Method for monitoring plurality of rotary machines

Abstract

The present invention relates to a method for monitoring a plurality of rotary machines. In the present invention, the method for monitoring a plurality of rotary machines respectively installed at multiple locations comprises: a step for installing a first rotary machine at a first location and acquiring reference data having a trajectory pattern from the first rotary machine in a normal state; a step for installing a second rotary machine at a second location different from the first location; a step for processing a signal output from the first rotary machine to acquire first output data having a trajectory pattern; a step for processing a signal output from the second rotary machine to acquire second output data having a trajectory pattern; and a step for comparing the reference data and the first output data and comparing the reference data and the second output data to monitor the first rotary machine and the second rotary machine.

Description

Monitoring method for multiple rotating machines

[0001] The present invention relates to a diagnostic system for rotating machines installed in various locations and a monitoring method for a plurality of rotating machines.

[0002] This research is a project supported by the Ministry of Trade, Industry and Energy (MOTIE) and the Korea Energy Technology Evaluation and Planning Institute (KETEP). (No. 20212020800120)

[0003] Failures in mechanical and electronic equipment used in key industries of modern society, such as construction manufacturing, defense, and information and communication technology, occur frequently. Since failures occurring under unforeseen circumstances are highly critical, prognostics and health management (PHM) is applied with great importance.

[0004] In particular, various mechanical equipment is used at construction sites, and devices such as electric motors with rotating shafts are essential equipment for construction sites. However, due to the unique characteristics of each site and the large size of construction mechanical equipment, it has been difficult to predict or diagnose failures of rotating machinery tailored to the specific construction site.

[0005] However, fault diagnosis technology capable of preventing accidents caused by failures in rotating machinery used in construction is emerging as an important aspect alongside maintenance. Korean Published Patent Application No. 10-2005-0063441 discloses a device for diagnosing abnormal conditions in induction motors. However, for certain low-energy-level failures, such as bearing failures, the aforementioned diagnostic device has difficulty easily detecting abnormal conditions due to noise, and there are difficulties in accurately predictive maintenance.

[0006] The present invention relates to a system and method for accurately and rapidly diagnosing rotating machines installed at multiple points by utilizing an axial trajectory generated from vibration data measured in the rotating machine.

[0007] An embodiment of the present invention provides a method for monitoring a plurality of rotating machines installed at a plurality of locations, comprising the steps of: installing a first rotating machine at a first location and obtaining reference data having a trajectory pattern from the first rotating machine in a normal state; installing a second rotating machine at a second location different from the first location; processing a signal output from the first rotating machine to obtain first output data having a trajectory pattern; processing a signal output from the second rotating machine to obtain second output data having a trajectory pattern; comparing the reference data with the first output data and comparing the reference data with the second output data to monitor the first rotating machine and the second rotating machine.

[0008] A diagnostic system for a rotating machine and a monitoring method for a plurality of rotating machines according to one embodiment of the present invention can accurately and quickly diagnose whether there is an abnormality in the rotating machine based on the pattern of the shaft trajectory of the rotating machine.

[0009] The diagnostic system for a rotating machine and the monitoring method for a plurality of rotating machines according to the present invention can integrally monitor and control a plurality of installation locations where rotating machines are installed by utilizing shaft track information generated from a plurality of rotating machines installed at a plurality of points.

[0010] FIG. 1 is a diagram illustrating a diagnostic system for a rotating machine according to one embodiment of the present invention.

[0011] Figure 2 is a cross-sectional view illustrating the rotating machine of Figure 1.

[0012] Figure 3 is a drawing illustrating the diagnostic device of Figure 1.

[0013] Figure 4 is a drawing illustrating the storage device of Figure 1.

[0014] Figures 5 and 6 are diagrams illustrating the generation of an axial trajectory from vibration data in the diagnostic device of Figure 3.

[0015] Figure 7 is a diagram explaining the determination of whether there is an abnormality in the diagnostic device of Figure 3.

[0016] FIG. 8 is a flowchart illustrating a method for determining whether a rotating machine is faulty according to another embodiment of the present invention.

[0017] Figures 9 and 10 are flowcharts illustrating any one of the steps of Figure 8.

[0018] An embodiment of the present invention provides a method for monitoring a plurality of rotating machines installed at a plurality of locations, comprising the steps of: installing a first rotating machine at a first location and obtaining reference data having a trajectory pattern from the first rotating machine in a normal state; installing a second rotating machine at a second location different from the first location; processing a signal output from the first rotating machine to obtain first output data having a trajectory pattern; processing a signal output from the second rotating machine to obtain second output data having a trajectory pattern; comparing the reference data with the first output data and comparing the reference data with the second output data to monitor the first rotating machine and the second rotating machine.

[0019] In addition, in the step of acquiring the reference data, the second output data can be updated by reflecting the second rotating machine being determined to be in a normal state in the monitoring step.

