll period and centricity solution with error covariance values. The initial data matrices (MS1A and ML1A) contain columns of motion data, including but not limited to rate gyro, lateral acceleration, and absolute azimuth roll.

[0061] The first routine, labeled "Main," is shown in the flow diagram in Figure 7. The "Main" routine: - Collect and organize sensor data sets into matrices. - Pass the full matrix to a transformation routine that produces a signal vector. - analyzing the strength of each signal and passing the appropriate signal to the respective Kalman filter routine (roll period filter and / or centration height filter); -Present the resulting converted information to the user.

[0062] The transformation routine is shown in Figure 8. The transformation routine converts the full data matrix from the time domain to the frequency domain. Possible transformation methods include Fast Discrete Fourier Transform, Optimal Fourier Transform, Discrete Fourier Transform, Welch's method, and Autocorrelation.

[0063] The Kalman routine shown in Figure 9 includes two functions, KLMgm and KLMrp, which implement a Kalman filter that performs optimal mean square estimation on the output variables of roll period and gyration height (GM), respectively.

[0064] Below is provided pseudocode for the RPSD algorithm for the routines in Figures 7-9 that can be used to calculate the roll period and / or centric height (GM).

[0065] The pseudocode defines the variables as follows: variable: Input (also global variables): ** All units are meters, even lengths ** Required B: Beam of ship (may be given as width instead of beam) Optional C: Roll Factor --- default value is 0.7 (in meters) T: Ship type (select from 8 types) --- default is nil, better default C is possible G: Maximum design GM --- default value is 5.0 meters e: Minimum design roll period --- default is C* B / sqrt(G) q: Estimated initialization roll period --- default value is e D: Estimated daily change in GM due to fuel consumption --- default value is 0 R: Roll amplitude alarm threshold --- default value is nil P: Pitch amplitude alarm threshold --- default is nil S:GM alarm threshold --- default is nil r: Roll cycle alarm threshold --- default is nil

[0066] Tuning parameters (including global variables) Ih: Health threshold - minimum roll period health diagram (in frequency domain) for further processing / presentation to user --- Default value is 2.5 Ra: Roll Amplitude Threshold - Maximum roll amplitude (in time domain) for calculating and providing GM for the user --- default is 10 degrees Rb: Roll frequency bias - an adjustment applied to user-provided (or system-calculated) e to ensure a minimum roll period is observed --- default is 0.9 Sf:Sensor sample frequency - frequency of time series data batches received from the sensor --- default is 10Hz ** This may be outside the control of the algorithm, so set a minimum value of 5Hz. ** Me: The minimum roll period converted to observe the period under condition E --- default value is 5 Sp: Roll period threshold that triggers two simultaneous data capture events to ensure sufficient roll period accuracy and updates. -- Default value is 30

[0067] Global variables: Rol: A single decimal value of the known or reliable roll period received from the Kalman filter at each iteration. Initialized to the minimum reasonable roll period for the ship. - Initialize as Rol=q - Updated by Kalman filter GMc: A single decimal value of the known or reliable roll period received from the Kalman filter at each iteration. Initialized to the minimum reasonable roll period for the ship. - Initialize as Rol=q - Updated by Kalman filter Egm: "Pk" Kalman error covariance of the GM filter - passed to the user as a measure of the soundness of the GM solution Erp: Kalman error covariance of the "Pk" roll periodic filter - passed to the user as a soundness value for the roll periodic solution Lco: Low-pass filter cutoff frequency - A low-pass filter removes all values ​​with frequencies higher (low periods) than Lco before converting from time to frequency domain. - Leo=e * Rb

[0068] Function-type variables Function MAIN Description: Commands sensor readings and handles the calls to the TRANS function and two Kalman functions

[0069] Under long roll period conditions (when the system must operate at peak speed), simultaneous data acquisition may be required. In this case, a short matrix (MSA1) is constructed together with a long matrix (MLAl). MSA1 is always generated and takes 1-22 minutes to generate. MLAl is generated when Rol >= Sp and takes 1-60 minutes to generate. BS1A: Batch size 1 - An integer representing the number of data points in the unparsed short data matrix SSI. --- Extracted from MSCA based on Rol MS1A: A matrix of N columns and BS1A rows containing unparsed short data. --- Received from the sensor (via DATAQ) FS2A: Short Frequency 2 - Desired frequency of short data after parsing before conversion --- Extracted from MSCA based on Rol BL1A: Batch size 1 - An integer representing the number of data points in the unparsed long data matrix ML1 --- Extracted from MSCA based on Rol BS2A:BatchSize2 - An integer representing the number of data points in the parsed short data matrix. --- Extracted from MSCA based on Rol BL2A:BatchSize2 - An integer representing the number of data points in the parsed long data matrix. --- Extracted from MLCA based on Rol ML1A: A 3 column, BL1A row matrix containing unparsed long data. The columns contain the same data as MS1A. --- Received from the sensor (via DATAQ) FL2A: Long Frequency 2 - Desired frequency of the long data after parsing before conversion --- Extracted from MLCA based on Rol Matl: A matrix processing variable that sends a complete matrix to a transformation function. MenR: The calculated mean amplitude of the absolute heading roll solution (as given in ML1A or MS1A), i.e. the current ship's roll state. MenP: The calculated mean amplitude of the absolute heading pitch solution (as given in ML1A or MS1A), i.e. the current ship pitch state. MSCA: Short-period rule table matrix - currently in the second sheet of FFT_PreProc.xlsx MLCA: Long-period rule table matrix - currently in the third sheet of FFT_PreProc.xlsx RppA: Vector of observed roll periods in the frequency domain (seconds)

