JP2002188411A - Abnormality diagnosing apparatus - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an abnormality diagnosing apparatus capable of carrying out a highly reliable diagnosis of abnormalities, without having to depend on experience, etc., of the operator. SOLUTION: The abnormality diagnosing apparatus is capable of carrying out a highly reliable diagnosis of abnormalities, without depending on the experiences of the operator, etc., by obtaining detailed information, such as the conditions of the sliding part (contact part) of the bearing 2 is in, and on what mechanism the abnormalities found there are based, etc., through having an AE sensor 5 detect the development of cracks on a bearing 2 and an elastic wave thereon at the time of direct contact, having a worn fragment sensor 6 detect the wear phenomenon by means of the minute particles with their forms being reflected, and having an abnormality diagnosing means 7 diagnose abnormalities, while integrating different types of information.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an abnormality diagnosis apparatus for diagnosing abnormalities such as wear and cracks in a support portion for supporting a movable portion, particularly for a bearing portion for supporting a rotating shaft.

[0002]

2. Description of the Related Art For example, in a power plant equipped with a gas turbine or a steam turbine, a large number of devices having a sliding member and a rotating shaft supported by bearings are provided. During operation of the equipment, fine wear powder and the like are generated from the sliding member and the support (contact part) of the rotating shaft, and the wear powder and the like become foreign matters and are mixed into the lubricating oil and seize on the support. And so on. In addition, bearings (particularly ball bearings) have a lifetime, and if the operation is continued beyond the lifetime, damage such as cracks may occur.

[0003] As means for quickly diagnosing the occurrence of serious damage that hinders the normal operation of such equipment, vibrations, components of lubricating oil, foreign substances contained in lubricating oil, etc., which are indicators of plant operating conditions, are used. Diagnosis for measuring the number of pieces has been conventionally performed, and the support section is managed by the abnormality diagnosis.

[0004] In the conventional abnormality diagnosis, a vibration detecting means (such as an ultrasonic vibration sensor) is provided in a bearing portion to detect vibration of a bearing portion, and the detected vibration is analyzed. And the state of occurrence, such as damage and damage, are estimated. Further, the lubricant is sampled, and the properties, distribution, and the like of the wear powder in the sampled oil are analyzed, so that the operator estimates the state of a crack, damage, or the like based on the analysis result.
Then, when any abnormality is estimated, an alarm or the like is issued to cause a worker on site to take necessary measures such as replacing parts or stop the operation of the plant.

[0005]

In the conventional abnormality diagnosis, vibration which is an index of a plant operating state, components of lubricating oil, foreign substances contained in lubricating oil, and the like are measured. It is analyzed and analyzed and notified to the worker as information. The worker integrates and organizes information based on experience and the like, and diagnoses abnormalities by comprehensively estimating the state of cracks, damage, and the like. For this reason, in the conventional abnormality diagnosis, at present, the reliability of the diagnosis result largely depends on the skill level such as the experience of the worker. Further, at present, the reliability of the diagnosis result is also affected by the type of the device.

SUMMARY OF THE INVENTION The present invention has been made in view of the above circumstances, and has as its object to provide an abnormality diagnosis apparatus capable of performing highly reliable abnormality diagnosis regardless of the experience of an operator.

[0007]

According to a first aspect of the present invention, there is provided an abnormality diagnosing apparatus for at least one or more vibration detecting means for detecting a state of vibration of a supporting portion supporting a movable portion. And at least one wear powder detecting means for detecting the state of the wear powder, and abnormality diagnosis means for diagnosing an abnormality based on the detection information of the vibration detection means and the wear powder detection means.

According to another aspect of the present invention, there is provided an abnormality diagnosing apparatus for detecting at least one vibration detecting means for detecting a vibration state of a bearing portion supporting a rotary shaft. It is characterized by comprising at least one or more wear powder detecting means for detecting a state of wear powder at a bearing portion, and abnormality diagnosis means for diagnosing an abnormality based on detection information of the vibration detection means and the wear powder detection means. .

The abnormality diagnosis means includes a vibration generation detection function for detecting sudden vibration generation, intermittent vibration generation, and continuous vibration generation based on information from the vibration detection means, and a vibration generation detection function based on the detection information from the wear powder detection means. It is provided with a particle detection function for detecting the number of particles, a particle diameter and a particle shape of wear powder, and a function for detecting a foreign matter mixing state based on information of vibration detection means and detection information of wear powder detection means. I do.

The abnormality diagnosis means includes a storage function for storing a diagnosis result as time-series data, and a variation pattern derived based on the time-series data stored in the storage function to diagnose an abnormality according to the variation pattern. And a function to perform the function. Further, the bearing is immersed in the lubricating oil reservoir, the vibration detecting means is disposed in the lubricating oil in the lubricating oil reservoir, and the abnormality diagnosing means has a function of detecting vibration propagating the lubricating oil and diagnosing the abnormality. It is characterized by having. Further, a plurality of vibration detecting means are provided in the circumferential direction of the rotating shaft, and the abnormality diagnosing means divides the rotating shaft into a plurality of regions in the circumferential direction, synthesizes the output states of the plurality of vibration detecting means, and It is characterized in that a function of specifying a generation area is provided. In addition, the vibration generation detection function is to detect sudden vibration generation, intermittent vibration generation, and continuous vibration generation by sampling the state of vibration from the vibration detection means at low frequency and sampling at high frequency. It is characterized by. In addition, the particle detection function of the abnormality diagnosis means is characterized in that a wear state is diagnosed by evaluating a particle shape based on a particle size of the wear powder and a needle ratio which is a ratio of a minor axis to a major axis of the wear powder. I do.

[0011]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS FIG. 1 shows a schematic configuration of a rotary shaft support provided with an abnormality diagnosis device according to an embodiment of the present invention, and FIG. 2 shows a block configuration of an abnormality diagnosis means. FIG.
Is applied, for example, to a bearing portion of a rotary shaft of an air heater for recovering exhaust heat of a generator in a power plant equipped with a gas turbine or a steam turbine. The location to which the present invention is applied is not limited to the bearing of the rotating shaft of the air heater, but can be applied to the bearing of the rotating shaft of various devices. The present invention can be applied to a portion (supporting portion) of a sliding support member of a sliding member (movable portion).

As shown in FIG. 1, a rotating shaft 1 as a movable portion is rotatably supported by a bearing 2 (ball bearing) (support portion). The lower part of the bearing 2 is an oil bath 3
The lubricating oil is supplied and discharged from the lubrication line 4 to the oil bath 3. The lubricating oil in the oil bath 3 is supplied to the bearing 2 with the rotation of the rotating shaft 1.

An ultrasonic vibration sensor (AE sensor) 5 as a vibration detecting means is mounted on the outer ring side above the bearing 2, and the AE sensor 5 detects the state of vibration of the bearing 2. A wear powder sensor 6 is provided in the lubrication line 4,
The state of the wear powder on the bearing 2 is detected by the wear powder sensor 6. The detection signals of the AE sensor 5 and the abrasion powder sensor 6 are input to the abnormality diagnosis means 7 (control device).

The abnormality diagnosing means 7 diagnoses an abnormality based on the state of vibration (vibration detection function) and diagnoses an abnormality based on the state of wear powder (particle detection function).
An abnormality is diagnosed based on the state of vibration and the state of the abrasion powder due to the state of foreign substance contamination (function of detecting the state of foreign substance contamination).

That is, the AE sensor 5 detects the propagation of a crack in the material or an elastic wave at the time of direct contact, and the abrasion powder sensor 6 detects the wear phenomenon with fine particles reflecting the shape of the material. The information obtained is different. The abnormality diagnosis means 7 diagnoses an abnormality by integrating these different types of information. As a result, it is possible to obtain detailed information such as the current state of the sliding portion (contact portion) and the mechanism based on which abnormality has occurred.

The AE sensor 5 and the abrasion powder sensor 6 are
One or a plurality are provided depending on the size of the device, detection conditions, and the like.

As shown in FIG. 2, the detection signal of the AE sensor 5 is subjected to processing such as amplification and filter processing by an amplifier 8 and then passed through an AD converter 9 to calculate a vibration parameter. Is input to In the vibration processing unit 10,
The input data is parameterized into the number of ultrasonic events, amplitude, characteristic frequency, and the like, and the sliding state (contact state) is quantified. The detection signal of the wear powder sensor 6 is amplified and
After being subjected to processing such as filter processing, the data is input to a particle processing unit 13 that calculates particle parameters via an AD converter 12. In the particle processing unit 13, the input data is parameterized into the number and particle size of the abrasion powder, and the sliding state (contact state) is set.
Is quantified.

