JP2018034585A - Analysis of propulsion performance of ship - Google Patents
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- 230000002000 scavenging effect Effects 0.000 claims description 12
- 238000012937 correction Methods 0.000 claims description 8
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Abstract
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本発明は船舶の推進性能を解析するための計算機システム、船舶の推進性の解析方法、そのためのプログラム、及び、記録媒体に関する。 The present invention relates to a computer system for analyzing ship propulsion performance, a ship propulsion analysis method, a program therefor, and a recording medium.
船舶の運航支援等のために、船舶の推進性能を解析することが行われている。しかしながら、海気象の影響が大きいため、船舶の運航データから船舶の推進性能を把握しようとしてもこれは困難であった。 Analysis of the propulsion performance of a ship is performed for ship operation support and the like. However, due to the great influence of sea weather, it was difficult to grasp the propulsion performance of the ship from the ship operation data.
そこで、模型による水槽試験、数値流体解析などの物理モデルを用いて理論推進性能を演算し、これを基本データとして、海気象に基づいた補正値を当てはめて、実海域環境下での推進性能を推定することが行われていた（特開2016-78685号公報）。この従来例によれば、船舶の推進性能の推定値は、船舶の実海域航行に於ける実態に近づいたものになることが期待される。 Therefore, the theoretical propulsion performance is calculated using a physical model such as a tank test using a model, numerical fluid analysis, etc., and using this as basic data, a correction value based on sea weather is applied to improve the propulsion performance in an actual sea environment. Estimation has been performed (Japanese Patent Laid-Open No. 2016-78685). According to this conventional example, the estimated value of the propulsion performance of the ship is expected to be close to the actual condition of the ship in actual sea navigation.
しかしながら、物理モデルによる理論推進性能の演算には多大なコストを伴い、さらに、補正値を算出するためには、波や海流を計測する為の機器を新たに装備しなければならないという課題がある。したがって、コストや手間を惜しむあまり、実海域での経年劣化を伴った状態における推進性能を正しく推定できないという懸念がある。 However, the calculation of theoretical propulsion performance using a physical model involves a great deal of cost, and there is a problem that a device for measuring waves and ocean currents must be newly installed in order to calculate a correction value. . Therefore, there is a concern that the propulsion performance in a state accompanied by aging deterioration in the actual sea area cannot be accurately estimated due to excessive cost and labor.
そこで、出願人は、物理モデルや波や海流を計測する為の機器を必要としなくても、船舶の運航における計測値に基づいて船速を推定可能な解析システムを提案した（特開2015-190970号公報）。このシステムは、船舶の運航に係る複数の項目の計測値から、複数の項目間の相関モデルを機械学習によって算出して船速に関連性を有する関連項目を決定し、この関連項目の計測値に基づいて、船速の推定値を算出することを可能にしている。 Therefore, the applicant has proposed an analysis system that can estimate the ship speed based on the measured values in ship operation without requiring a physical model or equipment for measuring waves or ocean currents (Japanese Patent Laid-Open No. 2015-2015). 190970). This system calculates a correlation model between multiple items by machine learning from the measurement values of multiple items related to ship operation, and determines related items that are related to ship speed. Based on the above, it is possible to calculate an estimated value of the ship speed.
この解析システムによれば、船体の構造に起因する外乱や波や風など実海環境に起因する外乱を除いて、船速の推定値を精度よく求めることができる。しかしながら、本発明者が検討したところ、この種の解析システムは、波や風など実海環境に起因する外乱がホワイトノイズの類であれば、これを除去することは可能であるが、外乱が直流成分、又は、周波数を極端に低くする成分、例えば、追い風、又は、向い風等一定の方向から風を受けている場合であると、この外乱による誤差が船速の推定値に組み込まれてしまい、船速の推定値の精度が低下せざるを得ないことが分かった。 According to this analysis system, it is possible to accurately obtain an estimated value of the ship speed, excluding disturbances caused by the structure of the hull and disturbances caused by the actual sea environment such as waves and winds. However, as a result of examination by the present inventor, this type of analysis system can remove a disturbance caused by a real sea environment such as a wave or a wind if it is a kind of white noise. If the DC component or component that makes the frequency extremely low, for example, wind from a certain direction such as tailwind or heading wind, the error due to this disturbance is incorporated into the estimated ship speed. It was found that the accuracy of the estimated ship speed was inevitably lowered.
そこで、本発明は、船舶が実海域において運航されている際に記録されたデータ群に基づいて、船舶の推進性能を精度よく解析できる計算機システム等を提供することを目的とする。 Accordingly, an object of the present invention is to provide a computer system or the like that can accurately analyze the propulsion performance of a ship based on a data group recorded when the ship is operated in a real sea area.
前記目的を達成するために、本発明は、船舶が実海域において運航されている際に記録されたデータ群を格納するメモリと、船舶の推進性能を解析するコントローラと、を備える計算機システムであって、前記コントローラは、前記データ群を利用して、所定の気象環境下における船舶の推進性能の推定値を算出し、海気象の計測値に基いて前記算出された推定値を補正することを特徴とする。本発明は、さらに、船舶の推進性能の解析方法、そのためのプログラム、及び、記録媒体でもある。 In order to achieve the above object, the present invention is a computer system comprising a memory for storing a data group recorded when a ship is operated in a real sea area, and a controller for analyzing the propulsion performance of the ship. The controller calculates the estimated value of the propulsion performance of the ship under a predetermined weather environment using the data group, and corrects the calculated estimated value based on the measured value of the sea weather. Features. The present invention is also a ship propulsion performance analysis method, a program therefor, and a recording medium.
