Estimation device, estimation method, and bearing life extension method

Abstract

This helps to estimate the occurrence of delamination, etc. [Solution] The estimation device identifies the operating time for which the bearing temperature and rotational speed belong to each of the eight ranges, and estimates the occurrence of delamination and other issues based on the operating time for each of the eight ranges and the modified rated life for each of the eight ranges.

Description

[Technical Field]

[0001] This disclosure relates to an estimation device, an estimation method, and a method for extending the lifespan of bearings. [Background technology]

[0002] For example, Japanese Patent Publication No. 2021-12185 (Patent Document 1) discloses a life-life diagnosis method for diagnosing the lifespan of bearings. This life-life diagnosis method allows bearing managers and others to recognize the lifespan of bearings. [Prior art documents] [Patent Documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2021-12185 [Overview of the Initiative] [Problems that the invention aims to solve]

[0004] Generally, when a bearing fails due to its lifespan, the worker needs to replace it. However, replacing a bearing incurs significant costs. Therefore, it is preferable for the worker to recognize damage to the bearing before it fails due to its lifespan and to perform maintenance to extend its life. However, conventional lifespan diagnosis methods have not taken into consideration the detection of bearing damage before it fails.

[0005] This disclosure is made to solve the above-mentioned problems, and its purpose is to estimate at least one of the following: the occurrence of bearing damage, the future timing of such damage, the degree of bearing fatigue, or to extend the life of the bearing. [Means for solving the problem]

[0006] The estimation device of this disclosure comprises an interface for acquiring a first physical quantity of a bearing for which a rated life is defined, a memory for storing range information for a plurality of first ranges of the first physical quantity, and a control device. The modified rated life is associated with each of the plurality of first ranges. For each of the plurality of first ranges, the control device identifies a time parameter relating to the time in which the first physical quantity acquired by the interface belongs to that first range. The control device estimates at least one of the following: whether a first failure of the bearing has occurred or, if no first failure has occurred, the future timing of the first failure, and the fatigue level of the bearing, based on the time parameter for each of the plurality of first ranges and the modified rated life for each of the plurality of first ranges.

[0007] The estimation method of this disclosure comprises obtaining a first physical quantity of a bearing for which a rated life is defined. The estimation method also comprises identifying a time parameter relating to the time to which the first physical quantity belongs for each of a plurality of first ranges of the first physical quantity. Furthermore, the estimation method comprises estimating at least one of the following based on the time parameter for each of the plurality of first ranges and the modified rated life for each of the plurality of first ranges: the presence or absence of first damage to the bearing, the future timing of the occurrence of first damage, and the fatigue level of the bearing.

[0008] The life extension method of this disclosure comprises obtaining a first physical quantity of a bearing whose rated life is defined. The life extension method also comprises identifying a time parameter relating to the time to which the first physical quantity belongs for each of a plurality of first ranges of the first physical quantity. The life extension method also comprises estimating the future timing of the occurrence of a first failure of the bearing based on the time parameter for each of the plurality of first ranges and the modified rated life for each of the plurality of first ranges. Furthermore, the life extension method comprises extending the life of the bearing based on the timing of occurrence. The bearing comprises a predetermined member and a lubricant for lubricating the predetermined member. Extending the life of the bearing also includes at least one of the following: suppressing the operation of a rotating machine including the bearing; replacing the lubricant; flushing the lubricant; and adding an additive to the lubricant to reduce protrusions caused by the first failure. [Effects of the Invention]

[0009] According to the present disclosure, it is possible to estimate at least one of the occurrence of bearing damage, the future occurrence time of this damage, and the fatigue degree of the bearing, or to extend the life of the bearing.

Brief Description of the Drawings

[0010] [Figure 1] It is a diagram showing a configuration example of the management system of the present disclosure. [Figure 2] It is a diagram for explaining peeling. [Figure 3] It is a diagram for explaining micropitching. [Figure 4] It is a diagram showing a part of the reliability coefficient. [Figure 5] It is a diagram for explaining the contamination coefficient. [Figure 6] It is a diagram showing a function for calculating the corrected rated life. [Figure 7] It is a diagram for explaining the estimation of the total fatigue degree. [Figure 8] It is a functional block diagram of the estimation device. [Figure 9] It is a flowchart of the estimation device. [Figure 10] It is a flowchart of the estimation device. [Figure 11] It is a flowchart of the estimation device. [Figure 12] It is a diagram for explaining an example of soundness. [Figure 13] It is a diagram for explaining an image displayed on the operator terminal. [Figure 14] It is a diagram for explaining an image displayed on the operator terminal. [Figure 15] It is a diagram for explaining an image displayed on the operator terminal. [Figure 16] It is a diagram for explaining an image displayed on the operator terminal. [Figure 17] It is a diagram for explaining an image displayed on the operator terminal. [Figure 18] It is a flowchart showing the processing of the operator. [Figure 19] It is a flowchart showing the operator's process. [Figure 20] It is a flowchart showing the operator's process. [Figure 21] It is a flowchart showing the operator's process. [Figure 22] It is a flowchart showing the user's process.

Embodiments for Carrying Out the Invention

[0011] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings. In the embodiments described below, when referring to the number, amount, etc., unless otherwise specified, the scope of the present disclosure is not necessarily limited to the number, amount, etc. The same parts and corresponding parts are given the same reference numerals, and duplicate explanations may not be repeated. It is initially planned to use the configurations in the embodiments in appropriate combinations.

[0012] [Management System] FIG. 1 is a diagram showing a configuration example of the management system 10 of the present disclosure. The management system 10 of the present disclosure includes at least one wind power generation unit 60 and an estimation device 100. The estimation device 100 can communicate with the collection device 30, the user terminal 50 described later, and the operator terminal 70 described later through the network NW. In the present disclosure, the processing of the estimation device 100 includes both the estimation device 100 itself executing and the estimation device 100 and at least one information processing device (not shown) sharing the execution. In addition, a so-called CMS (Condition Monitoring System) is adopted in the management system 10.

[0013] The wind power generation unit 60 includes a wind power generation device 20 and a collection device 30. The wind power generation device 20 is a device that generates electricity by receiving wind power. The wind power generation device 20 corresponds to an example of the "rotary machine" of the present disclosure.

[0014] The wind power generation device 20 includes a bearing 120, a speed sensor 41, and a temperature sensor 42, etc. The bearing 120 is a rolling bearing or a sliding bearing, etc. In this embodiment, the bearing 120 is a rolling bearing. The bearing 120 includes rolling elements 191, raceway rings 192, and a lubricant 193, etc. The surface of the rolling element 191 and the surface of the raceway ring 192 are in contact. The lubricant 193 mainly lubricates the contact portion between the rolling element 191 and the raceway ring 192. The contact portion may be the rolling contact portion between the raceway surface of the raceway ring (inner ring or outer ring) and the rolling surface of the rolling element. Alternatively, the contact portion may be the sliding portion between the flange portion of the raceway ring and the end face of the rolling element. At least one of the rolling element 191 and the raceway ring 192 corresponds to the “predetermined member” of this disclosure.

[0015] The speed sensor 41 detects the rotational speed of the rotating shaft of the bearing 120 under inspection. The temperature sensor 42 detects the temperature (bearing temperature) of the bearing 120 under inspection. The rotational speed of the rotating shaft detected by the speed sensor 41 and the bearing temperature of the bearing 120 detected by the temperature sensor 42 are transmitted to the data collection device 30 as time-series data. Hereafter, the time-series data of rotational speed and the time-series data of bearing temperature may be collectively referred to as "operation data".

[0016] The speed sensor 41 is also referred to as the "first sensor." The rotational speed of the rotating shaft detected by the speed sensor 41 corresponds to the "first physical quantity" in this disclosure. The temperature sensor 42 is also referred to as the "second sensor." The bearing temperature of the bearing 120 detected by the temperature sensor 42 corresponds to the "second physical quantity" in this disclosure.

[0017] The data collection device 30 transmits operating data (rotational speed from the speed sensor 41 and bearing temperature from the temperature sensor 42) to the estimation device 100 via the network NW.

[0018] User terminal 50 is the terminal device of user A. "User" is typically the owner of the wind power generation equipment 20 or the operator of the wind power generation equipment 20. Also, user terminal 50 is typically a portable terminal that user A can carry with them. User terminal 50 may also be a stationary computer terminal.

[0019] The worker terminal 70 is the terminal device of worker B. A "worker" is typically a person who performs maintenance on the wind turbine 20. Maintenance includes inspection and repair of the wind turbine 20. Repair includes replacing the lubricant 193 in the bearing 120.

