JP6677608B2 - Erosion prediction device and prediction method for hydraulic machine - Google Patents
Erosion prediction device and prediction method for hydraulic machine Download PDFInfo
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Description
本発明の実施形態は、水力機械の壊食予測装置および予測方法に関する。 An embodiment of the present invention relates to an erosion prediction device and a prediction method for a hydraulic machine.
ランナベーンでキャビテーションが発生すると、水力機械の水力性能や機器の寿命が低
下する。したがって、キャビテーションに起因する壊食を予測することは、水力機器を運
用する上で重要となる。
When cavitation occurs in the runner vanes, the hydraulic performance of the hydraulic machine and the life of the equipment are reduced. Therefore, predicting erosion due to cavitation is important in operating hydraulic equipment.
従来の壊食予測方法は、センサや画像解析のためのカメラを備え、センサリングによっ
て壊食を予測する方法や、試験片を用いた実験に基づいてデータベースを作成し、実機の
運転状況と比較して壊食を予測する方法などが提案されている。しかしながら、キャビテ
ーションの現象が複雑であるために、壊食予測の精度を向上するためには未だ多くの課題
を抱えている。そこで、水力機械を運転させたまま、実機の状況を反映した精度の高い水
力機械の壊食を予測する方法が求められている。
The conventional erosion prediction method has a sensor and a camera for image analysis, creates a database based on erosion prediction by sensoring, and creates a database based on experiments using test specimens and compares it with the actual machine operation situation A method of predicting erosion has been proposed. However, since the cavitation phenomenon is complicated, there are still many problems to improve the accuracy of erosion prediction. Therefore, there is a need for a method of accurately predicting the erosion of a hydraulic machine that reflects the state of the actual machine while the hydraulic machine is in operation.
本発明が解決しようとする課題は、実機の状況を反映した精度の高い水力機械の壊食予
測装置および予測方法を提供することにある。
The problem to be solved by the present invention is to provide a highly accurate erosion prediction device and a prediction method for a hydraulic machine that reflects the situation of an actual machine.
上記の課題を解決するために、本発明の実施形態によれば、水力機械に接続され、キャ
ビテーションの発生をセンシングするセンサと、実験用水力機械による実験で測定したキ
ャビテーションの衝撃力と前記衝撃力により前記実験用水力機械に生じる壊食量との関係
および前記センサにより得られたデータとを比較して予測壊食量を算出する壊食量導出部
と、前記水力機械について数値流体解析を行い、前記解析の結果を出力する演算処理装置
と、を備え、前記演算処理装置は、前記水力機械の運転条件に基づいて前記数値流体解析
を行う演算処理部と、前記数値流体解析の結果に基づいて実機性能を予測する性能予測部
とを具備し、前記予測壊食量と前記実機性能とを用いて前期水力機械の形状モデルの作成
を可能とする。
According to an embodiment of the present invention, there is provided a sensor connected to a hydraulic machine, for sensing the occurrence of cavitation, the cavitation impact force measured in an experiment using an experimental hydraulic machine, and the impact force. An erosion amount deriving unit that calculates a predicted erosion amount by comparing the relationship with the erosion amount generated in the experimental hydraulic machine and the data obtained by the sensor, performs a numerical fluid analysis on the hydraulic machine, and performs the analysis. An arithmetic processing unit that outputs the result of the numerical fluid analysis, wherein the arithmetic processing unit performs the numerical fluid analysis based on the operating conditions of the hydraulic machine, and an actual processing performance based on the result of the numerical fluid analysis. And a performance predicting unit for predicting the above-mentioned condition, and it is possible to create a shape model of the hydraulic machine using the predicted erosion amount and the performance of the actual machine.
以下、実施形態に係る壊食予測装置および予測方法について説明する。 Hereinafter, an erosion prediction device and a prediction method according to the embodiment will be described.
