CN103508303B - Abnormality diagnostic method, apparatus for diagnosis of abnormality and there is the apparatus of passenger conveyor of apparatus for diagnosis of abnormality - Google Patents
Abnormality diagnostic method, apparatus for diagnosis of abnormality and there is the apparatus of passenger conveyor of apparatus for diagnosis of abnormality Download PDFInfo
- Publication number
- CN103508303B CN103508303B CN201310053558.1A CN201310053558A CN103508303B CN 103508303 B CN103508303 B CN 103508303B CN 201310053558 A CN201310053558 A CN 201310053558A CN 103508303 B CN103508303 B CN 103508303B
- Authority
- CN
- China
- Prior art keywords
- characteristic quantity
- vibration values
- vibration
- study
- diagnosis
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Abstract
A kind of abnormality diagnostic method is provided, apparatus for diagnosis of abnormality and there is the apparatus of passenger conveyor of apparatus for diagnosis of abnormality, when diagnosing the exception of mechanical equipment according to the vibration values collected by the vibration sensor be arranged on mechanical equipment, according to the first study vibration values corresponding to the first running state collected when learning by vibration sensor, vibration values is learnt with correspond to second running state different from the first running state collected when learning by vibration sensor second, calculate difference and the learning value characteristic quantity difference value of each characteristic quantity, according to the first study vibration values corresponding to the first running state collected when diagnosing by vibration sensor, with the second study vibration values corresponding to the second running state collected when diagnosing by vibration sensor, calculate difference and the diagnostic value characteristic quantity difference value of each characteristic quantity, learning value characteristic quantity difference value and diagnostic value characteristic quantity difference value are compared, judge that mechanical equipment is abnormal with or without generation.
Description
Technical field
The present invention relates to and a kind ofly diagnose the abnormality diagnostic method of mechanical unit exception, apparatus for diagnosis of abnormality and there is the apparatus of passenger conveyor of apparatus for diagnosis of abnormality.
Background technology
In order to find the exception of mechanical equipment, such as, in order to find the exception as a kind of escalator in apparatus of passenger conveyor, the apparatus for diagnosis of abnormality (such as patent documentation 1 to patent documentation 3) of various escalator is proposed.When there occurs abnormal vibrations in escalator, probably meaning and there occurs abnormal or abnormal sign, by detecting abnormal vibrations, counter-measure can be taked to the fault etc. of escalator as soon as possible.As the method that diagnosis is abnormal, can list and diagnose abnormal method by sound and detect abnormal method etc. by vibration.
At first technical literature
Patent documentation
Patent documentation 1 Japanese Patent Laid-Open 2009-234747 publication
Patent documentation 2 Japanese Patent Laid-Open 2009-12891 publication
Patent documentation 3 Japanese Patent Laid-Open 2005-67847 publication
When finding the exception of escalator by detection vibration, because the periphery at escalator can produce various vibration, so the generation of error detection likely can be caused, make, when the vibration be measured to is not the abnormal vibrations of escalator, to be judged as that escalator there occurs exception.In addition, when conditioning unit, ventilating fan and power supply fan etc. that the surrounding of the setting place of escalator is such as provided with in building understand other mechanical equipments vibrative, the vibration of the surrounding environment caused by these mechanical equipments and ambient vibration etc. likely can be mixed into take off data, make error detection occurs.
In patent documentation 1, for the handrail of escalator, collect and run operation sound partly and the surrounding's sound with operation spaced-apart, obtain the frequency spectrum of these sound, calculate the degree of deviation according to its difference, and it is abnormal to determine whether generation according to the degree of deviation.But, due to the method mensuration is sound instead of vibration, so the place away from operation part collect simultaneously run sound and around sound, due to collection location with there is place relatively far apart, so sound is probably different from there is surrounding's sound in place around operation part is heard.
In patent documentation 2, the vibration data that produces on step when measuring escalator operation, and itself and vibration data time normal are compared, determine whether thus and exception occurs.; when adopting the method; when causing ambient vibration to there occurs change because of reasons such as Long-Time Service; the ambient vibration comprised in the vibration data measured during diagnosis and normal time vibration data in the ambient vibration that comprises may there is difference, thus error detection may be caused to occur.
