WO2018207464A1 - System and method for monitoring grease of wind power generator - Google Patents

System and method for monitoring grease of wind power generator Download PDF

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Publication number
WO2018207464A1
WO2018207464A1 PCT/JP2018/010712 JP2018010712W WO2018207464A1 WO 2018207464 A1 WO2018207464 A1 WO 2018207464A1 JP 2018010712 W JP2018010712 W JP 2018010712W WO 2018207464 A1 WO2018207464 A1 WO 2018207464A1
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Prior art keywords
grease
wind power
power generator
physical property
optical sensor
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PCT/JP2018/010712
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French (fr)
Japanese (ja)
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小島　恭子
満 佐伯
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株式会社日立製作所
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Publication of WO2018207464A1 publication Critical patent/WO2018207464A1/en

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    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F03—MACHINES OR ENGINES FOR LIQUIDS; WIND, SPRING, OR WEIGHT MOTORS; PRODUCING MECHANICAL POWER OR A REACTIVE PROPULSIVE THRUST, NOT OTHERWISE PROVIDED FOR
    • F03D—WIND MOTORS
    • F03D80/00—Details, components or accessories not provided for in groups F03D1/00 - F03D17/00
    • F03D80/70—Bearing or lubricating arrangements
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F16—ENGINEERING ELEMENTS AND UNITS; GENERAL MEASURES FOR PRODUCING AND MAINTAINING EFFECTIVE FUNCTIONING OF MACHINES OR INSTALLATIONS; THERMAL INSULATION IN GENERAL
    • F16N—LUBRICATING
    • F16N29/00—Special means in lubricating arrangements or systems providing for the indication or detection of undesired conditions; Use of devices responsive to conditions in lubricating arrangements or systems
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
    • G01M99/00—Subject matter not provided for in other groups of this subclass
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00—Energy generation through renewable energy sources
    • Y02E10/70—Wind energy
    • Y02E10/72—Wind turbines with rotation axis in wind direction

