SG188710A1 - Equipment and method for abnormality diagnosis of elevator - Google Patents
Equipment and method for abnormality diagnosis of elevator Download PDFInfo
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- SG188710A1 SG188710A1 SG2012050514A SG2012050514A SG188710A1 SG 188710 A1 SG188710 A1 SG 188710A1 SG 2012050514 A SG2012050514 A SG 2012050514A SG 2012050514 A SG2012050514 A SG 2012050514A SG 188710 A1 SG188710 A1 SG 188710A1
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- 230000005856 abnormality Effects 0.000 title claims abstract description 68
- 238000003745 diagnosis Methods 0.000 title claims abstract description 37
- 238000000034 method Methods 0.000 title claims abstract description 13
- 230000002159 abnormal effect Effects 0.000 claims abstract description 46
- 230000007613 environmental effect Effects 0.000 abstract description 5
- 238000007781 pre-processing Methods 0.000 abstract 2
- 238000010586 diagram Methods 0.000 description 10
- 238000005516 engineering process Methods 0.000 description 8
- 230000006870 function Effects 0.000 description 4
- 238000004458 analytical method Methods 0.000 description 2
- 238000012544 monitoring process Methods 0.000 description 2
- 238000007619 statistical method Methods 0.000 description 2
- 241000252067 Megalops atlanticus Species 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
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Abstract
EQUIPMENT AND METHOD FOR ABNORMALITY DIAGNOSIS OF ELEVATOR5 At least two sound collecting units are placedoutside or inside an elevator car at intervals (base length). A sound source pbsition is calculated according to, for example, the stereo principle. Preprocessing of abnormality diagnosis in which the10 sound source position is judged to be in the vicinity of a unit of the elevator is carried out, after which abnormality diagnosis is carried out through a comparison with a previous normal sound in the vicinity of the unit of the elevator that has been judged to be15 the sound source. If an abnormality is diagnosed to be present, an alarm is generated. Through preprocessing, it is possible to prevent various environmental sounds not arising from the elevator from being mistakenly detected as an abnormal sound of the elevator.20Figure 1
Description
EQUIPMENT AND METHOD FCR ABNORMALITY DIAGNOSIS OF
ELEVATOR
The present invention relates to abnormality diagnosis equipment that detects an abnormality in an elevator system and to a method of diagnosing abnormalities in the elevator system.
Elevators are widely used in buildings, personal homes, and other places. Usually, places where elevators are installed and a person who manages elevators, that is, a monitoring center or the like, are separated from each other. Although elevators are periodically inspected to see whether an abnormality has occurred, they should alse be monitecred during normal operation because the elevators are always used by users. If there is any abnormality, it is desirable : to notify the monitoring center as early as possible even before periodic inspection.
In view of the above situation, various types of elevator abnormality diagnosis equipment have been proposed to find elevator abnormalities during elevator operation. They include equipment that detects sounds.
If an elevator generates an abnormal sound, it often indicates that the elevator has an abnormality or its sign. When an abnormal sound is detected, action can be taken for an elevator abnormality and the like at an early stage.
PRIOR TECHNICAL DOCUMENT
PATENT DOCUMENT
PATENT DOCUMENT 1: Japanese Laid-open Patent
Publication No. 2010-132441
PATENT BDCCUMENT 2: Japanese Laid-open Patent
Publication No. 2009%-274805
PATENT DOCUMENT 3: Japanese Laid-open Patent
Publication No. 2009-162413
PATENT DOCUMENT 4: Japanese Laid-open Patent
Publication No. 2001-278562
With a method of finding an elevator abnormality by detecting an abnormal sound generated from an elevator, incorrect detection may occur. For example, if a wide variety of sounds are generated around the elevator, the collected sound may not be an abnormal sound from the elevator. Alternatively, environmental sounds such as sounds from vehicles and voices in conversation of persons may be mistakenly detected as abnormal sounds from the elevator, depending on the place where the elevator 1s installed.
With the conventional technology described in
PATENT DOCUMENT 1, a sliding sound between the guide rall of an elevator and its guided member is collected and an abnormality is detected by comparing the collected sound with the pitch and loudness of a predetermined sound. However, since targets for which to detect abnormal sounds are limited to the guide rail and only one sound collecting means is used, this technology cannot identify the position of the sound source.
The conventional technology described in PATENT
DOCUMENT 2 uses sound collecting microphones attached to the traction machine of the elevator and to individual floors to collect abnormal sounds and detect an abnormality according to the characteristics of the collected sounds. This conventional technology is problematic in that costs are increased because a sound collecting microphone has to be attached to each floor.