In patent documentation 3, detect the take off data that is arranged on acceleration pick-up on multiple steps of escalator and obtain in advance normal time data between difference, obtain the step position of difference more than the value preset as abnormal occurrence positions., the method is the same with the method disclosed in patent documentation 2, when causing ambient vibration to there occurs change because of reasons such as Long-Time Service, error detection may be caused to produce.
Summary of the invention
The object of the present invention is to provide a kind of abnormality diagnostic method and apparatus for diagnosis of abnormality, make when diagnosing the exception of mechanical equipment according to vibration, even if there occurs change compared with ambient vibration when ambient vibration during diagnosis and study, also can reduce the impact of ambient vibration, the generation of error detection can be reduced thus.
In order to solve the problem, in the present invention, such as when diagnosing the exception of described mechanical equipment according to the vibration values collected by the vibration sensor be arranged on mechanical equipment, difference and the learning value characteristic quantity difference value of each characteristic quantity is calculated according to the first study vibration values and the second study vibration values, wherein this first study vibration values corresponds to the first running state collected when learning by described vibration sensor, this the second study vibration values corresponds to second running state different from described first running state collected when learning by described vibration sensor, and, difference and the diagnostic value characteristic quantity difference value of each characteristic quantity is calculated according to the first study vibration values and the second study vibration values, wherein this first study vibration values corresponds to described first running state collected when diagnosing by described vibration sensor, this the second study vibration values corresponds to described second running state collected when diagnosing by described vibration sensor, in addition, described learning value characteristic quantity difference value and described diagnostic value characteristic quantity difference value are compared, judge that described mechanical equipment is abnormal with or without generation.
Invention effect
According to the present invention, when being diagnosed the exception of mechanical equipment by detection vibration, even if ambient vibration when ambient vibration during diagnosis and study is compared there occurs change, also can reduce the impact of ambient vibration, the generation of error detection can be reduced thus.
Accompanying drawing explanation
Fig. 1 is the block diagram of the summary representing apparatus for diagnosis of abnormality of the present invention.
Fig. 2 is the synoptic map of the facilities of the vibration sensor represented on escalator.
Detailed description of the invention
Fig. 1 is the block diagram of the summary representing apparatus for diagnosis of abnormality of the present invention, and Fig. 2 is the synoptic map of the facilities of the vibration sensor represented on escalator.At this, for the one in apparatus of passenger conveyor and escalator 200, the mechanical equipment as abnormity diagnosis object is described.
As shown in Figure 1, apparatus for diagnosis of abnormality 100 has learning value storage area B10, diagnostic value storage area B20, differential comparison part B30 and alarm generating portion 80.Namely the vibration values that namely vibration values inputting study to apparatus for diagnosis of abnormality 100 learns vibration values S10 and diagnosis diagnoses vibration values S20, and the result diagnosed represent there occurs abnormal time, export and represent abnormal alarm signal S30.
Learning value storage area B10 has the study vibration values storage area 10 of running state A and the study vibration values storage area 20 of running state B, and study vibration values S10 inputs to the study vibration values storage area 10 of running state A and the study vibration values storage area 20 of running state B.In the study vibration values storage area 10 of running state A, store the study vibration values S10 corresponding with the running state A of escalator, in the study vibration values storage area 20 of running state B, store the study vibration values S10 corresponding with the running state and running state B that are different from running state A.The study vibration values be stored in the study vibration values storage area 10 of running state A and the study vibration values storage area 20 of running state B is output in learning value characteristic quantity Difference Calculation part 50.
At this, study vibration values S10 is the study vibration values as benchmark obtained from the vibration sensor be arranged on normal escalator, and this study vibration values S10 obtains in advance before diagnosis.Study vibration values S10 in advance from the escalator as diagnosis object itself acquisition of (when such as arranging etc.) being in normal condition, also can obtain from the normal study escalator as the same model beyond the escalator of diagnosis object.
Running state A and running state B is running state different from each other.At this, occasion when running state not only comprises mobile, and occasion when comprising stopping.As long as at least one in the service direction of escalator (rise, decline and stopping etc.), running velocity (at a high speed, speed, low speed and stopping etc. usually) etc. is different.Such as, running state A can be listed rise to run and running state B declines that the occasion, the running state A that run are rising operation at a high speed and rising that running state B is low speed runs occasion and running state A run for rising and running state B be the occasion etc. of basic operation (Background Working).Wherein, basic operation refers to that the power supply of escalator is in on-state but step is in the operation of halted state (step does not move).
