A method for monitoring and notifying a group of offshore floating wind platforms

Abstract

The present disclosure provides a method and system for monitoring and reporting the status of a group of floating platforms, such as offshore floating wind platforms, by using the motion of the floating platforms in the group to detect one or more anomalies and identify one or more faults (including irregularities) in the group. Inputs for the method may include wind speed, and wind turbine nacelle direction and orientation information. The platform orientation may complement the orientation of the wind turbine nacelle on the platform if the platform is equipped with a turret. Faults include, but are not limited to, broken mooring lines, moving drag anchors, other issues with mooring system components such as fairleads, issues with the floater ballast configuration, issues with the turret (if any), issues with the nacelle swivel, issues with the rotor, and issues with the blades.

Description

[Technical field]

[0001] (CROSS REFERENCE TO RELATED APPLICATIONS) Not applicable.

[0002] STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT Not applicable.

[0003] (See Appendix) Not applicable.

[0004] FIELD OF THEINVENTION The present disclosure relates generally to groups of floating platforms and, more particularly, to monitoring and reporting the status of a group of floating platforms based on evaluation of the group to detect faults. [Background technology]

[0005] The detection of mooring line breakage is primarily done by monitoring the tension of the lines individually. A technique developed to look at the vessel position for given environmental conditions and direction. The known position of the vessel is compared to the predicted position by a numerical model for the same environmental conditions and direction. The vessel position is totally different in an intact line condition compared to one with a broken line. The method requires monitoring the vessel position and the environmental conditions. The measured position and environmental conditions must be perfectly synchronized for the method for accuracy, otherwise the area the vessel can reach in a harsh environment may overlap with the area it can reach in a calm environment with a broken mooring line.

[0006] A recently filed application uses the vessel's period at a given vessel position to determine mooring line breakage. An intact line condition and a severed line have different stiffness of the system and therefore different vessel period. This approach only requires monitoring the vessel's position and does not require monitoring of environmental conditions and individual monitoring of mooring line tension.

[0007] A recently filed application uses the hull yaw angle along with the hull roll and / or pitch angles at a given hull location to determine a mooring line break. For most floating platforms, the hull yaw, roll and pitch angles are the vessel's yaw, roll and pitch angles. For turret-moored FPSOs, the hull yaw, roll and pitch angles are the turret body's yaw, roll and pitch angles. The hull yaw angle will be quite different for intact and severed line conditions.

[0008] A need remains for a group of platforms to provide a predictable monitoring and notification method for identifying one or more non-compliant platforms. Summary of the Invention

[0009] The present disclosure provides a method and system for monitoring and reporting the status of a group of offshore floating platforms, such as a group of offshore floating wind platforms, by using the positions of the floating platforms in the group, and detecting one or more anomalies that can be used to identify one or more faults (including irregularities) in the group. The monitoring can use platform motion, which can include translational or rotational motion of the platform and components coupled to the platform, such as the wind turbine and wind turbine nacelle. Using multi-source data can improve the detection of anomalies and the identification of types of faults in the offshore floating platforms. Inputs for the method can include information of environmental conditions, such as wind speed and direction, such as estimated or from instruments, such as anemometers, as well as the orientation of the wind turbine nacelle, and the speed and direction of the water current. The orientation of the platform can be supplemented with the orientation of the wind turbine nacelle of the wind turbine on the platform, if the platform is equipped with a turret. Faults include, but are not limited to, broken mooring lines, movement of drag anchors, other problems with mooring system components such as fairleads, problems with the floater ballast arrangement, problems with the turret (if present), problems with the nacelle swivel, problems with the rotor, and problems with the blades.

[0010] The present disclosure provides a method for monitoring and notifying a group of selected floating platforms, the method including: a. selecting a time window for the group of selected floating platforms to determine the presence of one or more anomalies within the group; b. determining at least one value of at least one variable of platform motion of the selected floating platforms for the selected time window; c. comparing the at least one value of the at least one variable of platform motion of one of the selected floating platforms with the at least one value of the at least one variable of platform motion of the other selected floating platforms to determine whether the at least one value for the one platform is within a determined distribution of the at least one value for the other selected floating platforms; d. repeating step (c) for other selected floating platforms in the group; and e. identifying any selected floating platforms having values ​​outside the determined distribution as outlier platforms.

[0011] The present disclosure also provides a method for monitoring and notifying a group of selected buoyant platforms, the method including: a. selecting a time window for the selected buoyant platforms to determine the presence of one or more anomalies in the group; b. calculating at least one value of at least one variable of platform motion of the selected buoyant platforms for the selected time window; c. providing a value of at least one environmental condition of the selected buoyant platforms; d. arranging the selected buoyant platforms in a relative order to establish a relative position based on the value of the at least one environmental condition; e. comparing the at least one value of the at least one variable of platform motion of one of the selected buoyant platforms with the at least one value of the at least one variable of platform motion of the other selected buoyant platforms with respect to the relative position based on the value of the at least one environmental condition to determine whether the at least one value for the one platform is within a determined distribution of the at least one value for the other selected buoyant platforms; f. repeating step (e) for other selected buoyant platforms in the group; and g. identifying any selected buoyant platforms having a value outside the determined distribution as an outlier platform.

