Lifetime estimation system, lifetime estimation method, and lifetime estimation program

Abstract

The present invention accurately estimates the lifetime of a support component by even considering the shape of foreign matter generated inside the support component, such as a rolling bearing for supporting a rotating body.　This lifetime estimation system, which estimates the lifetime of a component supporting a rotating body, executes: a particle size analysis step for analyzing a particle size distribution of foreign matter mixed in a lubricant supplied to the component; a shape analysis step for analyzing a shape composition ratio of the foreign matter mixed in the lubricant; a calculation step for determining the degree of contamination of the lubricant on the basis of the particle size distribution, and calculating a correction lifetime coefficient used for estimating the lifetime of the component on the basis of the degree of contamination; a calculation step for calculating a correction coefficient for correcting the correction lifetime coefficient on the basis of the shape composition ratio; and a correction step for synthesizing the correction coefficient with the correction lifetime coefficient to correct the correction lifetime coefficient.

Description

Lifetime estimation system, lifetime estimation method, and lifetime estimation program

[0001] This disclosure relates to a lifetime estimation system, a lifetime estimation method, and a lifetime estimation program. The present invention claims priority to Japanese Patent Application No. 2024-199023, filed on 14 November 2024, and in designated countries where reference by reference is permitted, the contents described in that application are incorporated into this application by reference.

[0002] Traditionally, rotating machinery has utilized components such as rolling bearings, ball screws, and linear guides to support the rotating body. As these support components deteriorate, abnormalities occur in the machine's operation, leading to failure. Therefore, estimating the lifespan of these support components before any abnormalities occur is crucial for efficient machine operation and effective maintenance management.

[0003] For example, Patent Document 1 discloses a method for estimating the lifespan of a rolling bearing by sampling the lubricant supplied for lubrication inside the rolling bearing and estimating the size of any foreign matter present.

[0004] Japanese Patent Publication No. 2006-258473

[0005] In addition to rolling wear, there are other types of surface damage related to the sliding and rolling of support components, such as abrasive wear and adhesive wear. Rolling wear, or rolling fatigue, is a phenomenon in which the surface hardens due to repeated stress acting on the contact surface, causing microscopic cracks to form and propagate, resulting in delamination damage (flaking). This phenomenon is a sign that fatigue damage to the support component is progressing and its lifespan is decreasing. The debris that falls off due to delamination mixes with the lubricant as foreign matter. On the other hand, abrasive wear and adhesive wear are phenomena that mainly occur due to cutting and sliding of the contact surface, and the shape of the foreign matter that is generated differs from that generated by rolling fatigue.

[0006] As described above, there are various types of surface damage to support components, and foreign matter mixed into lubricants also varies greatly in size, number, material, and shape. In the aforementioned Patent Document 1, the lifespan of a rolling bearing is estimated based on the size of the foreign matter mixed into the lubricant. However, since the lifespan is estimated without determining whether the foreign matter was caused by rolling fatigue, the estimate may not be accurate.

[0007] The present invention aims to accurately estimate the lifespan of support components, such as rolling bearings that support rotating bodies, by taking into account even the shape of foreign matter that may occur inside these support components.

[0008] This application includes several means to solve at least some of the above problems, and some examples are as follows.

[0009] One aspect of the present invention is a life estimation system for estimating the life of a component that supports a rotating body, which includes a particle size analysis step for analyzing the particle size distribution of foreign matter mixed into a lubricant supplied to the component, a shape analysis step for analyzing the proportion of shapes of foreign matter mixed into the lubricant, a calculation step for determining the degree of contamination of the lubricant based on the particle size distribution and calculating a corrected life coefficient used for estimating the life of the component based on the degree of contamination, a calculation step for calculating a correction coefficient for correcting the corrected life coefficient based on the proportion of shapes, and a correction step for correcting the corrected life coefficient by combining the correction coefficient with the corrected life coefficient.