Diagnostic value storage area B20 has the diagnosis vibration values storage area 30 of running state A and the diagnosis vibration values storage area 40 of running state B, and diagnosis vibration values S20 is input to the diagnosis vibration values storage area 30 of running state A and the diagnosis vibration values storage area 40 of running state B.In the diagnosis vibration values storage area 30 of running state A, store the diagnosis vibration values S20 corresponding with the running state A of escalator, in the diagnosis vibration values storage area 40 of running state B, store the diagnosis vibration values S20 corresponding with the running state B of escalator.The diagnosis vibration values be stored in the diagnosis vibration values storage area 30 of running state A and the diagnosis vibration values storage area 40 of running state B is output in diagnostic value characteristic quantity Difference Calculation part 60.
At this, running state A when obtaining diagnosis vibration values S20 is set as the running state identical with running state B with the running state A obtained when learning vibration values S10 respectively with running state B.
Differential comparison part B30 has learning value characteristic quantity Difference Calculation part 50, diagnostic value characteristic quantity Difference Calculation part 60 and multilevel iudge part 70, the vibration values of its in the future diagnosis vibration values storage area 40 of the study vibration values storage area 10 of self-operating state A, the study vibration values storage area 20 of running state B, the diagnosis vibration values storage area 30 of running state A and running state B as input, and exports the energizing signal of alarm signal S30 to alarm generating portion 80.
Learning value characteristic quantity Difference Calculation part 50 using running state A during study and the vibration values of running state B as input, calculate the difference of the characteristic quantity of the vibration values of two kinds of running statees, and export the difference value (learning value characteristic quantity difference value) of the characteristic quantity of vibration values when learning to multilevel iudge part 70.By calculating the difference value of the characteristic quantity of two kinds of running statees, the escalator that can remove in the vibration values being simultaneously included in two kinds of running statees arranges the vibration values of the ambient vibration of environment, makes the difference of the characteristic quantity of the vibration values of two kinds of running statees after the residue removal impact of ambient vibration.
As the method for calculating of the difference of the characteristic quantity of the vibration values of two kinds of running statees, can list and calculate integral value (O.A. value respectively, the value that obtains using sqrt after square value adds up to) as the characteristic quantity of running state A and running state B, and obtain the method for the difference of the O.A. value of running state A and running state B.In addition, the frequency component that calculates vibration values respectively can also be listed and as the characteristic quantity of running state A and running state B, and calculate the method for the difference of the characteristic quantity of each frequency component.Wherein, when calculating the difference of characteristic quantity of each frequency component, the frequency band of regulation can be pre-set, and only calculate difference at the frequency band of this regulation, or also can carry out principal component and resolve the frequency band deciding the regulation of carrying out Difference Calculation, and only calculate difference at the frequency band of this regulation.
Diagnostic value characteristic quantity Difference Calculation part 60 using running state A during diagnosis and the vibration values of running state B as input, calculate the difference of the characteristic quantity of the vibration values of two kinds of running statees, and the difference value (diagnostic value characteristic quantity difference value) of the characteristic quantity of vibration values during diagnosis is outputted to multilevel iudge part 70.By calculating the difference value of the characteristic quantity of two kinds of running statees, the escalator that can remove in the vibration values being simultaneously included in two kinds of running statees arranges the vibration values of the ambient vibration of environment.At this, when escalator there occurs abnormal, then can two kinds of running statees after the residue removal impact of ambient vibration vibration values characteristic quantity difference and eliminate ambient vibration impact after the difference of characteristic quantity of abnormal vibrations value of two kinds of running statees.On the other hand, when escalator does not occur abnormal, the difference of the characteristic quantity of the vibration values of two kinds of running statees after the residue removal impact of ambient vibration.In addition, the method for calculating of the difference of the characteristic quantity of two vibration values must be set as the method identical with learning value characteristic quantity Difference Calculation part 50.