[0020] The worker terminal 70 is typically a portable terminal that worker B can carry. Alternatively, the worker terminal 70 may be a stationary computer terminal. Worker B performs the maintenance indicated in the image displayed on the worker terminal 70. In addition, worker B performs periodic inspections (maintenance) of the wind turbine 20. Worker B inputs inspection data showing the results of the periodic inspections into the worker terminal 70. The worker terminal 70 transmits the input inspection data to the estimation device 100. The inspection data may also be transmitted to the collection device 30, and then from the collection device 30 to the estimation device 100. Inspection data and operation data are collectively referred to as damage data.

[0021] Each of the at least one wind turbine 20 included in the management system 10 is assigned a wind turbine ID (identification). Each of the at least one user terminal 50 included in the management system 10 is assigned a user terminal ID. Each of the at least one worker terminal 70 included in the management system 10 is assigned a worker terminal ID. Furthermore, each bearing 120 of the at least one wind turbine 20 is assigned a bearing ID.

[0022] Each wind turbine ID is associated with at least one of the user terminal ID and / or worker terminal ID. The estimation device 100 maintains a table (not shown) that shows this association. The estimation device 100 refers to this table and transmits image data to the user terminal 50 or worker terminal 70.

[0023] The estimation device 100 includes a CPU (Central Processing Unit) 102, a memory 104, and an interface 106. The CPU 102 performs various processes. The CPU 102 corresponds to the “control device” in this disclosure. The control device may also be called a control circuit.

[0024] Memory 104 includes ROM (Read Only Memory) and RAM (Random Access Memory). ROM is non-rewritable, non-volatile memory, while RAM is volatile memory.

[0025] The ROM stores a program that describes the processing procedure for the CPU 102. The CPU 102 loads the program stored in the ROM into RAM or other memory and executes it. The interface 106 communicates with external devices (collection device 30, user terminal 50, and worker terminal 70) via the network NW.

[0026] When the estimation device 100 acquires operating data from the collection device 30, it performs the sorting process described below on the operating data in real time. The estimation device 100 uses the data after this sorting process (see Figure 7 described below) to detect damage. Damage in this embodiment includes micropitting and delamination. Micropitting and delamination can occur on at least one surface (contact portion) of the rolling element 191 and the raceway wheel 192 (see Figures 2 and 3 described below).

[0027] Delamination corresponds to an example of “first damage” in this disclosure. Micropitting corresponds to an example of “second damage” in this disclosure. The second damage may also include, for example, at least one of wear and false brinering. False brinering is a wear mark caused by minute vibrations of the bearing 120, etc.

[0028] [Exfoliation and micropitching] Next, we will describe delamination and micropitting, which can occur in the bearing 120. Typically, delamination is a more severe form of damage than micropitting. Damage scale refers to the approximate diameter of the delaminated area when viewed from a vertically upward direction, and a larger scale means a larger approximate diameter.

[0029] Delamination typically involves damage of 100 μm or more on at least one surface of the rolling element 191 and the raceway 192. Micropitting typically involves a collection of minute damages of approximately 10 μm on at least one surface of the rolling element 191 and the raceway 192. The scale of micropitting damage can be determined by the approximate diameter of each individual minute damage.

[0030] Figure 2 is a diagram illustrating delamination. In the example in Figure 2(A), delamination 180 that has occurred on the surface 191A of the rolling element 191 is shown. The occurrence of delamination 180 forms a recess 180A. Furthermore, the edge 180B of the recess 180A is formed.

[0031] In this embodiment, if it is determined that peeling 180 has occurred, an additive is added to the lubricant 193 by worker B or the like. Here, the additive is intended to increase the radius of curvature of the edge 180B of the recess 180A. The additive is also called a concentrate. The additive includes a first component, a second component, graphite, and muscovite. The first component is a component belonging to a three-layer silicate. The second component is at least one of bentonite, pyrogenic silicic acid, and talc.

[0032] Figure 2(B) shows an example of peeling 181 after the additive has been added to the lubricant 193 and the wind power generation device 20 has been operated for a predetermined period of time. After the additive has been added to the lubricant 193, when the bearing 120 is driven, the additive added to the lubricant 193 promotes wear of the edge portion 180B, causing the radius of curvature of the edge portion to increase. Figure 2(B) shows the edge portion 181B and the recess 181A with an increased radius of curvature.

[0033] Furthermore, the cases in which delamination occurs include the following first and second cases. The first case is when delamination is formed due to the progression of micropitting. The second case is when foreign matter enters the bearing 120, an indentation is formed by the foreign matter, and this indentation progresses to form delamination.

[0034] Figure 3 is a diagram illustrating micropitching. In the example in Figure 3(A), micropitching 170 that has occurred on the surface 191A of the rolling element 191 is shown. The occurrence of micropitching 170 forms numerous recesses 170A. Furthermore, protrusions 170B are formed on the edges of the recesses 170A.

[0035] In this embodiment, if it is determined that micro-pitching 170 has occurred, an additive is added to the lubricant 193 by worker B or the like.

[0036] Figure 3(B) shows an example of micropitting 171 after the additive has been added to the lubricant 193 and the wind power generation device 20 has been operated for a predetermined period. When the bearing 120 is driven after the additive has been added to the lubricant 193, the additive added to the lubricant 193 promotes wear of the protrusions 170B, and the height of the protrusions 170B is reduced. Figure 3(B) shows these reduced protrusions 171B. Figure 3(B) also shows the recesses 171A after the additive has been added to the lubricant 193. In this way, the addition of the additive to the lubricant 193 promotes the settling of the surface roughness of the rolling elements 191. This promotion of settling occurs not only for the protrusions formed by the occurrence of micropitting, but also for the surface roughness formed by machining during the manufacturing of the rotating body. Furthermore, the promotion of settling also occurs similarly for the surface roughness of the rolling elements that are the counterparts to the rotating body.

[0037] Furthermore, the process of adding additives to the lubricant 193 includes not only the process of adding additives to the existing lubricant 193 of the bearing 120, but also the process of replacing the lubricant 193 with a lubricant that contains additives.

[0038] [Method for estimating delamination] Next, the method for estimating the timing of delamination using the estimation device 100 will be explained. In the following, the period from the start of operation of the wind power generation device 20 to the estimated timing of delamination will also be referred to as the "delamination life." Similarly, the period from the start of operation of the wind power generation device 20 to the estimated timing of micropitting will also be referred to as the "micropitting remaining life."

[0039] In this embodiment, the estimation device 100 estimates the future timing of delamination using the calculated value of the modified rated life L of the bearing 120 (rolling bearing) in accordance with ISO 281 (2007). The bearing 120 has a specified basic dynamic load rating. ISO 281 (2007) specifies a method for calculating the life (basic rated life) when used under ideal operating conditions, based on this basic dynamic load rating and the load applied to the bearing. The "rated life" in this disclosure corresponds to this basic rated life. Furthermore, ISO 281 (2007) specifies a method for calculating the life (modified rated life) that takes operating conditions into account by multiplying the basic rated life by a coefficient that takes into account life variations due to operating conditions. Thus, the modified rated life is the life calculated from the basic rated life.

[0040] The modified rated life L is calculated using the following formula (1). Note that the notation of coefficients and other terms in the following explanation differs from the notation specified in ISO 281 (2007) for convenience.

[0041] L = a1·a2·Lx (1) However, a1 on the right side of equation (1) is the reliability coefficient, which will be explained in Figure 4 below. Also, a2 on the right side of equation (1) is calculated using equation (6) below. Lx on the right side of equation (1) is the rated life as described above. If bearing 120 is a ball bearing, the rated life is specified by equation (2). Also, if bearing 120 is a roller bearing, the rated life is specified by equation (3).

[0042] Lx = (C / P) 3 (2) Lx = (C / P) 10 / 3 (3) In equations (2) and (3), C is the basic same load rating (N) and is specified for each type of bearing. For example, if bearing 120 is a radial bearing, the basic same load rating C is Cr. If bearing 120 is a thrust bearing, the basic same load rating C is Ca.

[0043] Furthermore, P in equations (2) and (3) is the equivalent dynamic load (N), which is a value calculated from the equivalent dynamic load derived from the radial load and the axial load. For example, if bearing 120 is a radial bearing, the equivalent dynamic load P is the equivalent dynamic radial load Pr. If bearing 120 is a thrust bearing, the equivalent dynamic load P is the equivalent dynamic axial load Pa.

[0044] Furthermore, the basic rated life may be expressed in hours by the following formula (4). L'=(10 6 / 60n)·L (4) However, L on the right side of equation (4) is the basic rated life as described above, and n is the rotational speed (min -1 )

[0045] The dynamic equivalent load P of the bearing 120 may vary depending on the wind conditions at the installation site of the wind turbine 20. Therefore, the dynamic equivalent load P is estimated from a relational equation that shows the relationship between P and the rotational speed of the main shaft of the bearing 120. If such a relational equation does not exist, the dynamic equivalent load P used is the maximum load that can occur within the required lifespan of the wind turbine 20, or the dynamic equivalent load that is most likely to occur within the required lifespan. The required lifespan is the operating period required for the wind turbine 20, and is a predetermined period.