Definitions

  • the present invention relates to a wind power generator, and more particularly, to a wind power generator capable of supporting maintenance and management of lubricating oil and grease in a nacelle.
  • Patent Document 1 discloses a technique for providing a wind turbine generator that can support a platform with a simple structure, can cope with leakage of lubricating oil from the nacelle, and can improve reliability. .
  • Patent Document 2 techniques for determining the state of oil are disclosed in, for example, Patent Document 2 and Patent Document 3.
  • FIG. 1 shows a schematic overall configuration diagram of a wind turbine generator targeted by the present invention.
  • each device arranged in the nacelle 3 is indicated by a dotted line.
  • the wind turbine generator 1 includes a blade 5 that rotates by receiving wind, a hub 4 that supports the blade 5, a nacelle 3, and a tower 2 that rotatably supports the nacelle 3.
  • a main shaft 31 connected to the hub 4 and rotating together with the hub 4, a shrink disk 32 connected to the main shaft 31, a speed increasing device 33 connected to the main shaft 31 via the shrink disk 32 and increasing the rotation speed, And a generator 34 that performs a power generation operation by rotating the rotor at a rotational speed increased by the speed increaser 33 via the coupling 38.
  • the part that transmits the rotational energy of the blade 5 to the generator 34 is called a power transmission unit.
  • the main shaft 31, the shrink disk 32, the speed increaser 33, and the coupling 38 are included in the power transmission unit.
  • the speed increaser 33 and the generator 34 are held on the main frame 35.
  • a grease tank 37 that stores grease for lubricating the power transmission unit is installed on the main frame 35.
  • a radiator 36 is disposed on the windward side of the nacelle partition wall 30.
  • the wind power generator 1 shown in FIG. 1 shows a 5 MW class wind power generator as an example.
  • the radiator 36 is arranged between an outside air inlet (not shown) provided on the upper surface of the nacelle 3 and an air outlet (not shown) in the nacelle. Is done.
  • Grease is based on a liquid lubricant and thickener, and contains additives such as antioxidants, antiwear agents, and extreme pressure agents.
  • the thickener is used to mix the base oil, which is a liquid, into a gel like a grease. Extreme pressure agents are added to lubricants to reduce friction and wear between two metal surfaces and to prevent seizure.
  • Deterioration over time refers to changes in physicochemical properties over time according to grease specifications. Specifically, flow characteristics (shear rate dependence and time dependence), heat resistance, oil separation, Properties such as oxidation stability and rust prevention. Flow characteristics are important because grease stays in the bearing.For example, if heat resistance is insufficient, oxidative deterioration is likely to be accelerated. It is inconvenient. Due to oxidative degradation, the lubricant and the thickener may be separated and the function as a grease may be impaired.
  • grease used in wind power generators is usually collected every half year by humans, and the state of parts is measured by measuring the above physicochemical properties and the concentration of solids such as wear powder. I manage.
  • Grease is used for several years, but the chronological change in physicochemical properties is small at the initial stage, gradually increases with the progress of oxidative degradation, and is very accelerated at the end stage. You may not be able to find any signs. Further, if the grease is increased or replaced at an excessive frequency preventively, maintenance costs increase.
  • bearing failure due to wear powder may develop symptoms within a few weeks to a few minutes, so it may not be possible to grasp the signs of a semi-annual inspection.
  • a vibration sensor or the like when detecting a bearing abnormality with a vibration sensor or the like, it is possible to detect the abnormality itself and not a sign of abnormality.
  • One aspect of the present invention is a monitoring system for grease supplied to a mechanical drive unit of a wind power generator.
  • the system is basically composed of an input device, a processing device, a storage device, a server including an output device, and the like.
  • the input device receives measurement data obtained from an optical sensor disposed in at least a part of the grease path, and inputs wind turbine operating parameters if necessary.
  • the processing device generates a physical property parameter of the grease from the measurement data.
  • the storage device stores physical property parameters in time series. The processing device monitors the physical property parameter or predicts the future based on the time-series physical property parameter.
  • the future prediction of the physical property parameter can be performed based on the time-series physical property parameter and the operation parameter.
  • the wind power generator targeted by this method is a wind power generator with an optical sensor, which measures the optical properties of grease used in the components of the wind power generator.
  • the monitoring method is basically executed by a server or the like including an input device, a processing device, a storage device, and an output device.
  • the contents of the processing are based on the first step of receiving the measurement data from the optical sensor, the second step of generating the physical property parameter of the grease from the measurement data, the third step of storing the physical property parameter, and the physical property parameter.
  • the fourth step of monitoring current data of physical property parameters or predicting future data is executed.
  • the fifth step of receiving the operating parameter of the wind power generator is executed, and in the fourth step, based on the past data of the physical property parameter and the past and future data of the operating parameter, Predict future data of physical property parameters.
  • the schematic whole block diagram of a wind power generator Schematic of a wind power generator having an automatic grease supply device. Schematic of bearing parts equipped with automatic grease supply device and optical sensor.
  • the block diagram of the wind power generator which has a grease automatic supply device and an optical sensor.
  • Notations such as “first”, “second”, and “third” in this specification and the like are attached to identify the constituent elements, and do not necessarily limit the number, order, or contents thereof. is not.
  • a number for identifying a component is used for each context, and a number used in one context does not necessarily indicate the same configuration in another context. Further, it does not preclude that a component identified by a certain number also functions as a component identified by another number.
  • the wind power generator according to the embodiment includes an automatic grease supply device and a bearing component including a grease discharge channel.
  • An optical sensor is installed in the grease discharge passage, and the grease of the wind power generator is monitored and diagnosed based on the physical property value (chromaticity) of the grease acquired by the optical sensor.
  • ⁇ Grease diagnosis by color difference is performed as follows. Diagnose the degree of oxidative degradation of grease and contamination with solid particles such as wear powder by color difference measurement. The color of the grease is quantitatively expressed by the three primary colors of light (R, G, B) as measured by the color difference sensor.
  • ⁇ E RGB quantification indexes
  • MCD quantification indexes
  • the change in grease condition depends on the operating condition of the wind power generator. For this reason, various parameters indicating the operating status of the wind power generator are simultaneously acquired, and future characteristic changes of the grease are predicted using these parameters.
  • FIG. 2 shows an extracted nacelle 3 portion of the wind power generator 1 of FIG. Inside the nacelle 3, there are a main shaft 31, a speed increaser 33, a generator 34, bearings such as yaw and pitch (not shown), and grease is supplied from a grease tank 37.
  • a plurality of wind power generators 1 are usually installed in the same site, and these are collectively called a farm 200a.
  • Each wind turbine generator 1 is provided with a sensor in the grease supply system, and sensor signals reflecting the state of the grease are collected in the server 210 in the nacelle 3. Further, the sensor signal obtained from the server 210 of each wind power generator 1 is sent to the aggregation server 220 arranged for each farm 200. Data from the aggregation server 220 is sent to the central server 240 via the network 230. Data from other farms 200b and 200c is also sent to the central server 240. Further, the central server 240 can send an instruction to each wind turbine generator 1 via the aggregation server 220 or the server 210.
  • FIG. 3 is a schematic view of a sensor arranged in a grease supply system.
  • the grease is supplied from the automatic grease supply device 301 to the bearing component 302.
  • the automatic grease supply device 301 is connected to the grease tank 37 and receives supply of grease.
  • the bearing component 302 is, for example, a general part where mechanical contact with the speed increaser 33 or the like occurs, and is not particularly limited.
  • the grease supplied to the bearing component 302 is discharged from a grease discharge portion (drain) 303, for example, as indicated by an arrow in the drawing after being used for a predetermined period.
  • the discharge is performed automatically or manually.
  • An optical sensor 304 is disposed in the vicinity of the grease discharge portion, and optically detects the grease characteristics. Since the drain 303 is located near the end of the grease path, it is considered that the grease in this vicinity is most deteriorated, and it is desirable to arrange the optical sensor 304 around the drain.
  • Grease deteriorates in quality due to use and does not perform its initial function. For this reason, it is necessary to perform maintenance such as replacement depending on the quality degradation state. It is useful in terms of maintenance management efficiency to be able to know the timing of such maintenance at a remote place.
  • FIG. 4 is a flowchart of grease diagnosis by the optical sensor.
  • the process shown in FIG. 4 may be performed by any of the server 210, the aggregation server 220, and the central server 240 in FIG. That is, in the present embodiment, functions such as calculation and control are realized in cooperation with other hardware by executing software stored in the storage device of the server by the processor.
  • a function equivalent to the function configured by software can be realized by hardware such as an FPGA (Field Programmable Gate Array) and an ASIC (Application Specific Integrated Circuit).
  • Measurement is performed by fixed point observation, for example, once a day.
  • a measurement instruction may be given from the central server 240 at any time and performed at an arbitrary timing.
  • the optical sensor measures the chromaticity of the grease (S402).
  • the RGB component of the reflected (or transmitted) light of the grease is detected.
  • the measurement value obtained by the optical sensor is transmitted to a server that performs processing.
  • the color of the grease can be shown as coordinates in a three-dimensional space with the RGB components as axes (color coordinate expression).
  • ⁇ E RGB corresponds to the distance on the color coordinate between the measured grease color and black. A decrease in ⁇ E RGB indicates that the color of the grease approaches black. When the color of grease approaches black, there is a possibility of contamination by solid particles such as wear powder.
  • MCD maximum color difference
  • the above ⁇ E RGB and the maximum color difference MCD are used.
  • ⁇ E RGB exceeds a predetermined threshold (S403).
  • a predetermined threshold S403
  • particle contamination of grease include iron powder mixed into grease due to wear of parts.
  • the RGB components are evenly reduced, in addition to the alteration of the grease itself, it is a state in which mixing of fine particle powder is suspected. If the threshold is exceeded, the operator is instructed to perform grease maintenance (S405).
  • the maximum color difference MCD exceeds a threshold value (S404).
  • the alteration of the grease can be detected by the MCD determination. For example, when the value of B (blue) decreases and MCD increases, the grease is red or yellow, and oxidation is suspected. If the threshold is exceeded, the operator is instructed to perform grease maintenance (S405).
  • the threshold value may be determined by comparing the ⁇ E RGB value and MCD value of the new grease and the deteriorated grease.
  • FIG. 5 shows the measured values after two years from the start of operation.
  • ⁇ E RGB decreased, the maximum color difference increased, and oxidation degradation was promoted.
  • ⁇ E RGB increased as in the wind power generator A, but the maximum color difference was a slight increase, and it was confirmed that there was a suspicion of wear particle contamination.
  • the abnormality of the grease can be detected early using the optical sensor, so that the abnormality of the wind power generator can be detected in advance or early. This is a significant advantage compared with the case where, for example, a vibration sensor or the like is difficult to discover until the abnormality of the apparatus becomes obvious. Further, data from the optical sensor is transmitted to a remote server via a network, so that it is possible to monitor from a remote location and work efficiency is improved.
  • Example 2 shows an example in which the maintenance time is predicted using time-series data obtained from an optical sensor.
  • FIG. 6 shows the nacelle 3 portion of the wind turbine generator 1 of FIG. 1 extracted as in FIG.
  • the same components are denoted by the same reference numerals and description thereof is omitted.
  • An automatic grease supply device 301 is installed in each drive unit in the nacelle 3, for example, the speed increaser 33, the generator 34, the pitch bearing 41, and the slewing bearing 45 to supply grease.
  • An optical sensor 304 is disposed in the drain 303 for discharging grease, and detects color information of the grease.
  • the grease discharged from the drain 303 was measured by the optical sensor 304 every 24 hours using the system of FIG.
  • FIG. 7 plots ⁇ E RGB measurement values at the time of the start of operation, after 0.5 years, after 1 year, and after 1.5 years, with the operation time of the wind turbine generator 1 on the horizontal axis. Is. ⁇ E RGB is considered to reflect the solid particle contamination of the grease.
  • the threshold value of ⁇ E RGB which requires grease maintenance, is 350, and when an approximate curve is set for the transition time, ⁇ E RGB is predicted to exceed the threshold value in about 2.2 years.
  • FIG. 8 plots the maximum color difference MCD measurement value at the start of operation, after 0.5 years, after 1 year, and after 1.5 years, with the operation time of the wind turbine generator 1 on the horizontal axis. It is a thing.
  • the maximum color difference MCD is considered to reflect the oxidative degradation of the grease.
  • the threshold for MCD, which requires grease maintenance, was 100, and when an approximate curve was set for the operating time, the MCD was predicted to exceed the threshold in about 2.4 years.
  • artificial fluctuations in operating conditions include a period during which equipment is stopped for inspection and operation adjustment for power generation amount adjustment.
  • These fluctuation parameters can be acquired as control parameters of the wind turbine generator 1.
  • factors that fluctuate the driving situation due to the natural world include wind speed and other weather, temperature, and humidity. These fluctuation factors of the driving situation can be measured by various sensors, respectively. Therefore, by reflecting these operating conditions, the state of the grease can be determined and predicted more accurately.
  • These temperature sensors and humidity sensors are preferably installed in an environment close to grease, such as around the automatic grease supply device 301 and in the nacelle 3, and like the optical sensor 304, the central server 220 is connected via the server 210. Or sent to the central server 240. Further, the control parameters of the wind turbine generator 1 can be obtained from the server 210, the aggregation server 220, or the central server 240 that performs the control.
  • FIG. 9 is a flow chart of a grease state prediction method reflecting the operation state.
  • the grease supply mechanism to the bearing unit is targeted, and the signal from the optical sensor is mainly focused on solid particle contamination as one ⁇ E RGB value of the physical property parameter. did.
  • an operation parameter indicating an operation state a control parameter for the rotational speed R (rpm) of the shaft is used.
  • the physical property parameter and the operation parameter are not limited to this, and various other parameters can be used.
  • the optical sensor 304 is periodically measured, and when the measurement time is reached (S901), the optical sensor 304 measures chromaticity (S902).
  • the data of various sensors are collected in the central server 240 and collectively processed here.
  • the present invention is not limited to this.
  • the central server 240 calculates ⁇ E RGB from the optical sensor data (S903), and obtains the parameter of the rotational speed R of the shaft (S904).
  • the temporal resolution of R may be the same as or shorter than the data cycle of the optical sensor.
  • FIGS. 10A and 10B are graphs showing an example of predicting and displaying the value of the future 1002 based on the data of the wind power generator 1 for the past year 1001.
  • FIG. The past data 1003 for one year is an actual measurement value.
  • Future data 1004A and 1004B are predicted values.
  • FIG. 10B the future driving situation has changed, and the rotational speed R has been doubled over the past year.
  • the prediction data of ⁇ E RGB does not change as in the past year, and the decrease rate becomes large as shown in FIG. 10B, for example.
  • the timing at which the physical property parameter indicating the grease quality such as ⁇ E RGB exceeds the threshold value is more accurately determined. It becomes possible. That is, the future physical property parameter can be determined more accurately based on the past physical property parameter, the past operation parameter, and the future operation parameter.
  • the prediction system can be enhanced by similarly using the parameter representing the operating state for the prediction of the physical property parameter indicating the grease quality.
  • an automatic grease supply mechanism is used. Monitoring is performed regularly by installing a sensor in the grease discharge section provided. In addition, accurate predictive diagnosis can be performed by monitoring parameters of the operating condition of the wind power generator. In addition, the wind generator grease can be constantly monitored remotely via the network. For this reason, since the bearing sign is known early and the stop time of the wind power generator is shortened, the maintenance cost is reduced and the power generation amount is improved.
  • the present invention is not limited to the above-described embodiment, and includes various modifications.
  • a part of the configuration of one embodiment can be replaced with the configuration of another embodiment, and the configuration of another embodiment can be added to the configuration of one embodiment.
  • the present invention can be used for maintenance of wind power generators.