The difference value of the characteristic quantity of the running state A when difference value of the characteristic quantity of running state A during each study of multilevel iudge part 70 in the future self study value tag amount Difference Calculation part 50 and diagnostic value characteristic quantity Difference Calculation part 60 and the vibration values of running state B and diagnosis and the vibration values of running state B is as input, comparing to determine whether to the difference value of two characteristic quantities occurs extremely, when being judged as there occurs abnormal, export the energizing signal of alarm signal S30 to alarm generating portion 80.
At this, by the difference of difference value when difference value during calculating study and diagnosis, the difference value of the characteristic quantity of the vibration values of the two kinds of running statees be simultaneously included in two difference values can be removed.When escalator there occurs abnormal, remain the difference of the characteristic quantity of the abnormal vibrations value of two kinds of running statees.When escalator does not occur abnormal, do not produce difference.Determining whether as comparing two difference values the method that exception occurs, the difference of calculating two difference values can be listed, when the value calculated is more than prespecified threshold value, be judged as there occurs abnormal method.
The energizing signal of alarm signal S30 as input, judges whether to need to export alarm signal S30 by alarm generating portion 80, when being judged as needing to export, exports alarm signal S30.The following two kinds method can be listed, the first exports the method for alarm signal S30 immediately after the energizing signal that have input alarm signal S30, it two is count the energizing signal of alarm signal S30 of input, when count value only within the prespecified time reaches more than the threshold value pre-set, just be judged as more than the frequency preset, and export the method for alarm signal S30.
Alarm signal S30 is sent to central monitoring position.In addition, also can be arranged in after outputing alarm signal S30, adopt sound or light etc. to notify to there occurs exception.
Fig. 2 is the synoptic map of the facilities of the vibration sensor represented on escalator.Escalator 200 have actuating device 205, the driving extreme gear 202A driven by actuating device 205, the step chain 204 be wound on driving extreme gear 202A, winding step chain 204 carrying out driven driven extreme gear 202B, connected into by step chain 204 ring-type with carry out loopy moving multiple steps 203, with step 203 synchronously driven handrail 206 and drive the handrail driving roller 207 of handrail 206.
The diagnosis object of apparatus for diagnosis of abnormality 100 can be such as the extreme gear bearing 201, handrail driving roller 207 etc. that are arranged on driving extreme gear 202A, driven extreme gear 202B.Figure 2 illustrates and vibration sensor 300 is set on extreme gear bearing 201, handrail driving roller 207 arranges the example of vibration sensor 301, but the present invention is not limited to this.As vibration sensor 300,301, such as, acceleration pick-up etc. can be adopted.
Apparatus for diagnosis of abnormality 100 is arranged on not shown arbitrary site, under various running state, obtain diagnosis vibration values S20, to carry out abnormity diagnosis from vibration sensor 300, vibration sensor 301.This abnormity diagnosis can regularly carry out, and also can carry out at common run duration.Undertaken by being arranged in common run duration, can be abnormal to central monitoring position circular as soon as possible before periodic inspection.
The diagnosis of apparatus for diagnosis of abnormality 100 also can be applied to as in a kind of electric channel of apparatus of passenger conveyor.Further, the present invention is not limited in apparatus of passenger conveyor, also can be applied in other mechanical equipment.
According to the apparatus for diagnosis of abnormality of the present embodiment, when diagnosing the exception of mechanical equipment according to vibration, respectively when learning and diagnosis time calculate the difference of characteristic quantity of the vibration values of running state A and running state B, so can respectively when learning and diagnosis time remove the impact of ambient vibration, even if the ambient vibration when ambient vibration when learning and diagnosis there occurs change, also can reduce the impact of ambient vibration, the generation of error detection can be reduced thus.
Due to when learning and diagnosis time eliminate the impact of ambient vibration respectively, even if so when learning and diagnosis time use the different mechanical equipments of same model to obtain vibration values, also can diagnose.
In addition, the vibration values of the ambient vibration of the machine position of diagnosis object is comprised due to a vibration sensor can be adopted to measure, so, come with adopting other the vibration sensor be arranged on diverse location compared with the occasion that measurement environment vibrates, can correct diagnosis be carried out.
By the running state of the side in running state A and running state B being set as the basic state run, the abnormal vibrations that only just can produce when mobile more correctly can be detected.
Be illustrated embodiments of the invention above, the structure illustrated in each embodiment above-mentioned is an example only, and the present invention can carry out suitable change in the scope not departing from its technological thought.In addition, the structure illustrated in various embodiments, as long as do not produce contradiction each other, then also can combinationally use.