[0070] Function TRANS Description: It performs all of the data processing (parsing, detrending, filtering), the actual transformations, and the spectral analysis. All operations are performed on each column containing the data. ** Matr: The resulting matrix ** Frq2: the desired frequency of the matrix after the parsing operation ** Len2: The length of the data set after parsing from Sf to Frq2 Indx: Periodicity index multiplier in Hz --- Indx=(Frq2 / 2) / (Len2 / 2) Sdev: A vector of standard deviations for each periodogram Mean: A vector of the mean values ​​of each periodogram *Frqs: Roll frequency vector (hz) observed as the maximum value of each periodogram Strg: A vector of the intensity of each frequency observed in each periodogram *Ingy: A vector of health values ​​derived as the number of standard deviations from the mean for each signal *** (sometimes it is better to use a standard signal-to-noise approach) --- Ingy=(Frqs-Mean) / Sdev **Obtained from Main *Return to Main

[0071] Procedure KLMrp Description: Implemented a 1D Kalman filter for post-processing of the roll cycle **Zsbk: Measurement value "Zk" derived from FFT (Frqs vector) **Intg: Integrity value obtained from FFT (Ingy vector) RPkO: "X-hat0" Pre-state variable of the roll period at each iteration, initialized to Rol Kalm: "Kk" Kalman gain Psbk: "Pk" past error covariance *RPkl: Post-state variable of "X-hatl" roll period Atrn: "A" transition multiplier, default is 1 Bcon: "B" control multiplier, default is 1 Usbk: "Uk", control signal based on D, default value is 0 Time: Time since the last iteration of KLMrp (only required when using Bcon and Usbk) ** Obtained from Main *Return to Main

[0072] Procedure KLMgm Description: Kalman filter is used as post-processing for centripetal height (GM) **Zsbk: Measurement value "Zk" received from Main **Intg: Integrity value (Ingy vector) derived from FFT GMkO: "X-hatO": Pre-state variable of roll period at each iteration, initialized to Rol Kalm: "Kk" Kalman gain Psbk: "Pk" prior error covariance SetErr=Psbk after each iteration. *GMkl: Post-state variables for "X-hatl" roll cycle Atrn: "A" transition multiplier, default is 1 Bcon: "B" control multiplier, default is 1 Usbk: "Uk", control signal based on D, default value is 0 Time: Time since the last iteration of KLMrp (only required when using Bcon and Usbk) **Obtained from Main *Return to Main

[0073] The pseudocode provides the RPSD program. / / Program RPSD / / Course mod2 void main() { Read short matrix MS1A of length BS1A - start recording; / / If you know the roll period is long, generate both long and short matrices at the same time if(Rol>=Sp) Read long matrix MS1A of length BS1A - start recording; if (MS1A or ML1A is complete) { Assign Matl=Complete matrix; / / If either matrix is ​​complete, use the TRANS function to convert it from the time domain to the frequency domain. TRANS(Matl,FL2A,BL2A); / / Each processed matrix produces at least three periods with associated intensity values } while(true) { if(Ingy(l) <Ihならば) { Discard Ingy(l) and Frqs(l) } Otherwise { / / Feed all signals with sufficient strength to the roll period Kalman filter KLMrp(Frqs(l),Ingy(l)); if(MenR <Raならば) { / / Signals derived from samples with smaller roll amplitudes may also be sent to the centered Kalman filter KLMgm(Frqs(l),Ingy(l)); } } if(Ingy=empty) break; } Write to user:Rol,Erp,GMc,Egm,; } Vector conversion (Matr, Frq2, Len2) { / / Reduce the sample frequency from the value provided by the sensor to a rate optimal for data analysis 1. Parse Matr from Sf to Frq2 --- currently contains Len2 rows / / Preprocess the data in steps 2-4 before transforming from time domain to frequency domain 2. Remove the population mean from each column 3. Use linear regression to remove any trend lines from each column. 4. Non-causal low-pass filter for all columns - cutoff frequency is Lco 5. Perform a time to frequency domain transformation on each column 6. Index the N periodograms obtained by the multiplier Indx. 7. Observe the index and maximum value of each periodogram: Frqs / / Determine the health vector using signal-to-noise ratio, standard deviation from the mean, or other methods 8. Determine the health vector Ingy Frqs, return Ingy }