[0046] Furthermore, a1 in equation (1) is a coefficient (reliability coefficient) that indicates the reliability of the estimated peeling lifetime. Figure 4 shows a part of the reliability coefficient a1. Figure 4 shows an example of the reliability coefficient when the reliability is 90% or higher.

[0047] In the example in Figure 4, the reliability coefficient a1 decreases as the reliability of the peeling life increases. In other words, the lower the reliability of the peeling life calculated by equation (1) above, the longer the modified rated life calculated by equation (1). As will be described later, the longer the modified rated life, the longer the calculated peeling life. In other words, the lower the reliability, the longer the calculated peeling life.

[0048] In the example in Figure 4, a reliability of 90% means that the reliability of the estimated delamination life is 90%, and the reliability coefficient a1 is a coefficient that represents how much the life increases or decreases relative to the basic rated life when the reliability is not 90%. For example, in the example in Figure 4, if the reliability is 90%, the reliability coefficient a1 will be "1".

[0049] Furthermore, the confidence coefficient a1 when the confidence level is less than 90% can be calculated using the following formula (5).

[0050]

number

[0051] (5) However, in equation (5), n is 100 minus the confidence level. For example, if the confidence level is 80%, then n = 20. Also, e is the Weibull slope. If bearing 120 is a ball bearing, then e is "10 / 9". If bearing 120 is a roller bearing, then e is "9 / 8".

[0052] Furthermore, a2 in equation (1) above is a correction coefficient. This correction coefficient is a coefficient that reflects the lubrication conditions, the presence of foreign matter (sand and dust or wear particles from machine parts), or the interaction of these influencing factors for the peeling life of the bearing 120. a2 is calculated by a function of the following equation (6).

[0053]

number

[0054] (6) Here, Cu in equation (6) is the fatigue limit load, which is the load at which a stress equivalent to the material's fatigue limit occurs at the maximum load contact point of the raceway of the bearing 120. Cu is specified according to the type of bearing. e in equation (6) is the contamination coefficient. The contamination coefficient e is a value that indicates the degree of cleanliness of the bearing 120; the higher the contamination coefficient e, the cleaner the bearing 120 is.

[0055] For example, foreign matter (e.g., hard contaminant particles) mixed into the lubricant 193 may form indentations on the surface of the bearing 120 (the raceway or rolling surface in Figure 2 or 3). The contamination coefficient e reflects the reduction in delamination life due to the presence of these indentations. The value of the contamination coefficient e can be determined by various methods.

[0056] Figure 5 is a diagram illustrating the contamination coefficient e. In the example in Figure 5, the contamination level based on the contamination coefficient e is divided into seven levels. Furthermore, in the example in Figure 5, the levels are divided according to the pitch diameter D of the bearing 120. In the example in Figure 5, the levels are divided according to whether the pitch diameter D is 100 mm or more. For example, if the contamination level of a bearing 120 with a pitch diameter D of 100 mm or more is 0.85, then this bearing 120 is judged to have a high degree of cleanliness.

[0057] For example, as described above, worker B transmits inspection data obtained through periodic inspections to the estimation device 100 via worker terminal 70. The manager of the estimation device 100 determines the contamination coefficient e based on the inspection data using the table in Figure 5.

[0058] In addition, the contamination coefficient e when the lubricant is a lubricating oil may be defined, for example, using the filter filtration ratio βx(c) described in ISO 16889. Alternatively, the contamination coefficient e when the lubricant is a lubricating oil may be defined, for example, by referring to the oil contamination code described in ISO 4406. Diagrams for determining the contamination coefficient e using these methods are specified in ISO 281 (2007).

[0059] Furthermore, in this embodiment, the pollution coefficient e is determined by a method corresponding to the lubrication method of the bearing 120 to be maintained. For example, the bearing 120 incorporated into the gearbox of the wind power generation device 20 often uses lubricating oil as a lubricant. During the periodic inspection of the wind power generation device 20, the pollution degree code specified in ISO 4406 is checked for the lubricating oil of the bearing 120 for the gearbox, and the pollution coefficient e is determined based on the result.

[0060] As a variation, worker B may determine the value of the contamination coefficient e by visually inspecting the bearing 120. Alternatively, the estimation device 100 may calculate the contamination coefficient e using data transmitted from the collection device 30, the user terminal 50, or the worker terminal 70.

[0061] Furthermore, in equation (6), k is the viscosity ratio of the lubricant. Under favorable lubrication conditions, the raceway surface of the raceway ring 192 and the rolling surface of the rolling element 191 are separated from each other by an oil film. However, if the viscosity of the lubricant 193 is low, this separation becomes insufficient. As a result, contact occurs between the raceway ring and the rolling element due to surface roughness. This makes it easier for peeling cracks to occur from the surface (such as surface 191A in Figure 2). The viscosity ratio k is a coefficient that reflects the reduction in bearing peeling life due to this effect and can be calculated using the following equation (7).

[0062] k = A 1.3 (7) The A on the right-hand side of equation (7) is an index representing the separation state of the oil film between the raceway surface and the rolling surface of the bearing 120, and is also called the oil film parameter. The oil film parameter A is calculated by the following equation (8).

[0063] Oil film parameter A = h / {(R 2 +S 2 )} 0.5 (8) Here, the oil film thickness h represents the oil film thickness formed at the contact portion between the rolling element 191 and the raceway wheel 192. R represents the root mean square roughness of the contact surface of the rolling element 191 with the raceway wheel 192. S represents the root mean square roughness of the contact surface of the raceway wheel 192 with the rolling element 191. For R and S, if measured data is available, those values ​​should be used; otherwise, specified values ​​should be used.

[0064] Furthermore, h is calculated by the function H applied to the following equation (9). h=H(V, T) (9) Here, the function H on the right side of Equation (9) takes as inputs the rotational speed V of the bearing 120 and the temperature of the lubricant 193, etc. The rotational speed V of the bearing 120 is the rotational speed detected by the speed sensor 41. For the temperature of the lubricant 193, the bearing temperature detected by the temperature sensor 42 is used. The function H is a function that outputs a larger oil film thickness h as the rotational speed detected by the speed sensor 41 is higher. Also, the function H is a function that outputs a larger oil film thickness h as the temperature detected by the temperature sensor 42 is lower.

[0065] The oil film thickness h required for calculating the viscosity ratio k can be obtained using a general EHL (Elasto-hydrodynamic Lubrication) oil film thickness calculation formula. As EHL oil film thickness calculation formulas, there are the formula by Dowson et al. for line contact, and the formula by Chittenden et al. for point or elliptical contact, etc. Taking the formula by Chittenden et al. as an example, h can be obtained from the following Equation (10). For the sake of convenience, the notations of the coefficients etc. used in Equation (10) are made different from the coefficient notations of the actual formula by Chittenden et al. for convenience.

[0066]

Equation

[0067] (10) R in Equation (10) x and R y are the equivalent curvature radii in the rolling direction and the axial direction respectively, and can be obtained based on the dimensional specifications of the rolling elements and the raceways. E is the equivalent Young's modulus and is obtained from the Young's moduli of the materials of the rolling elements and the raceways. μ is the average value of the surface speeds of the raceway surface of the raceway and the rolling surface of the rolling element. As the rotational speed detected by the speed sensor 41 is higher, μ becomes larger. Also, W is the rolling element load. η and α are the atmospheric pressure viscosity and the viscosity-pressure coefficient of the lubricant respectively, and are values specific to the lubricant. As the bearing temperature detected by the temperature sensor 42 is smaller, α becomes larger. Also, R in Equation (10) x 、R yE and η are values ​​that depend on the bearing's dimensions, material, and type of lubricant.

[0068] Figure 6 shows the details of the function of equation (6). In the example in Figure 6, the bearing 120 is defined by whether it is a ball bearing or a roller bearing, and by the viscosity ratio k of the lubricant 193. In the example in Figure 6, when 0.1 ≤ viscosity ratio k < 0.4 and the bearing 120 is a ball bearing, equation A is used as the function of equation (6).

[0069] As described above, the estimation device 100 calculates the corrected rated life using equation (1) with respect to the rotational speed detected by the speed sensor 41 and the bearing temperature detected by the temperature sensor 42. Furthermore, as described above, function H is a function that outputs a larger oil film thickness h as the rotational speed detected by the speed sensor 41 increases. Also, function H is a function that outputs a larger oil film thickness h as the temperature detected by the temperature sensor 42 decreases.

[0070] Figure 7 is a diagram illustrating the method for estimating total fatigue by the estimation device 100. In Figure 7, the range information 121 stored by the estimation device 100 is shown to be the bearing temperature range and the rotational speed range.

[0071] In the example shown in Figure 7, the range ID, bearing temperature range, rotational speed range, modified rated life, operating hours (h), and accumulated fatigue degree related to delamination are specified from left to right. The accumulated fatigue degree corresponds to the “unit fatigue degree” in this disclosure.

[0072] A range ID is an ID assigned to each range. The bearing temperature range is a range relating to the bearing temperature of bearing 120. The bearing temperature range consists of N ranges (where N is an integer of 2 or more). In the example in Figure 7, the bearing temperature range consists of two ranges, that is, N=2. In the example in Figure 7, one range is, for example, 55 degrees or more and less than 60 degrees. Each of the N ranges corresponds to the “second range” of this disclosure.

[0073] The rotational speed range includes multiple ranges relating to the rotational speed of the bearing 120. In the example of Figure 7, the rotational speed range is a range obtained by further dividing the second range into at least one further range. The divided range corresponds to the “first range” of this disclosure. In other words, in the range information, each of the multiple second ranges is composed of at least one first range.

[0074] In the example in Figure 7, the second range where the bearing temperature is 55 degrees Celsius or higher but less than 60 degrees Celsius is comprised of four first ranges. One of these four first ranges is, for example, the range where the rotational speed is 3 rpm or higher but less than 4 rpm. Also in the example in Figure 7, the second range where the bearing temperature is less than 45 degrees Celsius is comprised of one first range. This one first range is the range where the rotational speed is 0 rpm or higher but less than 1 rpm.

[0075] Furthermore, the example in Figure 7 also specifies the period during which the wind power generation device 20 is shut down. In the example in Figure 7, the rotational speed and bearing temperature of the bearing 120 are divided into eight ranges. In the example in Figure 7, each of the eight ranges is assigned a range ID from M1 to M8. Hereafter, the range ID may be referred to as a reference code for the eight ranges. For example, the range with range ID M1 is also called "range M1".

[0076] The modified rated life is calculated for each range by the estimation device 100. Specifically, when predetermined conditions are met, the estimation device 100 obtains values ​​used to calculate the modified rated life (for example, the pollution coefficient e) from the worker terminal 70 or the like. The predetermined conditions are, for example, when the estimation device 100 receives a completion signal indicating that the periodic inspection by worker B has been completed. The estimation device 100 then calculates the modified rated life for each range ID. For example, for the modified rated life of range M1, the estimation device 100 calculates the modified rated life by substituting the median value of the bearing temperature range (57.5), the median value of the rotational speed range (3.5), and other predetermined values ​​necessary for the modified rated life (for example, the pollution coefficient e) into the above formula (1). The "median value of the rotational speed range" corresponds to the "value based on the first physical quantity defined in the first range" in this disclosure.

[0077] In the example shown in Figure 7, "10000" is calculated as the corrected rated life for range M1. The estimation device 100 also calculates the corrected rated life for other ranges. For range M8, the corrected rated life is considered to be infinite.

[0078] The operating time is the time during which the rotational speed and bearing temperature in past operating periods fall within the eight ranges shown in Figure 7. When the estimation device 100 acquires operating data from the collection device 30, it performs the sorting process described later on the operating data in real time. This sorting process defines the operating time shown in Figure 7. The operating time is an example of the "time parameter" in this disclosure. The time parameter may also be the operating time ratio obtained by dividing the operating time by the total operating time.

[0079] Figure 7 shows an example where, out of 1800 hours of operation in the past, 300 hours were determined to be within range M1 (the range where the bearing temperature is between 55°C and 60°C, and the rotational speed is between 3 rpm and 4 rpm).

[0080] The accumulated fatigue level G is the fatigue level related to delamination accumulated by operation within each range. The delamination life in this embodiment can be estimated using the concept of Miner's cumulative damage law (hereinafter referred to as Miner's law). In Miner's law, for example, if the modified rated life L1 is the operating condition in range M1, and the time of operation under this condition is h1, then the fatigue level for the operating period in range M1 is calculated as h1 / L1. The fatigue level is calculated similarly under other operating conditions.

[0081] In other words, the estimation device 100 calculates the fatigue level (accumulated fatigue level G) accumulated by operation within each range. Specifically, for each range ID, the estimation device 100 calculates the accumulated fatigue level G corresponding to the range ID by dividing the operating time corresponding to the range ID by the modified rated life corresponding to the range ID.

[0082] For example, the estimation device 100 calculates 0.03 (accumulated fatigue in range M1) for range M1 by dividing 300 (operating time) by 10000 (modified rated life). The estimation device 100 also calculates the accumulated fatigue for other ranges. The estimation device 100 then calculates the total fatigue by summing the accumulated fatigue of all range IDs. The total fatigue corresponds to "fatigue" in this disclosure.

[0083] The bearing 120 included in the wind power generation device 20 operates under conditions that change depending on the wind conditions. Taking this change into consideration, the estimation device 100 of this embodiment calculates the modified rated life L for the delamination of the bearing 120 under specific rotational speed and bearing temperature conditions (range M1 to M8). Therefore, in such cases, the estimation device 100 can calculate the accumulated fatigue degree G and total fatigue degree Gx corresponding to the time the bearing was operated under the changeable operating conditions, which determine the life until the final delamination of the bearing occurs.

[0084] Furthermore, the estimation device 100 calculates the total fatigue Gx accumulated in the bearing 120 during past operation (1800 hours in the example of Figure 7) using the following formula (11).

[0085]

number

[0086] (11) Here, r on the right-hand side of equation (11) is a variable that indicates the range ID, and R is the number of ranges. In the example in Figure 7, R is 8. Also, hr indicates the operating time when the range ID is r, and Lr indicates the operating time when the range ID is r. In the example in Figure 7, the estimation device 100 uses the above equation (11) to calculate the total fatigue level Gx as "0.206".

[0087] Furthermore, Minor's rule assumes that delamination occurs when the total fatigue level Gx reaches a predetermined value. In this embodiment, the predetermined value is "1". If the total fatigue level Gx is greater than 1, the estimation device 100 determines that delamination has already occurred.

[0088] On the other hand, if the total fatigue level Gx is less than 1, the estimation device 100 determines that delamination has not occurred. In the example in Figure 7, the total fatigue level is "0.206", and the estimation device 100 determines that delamination has not occurred at the time this "0.206" is calculated. When the estimation device 100 makes this determination, it is assumed that even after the total fatigue level is calculated, the wind power generation device 20 will continue to operate in the same manner as in the past operation (1800 hours). The estimation device 100 then estimates the delamination life (timing of delamination occurrence) using the following equation (12).

[0089] Peeling life = (Prescribed value / Total fatigue) × Total operating time (12) The total fatigue level is "0.206", the predetermined value is "1", and the total operating time to date is 1800h. Therefore, using the above formula (12), the delamination life is calculated to be approximately 8730h. In other words, the estimation device 100 estimates that the time when delamination occurs is approximately 8730h after the wind power generation device 20 has started operation.

[0090] Furthermore, the estimation device 100 can also estimate micropitting in the same way as delamination. In other words, the estimation device 100 can calculate the remaining lifespan of the bearing that is prone to micropitting. Therefore, the estimation device 100 can estimate whether micropitting has already occurred in the bearing 120, and even if micropitting has not yet occurred, it can estimate when micropitting will occur.

[0091] [Functional block diagram of estimation device 100] Figure 8 is a functional block diagram of the estimation device 100. The estimation device 100 comprises an acquisition unit 112, a processing unit 114, and a storage unit 116. The acquisition unit 112 corresponds to the interface 106 described above. The processing unit 114 corresponds to the CPU 102 described above and the "control device" of this disclosure. The storage unit 116 corresponds to the memory 104 described above.

[0092] The acquisition unit 112 of the estimation device 100 acquires the bearing ID and the aforementioned operating data from the collection device 30. The acquisition unit 112 also acquires the bearing ID and the aforementioned inspection data from the worker terminal 70. The operating data and inspection data acquired by the acquisition unit 112 are output to the processing unit 114.

[0093] The processing unit 114 stores the operating data and inspection data acquired by the acquisition unit 112 as past damage data 127. The past damage data 127 includes, for example, a contamination coefficient e. The processing unit 114 stores the past damage data 127 for each bearing ID.

[0094] The memory unit 116 also stores range information 121, a delamination life function 131, and a micropitching life function 132. The range information 121 includes the range ID, bearing temperature range, and rotational speed range shown in Figure 7. The delamination life function 131 is, for example, an equation for calculating the total fatigue degree Gx related to delamination, such as equation (11) above.

[0095] Furthermore, the micropitching life function 132 is, for example, an equation for calculating the total fatigue related to micropitching, and is disclosed, for example, in Japanese Patent Application No. 2023-192977, which is an application of the same applicant.

[0096] The processing unit 114 uses past damage data 127 (for example, the most recently transmitted contamination coefficient e) and the delamination lifetime function 131 to determine whether delamination has already occurred. If the processing unit 114 determines that delamination has not occurred, it estimates the future timing of delamination (delamination lifetime).

[0097] The processing unit 114 uses past damage data 127 (for example, the most recently transmitted contamination coefficient e) and the micropitching lifetime function 132 to determine whether or not micropitching has already occurred. If the processing unit 114 determines that micropitching has not occurred, it estimates the future timing of micropitching (remaining micropitching lifetime).

[0098] Furthermore, the processing unit 114 generates recommended image data indicating recommended maintenance procedures to extend the lifespan of the bearing 120, based on the estimation results. The processing unit 114 then transmits the image data to a predetermined terminal (user terminal 50 or worker terminal 70).

[0099] [flowchart] Figures 9 to 11 are flowcharts showing the main processes of the estimation device 100. Worker B performs a periodic inspection and sends a message to the worker terminal 70 indicating that the periodic inspection is complete. The worker terminal 70 sends a completion signal to the estimation device 100 indicating that the inspection is complete. When the estimation device 100 receives this completion signal, it starts the process shown in this flowchart.

[0100] First, in step S2, the estimation device 100 calculates the modified rated life for each range using the pollution coefficient e and equation 1. Here, equation 1 is the equation when the confidence coefficient a1 in equation (1) is the first value (for example, 90%). Furthermore, in step S2, the estimation device 100 identifies the operating time for each range of the range information 121 described in Figure 7.

[0101] Next, in step S4, the estimation device 100 calculates the delamination life using equation (12). Next, in step S6, the estimation device 100 determines whether delamination has already occurred based on the total fatigue degree Gx. For example, if the total fatigue degree Gx is 1 or greater, the estimation device 100 determines that delamination has already occurred. If delamination has already occurred (YES in step S6), in step S8, the estimation device 100 sends recommended image data recommending controlled operation of the wind power generation device 20 to the user terminal 50. Controlled operation is an operation to reduce the rotational speed of the rotating body of the bearing 120, for example, an operation to reduce the rotational speed of the main shaft of the wind power generation device 20. By performing such controlled operation, the number of loads per unit time that cause delamination can be reduced, and thus the expansion of delamination can be suppressed.

[0102] Furthermore, in step S8, the estimation device 100 transmits recommended image data to the operator terminal 70 recommending the addition of an additive to the lubricant 193. Thus, the estimation device 100 can recommend that the radius of curvature of the edge portion 180B caused by peeling can be increased by adding the additive.

[0103] On the other hand, if the result in step S6 is NO, then in step S10, the estimation device 100 determines whether or not delamination will occur within the required lifespan of the wind power generation device 20 from the present time. The estimation device 100 determines whether or not the delamination lifespan is longer than the required operating period (required lifespan) of the wind power generation device 20. If the delamination lifespan is equal to or greater than the required lifespan, the estimation device 100 determines that delamination will not occur within the required lifespan of the wind power generation device 20 (NO in step S10). On the other hand, if the delamination lifespan is less than the required lifespan, the estimation device 100 determines that delamination will occur within the required lifespan of the wind power generation device 20 (YES in step S10).

[0104] If the result in step S10 is NO, in step S12 the estimation device 100 sends recommended image data recommending continued operation of the wind power generation device 20 to the user terminal 50. Then the process ends.

[0105] On the other hand, if it is determined that YES is desired in step S10, the process proceeds to step S14. In step S14, the estimation device 100 determines whether or not user A has input indicating a desire to extend the lifespan of the wind power generation equipment 20. In step S10, for example, the estimation device 100 sends inquiry image data to the user terminal 50, which contains a message asking user A whether or not they wish to extend the lifespan of the wind power generation equipment 20. User A then inputs a response into the user terminal 50 displaying the inquiry image. This response can be either "I wish to extend the lifespan of the wind power generation equipment 20" or "I do not wish to extend the lifespan of the wind power generation equipment 20".

[0106] The user terminal 50 transmits the response image data showing the answer to the estimation device 100. Based on the content of this response image, the estimation device 100 performs the process in step S14. If it is determined to be NO in step S14, the need for maintenance (life extension treatment) for worker B is low, and the process proceeds to step S12.

[0107] On the other hand, if the result in step S14 is YES, in step S16 the estimation device 100 determines whether or not peeling will occur before the next periodic inspection. The period from when the process in step S16 is performed until the next periodic inspection is performed is also referred to as the "period until the next inspection".

[0108] In step S16, the estimation device 100 compares the sum of the period until the next inspection and the total operating time with the peeling life. If the peeling life is less than the sum of the period until the next inspection and the total operating time, the estimation device 100 determines that peeling will occur before the next periodic inspection (YES in step S16). In this case, it is estimated that the bearing 120 is deteriorating. The process then proceeds to step S18.

[0109] On the other hand, if the peeling life is longer than the period until the next inspection (NO in step S16), the estimation device 100 determines that peeling will not occur until the next periodic inspection. Then, the process proceeds to step S25 in Figure 10.

[0110] In step S18, the estimation device 100 determines whether the contamination coefficient e most recently obtained from the worker terminal 70 is less than a predetermined threshold. For example, if the pitch diameter D is 100 mm or more, the threshold is set to 0.6. If the pitch diameter D is less than 100 mm, the threshold is set to 0.5.

[0111] If the contamination coefficient e is less than the threshold (YES in step S18), that is, if the bearing 120 is contaminated, the process proceeds to step S20. When it is determined to be YES in step S18, it is assumed that the peeling determined to be YES in step S10 is caused by contamination by foreign matter mixed into the lubricant 193 of the bearing 120. In this embodiment, it is assumed that an indentation has been formed by the foreign matter, and in step S20, the estimation device 100 sends recommended image data to the operator terminal 70 recommending the addition of an additive to the lubricant 193 to reduce the height of the protrusion formed on the edge of the indentation. The process then ends.

[0112] On the other hand, if NO is determined in step S18, that is, if the bearing 120 is not contaminated, then in step S22, the estimation device 100 determines whether or not micropitting has occurred. In step S22, the estimation device 100 determines whether or not micropitting has already occurred based on the total fatigue degree related to the remaining life of micropitting. For example, if the total fatigue degree of micropitting is 1 or more, the estimation device 100 determines that micropitting has already occurred (YES in step S22). In this case, the process proceeds to step S20. In step S20, the recommended additive is added to the lubricant 193, which reduces the protrusions 170B caused by micropitting 171 (see Figure 3), thereby suppressing the expansion of micropitting.

[0113] On the other hand, in step S22, if the total fatigue level of micropitting is less than 1, the estimation device 100 determines that micropitting has not occurred (NO in step S22). The determination of NO in step S22 suggests that the reason for the YES determination in step S16 was that the wind turbine 20 experienced a large dynamic equivalent load for an extended period due to wind conditions. This condition is difficult to resolve with maintenance of the bearing 120. Therefore, in step S24, the estimation device 100 sends recommended image data to the user terminal 50 recommending controlled operation of the wind turbine 20. By executing controlled operation of the wind turbine 20, the number of loads applied to the bearing 120 per unit time can be reduced, thereby extending the lifespan of the bearing 120. The process then ends.

[0114] Furthermore, if NO is determined in step S16, in step S25 of Figure 10, the estimation device 100 calculates the peeling life using the second formula and calculates the corrected rated life based on this peeling life. Here, the second formula is one in which a second value (for example, 80%) with a lower reliability coefficient than the first formula (see step S4) is adopted. In other words, even if the values ​​input to the first and second formulas (bearing temperature, rotational speed, etc.) are the same, the peeling life calculated by the second formula is longer than the peeling life calculated by the first formula. Furthermore, in step S25, the estimation device 100 calculates the peeling life based on the corrected rated life calculated by the second formula.

[0115] Next, in step S26, the estimation device 100 determines whether or not delamination will occur within the required lifespan of the wind power generation device 20, based on the delamination lifespan calculated in step S25. This determination is the same as the method described in step S10. If the determination in step S26 is NO, that is, if delamination will occur within the required lifespan according to the delamination lifespan calculated by the first equation (YES in step S10), but delamination will not occur within the required lifespan according to the delamination lifespan calculated by the second equation (NO in step S26), the process proceeds to step S28.

[0116] If the result in step S26 is NO, there is a low probability (80%) that delamination will occur within the required lifespan as determined in step S26, meaning that delamination may not occur within the required lifespan. Therefore, in step S28, the estimation device 100 sends recommended image data to the user terminal 50, recommending further observation.

[0117] Furthermore, if the result in step S26 is YES, that is, if it is determined that peeling will occur within the required lifespan regardless of whether the peeling lifespan calculated using the first formula or the second formula is used, the process proceeds to step S30.