Nomenclature
10 ... the study vibration values storage area of running state A, 20 ... the study vibration values storage area of running state B, 30 ... the diagnosis vibration values storage area of running state A, 40 ... the diagnosis vibration values storage area of running state B, 50 ... learning value characteristic quantity Difference Calculation part, 60 ... diagnostic value characteristic quantity Difference Calculation part, 70 ... multilevel iudge part, 80 ... alarm generating portion, 100 ... apparatus for diagnosis of abnormality, B10 ... learning value storage area, B20 ... diagnostic value storage area, B30 ... differential comparison part, S10 ... study vibration values, S20 ... diagnosis vibration values, S30 ... alarm signal.
Claims (15)
1. an abnormality diagnostic method, it diagnoses the exception of described mechanical equipment according to the vibration values collected by the vibration sensor be arranged on mechanical equipment, and the feature of described abnormality diagnostic method is,
Difference and the learning value characteristic quantity difference value of each characteristic quantity is calculated according to the first study vibration values and the second study vibration values, wherein this first study vibration values corresponds to the first running state collected when learning by described vibration sensor, this the second study vibration values corresponds to second running state different from described first running state collected when learning by described vibration sensor
And difference and the diagnostic value characteristic quantity difference value of each characteristic quantity is calculated according to the first study vibration values and the second study vibration values, wherein this first study vibration values corresponds to described first running state collected when diagnosing by described vibration sensor, this the second study vibration values corresponds to described second running state collected when diagnosing by described vibration sensor
Described learning value characteristic quantity difference value and described diagnostic value characteristic quantity difference value are compared, judge that described mechanical equipment is abnormal with or without generation,
A side in described first running state and described second running state is the basic state run.
2. abnormality diagnostic method as claimed in claim 1, is characterized in that,
The mechanical equipment collecting vibration values when described study and the mechanical equipment collecting vibration values when described diagnosis are same mechanical equipments.
3. abnormality diagnostic method as claimed in claim 1, is characterized in that,
The mechanical equipment collecting vibration values when described study is identical with the model of collecting the mechanical equipment of vibration values during in described diagnosis, but is not same mechanical equipment.
4. abnormality diagnostic method as claimed in claim 1, is characterized in that,
Described characteristic quantity is integral value.
5. abnormality diagnostic method as claimed in claim 1, is characterized in that,
Described characteristic quantity is the frequency component of vibration values.
6. abnormality diagnostic method as claimed in claim 5, is characterized in that,
When calculating the difference of described characteristic quantity, only calculate difference at the frequency band of regulation.
7. an apparatus for diagnosis of abnormality, it diagnoses the exception of described mechanical equipment according to the vibration values collected by the vibration sensor be arranged on mechanical equipment, and the feature of described apparatus for diagnosis of abnormality is,
Described apparatus for diagnosis of abnormality has learning value characteristic quantity Difference Calculation part, diagnostic value characteristic quantity Difference Calculation part and multilevel iudge part,
Described learning value characteristic quantity Difference Calculation part calculates difference and the learning value characteristic quantity difference value of each characteristic quantity according to the first study vibration values and the second study vibration values, wherein this first study vibration values corresponds to the first running state collected when learning by described vibration sensor, this the second study vibration values corresponds to second running state different from described first running state collected when learning by described vibration sensor
Described diagnostic value characteristic quantity Difference Calculation part calculates difference and the diagnostic value characteristic quantity difference value of each characteristic quantity according to the first study vibration values and the second study vibration values, wherein this first study vibration values corresponds to described first running state collected when diagnosing by described vibration sensor, this the second study vibration values corresponds to described second running state collected when diagnosing by described vibration sensor
Described multilevel iudge part compares described learning value characteristic quantity difference value and described diagnostic value characteristic quantity difference value, judges that described mechanical equipment is abnormal with or without generation,
A side in described first running state and described second running state is the basic state run.
8. apparatus for diagnosis of abnormality as claimed in claim 7, is characterized in that,
The mechanical equipment collecting vibration values when described study and the mechanical equipment collecting vibration values when described diagnosis are same mechanical equipments.