[0020] In addition, in the step of monitoring the first rotating machine and the second rotating machine, the scale can be adjusted so that the second output data corresponds to the first output data by considering the operating conditions of the second rotating machine.

[0021] In addition, in the step of monitoring the first rotating machine and the second rotating machine, the size of the trajectory of the reference data and the size of the trajectory of the first output data or the second output data can be compared.

[0022] The present invention is capable of various modifications and may have various embodiments; specific embodiments are illustrated in the drawings and described in detail in the detailed description. The effects and features of the present invention, and the methods for achieving them, will become clear by referring to the embodiments described below in detail together with the drawings. However, the present invention is not limited to the embodiments disclosed below but can be implemented in various forms.

[0023] Hereinafter, embodiments of the present invention will be described in detail with reference to the attached drawings. When describing with reference to the drawings, identical or corresponding components are given the same reference numerals, and redundant descriptions thereof will be omitted.

[0024] In the following embodiments, terms such as first, second, etc. are used not in a limiting sense, but for the purpose of distinguishing one component from another component.

[0025] In the following examples, singular expressions include plural expressions unless the context clearly indicates otherwise.

[0026] In the following embodiments, terms such as "include" or "have" mean that the features or components described in the specification are present, and do not preclude the possibility that one or more other features or components may be added.

[0027] In the following embodiments, when a part such as a film, region, or component is described as being on or above another part, it includes not only cases where it is directly on top of another part, but also cases where another film, region, or component is interposed in between.

[0028] In the drawings, the size of components may be exaggerated or reduced for convenience of explanation. For example, the size and thickness of each component shown in the drawings are depicted arbitrarily for convenience of explanation, so the present invention is not necessarily limited to what is illustrated.

[0029] Where an embodiment can be implemented differently, a specific process sequence may be performed differently from the order described. For example, two processes described consecutively may be performed substantially simultaneously or proceed in the reverse order of the description.

[0030] In the following embodiments, when it is stated that a membrane, region, component, etc. is connected, it includes not only cases where the membrane, region, or component is directly connected, but also cases where other membranes, regions, or components are interposed between them to form an indirect connection. For example, when it is stated in this specification that a membrane, region, component, etc. is electrically connected, it includes not only cases where the membrane, region, or component, etc. are directly electrically connected, but also cases where other membranes, regions, or components are interposed between them to form an indirect electrical connection.

[0031] FIG. 1 is a diagram illustrating a diagnostic system for a rotating machine according to one embodiment of the present invention.

[0032] Referring to FIG. 1, a diagnostic system (1) for a rotating machine can diagnose whether there is an abnormality in the rotating machine based on vibration data measured from the rotating machine. The diagnostic system (1) for a rotating machine can generate and store vibration data of the rotating machine in advance as reference data, and determine whether there is an abnormality based on vibration data of the rotating machine that is monitored in real time based on this.

[0033] In the following, "reference data" refers to data for diagnosing a rotating machine and may include data acquired in a normal state and data acquired in an abnormal state. Such reference data may have an axis trajectory pattern processed from vibration data.

[0034] A diagnostic system (1) for a rotating machine according to one embodiment of the present invention may include a rotating machine installed in a plurality of locations. For example, each rotating machine may be installed at different construction sites.

[0035] The diagnostic system (1) of a rotating machine may include a plurality of rotating machines, a diagnostic device (200), a storage device (300), and a user interface device (400).

[0036] In an exemplary embodiment, a first rotating machine (100A) may be installed at a first location (S1), a second rotating machine (100B) may be installed at a second location (S2), and a third rotating machine (100C) may be installed at a third location (S3).

[0037] The first location (S1), the second location (S2), and the third location (S3) define the space where the rotating machine is installed and can be designated independently. Additionally, the first rotating machine (100A), the second rotating machine (100B), and the third rotating machine (100C) are defined as having similar dynamic behavior.

[0038] The first rotating machine (100A) is installed at the first location (S1) and connected to the first machine device (DD1) so that it can transmit power to the first machine device (DD1). The second rotating machine (100B) is installed at the second location (S2) and connected to the second machine device (DD2) so that it can transmit power to the second machine device (DD2). The third rotating machine (100C) is installed at the third location (S3) and connected to the third machine device (DD3) so that it can transmit power to the third machine device (DD3).

[0039] The diagnostic system (1) of the rotating machine can generate vibration data received in advance from at least one of the first rotating machine (100A) to the third rotating machine (100C) as reference data, and simultaneously generate vibration data received in real time from the first rotating machine (100A) to the third rotating machine (100C) as output data. Subsequently, the diagnostic system (1) of the rotating machine can diagnose whether there is an abnormality in the first rotating machine (100A) to the third rotating machine (100C) by comparing the output data with the reference data.