The sliding state (contact state) based on the vibration and wear powder quantified by the vibration processing unit 10 and the particle processing unit 13
Is sent to the first diagnostic unit 14, and the first diagnostic unit 14 uses a neural network that self-organizes diagnostic criteria by learning, an expert system that has diagnostic criteria created from past knowledge and experience of experiments, and the like. Short-term diagnosis such as sliding state evaluation and damage site diagnosis is performed.

That is, first, a slight level of direct contact with the sliding surface where damage does not surface is detected by the detection signal of the AE sensor 5. The severity of the sliding state can be evaluated based on the absolute value of the amplitude or the rate of change from the initial value.
Further, by frequency analysis, it is possible to detect synchronization with the rotation frequency and to estimate a damaged element. The particle size and particle distribution of the wear powder in the lubricating oil are detected by the detection signal of the wear powder sensor 6, and the severity of the sliding state can be evaluated from the information. At this time, the more abrasion powder having a large particle size, the more severe the sliding state.

It is conceivable that the abrasion powder originates from the sliding part and the abrasion powder generated by elements other than the sliding part is mixed. If abrasion powder is generated from the sliding part,
Wear powder is detected in response to the increase in the output of the E sensor 5. On the other hand, when contamination from the outside occurs, first, the output of the abrasion powder sensor 6 increases, and accompanying this, the output of the AE sensor 5 is detected. For this reason, the generation of the wear powder originating from the sliding portion and the mixing of the wear powder from the outside can be distinguished by the generation state of the output of the AE sensor 5 and the wear powder sensor 6.

The details of the short-term diagnosis will be described later with reference to FIGS.

Further, as shown in FIG.
Is also sent to the time-series data storage unit 15, and A
The time-series data storage unit 1 stores instantaneous values and diagnostic histories of diagnostic parameters based on the outputs of the E sensor 5 and the wear powder sensor 6.
5 is stored. The data stored in the time-series data storage unit 15 is sent to a second diagnosis unit 16, which creates a self-organized diagnosis criterion by learning from a neural network, learning from past knowledge, experience from experiments, and the like. An expert system or the like having the diagnostic criteria described above evaluates a sliding state and diagnoses a tendency in consideration of a variation pattern of a damaged portion or the like.

The details of the diagnosis of the tendency are shown in FIGS.
Will be described later.

The abnormality diagnosis (vibration generation detection function) based on vibration based on the state of signal processing of the AE sensor 5 will be described in detail with reference to FIGS. FIG. 3 is a block diagram of the configuration of the vibration generation detection function, FIG. 4 is a flowchart of the processing of the vibration signal, and FIG.

As shown in FIG. 3, the signal of the AE sensor 5 is sampled by the low frequency analyzer 21 and the high frequency analyzer 22. With respect to the vibration signal in the low frequency band sampled by the low frequency analysis device 21, parameters are extracted by the frequency analysis processing unit 23 using the original waveform and the envelope waveform (one waveform obtained by averaging a plurality of original waveforms). I do. With respect to the vibration signal in the high frequency band sampled by the high frequency analysis device 22, parameters are extracted by the signal shape evaluation signal processing unit 24 using the original waveform. In addition, the amplitude evaluation signal processing unit 25 of the vibration signal waveform extracts parameters for both the vibration signal in the low frequency band and the vibration signal in the high frequency band. These parameters are used together for diagnosis. The high frequency band is set to a frequency of about megahertz, and the low frequency band is set to an appropriate frequency according to the scale of the device, the number of rotations of the rotating shaft 1 to be operated, and the like.

Since the vibration signal has different phenomena suitable for measurement in the low-frequency band and the high-frequency band, detailed diagnosis of abnormalities can be made by combining the two diagnoses and using them for analysis.

In a relatively low frequency band, detection of a signal mainly corresponding to the rotation frequency is performed. For example, it has been known that damage corresponding to the inner and outer rings and the rolling elements of the bearing 2 generates a signal having a correlation with the rotation speed of the bearing 2. For this reason, it is possible to diagnose a damaged portion from the occurrence cycle.

The waveform of the vibration signal in the high frequency band is analyzed to determine whether the signal is generated continuously, independently, or intermittently. Or identify. That is, as shown in FIG. 4, when a vibration signal is generated, it is determined in step S1 whether another vibration signal is generated within a predetermined time, and when it is determined that another vibration signal is not generated. Single vibration (as shown in Fig. 5 (a))
It is assumed. If it is determined in step S1 that another vibration signal is generated within a predetermined time, it is determined in step S2 whether or not the signal is a continuous wave. If it is determined in step S2 that the wave is not a continuous wave, an intermittent vibration (the state shown in FIG. 5C) is set.
If it is determined in step S2 that the wave is a continuous wave, continuous vibration (the state shown in FIG. 5B) is set.

The solitary vibration corresponds to the propagation of a crack inside or on the surface of the material, and the intermittent vibration corresponds to the phenomenon such as stick-slip or fretting.
It is considered that continuous vibration corresponds to direct contact between two surfaces due to poor lubrication, skidding, or damage to a sliding surface. For this reason, the sliding state (contact state) can be diagnosed by analyzing the waveform of the vibration signal.

Referring to FIGS. 6 to 9, a description will be given of a function for specifying a specific mounting state of the AE sensor 5 and a position where an abnormality has occurred (a function for specifying an abnormality occurrence region). FIG. 6 shows an arrangement state of the AE sensor 5, and FIGS.
The output state of the sensor 5 is shown.

As shown in FIG. 6, in this embodiment, two AE sensors 5a and 5b are arranged 180 degrees symmetrically concentrically in the circumferential direction of the rotating shaft 1 (the circumferential direction of the bearing 2). 2
Is divided into two regions A and B in the circumferential direction with the boundary S interposed therebetween. From the time difference between the output signals of the two AE sensors 5a and 5b, the approximate position of the output source and the presence or absence of movement of the output source are estimated. Since the inside of the bearing 2 has a relatively complicated structure, accurate position locating may not be desired even when a normal position locating algorithm is used. For this reason, two AE sensors 5a and 5b are arranged concentrically around the bearing 2 mainly for the purpose of detecting the movement of the vibration source. Note that the two AE sensors 5a and 5b are not necessarily limited to concentric shapes as long as they are arranged around the bearing 2.

In the case of the two AE sensors 5a and 5b, it is possible to know whether a vibration signal is generated in the region A, the region B or on the boundary S line based on the time difference when the vibration wave is detected. Generally, since the bearing 2 has a concentric three-dimensional structure, it is possible to project three-dimensional information onto a two-dimensional plane for evaluation.

For example, as shown in FIG.
If there is no time difference between a and the signal output of the AE sensor 5b, it is estimated that an abnormality has occurred on the boundary S line. As shown in FIG. 8, when the signal output of the AE sensor 5a is generated first and then the signal output of the AE sensor 5b is generated with a time difference, it is estimated that an abnormality has occurred in the region A. As shown in FIG. 9, first, the signal output of the AE sensor 5a is generated, then the signal output of the AE sensor 5b is generated with a time difference T1, then the signal output of the AE sensor 5a is generated, and then the time difference T2 ( AE sensor 5 with T1 <T2)
When the signal output of b occurs, it is estimated that an abnormality has occurred in the area A and the place of occurrence has moved to the rear side in the rotation direction.

In this way, by estimating the location where an abnormality has occurred to some extent, it is possible to provide useful information for a work plan at the time of maintenance.

As shown in FIG. 10, for example, three AE sensors 5a, 5b, 5c are provided at equal angular intervals, and the bearings 2 are arranged at the boundaries S1, S2, S3 in the circumferential direction, for example, at six positions. It is also possible to divide into areas A, B, C, D, E and F. It is also possible to provide three or more AE sensors 5 and divide them into six or more regions. Thus, AE
The spatial resolution can be improved by increasing the number of sensors 5 and the number of divided areas. Also, A in the height direction
By arranging the E sensor 5, the same evaluation can be extended to three dimensions.

The situation (particle detection function) for evaluating the particle shape of the wear powder detected by the wear powder sensor 6 will be described with reference to FIGS. FIG. 11 illustrates the acicular ratio of the abrasion powder, FIG. 12 illustrates a temporal change of the acicular ratio, and FIG. 13 illustrates a flowchart of abnormality diagnosis based on the particle shape.

In the present embodiment, the particle size of the wear powder detected by the wear powder sensor 6 is evaluated, and the state of the acicular ratio, which is the ratio of the minor axis to the major axis of the wear powder, is evaluated. As shown in FIG. 11, the minor axis W with respect to the major axis L of the abrasion powder 17.
Is derived, and the needle ratio L / W is used for abnormality diagnosis. Since the shape of the abrasion powder 17 is related to the sliding state and the abrasion mechanism, the sign of seizure and abrasive wear can be identified by the magnitude of the needle ratio L / W. FIG.
As shown in FIG. 2, it is possible to derive the needle ratio L / W with the passage of time and determine that the wear is abnormal when the needle ratio L / W exceeds a predetermined value P (for example, 3). it can. In addition, even before the needle ratio L / W reaches the predetermined value P, when the value exceeds the specified value Q (Q <P), a sign of abnormality (sign of seizure) is determined to determine the severity of wear. Can be diagnosed.

That is, as shown in FIG.
Is measured, it is determined in step S11 whether or not the particle size is equal to or smaller than a specified value (whether or not it is small). If it is determined in step S11 that the particle size is smaller than the specified value, it is determined that mild wear is present. If it is determined in step S11 that the particle size exceeds the specified value, it is determined in step S12 whether the needle ratio L / W is equal to or greater than a predetermined value P. In step S12, the needle ratio L / W
Is greater than or equal to the predetermined value P, the needle ratio L / W
Is extremely large, it is determined that the abrasive wear.
If it is determined in step S12 that the needle ratio L / W is less than the predetermined value P, it is determined that the wear is severe because the particle size is large but the needle ratio is small. In a state of severe wear, it is determined whether or not the needle ratio L / W is equal to or more than a specified value Q in a step S13. Means that the sliding state has deteriorated, and is judged to be a sign of seizure.

That is, when the particle size of the wear powder is less than a specified value, mild wear occurs. When the particle size of the wear powder exceeds the specified value and the acicular ratio L / W of the wear powder is equal to or more than a predetermined value P, it is abrasive. When the particle size of the wear powder exceeds the specified value but the needle ratio L / W of the wear powder does not exceed the predetermined value P, severe wear occurs, and the needle ratio L / W increases during severe wear ( When the needle ratio L / W is equal to or more than the specified value Q), it is a sign of seizure. In general, the needle-like ratio L / W significantly increases during abrasive wear. Therefore, first, mild wear is determined based on the particle size of wear powder, and abrasive wear is determined based on the needle-like ratio L / W. Then, during severe wear in which the particle size of the wear powder is large, the severity of wear is diagnosed by the magnitude of the needle ratio L / W.

Therefore, by using the wear powder sensor 6 capable of simultaneously measuring the particle diameter and the particle shape of the wear powder 17, the particle size distribution can be measured online, and the wear powder 17 can be measured.
It is possible to improve the accuracy of diagnosis and the immediacy of diagnosis based on the needle ratio.

Referring to FIGS. 14 and 15, a situation in which the sliding state is diagnosed in consideration of the history of output signals in a time series will be described. FIG. 14 shows a block configuration of the time-series diagnosis, and FIG. 15 shows the situation of the output signal.

The instantaneous value 31 and the instantaneous value diagnostic result 3 of the diagnostic parameter based on the output of the AE sensor 5 and the wear powder sensor 6
2 (diagnosis history) is stored as time-series data 33 (the time-series data storage unit 15 in FIG. 2), and a time-series diagnosis unit 34 (second in FIG. 2) that performs diagnosis based on the stored time-series data 33.
A diagnostic unit 16) is provided. Thus, by accumulating the time-series data 33 for a predetermined time and using the variation pattern for diagnosis, it is possible to predict the value of the diagnostic parameter and determine the cause of the variation even if the instantaneous value 31 varies. And make reliable diagnosis.

That is, as shown in FIG. 15 (a), when the level of the signal of interest gradually rises (gradually increases), the signal level rises in the future by considering its history and the threshold value increases. Is expected to be exceeded, and it is possible to give a notice of the occurrence of an abnormality at an early stage before the threshold is exceeded. Further, as shown in FIG. 15 (b), when a state in which an abnormal signal level is detected only for a short time continues for a long period of time (unsteady state), a sudden abnormality is continuously generated. It can be diagnosed that the moving state is in an unstable state.
Further, as shown in FIG. 15 (c), if a signal level exceeding the threshold value is temporarily detected and normalizes immediately (burst), the signal level abnormality is determined as a temporary phenomenon, and the abnormality is determined. Diagnosis can be suppressed.

In the abnormality diagnosis based on the instantaneous value, an abnormality may frequently occur due to various factors in spite of the fact that there is no problem in actual machine operation, which is a practical problem. For this reason, as described above, deriving a fluctuation pattern based on time-series data and diagnosing an abnormality according to the fluctuation pattern are effective for machine state diagnosis and remaining life evaluation. In particular, when the bearing 2 is a rolling bearing, a design based on a finite life is usually made, and it is effective to diagnose an abnormality according to a fluctuation pattern.

Another embodiment of the present invention will be described with reference to FIGS. FIG. 16 shows a schematic configuration of a rotary shaft support unit provided with an abnormality diagnosis device according to another embodiment of the present invention, and FIG. 17 shows a graph showing a result of confirming a propagation signal in oil. The same members as those shown in FIG. 1 are denoted by the same reference numerals, and duplicate description is omitted.

As shown in FIG. 16, when the rolling element (sliding portion) of the bearing 2 is in contact with the oil bath 3, the ultrasonic vibration sensor (AE sensor) 19 which has been subjected to the oil-proofing process is used. And into the adjacent oil bath 3. The AE sensor 19 detects the vibration propagating the lubricating oil in the oil bath 3. Other configurations are the same as those in FIG.

Normally, when the AE sensor is mounted on the casing of the bearing 2 or the like, silicon grease or the like is applied to reduce signal attenuation due to a gap between the contact surfaces. Also,
When attaching to the casing etc. of the bearing 2 with existing equipment,
It requires significant remodeling and makes it difficult to install additional AE sensors. In contrast, in the present embodiment, the AE sensor 19
Is put in the oil bath 3 so that the AE sensor 19
The space between the bearing and the bearing 2 is filled with oil, and there is no need to apply silicon grease or the like. In addition, since the oil bath 3 is provided with a refueling port and an opening for sampling, the existing device can be remodeled by introducing the AE sensor 19 subjected to the oil-proofing process from the refueling port and the opening. The AE sensor 19 can be installed without any
9 becomes very easy to install.

Incidentally, even when the AE sensor 19 is put into the oil bath 3 and installed, as shown in FIG. 5 to FIG.
It is also possible to estimate the location where the abnormality has occurred to some extent by dividing this area.

It is generally known that liquids transmit sound waves relatively well. FIG. 17 shows a graph comparing the signal levels of an ultrasonic signal propagating in a solid (indicated by ○ in the figure) and an ultrasonic signal propagating in oil (indicated by ● in the figure). The horizontal axis represents the load N. Formally, an increase in the load corresponds to a severer sliding state of the bearing. For both the ultrasonic signal propagating in the solid and the ultrasonic signal propagating in the oil, the signal level that increases with increasing load is compared as a ratio to the initial voltage value. When the two ultrasonic signals are compared, when the load applied to the bearing increases, an equivalent increase in the signal level can be confirmed in each case. For this reason, there is no problem when applied to vibration measurement using an ultrasonic signal propagating in oil instead of an ultrasonic signal propagating through a solid.

[0050]

The abnormality diagnosis apparatus according to the present invention comprises at least one or more vibration detecting means for detecting a state of vibration of a supporting portion for supporting a movable portion, and at least one vibration detecting means for detecting a state of wear powder on the supporting portion. Since the above-mentioned wear powder detection means and the abnormality diagnosis means for diagnosing an abnormality based on the detection information of the vibration detection means and the wear powder detection means, the state of the vibration of the support portion, the state of the wear powder and It is possible to diagnose the abnormality of the supporting portion by judging the mixing state of the wear powder. As a result, it is possible to provide an abnormality diagnosis device capable of performing highly reliable abnormality diagnosis regardless of the experience of the operator.

Further, the abnormality diagnosis apparatus according to the present invention has at least one device for detecting a state of vibration of a bearing portion supporting a rotating shaft.
At least one or more pieces of vibration detection means for detecting the state of wear powder at the bearing portion, and abnormality diagnosis means for diagnosing an abnormality based on the detection information of the vibration detection means and wear powder detection means. Therefore, the abnormality diagnosis means can determine the vibration state of the bearing portion, the state of the wear powder, and the mixed state of the wear powder, and diagnose the abnormality of the bearing portion. As a result, it is possible to provide an abnormality diagnosis device capable of performing highly reliable abnormality diagnosis regardless of the experience of the operator.

The abnormality diagnosis means has a vibration generation detecting function for detecting sudden vibration generation, intermittent vibration generation and continuous vibration generation based on information from the vibration detection means, and a detection means based on the detection information from the wear powder detection means. It has a particle detection function to detect the number, size and shape of particles of wear powder, and a function to detect the presence of foreign matter by the information of vibration detection means and the detection information of wear powder detection means. An abnormality diagnosis can be performed based on the state of the element or the damage, and the foreign matter due to the damage can be distinguished from the foreign matter due to the external cause.

The abnormality diagnosis means includes a storage function for storing the diagnosis results as time-series data, and a variation pattern is derived based on the time-series data stored in the storage function to diagnose an abnormality according to the variation pattern. Function to predict the value of a diagnostic parameter,
Even if there is a variation in the instantaneous value, a reliable diagnosis can be performed by determining the cause of the variation.

The bearing is immersed in the lubricating oil reservoir, the vibration detecting means is disposed in the lubricating oil in the lubricating oil reservoir, and the abnormality diagnosing means has a function of detecting vibration propagating the lubricating oil to diagnose an abnormality. Since it is provided, there is no need to interpose a fluid that reduces signal attenuation in the installation of the vibration detection means,
Further, the vibration detecting means can be easily installed in the lubricating oil reservoir from an opening or the like without modifying the existing device, and the additional installation of the vibration detecting means becomes very easy.

Further, a plurality of vibration detecting means are provided in the circumferential direction of the rotating shaft, and the abnormality diagnosing means divides the rotating shaft into a plurality of areas in the circumferential direction, and synthesizes output states of the plurality of vibration detecting means. Since the function for specifying the abnormality occurrence area is provided, it is possible to estimate the abnormality occurrence part to some extent, and it is possible to provide useful information to a work plan at the time of maintenance.

Further, the vibration generation detecting function samples the situation of the vibration from the vibration detecting means at a low frequency and at a high frequency, thereby preventing sudden vibration generation, intermittent vibration generation and continuous vibration generation. Since the detection is performed, it is possible to diagnose abnormalities corresponding to various phenomena.

Further, the particle detecting function of the abnormality diagnosis means evaluates the particle shape based on the particle diameter of the wear powder and the acicular ratio which is the ratio of the minor axis to the major axis of the wear powder to diagnose the state of wear. As a result, the particle size distribution can be measured online, and the accuracy of diagnosis and the immediateness of diagnosis based on the acicular ratio of abrasion powder can be improved.

[Brief description of the drawings]

FIG. 1 is a schematic configuration diagram of a rotating shaft support provided with an abnormality diagnosis device according to an embodiment of the present invention.

FIG. 2 is a block diagram of an abnormality diagnosis unit.

FIG. 3 is a block diagram of a vibration generation detection function.

FIG. 4 is a processing flowchart of a vibration signal.

FIG. 5 is a graph showing a change over time in a state of occurrence of vibration.

FIG. 6 is an explanatory diagram of an arrangement state of an AE sensor 5;

FIG. 7 is an explanatory diagram of an output state of the AE sensor 5.

FIG. 8 is an explanatory diagram of an output state of the AE sensor 5.

FIG. 9 is an explanatory diagram of an output state of the AE sensor 5;

FIG. 10 is an explanatory diagram illustrating another example of an arrangement state of the AE sensor.

FIG. 11 is an explanatory diagram of a needle ratio of wear powder.

FIG. 12 is a graph showing the change with time of the needle ratio.

FIG. 13 is a flowchart of abnormality diagnosis based on a particle shape.

FIG. 14 is a block diagram of a time series diagnosis.

FIG. 15 is a diagram illustrating the situation of an output signal.

FIG. 16 is a schematic configuration diagram of a rotating shaft support provided with an abnormality diagnosis device according to another embodiment of the present invention.

FIG. 17 is a graph showing a result of confirming a propagation signal in oil.

[Explanation of symbols]

 DESCRIPTION OF SYMBOLS 1 Rotary shaft 2 Bearing 3 Oil bath 4 Lubrication line 5 Ultrasonic vibration sensor (AE sensor) 6 Wear powder sensor 7 Abnormality diagnosis means 8, 11 Amplifier 9, 12 AD converter 10 Vibration processing unit 13 Particle processing unit 14 First diagnosis Unit 15 Time-series data storage unit 16 Second diagnostic unit 17 Wear powder 19 Ultrasonic vibration sensor (AE sensor) subjected to oil-proof processing 21 Low-frequency analysis device 22 High-frequency analysis device 23 Frequency analysis processing unit 24 Signal shape evaluation signal processing unit

 ──────────────────────────────────────────────────続 き Continuing from the front page (72) Inventor Masaya Kono 5-717-1 Fukahori-cho, Nagasaki-shi, Nagasaki Prefecture, Nagasaki Research Laboratory, Sanishi Heavy Industries Co., Ltd. F-term (reference) at Shimonoseki Shipyard, Mitsubishi Heavy Industries, Ltd. 3J011 EA02 EA05 5H223 AA02 EE28

Claims (8)

[Claims] 1. At least one or more vibration detecting means for detecting a state of vibration of a support part supporting a movable part, at least one or more wear powder detecting means for detecting a state of wear powder at a support part, An abnormality diagnosis device comprising: abnormality diagnosis means for diagnosing an abnormality based on detection information of the vibration detection means and the wear powder detection means. 2. At least one or more vibration detecting means for detecting a state of vibration of a bearing portion supporting the rotating shaft, at least one or more wear powder detecting means for detecting a state of wear powder at the bearing portion, An abnormality diagnosis device comprising: an abnormality diagnosis unit that diagnoses an abnormality based on detection information of a vibration detection unit and a wear powder detection unit. 3. The abnormality diagnosis means according to claim 1, wherein the abnormality diagnosis means has a vibration generation detection function for detecting sudden vibration generation, intermittent vibration generation, and continuous vibration generation based on information of the vibration detection means. A particle detection function for detecting the number, size and shape of the particles of the wear powder based on the detection information of the wear powder detection means, and a function of detecting the state of foreign matter inclusion based on the information of the vibration detection means and the detection information of the wear powder detection means. An abnormality diagnosis device, comprising: 4. The abnormality diagnosing means according to claim 1, wherein the abnormality diagnosing means includes a storage function for storing the diagnosis result as time-series data, and a variation pattern derived based on the time-series data stored in the storage function. And a function of diagnosing an abnormality according to a fluctuation pattern. 5. The lubricating oil reservoir according to claim 2, wherein the bearing is immersed in the lubricating oil reservoir, the vibration detecting means is disposed in the lubricating oil in the lubricating oil reservoir, and the abnormality diagnosing means detects vibration propagating the lubricating oil. An abnormality diagnosis device having a function of diagnosing an abnormality. 6. The vibration detecting means according to claim 2, wherein a plurality of vibration detecting means are provided in a circumferential direction of the rotating shaft, and the abnormality diagnosing means comprises dividing the rotating shaft into a plurality of areas in the circumferential direction, and a plurality of vibration detecting means. An abnormality diagnosis device provided with a function of synthesizing the output states of the above and specifying an abnormality occurrence area. 7. The vibration generation detection function according to claim 3, wherein the vibration state from the vibration detection means is sampled at a low frequency and at a high frequency to generate sudden vibrations and intermittent vibrations. An abnormality diagnostic device that detects continuous vibration generation. 8. A particle detecting function according to claim 3, wherein the particle detecting function of the abnormality diagnosing means evaluates a particle shape based on a particle size of the wear powder and a needle ratio which is a ratio of a minor axis to a major axis of the wear powder. An abnormality diagnosis device for diagnosing a situation.