[0012] The present disclosure further provides a system for monitoring and notifying a group of selected floating wind platforms having known positions at a baseline state, the system comprising: a. selecting a time window for the group of selected floating platforms to determine the presence of one or more anomalies in the group; b. calculating at least one value of at least one variable of platform motion of the selected floating platforms for the selected time window; c. comparing the at least one value of the at least one variable of platform motion of one of the selected floating platforms with the at least one value of the at least one variable of platform motion of the other selected floating platforms to determine whether the at least one value for the one platform is within a determined distribution of the at least one value for the other selected floating platforms; d. repeating step (c) for other selected floating platforms in the group; and e. identifying any selected floating platforms having values ​​outside the determined distribution as outlier platforms. [Brief description of the drawings]

[0013] [Figure 1] FIG. 2 is a schematic diagram of an exemplary flow chart of one embodiment of the present invention for detecting a fault; [Diagram 2] FIG. 2 is a schematic diagram of an exemplary flow chart of a more specific embodiment of the present invention for detecting anomalies. [Diagram 3] FIG. 1 is a schematic plan view of a group of floating platforms exposed to wind variations and anomalies. [Figure 4A] FIG. 2 is a schematic plan view of an example of a group of floating platforms. [Figure 4B] FIG. 2 is a schematic plan view of an example forward and downstream platform with illustrated horizontal wind reducers. [Figure 4C]FIG. 2 is a schematic side view of an example forward and downstream platform with illustrated vertical wind reductions. [Diagram 5] 1 illustrates an example of a computing system in which steps are performed to monitor a group of floating platforms, such as offshore floating wind platforms, to detect anomalies within the group, according to disclosed embodiments. [Figure 6] 1 illustrates an exemplary server that may be used as one of one or more servers on a computing network. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0014] The drawings above and the following written description of specific structures and functions are not presented to limit the scope of applicant's invention or the scope of the appended claims. Rather, the drawings and written description are provided to teach one of ordinary skill in the art how to make and use the invention for which patent protection is sought. Those skilled in the art will appreciate that not all features of a commercial embodiment of the invention are described or illustrated for clarity and understanding. Those skilled in the art will also appreciate that the development of an actual commercial embodiment incorporating aspects of the present disclosure will require numerous implementation-specific decisions to achieve the developer's ultimate goals for the commercial embodiment. Such implementation-specific decisions may include, but are not limited to, compliance with system-related, business-related, government-related, and other constraints that may vary by particular implementation, location, or over time. While the developer's efforts may be complex and time-consuming in the absolute sense, such efforts would be a routine undertaking for one of ordinary skill in the art having the benefit of this disclosure. It should be understood that the invention disclosed and taught herein is susceptible to numerous and varied modifications and alternative forms. The use of singular terms, such as, but not limited to, "a", is not intended to limit the number of items. Furthermore, various methods and embodiments of the system can be included in combination with each other to produce variations of the disclosed methods and embodiments. Discussion of a singular element can include a plurality of elements and vice versa. Reference to at least one item can include one or more items. Also, various aspects of the embodiments can be used in conjunction with each other to achieve the understood goals of the present disclosure. Unless the context requires otherwise, the term "comprise" or variations such as "comprises" or "comprising" should be understood to mean the inclusion of at least the stated elements or steps or groups of elements or steps or equivalents thereof and not the exclusion of a larger quantity or any other elements or steps or groups of elements or steps or equivalents thereof. A device or system may be used in several directions and orientations.Directional terms such as "top", "up", "upward", "bottom", "down", "downward" and the like are used to indicate orientation relative to the figures and their illustrated orientations, and are not absolute relative to a fixed reference such as the earth in commercial use. Terms such as "inner", "inwardly", "inside" and the like refer to a direction toward a central portion of an assembly or component, such as a longitudinal centerline of the assembly or component, and terms such as "outer", "outwardly", "external" and the like refer to a direction away from the central portion of the assembly or component. The terms "coupled", "couple", "coupler", and similar terms are used broadly herein and may include any method or device for, for example, mechanically, magnetically, electrically, chemically, operatively, directly or indirectly, fixing, coupling, adhering, fastening, attaching, joining, inserting therein, forming on or within, communicating with, or otherwise associating one or more parts of a member with an intermediate element, and may further include, without limitation, integrally forming one functional member with another functional member in a unitary manner. Coupling may occur in any direction, including rotational direction. The order of steps can occur in various orders unless specifically limited. Various steps described herein can be combined with other steps, the steps described can be interleaved, and / or split into multiple steps. Similarly, elements are described functionally and can be embodied as separate components or combined into components having multiple functions. Some elements are named by device names for simplicity and will be understood to include systems of related components that are known to those skilled in the art and may not be specifically described. Various examples are provided in the description and figures that perform various functions and serve as exemplary structures that are non-limiting in shape, size, and description but may vary as known to those skilled in the art given the teachings contained herein. Thus, the use of the term "exemplary" is the adjective form of the noun "example," and similarly refers to exemplary structures, not necessarily preferred embodiments.Element numbers with a letter suffix such as "A", "B", or numbers with a prime, double prime, etc., such as 1, 1', 1'', are intended to designate different elements within a group of similar elements having similar structure or function, while corresponding element numbers without a letter are intended to generally refer to one or more similar elements. Because several embodiments are disclosed that use various element numbers for similar elements, any element numbers in the claims that correspond to elements disclosed in this application are exemplary and not exclusive.