[0074] void KLMgm(Zsbk,Intg) { / / Estimate the centerline height using a transition variable associated with fuel consumption Predict the next tilt height Applying the conditional probability of measurement given the predicted centroid height and integrity value from the FFT, taking into account the uncertainty of the measured and estimated values New measurements lead to revised predictions Update global variables GMc and Egm using the Kalman updated GM and error covariance, respectively; }

[0075] void KLMrp(Zsbk,Intg) { / / Estimate the roll period using transition variables associated with fuel combustion Predicting subsequent roll periods; / / Apply conditional probability of measurements given predicted roll period and health value from FFT, taking into account uncertainties in measurements and estimates Revising predictions with new measurements; Update global variables Rol and Erp using the Kalman updated GM and error covariance, respectively;

[0076] Many variations and other implementations of the disclosure described herein will come to mind to one skilled in the art to which this disclosure pertains having the benefit of the teachings presented in the above description and the accompanying drawings. It is therefore to be understood that the disclosure is not limited to the particular implementations disclosed, and that modifications and other implementations are intended to be included within the scope of the appended claims. Furthermore, while the above description and accompanying drawings describe example implementations in terms of particular example combinations of elements and / or functions, it will be understood that different combinations of elements and / or functions can be provided in alternative implementations without departing from the scope of the appended claims. In this regard, for example, combinations of elements and / or functions other than those explicitly described above may also be construed as being set forth in some of the appended claims. Although specific terms are employed herein, they are used in a generic and descriptive sense only and are not intended to limit the invention.

Claims

1. A portable detection device for determining the stability state of a vessel, comprising: (A) one or more motion sensors that detect motion data of the vessel; (B) one or more freeboard sensors that determine the freeboard of the vessel; and (C) a computing system, comprising: (a) converting the motion data from time domain motion data to frequency domain motion data; (b) processing the frequency domain motion data to determine at least one stability measure for the vessel; (c) a portable sensing device including a computing system programmed to determine the stability state of the vessel from the stability rating and the freeboard.

2. The portable sensing device of claim 1 , wherein the computing system is programmed to determine a roll period of the vessel from the frequency domain motion data.

3. The portable sensing device of claim 1 , wherein the computing system is programmed to determine the vessel's centering height from the frequency domain motion data.

4. The portable sensing device of claim 1 , including a housing that houses the one or more motion sensors, the housing configured to be removably mounted to a marine vessel.

5. 10. The portable sensing device of claim 1, including an interface for receiving one or more inputs of vessel specific information.

6. 2. The portable sensing device of claim 1, wherein the computing system is programmed to convert a roll period to a centering height of the vessel.

7. The portable sensing device of claim 1 further comprising a display for displaying at least one of the vessel's roll period and the vessel's centering height.

8. 8. The portable sensing device of claim 7, wherein the display is programmed to display one or more of average or maximum pitch and roll amplitude over time.

9. The portable sensing device of claim 7 , wherein the display is configured to display the stable state.

10. 10. The portable sensing instrument of claim 9, wherein the display is configured to display the steady state on a graph of freeboard versus roll period.

11. 10. The portable sensing device of claim 9, wherein the display is configured to indicate the stable state using one or more status lights.

12. 10. The portable sensing device of claim 1, wherein the computing system is programmed to determine the stability state of the vessel using displacement data received by the computing system from the one or more freeboard sensors.

13. 1. A method for determining a stable state of a vessel, comprising: one or more motion sensors for detecting motion data of the vessel; and a computing system for processing the motion data from the one or more motion sensors to determine a roll period of the vessel, the method comprising: generating an initial indication of the roll period of the vessel; determining a freeboard of the vessel; determining a stable state of the vessel from the roll period and the freeboard.

14. 14. The method of claim 13, wherein the time to generate the early indicator is less than 5 minutes.

15. 14. The method of claim 13, wherein generating the initial indication of the roll period of the vessel comprises converting, by the computing system, the motion data from time domain motion data to frequency domain motion data; and processing, by the computing system, the frequency domain motion data to determine at least one stability assessment of the vessel.

16. 14. The method of claim 13, including plotting the steady state as a graph of freeboard versus roll period.

17. 14. The method of claim 13, including indicating the stable state using one or more status lights.

18. 1. A method for determining at least one stability measure for a vessel, the method comprising: one or more motion sensors for detecting motion data of the vessel; and a computing system for processing motion data from the one or more motion sensors to determine a roll period of the vessel, the method comprising: generating an indication of the roll period of the vessel; and verifying the accuracy or precision of the detected roll period; determining the at least one stability rating of the vessel from the roll period.

19. 20. The method of claim 18, wherein generating the indication of the roll period of the vessel comprises converting, by the computing system, the motion data from time domain motion data to frequency domain motion data; and processing, by the computing system, the frequency domain motion data to determine the roll period of the vessel.

20. 20. The method of claim 18, comprising determining a freeboard of the vessel and determining a stable state of the vessel from the roll period and the freeboard.

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