Another problem is that since a sound collecting microphone is not attached to the elevator car itself, it is difficult to detect an abnormal scund from the elevator car during its movement.
With the conventional technology described in
PATENT DOCUMENT 3, a microphone mounted on a vehicle collects a gunshot, the collected gunshot is measured, and its sound source is identified according to the principle of triangulation. However, if there are a plurality of sound sources, their positions cannot be identified. Another problem with this conventional technology is that a distance measurement sensor or map information is needed separately to locate a sound source position.
With the conventional technology described in
PATENT DOCUMENT 4, an abnormal sound is collected with sound collecting microphones attached to the inside and outside of the elevator car and an abnormality is detected by comparing the collected abnormal scund with a predetermined reference value. This conventional technology is problematic in that since sound collecting microphones are attached to the inside and outside of the elevator car, the position of the sound source cannot be identified. Another problem is that it is difficult to distinguish environmental sounds at the elevator hall from sounds from the eievator itself.
Accordingly, an object of the present invention is to diagnose elevator abnormalities by distinguishing
—- F - between noise from other than the elevator and abnormal sounds from the elevator.
To solve the problems described above, in a preferred embodiment of the present invention, a difference between sounds collected by at least two sound collecting means {sound collecting units) attached to the inside or outside of an elevator car is used to calculate the position of a sound source according to, for example, the stereo principle, the presence or absence of an abnormality at the position of the sound source is diagnosed, and if an abnormality is detected, an alarm is output.
In a specific embodiment of the present invention, a microphone in an interphone provided in the elevator car 1s used as one of the sound collecting means.
According to the preferred embodiment of the present invention, it is possible to judge whether the sound source position 1s in the vicinity of the elevator even if the elevator is stopping or moving or the elevator door is open. Furthermore, since the sound source position is judged only from the collected sounds, another sensor is not required; at least two sound collecting means are sufficient. This enables the equipment to be installed economically.
Other objects and features of the present invention will be clarified in embodiments described below.
FIG. 1 is a block diagram that schematically illustrates the structure of elevator abnormality diagnosis equipment in a first embodiment of the present invention.
FIG. 2 is a flowchart of processing executed by the elevator abnormality diagnosis equipment in the first embodiment.
FIG. 3 illustrates an example in which two sound collecting means (sound collecting units) are attached to the inside of an elevator car.
FIG. 4 is a block diagram illustrating an example of a sound source position calculating means.
FIG. 5 is a block diagram illustrating an example of an abnormal sound diagnosing means.
FIG. 6 is a block diagram that schematically illustrates the structure of elevator abnormality diagnosis equipment in a second embodiment of the present invention.
FIG. 7 illustrates an example in which two sound collecting means (sound collecting units) are attached to the outside of an elevator car.
FIG. 8 is an overall block diagram that schematically illustrates the structure of elevator abnormality diagnosis eguipment in a third embodiment of the present invention.
Embodiments of the present invention will be described with reference to the drawings.
A first embodiment of the present invention will be described first. {Embodiment 1}
FIG. 1 1s a block diagram that schematically illustrates the structure cf elevator abnormality diagnosis equipment in the first embodiment of the present invention. An elevator 100 having an abnormality diagnosis function includes an elevator car unit B10 and an abnormal sound diagnosing unit B20. The elevator 100 receives at least one sound S10 and outputs an alarm S30.
The elevator car unit B10 includes at least two intra-car sound collecting units 10 and 20. The elevator car unit B10 receives and measures the sound
S10, converts it to a piece of acoustic data (an acoustic signal) S520, and outputs it. Sounds include sounds generated while the elevator is moving, sounds generated while devices of the elevator are operating, sounds from vehicles, and voices in conversations of persons.
The abnormal sound diagnosing unit B20 includes a sound source position calculating means 30, an abnormal sound diagnosing means 40, and an alarm generating means 50. The abnormal sound diagnosing unit B20 receives the acoustic data S20 and outputs the alarm
S30.
The sound source position calculating means 30 calculates the sound source position from the sound features of the received acoustic data S20. The sound features include the loudness {intensity}, pitch, frequency, and other parameters of the sound. A possible example of a means for calculating the sound source position is the sterec principle. The sound source position calculating means 30 judges whether the sound source 1s in the vicinity of the elevator. If the sound source is in the vicinity of the elevator, the sound source position calculating means 30 outputs the acoustic data S20 the abnormal sound diagnosing means 40. If the sound source is not in the vicinity of the elevator, the sound source position calculating means 30 terminates the processing and calculates the position of a sound source for the next acoustic data
S20.
The abnormal sound diagnosing means 40 receives the acoustic data S20 and judges whether there is an abnormality. If there is an abnormality, the abnormal sound diagnosing means 40 outputs a trigger for an alarm. Possible means for judging whether there 1s an abnormality include a method of comparing the acoustic data $20 with a predetermined threshold and a method of comparing the received acoustic data S20 with previous acoustic data S20 that has been stored in advance. For example, the abnormal sound diagnosing means 40 compares the acoustic data S20 with previous accoustic data (normal sound, for example) corresponding to the sound source position calculated by the sound scurce position calculating means 30 placed behind the abnormal sound diagnosing means 40, and judges whether the relevant place (component or unit} has an abnormality according to the comparison result.
The alarm generating means 50 receives the trigger for an alarm and judges whether to output an alarm. If the alarm generating means 50 judges that an alarm needs to be output, it outputs an alarm $30. Two methods can be considered to output the alarm S30. In one method, upon receipt of the trigger for an alarm, an alarm is output immediately. In the other method, the number of received triggers for alarms is counted, and only when that number becomes equal to or larger than a predetermined threshold within a predetermined time, the frequency at which triggers for alarms have been generated is considered to be equal to or larger than a predetermined frequency and an alarm S30 is output.
FIG. 2 1s a flowchart of processing executed by the elevator abnormality diagnosis equipment in the first embodiment of the present invention.
First, it is assumed that noise has been generated while the elevator was in normal operation. The two intra-car sound collecting units 10 and 20 collect the noise in sound collection steps Fl and F2 and create acoustic data in acoustic data acquisition steps F3 and
F4. In step F5, a difference in intensity between acoustic signals of the two acoustic data items and a difference in time between the signals are calculated, and a sound source position is calculated from the difference in intensity between the acoustic signals of the two acoustic data items and the difference in time between the signals. In step F6, whether the sound source is in the vicinity of the elevator is judged according toe the calculated sound source position. If the sound source is judged to be not in the vicinity of the elevator, the sequence proceeds to step F17 and the diagnosis is canceled. If the sound source is judged to
- 11 =- be in the vicinity of the elevator, predominant acoustic data is first determined according to the intensities of the acoustic signals in acoustic data selection step F7. The difference between the two acoustic data items is compared with a predetermined threshold. If the difference is greater than or equal to the threshold, it is judged that the selected acoustic data was apparently predominant.
Next, frequency analysis processing, such as a Fast
Fecurier transform (FFT), is carried cut on the two acoustic data items to covert them to frequency data items in steps F8 and F9. A feature quantity is calculated from each frequency data item by using a statistical method in steps F10 and Fl1l. Examples of the statistical method include main component analysis and clustering. In steps Fl12Z2 and F13, the calculated feature quantities are compared with learning data 201 and 202 to calculate differences. Examples of the learning data 201 and 202 are normal sounds. In steps
F14 and F15, if the differences are greater than or equal to the threshold, the acoustic data is judged to be abnormal, and if they are smaller than the threshold, it is judged to be normal. If one of the two acoustic data items is judged to be abnormal, an alarm is generated in step F16. In cases other than that, the
- 172 = sequence proceeds to step F17 and diagnosis is terminated.
If the predominance between the two acoustic data items is noticeable, whether the acoustic data items are abnormal is preferably judged according to the diagnosis result for the predominant acoustic data.
Specifically, if the predominant acoustic data is judged to be abnormal, it may be judged that there is an abnormality and an alarm may be generated in step
Fle.
If the predominant acoustic data is judged to be normal, it may be judged that there is no abnormality and the diagnosis may be terminated in step F17.
FIG. 3 illustrates an example in which the two sound collecting units 10 and 20 are attached to the inside of an elevator car. In example (A), the two sound collecting units 10 and 20 are attached to the right and left of the upper end on the door surface. In example (B), the two sound collecting units 10 and 20 are attached to the right and left of the upper end of a surface opposite to the door. In example (C), the two sound collecting units 10 and 20 are attached to diagonal corners of the elevator car. In example (D), the two sound collecting units 10 and 20 are attached te the upper end and lower end in the elevator car. In example (E), one sound ccllecting unit is attached to a corner of the top plate at which a monitoring camera or the like is attached, and the microphone of the interphone is used as the other sound collecting unit.
In example (A), since the two sound collecting units 10 and 20 are attached near the top plate, on which many parts of the elevator are attached, and the door surface, sounds can be collected from many parts.
Particularly, since many pieces of door-related equipment are concentrated on the top plate, sounds can be collected from the door motor, the driven roller, the door rail, and the like.
In example (B), since the two sound collecting units 10 and 20 are attached to the place where the monitoring camera or the like is attached, sound collecting means can be easily added. Since the place is opposite to the door, sounds can be collected that are generated from the door when the door state is abnormal, for example, when the door rattles or a person or a thing is caught by the door.
In example (C), since the two sound collecting units 10 and 20 are attached to diagonal corners of the elevator car, the distance between them (base length) is maximized. Accordingly, sounds generated in the elevator car can be evenly collected.
In example (D}, since the two scund collecting units 10 and 20 are attached to the upper end and lower end in the elevator car, sounds can be easily collected from parts on the top plate and below the floor, particularly, the sill groove and door shoe.
In example (E), since the originally attached interphone is used, only one sound collecting unit has to be attached. Furthermore, as in example (C), sounds generated in the elevator car can be evenly collected.
FIG. 4 is a block diagram illustrating an example of the sound source position calculating means 30. It includes a sound source position calculating unit B30 and a sound source position judging unit B40. The sound source position calculating means 30 receives the acoustic data S520 and outputs the acoustic data S20 only when it is judged that the acoustic data S20 is : involved in a scund generated in the vicinity of the elevator.
The sound source position calculating unit B30 receives the acoustic data $820, calculates the sound source position of the acoustic data S20 from the features of the received acoustic data S20, and outputs a sound source position S40. Specifically, the sound source position calculating unit B30 uses the stereo principle as the calculation method to calculate the
—- 15 —~ sound source position S40 from the difference between the acoustic data S20 output by the two sound collecting units 10 and 20 and from the distance between the two sound collecting units 10 and 20 {base length).
The sound source position judging unit B40 receives the sound source position S40 and judges whether the sound source position S540 is involved in a sound generated in the vicinity of the elevator. The sound source position judging unit B40 outputs the acoustic data S520 only when the sound source position £40 is judged to be involved in a sound generated in the vicinity of the elevator. In this judgment, the sound source position $40 is compared with a threshold that is defined in advance to be a sound in the vicinity of the elevator, and if the sound source position 840 is lower than or equal to the threshold, the acoustic data 520 is judged to be involved in a sound in the vicinity of the elevator.
FIG. 5 1s a block diagram illustrating an example of the abnermal sound diagnosing means 40. The abnormal sound diagnosing means 40 includes a previous normal sound database 410 and an abnormal scund judging unit
B50. The abnormal sound diagnosing means 40 receives the $20 and outputs a trigger $50 for an alarm only when an elevator abnormality has been detected.
The previous normal sound database 410 prestores a previous normal scund S60 of the elevator.
The abnormal sound judging unit B50 receives the acoustic data $20 and previous normal sound $60, compares them, and judges whether the elevator has an abnormality. Only when the elevator is judged to be abnormal, the abnormal sound judging unit B50 outputs the trigger for an alarm S50. A possible example of a judgment method is to calculate similarity between the accoustic data $520 and the previous normal sound S560.
Another possible example is to learn the previous normal sound S60 and diagnose the acoustic data $20.
The previous normal sound database 410 may prestore the previous normal sound S60 for each sound source position identifiable by the sound source position calculating means 30. That is the prestored normal sound may include a plurality of normal sounds corresponding to a plurality of sound source positions respectively that can be identified by a combination of the at least two sound collecting units. The abnormal sound diagnosing means 40 may receive not only the acoustic data $20 but also the sound source position
S40 from the sound source position calculating means 30 and may judge whether there is an abnormal sound by
- 17 = using the previous normal sound S60 corresponding to the sound source position S40.
Next, a second embodiment of the present invention will be described. {Embodiment 2}
FIG. 6 is a block diagram that schematically illustrates the structure of elevator abnormality diagnosis equipment in the second embodiment of the present invention. An elevator 200 having an abnormality diagnosis function includes an elevator car unit B10 and an abnormal sound diagnosing unit B20. The elevator 200 receives at least one sound S10 and outputs an alarm S30. The elevator car unit B10 includes at least two exo-car sound collecting units 110 and 120. The elevator car unit Bl0 receives the sound S10 and outputs the acoustic data $20. The abnormal sound diagnosing unit B20 and alarm S30 are the same as in the first embodiment.