[0015] The present disclosure provides a method and system for monitoring and reporting the status of a group of floating platforms, such as a group of offshore floating wind platforms, by using the positions of the floating platforms in the group, and detecting one or more anomalies that can be used to identify one or more faults (including irregularities) in the group. Monitoring can use platform motion, which can include translational or rotational motion of the platform and components coupled to the platform, such as the wind turbine and wind turbine nacelle. Platform motion is defined herein to include variables such as surge, sway, heave, yaw, roll, and pitch; orientation of the wind turbine nacelle coupled to the platform; structural response and sound characteristics from the movement of the platform or components, including frequency and intensity; power output of the wind turbine, rotor performance of the wind turbine, and other variables of the platform motion. Using multi-source data can improve the detection of anomalies and identification of types of faults in offshore floating wind platforms. Inputs for the method can include information on environmental conditions, such as wind speed and direction, such as estimated or from instruments such as anemometers, as well as the orientation of the wind turbine nacelle, and the speed and direction of water currents. The orientation of the platform may complement the orientation of a wind turbine nacelle of a wind turbine on the platform if the platform is equipped with a turret. Faults (defined to include irregularities) may be, for example, but are not limited to, broken mooring lines, movement of drag anchors, other issues with mooring system components such as fairleads, issues with floater ballast configurations, issues with the turret (if present), issues with the nacelle swivel, issues with the rotor, and issues with the blades.

[0016] A combination of expert systems and iterative approaches can be used to implement the detection system described herein. Detection of anomalies can utilize artificial intelligence (AI) such as, but not limited to, artificial neural networks (ANNs), expert systems and fuzzy logic, and / or other numerical algorithms for pattern recognition and classification. Machine learning or ANNs can be trained with examples of normal and abnormal patterns for the model to recognize, classify, and identify specific patterns. These training patterns can be generated using simulations and can be combined with measurement data. The patterns are presented as ANN inputs, which can be in the form of statistics of platform motion. The ANN output can provide identification of specific patterns and provide an estimated accuracy factor. A set of rules can be constructed to define normal and abnormal patterns along with associated faults. Different types of anomalies can be included. The rules and criteria that define normal and abnormal patterns can be formed as a function of statistics of platform motion. This set of rules can be used as a backbone to define a knowledge-based system and develop an expert system. Fuzzy logic can be used to interpret the results of various models and algorithms to improve the confidence level of the predictions of the monitoring system. An iterative approach can be used to evaluate values ​​including trends of platform motion statistics for multiple platforms. Each iteration can attempt to identify a platform that is considered an outlier platform, and the iteration can be stopped when convergence of identified platforms that are considered to be outlier platforms occurs within a defined acceptable variance. The determination of the platform that is considered to be an outlier platform in each iteration can be based on an evaluation of the value of a measurement variable of interest, such as a platform motion statistics.

[0017] The method may have one or more of the following advantages. One or more of the platform movements may be derived from its position, which may be monitored by the Global Positioning System (GPS) or other position determining technology. Post-processing techniques of the monitored data to obtain the desired variables are standard practice. This approach does not require monitoring of environmental conditions and can use estimates. The computer programs for the surveillance system can run on a standard computer. The program can be executed in the cloud, away from the platform, with data transmitted to the cloud. Fault identification can be done in near real time. The monitoring tool may be in a protected area that is generally not exposed to seawater or sea spray.

[0018] FIG. 1 is a schematic diagram of an exemplary flow chart of an embodiment of the present invention for detecting faults. FIG. 3 is a schematic plan view of a group of floating platforms exposed to wind fluctuations and anomalies. Advantageously, the group 2 of floating platforms has similar response characteristics to environmental condition variables such as wind direction and speed, and waves and currents. For illustrative purposes, wind platforms and components such as nacelles are described herein, but it should be understood that the principles are applicable to other types of floating platform groups. In general, iterative techniques in combination with expert systems can be used to implement processes and associated systems for detecting anomalies and identifying faults in a group of floating platforms.

[0019] 1 and 3, process 1 may begin with identifying a group of floating platforms 2, such as a group of offshore floating wind platforms known as wind farms. Other examples of groups of floating platforms may be hydrocarbon floating platforms and FPSOs. For purposes of illustration herein, an example of a group of offshore floating wind platforms is described, and reference is made to specific features such as wind turbine nacelles where applicable, however, it should be understood that similar steps may be performed on groups of other types of floating platforms, which may be characterized with attributes of each group.

[0020] A group of floating platforms may have one or more forward platforms 8 that are upstream of the other platforms at a given time. Each floating platform may have one or more types of platform motion. Some platform motions may be affected by environmental conditions, such as average wind direction 24 relative to a reference 38, such as compass north N. The first stage downstream platform 10 is downstream of the forward platform 8, the second stage downstream platform 14 is downstream of the first stage downstream platform 10, the third stage downstream platform 16 is downstream of the second stage downstream platform 14, the fourth stage downstream platform 22 is downstream of the third stage downstream platform 16, and so on. The platforms may each have an initial position 32 that may form a baseline from which other measurements may be taken. The platforms may have respective motions, such as being offset from the initial position 32 by a distance 6 to an expected position 34 having a heading 4. If one or more of the platforms are outside of the expected range by heading 4' or distance 6' or both, the platform may be identified as an outlier platform 18 at an outlier position 36, as described in further detail herein.

[0021] In at least one embodiment, the steps generally comprise: initiating a process for a group of selected platforms for a selected time window; determining (by providing and / or calculating) at least one value of one or more variables of platform motion for a selected platform for a selected time window; comparing one or more values ​​of the variables for the platforms to determine one or more platforms that are considered outlier platforms, optionally taking into account in the comparison the relative upstream and / or downstream location of the platforms, which may factor in one or more environmental conditions; Optionally, using the values ​​of the variables to identify specific faults, if any, of a platform that is deemed an outlier platform; and Optionally, repeating the process for another time window.

[0022] In step 20, a time window for relating variables of platform motion, and potentially other parameters, is selected for performing the analysis described herein. The time window may be past time, actual time, or delayed time, a period of time, or in some embodiments, a moment in time.

[0023] In step 25, values ​​for one or more variables related to platform motion for the selected group of platforms may be determined for the group of platforms at that time. In general, it is expected that some of the values ​​will include values ​​of variables related to the position of the platform and its coupled components in the x-axis and y-axis, and in some embodiments the z-axis, as shown in Figures 4B-4C. Values ​​generated directly from available estimated or measured data may be referred to herein as "direct values". The direct values ​​may be analyzed using statistical calculations to further evaluate the platform motion and generate statistics. One or more values ​​may exist for each variable determined at a given time. For example, the offset direction 4 of the platform motion shown in Figure 3 may be established as a direct value for each selected platform relative to a fixed reference 38, such as compass direction N, or a reference that may be available during a given time window in step 20, such as average wind direction 24. Statistical values ​​of the offsets, such as group average offset 26, may be established as a result of the individual platform direct values. Additionally, remote monitoring, such as obtained through image recognition at different times, may indicate different positions of the platform, nacelle, and other structures that have changed through the intervening platform motion. Statistics of platform motion may include, but are not limited to, mean, median, and modal mean, standard deviation, RMS, period (low frequency period, zero crossing period), and other statistical permutations including trends of such variables.

[0024] In step 45, the values ​​of the variables for each of the selected platforms may be compared to the values ​​of the variables for the other selected platforms, either individually or as a group, optionally taking into account the relative position of the platform within the group. A platform having its value (direct or statistical) comparison that is outside of an acceptable variance may be identified as an outlier platform 18. For example, an outlier platform may have a different offset direction 4', a different offset distance 6', a different nacelle orientation (not shown), and / or other anomalies compared to other platforms in the group of platforms that may indicate a fault compared to the other platforms. This evaluation may also use an artificial intelligence (AI) based evaluation, such as fuzzy logic. The monitoring or evaluation of any anomalies of each variable between the platforms may be done in near real time, and the evaluation is also available in near real time.

[0025] Once any platform is determined as an outlier platform in step 60, the process can be used to help identify a particular fault depending on the applicable variables, including the trend of the variables that caused the identification of the outlier platform. In some determinations, individual variables can be used, and in other determinations, known combinations of variables can be used to indicate one or more identifiable faults. The identification can also be based on a comparison with a library of anomaly signatures having associated faults. The library of anomaly signatures can be generated prior to deployment of the platform using simulations that encompass potential faults, and the library can be updated with the actual behavior and response of a particular platform or group of platforms. A set of rules and criteria can be used to detect, recognize, and identify types of anomalies having one or more associated faults based on the constructed library of anomaly signatures. The process can indicate the identified potential faults and can include a confidence index, such as a percentage, for the accuracy of the identified faults.

[0026] At step 65, the process may be considered complete for the selected time window in the evaluation. Further evaluation of the group of buoyant platforms in the next selected time window may begin by returning to step 20.

[0027] 2 is a schematic diagram of an exemplary flow chart of a more specific embodiment of the present invention for detecting anomalies. The flow chart uses aspects from the flow chart of FIG. 1 and provides variations, further details, and / or additional steps. For example, steps 20 and 25 of FIG. 2 are at least similar to steps 20 and 25 described with respect to FIG. 1.

