JP2019011716A - Lube oil monitor system of aerogenerator and method - Google Patents

Abstract

To optimize the replacement cycle of lube oil by appropriate lube oil diagnosis.SOLUTION: A monitor system for lube oil supplied to a mechanical drive of an aerogenerator. This system comprises: an input device; a processing unit; a memory and an output device. The memory stores additive concentration data that stores the concentration of additives of lube oil in time series, and the processing unit estimates the time during which the concentration of the additive reaches a predetermined threshold value based on the additive concentration data.SELECTED DRAWING: Figure 6

Description

  The present invention relates to a wind power generator, and more particularly to a technique that can support maintenance and management of lubricating oil used in a nacelle or the like.

  In recent years, power generation systems using natural energy have been attracting attention in order to prevent global warming, and wind power generators are widely used.

  In wind power generators, lubricating oil or the like is used to reduce the mechanical friction coefficient between components. Various techniques have been proposed to maintain the properties sufficient for lubricating oil to provide lubrication.

  For example, in Patent Document 1, an initial ideal remaining life is determined for a lubricating oil from a wind turbine, and a temperature-based remaining life for the lubricating oil is determined based on a temperature measurement value of the lubricating oil from the wind turbine. Calculating the lubrication coefficient of the lubricating oil based on the contaminated samples of the oil and determining an updated ideal remaining life for the lubricating oil based on the contamination coefficient, the initial ideal remaining life and the temperature-based remaining life, It is disclosed to monitor lubricating oil from a wind turbine by determining an actual remaining life for the lubricating oil based on a life loss factor.

  Further, as a technique for evaluating the characteristics of an object such as oil using a sensor, Patent Document 2 measures the resonance impedance spectrum response of an LCR resonator, and Patent Document 3 detects a color component. Measuring is disclosed.

JP, 2006-046881, A Japanese Patent Laid-Open No. 2006-126007 WO2010 / 150526

  FIG. 1 shows a schematic overall configuration diagram of a wind power generator which is an example of an apparatus 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 power 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 in a horizontal plane. .

  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, In addition, a generator 34 that rotates the rotor at a rotational speed increased by the speed increaser 33 via the coupling 38 and performs a power generation operation is provided.

  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. On the main frame 35, one or a plurality of oil tanks 37 for storing lubricating oil for lubricating the power transmission unit are installed. Further, a radiator 36 is disposed in the nacelle 3 on the windward side of the nacelle partition wall 30.

  In wind power generators, lubricating oil is used in many rotating parts. For example, in FIG. 1, lubricating oil is supplied to bearings such as a main shaft 31, a speed increaser 33, a generator 34, and yaw and pitch (not shown). The pitch control of the blades controls the output by changing the blade angle according to the wind speed, and the yaw control swings the head according to the wind direction.

  It is necessary to supply lubricating oil to such movable parts. Lubricating oil reduces friction on the rotating parts and prevents wear and damage to parts or energy loss. However, when the lubrication performance deteriorates due to deterioration of the lubricating oil over time, the friction coefficient increases and the risk of failure of the wind power generator increases.

  When a wind turbine breaks down, there is a huge loss cost, such as the cost of replacing faulty parts and a decrease in power generation revenue during a power outage. Yes. In particular, a speed increaser, which is an important component, increases the risk of failure when the performance of the lubricating oil decreases. Therefore, a technique for estimating the remaining life and replacement time of the lubricating oil as early as possible is important.

  Assuming that the wind turbine generator lubricant is the monitoring target, for example, in the evaluation of the characteristics by viscosity, the wind turbine gearbox lubricant is a chemically very stable synthetic oil, and the viscosity changes little. Therefore, it is not suitable as an index for remaining life estimation. In addition, in the measurement of the total acid value indicating deterioration due to oxidation, the lubricating oil of the wind turbine speed increaser is a synthetic oil that is very stable against oxidation, and the total acid value hardly changes. It is not suitable as an estimation index. Therefore, the inventors have recognized that there is an examination subject in the performance evaluation method in the lubricating oil periodic analysis of the wind power generator in order to estimate the remaining life of the lubricating oil early.

  Therefore, an object of the present invention is to optimize the replacement period of the lubricating oil by appropriate lubricating oil diagnosis.

  One aspect of the present invention is a monitoring system for lubricating oil supplied to a mechanical drive of a wind power generator. The system includes an input device, a processing device, a storage device, and an output device. The storage device stores additive concentration data in which the concentration of the additive of the lubricating oil is stored in time series, and the processing device estimates the time when the concentration of the additive becomes a predetermined threshold based on the additive concentration data. To do.

  Another aspect of the present invention is a method for monitoring lubricating oil of a wind power generator using a server including a processing device, a storage device, an input device, and an output device. In this method, a first step of collecting a sample of lubricating oil from a wind power generator, a second step of measuring the concentration of the additive contained in the sample, and the measured concentration of the additive in time series in the storage device A third step of storing and using the additive concentration data is executed, and a fourth step of estimating a time when the concentration of the additive becomes a predetermined threshold is executed by the processing device processing the additive concentration data.

  Specific examples of the additive include, for example, an antioxidant and an extreme pressure additive. A specific example of the additive concentration analysis is analysis using, for example, liquid chromatography.

  With the appropriate lubricant diagnosis, the lubricant replacement cycle can be optimized.

The schematic whole block diagram of a wind power generator. The graph which shows the phosphorus density | concentration measurement result in the lubricating oil by ICP elemental analysis. The graph which shows the phosphorus system extreme pressure additive density | concentration measurement result in the lubricating oil obtained by LC measurement. Schematic of a wind power generator system having a lubricating oil supply system. The conceptual diagram of the bearing components provided with the sensor for lubricating oil. Lubricant diagnosis flow diagram. The graph which shows the concept of lubricating oil remaining life estimation. The graph which shows the concept of other lubricating oil remaining life estimation. The block diagram which shows an example of the central server of an Example. The graph which shows the concept of lubricating oil remaining life estimation. The graph which shows the concept of lubricating oil remaining life estimation.

  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.

  In the structures 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.

  In the case where there are a plurality of elements having the same or similar functions, the same reference numerals may be given with different subscripts. However, when there is no need to distinguish between a plurality of elements, the description may be omitted.

  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.

  The position, size, shape, range, and the like of each component illustrated in the drawings and the like may not represent the actual position, size, shape, range, or the like 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.

  First, the lubricating oil which is the monitoring target in the embodiment will be described. Various parameters such as viscosity, total acid value measurement, and component element analysis are conceivable as monitoring target parameters for evaluating the characteristics of the lubricating oil. However, as described above, since the viscosity and total oxidation of the lubricating oil of the wind power generator hardly change, this alone is not suitable as an index for estimating the remaining life. In addition, a method of measuring fine particle powder and moisture contained in the lubricating oil can be considered, but at the time when these inclusions are detected in the lubricating oil, there is a possibility that wear or leakage has already occurred, Furthermore, it is desirable to detect a sign at an early stage.

  By the way, various additives are contained in lubricating oil in order to maintain lubricating performance. For example, if the lubrication conditions are severe and the pressure at the contact area is high, the sliding speed is low, or the viscosity of the oil is too low, the lubricating oil film between the friction surfaces becomes thin, and the friction resistance is reduced. Increases and wears. This state is called boundary lubrication, and seizure occurs in an extreme case. Oil-based agents, anti-wear agents, and extreme pressure additives (extreme pressure agents) work to reduce friction and wear in this boundary lubrication state. These are collectively called load-bearing additives. Sometimes. Other additives include, for example, antioxidants and antifoaming agents.

  The oil-based agent adsorbs on the metal surface to form an adsorbing film, which acts to reduce friction and wear by preventing direct contact between the metal in the boundary lubrication state. As the oily agent, higher fatty acids, higher alcohols and amines, esters, metal soaps, and the like that have a high adsorbing power on the metal surface are used.

  Antiwear agents are more effective in preventing wear under conditions of load more severe than oil-based agents. In general, phosphate esters, phosphite esters, and thiophosphates are often used. Antiwear agents are used in turbine oils, antiwear hydraulic oils, and the like. In particular, zinc dialkyldithiophosphate (also called ZnDTP: Zinc Dialkyldithiophosphate, ZDDP) also has antioxidant performance.

  On the contact surface in the heavy load state, which is the most severe condition of the boundary lubrication state, the temperature of the friction surface becomes very high, and the adsorption film by the oily agent is desorbed and becomes ineffective, but the extreme pressure additive is sulfur, chlorine, Since it is a chemically active substance containing phosphorus, it reacts with the metal surface to form a compound containing sulfur, chlorine, phosphorus, etc., and it becomes a film with low shearing force to prevent wear, seizure, and fusion.

  Extreme pressure additives are substances that generally contain sulfur, chlorine, phosphorus, etc., in addition to sulfurized fats and oils, sulfurized esters, sulfides, chlorinated hydrocarbons, lead naphthenate, sulfur, phosphorus, Compounds containing two or more elements in chlorine are also used. Specific extreme pressure additives include sulfurized palm oil, sulfurized fatty ester, dibenzyl disulfide, alkyl polysulfide, olefin polysulfide, xanthic sulfide, chlorinated paraffin, methyl trichlorostearate, lead naphthenate, alkylthiophosphate amine Chloroalkyl xanthate, triphenyl phosphorothioate (TPPT), and the like.

  Antioxidants are used to prevent deterioration of base oils due to oxidation. There are three types of antioxidants. Suppresses the formation of free radicals (radicals) at the initial stage of oxidation, stops the chain of hydrocarbon oxidation reaction, free radical inhibitor, decomposes the generated peroxide, and stable non-free radical compounds These are a peroxide decomposer (Peroxide Decomposer) and a metal deactivator that forms a strong adsorption film (inert anticorrosion film). The role of the metal deactivator is to prevent iron and copper from being dissolved by the metal corrosiveness of the peroxide generated by oxidation of the lubricating oil.

  Specific antioxidants include phenol derivatives (2,6-di-tert-butyl p-cresol (BHT), 2,6-di-tert-butyl p-phenol (DBP), 4,4′-methylenebis. (2,6-dialkylphenol)), amine derivatives (2,6-dialkyl-α-dimethylaminoparacresol, 4,4'-tetramethyldiaminodiphenylmethane, octylated phenylnaphthylamine, di-octyl-diphenylamine, dinonyl- Diphenylamine, phenothiazine, 2,2,4-trimethyldihydroxyquiniline, etc.), metal dithiophosphate, alkyl sulfide, etc., 1,4-dioxydianthraquinone (also known as quinizarin), 1,2-dioxydi Anthraquinone (also known as alizarin), benzotriazole, alkylbenzotriazole, etc.

  It is necessary for maintaining the desired lubricating performance that the additive is contained in a predetermined ratio (concentration) with respect to the lubricating oil.

  In Patent Document 1, the contamination coefficient is calculated by acquiring and analyzing at least one of the number of iron particles, water content, dielectric constant, and / or International Standard Organization (ISO) particle level in the lubricating oil. However, it measures impurities and physical properties such as particles and water, and does not directly measure changes in the components of the lubricating oil itself, particularly the additive concentration of the lubricating oil. Therefore, the inventors compared and examined methods for predictive diagnosis by monitoring the state of the additive contained in the lubricating oil, particularly the change in concentration.

  FIG. 2 shows the result of measuring the concentration of phosphorus, which is a component of an extreme pressure additive in lubricating oil, by ICP (Inductively Coupled Plasma) elemental analysis, which is known as one of the component analysis methods. Show. The horizontal axis is the elapsed time (months), and the vertical axis is the phosphorus concentration (ppm). This result shows no significant relationship between elapsed time and phosphorus concentration. This suggests that elemental analysis accuracy may be insufficient for predictive diagnosis.

  According to the measurement results shown in FIG. 2, the phosphorus concentration once decreased increases again, but it is not considered that the concentration of the extreme pressure additive naturally increases. As a cause of such a measurement result, in the ICP elemental analysis, it is considered that measurement is performed including phosphoric acid which is a decomposition product of the extreme pressure additive. In the ICP elemental analysis, the liquid component (lubricating oil, additive, additive decomposition product, etc.) and the solid component (wear powder, etc.) are analyzed together in order to make the sample into plasma. It is thought that it is not suitable for quantitative determination of the additive components.

  FIG. 3 is a graph showing the results of consumption behavior of phosphorus-based extreme pressure additives in lubricating oil during wind turbine operation, obtained by LC (Liquid Chromatography) measurement (detector is UV detector). is there. In this example, the phosphorus-based extreme pressure additive is specifically TPPT. The horizontal axis is the elapsed time (number of months), and the vertical axis is the TPPT concentration (relative value to new oil). In this result, a significant relationship is observed between the elapsed time and the concentration, and the concentration decreases linearly with the number of elapsed months.

  In LC measurement, components of a liquid sample are separated by the principle of chromatography. Next, the components separated here are detected by a UV detector, a refractive index detector, and a mass spectrometer. LC measurement is suitable for qualitative and quantitative determination of organic compounds. In particular, when a mass spectrometer is used as the detector, only the additive in the lubricating oil can be quantified with high accuracy and high sensitivity.

Based on the above study, in order to monitor the change in the concentration of the additive in the lubricating oil over time and maintain the function of the additive, the concentration of the additive in the lubricating oil can be directly measured as in LC measurement. It was found that a measurement method capable of measuring was suitable. Further, at this time, it has been found that if the concentration of the additive in the lubricating oil falls below a predetermined threshold, the performance of the lubricating oil becomes insufficient, leading to a failure of the apparatus. In addition to LC measurement, methods that can directly and accurately measure the concentration of additives in lubricating oil include Fourier transform infrared spectroscopy (FT-IR) and nuclear magnetic resonance (NMR).
Hereinafter, a specific configuration of the present embodiment will be described.

(1. Overall system configuration)
A system for diagnosing the concentration of the additive in the lubricating oil will be described with reference to FIG. For the sake of explanation, FIG. 4 shows the 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 lubricating oil is supplied from an oil tank 37.

  As shown in FIG. 4, a plurality of wind power generators 1 are usually installed in the same site, and these are collectively called a farm 200a. Each wind power generator 1 is provided with various sensors (not shown) in the lubricating oil supply system, and sensor signals reflecting the state of the lubricating oil are collected in the server 210 in the nacelle 3. 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 power generator 1 via the aggregation server 220 or the server 210.

(2. Sensor arrangement)
FIG. 5 is a schematic view of a sensor arranged in a lubricating oil supply system. Lubricating oil is supplied from the lubricating oil supply device 301 to the bearing component 302. The lubricating oil supply device 301 is connected to the oil tank 37 and receives supply of lubricating oil. 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 sensor 304 is disposed in a lubricating oil flow path or the like in order to detect the state of the lubricating oil. The sensor measures various parameters of the lubricating oil. For example, physical quantities include temperature and hydraulic pressure. These can be measured using a known sensor as disclosed in Patent Documents 1 to 3, for example. Based on the temporal change of these parameters, the state of the lubricating oil can be evaluated.

  For example, the sensor can also measure information about contaminating particles contained in the lubricating oil, such as particle concentration. It is highly possible that the particles are derived from wear of parts, and it is possible to detect deterioration of the lubricating oil or abnormality of the apparatus. As described above, the abnormality detected by these sensors may be an abnormality that has already started, but it is useful to monitor the sensor information because it can be acquired in real time. In diagnosis based on sensor data, diagnosis is performed based on one or more types of sensor data.

  In the example of FIG. 5, part of the lubricating oil supplied to the bearing component 302 is introduced into the measurement unit 303. A sensor 304 is disposed in the measurement unit 303 and detects various characteristics of the lubricating oil. The measuring unit 303 is disposed near the end of the lubricating oil path, for example.

  Lubricating oil 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. In order to know the timing of such maintenance, it is useful in terms of maintenance management efficiency to enable data that can be collected by the sensor 304 installed in the field to be monitored remotely. The data collected by the sensor 304 is collected by, for example, the server 210 in the nacelle 3, and then sent to the central server 240 that aggregates data of a plurality of farms via the aggregation server 220 that aggregates data in the farm 200.

  However, for analysis that requires equipment for measurement, such as LC measurement, FT-IR measurement, and NMR measurement, it is necessary to collect a sample of the lubricating oil as appropriate and perform analysis using equipment separately provided. Results obtained by LC measurement, FT-IR measurement, and NMR measurement are also separately stored as data in the central server 240, and the data is aggregated.

  Further, the data to be aggregated may include not only data relating to the lubricating oil but also data indicating the operating status of the wind power generator. For example, the wind turbine output value (the larger the larger the deterioration rate of the lubricating oil), the actual operation time (the longer the longer the deterioration rate of the lubricating oil), the machine temperature (the higher the higher the deterioration rate of the lubricating oil), the shaft rotation speed (the faster Such as a large deterioration rate of the lubricating oil). These can be collected from sensors of known configurations installed at various locations of the wind power generator and control signals of the apparatus.

(3. Flow of lubricant diagnosis)
FIG. 6 is a flowchart showing a lubricating oil diagnosis process according to this embodiment. The process shown in FIG. 6 is performed under the control of any of the server 210, the aggregation server 220, and the central server 240 in FIG. In the following example, it is assumed that the central server 240 performs. However, as will be described later, processing such as collection of lubricant samples (S607), concentration measurement of additives (S608), replacement of lubricant (S603), etc. is performed separately by a dedicated measuring device (liquid chromatograph, etc.) or a worker. The server is used to output instructions and input necessary information. Other 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 a function configured by software can be realized by hardware such as an FPGA (Field Programmable Gate Array) and an ASIC (Application Specific Integrated Circuit).

  When the central server 240 performs control, since the subordinate has a plurality of wind power generators 1, the following processing is performed for each wind power generator. This process is basically a repetitive process, and the start timing is set by a timer or the like. For example, the process is started every day at 0:00 (S601). Moreover, the central server 240 can also perform at arbitrary timing according to an operator's instruction | indication.

  In process S602, the central server 240 checks the replacement time of the lubricating oil. The initial value of the replacement time can be calculated physically by using the Arrhenius reaction rate on the assumption that the lubricant is operating at the design temperature, and the remaining life can be initially set. Such a calculation method is described in Patent Document 1, for example. This replacement time can be updated later in step S610 based on the actual measurement data.

  If it is time to replace the lubricating oil, the lubricating oil is replaced in step S603. Since the lubricating oil replacement is usually performed by a worker, the central server 240 performs display and notification for instructing the worker when to perform replacement and the target.

  If it is not time to replace the lubricating oil, in step S604, the central server 240 performs a diagnosis based on the sensor data. As sensor data, temperature, oil pressure, concentration of contained particles, and the like can be used. Since these measurement techniques and diagnostic techniques are described in, for example, Patent Documents 1 to 3 and the like and are basically known, explanations thereof are omitted. The data collected by the sensor 304 is sent to the central server 240, which evaluates the characteristics of the lubricating oil, for example, by comparing parameters obtained from the sensor with predetermined thresholds.

  If the diagnosis result is abnormal in step S605, the lubricating oil is replaced in step S603. If there is no abnormality, the central server 240 checks in step S606 whether or not it is the timing for collecting the lubricant sample. Lubricating oil sample collection usually involves work by workers and is therefore not economical to do frequently. However, in the case where a predetermined equipment is required for processing, such as measurement of additive concentration by LC, FT-IR, NMR, etc., it is necessary to collect a sample. The sample collection timing is set, for example, once a month or once a year.

  When it is the sample collection timing, the central server 240 performs display and notification for instructing the worker when to collect the sample and the target. In process S607, the worker collects the sample and sends it to a facility equipped with a liquid chromatograph device, an FT-IR device, an NMR device, and the like to measure the additive concentration.

  As is well known, the liquid chromatographic method is a device that separates compounds with a liquid chromatograph and quantitatively analyzes the separated substances with a UV absorption detector, a refractive index detector, a mass spectrometer, and the like. This is possible. Since the apparatus and the analysis method itself are well-known techniques, description thereof will be omitted. The important point is that the concentration of the additive added to the lubricating oil can be accurately grasped by the measurement by LC. Since FT-IR and NMR are also well-known methods, description thereof will be omitted. The important point is that the additive concentration in the lubricating oil can be accurately grasped by measurement by FT-IR and NMR.

  In process S609, additive concentration measurement data is input to the central server 240, and the data is stored in time series. The measurement data may be input directly from an additive measuring device such as a liquid chromatograph, FT-IR, or NMR device or a server connected thereto, or may be input by a separate operator. The important point is that the data includes sampling time information.

  FIG. 7 is a graph showing the concept of additive concentration measurement results stored in time series. The horizontal axis represents time (month), and the vertical axis represents the relative concentration when the additive concentration at the time of a new article is 100. For example, it is assumed that the additive concentration is monitored at a fixed point every month, and concentration data 700 is plotted up to three months. As described with reference to FIG. 3, a significant relationship is recognized between the elapsed time and the additive concentration. For example, the concentration decreases linearly with time. Therefore, the additive consumption rate can be calculated from the additive concentration measurement results stored in time series. Here, when the additive concentration is about half that of a new product, it is assumed that the performance of the lubricating oil falls below the allowable range. Such a threshold can be determined experimentally.

  In this example, in step S610, the threshold value is set to 50, and the time point at which the concentration estimated from the additive concentration measurement result stored in time series becomes 50 is estimated as the replacement time. Various known methods may be employed as the estimation method. If an actual measurement value as shown in FIG. 3 is obtained, a known method for extrapolating data can be used on the assumption that the concentration decreases monotonously. Further, when the concentration changes more complicatedly, a known method such as function fitting (curve fitting) can be used.

  The replacement time estimation result in the process S610 can be displayed as the lubricant diagnosis result (process S611). 7, 10, and 11 show display examples of the results obtained in step S <b> 610.

  In the example of FIG. 7, the additive is TPPT, and the concentration becomes 50 after about 5 months. Therefore, the previous time (for example, half a month before) may be set as a new replacement time. In step S612, one cycle of processing is completed, and in step S602 of the next cycle, determination processing is performed according to a new replacement time. In the example of FIG. 10, the additive is ZnDTP, and the concentration becomes 50 after about 10 months. Therefore, the previous time (for example, one month before) may be set as a new replacement time. In step S612, one cycle of processing is completed, and in step S602 of the next cycle, determination processing is performed according to a new replacement time.

  In the example of FIG. 11, the additive is BHT, and the threshold of BHT is 30. Since the concentration becomes 30 after about 20 months, the previous time (for example, one month before) may be set as a new replacement time. In step S612, one cycle of processing is completed, and in step S602 of the next cycle, determination processing is performed according to a new replacement time.

  As described above, according to the present embodiment, the life of the lubricating oil can be detected early by knowing the consumption rate of the additive in the lubricating oil using the additive concentration measurement result. For this reason, abnormality of a wind power generator can be prevented beforehand by maintenance, such as appropriate lubricating oil exchange.

  In the second embodiment, an example of correcting the life estimation of the lubricating oil using data obtained from the sensor will be described. In the first embodiment, it is assumed that the operating status of the wind power generator 1 is constant. However, in practice, the operating status of the wind power generator 1 is not constant, and the status changes due to various factors.

  For example, artificial fluctuations in operating conditions include a period during which an apparatus is stopped for inspection and an operation adjustment for power generation amount adjustment. These fluctuation parameters can be acquired as operating parameters of the wind power generator 1.

  In addition, examples of the fluctuation factors of the driving situation caused by the natural world include those inside and outside the wind power generator such as the 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 as sensor data, the state of the lubricating oil can be determined and predicted more accurately.

  As described with reference to FIGS. 4 and 5, various sensors can be installed in the wind power generator. Sensor data from the sensor 304 is transmitted to the aggregation server 220 and the central server 240 via the server 210. Further, the operating parameters of the wind power generator 1 can be obtained from the server 210, the aggregation server 220, or the central server 240 that performs the control.

  With reference to FIG. 6 again, a method for monitoring the lubricating oil reflecting the operation status will be described. The basic process is the same as in FIG. 6, but in the diagnosis process (S604) using sensor data, sensor data or operation parameters are stored in time series and used in the replacement time estimation and update process (S610). .

  In order to simplify the explanation, in this example, the mechanism for supplying the lubricating oil to the bearing unit is targeted, and the control parameter for the rotational speed R (rpm) of the shaft is used as the operation parameter indicating the operation status. . Sensor data and operation parameters are not limited to this, and other various data can be used. 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.

  In the central server 240, in the replacement time estimation and update process (S610), the additive concentration measurement result input in process S609 and the control parameter for the rotational speed R of the shaft stored in process S604 are acquired. These data are stored in the storage device in time series together with the time data.

Now, as a simple example, it is assumed that the rotation speed R (rpm) of the shaft is related to the decrease in the concentration of the extreme pressure agent, that is, the consumption. Under this assumption, the concentration C (t) of the extreme pressure agent can be grasped as a function of the time t and the rotational speed R of the shaft.
f (t, R) = C (t)
It becomes. It is possible to model the function f (t, R) by experiment or simulation, or based on past t, R and extreme pressure agent concentration data. Therefore, when the future prediction of C (t) is performed in the replacement time estimation and update process (S610), the change in the rotational speed R of the shaft is reflected. The result is displayed on a display device, for example.

  FIG. 8 is a graph showing an example of predicting and displaying a future value 1002 based on the data 1001 of the past year of the wind power generator 1. The past data 1003 for one year is an actual measurement value. Future data 1004A and 1004B are predicted values.

  In FIG. 8 (a), the future driving situation does not change, and the rotational speed R is always constant. In this case, the extreme pressure agent concentration prediction data 1002 changes in the same manner as the data 1001 for the past year. In this case, the extreme pressure agent concentration limit is predicted to arrive at the time t1.

  In FIG. 8 (b), the future driving situation has changed, and the rotational speed R after one year has been doubled from the past year. Here, if the consumption rate of the extreme pressure agent is proportional to the rotation speed R, the prediction data of the extreme pressure agent concentration does not change in the same manner as in the past year. For example, as shown in FIG. Becomes larger. In this case, the extreme pressure agent concentration limit is predicted to arrive at a time point t2 shorter than t1.

  In the above description, the estimated consumption rate of the additive is corrected using the rotational speed R of the shaft as an operation parameter, but sensor data can also be used. For example, it is considered that the temperature T (° C.) of the lubricating oil is related to the decrease in the concentration of the extreme pressure agent. Under this assumption, the concentration C (t) of the extreme pressure agent can be grasped as a function of the time t and the temperature T, and the estimated consumption rate of the extreme pressure agent can be corrected in the same manner as in the case of the rotational speed R of the shaft.

  As shown in the example of FIG. 8, by reflecting the operation parameters and sensor data representing the operation state of the wind power generator in the prediction data, the timing at which the parameter indicating the lubricating oil quality such as the extreme pressure agent concentration exceeds the threshold value is further increased. It becomes possible to judge accurately. That is, the future extreme pressure agent concentration can be more accurately determined based on the past extreme pressure agent concentration, the past operation parameter (or sensor data), and the future operation parameter (or predicted sensor data).

  Of the parameters representing the operation status, those that can be controlled artificially, such as the operation time and the power generation target value, can prepare future data according to the operation schedule and the like. For this reason, a prediction system can be raised by using the parameter showing an operation condition for prediction of the additive concentration which shows lubricating oil quality.

  In the case of things that cannot be artificially controlled, such as weather and temperature, future data can be predicted from past performance data. For this reason, a prediction system can be raised by using the parameter showing an operating condition similarly for the prediction of the additive density | concentration which shows lubricating oil quality.

  FIG. 9 is a block diagram illustrating a configuration example of the central server 240 of the present embodiment. The system includes a processing device 2401, a storage device 2402 (such as a magnetic disk device and a semiconductor memory), and an input / output device 2403, which are basic server configurations. The input / output device 2403 includes a general input device such as a keyboard and a mouse, and an output device such as an image display device and a printer. The input / output device also includes a network interface for exchanging data with the wind turbine generator 1, its server 210, the aggregation server 220, or the additive quantitative analysis system 900 such as a liquid chromatograph mass spectrometer via the network 230.

  Various operating parameters and sensor data are input to the central server 240 from the wind power generator 1 and its sensor 304 directly or via the server 210 or the aggregation server 220. Or you may input into the central server 240 not via a network but via a portable recording medium. These data are stored in the storage device 2402 as time-series operation parameter data 901 or as time-series sensor data 902.

  In the additive quantitative analysis system 900, the concentration of the additive is measured from the lubricating oil sample obtained at the wind power plant 1 using a liquid chromatograph, a Fourier transform infrared spectrophotometer, NMR or the like. Similar to the operation parameter data 901 and sensor data 902, the measured additive concentration is stored in the storage device 2402 as time-series additive concentration data 903.

  Additives that perform quantification are specifically oil-based agents such as higher fatty acids, higher alcohols and amines, esters, metal soaps, antiwear agents such as zinc dialkyldithiophosphate (ZnDTP: also called ZDDP), Lead naphthenate, sulfurized palm oil, sulfurized fatty ester, dibenzyl disulfide, alkyl polysulfide, olefin polysulfide, xanthic sulfide, chlorinated paraffin, methyl trichlorostearate, lead naphthenate, amine alkylthiophosphate, chloroalkyl xanthate, Extreme pressure agents such as triphenyl phosphorothioate (TPPT), phenol derivatives (2,6-di-tert-butyl p-cresol (BHT), 2,6-di-tert-butyl p-phenol ( DBP), 4,4'-methylene (2,6-dialkylphenol), amine derivatives (2,6-dialkyl-α-dimethylaminoparacresol, 4,4'-tetramethyldiaminodiphenylmethane, octylated phenylnaphthylamine, di-octyl-diphenylamine, dinonyl -Diphenylamine, phenothiazine 2,2,4-trimethyldihydroxyquiniline, etc.), metal dithiophosphate, alkyl sulfide, etc., 1,4-dioxydianthraquinone (also known as quinizarin), 1,2-dioxydi One or more additives selected from antioxidants such as anthraquinone (also known as alizarin), benzotriazole, and alkylbenzotriazole.

  For example, when additives having different functions such as ZnDTP and BHT are quantified and the results are used for diagnosis, more accurate diagnosis can be performed.

  The processing device 2401 uses the additive concentration data 903 stored in the storage device 2402 and, if necessary, the operation parameter data 901 and the sensor data 902 to predict the consumption rate of the additive concentration and outputs it to the output device. .

  As described above, in this embodiment, the concentration of additives is measured in order to properly monitor the lubricating oil used in important rotating parts (bearings) such as the main shaft of the wind power generator, generator, yaw, and pitch. To do. In addition, monitoring is constantly performed by installing a sensor in the part of the automatic oil supply mechanism. In addition, accurate predictive diagnosis can be performed by monitoring parameters of the operating condition of the wind power generator. For this reason, it becomes possible to predict the replacement time of the lubricating oil at an early stage, and the stop time of the wind power generator is shortened, so that the maintenance cost is reduced and the power generation amount is improved.

  The present invention is not limited to the embodiments described above, 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.

  Wind generator 1, tower 2, nacelle 3, hub 4, blade 5, additive quantitative analysis system 900, operating parameter data 901, sensor data 902, additive concentration data 903

Claims (10)

A monitoring system for lubricating oil supplied to a mechanical drive of a wind power generator,
An input device, a processing device, a storage device, and an output device;
The storage device
Stores additive concentration data in which the concentration of the additive of the lubricating oil is stored in time series,
The processor is
A monitoring system for a lubricating oil of a wind power generator that estimates a time during which the concentration of the additive becomes a predetermined threshold based on the additive concentration data. The storage device
Storing sensor data storing data from sensors installed in the wind power generator in time series;
The processing device uses the sensor data in addition to the additive concentration data to estimate a time when the concentration of the additive becomes a predetermined threshold value.
The monitoring system for lubricating oil of a wind power generator according to claim 1. The storage device
Storing operation parameter data storing operation parameters of the wind power generator in time series;
The processing device uses the operation parameter data in addition to the additive concentration data to estimate a time when the concentration of the additive becomes a predetermined threshold value.
The monitoring system for lubricating oil of a wind power generator according to claim 1. The output device is
Notifying or outputting the time when the concentration of the additive becomes a predetermined threshold,
The monitoring system for lubricating oil of a wind power generator according to claim 1. The output device is
In the form of a graph in which the concentration of the additive is displayed on the first axis and the time is displayed on the second axis, the time when the concentration of the additive becomes a predetermined threshold is displayed as an image.
The monitoring system for lubricating oil of a wind power generator according to claim 1. The additive is at least one selected from an oily agent, an antiwear agent, an extreme pressure additive, an antioxidant, and an antifoaming agent.
The monitoring system for lubricating oil of a wind power generator according to claim 1. A method for monitoring lubricating oil of a wind power generator using a server including a processing device, a storage device, an input device, and an output device,
A first step of taking a sample of the lubricating oil from the wind power generator;
A second step of measuring the concentration of the additive contained in the sample;
A third step in which the measured concentration of the additive is stored in the storage device in time series and used as additive concentration data;
A fourth step of estimating a time at which the concentration of the additive becomes a predetermined threshold by the processing device processing the additive concentration data;
To perform wind generator lubricant monitoring method. Further, the fifth step of receiving data from the sensor installed in the wind power generator from the input device and storing the data in the storage device in time series is used as sensor data,
In the fourth step,
Predicting future data of the additive concentration data based on past data of the additive concentration data and past data and future prediction data of the sensor data;
The method for monitoring lubricating oil of a wind power generator according to claim 7. Furthermore, the operation parameter of the wind power generator is received from the input device, stored in the storage device in time series, and a fifth step is performed as operation parameter data,
In the fourth step,
Predicting future data of the additive concentration data based on past data of the additive concentration data and past data and future prediction data of the operating parameter data;
The method for monitoring lubricating oil of a wind power generator according to claim 7. The additive is at least one selected from an oily agent, an antiwear agent, an extreme pressure additive, an antioxidant, and an antifoaming agent.
The method for monitoring lubricating oil of a wind power generator according to claim 7.

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