本発明によれば、船舶が実海域において運航されている際に記録されたデータ群に基づいて、船舶の推進性能を精度よく解析できる。 According to the present invention, it is possible to accurately analyze the propulsion performance of a ship based on a data group recorded when the ship is operated in a real sea area.
次に本発明の実施形態を図面を参照しながら説明する。図１に本発明に係る計算機システムのハードウェア構成の一例を示す。この計算機システムは、船舶が実海域において運航されている際に記録されたデータ群を解析して、船舶の推進性能の推定値を算出し、推定値に基づいて船舶の運航を評価するための評価指標を生成する。 Next, embodiments of the present invention will be described with reference to the drawings. FIG. 1 shows an example of a hardware configuration of a computer system according to the present invention. This computer system is used to analyze data groups recorded when a ship is operating in the actual sea area, calculate an estimated value of the propulsion performance of the ship, and evaluate the operation of the ship based on the estimated value. Generate an evaluation index.
計算機システム１００は、コントローラ１０２、メモリ１０４等の周知なハードウェア資源を備えたコンピュータとして構成されている。コントローラ１０２は演算処理手段として機能し、メモリ１０４に記憶されている解析プログラムを実行して、船舶の推進性能に係る計測値に基づいて解析処理を実行する。 The computer system 100 is configured as a computer having known hardware resources such as a controller 102 and a memory 104. The controller 102 functions as arithmetic processing means, executes an analysis program stored in the memory 104, and executes an analysis process based on a measurement value related to the propulsion performance of the ship.
計算機システム１００は、キーボード、スイッチやポインティングデバイス、マイクロフォン等の入力装置１０６と、モニタディスプレイやスピーカ等の出力装置１０８とを備えており、入力装置から各種パラメータを設定したり、出力装置に解析結果を表示することができる。 The computer system 100 includes an input device 106 such as a keyboard, a switch, a pointing device, and a microphone, and an output device 108 such as a monitor display and a speaker. Various parameters are set from the input device, and analysis results are output to the output device. Can be displayed.
メモリ１０４は、時系列に記録されたデータ群を格納する。データ群は、複数の船舶の夫々、そして、複数の航海の夫々に分類されている。船舶、そして、航海はＩＤによって管理される。メモリ１０４は、ハードディスク、フラッシュメモリ等、非一時的な記録媒体を備えている。データ群の記憶領域は計算機システム１００の外部のストレージシステムに存在していてもよい。 The memory 104 stores a data group recorded in time series. The data group is classified into each of a plurality of ships and each of a plurality of voyages. Ships and voyages are managed by ID. The memory 104 includes a non-temporary recording medium such as a hard disk or a flash memory. The storage area of the data group may exist in a storage system outside the computer system 100.
計算機システム１００は、複数のクライアント計算機と情報ネットワークによって接続されるサーバとして構成されてもよい。コントローラ１０２は、複数のクライアント計算機の夫々からデータ群を収集し、これをメモリ１０４に格納してもよい。コントローラ１０２は、各船舶の航海毎に、推進性能の推定値、評価指標等の解析結果をメモリ１０４に記録する。計算機システム１００は、クライアント計算機には接続されない独立システムとして構成されてもよい。さらに、計算機システム１００は、クライアント計算機のデータを保存、管理するデータセンタとして構成されてもよい。さらにまた、計算機システム１００は、船舶推進性能の解析サービスの運営事業者によって管理されてもよい。 The computer system 100 may be configured as a server connected to a plurality of client computers via an information network. The controller 102 may collect a data group from each of a plurality of client computers and store it in the memory 104. The controller 102 records analysis results such as an estimated value of propulsion performance, an evaluation index, etc. in the memory 104 for each voyage of each ship. The computer system 100 may be configured as an independent system that is not connected to a client computer. Furthermore, the computer system 100 may be configured as a data center that stores and manages data of client computers. Furthermore, the computer system 100 may be managed by an operator of a ship propulsion performance analysis service.
船舶の推進性能には、船速（対水船速、対地船速）、プロペラ回転速度、及び、主機関出力が含まれる。船舶の推進性能に関係する項目とは、船舶の推進性能に直接、又は、間接的に関係する項目である。特開2015-190970号公報には、対水船速に直接関連する第１の項目として、プロペラ回転速度、及び、主機関出力が示されている。さらに、第１の項目に直接関連する第２の項目として、燃料投入量、掃気圧力（過給圧力）、そして、燃料発熱量が例示されている。さらに、第２の項目に関係する第３の項目として、過給機回転速度や吸入空気温度が示されている。さらにまた、第３の項目に直接関連する第４の項目とし過給機出口の排ガス温度や、シリンダ出口の排ガス温度が例示されている。 Ship propulsion performance includes ship speed (speed against water, ship speed against ground), propeller rotational speed, and main engine output. The item related to the propulsion performance of the ship is an item directly or indirectly related to the propulsion performance of the ship. JP-A-2015-190970 discloses propeller rotational speed and main engine output as the first items directly related to the speed of watercraft. Furthermore, as a second item directly related to the first item, a fuel input amount, a scavenging pressure (supercharging pressure), and a fuel heating value are illustrated. Further, as the third item related to the second item, the supercharger rotation speed and the intake air temperature are shown. Furthermore, as the fourth item directly related to the third item, the exhaust gas temperature at the supercharger outlet and the exhaust gas temperature at the cylinder outlet are illustrated.