[0028] In step 30, an iterative sequence begins which may include data estimation and convergence.

[0029] In step 35, one or more values ​​for one or more environmental conditions, such as wind direction, wind speed, water current direction, and / or water current velocity, may be provided by estimated or actual values ​​obtained through instrument data or other measurements. Environmental conditions for which values ​​are provided from estimated or measured data are considered herein as evaluated environmental conditions. The evaluated environmental conditions may be used as a basis for arranging platform orders, data comparison and convergence, and other uses. For example, estimated wind direction 24 (average or other statistical value) may be an evaluated environmental condition as an estimated average wind direction for a group of platforms 2. Wind speed may also be estimated as another evaluated environmental condition. The direction 4 and distance 6 of the offset of the selected platform may be measured from the platform's location via GPS or other means. In some systems, remotely accessible information on wind speed and direction may be obtained from instruments such as anemometers on the wind turbine nacelle 12 (shown in Figures 4B-4C). In areas with significant water currents, water current environmental conditions such as direction and / or speed may be estimated, but measurements may also be used if those measurements are also available. Remotely accessible information regarding the orientation of the wind turbine nacelle 12 may also be obtained. In at least one embodiment, the platform offset direction, wind speed and direction information, and / or the orientation of the wind turbine nacelle may be used to estimate one or more environmental conditions affecting the platform, and in some embodiments, the distance of the platform from an initial platform position may be used to estimate speed.

[0030] In step 40, the platforms in the group may be arranged in a relative order, such as an upstream and downstream sequence, based on one or more values ​​(estimated or measured) of one or more assessed environmental conditions, such as direction. The relative order may be from the forward platform to the downstream most platform. In at least one embodiment, arranging the relative order may be useful because the theoretically or empirically determined position and orientation of a platform or component is influenced by the order of the platform relative to other platforms in the group. Variables such as downwind effect, turbulence, progressive reduction in energy, and other variables affect the wind and tidal currents that pass through and interact with other floating platforms in the group, thus affecting one or more of the platform motions. The sequence of platforms may be arranged in a relative order based on criteria such as the distance and direction of a particular platform position relative to the environmental conditions in a particular time window selected for analysis, compared to the platform's position in one or more baseline environmental conditions. Other criteria are possible.

[0031] FIG. 4A is a schematic plan view of an example of a group of floating platforms. FIG. 4B is a schematic plan view of an example of a forward platform and a downstream platform with horizontal wind reducers illustrated. FIG. 4C is a schematic side view of an example of a forward platform and a downstream platform with vertical wind reducers illustrated. To illustrate the above-mentioned effects on the downstream platform that may change the performance and position of the downstream platform, FIGS. 4A-4C use a similar concept applied to water currents to represent the wind downwind from the platforms affecting the downstream platform relative to the downstream platform's position. The forward platforms 8A, 8B, and 8C (generally 8) generally have no upstream downwind affecting them. The nacelle 12 can be aligned with the wind direction and have the maximum wind thrust under normal operating conditions unhindered by other platforms. However, the forward platform 8 generates downstream downwind 28A-28C (generally 28). A set of first stage downstream platforms 10A and 10B (generally 10) receive the downwind 28 of the forward platform 8 as the second line of platforms. The leeward wind 28 generally reduces wind speed on the downstream platform 10 and can change wind direction caused by interference from the leeward wind 28 from the forward platform 8. Depending on the relative positions, the first stage downstream platform 10 may be subjected to leeward winds from two or more forward platforms, such as leeward winds 28A and 28B from forward platforms 8A and 8B, respectively, overlapping on the first stage downstream platform 10A. Similarly, the second stage downstream platform 14 is subjected to influences from leeward winds 30A-30B (generally, 30) from the first stage downstream platform 10 and residual influences of the leeward winds 28 of the forward platform 8 after passing the platform 10. Any platform downstream of the platform 14 is subjected to influences from leeward winds 32A-32C (generally, 32) of the platform 14 and residual influences of the upstream leeward winds 28 and 30.

[0032] More specifically, in at least one embodiment, ordering may be accomplished in the following example steps, with reference to Figures 4A-4C, with the understanding that other ordering methods are available and other environmental conditions may be the basis for ordering. For each platform i in the group, an in-line axis X perpendicular to the evaluated environmental conditions, such as wind direction 24 shown in FIG. 4A i and the horizontal axis Y i To determine, For each platform j downstream of platform i, calculating the inline distance x(ij) and lateral distance y(ij) between platform i and platform j, and the wind direction for platform i; Calculating a reduction factor of the flow velocity of each platform j due to platform i using an existing downwind model based on the inline distance x(ij) and the lateral distance y(ij); and Calculate wind speed coefficient=1.0-reduction coefficient, where the reduction coefficient is 0 for platform j that is not downwind of platform i, and therefore the wind speed coefficient is equal to 1.0 (although it should be understood that other baseline numbers other than 1.0 may be used).