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Abstract

The present invention carries out steady monitoring and predictive diagnosis of grease used for important rotating components (bearings) of a wind power generator, such as the main shaft, generator, yaw bearing, and pitch bearing. The present invention is a system for monitoring grease supplied to a mechanical drive unit of a wind power generator. This system is provided with a server, or the like, essentially comprising an input device, processing device, storage device, and output device. The input device receives measurement data obtained from an optical sensor disposed in at least a part of a grease route and receives an operation parameter for the wind power generator. The processing device generates a physical parameter for the grease from the measurement data. The storage device stores the physical parameter as a time series. The processing device predicts a future physical parameter on the basis of the physical parameter time series and the operation parameter.

Description

風力発電機のグリースの監視システムおよび方法Wind generator grease monitoring system and method
　本発明は、風力発電装置に係り、特に、ナセル内の潤滑油やグリースの維持管理に対応可能な風力発電装置に関する。 The present invention relates to a wind power generator, and more particularly, to a wind power generator capable of supporting maintenance and management of lubricating oil and grease in a nacelle.
　近年、地球温暖化防止のため自然エネルギーを利用した発電システムが注目を浴びており、中でも風力発電装置については幅広く普及されている。 In recent years, a power generation system using natural energy has been attracting attention for the prevention of global warming, and wind power generators are particularly widespread.
　風力発電装置のナセル内には、動力伝達部の潤滑用に潤滑油を貯留するオイルタンクが設置される。例えば、特許文献１には、簡易な構造でプラットフォームを支持すると共に、ナセル内からの潤滑油の漏洩に対応でき、信頼性を向上し得る風力発電装置を提供するための技術が開示されている。 An oil tank for storing lubricating oil is installed in the nacelle of the wind power generator for lubricating the power transmission unit. For example, Patent Document 1 discloses a technique for providing a wind turbine generator that can support a platform with a simple structure, can cope with leakage of lubricating oil from the nacelle, and can improve reliability. .
　また、油の状態を判定する技術については、例えば特許文献２や特許文献３に開示がある。 Further, techniques for determining the state of oil are disclosed in, for example, Patent Document 2 and Patent Document 3.
特開２０１７－２７２９号公報JP 2017-2729 A ＷＯ２０１０－１５０５２６号公報WO2010-150526 特開２０１２－１１７９５１号公報JP 2012-117951 A
　図１に本発明が対象とする風力発電装置の概略全体構成図を示す。図１では、ナセル３内に配される各機器を点線にて示している。図１に示すように、風力発電装置１は、風を受けて回転するブレード５、ブレード５を支持するハブ４、ナセル３、及びナセル３を回動可能に支持するタワー２を備える。 FIG. 1 shows a schematic overall configuration diagram of a wind turbine generator targeted by the present invention. In FIG. 1, each device arranged in the nacelle 3 is indicated by a dotted line. As shown in FIG. 1, the wind turbine generator 1 includes a blade 5 that rotates by receiving wind, a hub 4 that supports the blade 5, a nacelle 3, and a tower 2 that rotatably supports the nacelle 3.
　ナセル３内に、ハブ４に接続されハブ４と共に回転する主軸３１、主軸３１に連結されるシュリンクディスク３２、シュリンクディスク３２を介して主軸３１に接続され回転速度を増速する増速機３３、及びカップリング３８を介して増速機３３により増速された回転速度で回転子を回転させて発電運転する発電機３４を備えている。 In the nacelle 3, a main shaft 31 connected to the hub 4 and rotating together with the hub 4, a shrink disk 32 connected to the main shaft 31, a speed increasing device 33 connected to the main shaft 31 via the shrink disk 32 and increasing the rotation speed, And a generator 34 that performs a power generation operation by rotating the rotor at a rotational speed increased by the speed increaser 33 via the coupling 38.
　ブレード５の回転エネルギーを発電機３４に伝達する部位は、動力伝達部と呼ばれ、本実施例では、主軸３１、シュリンクディスク３２、増速機３３及びカップリング３８が動力伝達部に含まれる。そして、増速機３３及び発電機３４は、メインフレーム３５上に保持されている。また、メインフレーム３５上には、動力伝達部の潤滑用にグリースを貯留するグリースタンク３７が設置されている。 The part that transmits the rotational energy of the blade 5 to the generator 34 is called a power transmission unit. In this embodiment, the main shaft 31, the shrink disk 32, the speed increaser 33, and the coupling 38 are included in the power transmission unit. The speed increaser 33 and the generator 34 are held on the main frame 35. A grease tank 37 that stores grease for lubricating the power transmission unit is installed on the main frame 35.
　また、ナセル３内には、ナセル隔壁３０よりも風上側にラジエータ３６が配されている。図１に示す風力発電装置１は、一例として５ＭＷ級の風力発電装置を示している。これに対し、例えば、２ＭＷ級の風力発電装置では、ラジエータ３６は、ナセル３の上面に設けられた外気導入口（図示せず）とナセル内空気排出口（図示せず）との間に配される。 In the nacelle 3, a radiator 36 is disposed on the windward side of the nacelle partition wall 30. The wind power generator 1 shown in FIG. 1 shows a 5 MW class wind power generator as an example. On the other hand, for example, in a 2 MW class wind power generator, the radiator 36 is arranged between an outside air inlet (not shown) provided on the upper surface of the nacelle 3 and an air outlet (not shown) in the nacelle. Is done.
　風力発電機では、多くの回転部品でグリースが使用されている。図１において、主軸３１、発電機３４、ヨー、ピッチなどの軸受で使用されるグリースは、経時的な劣化と摩耗粉などの固形分による汚染による潤滑性能の低下が起こり、風力発電機の故障リスクが増大する。なお、風速に応じて翼の角度を変え、出力を制御するのが翼のピッチ制御であり、風向きに応じて首を振るのがヨー制御である。いずれも、可動部分については、グリースを供給する必要がある。 In wind power generators, grease is used in many rotating parts. In FIG. 1, grease used in bearings such as the main shaft 31, the generator 34, the yaw, and the pitch deteriorates with time and deteriorates in lubrication performance due to contamination by solid content such as wear powder, resulting in failure of the wind power generator. Risk increases. The blade pitch control changes the blade angle according to the wind speed and controls the output, and the yaw control swings the head according to the wind direction. In any case, it is necessary to supply grease to the movable part.
　グリースは、液体の潤滑剤と増ちょう剤を基材とし、酸化防止剤、摩耗防止剤、極圧剤などの添加剤を配合したものである。増ちょう剤は、液体であるベースオイルをグリースのようなゲル状にする為に混ぜるものである。極圧剤は、金属の二面の間の摩擦，摩耗の減少や，焼付の防止のために潤滑油に加えられるものである。 Grease is based on a liquid lubricant and thickener, and contains additives such as antioxidants, antiwear agents, and extreme pressure agents. The thickener is used to mix the base oil, which is a liquid, into a gel like a grease. Extreme pressure agents are added to lubricants to reduce friction and wear between two metal surfaces and to prevent seizure.
　経時的な劣化とは、グリースの仕様に伴う、物理化学的性質の経時変化のことを示し、具体的には、流動特性（せん断速度依存性および時間依存性）、耐熱性、油分離性、酸化安定性、さび止め性などの性質である。流動特性は、グリースが軸受内にとどまるために重要であり、たとえば、耐熱性が不足すると酸化劣化が促進されやすく、使用にともなう熱負荷により、グリースの粘度が低下すると、グリースが軸受内にとどまらず、不都合である。酸化劣化によって、潤滑剤と増ちょう剤が分離し、グリースとしての機能が損なわれることがある。また、酸化劣化が進むと、カルボン酸化合物や、酸性の添加剤の分解生成物の濃度が増加して腐食反応の触媒となるため、さび止めの効果が弱まり、軸受の腐食が起こりやすくなる。 Deterioration over time refers to changes in physicochemical properties over time according to grease specifications. Specifically, flow characteristics (shear rate dependence and time dependence), heat resistance, oil separation, Properties such as oxidation stability and rust prevention. Flow characteristics are important because grease stays in the bearing.For example, if heat resistance is insufficient, oxidative deterioration is likely to be accelerated. It is inconvenient. Due to oxidative degradation, the lubricant and the thickener may be separated and the function as a grease may be impaired. Further, as oxidation deterioration progresses, the concentration of carboxylic acid compounds and decomposition products of acidic additives increases and becomes a catalyst for a corrosion reaction, so that the effect of rust prevention is weakened, and the corrosion of the bearing is likely to occur.
　摩耗粉などの固形分による汚染は、グリースの潤滑面に入り込むと、軸受の摩耗を促進し、さらにグリース中の摩耗粉が増える。特に、数十ミクロン以上の硬質金属粒子は、軸受の致命的な故障の原因となることが知られている。 When contamination due to solids such as wear powder enters the lubricated surface of the grease, the wear of the bearing is accelerated and the wear powder in the grease further increases. In particular, it is known that hard metal particles of several tens of microns or more cause a fatal failure of the bearing.
　従って、通常、風力発電機で使用されているグリースは、たとえば半年毎に、人間が少量を採取して、上記物理化学的性質や摩耗粉などの固形分濃度を計測することによって部品の状態を管理している。 Therefore, grease used in wind power generators is usually collected every half year by humans, and the state of parts is measured by measuring the above physicochemical properties and the concentration of solids such as wear powder. I manage.
　グリースは、数年間にわたって使用されるが、物理化学的性質の経時変化は、初期では変化が小さく、酸化劣化の進行とともに次第に加速し、末期には非常に加速されるため、半年毎の点検では予兆を発見できないことがある。また、予防的に過剰な頻度でグリースアップやグリース交換を行うことは、保守コスト増大につながる。 Grease is used for several years, but the chronological change in physicochemical properties is small at the initial stage, gradually increases with the progress of oxidative degradation, and is very accelerated at the end stage. You may not be able to find any signs. Further, if the grease is increased or replaced at an excessive frequency preventively, maintenance costs increase.
　また、摩耗粉による軸受故障は、数週間から数分の間に症状が進行することがあるため、半年毎の点検では予兆を把握できないことがある。例えば、振動センサなどで軸受けの異常を検出しようと場合、検出できるのは異常そのものであり、異常の予兆ではない場合がある。 Also, bearing failure due to wear powder may develop symptoms within a few weeks to a few minutes, so it may not be possible to grasp the signs of a semi-annual inspection. For example, when detecting a bearing abnormality with a vibration sensor or the like, it is possible to detect the abnormality itself and not a sign of abnormality.
　最近では、風力発電機が大型化し、部品が高額なため、故障時の保守コストが増加している。今後は洋上風車も増加するため、リアルタイム遠隔監視技術の需要が高まっている。したがって、風力発電機の、主軸、発電機、ヨー、ピッチなどの重要な回転部品（軸受）で使用されるグリースの定常的な監視および予兆診断が重要となる。 Recently, since the wind power generator has become larger and the parts are expensive, the maintenance cost at the time of failure has increased. As the number of offshore wind turbines increases in the future, the demand for real-time remote monitoring technology is increasing. Therefore, steady monitoring and predictive diagnosis of grease used in important rotating parts (bearings) such as the main shaft, generator, yaw, and pitch of the wind power generator are important.
　本発明の一側面は、風力発電機の機械的駆動部に供給されるグリースの監視システムである。当該システムは、基本的に入力装置、処理装置、記憶装置、および出力装置を備えるサーバ等で構成される。入力装置は、グリースの経路の少なくとも一部に配置された光学式センサから得られる、測定データが入力され、また、必要な場合には、風力発電機の運転パラメータが入力される。処理装置は、測定データからグリースの物性パラメータを生成する。記憶装置は、物性パラメータを時系列的に格納する。処理装置は、時系列的な物性パラメータに基づいて、物性パラメータの監視もしくは将来的な予測を行なうものである。 One aspect of the present invention is a monitoring system for grease supplied to a mechanical drive unit of a wind power generator. The system is basically composed of an input device, a processing device, a storage device, a server including an output device, and the like. The input device receives measurement data obtained from an optical sensor disposed in at least a part of the grease path, and inputs wind turbine operating parameters if necessary. The processing device generates a physical property parameter of the grease from the measurement data. The storage device stores physical property parameters in time series. The processing device monitors the physical property parameter or predicts the future based on the time-series physical property parameter.
　また、運転パラメータを利用するさらに具体的な例では、時系列的な物性パラメータと、運転パラメータに基づいて、物性パラメータの将来的な予測を行なうことができる。 Further, in a more specific example using the operation parameter, the future prediction of the physical property parameter can be performed based on the time-series physical property parameter and the operation parameter.
　本発明の他の一側面は、風力発電機のグリースの監視方法である。この方法が対象とする風力発電機は、光学式センサを備えた風力発電機であって、光学式センサが風力発電機の部品で使用されるグリースの光学的特性を測定するものである。監視方法は、基本的に入力装置、処理装置、記憶装置、および出力装置を備えるサーバ等で実行される。処理の内容は、光学式センサからの測定データを受信する第１のステップ、測定データからグリースの物性パラメータを生成する第２のステップ、物性パラメータを記憶する第３のステップ、物性パラメータに基づいて、物性パラメータの現在のデータを監視し、または、将来のデータを予測する第４のステップを実行する。 Another aspect of the present invention is a method for monitoring grease of a wind power generator. The wind power generator targeted by this method is a wind power generator with an optical sensor, which measures the optical properties of grease used in the components of the wind power generator. The monitoring method is basically executed by a server or the like including an input device, a processing device, a storage device, and an output device. The contents of the processing are based on the first step of receiving the measurement data from the optical sensor, the second step of generating the physical property parameter of the grease from the measurement data, the third step of storing the physical property parameter, and the physical property parameter. The fourth step of monitoring current data of physical property parameters or predicting future data is executed.
　さらに具体的な例では、風力発電機の運転パラメータを受信する第５のステップを実行し、第４のステップでは、物性パラメータの過去のデータと、運転パラメータの過去および将来のデータに基づいて、物性パラメータの将来のデータを予測する。 In a more specific example, the fifth step of receiving the operating parameter of the wind power generator is executed, and in the fourth step, based on the past data of the physical property parameter and the past and future data of the operating parameter, Predict future data of physical property parameters.
　風力発電機の、主軸、発電機、ヨー、ピッチなどの重要な回転部品（軸受）で使用されるグリースの定常的な監視および予兆診断が可能となる。 ∙ Regular monitoring and predictive diagnosis of grease used in important rotating parts (bearings) such as the main shaft, generator, yaw, and pitch of wind power generators are possible.
風力発電装置の概略全体構成図。The schematic whole block diagram of a wind power generator. グリース自動供給デバイスを有する風力発電機の概略図。Schematic of a wind power generator having an automatic grease supply device. グリース自動供給デバイス、光学式センサを備えた軸受部品の概略図。Schematic of bearing parts equipped with automatic grease supply device and optical sensor. 光学式センサによるグリース劣化診断フロー図。The grease deterioration diagnosis flow chart by an optical sensor. 運転開始から２年経過後の計測値を示す表図。The table which shows the measured value after two years progress from a driving | operation start. グリース自動供給デバイスおよび光学センサを有する風力発電機の構成図。The block diagram of the wind power generator which has a grease automatic supply device and an optical sensor. 使用時間に対するΔＥＲＧＢの変化を示すグラフ図。The graph which shows the change of (DELTA) E RGB with respect to use time. 使用時間に対する最大色差の変化を示すグラフ図。The graph which shows the change of the largest color difference with respect to use time. 光学式センサによるグリース劣化予想フロー図。Grease deterioration prediction flow diagram by optical sensor. 光学式センサによるグリース劣化予想を示すグラフ図。The graph figure which shows the grease deterioration estimation by an optical sensor. 光学式センサによるグリース劣化予想を示すグラフ図。The graph figure which shows the grease deterioration estimation by an optical sensor.
　以下、実施の形態について、図面を用いて詳細に説明する。ただし、本発明は以下に示す実施の形態の記載内容に限定して解釈されるものではない。本発明の思想ないし趣旨から逸脱しない範囲で、その具体的構成を変更し得ることは当業者であれば容易に理解される。 Hereinafter, embodiments will be described in detail with reference to the drawings. However, the present invention is not construed as being limited to the description of the embodiments below. Those skilled in the art will readily understand that the specific configuration can be changed without departing from the spirit or the spirit of the present invention.
　以下に説明する発明の構成において、同一部分又は同様な機能を有する部分には同一の符号を異なる図面間で共通して用い、重複する説明は省略することがある。 In the structure of the invention described below, the same portions or portions having similar functions are denoted by the same reference numerals in different drawings, and redundant description may be omitted.
　同一あるいは同様な機能を有する要素が複数ある場合には、同一の符号に異なる添字を付して説明する場合がある。ただし、複数の要素を区別する必要がない場合には、添字を省略して説明する場合がある。 When there are a plurality of elements having the same or similar functions, there may be cases where the same reference numerals are attached with different subscripts. However, when there is no need to distinguish between a plurality of elements, the description may be omitted.
　本明細書等における「第１」、「第２」、「第３」などの表記は、構成要素を識別するために付するものであり、必ずしも、数、順序、もしくはその内容を限定するものではない。また、構成要素の識別のための番号は文脈毎に用いられ、一つの文脈で用いた番号が、他の文脈で必ずしも同一の構成を示すとは限らない。また、ある番号で識別された構成要素が、他の番号で識別された構成要素の機能を兼ねることを妨げるものではない。 Notations such as “first”, “second”, and “third” in this specification and the like are attached to identify the constituent elements, and do not necessarily limit the number, order, or contents thereof. is not. In addition, a number for identifying a component is used for each context, and a number used in one context does not necessarily indicate the same configuration in another context. Further, it does not preclude that a component identified by a certain number also functions as a component identified by another number.
　図面等において示す各構成の位置、大きさ、形状、範囲などは、発明の理解を容易にするため、実際の位置、大きさ、形状、範囲などを表していない場合がある。このため、本発明は、必ずしも、図面等に開示された位置、大きさ、形状、範囲などに限定されない。 The position, size, shape, range, etc. of each component shown in the drawings and the like may not represent the actual position, size, shape, range, etc. in order to facilitate understanding of the invention. For this reason, the present invention is not necessarily limited to the position, size, shape, range, and the like disclosed in the drawings and the like.
　実施例で説明される技術の概要を説明する。実施例の風力発電機は、グリースの自動供給デバイスと、グリースの排出流路を備えた軸受部品を有する。グリース排出流路中には、光学式センサを設置し、光学式センサによって取得されるグリース物性値（色度）に基づいて、風力発電機のグリースを監視、診断する。 The outline of the technology described in the examples will be described. The wind power generator according to the embodiment includes an automatic grease supply device and a bearing component including a grease discharge channel. An optical sensor is installed in the grease discharge passage, and the grease of the wind power generator is monitored and diagnosed based on the physical property value (chromaticity) of the grease acquired by the optical sensor.
　色差によるグリースの診断は以下のように行う。色差測定により、グリースの酸化劣化度と、摩耗粉などの固形粒子による汚染を診断する。色差センサによる測定で、グリースの色を、光の三原色（Ｒ・Ｇ・Ｂ）で定量的に表す。 ¡Grease diagnosis by color difference is performed as follows. Diagnose the degree of oxidative degradation of grease and contamination with solid particles such as wear powder by color difference measurement. The color of the grease is quantitatively expressed by the three primary colors of light (R, G, B) as measured by the color difference sensor.
　本実施例では、定量化の指標は２種類あり、ΔＥＲＧＢとＭＣＤである。グリースの酸化劣化が進行している場合には、三原色座標のうち、Ｂ値が大きく低下し、ＭＣＤ値が大きくなる。固形粒子による汚染が進行している場合には、三原色座標の値が三色ともに減少し、ΔＥＲＧＢ が減少するとともにＭＣＤ値は微増もしくは微減である。グリース新品の測定値と、使用により劣化したグリースまたは、酸化試験や強制的に汚染させたグリースサンプルとの測定値より診断の閾値を定め、閾値を超えた場合に、グリース補充や軸受点検などのメンテナンスを行うことができる。 In the present embodiment, there are two types of quantification indexes, ΔE RGB and MCD. When the oxidative deterioration of the grease is progressing, the B value greatly decreases and the MCD value increases among the three primary color coordinates. When contamination by solid particles is progressing, the values of the three primary color coordinates are decreased for all three colors, ΔE RGB is decreased, and the MCD value is slightly increased or decreased. The diagnostic threshold is determined based on the measured value of the new grease and the grease deteriorated by use or the grease sample that has been forcibly contaminated by oxidation test. Maintenance can be performed.
　また、グリースの状態の変化は、風力発電機の運転状況にも依存する。このため、風力発電機の運転状況を示す種々のパラメータを同時に取得し、これらのパラメータを用いて、グリースの将来的な特性変化を予測する。 Also, the change in grease condition depends on the operating condition of the wind power generator. For this reason, various parameters indicating the operating status of the wind power generator are simultaneously acquired, and future characteristic changes of the grease are predicted using these parameters.
　（１．システム全体構成）
　図２により、実施例１の酸化劣化と粒子汚染の診断を行うシステムを説明する。図２には説明のため、図１の風力発電装置１のナセル３部分を抽出して示している。ナセル３内部には、主軸３１、増速機３３、発電機３４、図示しないヨー、ピッチなどの軸受があり、これらにはグリースタンク３７からグリースが供給される。 (1. Overall system configuration)
With reference to FIG. 2, a system for diagnosing oxidative degradation and particle contamination of Example 1 will be described. For the sake of explanation, FIG. 2 shows an extracted nacelle 3 portion of the wind power generator 1 of FIG. Inside the nacelle 3, there are a main shaft 31, a speed increaser 33, a generator 34, bearings such as yaw and pitch (not shown), and grease is supplied from a grease tank 37.
　図２に示すように、風力発電装置１は通常複数が同一敷地内に設置され、これをまとめてファーム２００ａなどと呼ばれる。それぞれの風力発電装置１には、グリースの供給系統にセンサが設置され、グリースの状態を反映したセンサ信号は、ナセル３内のサーバ２１０に集約される。また、各風力発電装置１のサーバ２１０から得られるセンサ信号は、ファーム２００ごとに配置される集約サーバ２２０に送られる。集約サーバ２２０からのデータは、ネットワーク２３０を介して中央サーバ２４０へ送られる。中央サーバ２４０へは、他のファーム２００ｂや２００ｃからのデータも送られる。また、中央サーバ２４０は、集約サーバ２２０やサーバ２１０を介して、各風力発電装置１に指示を送ることができる。 As shown in FIG. 2, a plurality of wind power generators 1 are usually installed in the same site, and these are collectively called a farm 200a. Each wind turbine generator 1 is provided with a sensor in the grease supply system, and sensor signals reflecting the state of the grease are collected in the server 210 in the nacelle 3. Further, the sensor signal obtained from the server 210 of each wind power generator 1 is sent to the aggregation server 220 arranged for each farm 200. Data from the aggregation server 220 is sent to the central server 240 via the network 230. Data from other farms 200b and 200c is also sent to the central server 240. Further, the central server 240 can send an instruction to each wind turbine generator 1 via the aggregation server 220 or the server 210.
　（２.センサ配置）
　図３は、グリースの供給系統に配置されたセンサの模式図である。グリースは、グリース自動供給デバイス３０１から軸受部品３０２に供給される。グリース自動供給デバイス３０１は、グリースタンク３７に接続されてグリースの供給を受ける。軸受部品３０２は、例えば増速機３３その他の機械的な接触が生じる部位一般であり、特に制限するものではない。 (2. Sensor arrangement)
FIG. 3 is a schematic view of a sensor arranged in a grease supply system. The grease is supplied from the automatic grease supply device 301 to the bearing component 302. The automatic grease supply device 301 is connected to the grease tank 37 and receives supply of grease. The bearing component 302 is, for example, a general part where mechanical contact with the speed increaser 33 or the like occurs, and is not particularly limited.
　軸受部品３０２に供給されたグリースは、所定期間使用された後、例えば図中矢印のように、グリース排出部（ドレイン）３０３から排出される。排出は自動もしくは手動で行われる。グリース排出部付近には光学式センサ３０４が配置されており、グリースの特性を光学的に検出する。ドレイン３０３はグリース経路の末端付近に位置するので、この付近のグリースは、最も劣化が進んでいると考えられ、ドレインの周辺に光学式センサ３０４を配置しておくのが望ましい。 The grease supplied to the bearing component 302 is discharged from a grease discharge portion (drain) 303, for example, as indicated by an arrow in the drawing after being used for a predetermined period. The discharge is performed automatically or manually. An optical sensor 304 is disposed in the vicinity of the grease discharge portion, and optically detects the grease characteristics. Since the drain 303 is located near the end of the grease path, it is considered that the grease in this vicinity is most deteriorated, and it is desirable to arrange the optical sensor 304 around the drain.
　グリースは、使用により品質が劣化し、初期の機能を果たさなくなる。このため、品質の劣化状況に応じて、交換等のメンテナンスを行う必要がある。このようなメンテナンスのタイミングを、遠隔地で知ることができるようにすることは、保守管理の効率上有用である。 Grease deteriorates in quality due to use and does not perform its initial function. For this reason, it is necessary to perform maintenance such as replacement depending on the quality degradation state. It is useful in terms of maintenance management efficiency to be able to know the timing of such maintenance at a remote place.
　（３.グリース診断のフロー）
　図４は、光学式センサによるグリース診断のフロー図である。図４で示す処理は、図２のサーバ２１０，集約サーバ２２０，中央サーバ２４０のいずれで行ってもよい。すなわち、本実施例では計算や制御等の機能は、サーバの記憶装置に格納されたソフトウェアがプロセッサによって実行されることで、定められた処理を他のハードウェアと協働して実現される。なお、ソフトウェアで構成した機能と同等の機能は、FPGA（Field Programmable Gate Array）、ASIC（Application Specific Integrated Circuit）などのハードウェアでも実現できる。 (3. Flow of grease diagnosis)
FIG. 4 is a flowchart of grease diagnosis by the optical sensor. The process shown in FIG. 4 may be performed by any of the server 210, the aggregation server 220, and the central server 240 in FIG. That is, in the present embodiment, functions such as calculation and control are realized in cooperation with other hardware by executing software stored in the storage device of the server by the processor. A function equivalent to the function configured by software can be realized by hardware such as an FPGA (Field Programmable Gate Array) and an ASIC (Application Specific Integrated Circuit).
　最初にグリースの光学的測定の準備を行う（Ｓ４０１）。測定は例えば１日１回のように定点観測で行う。あるいは、中央サーバ２４０から随時測定指示を行って任意のタイミングで行ってもよい。 First, preparation for optical measurement of grease is performed (S401). Measurement is performed by fixed point observation, for example, once a day. Alternatively, a measurement instruction may be given from the central server 240 at any time and performed at an arbitrary timing.
　つぎに、光学式センサはグリースの色度測定を行う（Ｓ４０２）。光学式センサによるグリースの色度測定については、例えば特許文献２にも記載があるが、グリースの反射（あるいは透過）光のＲＧＢ成分を検出する。周知のように、色の表現法のひとつとして、赤 (Red)、緑 (Green)、青 (Blue) （ＲＧＢ成分）の三つの原色を混ぜて色彩を表現することができる。 Next, the optical sensor measures the chromaticity of the grease (S402). Regarding the measurement of chromaticity of grease by an optical sensor, for example, as described in Patent Document 2, the RGB component of the reflected (or transmitted) light of the grease is detected. As is well known, as one of the color expression methods, it is possible to express colors by mixing three primary colors of red, green, and blue (RGB components).
　光学式センサで得られた測定値は、処理を行うサーバに送信される。グリースの色彩は、ＲＧＢ成分の其々を軸とした３次元空間上の座標として示すことができる（色座標表現）。ここで、ΔＥＲＧＢというパラメータは、以下のように定義できる。
  
  　ΔＥＲＧＢ＝√（Ｒ２＋Ｇ2＋Ｂ2）
  
　なお、255階調の色座標では、（0,0,0）が黒、（255,255,255）が白となり、（0,255,255）がシアン、（0,255,0）が緑、（255,255,0）が黄、（255,0,0）が赤、（255,0,255）がマゼンダとなる。ΔＥＲＧＢは、測定したグリースの色と黒との色座標上の距離に相当する。ΔＥＲＧＢが小さくなるということは、グリースの色が黒に近づくことを示す。グリースの色が黒に近づく場合には、摩耗粉などの固形粒子による汚染の可能性がある。 The measurement value obtained by the optical sensor is transmitted to a server that performs processing. The color of the grease can be shown as coordinates in a three-dimensional space with the RGB components as axes (color coordinate expression). Here, the parameter ΔE RGB can be defined as follows.

ΔE RGB = √ (R 2 + G 2 + B 2 )

Note that with 255 color coordinates, (0,0,0) is black, (255,255,255) is white, (0,255,255) is cyan, (0,255,0) is green, (255,255,0) is yellow, 255,0,0) is red, and (255,0,255) is magenta. ΔE RGB corresponds to the distance on the color coordinate between the measured grease color and black. A decrease in ΔE RGB indicates that the color of the grease approaches black. When the color of grease approaches black, there is a possibility of contamination by solid particles such as wear powder.
　また、最大色差ＭＣＤというパラメータを導入する。ＭＣＤは、ＲＧＢ値における最大値と最小値の差であり、色味の変化を知ることができる。 Also, a parameter called maximum color difference MCD is introduced. MCD is the difference between the maximum value and the minimum value in RGB values, and the change in color can be known.
　本実施例のグリース診断では、上記ΔＥＲＧＢと最大色差ＭＣＤを用いる。まず、ΔＥＲＧＢが所定の閾値を超えたかどうかを判定する（Ｓ４０３）。これにより、グリースの粒子汚染を検出することができる。粒子汚染の原因としては、部品の磨耗によりグリースに混入する鉄粉などがある。特に、ＲＧＢ成分が均等に低下している場合には、グリースそのものの変質以外に、微粒子粉の混入が疑われる状態である。閾値を超えた場合は、グリースのメンテナンスを行うようにオペレータに指示する（Ｓ４０５）。 In the grease diagnosis of this embodiment, the above ΔE RGB and the maximum color difference MCD are used. First, it is determined whether or not ΔE RGB exceeds a predetermined threshold (S403). Thereby, particle contamination of grease can be detected. Causes of particle contamination include iron powder mixed into grease due to wear of parts. In particular, when the RGB components are evenly reduced, in addition to the alteration of the grease itself, it is a state in which mixing of fine particle powder is suspected. If the threshold is exceeded, the operator is instructed to perform grease maintenance (S405).
　次に、最大色差ＭＣＤが閾値を越えたかどうかを判定する（Ｓ４０４）。ＭＣＤの判定により、グリースの変質を検出することができる。例えば、Ｂ（青）の値が低下しＭＣＤが増大するということは、グリースが赤色もしくは黄色を呈し、酸化が疑われる状態である。閾値を超えた場合は、グリースのメンテナンスを行うようにオペレータに指示する（Ｓ４０５）。 Next, it is determined whether or not the maximum color difference MCD exceeds a threshold value (S404). The alteration of the grease can be detected by the MCD determination. For example, when the value of B (blue) decreases and MCD increases, the grease is red or yellow, and oxidation is suspected. If the threshold is exceeded, the operator is instructed to perform grease maintenance (S405).
　なお、閾値の設定については、新品のグリースと劣化後のグリースのΔＥＲＧＢ値、ＭＣＤ値を比較するなどして決めればよい。 The threshold value may be determined by comparing the ΔE RGB value and MCD value of the new grease and the deteriorated grease.
　（４.グリース診断結果例）
　風力発電装置Ａと風力発電装置Ｂについて、発電機軸受にグリース自動供給デバイス３０１を設置し、グリースのドレイン３０３に光学式センサ３０４をそれぞれ設置した。風力発電装置Ａと風力発電装置Ｂについて、ドレイン３０３から排出されたグリースを、光学式センサ３０４で２４時間毎に計測した。 (4. Example of grease diagnosis results)
For the wind power generator A and the wind power generator B, an automatic grease supply device 301 was installed on the generator bearing, and an optical sensor 304 was installed on the grease drain 303. For the wind power generator A and the wind power generator B, the grease discharged from the drain 303 was measured every 24 hours by the optical sensor 304.
　図５に運転開始から２年経過後の計測値を示す。風力発電装置Ａでは、ΔＥＲＧＢが減少し、かつ、最大色差が増大し、酸化劣化が促進していたことを確認した。風力発電装置Ｂでは、風力発電装置Ａと同様にΔＥＲＧＢが増大していたが、最大色差はわずかな増加であり、摩耗粒子汚染の疑いがあることを確認した。 FIG. 5 shows the measured values after two years from the start of operation. In the wind power generator A, it was confirmed that ΔE RGB decreased, the maximum color difference increased, and oxidation degradation was promoted. In the wind power generator B, ΔE RGB increased as in the wind power generator A, but the maximum color difference was a slight increase, and it was confirmed that there was a suspicion of wear particle contamination.
　以上のように、本実施例によると光学式のセンサを用いてグリースの異常を早期検出できるため、風力発電装置の異常を未然あるいは早期に発見することができる。これは、例えば振動センサ等では、装置の異常が顕在化してからでないと発見が困難であるのに比べて、顕著な利点である。また、光学式のセンサからのデータは、ネットワークを介して遠隔地のサーバに送信することで、遠隔地からのモニタが可能となり、作業効率が向上する。 As described above, according to the present embodiment, the abnormality of the grease can be detected early using the optical sensor, so that the abnormality of the wind power generator can be detected in advance or early. This is a significant advantage compared with the case where, for example, a vibration sensor or the like is difficult to discover until the abnormality of the apparatus becomes obvious. Further, data from the optical sensor is transmitted to a remote server via a network, so that it is possible to monitor from a remote location and work efficiency is improved.
　実施例２では、光学式センサからえられた時系列データを用いて、メンテナンス時期の予測を行う例を示す。 Example 2 shows an example in which the maintenance time is predicted using time-series data obtained from an optical sensor.
　図６は、図２と同様、図１の風力発電装置１のナセル３部分を抽出して示している。同じ構成は同じ符号を付して説明を省略する。ナセル３内部の各駆動部、例えば増速機３３、発電機３４、ピッチベアリング４１、旋回ベアリング４５には、グリース自動供給デバイス３０１が設置されて、グリースを供給する。またグリースの排出を行うドレイン３０３に、光学式センサ３０４が配置されており、グリースの色情報を検出している。 FIG. 6 shows the nacelle 3 portion of the wind turbine generator 1 of FIG. 1 extracted as in FIG. The same components are denoted by the same reference numerals and description thereof is omitted. An automatic grease supply device 301 is installed in each drive unit in the nacelle 3, for example, the speed increaser 33, the generator 34, the pitch bearing 41, and the slewing bearing 45 to supply grease. An optical sensor 304 is disposed in the drain 303 for discharging grease, and detects color information of the grease.
　図６のシステムを用いて、ドレイン３０３から排出されたグリースを、光学式センサ３０４で、２４時間毎に計測した。 The grease discharged from the drain 303 was measured by the optical sensor 304 every 24 hours using the system of FIG.
　図７は、風力発電装置１の運転時間を横軸に、縦軸には運転開始時、０．５年経過後、１年経過後、１．５年経過後のΔＥＲＧＢ計測値をプロットしたものである。ΔＥＲＧＢはグリースの固形粒子汚染を反映していると考えられる。グリースのメンテナンスが必要となる、ΔＥＲＧＢの閾値は３５０であり、推移を運転時間に対して近似曲線を設定したところ、ΔＥＲＧＢは約２．２年で閾値を超えると予測された。 FIG. 7 plots ΔE RGB measurement values at the time of the start of operation, after 0.5 years, after 1 year, and after 1.5 years, with the operation time of the wind turbine generator 1 on the horizontal axis. Is. ΔE RGB is considered to reflect the solid particle contamination of the grease. The threshold value of ΔE RGB , which requires grease maintenance, is 350, and when an approximate curve is set for the transition time, ΔE RGB is predicted to exceed the threshold value in about 2.2 years.
　図８は、風力発電装置１の運転時間を横軸に、縦軸には運転開始時、０．５年経過後、１年経過後、１．５年経過後の最大色差ＭＣＤ計測値をプロットしたものである。最大色差ＭＣＤはグリースの酸化劣化を反映していると考えられる。グリースのメンテナンスが必要となる、ＭＣＤの閾値は１００であり、推移を運転時間に対して近似曲線を設定したところ、ＭＣＤは約２．４年で閾値を超えると予測された。 FIG. 8 plots the maximum color difference MCD measurement value at the start of operation, after 0.5 years, after 1 year, and after 1.5 years, with the operation time of the wind turbine generator 1 on the horizontal axis. It is a thing. The maximum color difference MCD is considered to reflect the oxidative degradation of the grease. The threshold for MCD, which requires grease maintenance, was 100, and when an approximate curve was set for the operating time, the MCD was predicted to exceed the threshold in about 2.4 years.
　以上を総合すると、固形粒子汚染および酸化劣化の両方に対して余裕のあるメンテナンスの時期は、２年経過時と予測することができる。 In summary, it can be predicted that two years have passed since the maintenance period with room for both solid particle contamination and oxidative degradation.
　ところで、図７および図８の例では、風力発電装置１の運転状況が一定不変であることを前提としている。しかし、実際には風力発電装置１の運転状況は一定ではなく、さまざまな要因で状況が変化する。 By the way, in the example of FIG. 7 and FIG. 8, it is assumed that the operating state of the wind turbine generator 1 is constant. However, in practice, the operating status of the wind turbine generator 1 is not constant, and the status changes due to various factors.
　例えば、人為的な運転状況の変動としては、点検のための装置の停止期間や、発電量調整のための運転調整がある。これらの変動パラメータは、風力発電装置１の制御パラメータとして取得することができる。 For example, artificial fluctuations in operating conditions include a period during which equipment is stopped for inspection and operation adjustment for power generation amount adjustment. These fluctuation parameters can be acquired as control parameters of the wind turbine generator 1.
　また、自然界に起因する運転状況の変動要因としては、風速をはじめとする天候、温度、湿度、などがある。これらの運転状況の変動要因は、それぞれ各種センサで測定することができる。従って、これらの運転状況を反映することで、より正確にグリースの状態を判定および予測することができる。 Also, factors that fluctuate the driving situation due to the natural world include wind speed and other weather, temperature, and humidity. These fluctuation factors of the driving situation can be measured by various sensors, respectively. Therefore, by reflecting these operating conditions, the state of the grease can be determined and predicted more accurately.
　これらの温度センサや湿度センサは、グリース自動供給デバイス３０１周囲やナセル３内など、グリースに近い環境に設置されることが望ましく、光学式センサ３０４と同様に、サーバ２１０を介して、集約サーバ２２０や中央サーバ２４０に送信される。また、風力発電装置１の制御パラメータは、当該制御を行う、サーバ２１０、集約サーバ２２０あるいは中央サーバ２４０から得ることができる。 These temperature sensors and humidity sensors are preferably installed in an environment close to grease, such as around the automatic grease supply device 301 and in the nacelle 3, and like the optical sensor 304, the central server 220 is connected via the server 210. Or sent to the central server 240. Further, the control parameters of the wind turbine generator 1 can be obtained from the server 210, the aggregation server 220, or the central server 240 that performs the control.
　図９は、運転状況を反映したグリース状態予測方法のフロー図である。説明を単純化するために、この例では、軸受け部へのグリースの供給機構を対象とし、光学センサからの信号は物性パラメータのひとつのΔＥＲＧＢ値として、主に固形粒子汚染に着目することとした。また、運転状況を示す運転パラメータとしては、軸の回転数Ｒ（rpm）の制御パラメータを用いることにした。物性パラメータや運転パラメータはこれに制限されるものではなく、他の種々のものを利用可能である。 FIG. 9 is a flow chart of a grease state prediction method reflecting the operation state. In order to simplify the explanation, in this example, the grease supply mechanism to the bearing unit is targeted, and the signal from the optical sensor is mainly focused on solid particle contamination as one ΔE RGB value of the physical property parameter. did. In addition, as an operation parameter indicating an operation state, a control parameter for the rotational speed R (rpm) of the shaft is used. The physical property parameter and the operation parameter are not limited to this, and various other parameters can be used.
　本例では、定期的に光学式センサ３０４で測定を行うものとし、測定時間になると（Ｓ９０１）、光学式センサ３０４は色度を測定する（Ｓ９０２）。本実施例では、各種センサのデータは中央サーバ２４０へ集約し、ここで一括処理することにしたが、これに限るものではない。 In this example, the optical sensor 304 is periodically measured, and when the measurement time is reached (S901), the optical sensor 304 measures chromaticity (S902). In the present embodiment, the data of various sensors are collected in the central server 240 and collectively processed here. However, the present invention is not limited to this.
　中央サーバ２４０では、光学センサのデータからΔＥＲＧＢを計算し（Ｓ９０３）、また、軸の回転数Ｒのパラメータを取得する（Ｓ９０４）。Ｒの時間的分解能は光学センサのデータ周期と同じでもよいし、それより短くてもよい。これらのデータは、記憶装置に時間データとともに格納する（Ｓ９０５）。 The central server 240 calculates ΔE RGB from the optical sensor data (S903), and obtains the parameter of the rotational speed R of the shaft (S904). The temporal resolution of R may be the same as or shorter than the data cycle of the optical sensor. These data are stored together with the time data in the storage device (S905).
　ΔＥＲＧＢは、時間ｔと軸の回転数Ｒの関数と把握できるので、
　ｆ（ｔ，Ｒ）＝ΔＥＲＧＢ
　となる。過去のｔ、Ｒ，ΔＥＲＧＢのデータを元に関数ｆ（ｔ，Ｒ）をモデル化することも可能である。 Since ΔE RGB can be grasped as a function of time t and shaft rotation speed R,
f (t, R) = ΔE RGB
It becomes. It is also possible to model the function f (t, R) based on the past t, R, ΔE RGB data.
　また、ΔＥＲＧＢの将来予測を行う場合、軸の回転数Ｒの変化を反映する（Ｓ９０６）。結果は表示装置に表示する（Ｓ９０７）。 Further, when the future prediction of ΔE RGB is performed, the change in the rotational speed R of the shaft is reflected (S906). The result is displayed on the display device (S907).
　図１０Ａ，Ｂは、風力発電装置１の過去１年１００１のデータを元に、将来１００２の値を予測して表示する例を示すグラフ図である。１年分の過去データ１００３は実測値である。将来のデータ１００４Ａ，１００４Ｂは予測値である。 FIGS. 10A and 10B are graphs showing an example of predicting and displaying the value of the future 1002 based on the data of the wind power generator 1 for the past year 1001. FIG. The past data 1003 for one year is an actual measurement value. Future data 1004A and 1004B are predicted values.
　図１０Ａでは、将来の運転状況は変わらず、回転数Ｒは常に一定とした。この場合には、ΔＥＲＧＢの予測データは過去１年と同様に推移する。 In FIG. 10A, the future driving situation does not change, and the rotational speed R is always constant. In this case, the prediction data of ΔE RGB changes in the same manner as in the past year.
　図１０Ｂでは、将来の運転状況が変化し、回転数Ｒは過去１年の２倍とした。この場合には、ΔＥＲＧＢの予測データは過去１年と同様に推移せず、たとえば図１０Ｂに示すように、減少割合が大きくなる。 In FIG. 10B, the future driving situation has changed, and the rotational speed R has been doubled over the past year. In this case, the prediction data of ΔE RGB does not change as in the past year, and the decrease rate becomes large as shown in FIG. 10B, for example.
　図１０Ａ，Ｂの実施例のように、予測データに風力発電装置の運転状況を表すパラメータを反映することにより、ΔＥＲＧＢ等のグリース品質を示す物性パラメータが閾値を超えるタイミングをより正確に判断することが可能となる。すなわち、過去の物性パラメータ、過去の運転パラメータ、および将来の運転パラメータに基づいて、将来の物性パラメータをより正確に判断できる。 As in the embodiment of FIGS. 10A and 10B, by reflecting the parameter indicating the operating state of the wind power generator in the prediction data, the timing at which the physical property parameter indicating the grease quality such as ΔE RGB exceeds the threshold value is more accurately determined. It becomes possible. That is, the future physical property parameter can be determined more accurately based on the past physical property parameter, the past operation parameter, and the future operation parameter.
　運転状況を表すパラメータのうち、例えば運転時間や発電目標値のように、人為的にコントロールができるものについては、運転スケジュール等に従って、将来のデータを準備することができる。このため、運転状況を表すパラメータを、グリース品質を示す物性パラメータの予測に用いることにより、予測制度を高めることができる。 For parameters that represent operating conditions, such as operating time and power generation target values that can be controlled artificially, future data can be prepared according to the operating schedule and the like. For this reason, a prediction system can be improved by using the parameter showing an operation condition for prediction of the physical property parameter which shows grease quality.
　また、天候や温度のように人為的にコントロールができないものについては、過去の実績データから将来のデータを予想することができる。このため、同様に運転状況を表すパラメータを、グリース品質を示す物性パラメータの予測に用いることにより、予測制度を高めることができる。 In addition, for data that cannot be artificially controlled, such as weather and temperature, future data can be predicted from past performance data. For this reason, the prediction system can be enhanced by similarly using the parameter representing the operating state for the prediction of the physical property parameter indicating the grease quality.
　以上のように、本実施例では風力発電機の、主軸、発電機、ヨー、ピッチなどの重要な回転部品（軸受）で使用されるグリースの適切な監視を行うため、グリースの自動供給機構に備わるグリース排出部にセンサを設置することで、定常的に監視を行う。また、風力発電機の運転状況のパラメータをモニタすることで、正確な予測診断が可能となる。さらに、ネットワークを介して、風力発電機のグリースの常時遠隔監視が可能になる。このため、早期に軸受の予兆が判り、風力発電機の停止時間が短縮するため、保守コストが低減し、発電量が向上する。 As described above, in this embodiment, in order to appropriately monitor the grease used in important rotating parts (bearings) such as the main shaft, generator, yaw and pitch of the wind power generator, an automatic grease supply mechanism is used. Monitoring is performed regularly by installing a sensor in the grease discharge section provided. In addition, accurate predictive diagnosis can be performed by monitoring parameters of the operating condition of the wind power generator. In addition, the wind generator grease can be constantly monitored remotely via the network. For this reason, since the bearing sign is known early and the stop time of the wind power generator is shortened, the maintenance cost is reduced and the power generation amount is improved.
　本発明は上記した実施形態に限定されるものではなく、様々な変形例が含まれる。例えば、ある実施例の構成の一部を他の実施例の構成に置き換えることが可能であり、また、ある実施例の構成に他の実施例の構成を加えることが可能である。また、各実施例の構成の一部について、他の実施例の構成の追加・削除・置換をすることが可能である。 The present invention is not limited to the above-described embodiment, and includes various modifications. For example, a part of the configuration of one embodiment can be replaced with the configuration of another embodiment, and the configuration of another embodiment can be added to the configuration of one embodiment. Further, it is possible to add, delete, and replace the configurations of other embodiments with respect to a part of the configurations of the embodiments.
　本発明は、風力発電装置の維持管理に利用可能である。 The present invention can be used for maintenance of wind power generators.
　風力発電装置１、タワー２、ナセル３、ハブ４、ブレード５ Wind power generator 1, tower 2, nacelle 3, hub 4, blade 5

Claims (10)

  1. 　風力発電機の機械的駆動部に供給されるグリースの監視システムであって、
    　入力装置、処理装置、記憶装置、および出力装置を備え、
    　前記入力装置は、
    　前記グリースの経路の少なくとも一部に配置された光学式センサから得られる、測定データが入力され、
    　前記処理装置は、
    　前記測定データから前記グリースの物性パラメータを生成するものであり、
    　前記記憶装置は、
    　前記物性パラメータを時系列的に格納するものであり、
    　前記処理装置は、
    　時系列的な前記物性パラメータに基づいて、前記物性パラメータの監視もしくは将来的な予測を行なうものである、
    　風力発電機のグリースの監視システム。     A monitoring system for grease supplied to the mechanical drive of a wind power generator,
    An input device, a processing device, a storage device, and an output device;
    The input device is:
    Measurement data obtained from an optical sensor disposed in at least a part of the grease path is input,
    The processor is
    The physical property parameter of the grease is generated from the measurement data,
    The storage device
    The physical property parameters are stored in time series,
    The processor is
    Based on the time-series physical property parameters, the physical property parameters are monitored or predicted in the future.
    Wind generator grease monitoring system.
  2. 　前記入力装置は、
    　さらに、前記風力発電機の運転パラメータが入力され、
    　前記処理装置は、
    　時系列的な前記物性パラメータと、前記運転パラメータに基づいて、前記物性パラメータの将来的な予測を行なうものである、
    　請求項１記載の風力発電機のグリースの監視システム。     The input device is:
    Furthermore, operating parameters of the wind power generator are input,
    The processor is
    Based on the time-series physical property parameters and the operation parameters, the physical property parameters are predicted in the future.
    The wind power generator grease monitoring system according to claim 1.
  3. 　前記処理装置は、
    　前記物性パラメータの将来的な予測を行なう際に、予め設定された閾値を前記物性パラメータが超える時間を予測するものである、
    　請求項１記載の風力発電機のグリースの監視システム。     The processor is
    When predicting the physical property parameter in the future, the time when the physical property parameter exceeds a preset threshold is predicted.
    The wind power generator grease monitoring system according to claim 1.
  4. 　前記物性パラメータは、ΔＥＲＧＢである、
    　請求項１記載の風力発電機のグリースの監視システム。     The physical property parameter is ΔE RGB .
    The wind power generator grease monitoring system according to claim 1.
  5. 　前記物性パラメータは、最大色差である、
    　請求項１記載の風力発電機のグリースの監視システム。     The physical property parameter is a maximum color difference.
    The wind power generator grease monitoring system according to claim 1.
  6. 　前記出力装置は、
    　第１の軸に前記物性パラメータを表示し、第２の軸に時間を表示したグラフ形式で、前記物性パラメータの将来的な予測の結果を表示する、
    　請求項１記載の風力発電機のグリースの監視システム。     The output device is
    Displaying the results of future predictions of the physical property parameters in a graph format displaying the physical property parameters on a first axis and displaying time on a second axis;
    The wind power generator grease monitoring system according to claim 1.
  7. 　前記光学式センサは、
    　前記グリースの経路の末端付近に配置される、
    　請求項１記載の風力発電機のグリースの監視システム。     The optical sensor is
    Disposed near the end of the grease path;
    The wind power generator grease monitoring system according to claim 1.
  8. 　前記光学式センサは、
    　前記グリースの供給系統の排出部に配置される、
    　請求項１記載の風力発電機のグリースの監視システム。     The optical sensor is
    Arranged in the discharge part of the grease supply system,
    The wind power generator grease monitoring system according to claim 1.
  9. 　風力発電機のグリースの監視方法であって、
    　前記風力発電機は光学式センサを備えた風力発電機であって、前記光学式センサが前記風力発電機の部品で使用されるグリースの光学的特性を測定するものであり、
    　前記光学式センサからの測定データを受信する第１のステップ、
    　前記測定データから前記グリースの物性パラメータを生成する第２のステップ、
    　前記物性パラメータを記憶する第３のステップ、
    　前記物性パラメータに基づいて、前記物性パラメータの現在のデータを監視し、または、将来のデータを予測する第４のステップ、
    　を実行する風力発電機のグリースの監視方法。     A method for monitoring grease of a wind power generator,
    The wind power generator is a wind power generator provided with an optical sensor, and the optical sensor measures an optical characteristic of grease used in parts of the wind power generator,
    A first step of receiving measurement data from the optical sensor;
    A second step of generating a physical property parameter of the grease from the measurement data;
    A third step of storing the physical property parameters;
    A fourth step of monitoring current data of the physical property parameters or predicting future data based on the physical property parameters;
    Run wind generator grease monitoring method.
  10. 　さらに、前記風力発電機の運転パラメータを受信する第５のステップを実行し、
    　前記第４のステップでは、
    　前記物性パラメータの過去のデータと、前記運転パラメータの過去および将来のデータに基づいて、前記物性パラメータの将来のデータを予測する、
    　請求項９記載の風力発電機のグリースの監視方法。     A fifth step of receiving operating parameters of the wind power generator;
    In the fourth step,
    Predicting future data of the physical property parameters based on past data of the physical property parameters and past and future data of the operating parameters;
    The method for monitoring grease of a wind power generator according to claim 9.
PCT/JP2018/010712 2017-05-12 2018-03-19 System and method for monitoring grease of wind power generator WO2018207464A1 (en)

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