[0010] According to this disclosure, the lifespan of support components, such as rolling bearings, can be accurately estimated by taking into account even the shape of foreign matter that occurs inside the support components.

[0011] Other issues, configurations, and effects not mentioned above will be clarified by the following description of the embodiments.

[0012] This is a block diagram illustrating an example configuration of a life estimation system according to one embodiment of the present invention. This is a diagram illustrating an example of a lubricant sampling method. This is a flowchart illustrating an example of a life estimation method. This is a diagram illustrating an example of the shape of foreign matter. This is a diagram illustrating an example of the correspondence between the composition ratio of foreign matter shapes and correction coefficients. This is a diagram illustrating an example of life display. This is a diagram illustrating an example of life display.

[0013] Hereinafter, one embodiment of the present invention will be described with reference to the drawings. In all drawings used to describe the embodiment, the same reference numerals will be used for identical components, and repeated descriptions will be omitted as appropriate. Furthermore, in the following embodiment, it goes without saying that the components (including element steps, etc.) are not necessarily essential unless specifically stated or considered to be fundamentally essential. Furthermore, it goes without saying that other elements are not excluded unless specifically stated that only that element is included. Similarly, in the following embodiment, when referring to the shape, positional relationship, etc., of components, etc., it will include those that are substantially similar or approximate to their shape, etc., unless specifically stated or considered to be fundamentally different.

[0014] In this embodiment, a rolling bearing is used as an example of a support component that supports a rotating body, which is the subject of life estimation, but there is no intention to limit it. The life estimation method according to this embodiment is applicable to support components that function under rotational motion, whose lifespan is determined by rolling fatigue, and which suffer delamination damage starting from indentations due to the intrusion of foreign matter. For example, it can also be applied to ball screws, linear guides, and the like.

[0015] Furthermore, in this embodiment, a machine equipped with a support component that is subject to life estimation can also be considered as being subject to life estimation. For example, the estimated lifespan of a support component can be considered as the estimated lifespan of the machine equipped with that support component.

[0016] Figure 1 is a block diagram showing an example configuration of a life estimation system according to one embodiment of the present invention. The life estimation system comprises a life estimation device 1, an analyzer 2, and an analyzer 3. The analyzer 2 and the analyzer 3 can communicate with the life estimation device 1 via a wired connection or a wireless connection, respectively.

[0017] The lifespan estimation device 1 is, for example, an information processing device such as a PC (Personal Computer) or a server computer, and comprises a processing unit 10, a storage unit 11, an input unit 12, an output unit 13, a communication unit 14, and an external interface (IF) 15.

[0018] The processing unit 10 is, for example, one or more processors. A processor is an arithmetic unit that reads various programs stored in memory resources and executes processing corresponding to each program. A processor is, for example, a microprocessor, a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), an FPGA (Field Programmable Gate Array), a quantum processor, or other arithmetic semiconductor device.

[0019] The memory unit 11 is a storage device that serves as a memory resource, and is, for example, non-volatile memory and / or volatile memory. Volatile memory is, for example, RAM (Random Access Memory) or ROM (Read Only Memory). Non-volatile memory may be, for example, a rewritable storage medium such as flash memory, a hard disk, or an SSD (Solid State Drive), or it may be a USB (Universal Serial Bus) memory, a memory card, or a hard disk. In addition, RAM such as MRAM (Magnetoresistive RAM), PRAM (Phase Change RAM), and ReRAM (Resistive RAM) may be considered as non-volatile memory.

[0020] The input unit 12 is an input device that inputs user instructions to the computer, and is, for example, a keyboard, a touch panel, a pointing device such as a mouse, or an audio input device such as a microphone.

[0021] The output unit 13 is an output device that outputs information generated by a computer, such as a display, printer, and speech synthesizer.

[0022] The communication unit 14 is a communication device that performs information communication with an external device. The communication unit 14 performs information communication with an external device via a predetermined communication network, such as the Internet or a LAN.