（第一の実施形態）
図１は、第一の実施形態に係る壊食予測装置の概要図である。なお、本実施形態におい
て、水車はフランシス形水車を用いて説明するが、水車の種類は限定されない。第一の実
施形態に係る壊食予測装置は、センサ１０と、壊食量測定装置２０と、演算処理装置３０
からなる。
(First embodiment)
FIG. 1 is a schematic diagram of the erosion prediction device according to the first embodiment. In addition, in this embodiment, although a water wheel is demonstrated using a Francis type water wheel, the kind of a water wheel is not limited. The erosion prediction device according to the first embodiment includes a
Consists of
センサ１０は、キャビテーションにより発生する衝撃力の検出を行う。センサ１０は、
例えばランナベーン１の出入り口など、実機中で壊食を発生しやすい領域に設置される。
The
For example, it is installed in an area where erosion is likely to occur in the actual machine, such as the entrance of the
壊食量測定装置２０は、壊食データ記憶部２１と、壊食量測定部２２から構成される。
壊食データ記憶部２１は、複数の運転条件における壊食量とキャビテーションにより発生
する衝撃力との関係や、単位時間あたりの壊食量などをデータベース化して記憶する。運
転条件とは、水の流量や落差、実機の運転時間、ガイドベーン開度、回転速度などの条件
を表す。なお、壊食量とキャビテーションにより発生する衝撃力との関係は、例えばあら
かじめ試験片を用いた実験を行って導出する。壊食量測定部２２は、壊食データ記憶部で
記憶されたデータベースと、センサ１０で検出した衝撃力の結果とを組み合わせて壊食量
の導出を行う。
The erosion
The erosion data storage unit 21 stores the relationship between the amount of erosion under a plurality of operating conditions and the impact force generated by cavitation, the amount of erosion per unit time, and the like in a database. The operating conditions represent conditions such as the flow rate and head of water, the operating time of the actual machine, the opening degree of the guide vanes, and the rotation speed. The relationship between the amount of erosion and the impact force generated by cavitation is derived, for example, by conducting an experiment using a test piece in advance. The erosion
演算処理装置３０は、演算処理部３１と、性能予測部３２と、形状モデル作成部３３と
、予測結果記憶部３４から構成される。演算処理部３１は、実機の運転条件を反映して数
値流体解析を行う。性能予測部３２は、演算処理部３１で算出される数値流体解析の結果
に基づいて実機の性能を予測し、壊食部位を特定する。形状モデル作成部３３は、性能予
測部３２で予測される性能の結果に基づいて、壊食を反映した実機の形状モデルを作成す
る。予測結果記憶部３４は、性能予測部３２で予測した実機の性能や壊食部位の特定結果
を記憶する。運転範囲予測部３５は、性能予測部３２で予測した実機の性能や壊食部位の
特定結果に基づいて、水車の最適な運転条件を予測する。
The
センサ１０でセンシングした衝撃力の結果と、壊食データ記憶部２０のデータベースを
比較することにより、実機の壊食量が導出される。実機の壊食量と、演算処理装置３０で
算出された壊食部位や実機の性能予測とを組み合わせることで、実機の状態を反映した解
析が可能となる。
By comparing the result of the impact force sensed by the
図２は、第一の実施形態に係る経時後の性能予測方法を表すフローチャートである。演
算処理装置３０へ実機の運転条件を入力し（ステップＳ１）、演算処理部３１にて数値流
体解析による計算を行う（ステップＳ２）。演算処理部３１で算出される計算結果に基づ
いて、性能予測部３２にて現状の性能を予測し、壊食部位を特定する（ステップＳ３）。
性能予測部で得られる結果を予測結果記憶部３４にて記憶する。現状の性能を算出したデ
ータと壊食部位を算出したデータに加えて、センサ１０と壊食データ記憶部２０を用いて
導出した、実機の壊食量と単位時間あたりの壊食量を組み合わせることで、形状モデル作
成部にて壊食を反映した実機の形状モデルを作成する（ステップＳ４）。なお、センサ１
０と壊食データ記憶部２０を用いて実機の壊食範囲を予測し、性能予測部３２で特定した
壊食部位と比較してもよい。
FIG. 2 is a flowchart illustrating a performance prediction method after aging according to the first embodiment. The operating conditions of the actual machine are input to the arithmetic processing unit 30 (step S1), and the
The result obtained by the performance prediction unit is stored in the prediction
The erosion range of the actual machine may be predicted using 0 and the erosion
壊食を反映した実機の形状モデルの結果を演算処理装置３０に入力し、ステップＳ２か
らステップＳ４を繰り返し実行する。性能結果記憶部３４で記憶した現状性能の予測結果
と、ステップＳ２からステップＳ４を繰り返し実行して算出した結果を比較して（ステッ
プＳ５）、性能予測部３２にて経時後の実機の壊食状況や壊食を反映した性能を予測する
（ステップＳ６）。
The result of the shape model of the actual machine reflecting the erosion is input to the
経時後の実機の性能予測に基づいて、ランニングコストやメンテナンス費用などを見積
もり、経時後の実機の経済効果を予測する（ステップＳ７）。なお、ステップ７は演算処
理部３１で行ってもよいし、経済効果予測を行う別の装置にステップ６の結果を送信して
行ってもよい。
The running cost and the maintenance cost are estimated based on the performance prediction of the real machine after the lapse of time, and the economic effect of the real machine after the lapse of time is predicted (step S7). Note that step 7 may be performed by the