FIG. 7 illustrates an example in which the two sound collecting units 110 and 120 are attached to the outside of an elevator car. In example (A), the two sound collecting units 110 and 120 are attached to the upper end and lower end on the door surface. In example {(B}, the two sound collecting units 110 and 120 are attached to the top plate on the doer surface side and on the opposite side. In example (C), the two sound collecting units 110 and 120 are attached on the top plate and below the floor.
In example (A), since the two sound collecting units 110 and 120 are attached near the top plate, on which many parts of the elevator are attached, and the door surface, sounds can be collected from many parts.
Particularly, since many pieces of door-related egulipment are concentrated on the top plate, sounds can iQ be collected from the door motor, the driven roller, the door rail, and the like. Sounds from the sill groove and door shoe can be expected to be easily collected below the door.
In example (B) as well, since the two sound collecting units 110 and 120 are attached near the top plate, on which many parts of the elevator are attached, and the door surface, sounds can be collected from many parts. In addition, a unit that is generating an abnormal sound can be identified. Particularly, sounds can be collected from the door moter, the driven roller, the door rail, and the like.
In example (C), since the two sound collecting units 110 and 120 are attached near the top plate, on which many parts of the elevator are attached, and below the floor, the elevator car being interpose between the top plate and the floor, sounds to be diagnosed and environmental sounds can be easily separated at a time of sound collection. Particularly, since many pieces of door-related equipment are concentrated on the top plate, sounds can be collected from the door motor, the driven roller, the door rail, and the like as in example (A). Sounds from the sill groove and door shoe can be expected to be easily collected below the elevator car.
Next, a third embodiment of the present invention will be described. {Embodiment 3}
FIG. 8 is an overall block diagram that schematically illustrates the structure of elevator abnormality diagnosis equipment in the third embodiment of the present invention. An elevator 300 having an abnormality diagnosis function includes an elevator car
E10, an elevator door E20, a door motor E30, at least two intra-car sound collecting units 10A and 10B, and an abnormal sound diagnosing unit B20. The elevator 300 receives a sound and outputs an alarm S30 to a monitor
E40.
Particularly, in this embodiment, sounds from the elevator door E20 and door-related equipment are targets to be detected. The elevator car E10, which is eguivalent to the elevator car unit B10 in the first embodiment, includes the two intra-car sound collecting units 10A and 10B. The elevator car E10 receives sounds generated from the elevator door E20 and door motor E30 and outputs acoustic data S20.
The intra-car sound collecting unit 10A, which is a non~directional microphone, is attached above the elevator surface, and the intra-car sound collecting unit 10B, which is alsc a non-directional microphone, is attached to the same position as the interphone. The intra-car sound collecting unit 10A attached above the door surface can more easily collect sounds generated when the elevator door E20 is opened and closed as compared with the intra-car sound collecting unit 10B attached to the same position as the interphone, because the intra-car sound collecting unit 10A is closer to the elevator door E20 and door motor E30.
The abnormal sound diagnosing unit B20 and alarm
S30 are the same as in the first embodiment.
The abnormal sound diagnosing unit B20 can have predetermined thresholds for the intra-car sound collecting units 10A and 10B. If the acoustic data $20 from the intra-car sound collecting unit 102A is smaller than its threshold and the acoustic data $20 from the intra-car sound ccllecting unit 10B is larger than its
- 21 = threshold, then the abnormal sound diagnosing unit B20 can judge that the environmental sound is louder than the sound in the vicinity of the elevator and can cancel abnormal sound diagnosis.
The elevator having the abnormality diagnosis function in the present invention can judge whether the collected sound has been generated in the vicinity of the elevator and thereby can recognize an elevator abnormality by detecting a sound.
Claims (10)
1. Elevator abnormality diagnosis equipment that has at least two sound collecting means provided inside or outside an elevator car, an abnormality diagnosing means that diagnoses an abnormality according to acoustic signals collected inside or outside the elevator car, and an alarm that outputs an alarm signal according to an output from the abnormality diagnosing means, the at least two sound collecting means being a combination of at least two sound collecting units placed at intervals inside or outside the elevator car, the abnormality diagnosis equipment comprising: a sound source position calculating means that calculates a sound source position from a difference between acoustic signals collected by the at least two sound collecting units, and an abnormality diagnosing means that judges whether an abnormality is present at the sound source position of the acoustic signals, which has been calculated by the sound source position calculating means, according to the collected acoustic signals.