[0023] The external interface 15 is a communication device that communicates information with an external device. The external interface 15 communicates information with the external device via a predetermined communication cable, such as a USB cable. In this embodiment, analyzer 2 and analyzer 3 are each connected to the external interface 15, but they may also be connected in a way that allows communication via the communication unit 14.

[0024] Of course, the life estimation device 1 may be implemented using one physical or logical computer, or it may be implemented using two or more physical or logical computers. The two or more physical or logical computers may each be distributed and located on a network.

[0025] In this embodiment, processing performed by executing a program may be described. Here, the computer executes the program using a processor (e.g., CPU, GPU) and performs processing defined by the program using memory resources (e.g., memory) and interface devices (e.g., communication ports). Therefore, the main entity performing the processing by executing the program may be the processor. Similarly, the main entity performing the processing by executing the program may be a controller, device, system, computer, or node having a processor. The main entity performing the processing by executing the program may be an arithmetic unit, and may include a dedicated circuit that performs a specific processing. Here, a dedicated circuit is, for example, an FPGA (Field Programmable Gate Array), an ASIC (Application Specific Integrated Circuit), or a CPLD (Complex Programmable Logic Device).

[0026] The program may be installed on the computer from the program source. The program source may be, for example, a program distribution server or a storage medium readable by the computer. If the program source is a program distribution server, the program distribution server includes a processor and storage resources for storing the program to be distributed, and the processor of the program distribution server may distribute the program to other computers. In addition, in some embodiments, two or more programs may be implemented as a single program, or one program may be implemented as two or more programs.

[0027] The processing unit 10 estimates the lifespan of the support component (or the machine equipped with the support component) using the analysis data obtained by analyzers 2 and 3. Here, the basic method for calculating the lifespan is explained, and the specific calculation method will be described in detail later with reference to Figure 3.

[0028] Rolling bearings have a structure that allows foreign matter to be mixed into the lubricant, and they operate in environments where foreign matter is present. A lubricant (such as lubricating oil or grease) is supplied to the inside of a rolling bearing, and the movement of the components that make up the rolling bearing is lubricated.

[0029] According to ISO 281 (International Standard), the following formula (1) is specified for calculating the lifespan of rolling bearings.

[0030] L １０ : Basic rated life (rated fatigue life with 90% reliability calculated from load conditions, 106 rotations) C: Basic dynamic rated load P: Load on the object p: Index (Ball bearing: 3, Roller bearing: 10 / 3)

[0031] Furthermore, C can be set to a value specified in the specifications of the rolling bearing in question, for example. P can be set by the evaluator based on the operating environment of the rolling bearing in question. p can be set by the evaluator based on the type of rolling bearing in question.

[0032] Here, the accuracy of life estimation can be improved by applying various correction factors to Equation (1). When foreign matter is mixed into the lubricant and affects the life, the following Equation (2) can be used.

[0033] L １０ｍｒ : Corrected basic rated life R: Correction life coefficient

[0034] By setting an appropriate value for the correction life coefficient R, the life estimation accuracy can be improved. In this embodiment, the correction life coefficient R is derived based on a plurality of analysis results for foreign matter mixed into the rolling bearing. Specifically, in order to derive the correction life coefficient R, attention is paid to the size, quantity, and shape of the foreign matter contained in the lubricant within the rolling bearing. For this purpose, the analyzer 2 and the analyzer 3 are used.

[0035] The analyzer 2 uses the sampled lubricant within the rolling bearing as the analysis target, measures the particle size of the foreign matter contained in the lubricant, analyzes the distribution of the particle size of the foreign matter, and outputs it as analysis data. The configuration of the analyzer 2 is not limited as long as it can analyze the distribution of the particle size of the foreign matter. For example, it is an optical analyzer that measures the particle size by irradiating the target with a laser and measuring the diffraction / scattering pattern. Also, for example, it is an optical analyzer that uses a microscope to image the target with an image sensor such as a CCD or CMOS and measures / analyzes the particle size by image analysis processing.

