CN112777443A - Elevator operation evaluation method, device and computer readable medium - Google Patents
Elevator operation evaluation method, device and computer readable medium Download PDFInfo
- Publication number
- CN112777443A CN112777443A CN202110168335.4A CN202110168335A CN112777443A CN 112777443 A CN112777443 A CN 112777443A CN 202110168335 A CN202110168335 A CN 202110168335A CN 112777443 A CN112777443 A CN 112777443A
- Authority
- CN
- China
- Prior art keywords
- elevator
- evaluation method
- audio data
- data
- operation evaluation
- 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.)
- Pending
Links
- 238000011156 evaluation Methods 0.000 title claims abstract description 62
- 238000001228 spectrum Methods 0.000 claims abstract description 23
- 230000036541 health Effects 0.000 claims abstract description 16
- 230000002159 abnormal effect Effects 0.000 claims description 24
- 230000001133 acceleration Effects 0.000 claims description 24
- 238000000034 method Methods 0.000 claims description 24
- 230000005236 sound signal Effects 0.000 claims description 16
- 238000004590 computer program Methods 0.000 claims description 12
- 238000001514 detection method Methods 0.000 claims description 6
- 238000013210 evaluation model Methods 0.000 claims description 4
- 238000013135 deep learning Methods 0.000 claims description 3
- 238000012706 support-vector machine Methods 0.000 claims description 3
- 238000012423 maintenance Methods 0.000 description 5
- 230000006870 function Effects 0.000 description 3
- 230000003862 health status Effects 0.000 description 3
- 230000000694 effects Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
Images
Classifications
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66B—ELEVATORS; ESCALATORS OR MOVING WALKWAYS
- B66B5/00—Applications of checking, fault-correcting, or safety devices in elevators
- B66B5/0006—Monitoring devices or performance analysers
- B66B5/0037—Performance analysers
Landscapes
- Indicating And Signalling Devices For Elevators (AREA)
- Maintenance And Inspection Apparatuses For Elevators (AREA)
Abstract
The invention discloses an elevator operation evaluation method, equipment and a computer readable medium, wherein the elevator operation evaluation method comprises the following steps: collecting audio data during the operation of the elevator; judging whether the collected audio data during the operation of the elevator meets a preset rule or not, and evaluating the operation condition of the elevator; collecting audio data in real time when the elevator runs; and when the collected audio data reach the set number, carrying out Fourier transform on the collected audio data to obtain frequency spectrum information corresponding to the audio data, and evaluating the running condition of the elevator according to the frequency spectrum information. The elevator operation evaluation method, the elevator operation evaluation equipment and the computer readable medium can evaluate the health state of the elevator more comprehensively, improve the evaluation accuracy, have low cost and improve better guarantee for the elevator safety.
Description
Technical Field
The invention belongs to the technical field of elevator equipment, relates to elevator equipment, and particularly relates to an elevator operation evaluation method, equipment and a computer readable medium.
Background
As a transportation device, the elevator brings convenience to work, study and life of people. The elevator often breaks down, and the existing failure finding mode is that a user informs the property through a telephone after finding the failure, and the property informs an elevator maintenance unit.
Meanwhile, every time the elevator is in a period of time, the elevator maintenance unit needs to arrive at the elevator for maintenance inspection, and the efficiency is low; in addition, because the maintenance personnel have a limited detection time for each elevator, the operation condition of the elevator cannot be well known.
The health state evaluation of the elevator needs to be improved, and the existing manual maintenance mode cannot evaluate the state of the elevator comprehensively, so that certain misjudgment rate possibly exists under the evaluation of big data.
In view of the above, there is an urgent need to design a new elevator operation state evaluation method to overcome at least some of the above-mentioned disadvantages of the existing elevator operation state evaluation methods.
Disclosure of Invention
The invention provides an elevator operation evaluation method, equipment and a computer readable medium, which can more comprehensively evaluate the health state of an elevator, improve the accuracy of evaluation, have low cost and better guarantee for the safety of the elevator.
In order to solve the technical problem, according to one aspect of the present invention, the following technical solutions are adopted:
an elevator operation evaluation method, comprising:
collecting audio data of the elevator in operation within a set time period or/and at a set time point; and judging whether the collected audio data during the operation of the elevator meets a preset rule or not, thereby evaluating the operation condition of the elevator.
As an embodiment of the present invention, the elevator operation evaluation method includes: and acquiring frequency information or/and loudness information of the acquired audio data during the operation of the elevator, and judging whether the audio data acquired within a set time period or/and at a set time point meets a preset rule or not.
As an embodiment of the present invention, the elevator operation evaluating method further includes: collecting audio data in real time when the elevator runs; and when the collected audio data reach the set number, carrying out Fourier transform on the collected audio data to obtain frequency spectrum information corresponding to the audio data, and evaluating the running condition of the elevator according to the frequency spectrum information.