上述した第一の実施形態によれば、数値流体解析による計算と実機の壊食のデータを組
み合わせることで、壊食部位や壊食形状の予測だけでなく、実機の状況を反映した精度の
高い経時後の性能予測が可能となる。実機の経時後の性能予測が可能となるため、ランナ
の適切な取替え時期を把握することが容易になる。性能予測に実機の壊食状況を反映する
ため、発電所を停止する必要がなく、発電所を稼動させながら性能の予測が容易となる。
According to the first embodiment described above, by combining the computation by the numerical fluid analysis and the erosion data of the actual machine, not only the prediction of the erosion site and the erosion shape, but also high accuracy reflecting the situation of the actual machine Performance prediction after aging becomes possible. Since it is possible to predict the performance of the actual machine after a lapse of time, it is easy to grasp the appropriate replacement time of the runner. Since the erosion status of the actual machine is reflected in the performance prediction, there is no need to stop the power plant, and the performance can be easily predicted while the power plant is operating.
なお、ステップＳ１からステップＳ４をあらかじめ実行し、計算結果を予測結果記憶部
３４に記憶してもよい。
Steps S1 to S4 may be executed in advance, and the calculation result may be stored in the prediction
（第二の実施形態）
次に、第二の実施形態を説明する。なお、本実施形態において、水力機械の発電方式は
揚水式発電として説明するが、発電方式は限定されない。また、第一の実施形態と同様の
箇所については、説明を省略する。図３は、第二の実施形態に係る実機の運転範囲の変更
方法を表すフローチャートである。なお、第一の実施形態と同一の箇所については説明を
省略する。ステップＳ６において経時後の実機の壊食状況や性能を予測し、運転範囲予測
部３５にて実機の運転範囲が適切かを予測する（ステップＳ８）。壊食状況の予測に基づ
いて、キャビテーションが発生していないか、またはキャビテーションが発生しているも
のの、水車に著しい損傷を与えない（有害なキャビテーションに該当しない）と判断でき
る場合には、水力機械の下限出力を下げるよう制御装置を介して信号を送信する（ステッ
プＳ９）。キャビテーションが発生し、かつ水車に著しい損傷を与えると判断できる場合
には、水車の運転状態を変更した後に再度実機の性能予測を行う。
(Second embodiment)
Next, a second embodiment will be described. In this embodiment, the power generation system of the hydraulic machine will be described as a pumped-storage type power generation system, but the power generation system is not limited. The description of the same parts as in the first embodiment is omitted. FIG. 3 is a flowchart illustrating a method for changing the operation range of the actual machine according to the second embodiment. The description of the same parts as those in the first embodiment will be omitted. In step S6, the erosion state and performance of the actual machine after the lapse of time are predicted, and the operation
なお、水車に著しい損傷を与えるか否かの判断基準は、実機の稼動状態によって決定す
ればよい。例えば、過去の定期点検のデータや補修時の実機の状況から壊食部位と壊食量
の条件を設定して判断してもよいし、規格で定められた壊食量の範囲内か否かで判断して
もよい。
It should be noted that the criterion for determining whether or not the water turbine is significantly damaged may be determined according to the operating state of the actual machine. For example, erosion sites and erosion amount conditions may be set based on the data of past periodic inspections and the actual machine status at the time of repair. May be.
上述した第二の実施形態によれば、実機の状況を反映した運用が可能となる。一般に、
水車のキャビテーション発生境界領域は、模型を用いた実験や、数値解析により導出され
る。試験片を用いた実験の結果に加えて、数値流体解析による計算と実機の壊食のデータ
を組み合わせることで、実機の状況に合わせたキャビテーションの発生しない、もしくは
キャビテーションによる有害な壊食の発生しない適切な運転範囲の設定が容易となる。
According to the above-described second embodiment, operation that reflects the status of the actual device becomes possible. In general,
The cavitation occurrence boundary region of the water turbine is derived by an experiment using a model or by numerical analysis. In addition to the results of experiments using test specimens, cavitation tailored to the situation of the actual machine does not occur, or harmful erosion due to cavitation does not occur by combining the calculation by CFD and the erosion data of the actual machine It is easy to set an appropriate operation range.
本発明のいくつかの実施形態を説明したが、これらの実施形態は、例として提示したも
のであり、発明の範囲を限定することは意図していない。これら新規な実施形態は、その
他の様々な形態で実施されることが可能であり、発明の趣旨を逸脱しない範囲で、種々の
省略、置き換え、変更を行うことができる。これら実施形態やその変形は、発明の範囲や
要旨に含まれるとともに、特許請求の範囲に記載された発明とその均等の範囲に含まれる
。
Although several embodiments of the present invention have been described, these embodiments are provided by way of example and are not intended to limit the scope of the invention. These new embodiments can be implemented in other various forms, and various omissions, replacements, and changes can be made without departing from the spirit of the invention. These embodiments and their modifications are included in the scope and gist of the invention, and are also included in the invention described in the claims and their equivalents.
１．ランナベーン
２．クラウン
１０．センサ
２０．壊食量測定装置
２１．壊食データ記憶部
２２．壊食量導出部
３０．演算処理装置
３１．演算処理部
３２．性能予測部
３３．形状モデル作成部
３４．予測結果記憶部
３５．運転範囲予測部
1. Runner vane2.
Claims (5)
実験用水力機械による実験で測定したキャビテーションの衝撃力と前記衝撃力により前記実験用水力機械に生じる壊食量との関係および前記センサにより得られたデータとを比較して予測壊食量を算出する壊食量導出部と、
前記水力機械について数値流体解析を行い、前記数値流体解析の結果を出力する演算処理装置と、を備え、
前記演算処理装置は、前記水力機械の運転条件に基づいて前記数値流体解析を行う演算処理部と、前記数値流体解析の結果に基づいて壊食部位を特定する性能予測部と、前記予測壊食量と前記壊食部位の特定結果とに基づいて前記水力機械の形状モデルを作成する形状モデル作成部と、を具備し、
前記演算処理部は、前記形状モデルに基づいて前記数値流体解析を行って、経時変化後の前記水力機械の壊食状況を予測し、前記経時変化後の前記壊食状況の予測結果に基づいて、前記水力機械のランニングコストまたはメンテナンス費用を予測する、水力機械の壊食予測装置。 A sensor that is connected to the hydraulic machine and senses the occurrence of cavitation,
The relationship between the impact force of cavitation measured in an experiment using an experimental hydraulic machine and the amount of erosion that occurs in the experimental hydraulic machine due to the impact force and data obtained by the sensor are compared to calculate the predicted erosion amount. Food quantity derivation unit,
An arithmetic processing unit that performs a numerical fluid analysis on the hydraulic machine and outputs a result of the numerical fluid analysis,
The arithmetic processing unit, an arithmetic processing unit that performs the numerical fluid analysis based on the operating conditions of the hydraulic machine, a performance prediction unit that specifies an erosion site based on the result of the numerical fluid analysis, the predicted erosion amount wherein based on the identification result of the erosion site anda shape model generation unit that forms create a shape model of the hydraulic machine and,
The arithmetic processing unit performs the numerical fluid analysis based on the shape model, predicts the erosion state of the hydraulic machine after a change over time, and based on the prediction result of the erosion state after the change over time. An erosion prediction device for a hydraulic machine , for predicting a running cost or a maintenance cost of the hydraulic machine.
実験用水力機械による実験で測定したキャビテーションの衝撃力と前記衝撃力により前記実験用水力機械に生じる壊食量との関係および前記センサにより得られたデータとを比較して予測壊食量を算出する壊食量導出部と、The relationship between the impact force of cavitation measured in an experiment using an experimental hydraulic machine and the amount of erosion that occurs in the experimental hydraulic machine due to the impact force and data obtained by the sensor are compared to calculate the predicted erosion amount. Food quantity derivation unit,
前記水力機械について数値流体解析を行い、前記数値流体解析の結果を出力する演算処理装置と、を備え、An arithmetic processing unit that performs a numerical fluid analysis on the hydraulic machine and outputs a result of the numerical fluid analysis,
前記演算処理装置は、前記水力機械の運転条件に基づいて前記数値流体解析を行う演算処理部と、前記数値流体解析の結果に基づいて壊食部位を特定する性能予測部と、前記予測壊食量と前記壊食部位の特定結果とに基づいて前記水力機械の形状モデルを作成する形状モデル作成部と、を具備し、The arithmetic processing unit, an arithmetic processing unit that performs the numerical fluid analysis based on the operating conditions of the hydraulic machine, a performance prediction unit that specifies an erosion site based on the result of the numerical fluid analysis, the predicted erosion amount And a shape model creating unit that creates a shape model of the hydraulic machine based on the identification result of the erosion site,
前記演算処理部は、前記形状モデルに基づいて前記数値流体解析を行って、経時変化後の前記水力機械の壊食状況を予測し、The arithmetic processing unit performs the numerical fluid analysis based on the shape model, and predicts the erosion state of the hydraulic machine after a change over time,
前記演算処理装置は、前記経時変化後の前記壊食状況の予測結果に基づいて、前記水力機械の運転条件範囲を予測する運転範囲予測部を更に具備し、The arithmetic processing device further includes an operation range prediction unit that predicts an operation condition range of the hydraulic machine based on a prediction result of the erosion state after the change with time,
前記運転範囲予測部は、前記経時変化後に有害なキャビテーションの発生が予測されない場合に前記運転条件範囲を拡大する、水力機械の壊食予測装置。The erosion prediction device for a hydraulic machine, wherein the operation range prediction unit expands the operation condition range when occurrence of harmful cavitation is not predicted after the temporal change.
前記性能予測部は、前記解析記憶部に記憶された前記壊食部位の特定結果と前記予測壊食量とに基づいて前記水力機械の前記形状モデルを作成する、請求項１または２に記載の水力機械の壊食予測装置。 The arithmetic processing device further includes an analysis storage unit that stores the identification result of the erosion site ,
The performance prediction unit, that forms create the shape model of the hydraulic machine on the basis of the identification result and the predicted erosion amount of the erosion region stored in the analysis storage unit, according to claim 1 or 2 Erosion prediction device for hydraulic machinery.
前記実機の水力機械について数値流体解析を行い、この結果に基づいて壊食部位を特定し、前記予測壊食量と前記壊食部位の特定結果とに基づいて前記水力機械の形状モデルを作成し、
前記形状モデルに基づいて前記数値流体解析を行って、経時変化後の前記水力機械の壊食状況を予測し、
前記経時変化後の前記壊食状況の予測結果に基づいて、前記水力機械のランニングコストまたはメンテナンス費用を予測する、水力機械の壊食予測方法。 The relationship between the cavitation impact force measured in the experiment by the experimental hydraulic machine and the amount of erosion generated in the experimental hydraulic machine by the impact force and data obtained by a sensor connected to the actual hydraulic machine and sensing the occurrence of cavitation To calculate the predicted erosion volume,
It performed CFD for hydraulic machine of the actual, results to identify the erosion site based on, create a shape model of the hydraulic machine on the basis of the identification result of the erosion site and the predicted erosion amount ,
Performing the numerical fluid analysis based on the shape model, predicting the erosion situation of the hydraulic machine after a change over time,
On the basis of the prediction result of the erosion situation after aging, to predict the running costs or maintenance costs of the hydraulic machine, corrupted diet prediction method of the hydraulic machine.
前記実機の水力機械について数値流体解析を行い、この結果に基づいて壊食部位を特定し、前記予測壊食量と前記壊食部位の特定結果とに基づいて前記水力機械の形状モデルを作成し、Perform a numerical fluid analysis on the actual hydraulic machine, identify the erosion site based on this result, create a shape model of the hydraulic machine based on the predicted erosion amount and the identification result of the erosion site,
前記形状モデルに基づいて前記数値流体解析を行って、経時変化後の前記水力機械の壊食状況を予測し、Performing the numerical fluid analysis based on the shape model, predicting the erosion situation of the hydraulic machine after a change over time,
前記経時変化後の前記壊食状況の予測結果に基づいて、前記水力機械の運転条件範囲を予測し、前記経時変化後に有害なキャビテーションの発生が予測されない場合に前記運転条件範囲を拡大する、水力機械の壊食予測方法。Based on the prediction result of the erosion situation after the change over time, predict the operating condition range of the hydraulic machine, expand the operating condition range when the occurrence of harmful cavitation is not predicted after the change over time, Machine erosion prediction method.
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