[0036] The analyzer 3 uses the sampled lubricant within the rolling bearing as the analysis target, measures the shape of the foreign matter contained in the lubricant, and analyzes the composition ratio of the shape of the foreign matter. The configuration of the analyzer 3 is not limited as long as it can analyze the composition ratio of the shape of the foreign matter. For example, it is an optical analyzer that uses a microscope to image the target with an image sensor such as a CCD or CMOS and measures / analyzes the shape by image analysis processing.

[0037] FIG. 2 is a diagram for explaining an example of a lubricant sampling method. The lubricant is supplied to the support parts incorporated in the machine by a method such as a self - feeding type or a forced supply type. In FIG. 2, the case of the forced supply type is shown, and the flow of the lubricant is indicated by a dashed arrow.

[0038] In the annular flow path system A, the lubricant is supplied to the machine and the support parts therein by a circulation device such as a pump P driven by a motor M, and is discharged from the machine. On the other hand, through the flow path system B branched from the flow path system A, the lubricant is supplied to the machine and the support parts therein after unnecessary foreign matters are removed by passing through the filter F.

[0039] The analyzer 2 and the analyzer 3 are respectively connected to the flow path system A by supply paths and discharge paths. The lubricant is supplied to the analyzer 2 and the analyzer 3 through their respective supply paths, and is discharged from the analyzer 2 and the analyzer 3 through their respective discharge paths as necessary. The supply paths and the discharge paths may each be provided with a valve V to control opening and closing. If configured as shown in FIG. 2, sampling can be automatically performed by driving the circulation device.

[0040] Note that the lubricant may be sampled from a storage tank, a transport pipe, a pipe drain, etc. (all not shown) connected to the circulation device, the filter, the machine, the flow path system, etc., and the sampling location is not limited. Also, an operator may collect the lubricant in a container and supply it to the analyzer 2 and the analyzer 3. In this embodiment, the analyzer 2 and the analyzer 3 are separate devices, but they may also be a single device.

[0041] FIG. 3 is a flowchart showing an example of the life estimation method. The life estimation method according to this embodiment includes, for example, seven steps as shown in the figure. Specifically, they are the steps of sampling the lubricant, analyzing the particle size distribution of foreign matters, analyzing the composition ratio of the shapes of foreign matters, calculating the corrected life coefficient, calculating the correction coefficient, correcting the corrected life coefficient (synthesizing the correction coefficient), and estimating the life.

[0042] [Step S1: Sampling of lubricant] Lubricant is sampled from a machine having a support part for which life is to be estimated. Specifically, for example, in the case of the configuration of FIG. 2 described above, the analyzer 2 and the analyzer 3 each sample the lubricant through the supply path.

[0043] [Step S2: Analysis of foreign particle size distribution] The lubricant sampled in Step S1 is used as the analysis target to analyze the particle size distribution of foreign particles. Specifically, analyzer 2 measures the particle size of foreign particles contained in the lubricant, analyzes the distribution of the particle size of the foreign particles, and outputs the analysis data to life estimation device 1.

[0044] The analytical process using analyzer 2 will be described in detail. The particle size distribution is evaluated by converting it to the distribution per predetermined amount of lubricant. Foreign matter collected by the dust collection filter may be separated before being used for analysis. In this embodiment, it is preferable to exclude foreign matter with a particle size smaller than a predetermined size (e.g., 4 μm) from the analysis of the particle size distribution. This is because it has been shown that foreign matter with a particle size smaller than a predetermined size does not affect the life of the rolling bearing even if it is contained in the lubricant, and it is considered unlikely that it will cause indentations on the contact surface inside the rolling bearing, and therefore less likely that delamination damage will occur starting from indentations.

[0045] The particle size of foreign matter to be excluded may vary depending on the configuration of the rolling bearing and the operating environment. The particle size to be judged may be the long axis diameter of the foreign matter (the longest length of the foreign matter) or the equivalent circle diameter of the foreign matter (the diameter of a circle with the same projected area as the shadow of the foreign matter).

