Elevator traction machine bearing diagnostic device and elevator traction machine bearing diagnostic method

Abstract

To obtain a diagnostic device for an elevator hoisting machine bearing that can identify a type of a bearing of an elevator hoisting machine from among multiple types of bearings.SOLUTION: The diagnostic device for the elevator hoisting machine bearing includes: a vibration sensor unit 1 for measuring the vibration of an elevator hoisting machine; a frequency spectrum calculation unit 202 for calculating a frequency spectrum of the vibration of the elevator hoisting machine by using measurement results of the vibration sensor unit 1; and a classification unit 203 for identifying a type of a bearing of the elevator hoisting machine from among multiple types of bearings by using frequency values corresponding to peak values in the frequency spectrum calculated by the frequency spectrum calculation unit 202.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to an elevator hoisting machine bearing diagnostic device and an elevator hoisting machine bearing diagnostic method. [Background technology]

[0002] Conventionally, there is known a diagnostic device for elevator hoisting machine bearings that includes a vibration sensor unit, a frequency spectrum calculation unit, and a fault determination unit. The vibration sensor unit measures the vibration of the elevator hoisting machine. The frequency spectrum calculation unit calculates the frequency spectrum of the vibration of the elevator hoisting machine using the measurement results of the vibration sensor unit. The fault determination unit compares a preset peak value of the frequency spectrum with the peak value of the frequency spectrum calculated by the frequency spectrum calculation unit to determine a fault in the elevator hoisting machine bearings (see, for example, Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2005-247468 Summary of the Invention [Problem to be solved by the invention]

[0004] The elevator hoist uses a bearing of one type selected from a plurality of types of bearings, and the frequency corresponding to the peak value in the frequency spectrum calculated by the frequency spectrum calculation unit is determined according to the type of bearing used in the elevator hoist.

[0005] However, the configuration described in Patent Document 1 cannot identify the type of bearing that the elevator hoisting machine has from among multiple types of bearings. This poses a problem in that if the type of bearing that the elevator hoisting machine has is unknown, it is not possible to determine whether or not the bearing of the elevator hoisting machine has a malfunction.

[0006] The present disclosure has been made to solve the above-mentioned problems, and its purpose is to provide an elevator hoisting machine bearing diagnostic device and elevator hoisting machine bearing diagnostic method that can identify the type of bearing that an elevator hoisting machine has from among multiple bearing types. [Means for solving the problem]

[0007] The elevator hoisting machine bearing diagnosis device according to the present disclosure includes a vibration sensor unit that measures the vibration of the elevator hoisting machine, a frequency spectrum calculation unit that calculates a frequency spectrum of the vibration of the elevator hoisting machine using the measurement results of the vibration sensor unit, and a classification unit that identifies the type of bearing that the elevator hoisting machine has from among a plurality of bearing types using a frequency value that corresponds to a peak value in the frequency spectrum calculated by the frequency spectrum calculation unit. The elevator hoisting machine bearing diagnosis method according to the present disclosure includes a vibration measurement step of measuring the vibration of the elevator hoisting machine; a frequency spectrum calculation step of calculating a frequency spectrum of the vibration of the elevator hoisting machine using the measurement results of the vibration of the elevator hoisting machine measured in the vibration measurement step; and a bearing type identification step of identifying the type of bearing that the elevator hoisting machine has from among a plurality of bearing types using a frequency value corresponding to a peak value in the frequency spectrum calculated in the frequency spectrum calculation step. [Effects of the Invention]

[0008] According to the elevator hoisting machine bearing diagnostic device and elevator hoisting machine bearing diagnostic method of the present disclosure, it is possible to identify the type of bearing that an elevator hoisting machine has from among a plurality of bearing types. [Brief explanation of the drawings]

[0009] [Figure 1] 1 is a block diagram showing an elevator hoisting machine bearing diagnosis device according to a first embodiment. FIG. [Figure 2]2 is a graph showing the measurement results of the vibration sensor unit of FIG. 1. [Figure 3] 3 is a graph showing data when the brake is released in FIG. 2. [Figure 4] 3 is a diagram showing how the amplitude value in the constant speed section data is calibrated using the brake release data in FIG. 2. FIG. [Figure 5] FIG. 5 is a diagram showing how a frequency spectrum is calculated from the calibrated constant speed section data of FIG. [Figure 6] FIG. 6 is a diagram showing how the frequency spectrum of FIG. 5 is corrected. [Figure 7] FIG. 7 is a diagram showing how a plurality of portions are extracted from the frequency spectrum of FIG. 6. [Figure 8] 8 is a table illustrating portions of the extracted frequency spectrum of FIG. 7. [Figure 9] FIG. 8 is a diagram showing how the type of bearing of the elevator hoisting machine is identified from the extracted frequency spectrum portion of FIG. 7. [Figure 10] 3 is a flowchart showing a method for diagnosing an elevator hoisting machine bearing according to the first embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0010] 1 is a block diagram showing an elevator hoisting machine bearing diagnostic device according to Embodiment 1. The elevator hoisting machine bearing diagnostic device includes a vibration sensor unit 1 and an information processing unit 2.

[0011] The vibration sensor unit 1 is composed of an acceleration sensor. The vibration sensor unit 1 is detachably attached to an elevator hoisting machine (not shown). The vibration sensor unit 1 is attached to the elevator hoisting machine when determining whether or not there is a failure in the bearings of the elevator hoisting machine. The vibration sensor unit 1 measures the vibration of the elevator hoisting machine to which the vibration sensor unit 1 is attached.

[0012] The bearing of an elevator hoisting machine has an inner ring, an outer ring, and rolling elements. The rotating shaft of the elevator hoisting machine is fitted into the inner ring. The outer ring is arranged outside the inner ring in the radial direction of the rotating shaft of the elevator hoisting machine. The rolling elements are arranged between the inner ring and the outer ring. The rolling elements are rotatable relative to each of the inner ring and the outer ring. This allows the inner ring to rotate relative to the outer ring. When the rotating shaft of the elevator hoisting machine rotates, the inner ring rotates relative to the outer ring.

[0013] When the inner ring, outer ring, or rolling elements are damaged and the inner ring rotates relative to the outer ring, vibrations occur in the bearing. The frequency of the vibrations occurring in the bearing is determined by the type of bearing and the rotational speed of the elevator shaft. Therefore, the type of bearing can be identified by knowing the frequency of the vibrations occurring in the bearing and the rotational speed of the elevator shaft.

[0014] Fig. 2 is a graph showing the measurement results of the vibration sensor unit 1 of Fig. 1. In Fig. 2, the horizontal axis represents time, and the vertical axis represents the magnitude of vibration of the elevator hoisting machine measured by the vibration sensor unit 1.

[0015] The measurement results of the vibration sensor unit 1 include brake release data D1, acceleration section data D2, constant speed section data D3, and deceleration section data D4.

[0016] The brake release data D1 is data measured by the vibration sensor unit 1 when the brake of the elevator hoisting machine is released. The acceleration section data D2 is data measured by the vibration sensor unit 1 during a period when the rotation speed of the rotating shaft of the elevator hoisting machine gradually increases. The constant speed section data D3 is data measured by the vibration sensor unit 1 during a period when the rotating shaft of the elevator hoisting machine rotates at a constant speed. The deceleration section data D4 is data measured by the vibration sensor unit 1 during a period when the rotation speed of the rotating shaft of the elevator hoisting machine gradually decreases.

[0017] The information processing unit 2 is configured, for example, by a maintenance computer carried by a maintenance and inspection worker. Note that the information processing unit 2 is not limited to a maintenance computer, and may be, for example, a computer installed in an information center.

[0018] The information processing unit 2 includes a calibration unit 201 , a frequency spectrum calculation unit 202 , a classification unit 203 , and a display unit 204 .

[0019] Fig. 3 is a graph showing the brake release data D1 of Fig. 2. Fig. 4 is a diagram showing how the amplitude value V3 in the constant speed section data D3 is calibrated using the amplitude value V1 in the brake release data D1 of Fig. 2.

[0020] When the elevator machine brake is released, vibration occurs in the elevator machine. The amplitude of the vibration that occurs in the elevator machine when the elevator machine brake is released is constant regardless of the type of bearing.

[0021] The calibration unit 201 calibrates the amplitude value V3 of the constant speed section data D3 using the amplitude value V1 of the brake release data D1.

[0022] Specifically, the calibration unit 201 pre-stores calibrated brake release data. The calibrated brake release data is data measured by the vibration sensor unit 1, the sensitivity of which has been calibrated using a dedicated vibration exciter, and is data on vibrations occurring in the elevator hoisting machine when the brake is released. The calibration unit 201 calibrates the amplitude value V3 in the constant speed section data D3 so that the amplitude value in the pre-stored calibrated brake release data and the amplitude value V1 in the brake release data D1 match each other. FIG. 4 shows how the amplitude value V3 in the constant speed section data D3 is calibrated to be smaller when the amplitude value V1 in the brake release data D1 is larger than the amplitude value in the calibrated brake release data.

[0023] Fig. 5 is a diagram showing how a frequency spectrum is calculated from the calibrated constant speed section data D3 in Fig. 4. The frequency spectrum calculation unit 202 uses the measurement results of the vibration sensor unit 1 to calculate the frequency spectrum of the vibration generated in the elevator hoisting machine.

[0024] Specifically, the frequency spectrum calculation unit 202 calculates a frequency spectrum using the constant speed section data D3 calibrated by the calibration unit 201. The frequency spectrum calculation unit 202 uses, for example, FFT (Fast Fourier Transform) to calculate the frequency spectrum.

[0025] Figure 6 is a diagram showing how the frequency spectrum in Figure 5 is corrected. There is a correlation between the rotation speed of the rotating shaft of the elevator hoisting machine and the measurement results of the vibration sensor unit 1. Specifically, as the rotation speed of the rotating shaft of the elevator hoisting machine increases, the frequency of the vibration of the elevator hoisting machine measured by the vibration sensor unit 1 increases.

[0026] A reference speed value, which is a reference rotational speed value of the rotating shaft of the elevator hoisting machine, is set in advance in the frequency spectrum calculation unit 202. Furthermore, the value of the rotational speed of the rotating shaft of the elevator hoisting machine during the time when the rotating shaft of the elevator hoisting machine rotates at a constant speed is externally input to the frequency spectrum calculation unit 202. The frequency spectrum calculation unit 202 corrects the frequency values ​​in the calculated frequency spectrum using the reference speed value and the value of the rotational speed of the rotating shaft of the elevator hoisting machine during the time when the rotating shaft of the elevator hoisting machine rotates at a constant speed. Fig. 6 shows how the frequency values ​​in the calculated frequency spectrum are corrected to be smaller when the value of the rotational speed of the rotating shaft of the elevator hoisting machine during the time when the rotating shaft of the elevator hoisting machine rotates at a constant speed is greater than the reference speed value.

[0027] Fig. 7 is a diagram showing how multiple portions are extracted from the frequency spectrum of Fig. 6. Fig. 8 is a table showing multiple portions of the extracted frequency spectrum of Fig. 7. The range of frequencies of vibrations generated in an elevator hoisting machine due to bearing damage is a portion of the frequencies of vibrations generated in the elevator hoisting machine.

[0028] The classification unit 203 is preset with a frequency range of vibrations that occur in the elevator hoisting machine due to bearing damage. The classification unit 203 extracts multiple portions that fall within the preset frequency range from the frequency spectrum calculated by the frequency spectrum calculation unit 202. FIG. 7 shows three portions extracted from the frequency spectrum calculated by the frequency spectrum calculation unit 202. FIG. 7 also shows how the magnitude of the frequency spectrum is normalized. In FIG. 7, the frequency range near the second order is a frequency range that is twice the frequency range near the first order, and the frequency range near the third order is a frequency range that is three times the frequency range near the first order. When damage occurs to the bearing, peak values ​​occur in the frequency range near the first order, the frequency range near the second order, and the frequency range near the third order in the frequency spectrum.

[0029] The preset frequency range extracted from the frequency spectrum is a frequency range in which a peak value may occur when damage occurs to each of the multiple bearing types, and therefore, frequency ranges unrelated to the occurrence of bearing damage are excluded from the preset frequency range extracted from the frequency spectrum.

[0030] Fig. 9 is a diagram showing how the type of bearing included in the elevator hoisting machine is identified from the portion of the frequency spectrum extracted in Fig. 7. The classification unit 203 identifies the type of bearing included in the elevator hoisting machine by using the frequency value corresponding to the peak value in the portion extracted from the frequency spectrum.

[0031] Specifically, a machine learning model is preset in the classification unit 203. The classification unit 203 identifies the type of bearing included in the elevator hoisting machine by using the machine learning model and the value of the frequency corresponding to the peak value in the portion extracted from the frequency spectrum.

[0032] The machine learning model preset in the classification unit 203 may be, for example, a model using learning such as a random forest method, a k-nearest neighbor method, or a naive Bayes classifier.

[0033] In Figure 9, the frequency spectra of bearing model number A, bearing model number B, and bearing model number C have been learned in advance by the machine learning model, and it is shown that bearing model number A is inconsistent, bearing model number B is inconsistent, and bearing model number C is consistent, thereby identifying the type of bearing.

[0034] Display unit 204 displays the type of bearing and the peak value identified by classification unit 203. A maintenance and inspection worker can grasp the type of bearing the elevator hoisting machine has and the peak value in the frequency spectrum by visually checking display unit 204. The maintenance and inspection worker determines whether or not there is a fault in the bearing of the elevator hoisting machine using the type of bearing the elevator hoisting machine has and the peak value in the frequency spectrum.

[0035] Next, a method for diagnosing an elevator traction machine bearing using the elevator traction machine bearing diagnosis device will be described. Fig. 10 is a flowchart showing the method for diagnosing an elevator traction machine bearing according to the first embodiment. First, in step S101, a vibration measurement process is performed. In the vibration measurement process, a maintenance and inspection worker attaches a vibration sensor unit 1 to the elevator traction machine, and the vibration sensor unit 1 measures the vibration of the elevator traction machine.

[0036] Thereafter, in step S102, a data calibration step is performed. In the data calibration step, the calibration unit 201 calibrates the amplitude value V3 of the constant speed section data D3 using the amplitude value V1 of the brake release data D1.

[0037] Thereafter, in step S103, a frequency spectrum calculation step is performed. In the frequency spectrum calculation step, the frequency spectrum calculation unit 202 calculates the frequency spectrum of the vibration of the elevator hoisting machine using the calibrated constant speed section data D3.

[0038] Thereafter, in step S104, a frequency correction step is performed. In the frequency correction step, the frequency spectrum calculation unit 202 corrects the frequency values ​​in the frequency spectrum using the value of the rotation speed of the rotating shaft of the elevator hoisting machine during the time when the rotating shaft of the elevator hoisting machine rotates at a constant speed.

[0039] Thereafter, in step S105, a data extraction step is performed. In the data extraction step, the classification unit 203 extracts a part of the frequency spectrum corrected by the frequency spectrum calculation unit 202 that is included in a preset frequency range.

[0040] Thereafter, in step S106, a type identification step is performed. In the type identification step, the classification unit 203 identifies the type of bearing of the elevator hoisting machine by using the frequency value corresponding to the peak value in the portion extracted by the classification unit 203 from the corrected frequency spectrum.

[0041] Thereafter, in step S107, a display step is performed. In the display step, the display unit 204 displays the type of bearing identified by the classification unit 203 and the peak value in the frequency spectrum. A maintenance and inspection worker determines whether or not there is a fault in the elevator traction machine bearing by visually checking the display unit 204. This completes the elevator traction machine bearing diagnosis method using the elevator traction machine bearing diagnosis device.

[0042] As described above, the elevator hoisting machine bearing diagnosis device according to the first embodiment includes the vibration sensor unit 1, the frequency spectrum calculation unit 202, and the classification unit 203. The vibration sensor unit 1 measures the vibration of the elevator hoisting machine. The frequency spectrum calculation unit 202 calculates the frequency spectrum of the vibration of the elevator hoisting machine using the measurement results of the vibration sensor unit 1. The classification unit 203 identifies the type of bearing included in the elevator hoisting machine from among multiple bearing types, using the frequency value corresponding to the peak value in the frequency spectrum calculated by the frequency spectrum calculation unit 202. According to this configuration, the classification unit 203 identifies the type of bearing included in the elevator hoisting machine from among multiple bearing types, using the frequency value corresponding to the peak value in the frequency spectrum. This makes it possible to identify the type of bearing included in the elevator hoisting machine from among multiple bearing types. As a result, even if the type of bearing included in the elevator hoisting machine is unknown, it is possible to determine whether or not there is a fault in the bearing of the elevator hoisting machine based on the type of bearing included in the elevator hoisting machine.

[0043] Furthermore, in the elevator hoisting machine bearing diagnosis device according to the first embodiment, the classification unit 203 extracts a portion included in a preset frequency range from the frequency spectrum calculated by the frequency spectrum calculation unit 202. Furthermore, the classification unit 203 identifies the type of bearing of the elevator hoisting machine by using the frequency value corresponding to the peak value in the extracted portion. This configuration can reduce the time required for the classification unit 203 to classify the type of bearing.

[0044] Furthermore, in the elevator hoisting machine bearing diagnosis device according to the first embodiment, the preset frequency range is a frequency range in which a peak value can occur when damage occurs in each of the multiple bearing types. With this configuration, it is possible to exclude a frequency range that is unrelated to the occurrence of bearing damage from the frequency spectrum calculated by the frequency spectrum calculation unit 202. This makes it possible to reduce the time it takes for the classification unit 203 to classify the bearing types while maintaining the accuracy of the classification of the bearing types by the classification unit 203.

[0045] The elevator hoisting machine bearing diagnosis device according to the first embodiment also includes a display unit 204. Display unit 204 displays the model number of the type of bearing identified by classification unit 203 and the peak value in the frequency spectrum. With this configuration, a maintenance and inspection worker can visually check display unit 204, thereby determining whether or not there is a fault in the elevator hoisting machine bearing.

[0046] Furthermore, in the elevator hoisting machine bearing diagnosis device according to the first embodiment, the measurement results of the vibration sensor unit 1 include brake release data D1 and constant speed section data D3. The brake release data D1 is data measured when the brake of the elevator hoisting machine is released. The constant speed section data D3 is data measured during a period when the rotating shaft of the elevator hoisting machine rotates at a constant speed. The elevator hoisting machine bearing diagnosis device according to the first embodiment includes a calibration unit 201. The calibration unit 201 calibrates the amplitude value V3 of the constant speed section data D3 using the amplitude value V1 in the brake release data D1. The frequency spectrum calculation unit 202 calculates a frequency spectrum using the constant speed section data D3 calibrated by the calibration unit 201. With this configuration, when the sensitivity of the vibration sensor unit 1 changes and calibration of the vibration sensor unit 1 is necessary, the measurement results of the vibration sensor unit 1 can be calibrated without using a calibration device for calibrating the vibration sensor unit 1. This facilitates calibration of the measurement results of the vibration sensor unit 1.

[0047] Furthermore, in the elevator hoisting machine bearing diagnosis device according to the first embodiment, the frequency spectrum calculation unit 202 corrects the frequency values ​​in the frequency spectrum using the value of the rotation speed of the rotating shaft of the elevator hoisting machine during the time when the rotating shaft of the elevator hoisting machine rotates at a constant speed. With this configuration, it is possible to identify the type of bearing that each of a plurality of elevator hoisting machines has, with a simple configuration, for each of the elevator hoisting machines whose rotating shafts have different rotation speeds.

[0048] Furthermore, the elevator hoisting machine bearing diagnosis method according to the first embodiment includes a vibration measurement step, a frequency spectrum calculation step, and a type identification step. In the vibration measurement step, the vibration of the elevator hoisting machine is measured. In the frequency spectrum calculation step, a frequency spectrum of the vibration of the elevator hoisting machine is calculated using the measurement results of the vibration of the elevator hoisting machine measured in the vibration measurement step. In the type identification step, the type of bearings included in the elevator hoisting machine is identified from among a plurality of bearing types using a frequency value corresponding to a peak value in the frequency spectrum calculated in the frequency spectrum calculation step. According to this configuration, in the type identification step, the type of bearings included in the elevator hoisting machine is identified from among a plurality of bearing types using a frequency value corresponding to a peak value in the frequency spectrum. This makes it possible to identify the type of bearings included in the elevator hoisting machine from among a plurality of bearing types. As a result, even if the type of bearings included in the elevator hoisting machine is unknown, it is possible to determine whether or not there is a fault in the bearings of the elevator hoisting machine based on the type of bearings included in the elevator hoisting machine.

[0049] In the elevator hoisting machine bearing diagnosis device according to the first embodiment, the information processing unit 2 is configured to include the calibration unit 201 that calibrates the amplitude value V3 in the constant speed section data D3 using the amplitude value V1 in the brake release data D1. However, if the sensitivity of the vibration sensor unit 1 is calibrated, the information processing unit 2 may be configured without the calibration unit 201.

[0050] In the elevator hoisting machine bearing diagnosis device according to the first embodiment, the frequency spectrum calculation unit 202 is configured to correct the frequency values ​​in the frequency spectrum using the value of the rotational speed of the rotating shaft of the elevator hoisting machine. However, the frequency spectrum calculation unit 202 may be configured not to correct the frequency values ​​in the frequency spectrum. In this case, multiple machine learning models corresponding to multiple values ​​of the rotational speed of the rotating shaft of the elevator hoisting machine are pre-set in the classification unit 203. The classification unit 203 selects a machine learning model corresponding to the value of the rotational speed of the rotating shaft of the elevator hoisting machine from among the multiple machine learning models. The classification unit 203 also identifies the type of bearing of the elevator hoisting machine using the selected machine learning model and the frequency value corresponding to the peak value in the frequency spectrum. Alternatively, multiple reference speed values ​​may be pre-set in the frequency spectrum calculation unit 202, and the frequency spectrum calculation unit 202 may select a reference speed value closest to the rotational speed of the rotating shaft of the elevator hoisting machine from among the multiple reference speed values. In this case, the frequency spectrum calculation unit 202 corrects the frequency values ​​in the calculated frequency spectrum using the selected reference speed value and the value of the rotational speed of the rotating shaft of the elevator hoisting machine. In this case, a plurality of machine learning models corresponding to each of the plurality of reference speed values ​​are set in advance in the classification unit 203. The classification unit 203 selects a machine learning model corresponding to the reference speed value from the plurality of machine learning models. The classification unit 203 also identifies the type of bearing of the elevator hoisting machine using the selected machine learning model and the value of the frequency corresponding to the peak value in the frequency spectrum.

[0051] Furthermore, in the elevator hoisting machine bearing diagnosis device according to the first embodiment, the configuration of the classifying unit 203 has been described, in which the classifying unit 203 extracts, from the frequency spectrum, a plurality of portions included in a preset frequency range. However, the classifying unit 203 may be configured not to extract a plurality of portions from the frequency spectrum. In this case, the type of bearing of the elevator hoisting machine is identified using a plurality of frequency values ​​corresponding to all of the peak values ​​in the frequency spectrum calculated by the frequency spectrum calculating unit 202.

[0052] Furthermore, the elevator hoisting machine bearing diagnosis device according to the first embodiment may be configured so that information identifying the elevator hoisting machine is input to the information processing unit 2. In this case, a plurality of machine learning models corresponding to each of a plurality of elevator hoisting machines are set in advance in the classification unit 203. The classification unit 203 selects a machine learning model corresponding to the information identifying the elevator hoisting machine from among the plurality of machine learning models. Furthermore, the classification unit 203 identifies the type of bearing of the elevator hoisting machine using the selected machine learning model and the frequency value corresponding to the peak value in the portion extracted from the frequency spectrum.

[0053] The elevator traction machine bearing diagnostic device and elevator traction machine bearing diagnostic method according to the preferred embodiment 1 have been described above, but the present invention is not limited to the elevator traction machine bearing diagnostic device and elevator traction machine bearing diagnostic method according to the above-described embodiment 1. Various modifications and conversions can be made to the elevator traction machine bearing diagnostic device and elevator traction machine bearing diagnostic method according to the above-described embodiment 1 without departing from the scope of the claims. [Explanation of symbols]

[0054] 1 vibration sensor unit, 2 information processing unit, 201 calibration unit, 202 frequency spectrum calculation unit, 203 classification unit, 204 display unit.

Claims

1. a vibration sensor unit for measuring vibrations of the elevator hoisting machine; a frequency spectrum calculation unit that calculates a frequency spectrum of vibration of the elevator hoisting machine using the measurement result of the vibration sensor unit; a classification unit that identifies a type of bearing included in the elevator hoisting machine from among a plurality of bearing types, using a frequency value corresponding to a peak value in the frequency spectrum calculated by the frequency spectrum calculation unit; An elevator traction machine bearing diagnostic device comprising:

2. 2. The elevator hoisting machine bearing diagnosis device according to claim 1, wherein the classifying unit extracts a portion of the frequency spectrum calculated by the frequency spectrum calculating unit that is included in a predetermined frequency range, and identifies the type of bearing of the elevator hoisting machine by using a frequency value corresponding to the peak value in the extracted portion.

3. 3. The elevator hoist machine bearing diagnosis device according to claim 2, wherein the predetermined frequency range is a frequency range in which the peak value can occur when damage occurs in each of the plurality of bearing types.

4. 4. The elevator hoisting machine bearing diagnosis device according to claim 1, further comprising a display unit that displays the type of bearing identified by the classification unit and the peak value.

5. the measurement results of the vibration sensor unit include brake release data measured when a brake of the elevator hoisting machine is released and constant speed section data measured during a time when a rotating shaft of the elevator hoisting machine rotates at a constant speed, a calibration unit that calibrates the amplitude value in the constant speed section data using the amplitude value in the brake release data, 4. The elevator hoisting machine bearing diagnosis device according to claim 1, wherein the frequency spectrum calculation unit calculates the frequency spectrum using the constant speed section data calibrated by the calibration unit.

6. 6. The elevator hoist machine bearing diagnosis device according to claim 5, wherein the frequency spectrum calculation unit corrects the frequency values ​​in the frequency spectrum by using values ​​of the rotational speed of the rotating shaft of the elevator hoist machine during a time period when the rotating shaft of the elevator hoist machine rotates at a constant speed.

7. a vibration measurement step of measuring the vibration of the elevator hoisting machine; a frequency spectrum calculation step of calculating a frequency spectrum of the vibration of the elevator hoisting machine using the measurement results of the vibration of the elevator hoisting machine measured in the vibration measurement step; a type identification step of identifying a type of bearing included in the elevator hoisting machine from among a plurality of bearing types, using a frequency value corresponding to a peak value in the frequency spectrum calculated in the frequency spectrum calculation step; A diagnostic method for an elevator traction machine bearing comprising:

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