データ群には、海気象の観測値（風速、風向）、船舶の推進性能に関係する複数の項目の計測値である運航状況（対水船速、対地船速、進行方向、船首方位角等）及び主機関運転状況（プロペラ回転速度、掃気圧力、過給機回転速度等）が含まれる。主機関運転状況の値は計測値に代えて算出値でよい。また、進行方向はGPS信号による位置情報の時系列データからの算出値でもよい。データ群に含まれる計測値は、船舶の運航中、所定時間毎に船舶運航管理システムに記録される。 The data group includes observation values of sea weather (wind speed, wind direction), and operational status (measured against ship speed, ground ship speed, traveling direction, bow azimuth, etc.) that are measured values of multiple items related to ship propulsion performance. ) And main engine operating conditions (propeller rotation speed, scavenging pressure, turbocharger rotation speed, etc.). The value of the main engine operating status may be a calculated value instead of the measured value. Further, the traveling direction may be a calculated value from time series data of position information based on GPS signals. The measurement values included in the data group are recorded in the ship operation management system every predetermined time during the operation of the ship.
図２に、プロペラ回転速度の計測値と対水船速の計測値との相関の一例を示し、図３に、主機関出力の計測値と対水船速の計測値との相関の一例を示す。対水船速はドップラーレーダによって計測できる。なお、対地船速はＧＰＳを利用して計測できる。図２と図３のいずれの場合でも、実海環境の影響（風、波）に起因した大きなバラツキが存在する。 FIG. 2 shows an example of the correlation between the measured value of the propeller rotational speed and the measured value of the watercraft speed, and FIG. 3 shows an example of the correlation between the measured value of the main engine output and the measured value of the watercraft speed. Show. Vessel speed can be measured by Doppler radar. The ground speed can be measured using GPS. In either case of FIG. 2 or FIG. 3, there is a large variation due to the influence (wind, wave) of the actual sea environment.
これに対して、プロペラ回転速度の推定値、主機関出力の推定値、そして、対水船速の推定値との相関では、図４（プロペラ回転速度の推定値と対水船速の推定値との相関）、そして、図５（主機関出力の推定値と対水船速の推定値との相関）に示すように、これらの相関にはほぼ一意な関係が現れる。したがって、船舶の推進性能を把握するためには、計測値に基づいて算出される推定値が有益である。推定値とは、所定の海気象条件、特に、平水、無風状態に於ける船舶の推進性能の指標である。 On the other hand, the correlation between the estimated value of the propeller rotational speed, the estimated value of the main engine output, and the estimated value of the watercraft speed is shown in FIG. 4 (the estimated value of the propeller rotational speed and the estimated value of the watercraft speed). As shown in FIG. 5 (correlation between the estimated value of the main engine output and the estimated value of the watercraft speed), a substantially unique relationship appears in these correlations. Therefore, in order to grasp the propulsion performance of the ship, an estimated value calculated based on the measured value is useful. The estimated value is an index of the propulsion performance of the ship in a predetermined sea weather condition, particularly in a flat water and no wind condition.
対水船速の推定値は、プロペラ回転速度、及び／又は、主機関出力とを、特開2015-190970号公報に記載された相関関係モデルに適用して算出可能である。プロペラ回転速度と主機関出力とは、夫々、計測値であることを除外しないが、同公報記載に記載された、第２の項目、及び／又は、第３の項目、及び／又は、第４の項目の計測値を相関関係モデルに当てはめて算出された推定値であることが好ましい。後者の場合、後述するが、高価な主機関出力計を省略することができる。図６に、プロペラ回転速度の推定値と計測値との相関の一例を示し、図７に主機関出力の推定値と計測値との相関の一例を示す。これらにおいて、推定値と計測値とがばらつきが少なく一意に相関していることがわかり、計算機システム１００は、プロペラ回転速度の推定値と、主機関出力の推定値と、に基づいて対水船速の推定値を算出することにより、主機関の経年変化等に起因する誤差成分を除くことができる。対水船速の推定値と計測値との間には海気象に起因するかい離がある。 The estimated value of the speed against water can be calculated by applying the propeller rotational speed and / or the main engine output to the correlation model described in JP-A-2015-190970. The propeller rotational speed and the main engine output do not exclude the measured values, but the second item and / or the third item and / or the fourth item described in the publication It is preferable that the estimated value calculated by applying the measured value of the item to the correlation model. In the latter case, as will be described later, an expensive main engine output meter can be omitted. FIG. 6 shows an example of the correlation between the estimated value of the propeller rotational speed and the measured value, and FIG. 7 shows an example of the correlation between the estimated value of the main engine output and the measured value. In these, it can be seen that the estimated value and the measured value have a small variation and are uniquely correlated, and the computer system 100 is based on the estimated value of the propeller rotational speed and the estimated value of the main engine output. By calculating the estimated value of speed, it is possible to remove error components due to aging of the main engine. There is a separation caused by sea weather between the estimated value and the measured value of ship speed.