[0046] [Step S3: Analysis of the composition ratio of foreign matter shapes] The lubricant sampled in Step S1 is used as the analysis target to analyze the composition ratio of foreign matter shapes. Specifically, the analyzer 3 measures the shape of foreign matter contained in the lubricant, analyzes the composition ratio of foreign matter shapes, and outputs the analysis data to the life estimation device 1.

[0047] The analytical process using analyzer 3 will be described in detail. Foreign matter collected by the dust collection filter may be separated before being used for analysis. The coarseness of the dust collection filter may be set so that foreign matter of a desired particle size is collected. In this embodiment, it is preferable to analyze foreign matter of a predetermined particle size range (for example, particle size of 10 μm or more and less than 100 μm) for shape analysis. The upper limit of particle size is about 100 μm because large metallic foreign matter does not flow with the lubricating oil and remains somewhere. Foreign matter smaller than the lower limit of particle size is likely to have shrunk due to damage over time since its generation, making it difficult to estimate the original cause of generation. The lower limit of particle size for analysis in analyzer 3 is greater than the lower limit of particle size for analysis in analyzer 2.

[0048] The particle size of the foreign matter to be analyzed may vary depending on the configuration of the rolling bearing and the operating environment. The particle size to be determined may be the ratio of the major axis diameter (maximum length of the foreign matter) to the minor axis diameter (minimum length of the foreign matter), or the equivalent circle diameter (diameter of a circle with the same projected area as the shadow of the foreign matter).

[0049] In this embodiment, the shape of the foreign object of interest and its determination criteria are specified in advance. The shape of interest and its determination criteria may differ depending on the operating environment of the rolling bearing, but for example, they can be classified into foil-like pieces, rod-like pieces, and other shapes. Based on the classification results, the composition ratio of the shapes (e.g., frequency of occurrence or proportion) is analyzed. The composition ratio of the foreign object shapes is evaluated by converting it to a composition ratio per predetermined amount of lubricant.

[0050] As a means of analyzing shape and the proportion of shape composition, for example, a neural network can be used that comprehensively learns multiple parameters, including the shape of the foreign object and the criteria for identifying that shape, as well as color and surface properties, enabling rapid classification and quantification of data. Alternatively, a pre-trained model can be used, which has been machine-learned to process image data containing the shape, color, and surface properties of foreign objects, along with their type (classification), and is constructed to output the type of shape, proportion of shape, and evaluation value of the foreign objects contained in the image data. Another example is the use of rule-based processing, such as shape pattern matching for image data.

[0051] Figure 4 illustrates examples of foreign matter shapes. In this embodiment, three types of foreign matter shapes are given as examples for explanation. The shapes of foreign matter can be classified, for example, into foil-like shapes a, straight rod-like shapes b, and curved rod-like shapes c, which are similar to rectangles or circles. Each shape type is likely to occur in a specific type of wear. That is, foil-like shapes a are generated by rolling fatigue of the support part, straight rod-like shapes b are generated by sliding of the support part, and curved rod-like shapes c are generated by cutting of the support part. Therefore, as will be described later, the larger the proportion of foil-like shapes a is, the higher the degree of rolling fatigue can be judged to be.

[0052] [Step S4: Calculation of corrected life coefficient] Based on the analysis results (particle size distribution) from Step S2, the corrected life coefficient R is calculated. Specifically, the processing unit 10 of the life estimation device 1 acquires analysis data regarding the particle size distribution of foreign matter from the analyzer 2, and calculates the corrected life coefficient R in formula (2) above based on the analysis data and a predetermined calculation formula. More specifically, the degree of contamination of the lubricant is determined based on the particle size distribution, and the corrected life coefficient R is calculated based on the degree of contamination.

[0053] In this embodiment, the corrected lifetime coefficient R is α as defined in ISO 281. ＩＳＯA coefficient equivalent to the above can be used. The corrected life coefficient R is calculated using a formula defined as a function of variables such as bearing dimensions, rotational speed, lubricant viscosity, and lubricant contamination level. The variables such as bearing dimensions, rotational speed, and lubricant viscosity may be pre-set in the storage unit 11, or may be input by the user via a terminal device connected to the input unit 12 or communication unit 14. The degree of lubricant contamination can be determined (evaluated) using the particle size and number of foreign matter identified from the particle size distribution. The particle size and number of foreign matter identified from the particle size distribution may be converted to a code representation (ISO code) for the particle size and number of foreign matter as defined in ISO 4406 and used. The contamination coefficient defined in ISO 281 can be used as the degree of lubricant contamination. A lower contamination coefficient means that the lubricant is more contaminated and contains more foreign matter. The contamination coefficient can be calculated using the formula defined in ISO 281 Annex for each particle size and number of foreign matter, or for each code representation. The contamination coefficient is calculated using a formula defined as a function of variables such as the pitch circle diameter and viscosity ratio of the bearing under various contaminated lubrication conditions. The lubrication conditions, bearing pitch circle diameter, viscosity ratio, and other variables may be pre-set in the storage unit 11, or they may be input by the user via a terminal device connected to the input unit 12 or the communication unit 14.

[0054] [Step S5: Calculation of Correction Factor] Based on the analysis results (composition ratio of shapes) from Step S3, a correction factor R is calculated to correct the modified life coefficient R. ｎ Specifically, the processing unit 10 of the life estimation device 1 acquires analysis data regarding the composition ratio of the shape of foreign matter from the analyzer 3, and calculates the correction coefficient R based on the correspondence between the composition ratio of the shape and the correction coefficient predetermined. ｎ To decide.

[0055] In this embodiment, for example, a table can be used that associates the proportion of the shape with a correction coefficient. The processing unit 10 can obtain the correction coefficient by referring to the table based on the acquired proportion of the shape.

[0056] Figure 5 illustrates an example of the correspondence between the composition ratio of foreign object shapes and correction coefficients. As shown in this figure, a correction coefficient is associated with each composition ratio of shape. For example, if the composition ratio of foil-shaped a is 80%, and the composition ratios of rod-shaped b and rod-shaped c are 20%, the correction coefficient R ｎ The value is between 0 and 0.1. When the composition ratio of foil-shaped a is 50%, and the composition ratios of rod-shaped b and rod-shaped c are 50%, the correction coefficient R ｎ The value is 0.3 to 0.5. When the composition ratio of foil-shaped a is 20% and the composition ratio of rod-shaped b and rod-shaped c is 80%, the correction coefficient R ｎ It is between 0.6 and 0.8.

[0057] Here, as shown in the figure, a correspondence can be defined such that the higher the proportion of foil-like material a, the higher the degree of rolling fatigue and the degree of lubricant contamination (contamination coefficient). Therefore, the processing unit 10 can obtain the degree of rolling fatigue and the degree of lubricant contamination from the proportion by referring to a table that defines the correspondence between the proportion and the degree of rolling fatigue and the degree of lubricant contamination. It can also be said that the correction coefficient has a correspondence with the degree of rolling fatigue and the degree of lubricant contamination.

[0058] Thus, the more foil-like 'a' generated due to rolling fatigue, and the fewer rod-like 'b' and 'c' generated due to causes other than rolling fatigue, the smaller the correction coefficient can be set. As a result, the higher the degree of rolling fatigue, the smaller the corrected life coefficient R can be corrected.

[0059] Furthermore, the proportion of shapes and the number of corresponding correction coefficient categories are not limited to three, and may vary depending on the operating environment of the rolling bearing. Alternatively, the proportion of shapes may be converted into a degree of rolling fatigue or a degree of lubricant contamination, and correction coefficients corresponding to these degrees may be obtained.