[0040] The diagnostic device (200) can generate reference data using vibration data measured in advance at at least one of the first location (S1) to the third location (S3). Additionally, the diagnostic device (200) can convert vibration data measured in real time at at least one of the first location (S1) to the third location (S3) into output data and diagnose whether there is an abnormality in the rotating machine located at each location by comparing the output data with the reference data.

[0041] The storage device (300) can store reference data. For example, reference data generated by the diagnostic device (200) can be stored in the storage device (300). Subsequently, when the diagnostic device (200) performs a diagnosis, the storage device (300) can transmit the reference data to the diagnostic device (200).

[0042] Additionally, the storage device (300) can store the updated reference data when the vibration data measured in real time by the diagnostic device (200) is updated as reference data.

[0043] The user interface device (400) can provide signal input from the user and notify the user of the results diagnosed by the diagnostic device (200). The user interface device (400) can receive input signals from the user, including a touch screen, a keyboard, etc. Additionally, the user interface device (400) can transmit diagnostic results or alarm signals to the user, including an alarm such as an LED, a microphone, a vibration element, etc.

[0044] For example, if the rotating machine (100) is diagnosed as being in a faulty state by the diagnostic device (200), the user interface device (400) may generate a first alarm signal. If the rotating machine (100) is diagnosed as being in an aged state by the diagnostic device (200), the user interface device (400) may generate a second alarm signal. At this time, the first alarm signal and the second alarm signal may have different signals. For example, the first alarm signal and the second alarm signal may display different colors or different text.

[0045] Figure 2 is a cross-sectional view illustrating the rotating machine of Figure 1.

[0046] Referring to FIG. 2, the rotating machine (100) may include a driver (110), a rotating shaft (120), a bearing unit (130), a fan (140), and a housing (150). The first rotating machine (100A), second rotating machine (100B), and third rotating machine (100C) of FIG. 1 may be applied to the rotating machine (100) of FIG. 2.

[0047] The driver (110) can receive current from a power source and transmit driving force to the rotating shaft (120). In one embodiment, the driver (110) may be an electric motor. However, it is not limited thereto and may be various mechanical devices that generate rotational force.

[0048] The rotating shaft (120) can be connected to a driver (110). Another mechanical device (not shown) can be connected to the rotating shaft (120) so that the power of the rotating machine (100) can be transmitted to the mechanical device.

[0049] The rotation axis (120) may have a first rotation axis (121) positioned at the front end of the driver (110) and a second rotation axis (122) positioned at the rear end of the driver (110).

[0050] The first rotation shaft (121) is connected to the first bearing (131) and can be connected to an external mechanical device. The first rotation shaft (121) is positioned so that at least a portion is exposed to the outside and can be connected to the mechanical device.

[0051] The second rotation axis (122) is connected to the second bearing (132) and can be placed inside the housing (150). The second rotation axis (122) is equipped with a fan (140) and can drive the fan (140).

[0052] A bearing unit (130) can be inserted into a rotating shaft (120) so that the rotating shaft (120) can be installed to rotate. A first bearing (131) can be mounted on the first rotating shaft (121), and a second bearing (132) can be mounted on the second rotating shaft (122).

[0053] The fan (140) can cool the rotating machine (100). The fan (140) is mounted at the rear of the driver (110) and can flow external air to the driver (110) by the rotation of the second rotating shaft (122). A second bearing (132) may be mounted on one side of the fan (140).

[0054] The housing (150) forms the exterior of the rotating machine (100), and a driver (110), a rotating shaft (120), a bearing unit (130), and a fan (140) can be placed in the interior space.

[0055] The housing (150) may be divided into a plurality of parts. For example, the housing (150) may include a first bracket (151), a second bracket (152), and a main body (153). The first bracket (151) covers a first rotation axis (121) and may have a first bearing (131) placed inside. The second bracket (152) covers a second rotation axis (122) and may have a second bearing (132) placed inside. The main body (153) is placed between the first bracket (151) and the second bracket (152) and may cover the outside of the driver (110).

[0056] The housing (150) may be equipped with a plurality of sensors. A sensor unit (160) may be mounted in a preset area of ​​the housing (150) to measure vibrations transmitted to the housing (150).

[0057] The sensor unit (160) may be equipped with a first sensor (161), a second sensor (162), and a third sensor (163) for measuring vibration. The first sensor (161), the second sensor (162), and the third sensor (163) may be mounted at a preset position of the rotating machine (100).

[0058] The first sensor (161) may be installed on the front side of the rotating machine (100). The first sensor (161) may be positioned adjacent to the first rotation axis (121) of the rotating machine (100). The first sensor (161) may be installed on one side of the first bracket (151) to measure vibrations occurring near the first rotation axis (121) of the rotating machine (100).