[0033] Leeward is a region of flow that is disturbed as the fluid passes over a solid. As used herein, the reduction factor of flow velocity relative to the free stream flow velocity includes any factor of the leeward effect, velocity deficit, and velocity reduction factor as known in the art. After completing the above steps for each of the selected platforms, the following steps may be performed. · To calculate the total wind speed coefficient for each of the selected platforms to take into account the downwind effect of each of the selected platforms. Arranging the selected platforms in a relative order such as from the platform with the highest total wind speed coefficient to the platform with the lowest total wind speed coefficient. In-line distance for two or more platforms with the same total wind speed coefficient

[0034]

number

[0035]

number

[0036] In step 45, one or more values ​​of one or more variables of platform motion for each selected platform may be compared to corresponding values ​​of other platforms in the group or aggregate values ​​of the group, taking into account the relative position of the platform with respect to the evaluated environmental conditions, to determine any platforms that are considered outliers. The values ​​may include direct values ​​and / or statistical values, including trends of the variables that may be calculated using the direct values. Although the values ​​are generally numerical, non-numerical values ​​may be used to evaluate different variables, and thus the values ​​are not limited to numerical values. Anomalies in the values ​​of each variable among multiple nearby platforms may indicate group failure. The monitoring or evaluation of anomalies (if any) of one or more of the variables among multiple nearby platforms may be performed in near real time, and the evaluation may also be available in near real time. If the value of the variable of the selected platform is not within the acceptable variance of the values ​​of the other platforms, the selected platform is considered a potential outlier platform. The process may be repeated for each of the variables and each of the selected platforms.

[0037] In at least one embodiment, direct and / or statistical values ​​of variables of motion of the platform may be compared to other platforms using estimates of one or more of the environmental conditions (including the derivation of the environmental conditions) in step 35, and downwind effects, if any. Thus, the relative position of the platform in the order based on the estimated environmental conditions determined in step 40 may be taken into account in the comparison.

[0038] In another embodiment, the comparison in step 45 may include two secondary steps of comparing. One secondary step of comparing may include comparing measurements (direct values ​​and / or statistical values) of one or more variables from step 25 for each of the selected platforms with corresponding values ​​of such variables in the other selected platforms. The other secondary step may include comparing measurements of one or more variables for each of the selected platforms with estimated values ​​of such variables for such platforms, where the estimated values ​​may be based on one or more environmental conditions. The values ​​of the one or more environmental conditions may be estimated values.

[0039] Step 50 can be used to determine whether there is convergence of the identification of outlier platforms by comparing the results of the values ​​of multiple variables of platform motion between the selected platforms, including results based on environmental conditions (measured or estimated). If the value is a measurement, then there is likely convergence for that variable and the process can proceed to step 60 described below. This step can be particularly useful if the value is an estimate or is derived from estimates such as environmental conditions such as wind direction and / or speed, or water current direction and / or speed. In such estimates, a lack of convergence may indicate that the estimate of the environmental conditions needs to be refined in another iteration, which may change the simulated values ​​for the platform motion and therefore the amount of convergence that would benefit from another iteration, discussed in step 55 below. For the convergence analysis, the potential outlier platforms identified for each variable can be compared to the potential outlier platforms identified for the other variables. If the same platform is identified as an outlier platform for multiple variables within the acceptable variance, this part of the process is considered to have converged and the anomaly that identified these one or more platforms as an outlier platform is most likely indicative of an actual fault.

[0040] In step 55, if the same platform is not identified in multiple iterations within the acceptable variance (particularly when using estimates of certain variables), the process returns to previous step 35 and performs another iteration with different inputs for at least one of the variables, such as one or more environmental conditions, ordering the platforms and comparing values, as described above, until the identification of the outlier platform converges to within the acceptable variance.

[0041] Once any platform is determined to be an outlier platform in step 60, the process attempts to identify a fault depending on the applicable variables and the values ​​of the variables that caused the platform to be identified as an outlier platform. For example, the identification may be determined based on a known or predicted combination of variables that may indicate at least one particular fault. As another example, the determination may be based on a comparison of an anomaly signature of the fault to a library of anomaly signatures. The library of anomaly signatures may be generated prior to deployment of the platform using simulations that encompass potential faults. This library may be updated with the actual behavior and response of a particular platform or a group of platforms. A set of rules and criteria may be used to detect, recognize, and identify the type of fault based on the constructed library of anomaly signatures. The process may indicate potential faults and may include a confidence index, such as a percentage, regarding the accuracy of the identified fault.

[0042] At step 65, the process may be considered complete for the selected time window of evaluation. Further evaluation of the group of buoyant platforms in another selected time window may be initiated by returning to step 20.