ところで、既述したように、海気象に起因する外乱が、追い風、又は、向い風等一定の方向から風を受けるような態様のものであると、計算機システム１００は、この外乱による影響を船舶の推進性能の推定値から除去できず、推定値を正確に算出することが困難である。このような外乱を便宜上、“対象外乱”と以後記載する。 By the way, as described above, when the disturbance caused by the sea weather is such that the wind is received from a certain direction such as a tailwind or a headwind, the computer system 100 determines the influence of the disturbance on the ship. It cannot be removed from the estimated value of propulsion performance, and it is difficult to accurately calculate the estimated value. Such a disturbance is hereinafter referred to as “target disturbance” for convenience.
そこで、計算機システム１００は、解析プログラムを実行して、対象外乱に起因する誤差を推進性能の推定値から除くために、算出した推定値を補正する。対象外乱は、推進性能の計測値と推進性能の推定値に影響する。そこで、解析プログラムは、対象外乱の計測値と、対象外乱が影響する推進性能の影響量（推進性能の計測値とその推定値との差分）を変数とした多変量解析を利用して関係式を導出し、この関係式に基づいて、推定値を補正する。これをさらに説明する。なお、推定値を予測値と言い換えることもできる。 Therefore, the computer system 100 executes the analysis program and corrects the calculated estimated value in order to remove the error caused by the target disturbance from the estimated value of the propulsion performance. The target disturbance affects the measured value of propulsion performance and the estimated value of propulsion performance. Therefore, the analysis program uses multivariate analysis with the variable of the measured value of the target disturbance and the influence amount of the propulsion performance affected by the target disturbance (the difference between the measured value of the propulsive performance and its estimated value) as a relational expression. And the estimated value is corrected based on this relational expression. This will be further described. In addition, an estimated value can also be paraphrased as a predicted value.
対水船速の計測値にも風は影響する。船舶に対して追い風が作用すると対水船速の計測値も増加し、船舶に対して向かい風が作用すると対水船速の計測値も減少する。対水船速の計測値を“Ｖ１”とし、対水船速の推定値“Ｖ２”とすると、追い風又は向かい風によって増減する船速の差分（影響船速）は（Ｖ１）から（Ｖ２）を減じた値になる。したがって、影響船速にも風は関係することになる。 The wind also affects the measured value of speed against water. When the tailwind acts on the ship, the measured value of the watercraft speed increases, and when the headwind acts on the ship, the measured value of the watercraft speed decreases. Assuming that the measured value of water speed is “V1” and the estimated value of water speed is “V2,” the difference in ship speed (influence ship speed) that increases or decreases due to tailwind or headwind is from (V1) to (V2). Decrease value. Therefore, the wind is also related to the affected ship speed.
図８Ａは、実際の航海事例での計測値（時系列データ）に基づいて、影響船速と、真風向と、真風速との相関を示したグラフである。真風向は正面方向（船舶の推進方向）と横方向（船舶の推進方向と直交方向）に分けられる。正面方向の風速がプラスの場合は船舶に対して向かい風になり、マイナスの場合は船舶に対して追い風になる。図８Ａから、正面方向風速と横方向風速が影響船速に関係していることが分かる。 FIG. 8A is a graph showing the correlation between the affected ship speed, the true wind direction, and the true wind speed based on the measured values (time-series data) in an actual voyage case. The true wind direction is divided into a front direction (a propulsion direction of the ship) and a lateral direction (a direction orthogonal to the propulsion direction of the ship). When the wind speed in the front direction is positive, the wind is against the ship, and when it is negative, the wind is against the ship. It can be seen from FIG. 8A that the front wind speed and the lateral wind speed are related to the influence ship speed.
計算機システム１００は、風向計及び風速計の計測値から、船舶に作用する真風向、真風速（追い風成分又は向かい風成分の真風力、横風成分の真風力）の時系列情報を算出することができる。計算機システム１００は、さらに、対水船速の計測値（時系列データ）と対水船速の推定値（時系列データ）とから影響船速の時系列情報を算出できる。 The computer system 100 can calculate the time series information of the true wind direction and true wind speed (true wind of the tail wind component or the head wind component, the true wind of the cross wind component) acting on the ship from the measurement values of the anemometer and the anemometer. . The computer system 100 can further calculate time-series information of the affected ship speed from the measured value (time-series data) of the watercraft speed and the estimated value (time-series data) of the watercraft speed.
図９は、図８Ａと同一の航海事例の計測値に基づいて、正面方向風速、影響船速、そして、対水船速の計測値との相関を表し、図１０は、横方向風速、影響船速、そして、対水船速の計測値の相関を表す。これらから、対水船速の計測値の大小に亘って、真風速が影響船速に関係していることが分かる。なお、船速には、風以外に波の属性（波高、波長、波向）も関係するが、波は風に対する相関があり、波による船速への影響も風速と風向が代表しているものと見なし扱っている。 波の属性を計測する波高計などのデータがあればよりよい解析が可能であるが、本解析手法ではこれらのデータは必ずしも必要ではなく、高価な波高計などの波属性計測機器を装備することなく、適切に推進性能を推定できる。なお、対水船速に対する潮流の影響は無視できるレベルである。 FIG. 9 shows the correlation with the measured values of the front direction wind speed, the affected ship speed, and the speed of the watercraft based on the measured values of the same navigation example as FIG. 8A. FIG. It represents the correlation between the ship speed and the measured value of water speed. From these, it is understood that the true wind speed is related to the influence ship speed over the magnitude of the measured value of the ship speed against water. In addition to the wind, the ship speed is related to the wave attributes (wave height, wavelength, wave direction), but the wave has a correlation with the wind, and the influence of the wave on the ship speed is represented by the wind speed and the wind direction. Treated as a thing. Better analysis is possible if there is data such as a wave height meter that measures the wave attributes, but this analysis method does not necessarily require these data, and it is necessary to equip an expensive wave height measuring device such as a wave height meter. The propulsion performance can be estimated appropriately. In addition, the influence of the tidal current on the water speed is negligible.