[0059] The second sensor (162) may be installed on the rear side of the rotating machine (100). The second sensor (162) may be positioned adjacent to the second rotation axis (122) of the rotating machine (100). The second sensor (162) may be installed on one side of the second bracket (152) to measure vibrations occurring near the second rotation axis (122) of the rotating machine (100).

[0060] The third sensor (163) may be installed in the middle of the rotating machine (100). The second sensor (162) may be installed on the main body (153) of the rotating machine (100) to measure vibrations generated by the driver (110) of the rotating machine (100).

[0061] The first sensor (161), the second sensor (162), and the third sensor (163) can measure vibration data in at least one of the three axes.

[0062] The first sensor (161) can measure at least one of the X-axis, Y-axis, and Z-axis vibration data and transmit it to the diagnostic device (200). For example, the first sensor (161) can measure vibration data of the X-axis and vibration data of the Y-axis and transmit them to the diagnostic device (200).

[0063] The second sensor (162) can measure vibration data of the X-axis, Y-axis, and Z-axis and transmit it to the diagnostic device (200). For example, the second sensor (162) can measure vibration data of the X-axis and vibration data of the Y-axis and transmit it to the diagnostic device (200).

[0064] The third sensor (163) can measure vibration data of the X-axis, Y-axis, and Z-axis and transmit it to the diagnostic device (200). For example, the second sensor (163) can measure vibration data of the X-axis and vibration data of the Y-axis and transmit it to the diagnostic device (200).

[0065] In addition, the first sensor (161), the second sensor (162), and the third sensor (163) can each measure vibration data in three axes and transmit it to the diagnostic device (200).

[0066] Vibration data measured in advance by the sensor unit of each rotating machine installed at the first location (S1) to the third location (S3) can be converted into reference data in the diagnostic device (200). The reference data has an axial orbit and can be stored in the storage device (300).

[0067] Vibration data measured in real time by sensor units of each rotating machine installed at the first location (S1) to the third location (S3) can be converted into output data by the diagnostic device (200). The output data has an axial orbit, and the diagnostic device (200) can diagnose whether there is an abnormality in the rotating machine (100) by comparing the output data with reference data. In addition, the diagnostic device (200) can update the previously stored reference data based on the output data.

[0068] Figure 3 is a drawing illustrating the diagnostic device of Figure 1, and Figure 4 is a drawing illustrating the storage device of Figure 1.

[0069] Referring to FIGS. 3 and 4, the diagnostic device (200) may include an orbit generation module (210) and a diagnostic module (220).

[0070] The orbit generation module (210) can receive vibration data measured by the sensor unit (160) of the rotating machine (100), perform a Fast Fourier Transform (FFT) on the vibration data, and generate an axial orbit pattern based on this.

[0071] The "axial orbit pattern" can be stored as reference data or converted into output data depending on the source of the input vibration data.

[0072] Specifically, the orbit generation module (210) can receive vibration data from the sensor unit (160) of the rotating machine (100) in advance to generate reference data, and store it as reference data having an axial orbit pattern.

[0073] For example, a rotating machine (100) installed at the first location (S1) of FIG. 1 is operated in a normal state, and vibration data generated by the sensor unit (160) is transmitted to the orbit generation module (210). The orbit generation module (210) can generate an axial orbit pattern having the characteristics of the normal state of the rotating machine. For example, a first reference data (R1) having the characteristics of the normal state is generated, and the first reference data (R1) can have an approximately circular axial orbit pattern as shown in FIG. 5.

[0074] Additionally, the rotating machine (100) installed at the first location (S1) of FIG. 1 is operated in an abnormal state, and vibration data generated by the sensor unit (160) is transmitted to the orbit generation module (210). The orbit generation module (210) can generate an axial orbit pattern having the characteristics of the abnormal state of the rotating machine. For example, a second reference data (R2) having the characteristics of the abnormal state is generated, and the second reference data (R2) may have an axial orbit pattern that is roughly non-circularly twisted or semicircular.

[0075] The first reference data (R1) and the second reference data (R2) can be stored in a storage device (300).

[0076] In one embodiment, the orbit generation module (210) may include a receiving unit (211), a conversion unit (212), an orbit generation unit (213), and a learning unit (214).

[0077] The receiver (211) can receive vibration data from each sensor unit (160) of a plurality of rotating machines (100). The receiver (211) and the sensor unit (160) can transmit and receive signals via wired or wireless means.

[0078] The conversion unit (212) can perform a Fast Fourier Transform (FFT) on the vibration data. The conversion unit (212) can convert the time series vibration data into vibration spectrum frequency signals through the FFT transformation.

[0079] The orbit generation unit (213) can generate a pattern having an axial orbit from a vibration spectrum frequency signal. For example, the axial orbit can be generated based on the characteristics of the velocity or acceleration of the X-axis and Y-axis of the vibration spectrum frequency signal. This will be described below.

[0080] The learning unit (214) can learn the axial orbit pattern generated by the orbit generation unit (213) to generate or update reference data.

[0081] Figures 5 and 6 are diagrams illustrating the generation of an axial trajectory from vibration data in the diagnostic device of Figure 3.

[0082] Referring to FIGS. 3 and FIGS. 5, the orbit generation module (210) can generate data having an axial orbit pattern based on vibration data transmitted from the sensor unit (160). The orbit generation module (210) can generate data having an axial orbit pattern using at least one of the first sensor (161), the second sensor (162), and the third sensor (163).

[0083] Each sensor of the sensor unit (160) can measure vibration data in a time series in the three-axis direction. For example, the first sensor (161) can measure three-axis vibrations occurring in the front of the rotating machine (100) in a time series, the second sensor (162) can measure three-axis vibrations occurring in the rear of the rotating machine (100) in a time series, and the third sensor (163) can measure three-axis vibrations occurring in the center of the rotating machine (100) in a time series.

[0084] In one embodiment, as shown in FIG. 5, vibration data in the X-axis direction and vibration data in the Y-axis direction measured by the first sensor (161) are transmitted to the orbit generation module (210) through the receiver (211). The conversion unit (212) performs an FFT conversion on each data, and based on the converted data, the orbit generation unit (213) can generate an axis orbit pattern (RO).

[0085] Additionally, based on the vibration data in the X-axis direction and the vibration data in the Y-axis direction measured by the second sensor (162), the orbit generation module (210) can generate an axial orbit pattern.

[0086] Additionally, based on the vibration data in the X-axis direction and the vibration data in the Y-axis direction measured by the third sensor (163), the orbit generation module (210) can generate an axial orbit pattern.

[0087] The orbit generation unit (213) can generate reference data by using vibration data measured at the rotating machine (100) at the first location (S1). Vibration data collected when the rotating machine (100) is in a normal state is stored in the storage device (300) as first reference data (R1), and vibration data collected when the rotating machine (100) is in an abnormal state can be stored in the storage device (300) as second reference data (R2).

[0088] In addition, the reference data generated by the orbit generation unit (213) can be machine learned to increase the accuracy of the normal state pattern and the abnormal state pattern.

[0089] Meanwhile, after reference data is generated, each rotating machine installed at the first location (S1) to the third location (S3) is monitored. Vibration data measured at the first rotating machine (100A) to the third rotating machine (100C) can also be transmitted to the orbit generation module (210). At least one vibration data measured by the first sensor (161), the second sensor (162), and the third sensor (163) of each rotating machine is transmitted to the receiver (211), and subsequently, the vibration data is FFT-converted at the conversion unit (212), and an axial orbit pattern can be generated based on the converted data at the orbit generation unit (213). The generated axial orbit pattern is transmitted to the diagnosis module (220) as output data to diagnose abnormalities in the rotating machine.

[0090] Figure 7 is a diagram explaining the determination of whether there is an abnormality in the diagnostic device of Figure 3.

[0091] Referring to FIGS. 3 and 7, the diagnostic module (220) can diagnose whether there is an abnormality in the rotating machine (100) by comparing output data and reference data. The diagnostic module (220) may include an orbit selection unit (221), a comparison unit (222), and a diagnostic unit (223).

[0092] The orbit selection unit (221) can determine which pattern the output data corresponds to among the various axis orbit patterns of the reference data. It compares the axis orbit shape of the output data with the axis orbit shape of the reference data.

[0093] For example, the track selection unit (221) determines whether the shape of the shaft track of the output data matches the shape of the reference data, and based on the degree of match, the shape of the reference data can be specified as one of the circular, semicircular, or twisted shapes. If the shaft track of the output data is determined to be semicircular, the diagnosis unit (223) diagnoses that there is an abnormality in the shaft alignment of the rotating machine (100). If the shaft track of the output data is determined to be twisted, the diagnosis unit (223) can diagnose that the rotating machine has a defect in frictional contact.

[0094] For example, the track selection unit (221) can determine whether the axis track shape of the output data corresponds to a circle. It can determine to what extent the axis track shape of the output data matches a circle and, based on this, diagnose whether there is an abnormality in each rotating machine.

[0095] The comparison unit (222) can secondarily compare whether there is an abnormality in the axial trajectory of the output data after the trajectory selection unit (221) determines that it is normal. The comparison unit (222) can compare the axial trajectory of the output data with the original pattern of the normal pattern in the reference data.

[0096] Referring to FIG. 7, the comparison unit (222) can compare the output axis orbit (MO) of the output data with the normal axis orbit (RO) of the reference data.

[0097] In one embodiment, the comparison unit (222) can compare the size of the trajectory of the reference data with the size of the trajectory of the output data. The comparison unit (222) can compare the size of the area of ​​the output axis trajectory (MO) of the output data with the area of ​​the normal axis trajectory (RO) of the reference data. It can compare whether the difference between the area of ​​the output axis trajectory (MO) and the area of ​​the normal axis trajectory (RO) corresponds to a preset range.

[0098] The diagnostic unit (223) can diagnose that the rotating machine is normal if the difference between the area of ​​the output shaft track (MO) and the area of ​​the normal shaft track (RO) falls within a preset range. If the difference between the area of ​​the output shaft track (MO) and the area of ​​the normal shaft track (RO) falls outside the preset range, the rotating machine can be diagnosed as old or in need of inspection.

[0099] In another embodiment, the comparison unit (222) can compare the singularity of the trajectory of the reference data with the singularity of the trajectory of the output data.

[0100] A "singularity" is a point extracted to compare the characteristics of an axial orbit and can be set in various ways. For example, it can be defined as a point where the direction of curvature changes in the axial orbit, a convex or protruding point, the most protruding or most sunken point, or a point corresponding to a pre-set curvature range.

[0101] When a singularity is selected on the output axis orbit (MO), a corresponding point on the normal axis orbit (RO) can be selected. For example, it may have the same azimuth as the singularity on the output axis orbit (MO), be on an extension line, or be a convex or concave point corresponding to the singularity.

[0102] Referring to FIG. 7, for example, the output axis orbit (MO) may have five singularities where the direction of curvature changes, and the normal axis orbit (RO) may have five singularities at corresponding positions. That is, m1 may correspond to r1, m2 to r2, m3 to r3, m4 to r4, and m5 to r5.

[0103] The comparison unit (222) can measure the length of corresponding points and compare whether the measured distance corresponds to a preset range.

[0104] For example, a first separation distance between m1 and r1, a second separation distance between m2 and r2, a third separation distance between m3 and r3, a fourth separation distance between m4 and r4, and a fifth separation distance between m5 and r5 can be measured, and it can be determined whether the first to fifth separation distances correspond to a pre-set normal range of distances.

[0105] The comparison unit (222) can diagnose that the rotating machine (100) is normal if all of the multiple separation distances fall within the normal range.

[0106] Additionally, the comparison unit (222) can diagnose that the rotating machine is old or requires inspection as the number of separation distances outside the normal range increases.

[0107] For example, the diagnostic unit (223) may assign weights based on the number of deviations from the normal range. For example, if there is one or two deviations, it is considered to be in a normal state, but if it is determined that there are three or more deviations, it is considered that an inspection is required, and if there are four or more, it can be diagnosed that the rotating machine needs to be shut down.

[0108] Referring to FIG. 6, the diagnostic device (200) can receive three-axis vibration data from the sensors of each rotating machine and generate a three-dimensional axis trajectory.

[0109] The orbit generation module (210) receives three-axis vibration data from the sensor of the rotating machine (100) and can perform FFT conversion on them. Based on the converted data, it can generate a three-dimensional axis orbit.

[0110] Specifically, the orbit generation module (210) can first generate a three-dimensional axial orbit in a normal state and a three-dimensional axial orbit in an abnormal state as reference data and store them in a storage device (300), respectively.

[0111] Subsequently, the orbit generation module (210) can receive three-axis vibration data from a rotating machine (100) that requires monitoring and generate it as output data. Subsequently, the diagnosis module (220) can diagnose whether there is an abnormality in the rotating machine (100) by comparing it with reference data.

[0112] For example, the diagnostic module (220) can compare the spatial volume size of the three-dimensional axis orbit of the output data and the three-dimensional axis orbit of the reference data. The diagnostic module (220) can determine that there is a fault if the difference in volume exceeds a preset range.

[0113] As another example, the diagnostic module (220) can diagnose whether there is an abnormality in the rotating machine (100) by comparing the three-dimensional axis trajectory of the output data with the three-dimensional axis trajectory of the reference data.

[0114] The diagnostic system (1) for a rotating machine according to the present invention can diagnose whether there is an abnormality in the rotating machine based on the pattern of the shaft track of the rotating machine. The diagnostic system (1) for a rotating machine stores the shaft track of the rotating machine, which is driven in a normal state or an abnormal state, as reference data, converts vibration data measured in real time into output data having a shaft track, and compares the output data with the reference data to quickly and accurately determine the abnormality of the rotating machine.

[0115] The diagnostic system (1) of a rotating machine according to the present invention generates reference data including an axis track pattern in advance from a plurality of rotating machines installed at a plurality of points, then measures vibration data from the plurality of rotating machines in real time, and compares output data including an axis track generated based on this with the reference data, thereby enabling efficient monitoring of rotating machines placed at multiple locations.

[0116] The diagnostic system (1) of a rotating machine according to the present invention can first determine the shape of the axis track pattern being monitored and secondarily compare the difference with the normal state pattern to accurately diagnose the rotating machine.

[0117] FIG. 8 is a flowchart illustrating a method for determining whether a rotating machine is faulty according to another embodiment of the present invention, and FIG. 9 and FIG. 10 are flowcharts illustrating any one step of FIG. 8.

[0118] A monitoring method for a plurality of rotating machines installed at a plurality of locations according to another embodiment of the present invention may include the steps of: installing a first rotating machine at a first location and obtaining reference data having a trajectory pattern from the first rotating machine in a normal state; installing a second rotating machine at a second location different from the first location; processing a signal output from the first rotating machine to obtain first output data having a trajectory pattern; processing a signal output from the second rotating machine to obtain second output data having a trajectory pattern; comparing the reference data with the first output data and comparing the reference data with the second output data to monitor the first rotating machine and the second rotating machine.

[0119] Referring to FIGS. 8 to 10, a method for determining whether a rotating machine is abnormal may include the steps of measuring vibration data from a sensor of the rotating machine (S10), obtaining reference data (S20), obtaining output data from rotating machines installed at multiple points (S30), and comparing the reference data with each output data (S40).

[0120] In the step (S10) of measuring vibration data from a sensor of a rotating machine, vibration data of the rotating machine in a normal state and an abnormal state can be measured to generate reference data.

[0121] Referring to FIG. 1, vibration data can be obtained in advance from sensors of rotating machines installed at each of the first location (S1) to the third location (S3). Sensors of at least one of the first rotating machine (100A) to the third rotating machine (100C) can measure vibration data and transmit it to a diagnostic device (200). For example, vibration data can be obtained from only one of the first rotating machine (100A) to the third rotating machine (100C), or vibration data can be obtained from multiple rotating machines.

[0122] As a specific example, a first rotating machine (100A) can be installed at a first location (S1), and vibration data can be obtained from the first rotating machine (100A) in a normal state.

[0123] In the step of acquiring reference data (S20), the received vibration data can be FFT transformed, and reference data having an axial orbit pattern can be generated based on this. The generated reference data can be stored in a storage device.

[0124] For example, a first reference data can be obtained based on vibration data measured by driving the first rotating machine (100A) in a normal state. Additionally, a second reference data can be obtained based on vibration data measured by driving the rotating machine in an abnormal state.

[0125] In the step (S30) of obtaining output data from rotating machines installed at multiple locations, rotating machines are installed at multiple locations and vibration data is received from the sensors of each rotating machine in real time to obtain output data having a trajectory.

[0126] A second rotating machine (100B) can be installed at a second location (S2) different from the first location (S1), and a signal output from the first rotating machine (100A) can be processed to obtain first output data having a trajectory pattern. Additionally, a signal output from the second rotating machine (100B) can be processed to obtain second output data having a trajectory pattern.

[0127] In the step (S40) of comparing reference data and each output data, the presence or absence of an abnormality in the rotating machine can be monitored by comparing the output data and the reference data.

[0128] First, the axis trajectory pattern of the output data is compared with the axis trajectory pattern of the reference data to determine whether it is normal or abnormal.

[0129] If the rotating machine is determined to be abnormal by comparing the shaft track shape, the diagnostic device can notify the user that the rotating machine is faulty through the user interface.

[0130] If the rotating machine is determined to be normal by comparing the shaft track shapes, the necessity of inspection or the degree of aging of the rotating machine can be diagnosed.

[0131] In one embodiment, considering the operating conditions of the second rotating machine (100B), the scale can be adjusted so that the second output data corresponds to the first output data. Before comparing the first output data, the second output data, and the reference data, the diagnostic device (200) can adjust the scale of the first output data and the second output data as a preprocessing step.

[0132] As described in Fig. 7, the diagnostic device can diagnose the need for inspection or the degree of aging of a monitored rotating machine in real time by comparing the widths of the two shaft tracks or by comparing specific points of the shaft tracks.

[0133] In one example, in step (40), the size of the trajectory of the reference data and at least one of the size, width, and singularity of the trajectory of the first output data or the second output data can be compared.

[0134] Referring to FIG. 9, the step (40) of comparing reference data with each output data may include the step of receiving the trajectory of the output data and the reference data (S41), the step of determining whether the trajectory of the output data is a normal pattern (S42), and the step of comparing the trajectory of the output data with the trajectory size of the normal pattern (S43).

[0135] In the step (S41) of receiving the trajectory of the output data and the reference data, the reference data can be received from the storage device and the generated output data can be received.

[0136] In the step (S42) of determining whether the trajectory of the output data is a normal pattern, the reference data and the output data can be compared. Based on the axis trajectory of the first reference data in a normal state and the axis trajectory of the second reference data in an abnormal state, it can be determined which of the first reference data and the second reference data the trajectory of the output data is similar to.

[0137] If the axis trajectory of the output data is determined to be similar to the axis trajectory of the first reference data, the rotating machine can be primarily determined to be in a normal state.

[0138] If it is determined that the axis trajectory of the output data is similar to the axis trajectory of the second reference data, the rotating machine is determined to be in an abnormal state and an alarm can be given to the user.

[0139] In the step (S43) of comparing the trajectory of the output data with the trajectory size of the normal pattern, the area or volume of the axis trajectory of the output data can be compared with the area or volume of the axis trajectory of the first reference data. By comparing the two areas or volumes, if they fall within a preset range, it is determined that they are normal, and if they fall outside the preset range, it is determined that they require inspection or are old.

[0140] Referring to FIG. 10, the step (40) of comparing reference data with each output data may include the step of receiving the trajectory of the output data and the reference data (S41), the step of determining whether the trajectory of the output data is a normal pattern (S42), and the step of comparing the trajectory of the output data with the singularity of the normal pattern (S44).

[0141] In the step (S44) of comparing the trajectory of the output data with the singularity of the normal pattern, the axis trajectory of the first reference data and the axis trajectory of the output data can be compared. Singularities can be extracted from the axis trajectory of the output data, and points corresponding thereto can be extracted from the axis trajectory of the first reference data.

[0142] Subsequently, the distance between the two points is calculated, and if the distance falls within a preset range, it is determined to be normal; if it falls outside the preset range, it can be determined that an inspection is required or that the equipment is outdated.

[0143] Meanwhile, in the step (20) of obtaining reference data, the diagnosed output data is reflected back into the reference data so that the existing reference data can be updated. If the output data is determined to be in a normal state, the first reference data is updated, and if the output data is determined to be in an abnormal state, the second reference data is updated.

[0144] For example, if the second rotating machine is determined to be in a normal state, the first reference data can be updated by reflecting the second output data.

[0145] If the second output data measured at the second location (S2) is determined to be normal, the second output data can update the reference data. If the second output data is determined to be normal, the diagnostic device (200) can update the first reference data (R1) by reflecting the output data in the first reference data (R1). For example, the diagnostic device (200) can update the first reference data (R1) by machine learning the second output data.

[0146] The monitoring method for a plurality of rotating machines according to the present invention can diagnose whether there is an abnormality in the rotating machines based on the pattern of the shaft trajectories of the rotating machines. The method stores the shaft trajectories of the rotating machines operating in a normal or abnormal state as reference data, converts vibration data measured in real time into output data having shaft trajectories, and compares the output data with the reference data to quickly and accurately determine the abnormality of the rotating machines.

[0147] A monitoring method for a plurality of rotating machines according to the present invention generates reference data including an axis track pattern in advance from a plurality of rotating machines installed at a plurality of points, subsequently measures vibration data from the plurality of rotating machines in real time, and compares output data including an axis track generated based on this with the reference data, thereby enabling efficient monitoring of rotating machines placed at multiple locations.

[0148] The monitoring method for a plurality of rotating machines according to the present invention can accurately diagnose the rotating machine by first determining the shape of the axis track pattern being monitored and secondarily comparing the difference with the pattern in a normal state.

[0149] Although the present invention has been described with reference to an embodiment illustrated in the drawings, this is merely illustrative, and those skilled in the art will understand that various modifications and variations of the embodiments are possible therefrom. Accordingly, the true scope of technical protection of the present invention should be determined by the technical spirit of the appended claims.

Claims

1. A method for monitoring multiple rotating machines installed in multiple locations, respectively, A step of installing a first rotating machine at a first location and obtaining reference data having a trajectory pattern from the first rotating machine in a normal state; A step of installing a second rotating machine at a second location different from the first location mentioned above; A step of obtaining first output data having a trajectory pattern by processing a signal output from the first rotating machine; A step of obtaining second output data having a trajectory pattern by processing a signal output from the second rotating machine; and A method for monitoring a plurality of rotating machines, comprising the step of comparing the above reference data with the above first output data, and comparing the above reference data with the above second output data to monitor the first rotating machine and the second rotating machine.

2. In Paragraph 1, In the step of acquiring the above reference data A monitoring method for a plurality of rotating machines, wherein the second output data determined to be in a normal state in the above monitoring step is updated by reflecting the second rotating machine.

3. In Paragraph 1, In the step of monitoring the first rotating machine and the second rotating machine, A method for monitoring a plurality of rotating machines, wherein the scale is adjusted so that the second output data corresponds to the first output data, taking into account the operating conditions of the second rotating machine.

4. In Paragraph 1, In the step of monitoring the first rotating machine and the second rotating machine, A method for monitoring a plurality of rotating machines, comparing the size of the trajectory of the reference data with the size of the trajectory of the first output data or the second output data.

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