[0043] FIG. 5 illustrates an example of a computing system in which a step of monitoring a group of floating platforms, such as offshore floating wind platforms, to detect anomalies within the group of platforms is performed according to the disclosed embodiments. As can be seen, the system can include at least one user processing device 102 that can be connected to a network 106 via a network connection 104. In this example, the user processing device 102 can be a desktop computer, a notebook computer, a tablet, a smartphone, and other processing devices, and the network connection 104 can be a wired and / or wireless network connection. Alternatively, the processing device 102 can be a stand-alone system that does not interface with a network or network server. One or more network servers 108 can be connected to the network 106 using at least one database 110, which can be either an internal database residing within the network server 108 or a database residing in a location physically separate from the network server 108 (as shown herein), depending on the constraints (e.g., size, speed, etc.) of a particular implementation. It should be noted that the term "server" is used herein to include traditional servers as well as high-end computers, workstations, mainframes, supercomputers, and the like. Similarly, the at least one database 110 may be a relational database, an operational database, or other suitable database capable of storing data and information, including rules and criteria for defining normal and abnormal patterns with potential associated faults of the floating platform, as well as training examples for expert systems, pattern recognition, analysis results, and other data relevant to the processes described herein.

[0044] FIG. 6 illustrates an exemplary server that may be used as one of the one or more servers 108 on the computing network 106. As previously mentioned, the server 108 may be any suitable data processing system known to those skilled in the art, including high-end servers, workstations, mainframes, supercomputers, and the like. Such a server 108 typically includes a bus 128 or other communication mechanism for transferring information within the server 108, and a CPU 112 coupled to the bus 128 for processing information. The server 108 may also include a main memory 114, such as a random access memory ("random access memory, RAM") or other dynamic storage device coupled to the bus 128 for storing computer-readable instructions to be executed by the CPU 112. The main memory 114 may also be used to store temporary variables or other intermediate information during execution of instructions to be executed by the CPU 112. The server 108 may further include a read only memory ("read only memory, ROM") 116 or other static storage device coupled to the bus 128 for storing static information and instructions for the CPU 112. A computer-readable storage device 118 , such as a magnetic disk, optical disk, or solid-state memory device, may be coupled to bus 128 for storing information and instructions for CPU 112 .

[0045] The term "computer-readable instructions" as used above refers to any instructions that may be executed by the CPU 112 and / or other components. Similarly, the term "computer-readable medium" refers to any storage medium that may be used to store computer-readable instructions. Such media may take many forms, including but not limited to non-volatile media, volatile media, and transmission media. Non-volatile media may include, for example, optical or magnetic disks, such as the storage device 118. Volatile media may include dynamic memory, such as the main memory 114. Transmission media may include coaxial cables, copper wire, and fiber optics, including the wires of the bus 128. The transmission itself may take the form of sound or light waves, such as those generated during radio frequency ("radio frequency" ("RF") and infrared ("IR") data communications. Common forms of computer readable media may include, for example, a floppy disk, a flexible disk, a hard disk, a magnetic tape, other magnetic media, a CD-ROM, a DVD, other optical media, RAM, a PROM, an EPROM, a FLASH EPROM, other memory chips or cartridges, or any other medium from which a computer can read.

[0046] The CPU 112 may also be coupled via a bus 128 to a display 120 for displaying information to a user. One or more input devices 122, including alphanumeric and other keyboards, a mouse, a trackball, cursor direction keys, and the like, may be coupled to the bus 128 for communicating information and command selections to the CPU 112. The network interface 124 provides two-way data communication between the server 108 and other computers via the network 106. In one example, the network interface 124 may be an integrated services digital network ("ISDN") card or a modem used to provide a data communication connection to a corresponding type of telephone line. As another example, the network interface 124 may be a LAN card used to provide a data communication connection to a compatible local area network ("LAN"). Wireless links may also be implemented via the network interface 124. In brief, the primary function of the network interface 124 is to send and receive electrical, electromagnetic, optical, or other signals that carry digital data streams representing various types of information.

[0047] According to the disclosed embodiments, an application 126, or rather computer readable instructions therefor, for monitoring a group of floating platforms to detect anomalies within the platforms may also reside on the storage device 118. The computer readable instructions for the application 116 may then be executed by the CPU 112 and / or other components of the server 108 to detect faults within the platforms. Such an application 126 may be implemented using any suitable application development environment and programming language known to those skilled in the art to perform the steps of the algorithms disclosed and described herein. As mentioned above, in various embodiments, the application 126 may be a standalone application that may be executed independently of other applications, or may be in the form of a plug-in module to an existing software package, or the like.

[0048] Other and further embodiments may be devised that utilize one or more aspects of the invention described above without departing from the spirit of Applicant's invention. For example, as discussed above, using simulations and actual data to train an artificial intelligence model can be used to determine actual downwind effects and short / medium term production performance of a wind turbine or a group of wind turbines or other platforms. As other examples, other types of geo-location devices, various equipment such as alarms, software for remote sensing, dedicated software linked to a control system, etc. may be used to enhance the operation and notifications of the monitoring system, and other variations may occur while remaining within the scope of the claims.

[0049] The present invention has been described in the context of preferred and other embodiments, and not all embodiments of the present invention are described. Obvious modifications and changes to the described embodiments are available to those skilled in the art. The disclosed and undisclosed embodiments are not intended to limit or restrict the scope or applicability of the invention devised by the applicant, but rather, in accordance with the patent laws, the applicant intends to fully protect all such modifications and improvements that fall within the scope or range of equivalents of the following claims.