9. apparatus for diagnosis of abnormality as claimed in claim 7, is characterized in that,
The mechanical equipment collecting vibration values when described study is identical with the model of collecting the mechanical equipment of vibration values during in described diagnosis, but is not same mechanical equipment.
10. apparatus for diagnosis of abnormality as claimed in claim 7, is characterized in that,
Described characteristic quantity is integral value.
11. apparatus for diagnosis of abnormality as claimed in claim 7, is characterized in that,
Described characteristic quantity is the frequency component of vibration values.
12. apparatus for diagnosis of abnormality as claimed in claim 11, is characterized in that,
When calculating the difference of described characteristic quantity, only calculate difference at the frequency band of regulation.
13. 1 kinds of apparatus of passenger conveyor with the apparatus for diagnosis of abnormality as described in any one in claim 7 to 12.
14. apparatus of passenger conveyor as claimed in claim 13, is characterized in that,
Described vibration sensor is arranged on extreme gear bearing.
15. apparatus of passenger conveyor as described in claim 13 or 14, is characterized in that,
Described vibration sensor is arranged on handrail driving roller.
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP2012143678A JP5879214B2 (en) | 2012-06-27 | 2012-06-27 | Abnormality diagnosis method, abnormality diagnosis device, and passenger conveyor equipped with abnormality diagnosis device |
| JP2012-143678 | 2012-06-27 |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN103508303A CN103508303A (en) | 2014-01-15 |
| CN103508303B true CN103508303B (en) | 2015-08-05 |
Family
ID=49891813
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201310053558.1A Active CN103508303B (en) | 2012-06-27 | 2013-02-19 | Abnormality diagnostic method, apparatus for diagnosis of abnormality and there is the apparatus of passenger conveyor of apparatus for diagnosis of abnormality |
Country Status (2)
| Country | Link |
|---|---|
| JP (1) | JP5879214B2 (en) |
| CN (1) | CN103508303B (en) |
Families Citing this family (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106586796B (en) * | 2016-11-15 | 2018-09-14 | 王蕊 | A kind of escalator condition monitoring system and method |
| BR112020017560A2 (en) * | 2018-05-14 | 2020-12-22 | Inventio Ag | METHOD AND DEVICE FOR MONITORING A STATE OF A PASSENGER TRANSPORT INSTALLATION UNDER THE USE OF A DIGITAL DOUBLE |
| KR102464187B1 (en) * | 2018-05-31 | 2022-11-07 | 닛본 덴끼 가부시끼가이샤 | Surveillance Systems and Monitoring Methods |
| CN111606176B (en) * | 2020-06-04 | 2022-10-14 | 上海三菱电梯有限公司 | Passenger conveyor, abnormality diagnosis device and method thereof, and cycle recognition method |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1180163A (en) * | 1996-03-08 | 1998-04-29 | 固特异轮胎和橡胶公司 | Method of machine vibration analysis for tire uniformity machine |
| US20040176926A1 (en) * | 2003-03-06 | 2004-09-09 | Edie Paul Charles | System and method for machining data management |
| CN101354578A (en) * | 2007-07-23 | 2009-01-28 | 发那科株式会社 | Numeric control device of machine tool |
| CN201250044Y (en) * | 2008-07-15 | 2009-06-03 | 宁波宏大电梯有限公司 | Device for detecting and displaying errors of escalator or moving pavement |
| CN101624159A (en) * | 2008-07-10 | 2010-01-13 | 东芝电梯株式会社 | Abnormity diagnosis system of passenger conveyer |
| CN101638203A (en) * | 2008-07-29 | 2010-02-03 | 东芝电梯株式会社 | Passenger conveyer abnormality diagnosis system |
Family Cites Families (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH0758519B2 (en) * | 1987-08-18 | 1995-06-21 | 日比谷総合設備株式会社 | Remote diagnosis method for equipment |
| JP3872252B2 (en) * | 2000-03-31 | 2007-01-24 | 三菱電機ビルテクノサービス株式会社 | Elevator abnormal sound detection apparatus and method |
| JP2002082103A (en) * | 2000-09-11 | 2002-03-22 | Hitachi Building Systems Co Ltd | Device for reporting anomaly in water supply equipment |