[0060] Further, as a means for converting the shape composition ratio into the degree of rolling fatigue, the degree of lubricant contamination, or the correction coefficient, for example, a neural network that can comprehensively learn a plurality of parameters including the shape composition ratio and covering the target machine and its usage environment, and can quickly classify and digitize data may be utilized. Also, for example, a learned model constructed by learning the shape composition ratio and the degree of rolling fatigue, the degree of lubricant contamination, or the correction coefficient, and outputting the degree or correction coefficient when the shape composition ratio is input may be used.

[0061] [Step S6: Correction of the modified life coefficient (synthesis of correction coefficients)] The modified life coefficient R calculated in step S4 is corrected by synthesizing the correction coefficient R calculated in step S5. Specifically, the processing unit 10 corrects the modified life coefficient R by the following formula (3). ｎ By doing so, the correction according to the shape composition ratio of the foreign matter is reflected in the modified life coefficient R. In other words, according to the degree of rolling fatigue or the degree of lubricant contamination corresponding to the shape composition ratio of the foreign matter, the higher the degree, the more the modified life coefficient R is corrected to be smaller.

[0062] R: Modified life coefficient R ｎ : Correction coefficient

[0063] As a result, the correction according to the shape composition ratio of the foreign matter is reflected in the modified life coefficient R. In other words, according to the degree of rolling fatigue or the degree of lubricant contamination corresponding to the shape composition ratio of the foreign matter, the higher the degree, the more the modified life coefficient R is corrected to be smaller.

[0064] [Step S7: Life estimation] The life is estimated using the modified life coefficient R corrected in step S6. Specifically, the processing unit 10 sets the corrected modified life coefficient R, the basic dynamic load rating C, the load P on the target, and the exponent p for the above-mentioned formula (2), and calculates the modified basic rated life L １０ｍｒ The basic dynamic load rating C, the load P on the target, and the exponent p of the target bearing may be set in the storage unit 11 in advance, or may be input by the user via a terminal device connected to the input unit 12 or the communication unit 14.

[0065] The processing unit 10 calculates the calculated life, the modified life coefficient R before and after correction, and the correction coefficient R ｎNumerical values ​​such as these, and their time-series changes, may be displayed via the output unit 13 or on a terminal device connected via the communication unit 14. This allows users (e.g., manufacturers or maintenance companies) who monitor the support component (or the machine equipped with the support component) to understand the lifespan of the support component (or the machine equipped with the support component) and plan maintenance such as component replacement.

[0066] Figures 6 and 7 show examples of lifespan indications. In Figure 6, for a machine equipped with the target support component, the modified basic rated lifespan L is shown along with the installation location, identifier, date and time, and temperature. １０ｍｒ and the corresponding correction coefficient R ｎ The changes from a predetermined time (for example, the time of the previous analysis) to the time of the current analysis are displayed. In Figure 7, for the machine equipped with the target support component, a graph showing the change in remaining life based on the design life defined in the specifications, etc. (solid line) and a graph showing the change in remaining life based on the estimated life (dashed line) are displayed side by side, along with the installation location, identifier, date and time, and temperature.

[0067] One embodiment of the present invention has been described above. According to this embodiment, even the shape of foreign matter generated inside the support component, such as a rolling bearing, can be taken into consideration, and the lifespan of the support component due to rolling fatigue can be estimated with high accuracy.

[0068] The present invention is not limited to the embodiments described above, and various further modifications are possible. For example, the embodiments described above are described in detail for the purpose of clearly illustrating the present invention, and are not necessarily limited to those having all the configurations described. Furthermore, it is possible to replace some of the modifications with other modifications or to combine modifications.

[0069] Furthermore, some or all of the components, functions, processing units, and processing means of the life estimation device 1 described above may be implemented in hardware, for example, by designing them as integrated circuits. Also, the control lines and information lines shown are those deemed necessary for explanation purposes and do not necessarily represent all control lines and information lines in the actual product. In practice, it can be assumed that almost all components are interconnected.

[0070] The present invention can be provided in various forms, not limited to systems and methods, but also including devices, computer-readable programs, and storage media storing such programs.