[0118] In step S30, similar to step S18, it is determined whether the contamination coefficient e is below a predetermined threshold. If the contamination coefficient e is below the threshold (YES in step S30), that is, if the bearing 120 is contaminated, the process proceeds to step S32. If it is determined to be YES in step S30, it is assumed that the cause of the YES determination in step S26 is the deterioration of the lubricating oil.

[0119] Therefore, in this embodiment, from step S32 onward, a process related to the maintenance of the lubricant 193 is performed. The maintenance of the lubricant 193 includes replacing the lubricant 193 or flushing the lubricant 193.

[0120] In step S32, the estimation device 100 determines whether the lubricant 193 of the bearing 120 to be inspected has been maintained in the past, using past damage data 127. The past damage data 127 includes information indicating whether the lubricant 193 has been maintained in the past.

[0121] If the result in step S32 is NO, that is, if it is assumed that the reason the contamination coefficient e is lower than the threshold is due to the deterioration of the lubricant 193, the process proceeds to step S34. In step S34, the estimation device 100 transmits the following recommended image data to the operator terminal 70. This recommended image indicates that the presence or absence of indentations should be checked, and if indentations are found, an additive should be added to the lubricant 193; if no indentations are found, maintenance of the lubricant should be performed.

[0122] On the other hand, if it is determined to be YES in step S32, in step S36 the estimation device 100 determines, based on past damage data 127, whether the content of the bearing material in the lubricant 193 is increasing. In the example in Figure 10, the material of the bearing 120 is iron. The past damage data 127 includes the iron content of the lubricant 193 obtained from at least two past periodic inspections. If it is determined to be YES in step S36, the process proceeds to step S20. If it is determined to be YES in step S36, it is assumed that the contamination coefficient e has decreased due to wear particles (for example, iron) discharged from parts of the bearing 120 (YES in step S30). It is assumed that indentations have been formed or will be formed in the future by these wear particles. Therefore, in step S20, the estimation device 100 transmits the image data from step S20 in order to reduce the protrusions caused by the indentations.

[0123] Furthermore, if NO is determined in step S36, it is assumed that the contamination coefficient has decreased due to foreign matter entering the bearing 120, rather than the wear particles mentioned above (YES in step S30). Therefore, in step S38, the estimation device 100 transmits the following recommended image data to the operator terminal 70. This recommended image is an image indicating that the bearing 120 should be inspected for the presence or absence of indentations, and if indentations are found, an additive should be added to the lubricant 193; if there are no indentations, maintenance of the lubricant should be performed. This recommended image also indicates that if there is an abnormality in the foreign matter blocking mechanism of the bearing 120, repairs should be made to the foreign matter blocking mechanism. Then the process is completed. The foreign matter blocking mechanism is, for example, the seal of the bearing 120 or the oil filter of the speed increaser.

[0124] Furthermore, if the result in step S30 is NO, then in step S40 of Figure 11, the estimation device 100 determines whether or not micropitching has already occurred. The process in step S40 is the same as in step S22.

[0125] If the result in step S40 is YES, in step S42 the estimation device 100 transmits the following recommended image data to the operator terminal 70. This recommended image indicates that the presence or absence of micropitting should be checked during the next periodic inspection, and if micropitting is present, maintenance should be performed by adding an additive to the lubricant. Then the process is completed.

[0126] If the result in step S40 is NO, then in step S44 the estimation device 100 determines whether or not micropitting will occur within the required lifespan of the bearing 120. For example, it determines whether or not the micropitting lifespan is longer than the required lifespan of the wind turbine 20. If the micropitting lifespan is longer than or equal to the required lifespan, the estimation device 100 determines that micropitting will not occur within the required lifespan of the wind turbine 20 (NO in step S44). On the other hand, if the micropitting lifespan is shorter than the required lifespan, the estimation device 100 determines that micropitting will occur within the required lifespan of the wind turbine 20 (YES in step S44).

[0127] If the result in step S44 is YES, then in step S46, the estimation device 100 determines whether the degree of deterioration of the lubricant 193 has increased, based on past damage data 127. Here, "the degree of deterioration of the lubricant 193 has increased" includes at least one of the following: a decrease in the kinematic viscosity of the lubricant 193, and an increase in the water content of the lubricant 193.

[0128] If the determination in step S46 is YES, in step S48 the estimation device 100 sends a recommendation image data to the operator terminal 70 recommending that the lubricant 193 be replaced with a new lubricant with a higher kinematic viscosity than the lubricant 193. Then the process ends.

[0129] Furthermore, if the result is NO in step S44 or NO in step S46, the process proceeds to step S28.

[0130] [Health level] As shown in Figures 9 to 11, the estimation device 100 transmits image data to the operator terminal 70 or the like. In this embodiment, the recommended image data includes the soundness of the bearing 120. This is a parameter indicating the soundness of the bearing 120. Figure 12 is a diagram illustrating an example of the soundness.

[0131] In the example in Figure 12, as indicated in the remarks column, a soundness level of 1 is the healthiest, and a soundness level of 14 is the unhealthiest. For example, if the estimation device 100 performs the process in step S12 after determining NO in step S10, it will determine that the soundness level of the bearing 120 is "1". The soundness level table shown in Figure 12 is stored in the storage unit 116. The estimation device 100 refers to this soundness level table to determine the soundness level.

[0132] [Recommended image] Next, the recommended images displayed by the user terminal 50 or the worker terminal 70 will be described. The recommended images include images that recommend maintenance of the wind turbine 20 to user A or worker B.

[0133] Figure 13 is a diagram illustrating the image 71 displayed by the worker terminal 70. Image 71 is an example of an image displayed based on the image data transmitted in the processing of step S8. Image 71 includes an estimation image 71A showing the estimation result of the estimation device 100, a recommendation image 71B showing the processing recommended to worker B, and a health image 71C showing the health of the bearing 120.

[0134] In the example in Figure 13, the estimated image 71A shows that delamination has already occurred. The recommended image 71B is an image to recommend that worker B add an additive to the lubricant 193. The soundness image 71C shows "14" as the soundness level.

[0135] Figure 14 is a diagram illustrating the image 72 displayed by the worker terminal 70. Image 72 is an example of an image displayed based on the image data transmitted in step S34.

[0136] Image 72 includes an estimated image 72A, a recommended image 72B, a health assessment image 72C, and a time-of-onset image 72D indicating the timing of the peeling.

[0137] In the example in Figure 14, the estimated image 72A is an image that shows delamination will occur in the future. The recommendation image 72B is an image that recommends worker B to inspect for the presence or absence of indentations, add additives to lubricant 193 if indentations are found, and perform lubricant maintenance if no indentations are found. The soundness image 72C shows that the soundness is "9" if indentations are found, and "6" if no indentations are found. The timing image 72D shows AA as the timing of the future occurrence of delamination.

[0138] Figure 15 is a diagram illustrating the image 73 displayed by the worker terminal 70. Image 73 is an example of an image displayed based on the image data transmitted in the processing of step S20 after a YES determination in step S22.

[0139] In the example in Figure 15, the estimated image 73A shows that micropitching has already occurred. The recommended image 73B is an image to recommend that worker B add an additive to the lubricant 193. The soundness image 73C shows "11" as the soundness level.

[0140] Figure 16 is a diagram illustrating the image 74 displayed by the worker terminal 70. Image 74 is an example of an image displayed based on the image data transmitted in step S48.

[0141] In the example in Figure 16, the estimated image 74A is an image indicating that micropitting will occur in the future. The recommended image 74B is an image recommending that lubricant 193 be replaced with a new lubricant with a higher kinematic viscosity than lubricant 193. In the soundness image 74C, "7" is displayed as the soundness level. In the timing image 74D, BB is displayed as the timing of the future occurrence of micropitting.

[0142] Figure 17 is a diagram illustrating the image 75 displayed by the user terminal 50. Image 75 is an example of an image displayed based on the image data transmitted in step S8. In the example in Figure 17, the estimated image 75A is an image indicating that delamination has already occurred. The recommended image 75B is an image to recommend controlled operation of the wind power generation equipment to user A. In the health image 75C, "14" is displayed as the health level.

[0143] [Processing flow for User A or Worker B] Figure 18 is a flowchart showing the actions taken by worker B when the estimation device 100 determines that peeling has already occurred. For example, worker B, after viewing image 71 in Figure 13, performs the actions shown in Figure 18. In step S112, worker B adds an additive to the lubricant 193.

[0144] Figure 19 is a flowchart showing the actions taken by worker B when the estimation device 100 determines that delamination will occur in the future. For example, worker B, after viewing image 72 in Figure 14, performs the actions shown in Figure 19. In step S122, worker B determines whether or not there is an indentation on the bearing 120. If there is an indentation (YES in step S122), in step S124, worker B adds an additive to the lubricant 193. On the other hand, if there is no indentation (NO in step S122), in step S126, worker B performs maintenance on the lubricant 193 (replacement of lubricant 193 or flushing of lubricant 193).

[0145] Figure 20 is a flowchart showing the actions taken by worker B when the estimation device 100 determines that micropitching has already occurred. For example, worker B, after viewing image 73 in Figure 15, performs the actions shown in Figure 20. In step S132, worker B adds an additive to the lubricant 193.

[0146] Figure 21 is a flowchart showing the actions taken by worker B when the estimation device 100 determines that micropitching will occur in the future. For example, worker B, after viewing image 74 in Figure 16, performs the actions shown in Figure 21. In step S142, worker B replaces lubricant 193 with a new lubricant that has a higher kinematic viscosity than lubricant 193.

[0147] Figure 22 is a flowchart showing the process of user A when the estimation device 100 determines that delamination has already occurred. For example, user A, who has viewed image 75 in Figure 17, performs the process shown in Figure 22. In step S152, user A performs a controlled operation of the wind power generation device 20.

[0148] [Summary] (1) Generally, when a bearing 120 fails due to the end of its lifespan, worker B needs to replace the bearing 120. However, replacing the bearing 120 incurs significant costs. Furthermore, the bearing 120 (wind turbine 20) will experience downtime during the replacement process. Therefore, it is preferable for worker B to recognize any damage to the bearing 120 before it fails due to the end of its lifespan and to perform maintenance on the bearing 120.

[0149] Therefore, as explained in Figure 7 and other figures, the estimation device 100 of this embodiment estimates that delamination of the bearing 120 has already occurred. Furthermore, if the estimation device 100 estimates that delamination of the bearing 120 has not yet occurred, it estimates the future timing of this delamination. Thus, a person who observes the estimation result can recognize the delamination of the bearing 120 before it fails, and thus extend the lifespan of the bearing 120.

[0150] Furthermore, as shown in Figure 7, the estimation device 100 estimates whether delamination has occurred based on the operating time for each of the multiple ranges (ranges M1 to M8) and the modified rated life for each of the multiple ranges. Therefore, even if the operating conditions of the bearing 120 change and the bearing temperature and rotational speed of the bearing 120 change, it is possible to appropriately estimate whether delamination has occurred.

[0151] (2) In the example shown in Figure 7, the range is further subdivided by bearing temperature range and rotational speed range. Therefore, the estimation device 100 can estimate that delamination has occurred based on the operating time for each subdivided range and the modified rated life for each of the multiple ranges. Thus, the estimation accuracy can be improved.

[0152] (3) Furthermore, the pollution coefficient e changes depending on the operating period of the bearing 120. In this embodiment, the estimation device 100 uses the changing pollution coefficient e to calculate the corrected rated life for each of several ranges. Thus, the estimation device 100 can perform estimations according to the operating period of the bearing 120.

[0153] (4) The estimation device 100 also calculates the accumulated fatigue level for each of the multiple ranges by dividing the operating time in each range by the modified rated life associated with that range. The estimation device 100 then estimates the total accumulated fatigue level for the multiple ranges as the fatigue level. Therefore, even if the operating conditions of the bearing 120 change and the rotational speed and bearing temperature of the bearing 120 change, the estimation device 100 can calculate an appropriate fatigue level.

[0154] (5) Furthermore, as described in step S6 and elsewhere, the estimation device 100 estimates the time when the fatigue level reaches a predetermined value (in this embodiment, "1") as the time when peeling occurs. Therefore, the estimation device 100 can appropriately estimate the time when peeling occurs.

[0155] (6) Furthermore, as explained in Figure 7 and other figures, the estimation device 100 estimates the peeling life in such a way that the peeling life becomes shorter as the total fatigue level increases. Therefore, the estimation device 100 can appropriately estimate the timing of peeling occurrence.

[0156] (7) The estimation device 100 also displays the estimation result on the user terminal 50 or the worker terminal 70 (Figures 13 to 17). Therefore, user A or worker B can recognize the estimation result of the estimation device 100.

[0157] (8) The estimation device 100 also determines a recommended treatment for peeling based on its estimation results (see Figures 9 to 11). The estimation device 100 then displays an image indicating the recommended treatment on the user terminal 50 or the worker terminal 70 (Figures 13 to 17). Thus, user A or worker B can recognize the recommended treatment for peeling.

[0158] (9) The estimation device 100 also displays the soundness shown in Figure 12 on the user terminal 50 or the worker terminal 70 (Figures 13 to 17). Thus, user A or worker B can recognize the soundness of the bearing 120.

[0159] (10) When the estimation device 100 estimates that peeling has occurred, it determines that the recommended actions are to add an additive to the lubricant and to suppress the operation of the wind power generation device 20 (see step S8 in Figure 9). Then, as shown in Figure 18 or Figure 22, when this recommended action is performed by user A or worker B, the expansion of peeling can be suppressed.

[0160] (11) If the estimation device 100 estimates that peeling will occur in the future, it determines that the recommended treatment is to add an additive to the lubricant (step S20) or to perform maintenance on the lubricant 193 (steps S34, S38). Then, as shown in Figure 19, when this recommended treatment is performed by worker B, the occurrence of peeling can be suppressed.

[0161] (12) Furthermore, if the estimation device 100 determines that micropitching is occurring, it decides to add an additive to the lubricant 193 (step S42) as a recommended treatment. Then, as shown in Figure 20, when this recommended treatment is performed by operator B, the expansion of micropitching can be suppressed.

[0162] (13) When the estimation device 100 determines when micropitting is about to occur, it decides that the recommended procedure is to replace the lubricant 193 with a new lubricant that has a higher kinematic viscosity than the lubricant 193 (step S48). As shown in Figure 21, when this recommended procedure is performed by operator B, the expansion of micropitting can be suppressed.

[0163] Thus, the process for extending the life of the bearing 120 includes at least one of the following: controlled operation of the wind power generation device 20 (Figure 22), replacement of the lubricant 193 (Figures 19 and 21), flushing of the lubricant 193 (Figure 19), and addition of additives to the lubricant 193 (Figures 18 to 20). Therefore, the life of the bearing 120 can be adequately extended.

[0164] <Other Embodiments> (1) The flows in Figures 18 to 22 described above illustrate a configuration performed by a human (user A or worker B). However, at least some of the processes in the flows in Figures 18 to 22 may be performed by a work robot (work device).

[0165] (2) In the above-described embodiment, a configuration was described in which image 71 and image 75 are displayed on separate terminals (user terminal 50 and worker terminal 70). However, image 71 and image 75 may be displayed on the same terminal. With such a configuration, the same worker performs the processes shown in Figures 18 and 22.

[0166] (3) The estimation device 100 may be configured to display the total fatigue level on a designated terminal. With this configuration, the person viewing the designated terminal can recognize the total fatigue level.

[0167] (4) In the above-described embodiment, a configuration was described in which the estimation device 100 calculates the corrected rated life for each range each time a predetermined condition is met. However, the corrected rated life for each range may be a predetermined value.

[0168] [Note] (Note 1) An interface for obtaining the first physical quantity of a bearing whose rated life is specified, A memory that stores range information for multiple first ranges of a first physical quantity, Equipped with a control device, The modified rated life is associated with each of the aforementioned multiple first ranges, The control device is For each of the plurality of first ranges, the interface identifies a time parameter relating to the time period within that first range, An estimation device for estimating at least one of the following: whether a first damage has occurred in the bearing, or, if no first damage has occurred, the future timing of the first damage, and the fatigue level of the bearing, based on the time parameters for each of the plurality of first ranges and the modified rated life for each of the plurality of first ranges.

[0169] (Note 2) The interface acquires the second physical quantity of the bearing, The aforementioned range information includes information on a plurality of second ranges, The plurality of second ranges include at least one of the first ranges, The estimation device according to Appendix 1, wherein the control device identifies as the time parameter a parameter relating to time to which the second physical quantity belongs in each of the plurality of second ranges, and to which the first physical quantity belongs in a plurality of first ranges constituting the second range.

[0170] (Note 3) The estimation device described in Appendix 1 or Appendix 2 calculates the modified rated life for each of the plurality of first ranges based on a value derived from a first physical quantity defined in the first range, and associates the calculated modified rated life for each of the plurality of first ranges.

[0171] (Note 4) The control device is The unit fatigue degree for each of the multiple first ranges is calculated by dividing the time parameter in the first range by the modified rated life associated with the first range. An estimation device according to any one of the appendices 1 to 3, which estimates the total value of unit fatigue in the plurality of first ranges as the fatigue level.

[0172] (Note 5) The control device is an estimation device as described in Appendix 4, which estimates the time when the fatigue level reaches a predetermined value as the time when the first damage occurs.

[0173] (Note 6) The control device is an estimation device as described in Appendix 5, which estimates the timing of occurrence such that the greater the degree of fatigue, the shorter the period from the estimation of the degree of fatigue to the timing of occurrence.

[0174] (Note 7) The control device is an estimation device according to any one of the appendices 1 to 6, which displays the estimation result of the control device on a predetermined terminal.

[0175] (Note 8) The estimation device is, Based on the estimation results, a recommended treatment for the first injury is determined. The estimation device described in Appendix 7, which displays an image indicating the recommended processing on the predetermined terminal.

[0176] (Note 9) The estimation device is the estimation device described in Appendix 7 or Appendix 8, which displays an image indicating the soundness of the bearing on the predetermined terminal.

[0177] (Note 10) The bearing comprises a predetermined member and a lubricant for lubricating the predetermined member. The first damage is a peeling that occurs on the surface of the predetermined member, When the control device estimates that the peeling has occurred, Adding an additive to the lubricant to increase the radius of curvature of the edge formed by the aforementioned peeling, The estimation device described in Appendix 8, which determines that the recommended process is to suppress the operation of the rotating machine including the bearing.

[0178] (Note 11) The bearing comprises a predetermined member and a lubricant for lubricating the predetermined member. The first damage is a peeling that occurs on the surface of the predetermined member, The control device is When estimating the future timing of the aforementioned peeling, Adding an additive to reduce the surface protrusions, or The estimation apparatus described in Appendix 8, which determines that the recommended treatment is to replace the lubricant or to flush the lubricant.

[0179] (Note 12) The damage to the bearing is smaller in scale than the delamination and includes micropitting occurring on the surface of the predetermined member. The estimation device according to Appendix 10 or Appendix 11, wherein, when the control device determines that micropitching is occurring, it decides as the recommended treatment to add an additive to the lubricant to reduce the protrusions caused by the micropitching.

[0180] (Note 13) The control device, when it determines the timing of the occurrence of the micropitching, determines that replacing the lubricant is the recommended treatment, as described in Appendix 12.

[0181] (Note 14) To obtain the first physical quantity of a bearing for which the rated life is specified, For each of the multiple first ranges of the first physical quantity, a time parameter relating to the time to which the first physical quantity belongs in that first range is identified, An estimation method comprising estimating at least one of the following: the presence or absence of first damage to the bearing, the future timing of the first damage, and the fatigue level of the bearing, based on the time parameters for each of the plurality of first ranges and the modified rated life for each of the plurality of first ranges.

[0182] (Note 15) To obtain the first physical quantity of a bearing for which the rated life is specified, For each of the multiple first ranges of the first physical quantity, a time parameter relating to the time to which the first physical quantity belongs in that first range is identified, Based on the time parameters for each of the plurality of first ranges and the modified rated life for each of the plurality of first ranges, the timing of the future occurrence of the first damage to the bearing is estimated. The bearing's lifespan is extended based on the timing of the occurrence. The bearing comprises a predetermined member and a lubricant for lubricating the predetermined member. Extending the lifespan of the aforementioned bearing is To suppress the operation of the rotating machine including the bearing, The lubricant mentioned above will be replaced, The process involves flushing the aforementioned lubricant, A method for extending the life of a bearing, comprising at least one of the following: adding an additive to the lubricant for reducing the protrusions caused by the first damage.

[0183] The embodiments disclosed herein should be considered in all respects to be illustrative and not restrictive. The scope of the present invention is indicated by the claims rather than by the description of the embodiments above, and all modifications within the meaning and scope equivalent to the claims are intended to be included. [Explanation of Symbols]

[0184] 10 Management system, 20 Wind power generation device, 30 Collection device, 41 Speed ​​sensor, 42 Temperature sensor, 50 User terminal, 60 Wind power generation unit, 70 Worker terminal, 71-75 Images, 100 Estimation device, 104 Memory, 106 Interface, 112 Acquisition unit, 114 Processing unit, 116 Storage unit, 120 Bearing, 121 Range information, 127 Damage data, 131 Delamination life function, 132 Micropitching life function, 191 Rolling element, 192 Raceway ring, 193 Lubricant.

Claims

1. An interface for obtaining the first physical quantity of a bearing whose rated life is specified, A memory that stores range information for multiple first ranges of a first physical quantity, Equipped with a control device, The modified rated life is associated with each of the aforementioned multiple first ranges, The control device is For each of the plurality of first ranges, the interface identifies a time parameter relating to the time period within that first range, An estimation device that estimates at least one of the following: whether a first damage has occurred in the bearing, or, if no first damage has occurred, the future timing of the first damage, and the fatigue level of the bearing, based on the time parameters for each of the plurality of first ranges and the modified rated life for each of the plurality of first ranges.

2. The interface acquires the second physical quantity of the bearing, The aforementioned range information includes information on a plurality of second ranges, The plurality of second ranges include at least one of the first ranges, The estimation device according to claim 1, wherein the control device identifies as the time parameter a parameter relating to time to which the second physical quantity belongs in each of the plurality of second ranges and to which the first physical quantity belongs in a plurality of first ranges constituting the second range.

3. The estimation device according to claim 1 or claim 2, wherein the estimation device calculates the modified rated life for each of the plurality of first ranges based on a value derived from a first physical quantity defined in a first range, and associates the calculated modified rated life for each of the plurality of first ranges.

4. The control device is The unit fatigue degree for each of the plurality of first ranges is calculated by dividing the time parameter in the first range by the modified rated life associated with the first range. The estimation device according to claim 1 or claim 2, which estimates the total value of unit fatigue levels in a plurality of first ranges as the fatigue level.

5. The estimation device according to claim 4, wherein the control device estimates the time when the fatigue level reaches a predetermined value as the time when the first damage occurs.

6. The control device estimates the timing of occurrence such that the greater the degree of fatigue, the shorter the period from the time the degree of fatigue is estimated to the time of occurrence.

7. The estimation device according to claim 1 or claim 2, wherein the control device displays the estimation result of the control device on a predetermined terminal.

8. The estimation device is, Based on the estimation results, a recommended treatment for the first damage is determined. The estimation device according to claim 7, wherein an image indicating the recommended processing is displayed on the predetermined terminal.

9. The estimation device according to claim 7, wherein the estimation device displays an image indicating the soundness of the bearing on the predetermined terminal.

10. The bearing comprises a predetermined member and a lubricant for lubricating the predetermined member. The first damage is delamination occurring on the surface of the predetermined member, When the control device estimates that the peeling has occurred, Adding an additive to the lubricant to increase the radius of curvature of the edge of the recess created by the peeling, The estimation device according to claim 8, wherein the recommended process is to suppress the operation of the rotating machine including the bearing.

11. The bearing comprises a predetermined member and a lubricant for lubricating the predetermined member. The first damage is delamination occurring on the surface of the predetermined member, The control device is When estimating the future timing of the aforementioned peeling, Adding an additive to reduce the surface protrusions, or The estimation apparatus according to claim 8, wherein the recommended treatment is determined to be the replacement of the lubricant or the flushing of the lubricant.

12. The damage to the bearing is smaller in scale than the delamination and includes micropitting occurring on the surface of the predetermined member. The estimation device according to claim 10, wherein, when the control device determines that micropitching is occurring, it decides to add an additive to the lubricant to reduce the protrusions caused by the micropitching as the recommended treatment.

13. The estimation device according to claim 12, wherein the control device determines the timing of the occurrence of the micropitching and decides to replace the lubricant as the recommended treatment.

14. To obtain the first physical quantity of a bearing for which the rated life is specified, For each of the multiple first ranges of the first physical quantity, a time parameter relating to the time to which the first physical quantity belongs in that first range is identified, An estimation method comprising estimating at least one of the following: the presence or absence of first damage to the bearing, the future timing of the first damage, and the fatigue level of the bearing, based on the time parameters for each of the plurality of first ranges and the modified rated life for each of the plurality of first ranges.

15. To obtain the first physical quantity of a bearing for which the rated life is specified, For each of the multiple first ranges of the first physical quantity, a time parameter relating to the time to which the first physical quantity belongs in that first range is identified, Based on the time parameters for each of the plurality of first ranges and the modified rated life for each of the plurality of first ranges, the timing of the future occurrence of the first damage to the bearing is estimated. The bearing's lifespan is extended based on the timing of the occurrence. The bearing comprises a predetermined member and a lubricant for lubricating the predetermined member. Extending the lifespan of the aforementioned bearing is To suppress the operation of the rotating machine including the bearing, The lubricant mentioned above will be replaced, The process involves flushing the aforementioned lubricant, A method for extending the life of a bearing, comprising at least one of the following: adding an additive to the lubricant for reducing the protrusions caused by the first damage.

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