Claims

1. 1. A method for monitoring and notifying a group of selected floating platforms, comprising: a. selecting a time window for the group of selected floating platforms to determine the presence of one or more anomalies within the group; b. determining at least one value of at least one variable of platform motion of the selected buoyant platform for the selected time window; c) comparing the at least one value of the at least one variable of the platform motion of one of the selected floating platforms with the at least one value of the at least one variable of the platform motion of the other selected floating platforms; determining whether the at least one value for the one platform is within a determined variance of the at least one value for the other selected floating platforms; d. Repeating step (c) for other selected floating platforms in the group; e. identifying any selected floating platforms having values ​​outside the determined distribution as outlier platforms; Optionally, the method further comprises repeating step 1(b) for other variables of platform motion.

2. 2. The method of claim 1, further comprising identifying at least one of the specific faults in at least one of the outlier platforms compared to other platforms in the group and / or taking into account the relative geographical location of any selected buoyant platform in determining the selected buoyant platform as an outlier platform.

3. The method of claim 1 , wherein the at least one value of the at least one variable of the platform motion comprises at least one of a direct value or a statistical value of the direct value.

4. The method of claim 1 , wherein the at least one value of the at least one variable of the platform motion of other selected floating platforms comprises a statistical combination of the values ​​for each of the other selected floating platforms.

5. 1. A method for monitoring and notifying a group of selected floating platforms, comprising: selecting a time window for the selected floating platform to determine the presence of one or more anomalies within the group; b. calculating at least one value of at least one variable of platform motion of the selected buoyant platform for the selected time window; c. providing a value for at least one environmental condition of the selected buoyant platform; d. placing the selected buoyant platforms in a relative order to establish relative positions based on the value of the at least one environmental condition; e) comparing the at least one value of the at least one variable of the platform motion of one of the selected buoyant platforms with the at least one value of the at least one variable of the platform motion of the other selected buoyant platforms with respect to the relative position based on the value of the at least one environmental condition to determine whether the at least one value for the one platform is within a determined distribution of the at least one value for the other selected buoyant platforms; f. Repeating step (e) for other selected floating platforms in said group; g. identifying any selected floating platforms having values ​​outside the determined distribution as outlier platforms; Optionally, step (e) comprises: The method further comprising comparing measured values ​​for one or more variables for each of the selected platforms to estimated values ​​for such variables for such platforms, the estimated values ​​being based on one or more environmental conditions, and further optionally, the value of the at least one environmental condition being an estimated value.

6. h. further comprising evaluating convergence in step (g) by comparing results for values ​​of a plurality of variables; and optionally, The method of claim 5, further comprising repeating steps (c) through (h) if the convergence is not within a predetermined acceptable variance with at least different values ​​of the variables.

7. 9. The method of claim 6, further comprising identifying at least one of the particular impairments in at least one of the outlier platforms as compared to other platforms in the group.

8. In step (d), arranging the selected buoyant platforms in the relative order comprises: d.

1. For an initial selected floating platform i, determining an in-line axis and a transverse axis perpendicular to said environmental conditions in step (a); d.

2. The in-line and lateral distances between a selected floating platform i and a platform j downstream of said selected floating platform i; and Calculating the wind direction for the selected floating platform j; d.

3. Calculating at least one reduction factor of the flow velocity of the selected floating platform j due to the selected floating platform i based on the in-line distance and the lateral distance; d.

4. Calculating a wind speed coefficient by subtracting the reduction factor from 1.0; the reduction factor is 0 for platform j that is not downwind of platform i, and the wind speed factor is 1.0; d.

5. Repeating steps (d.2) through (d.4) for each platform j; and d.

6. Repeating steps (d.1) to (d.5) for each selected platform i; d.

7. Calculating wind speed coefficients for each of the selected platforms; 8. ordering the selected platforms into a sequence based on the wind speed coefficient to create the relative ordering of the platforms.

9. 1. A system for monitoring and reporting a group of selected floating wind platforms having known positions at a baseline state, comprising: a. selecting a time window for the group of selected floating platforms to determine the presence of one or more anomalies within the group; b. calculating at least one value of at least one variable of platform motion of the selected buoyant platform for the selected time window; c) comparing the at least one value of the at least one variable of the platform motion of one of the selected buoyant platforms with the at least one value of the at least one variable of the platform motion of other selected buoyant platforms to determine whether the at least one value for the one platform is within the determined distribution of the at least one value for the other selected buoyant platforms; d. Repeating step (c) for other selected floating platforms in the group; e. identifying any selected floating platforms having values ​​outside the determined distribution as outlier platforms; Optionally, the data processing system is further configured to repeat step (b) for other variables of platform motion.

10. The data processing system comprises: The data processing system may further be configured to take into account a relative geographical location of any platform when determining the platform as an outlier platform, the data processing system comprising: The system of claim 9 , further configured to identify at least one of the particular faults in at least one of the outlier platforms relative to other platforms in the group.

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