[0071] 1 Life estimation device, 2 Analyzer, 3 Analyzer, 10 Processing unit, 11 Memory unit, 12 Input unit, 13 Output unit, 14 Communication unit, 15 External interface (IF)

Claims

1. A life estimation system for estimating the life of a component that supports a rotating body, comprising: a particle size analysis step for analyzing the particle size distribution of foreign matter mixed into a lubricant supplied to the component; a shape analysis step for analyzing the proportion of shapes of foreign matter mixed into the lubricant; a calculation step for determining the degree of contamination of the lubricant based on the particle size distribution and calculating a corrected life coefficient used for estimating the life of the component based on the degree of contamination; a calculation step for calculating a correction coefficient for correcting the corrected life coefficient based on the proportion of shapes; and a correction step for correcting the corrected life coefficient by combining the correction coefficient with the corrected life coefficient.

2. A life estimation system according to claim 1, wherein the corrected modified life coefficient is used in the following life calculation formula. However, L10mr is the modified basic rated life, R is the corrected modified life coefficient, C is the basic dynamic rated load, P is the load on the object, and p is an index corresponding to the type of object in the life estimation system.

3. A life estimation system according to claim 2, wherein the correction step is performed using the following correction formula. However, R ｎ This is the life estimation system, which is the correction coefficient.

4. A lifetime estimation system according to claim 1, wherein the lower limit of the particle size of the foreign substance to be analyzed in the shape analysis step is greater than the lower limit of the particle size of the foreign substance to be measured in the particle size analysis step.

5. A life estimation system according to claim 1, wherein in the shape analysis step, the foreign matter contained in the lubricant is classified into a plurality of predefined shape types to obtain the composition ratio of the shape.

6. A life estimation system according to claim 5, wherein the predefined plurality of shape types are shapes that are likely to occur in a particular type of wear.

7. A lifetime estimation system according to claim 1, comprising an output step of outputting at least one of the corrected modified lifetime coefficient and the correction coefficient.

8. A life estimation system according to claim 1, wherein an estimation step is performed to estimate the life of the component using the corrected life coefficient corrected in the correction step.

9. A life estimation system according to claim 8, wherein the estimation step estimates the life of the component using the following life calculation formula. However, L10mr is the modified basic rated life, R is the corrected modified life coefficient, C is the basic dynamic rated load, P is the load on the object, and p is an index corresponding to the type of object in the life estimation system.

10. A life estimation system according to claim 8, comprising an output step of outputting the estimated lifespan of the component.

11. A life estimation system according to claim 1, wherein the component is a rolling bearing, a ball screw, or a linear guide.

12. A method for estimating the lifespan of a component that supports a rotating body, comprising: a particle size analysis step of analyzing the particle size distribution of foreign matter mixed into a lubricant supplied to the component; a shape analysis step of analyzing the proportion of shapes of foreign matter mixed into the lubricant; a calculation step of determining the degree of contamination of the lubricant based on the particle size distribution and calculating a corrected lifespan coefficient used for estimating the lifespan of the component based on the degree of contamination; a calculation step of calculating a correction coefficient for correcting the corrected lifespan coefficient based on the proportion of shapes; and a correction step of combining the correction coefficient with the corrected lifespan coefficient to correct the corrected lifespan coefficient.

13. A computer-readable program for causing a computer to perform a process to estimate the lifespan of a component supporting a rotating body, the program causing the computer to perform the following steps: a particle size acquisition step for acquiring the particle size distribution of foreign matter mixed in a lubricant supplied to the component; a shape acquisition step for acquiring the proportion of shapes of foreign matter mixed in the lubricant; a calculation step for determining the degree of contamination of the lubricant based on the particle size distribution and calculating a corrected lifespan coefficient used for estimating the lifespan of the component based on the degree of contamination; a calculation step for calculating a correction coefficient for correcting the corrected lifespan coefficient based on the proportion of shapes; and a correction step for correcting the corrected lifespan coefficient by combining the correction coefficient with the corrected lifespan coefficient.

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