| JP2004333199A (en) * | 2003-05-01 | 2004-11-25 | Nidec Copal Corp | Apparatus and method for determining abnormal sound |
| JP4020204B2 (en) * | 2003-08-26 | 2007-12-12 | 三菱電機株式会社 | Man conveyor inspection device |
| JP4791093B2 (en) * | 2005-07-04 | 2011-10-12 | 三菱電機株式会社 | Passenger conveyor diagnostic equipment |
| JP4321581B2 (en) * | 2006-11-30 | 2009-08-26 | パナソニック電工株式会社 | Machine tool comprehensive monitoring device |
| JP2009234747A (en) * | 2008-03-27 | 2009-10-15 | Hitachi Building Systems Co Ltd | Sound diagnosis device of escalator |
-
2012
- 2012-06-27 JP JP2012143678A patent/JP5879214B2/en active Active
-
2013
- 2013-02-19 CN CN201310053558.1A patent/CN103508303B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1180163A (en) * | 1996-03-08 | 1998-04-29 | 固特异轮胎和橡胶公司 | Method of machine vibration analysis for tire uniformity machine |
| US20040176926A1 (en) * | 2003-03-06 | 2004-09-09 | Edie Paul Charles | System and method for machining data management |
| CN101354578A (en) * | 2007-07-23 | 2009-01-28 | 发那科株式会社 | Numeric control device of machine tool |
| CN101624159A (en) * | 2008-07-10 | 2010-01-13 | 东芝电梯株式会社 | Abnormity diagnosis system of passenger conveyer |
| CN201250044Y (en) * | 2008-07-15 | 2009-06-03 | 宁波宏大电梯有限公司 | Device for detecting and displaying errors of escalator or moving pavement |
| CN101638203A (en) * | 2008-07-29 | 2010-02-03 | 东芝电梯株式会社 | Passenger conveyer abnormality diagnosis system |
Also Published As
| Publication number | Publication date |
|---|---|
| CN103508303A (en) | 2014-01-15 |
| JP5879214B2 (en) | 2016-03-08 |
| JP2014005139A (en) | 2014-01-16 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US10837866B2 (en) | Self-learning malfunction monitoring and early warning system | |
| JP6428935B2 (en) | Failure diagnosis apparatus and failure diagnosis method | |
| CN111819042B (en) | Abnormality detection device and abnormality detection method | |
| CN103508303B (en) | Abnormality diagnostic method, apparatus for diagnosis of abnormality and there is the apparatus of passenger conveyor of apparatus for diagnosis of abnormality | |
| JP5460160B2 (en) | Equipment diagnostic equipment | |
| JP7185247B2 (en) | Machine diagnostic system and diagnostic program | |
| JP6796545B2 (en) | Railroad vehicle equipment diagnostic equipment and railroad vehicle equipment diagnostic method | |
| JPWO2019167171A6 (en) | Anomaly detection device and abnormality detection method | |
| JP2009109350A (en) | Monitoring and diagnosing system for rotary machine apparatus | |
| JP2009068950A (en) | Machine diagnostic system | |
| CN111771113A (en) | Abnormal type determination device and abnormal type determination method | |
| KR101498527B1 (en) | Diagnosis system using vibration frequency analysis program for rotation equipment of power plant | |
| CN101776921B (en) | Main chain tension predicting control system of paraffin continuous shaping machine | |
| KR102545672B1 (en) | Method and apparatus for machine fault diagnosis | |
| KR101455268B1 (en) | Monitoring System For State Of A Rotation Body Of Marine Structure | |
| JP2007112565A (en) | Drive system diagnostic device | |
| JP6714844B2 (en) | Abnormality diagnosis method | |
| CN109084997A (en) | A kind of the new-energy automobile fault detection means and detection method of automation | |
| US11333577B2 (en) | Method and device for diagnosing abnormality in rolling bearing | |
| CN103776625A (en) | Method and system for detecting faults of loads of driving device of telescopic mechanism | |
| WO2022224631A1 (en) | Rotating machine system and diagnostic method for same | |
| JP3659891B2 (en) | Lubrication target part diagnosis system and lubrication target part diagnosis method | |
| CN110165969B (en) | Control device for machine tool | |
| CN102788014B (en) | Gear oil pump tooth surface wearing fault diagnosis device and method | |
| KR20060077594A (en) | A system of vvvf inverter and aid-converter diagnose in high-speed railway |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant |