Device and method for diagnosing abnormalities in rotating machinery.
The abnormality diagnosis device for rotating machinery equipment addresses the limitations of conventional methods by analyzing relative vibration data across multiple sensors to accurately identify the abnormal location and cause, reducing diagnostic costs and preventing misdiagnosis.
Patent Information
- Authority / Receiving Office
- JP · JP
- Patent Type
- Patents
- Current Assignee / Owner
- JFE PLANT ENG CO LTD
- Filing Date
- 2023-07-21
- Publication Date
- 2026-06-08
AI Technical Summary
Conventional abnormal diagnosis methods for rotating machinery equipment fail to determine the overall abnormal location and cause by comparing analysis results across multiple parts, leading to unnecessary disassembly and maintenance of components that are not malfunctioning, and are dependent on the expertise of veteran diagnosticians, increasing costs.
An abnormality diagnosis device and method that identifies the abnormal location and cause in rotating machinery equipment by analyzing the relative relationships of vibration data from multiple sensors, using velocity and acceleration values, and performing frequency analysis to determine the true source of abnormalities.
Enables highly reliable abnormal diagnosis with reduced diagnostic costs by accurately identifying the abnormal location and cause, preventing misdiagnosis and unnecessary maintenance, thereby optimizing maintenance and reducing repair costs.
Smart Images
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Abstract
Description
Technical Field
[0001] The present invention relates to an abnormal diagnosis device and method for rotating machinery equipment.
Background Art
[0002] As an abnormal diagnosis method for rotating machinery equipment using a conventional vibration sensor, for example, those disclosed in Patent Documents 1 to 4 are available. The methods disclosed in these patent documents are generally as follows. For example, vibration sensors are installed on each of a motor, a bearing part, and a driven machine such as a pump that constitute rotating machinery equipment to collect vibration waveform data, and vibration magnitude evaluation, frequency analysis, etc. are performed for each part. Then, by comparing the similarity between the information obtained from the analysis result and the determination conditions of an abnormal determination matrix determined in advance for each abnormal cause, the one with a high similarity is estimated as the abnormal cause.
Prior Art Documents
Patent Documents
[0003]
Patent Document 1
Patent Document 2
Patent Document 3
Patent Document 4
Summary of the Invention
Problems to be Solved by the Invention
[0004] However, the conventional diagnosis logic estimates the abnormal cause for each part based on the analysis result for each vibration sensor (per part) attached to the rotating machinery equipment, and does not determine the overall abnormal location and abnormal cause of the equipment by comparing and examining the analysis results of a plurality of vibration sensors attached to a plurality of parts with each other.
[0005] For example, in equipment where a motor rotates the impeller of a blower, if there is an imbalance in the impeller, the vibration caused by the impeller's imbalance will also affect the motor and coupling. Therefore, if a diagnosis is performed on a component-by-component basis as in the conventional method, abnormal vibrations may be detected by all vibration sensors, and as a result, the system may automatically diagnose that there is an imbalance in all components.
[0006] In this case, unnecessary disassembly and maintenance, as well as irrelevant repairs and adjustments, were sometimes performed on motors and couplings that were not actually malfunctioning. Traditionally, to avoid such misdiagnoses, a thought process was required in which veteran diagnosticians comprehensively determined the true cause and location of the abnormality based on their knowledge and experience. In other words, based on the diagnostic results for each individual part obtained by automated diagnostics, experienced diagnosticians would take a comprehensive look at the entire system to determine which part was causing the malfunction.
[0007] However, requiring the comprehensive judgment of a veteran diagnostician would increase diagnostic costs, and the diagnostic results could also be influenced by the competence of the veteran diagnostician. Therefore, there was a need for a reliable abnormality detection device and method for rotating machinery equipment that could keep diagnostic costs down.
[0008] This invention addresses such requirements and aims to provide a highly reliable abnormality diagnosis device and method for rotating machinery equipment while keeping diagnostic costs down. [Means for solving the problem]
[0009] (1) The abnormality diagnosis device for rotating machinery equipment according to the present invention comprises a rotational drive unit that drives rotation, a transmission unit that transmits the driving force of the rotational drive unit, and a rotationally driven unit that rotates by the rotational force transmitted by the transmission unit, The system includes vibration sensors installed in the rotational drive unit, the transmission unit, and the rotationally driven unit, and an abnormality diagnosis unit that diagnoses abnormalities by inputting vibration data collected by the vibration sensors. The abnormality diagnosis unit is characterized by comprising an abnormality location identification unit that identifies the abnormal location of the rotating machinery equipment based on the relative relationships of the vibration data, and an abnormality cause identification unit that identifies the cause of the abnormality based on the vibration data at the identified abnormal location.
[0010] (2) Furthermore, in the device described in (1) above, the abnormal location identification unit is characterized in that it identifies the abnormal location based on the relative relationship between the velocity value and acceleration value of each vibration data.
[0011] (3) In addition, in the case described in (1) or (2) above, the abnormality cause identification unit is characterized in that it performs frequency analysis based on the vibration data and identifies the cause of the abnormality based on the results of the frequency analysis.
[0012] (4) The method for diagnosing abnormalities in rotating machinery equipment according to the present invention is a method for diagnosing abnormalities in rotating machinery equipment comprising a rotation drive unit that drives rotation, a transmission unit that transmits the driving force of the rotation drive unit, and a rotation driven unit that rotates by the rotational force transmitted by the transmission unit, The present invention is characterized by comprising: an abnormality location identification step that identifies an abnormal location in the rotating machinery based on the relative relationship of vibration data collected by vibration sensors installed in each of the rotational drive unit, the transmission unit, and the rotational driven unit; and an abnormality cause identification step that identifies the cause of the abnormality based on the vibration data at the identified abnormal location.
[0013] (5) Furthermore, in the case described in (4) above, the abnormal location identification step is characterized in that the abnormal location is identified based on the relative relationship between the velocity value and acceleration value of each vibration data.
[0014] (6) Also, in the case of the above (4) or (5), the abnormal cause identification step is characterized by performing frequency analysis based on the vibration data and identifying the abnormal cause based on the result of the frequency analysis.
Effect of the Invention
[0015] In the abnormal diagnosis device for rotating machinery equipment according to the present invention, the abnormal diagnosis unit includes an abnormal location identification unit that identifies an abnormal location of the rotating machinery equipment based on the relative relationship of each vibration data, and an abnormal cause identification unit that identifies an abnormal cause based on the vibration data at the identified abnormal location. As a result, it is possible to perform highly reliable abnormal diagnosis of rotating machinery equipment while suppressing the diagnosis cost. As a result, incorrect maintenance work and incorrect repair adjustments can be prevented, optimal maintenance can be realized, and repair costs can be reduced.
Brief Description of the Drawings
[0016] [Figure 1] It is a block diagram for explaining the configuration of the abnormal diagnosis device according to Embodiment 1. [Figure 2] It is a flowchart of the abnormal diagnosis method according to Embodiment 1. [Figure 3] It is a diagram showing the speed waveform detected by the vibration sensor at the attachment location (iv) in FIG. 1. [Figure 4] It is a graph showing the speed values detected by each vibration sensor. [Figure 5] It is a diagram showing an example of the database of the abnormal diagnosis device according to the present embodiment. [Figure 6] It is a diagram showing the result of frequency analysis of the data obtained by the vibration sensor. [Figure 7] It is an explanatory diagram of the attachment positions of the rotating machinery equipment and the vibration sensors targeted by the abnormal diagnosis method according to Embodiment 2. [Figure 8] It is a graph showing the speed values detected by each vibration sensor in FIG. 7. [Figure 9] It is a diagram showing the result of frequency analysis of the data obtained by the vibration sensors at the attachment locations (ii) and (iii) in FIG. 7. [Modes for carrying out the invention]
[0017] [Embodiment 1] In this embodiment, as shown in Figure 1, the blower equipment 13 to be diagnosed includes a motor 1 that rotates, a coupling 5 that connects the rotating shaft of the motor 1 to the drive shaft 3, a first bearing section 7 and a second bearing section 9 that incorporate bearings to support the rotation of the drive shaft 3, and an impeller 11 that rotates on the drive shaft 3. Furthermore, the motor 1 corresponds to the rotary drive unit of the present invention, the coupling 5, drive shaft 3, first bearing unit 7, and second bearing unit 9 correspond to the transmission unit of the present invention, the impeller 11 corresponds to the rotary driven unit of the present invention, and the blower equipment 13 corresponds to the rotating machinery equipment of the present invention.
[0018] The abnormality diagnosis device 15 of this embodiment, which targets the blower equipment 13 described above for diagnosis, includes, as shown in Figure 1, vibration sensors (i) and (ii) installed on the motor 1, a vibration sensor (iii) installed on the first bearing portion 7, which is closer to the shaft coupling 5, and a vibration sensor (iv) installed on the second bearing portion 9, which is closer to the impeller 11, and an abnormality diagnosis unit 17 that diagnoses abnormalities by inputting vibration data acquired by these vibration sensors (i) to (iv). The abnormality diagnosis unit 17 includes an abnormality location identification unit 19 that identifies the abnormal location of the blower equipment 13 based on the relative relationship of each vibration data, and an abnormality cause identification unit 21 that identifies the cause of the abnormality based on the vibration data at the identified abnormal location.
[0019] The abnormal location identification unit 19 of this embodiment 1 identifies the abnormal location based on the relative relationship between the velocity value and acceleration value of each vibration data. Furthermore, the abnormality cause identification unit 21 of this embodiment 1 performs frequency analysis based on vibration data and identifies the cause of the abnormality based on the results of the frequency analysis.
[0020] Next, the abnormality diagnosis method using the abnormality diagnosis device 15 shown in Figure 1 will be explained based on Figures 1 and 2 to 6. The abnormal location identification unit 19 acquires vibration data from vibration sensors (i) to (iv) and obtains velocity values (velocity waveforms) (S1). Figure 3 shows the velocity waveform acquired from vibration sensor (iv). As shown in Figure 3, it can be seen that vibrations of 6.0 mm / s occur every 20 ms at the location of vibration sensor (iv). Figure 4 shows graphs of the velocity values caused by vibrations from vibration sensors (i) to (iv). Table 1 shows each velocity value and the individual judgment results based on them.
[0021] [Table 1]
[0022] When examining the speed values individually, vibration sensors (iv), (iii), and (i) with speed values exceeding 3.0 are identified as requiring attention or indicating an abnormality at the location where they are installed. Furthermore, since the conventional diagnostic logic performs individual judgments on a part-by-part basis, as shown in Table 1, the diagnostic result indicates an imbalance abnormality in both motor 1 and blower.
[0023] In contrast, in this embodiment, the abnormality location identification unit 19 compares the velocity values of each vibration sensor (i) to (iv) (S2). The relative relationship of the velocity values is as shown in Table 1 and Figure 4, (iv)>(iii)>(i)>(ii). The abnormality location identification unit 19 refers to the database 22, which stores the relationship between the relative speed values and the abnormality location, and identifies that the abnormality is located in the impeller 11 (S5).
[0024] Here, an example of database 22 will be explained based on Figure 5. As shown in Figure 5, database 22 stores data corresponding to the name of the cause of the anomaly, including the magnitude distribution of velocity values, the magnitude distribution of acceleration values, the velocity frequency component of the anomaly location, and the acceleration frequency component of the anomaly location.
[0025] In the case of the blower equipment 13 shown in Figure 1, the parts where malfunctions may occur are the impeller 11, shaft coupling 5, motor 1, first bearing section 7, and second bearing section 9. The cause of malfunctions in the impeller 11 and motor 1 is unbalance, and the cause of malfunction in the shaft coupling 5 is misalignment (off-center). In addition, the cause of malfunctions in the first bearing section 7 and second bearing section 9 is damage (for example, wear or deformation of the balls in the ball bearings). Below, we will describe the characteristics of the velocity value magnitude distribution, acceleration value magnitude distribution, velocity frequency component of the abnormal location, and acceleration frequency component of the abnormal location for each abnormal location and cause, both under normal and abnormal conditions.
[0026] <Normal time> Under normal conditions, as shown in Figure 5, the velocity and acceleration values of each part are small and approximately the same in each part.
[0027] <Impeller Unbalanced> Unbalance refers to a state in which the mass distribution of a rotating body is uneven due to factors such as wear, deformation, or adhesion of foreign matter to a part of the rotating body. When a rotating body rotates in this unbalanced state, centrifugal force is generated in the uneven area, and this centrifugal force causes the impeller 11 and shaft to wobble and vibrate, resulting in abnormal vibrations. The oscillating vibration is transmitted to other parts via the rotating shaft connected to the rotating body with the non-uniform area, but the abnormal vibration is greatest in the part with the non-uniform area.
[0028] If an imbalance occurs in the impeller 11, the speed value will be at its maximum at vibration sensor (iv), which is closest to the impeller 11 where the imbalance occurs. However, since this abnormal vibration is transmitted to other parts, vibrations greater than normal will also be observed at vibration sensors (iii) to (i). The relative relationship of the magnitudes of the velocity values is (iv)>(iii)>(ii)>(i). Note that in Table 1 and Figure 4, the speed value of (i) is greater than that of (ii), because the vibration is amplified due to the structure of motor 1, which makes part (i) more prone to free movement. In other words, in the case of Figure 1, if an imbalance occurs in the impeller 11, the cases (iv)>(iii)>(ii)>(i) and (iv)>(iii)>(i)>(ii) can be assumed. Note that in the database 22 shown in Figure 5, the illustrations for (iv)>(iii)>(i)>(ii) are omitted.
[0029] In the case of imbalance, the acceleration value is not affected, so the acceleration values for the four vibration sensors (i) to (iv) are small and almost identical, similar to the normal values.
[0030] In the case of impeller imbalance, frequency analysis of the vibration data from the vibration sensor (iv) reveals that the velocity value increases at the rotation frequency (fr) of the impeller 11.
[0031] <Shaft coupling misalignment> If misalignment occurs in the shaft coupling 5, the vibration will increase at the locations of the two vibration sensors (ii) and (iii) on either side of the shaft coupling 5, causing the velocity values of the vibration sensors (ii) and (iii) to increase. Furthermore, since the abnormal location is the shaft coupling 5, the velocity values of the vibration sensors (ii) and (iii) on both sides of it will be almost identical.
[0032] In the case of misalignment, it does not affect the acceleration value, so the acceleration values of the four vibration sensors (i) to (iv) are small and almost identical, similar to the normal values.
[0033] In the case of shaft coupling misalignment, the speed value increases at rotational frequency (fr) and at high frequencies of twice that frequency or more.
[0034] <Motor unbalance> If an imbalance occurs in the rotation axis of motor 1 for any reason, the velocity value of vibration sensor (i), which is installed in a part of motor 1 that is easily swayed due to its structure, will increase, followed by the velocity value of vibration sensor (ii).
[0035] In the case of motor unbalance, it does not affect the acceleration value, so the acceleration values from the four vibration sensors (i) to (iv) are small and almost identical, similar to the normal values.
[0036] In the case of motor unbalance, frequency analysis of the vibration data from the vibration sensor (i) reveals that the velocity value increases at the rotation frequency (fr) of the impeller 11.
[0037] <Blower bearing damage (part (iii))> If the first bearing section 7 of the blower's bearing section, where the vibration sensor (iii) is installed, is damaged, high-frequency vibrations will occur at that location. In this case, there is no change in the velocity value, so the velocity values of the four vibration sensors (i) to (iv) are small and almost identical, similar to the normal values. On the other hand, the acceleration value from the vibration sensor (iii) is overwhelmingly larger. At this time, frequency analysis reveals that frequency components based on defects in the first bearing section 7 become larger, and frequency components more than twice that level also appear.
[0038] The above is an overview of the database 22. As mentioned above, the abnormality location identification unit 19 refers to the database 22 to determine the relationship between the relative vibration velocity values and the abnormality location. Since the magnitude and distribution of the velocity values shown in Figure 4 are similar to those of impeller unbalances stored in the database 22, it identifies the abnormality location as being in the impeller 11 (S5).
[0039] When the abnormality is identified as being in the impeller 11, the abnormality cause identification unit 21 performs frequency analysis of the identified location, i.e., the vibration data acquired by the vibration sensor (iv) (S7). The vibration waveform (velocity spectrum) of the frequency analysis result is shown in Figure 6. Here, the rotational speed of impeller 11 is 2963 rpm, so the rotational frequency (fr) is 2963 / 60 = 49.4 Hz. Also, the rotational period is 1 / 49.4 = 0.02 s (20 ms). Frequency analysis revealed that the vibration waveform has a one-rotation period, and the frequency analysis results show that the rotational frequency component of 49.4 Hz (fr component) is dominant. From this, the cause of the abnormality can be identified as an imbalance.
[0040] In this regard, as mentioned above, in the case of individual judgments of vibration sensors (i) to (iv), as shown in Table 1, it is determined that there is an imbalance in both motor 1 and impeller 11, whereas in this embodiment, it is correctly determined that the imbalance in impeller 11, not motor 1, is the cause of the abnormality. This eliminates the possibility of misdiagnosis as an imbalance on the motor 1 side, and abnormal vibrations can be resolved by servicing the blower side.
[0041] [Embodiment 2] Next, we will describe an example of abnormality diagnosis for a pump system 25, which includes a motor 1, a shaft coupling 5, a bearing section 23, and a pump body 24, as shown in Figure 7. Note that the reference numerals for each part in Figure 7 are the same as those used in Figure 1 for parts that correspond to those in Figure 1. The bearing section 23 is integrated with the pump body 24, and vibration sensors are provided at four locations (i) to (iv) as shown in Figure 7. This example shows a case where misalignment (off-centering) has occurred in the shaft coupling 5. Figure 8 shows graphs of velocity values caused by vibrations from vibration sensors (i) to (iv). Table 2 shows each velocity value and the individual judgment results based on them.
[0042] [Table 2]
[0043] As shown in Figure 8, the velocity value of the vibration sensor (iii) is exceptionally high, so if individual assessment is performed, it will be determined to be either a misalignment of the coupling 5 or play due to wear of the bearing portion 23, as shown in Table 2. This is because the vibration characteristics when there is play in the bearing portion 23 are similar to the vibration characteristics when there is a misalignment in the shaft coupling 5. In other words, if individual assessment is performed, it is not possible to determine whether the abnormality is in the shaft coupling 5 or the bearing portion 23, so both will need to be addressed. Furthermore, any play in the bearing section 23 will require disassembly and maintenance of the pump, and any misalignment of the shaft coupling 5 will require centering adjustment. Therefore, as in this example, even when there is a problem with the shaft coupling 5 but no problem with the bearing section 23, unnecessary maintenance is required, such as disassembling and servicing the pump.
[0044] In the case of misalignment of the shaft coupling 5, the vibration source is the shaft coupling 5, so it is common for the vibrations of vibration sensors (ii) and (iii) on both sides of the shaft coupling 5 to increase. In this regard, Figure 8 shows that the vibrations of vibration sensors (ii) and (iii) are increased. Furthermore, since the movement of the shaft coupling 5 itself constitutes a vibration waveform, the vibration waveforms of vibration sensors (ii) and (iii) that sandwich the shaft coupling 5 are similar. As a result, frequency analysis reveals, as shown in Figure 9, that when there is a misalignment, the components of the frequency spectra of parts (ii) and (iii) are similar. When misalignment occurs, the rotation frequency component fr and its harmonics (more than twice that frequency) appear.
[0045] In this second embodiment, the abnormality location identification unit 19 refers to a database 22 that stores the relative relationship between speed values and the abnormality location, and identifies the abnormality location as being in the shaft coupling 5 or the bearing section 23 based on the magnitude and distribution of the speed values. Then, the abnormality cause identification unit 21 identifies the cause of the abnormality as being due to misalignment of the shaft coupling 5, rather than wear and play in the bearing 23, because the frequency components of the vibration sensors (ii) and (iii) are similar. This prevents misdiagnosis of play in the bearing section 23, thus preventing the pump from being mistakenly disassembled and serviced.
[0046] As described in Embodiments 1 and 2 above, the present invention enables highly reliable abnormality diagnosis of rotating machinery equipment while reducing diagnostic costs. As a result, incorrect maintenance work and incorrect repair adjustments can be prevented, optimal maintenance can be achieved, and repair costs can be reduced. Furthermore, if the abnormal location and cause of the abnormality are identified, the abnormal location and cause may be displayed on a display unit 27 such as a monitor, and appropriate countermeasures (guidance text) may be automatically output (on a monitor or on paper). [Explanation of Symbols]
[0047] 1 motor 3 drive shafts 5. Shaft coupling 7 First bearing part 9 Second bearing part 11 Impeller 13 Blower equipment 15. Anomaly Diagnosis Device 17. Department of Abnormal Diagnosis 19. Abnormality Identification Section 21 Abnormality cause identification section 22 Databases 23 Bearing section 24 Pump body 25 Pumping equipment 27 Display section (i)~(iv) Vibration sensor, measurement location
Claims
1. An abnormality diagnosis device for rotating machinery equipment comprising a rotational drive unit that drives rotation, a transmission unit that transmits the driving force of the rotational drive unit, and a rotationally driven unit that rotates by the rotational force transmitted by the transmission unit, The system includes vibration sensors installed in the rotational drive unit, the transmission unit near the rotational drive unit, and the transmission unit near the rotationally driven unit, and an abnormality diagnosis unit that diagnoses abnormalities by inputting vibration data collected by the vibration sensors. The abnormality diagnosis device for rotating machinery is characterized by comprising: an abnormality location identification unit that identifies an abnormal location in the rotating machinery based on the relative relationship of the vibration data; and an abnormality cause identification unit that identifies the cause of the abnormality based on the vibration data at the identified abnormal location.
2. The abnormality detection unit identifies the abnormality based on the relative relationship between the velocity value and acceleration value of each vibration data, as described in claim 1, for the abnormality diagnosis device for rotating machinery equipment.
3. The abnormality diagnosis device for rotating machinery equipment according to claim 1 or 2, characterized in that the abnormality cause identification unit performs frequency analysis based on the vibration data and identifies the cause of the abnormality based on the results of the frequency analysis.
4. A method for diagnosing abnormalities in a rotating machinery, comprising a rotating drive unit that performs rotational driving, a transmission unit that transmits the driving force of the rotating drive unit, and a rotating driven unit that rotates by the rotational force transmitted by the transmission unit, A method for diagnosing abnormalities in rotating machinery, comprising: an abnormality location identification step for identifying an abnormal location in the rotating machinery based on the relative relationship of vibration data collected by vibration sensors installed in the rotating drive unit, the transmission unit near the rotating drive unit, and the transmission unit near the rotating driven unit; and an abnormality cause identification step for identifying the cause of the abnormality based on the vibration data at the identified abnormal location.
5. The abnormality diagnosis method for rotating machinery equipment according to claim 4, characterized in that the abnormality location identification step identifies the abnormality location based on the relative relationship between the velocity value and acceleration value of each vibration data.
6. The method for diagnosing abnormalities in rotating machinery equipment according to claim 4 or 5, characterized in that the abnormality cause identification step involves performing a frequency analysis based on the vibration data and identifying the cause of the abnormality based on the results of the frequency analysis.