発明者は、真風速が影響船速にどのように関係するために、多変量解析の一例として、正面方向風速と横方向風速とを夫々説明変数とし、影響船速を目的変数とする（線形）重回帰分析を行った。重回帰式は、例えば、以下のとおり表現される。 Since the inventor is concerned with how the true wind speed relates to the influence ship speed, as an example of the multivariate analysis, the front direction wind speed and the transverse direction wind speed are each an explanatory variable, and the influence ship speed is an objective variable (linear ) A multiple regression analysis was performed. The multiple regression equation is expressed as follows, for example.
Ｚ＝ａ＋（ｂ*ｘ）＋（ｃ＊ｘ2）＋（ｄ＊ｙ）＋（ｅ＊ｙ２）
Ｚ：影響船速（目的変数）
ｘ：正面方向風速（説明変数）
ｙ：横方向風速（説明変数）
ａ：定数項（ｙ切片）
ｂ−ｅ：偏回帰係数
発明者が、図８Ａに示す相関に基づいて、ａ−ｅを算出したところ、
ａ＝０．１０７１３，ｂ＝０．０４１７１９，c＝０．００２４８１，ｄ＝０．００６５２９，e＝０．００２３２７が得られた。得られた重回帰式を３次元座標にプロットすると図１１に示すようになる。
Z = a + (b * x) + (c * x 2 ) + (d * y) + (e * y 2 )
Z: Influence ship speed (objective variable)
x: Front wind speed (explanatory variable)
y: Lateral wind speed (explanatory variable)
a: Constant term (y intercept)
be: partial regression coefficient When the inventor calculated ae based on the correlation shown in FIG. 8A,
a = 0.100713, b = 0.041719, c = 0.0242481, d = 0.005529, e = 0.002327 were obtained. When the obtained multiple regression equation is plotted on three-dimensional coordinates, it is as shown in FIG.
重回帰式において、正面方向風速（ｘ）、及び、横方向風速（ｙ）が零の場合には影響船速も零であるべきであるが、ａ（定数項）は零になっていない。この値は、対水船速の推定値（算出値）が、対象外乱によって、本来の値からシフトしたことに起因するものといえる。そこで、重回帰式の定数項（ａ）の値に基づいて、対水船速の推定値（算出値）を補正、例えば、対水船速の推定値に（ａ）を加えることによって、航海の事例において、対水船速の推定値から対象外乱の影響を緩和ないし除くことができる。船舶が追い風の影響を向かい風よりも相対的に強く受けると（ａ）は負の値になり、逆の場合、（ａ）は正の値になる。 In the multiple regression equation, when the front wind speed (x) and the lateral wind speed (y) are zero, the influence ship speed should be zero, but a (constant term) is not zero. This value can be attributed to the fact that the estimated value (calculated value) of the watercraft speed has shifted from the original value due to the target disturbance. Therefore, based on the value of the constant term (a) of the multiple regression equation, the estimated value (calculated value) of the watercraft speed is corrected, for example, by adding (a) to the estimated value of the watercraft speed, In this case, the influence of the target disturbance can be mitigated or eliminated from the estimated value of the speed against water. When the ship is affected by the tail wind relatively stronger than the head wind, (a) becomes a negative value, and in the opposite case, (a) becomes a positive value.
図８Ａの相関関係において、補正された対水船速の推定値に基づいて影響船速を修正し、修正後の影響船速の真風力との関係をプロットし直すと、図８Ｂに示すようになる。図８Ｂに示す相関関係に基づいて重回帰式を算出したところ、（ａ）は、２．７７ｅ-4となり、（ａ）は零として扱ってもよいレベルになった。偏回帰係数（ｂ−ｅ）も有効桁数においては既述の重回帰式と同じであった。 In the correlation of FIG. 8A, when the affected ship speed is corrected based on the corrected estimated value of the ship speed against water, the relationship between the corrected affected ship speed and the true wind force is plotted again, as shown in FIG. 8B. become. When a multiple regression equation was calculated based on the correlation shown in FIG. 8B, (a) was 2.77e −4 , and (a) was at a level that could be treated as zero. The partial regression coefficient (be) was also the same as the multiple regression equation described above in terms of the number of significant digits.