2. The elevator abnormality diagnosis equipment according to Claim 1, wherein the sound source position calculating means calculates the sound source position from a difference in intensity between the acoustic signals collected by the at least two sound cellecting units and from a difference in time between the acoustic signals collected by the at least two sound collecting units.
3. The elevator abnormality diagnosis equipment according to Claim 1, wherein the sound source position calculating means calculates the sound source position from at least two acoustic signals collected by the at least two sound collecting units placed at intervals, according to a stereo principle.
4. The elevator abnormality diagnosis equipment according to Claim 1, further comprising an abnormal unit identifying means that identifies an abnormal unit according to the sound source position calculated by the sound source position calculating means.
5. The elevator abnormality diagnosis equipment according to Claim 1, further comprising an abnormality diagnosis execution/non-execution judging means that judges whether abnormality diagnosis by the abnormality diagnosing means 1s required, according to the sound source position calculated by the sound source position calculating means.
6. The elevator abnormality diagnosis equipment according to Claim 1, wherein a microphone in an interphone provided in the elevator car is used as one of the at least two sound collecting units.
7. The elevator abnormality diagnosis equipment according to Claim 1, wherein the abnormality diagnosing means diagnoses an abnormality by comparing the acoustic signals collected by the sound collecting units with a prestored normal sound.
8. The elevator abnormality diagnosis equipment according to Claim 7, wherein the prestored normal
. scund includes a plurality of normal sounds corresponding tec a plurality of sound source positions respectively that can be identified by a combination of the at least two sound collecting units.
9. The elevator abnormality diagnosis equipment according to Claim 1, wherein the alarm signal is output when a prescribed number of abnormal diagnoses have been carried out by the abnormality diagnosing means within a prescribed time.
10. An abnormality diagnosis method for an elevator that diagnoses an abnormality according to acoustic signals collected inside or outside an elevator car and outputs an alarm signal, in which at least two sound collecting units placed at intervals inside or outside the elevator car are combined, the method comprising the steps of: calculating a sound source position from the acoustic signals collected by the at least two sound collecting units according to a stereo principle, diagnosing whether an abnormality is present at the sound source position of the acoustic signals, which has been calculated by the step of calculating the sound source position, according to the collected acoustic signals, and outputting the alarm signal when an abnormality is diagnosed to be present at the sound source position.
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP2011201400A JP5513456B2 (en) | 2011-09-15 | 2011-09-15 | Elevator abnormality diagnosis apparatus and method |
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| Publication Number | Publication Date |
|---|---|
| SG188710A1 true SG188710A1 (en) | 2013-04-30 |
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ID=47921344
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| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| SG2012050514A SG188710A1 (en) | 2011-09-15 | 2012-07-09 | Equipment and method for abnormality diagnosis of elevator |
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| Country | Link |
|---|---|
| JP (1) | JP5513456B2 (en) |
| CN (1) | CN102992129A (en) |
| SG (1) | SG188710A1 (en) |
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| JP5334037B2 (en) * | 2008-07-11 | 2013-11-06 | インターナショナル・ビジネス・マシーンズ・コーポレーション | Sound source position detection method and system |
| JP4876136B2 (en) * | 2009-02-17 | 2012-02-15 | 株式会社日立製作所 | Abnormality diagnosis apparatus and abnormality diagnosis method |
| JP5397075B2 (en) * | 2009-08-06 | 2014-01-22 | 三菱電機ビルテクノサービス株式会社 | Elevator abnormal sound detection device |
| JP5452158B2 (en) * | 2009-10-07 | 2014-03-26 | 株式会社日立製作所 | Acoustic monitoring system and sound collection system |
-
2011
- 2011-09-15 JP JP2011201400A patent/JP5513456B2/en active Active
-
2012
- 2012-07-09 SG SG2012050514A patent/SG188710A1/en unknown
- 2012-07-31 CN CN2012102698714A patent/CN102992129A/en active Pending
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP3287405A1 (en) * | 2016-08-22 | 2018-02-28 | Inventio AG | Noise based elevator malfunction detection |
Also Published As
| Publication number | Publication date |
|---|---|
| CN102992129A (en) | 2013-03-27 |
| JP5513456B2 (en) | 2014-06-04 |
| JP2013060295A (en) | 2013-04-04 |
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