次に、対水船速の推定値を用いて推進性能を評価する他の指標について説明する。船速の３乗はプロペラ軸出力に概比例することが知られている。このことを利用して、対水船速（推定値）の３乗と対地船速（実測値）の３乗の比に比例する指数（推進抵抗指数）は、推進により発生する抵抗に加えて、波、風、潮などの海気象によって船舶が受ける抵抗の程度を示すものであり、推進抵抗指数が１の時は、海気象の影響がないことを示している。対水船速の推定値は、既述のように補正されたものが望ましい。 Next, another index for evaluating the propulsion performance using the estimated value for the speed of watercraft will be described. It is known that the cube of the ship speed is roughly proportional to the propeller shaft output. Using this, an index (propulsion resistance index) proportional to the ratio of the cube of the speed of water to the water (estimated value) and the cube of the speed of the ship to the ground (measured value) is added to the resistance generated by propulsion. This indicates the degree of resistance that the ship receives due to sea weather such as waves, wind, and tide. When the propulsion resistance index is 1, it indicates that there is no influence of sea weather. It is desirable that the estimated ship speed is corrected as described above.
推進抵抗指数∝（対水船速(推定値)３／対地船速(計測値)3）
推進抵抗指数は、船舶の推進に必要な倍率を表している。例えば、平水無風状態（推進抵抗指数が１.０）で、２０ｋｎｏｔの船速を得るために、１０，０００ｋＷの主機関出力を必要とする船舶が、推進抵抗指数が１．２となる海気象状態で、２０ｋｎｏｔの船速を維持するためには、主機関出力１０，０００ｋＷの１．２倍の主機関出力を必要とする。
Propulsion resistance index ∝ (Vessel speed (estimated value) 3 / Vessel speed (measured value) 3 )
The propulsion resistance index represents the magnification necessary for propulsion of the ship. For example, a ship that requires a main engine output of 10,000 kW in order to obtain a ship speed of 20 knots in a flat water no wind condition (propulsion resistance index of 1.0) has a propulsion resistance index of 1.2. In order to maintain a boat speed of 20 knots, a main engine output 1.2 times the main engine output 10,000 kW is required.
本発明者が検討したところ、推進抵抗指数、船舶の推進性能、例えば、（推進距離（ｍ）／プロペラの１回転）、そして、主機関出力との間には、図１２に示すように、一意の相関関係があることが分かった。計算機システム１００は、（推進距離（ｍ）／プロペラの１回転）を対水船速の計測値、プロペラの回転速度に基づいて算出することができる。 When the present inventor examined, between the propulsion resistance index, the propulsion performance of the ship, for example, (propulsion distance (m) / one rotation of the propeller), and the main engine output, as shown in FIG. It turns out that there is a unique correlation. The computer system 100 can calculate (propulsion distance (m) / one rotation of the propeller) based on the measured value of the speed of the watercraft and the rotation speed of the propeller.
したがって、計算機システム１００は、航海で蓄積されたデータ群に基づいて、相関関係を船舶の運航成績として算出し、複数の航海の間で運航成績を比較すると、船舶の推進性能の変化が分かるようになる。例えば、船体やプロペラが汚れると、推進抵抗が増加するため、相関関係の下方にシフトする。なお、図１２は一つの航海事例で蓄積されたデータ群に基づく運航成績を示し、図１３はこの航海事例から２月後の一つの航海事例で蓄積されたデータ群に基づく運航成績を示す。 Therefore, the computer system 100 calculates the correlation as the ship operation results based on the data group accumulated in the voyage, and compares the operation results among a plurality of voyages, so that the change in the propulsion performance of the ship can be seen. become. For example, if the hull or propeller becomes dirty, the propulsion resistance increases, and therefore shifts downward in the correlation. FIG. 12 shows the operation results based on the data group accumulated in one voyage case, and FIG. 13 shows the operation results based on the data group accumulated in one voyage case two months after this voyage case.
この結果、計算機システム１００は、複数の航海の間で相関関係を比較することによって船舶の推進性能の変化を定量的に把握し、所定の閾値との比較等を経て、船舶の推進性能の管理に関する判断、例えば、船舶の推進性能の経年劣化、その能力低下、船体やプロペラの汚れ等の状況を判定し、船体や主機関等のメンテナンス、船体等の洗浄のためのアドバイスを可能にする。このように、海気象による影響を「推進性能指数」として統一して指数化することで、船舶の推進性能の把握、推定、評価、分析、比較、判断等が可能になる。計算機システムの運営事業者は、推進抵抗指数を利用することにより、船舶の運航成績（推進抵抗を少なく運航できたか否か等）、船舶の状態等のレポートをユーザに提供することができる。なお、このレポートは、推進抵抗の特性、真風速と影響船速との関係等を、図面で説明したような映像情報として、含むようにしてよい。例えば、船が運航された運航路に沿って推進抵抗指数が変化している海図を示すことによって、船舶の運航生成が一見して分かるようになる。 As a result, the computer system 100 quantitatively grasps the change in the propulsion performance of the ship by comparing the correlation among a plurality of voyages, and manages the propulsion performance of the ship through comparison with a predetermined threshold. For example, it is possible to determine the situation such as deterioration of the propulsion performance of the ship, deterioration of its ability, dirt of the hull and propeller, etc., and advice for maintenance of the hull and the main engine and cleaning of the hull and the like. In this way, by unifying the influence of sea weather as a “propulsion performance index” and indexing it, it becomes possible to grasp, estimate, evaluate, analyze, compare, judge, etc. the propulsion performance of the ship. By using the propulsion resistance index, the operator of the computer system can provide the user with reports on the ship's operation results (whether the propulsion resistance has been reduced or not), the state of the ship, and the like. This report may include the characteristics of propulsion resistance, the relationship between the true wind speed and the affected ship speed, etc. as video information as described in the drawings. For example, by showing a chart in which the propulsion resistance index is changing along the route of operation of the ship, it is possible to understand the generation of the ship operation at a glance.
図１４に、図１３で利用された計測データのうち、掃気圧力（吸入空気温度に応じて標準状態に換算した値）と機関出力（プロペラ軸出力計）との相関関係を示す。図１４から分かるように、掃気圧力と主機関出力とは一意に相関していることが分かる。したがって、主機関の出力は、高価な出力計測装置（プロペラ軸出力計など）を利用しなくても、掃気圧力で代用できることが分かる。図１５に、機関出力の計測値を含めて解析した推進抵抗指数、船舶の推進性能、主機関掃気圧力との相関のグラフを示す。また、図１６に、機関出力の計測値を除外して解析した推進抵抗指数、船舶の推進性能、主機関掃気圧力との相関のグラフを示す。両者を比較すると、ほぼ同一の結果を示しており、このことからも機関出力やプロペラ軸出力データを用いなくても適切な推進性能の解析結果が得られることを示している。なお、掃気圧力と同様に機関出力と一意に相関のある過給機回転数と用いても同様の結果が得られる。 FIG. 14 shows the correlation between the scavenging pressure (the value converted into the standard state according to the intake air temperature) and the engine output (propeller shaft output meter) in the measurement data used in FIG. As can be seen from FIG. 14, the scavenging pressure and the main engine output are uniquely correlated. Therefore, it is understood that the scavenging pressure can be substituted for the output of the main engine without using an expensive output measuring device (such as a propeller shaft output meter). FIG. 15 shows a graph of the correlation between the propulsion resistance index, the ship propulsion performance, and the main engine scavenging pressure analyzed including the measured value of the engine output. FIG. 16 shows a graph of the correlation with the propulsion resistance index, the propulsion performance of the ship, and the main engine scavenging pressure analyzed by excluding the measured value of the engine output. Comparing the two shows almost the same result, which also shows that an analysis result of appropriate propulsion performance can be obtained without using engine output and propeller shaft output data. Similar results can be obtained by using the turbocharger speed that is uniquely correlated with the engine output as well as the scavenging pressure.
次に、計算機システム１００の動作を、図１７に基づいて改めて説明する。図１７は、コントローラ１０２の動作プロセスの一例を示すフローチャートである。 Next, the operation of the computer system 100 will be described again with reference to FIG. FIG. 17 is a flowchart illustrating an example of an operation process of the controller 102.
コントローラ１０２は、ステップＳ１において、データ群の中から、入力装置１０２から入力された船舶ＩＤ、航海ＩＤに関連する計測値を抽出する。コントローラ１０２は抽出された計測と所定の閾値とを比較し、閾値からかい離した計測値を除外してもよい。ステップＳ１は推進性能の解析の準備モジュールに相当する。 In step S1, the controller 102 extracts a measurement value related to the ship ID and the voyage ID input from the input device 102 from the data group. The controller 102 may compare the extracted measurement with a predetermined threshold value and exclude a measurement value that is far from the threshold value. Step S1 corresponds to a preparation module for analysis of propulsion performance.
次いで、コントローラ１０２は、ステップＳ２において、既述のとおり、特開2015-190970号公報で説明された手法を利用して、対水船速の推定値を算出する。ステップＳ２は、対水船速推定値算出モジュールに相当する。 Next, in step S2, the controller 102 calculates an estimated value of the speed of the watercraft using the method described in Japanese Patent Laid-Open No. 2015-190970 as described above. Step S2 corresponds to an anti-watercraft speed estimated value calculation module.
さらに、コントローラ１０２は、ステップＳ３において、既述のとおり、重回帰分析によって、対水船速の推定値を補正する。ステップＳ３は、対水船速推定値補正モジュールに相当する。 Further, in step S3, the controller 102 corrects the estimated value of the speed of the watercraft by multiple regression analysis as described above. Step S3 corresponds to an anti-watercraft speed estimated value correction module.
次いで、コントローラ１０２は、ステップＳ４において、既述のとおり、船舶の推進性能の評価指数の一例としての推進抵抗指数を算出する。ステップＳ４は、評価指数算出モジュールに相当する。さらに、コントローラ１０２は、ステップＳ５において、推進抵抗指数を利用して船舶の推進性能の評価処理を行い、評価結果を出力装置１０８に報知する。ステップＳ５は、船舶の推進性能の評価モジュールに相当する。 Next, in step S4, the controller 102 calculates a propulsion resistance index as an example of an evaluation index for the propulsion performance of the ship as described above. Step S4 corresponds to an evaluation index calculation module. Further, in step S5, the controller 102 uses the propulsion resistance index to perform an evaluation process on the propulsion performance of the ship, and notifies the output device 108 of the evaluation result. Step S5 corresponds to a ship propulsion performance evaluation module.
以上説明したように、計算機システムによれば、船舶の運航に関する物理モデルを用いた理論推進性能解析を利用することなく、計測値のみから船舶の推進性能を精度良く解析することができる。 As described above, according to the computer system, the propulsion performance of the ship can be accurately analyzed from only the measured values without using the theoretical propulsion performance analysis using the physical model related to the operation of the ship.
既述のとおり、本発明は船舶の推進性能を解析するものであるが、本発明の技術思想を適用できる限り、他のモデル、例えば、風の影響を受ける風力発電機の動作性能の解析システムにも本発明を適用することができる。 As described above, the present invention analyzes the propulsion performance of a ship. However, as long as the technical idea of the present invention can be applied, other models, for example, a system for analyzing the performance of a wind generator affected by wind are analyzed. The present invention can also be applied to.
Claims (13)
船舶の推進性能を解析するコントローラと、
を備え、
前記コントローラは、
前記データ群を利用して、所定の気象環境下における船舶の推進性能の推定値を算出し、
海気象の計測値に基づいて前記算出された推定値を補正する
計算機システム。 A memory for storing a group of data recorded when the ship is operating in the actual sea area;
A controller that analyzes the propulsion performance of the ship;
With
The controller is
Using the data group, calculate an estimated value of the propulsion performance of the ship under a predetermined weather environment,
A computer system for correcting the calculated estimated value based on a measurement value of sea weather.
前記海気象の計測値を利用して多変量解析を行い、
当該多変量解析の結果を前記算出された推定値に適用することによって、前記補正を実行する
請求項１記載の計算機システム。 The controller is
Perform multivariate analysis using the sea weather measurements,
The computer system according to claim 1, wherein the correction is performed by applying a result of the multivariate analysis to the calculated estimated value.
前記多変量解析を、前記推進性能の計測値と前記算出された推定値の差分とに基づいて行う
請求項２記載の計算機システム。 The controller is
The computer system according to claim 2, wherein the multivariate analysis is performed based on a measured value of the propulsion performance and a difference between the calculated estimated values.
前記船舶の推進性能を対水船速とし、
前記海気象の計測値を風の計測値とし、
当該風の計測値から、船舶に作用する第１の真風力と、第２の真風力と、を算出し、
前記対水船速の計測値とその推定値との差分と、前記第１の真風力と、前記第２の真風力とに基づいて、前記多変量解析としての重回帰分析を行う
請求項３記載の計算機システム。 The controller is
The propulsion performance of the ship is the speed against water,
The measurement value of the sea weather as the measurement value of the wind,
From the measured value of the wind, calculate the first true wind and the second true wind acting on the ship,
4. The multiple regression analysis as the multivariate analysis is performed based on a difference between the measured value of the watercraft speed and the estimated value thereof, the first true wind force, and the second true wind force. The computer system described.
前記第１の真風力を船舶に作用する追い風、又は、向かい風の値とし、
前記第２の真風力を船舶に作用する横風の値とする、
請求項４記載の計算機システム。 The controller is
The first true wind is a tail wind acting on the ship or a value of the head wind,
The second true wind is the value of the cross wind acting on the ship,
The computer system according to claim 4.
前記重回帰分析に係る重回帰式の定数項を前記多変量解析の結果として利用して、前記算出された対水船速の推定値を補正する
請求項５記載の計算機システム。 The controller is
The computer system according to claim 5, wherein a constant term of a multiple regression equation relating to the multiple regression analysis is used as a result of the multivariate analysis to correct the calculated estimated value of the watercraft speed.
前記補正された推定値に基づいて、船舶の推進性能を評価するための指標を算出する
請求項１記載の計算機システム。 The controller is
The computer system according to claim 1, wherein an index for evaluating the propulsion performance of the ship is calculated based on the corrected estimated value.
前記対水船速の推定値と、船舶の対地船速の計測値と、
に基づいて、船舶の推進性能を評価するための指標を算出する
請求項４ないし６の何れか１項記載の計算機システム。 The controller is
The estimated value of the ship speed against water and the measured value of the ship's speed to ground;
The computer system according to any one of claims 4 to 6, wherein an index for evaluating the propulsion performance of the ship is calculated based on.
請求項８記載の計算機システム。 The computer system according to claim 8, wherein the index is proportional to a speed against water (estimated value) 3 / a speed against ground (measured value) 3 .
前記船舶の推進性能を対水船速とし、
当該対水船速の推定値を、主機関、または、プロペラ軸の出力の計測装置によらずに、当該主機関の掃気圧力に基づいて算出する
請求項１記載の計算機システム。 The controller is
The propulsion performance of the ship is the speed against water,
The computer system according to claim 1, wherein the estimated value of the speed of the watercraft is calculated based on the scavenging pressure of the main engine without using the main engine or the propeller shaft output measuring device.
前記コンピュータは、
前記データ群を利用して、所定の気象環境下における船舶の推進性能の推定値を算出するステップと、
海気象の計測値に基づいて前記算出された推定値を補正するステップと、
を実行する
前記解析方法。 The computer is an analysis method for analyzing the propulsion performance of a ship based on a group of data recorded when the ship is operated in a real sea area,
The computer
Using the data group, calculating an estimated value of the propulsion performance of the ship under a predetermined weather environment; and
Correcting the calculated estimated value based on a measurement value of sea weather;
The analysis method.
前記データ群を利用して、所定の気象環境下における船舶の推進性能の推定値を算出する機能と、
海気象の計測値に基づいて前記算出された推定値を補正する機能と、
をコンピュータに実現させるためのプログラム。 A program for analyzing the propulsion performance of a ship based on a group of data recorded when the ship is operated in a real sea area,
A function for calculating an estimated value of the propulsion performance of the ship under a predetermined weather environment using the data group,
A function of correcting the calculated estimated value based on a measurement value of sea weather;
A program to make a computer realize.
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