As an embodiment of the present invention, the elevator operation evaluation method includes: detecting whether the frequency spectrum information has audio signals with frequency values higher than a set threshold value, and counting the frequency of the audio signals with the frequency values higher than the set threshold value in set time or/and the duration or/and the proportion of the duration to corresponding running time; or/and the light source is arranged in the light path,
the elevator operation evaluation method comprises the following steps: and detecting whether the audio signals with the volume loudness values higher than a set threshold exist in the frequency spectrum information, and counting the frequency or/and the duration of the audio signals with the volume loudness values higher than the set threshold in the set time or/and the proportion of the duration to the corresponding running time.
As an embodiment of the present invention, the elevator operation evaluation method includes: detecting whether an audio signal with a frequency value higher than 4000 exists in the frequency spectrum information.
As an embodiment of the present invention, the elevator operation evaluation method includes: carrying out deep learning on the existing data by using an svm support vector machine so as to obtain an evaluation model; and taking a classification result obtained according to the input elevator parameters as a judgment result for evaluating the health state of the elevator, wherein the input elevator parameters comprise frequency information or/and loudness information of collected audio data during the operation of the elevator or/and duration reaching the set frequency or/and duration reaching the set loudness.
As an embodiment of the present invention, the elevator operation evaluating method further includes: and identifying the running health state of the elevator according to the collected audio data of the running elevator and the condition corresponding to the running health state of the elevator.
As an embodiment of the present invention, the elevator operation evaluating method further includes: and comparing the acquired frequency spectrum of the audio data with the frequency spectrum of the audio data in the database, which represents normal operation or/and abnormal operation of the elevator, so as to evaluate whether the operation state of the elevator is normal.
As an embodiment of the present invention, the elevator operation evaluating method further includes: acquiring acceleration data or/and real-time position data during the operation of the elevator; simultaneously acquiring audio data during the operation of the elevator and elevator acceleration data or/and real-time position data at the same time; and comprehensively considering the audio data during the operation of the elevator, and the acceleration data or/and the real-time position data so as to evaluate whether the operation state of the elevator is normal.
As an embodiment of the present invention, the elevator operation evaluating method further includes: and comparing the audio data, the acceleration data or/and the real-time position data of the elevator in operation with the corresponding data of the elevator in a normal state or/and an abnormal whole state, thereby judging whether the elevator is abnormal in operation.
As an implementation mode of the invention, the audio data, the acceleration data or/and the real-time position data during the operation of the elevator are compared with the data in the database to judge whether the operation of the elevator is abnormal;
the database stores the operation data of the elevator in a normal state and the abnormal operation data of the elevator in various fault types;
and after the elevator is judged to be abnormal, acquiring the data with the highest similarity to the elevator running data in the database so as to judge the fault type of the elevator.
As an embodiment of the present invention, a method for acquiring real-time position data during operation of an elevator includes: and acquiring real-time position data of the elevator in operation according to the real-time acceleration data of the elevator in operation.
As an embodiment of the invention, the audio data of several elevators is counted and an elevator evaluation related to the audio detection is calculated.
According to another aspect of the invention, the following technical scheme is adopted: an apparatus for an elevator operation assessment method, the apparatus comprising a memory for storing computer program instructions and a processor for executing the computer program instructions, wherein the computer program instructions, when executed by the processor, trigger the apparatus to perform the method described above.
According to another aspect of the invention, the following technical scheme is adopted: a computer readable medium having stored thereon computer program instructions executable by a processor to implement a method as described above.
The invention has the beneficial effects that: the elevator operation evaluation method, the elevator operation evaluation equipment and the computer readable medium can evaluate the health state of the elevator more comprehensively, improve the evaluation accuracy, have low cost and improve better guarantee for the elevator safety.
Drawings
Fig. 1 is a flow chart of an elevator operation evaluation method in an embodiment of the present invention.
Detailed Description
Preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
For a further understanding of the invention, reference will now be made to the preferred embodiments of the invention by way of example, and it is to be understood that the description is intended to further illustrate features and advantages of the invention, and not to limit the scope of the claims.
The description in this section is for several exemplary embodiments only, and the present invention is not limited only to the scope of the embodiments described. It is within the scope of the present disclosure and protection that the same or similar prior art means and some features of the embodiments may be interchanged.
The steps in the embodiments in the specification are only expressed for convenience of description, and the implementation manner of the present application is not limited by the order of implementation of the steps. The term "connected" in the specification includes both direct connection and indirect connection.
The invention discloses an elevator operation evaluation method, and figure 1 is a flow chart of the elevator operation evaluation method in one embodiment of the invention; referring to fig. 1, the elevator operation evaluation method includes:
step S1, audio data during the operation of the elevator at a set time period or/and a set time point are collected.
Step S2, it is determined whether the collected audio data during the operation of the elevator meets a preset rule, thereby evaluating the operation condition of the elevator.
In one embodiment, the elevator operation evaluation method includes: and acquiring frequency information or/and loudness information of the acquired audio data during the operation of the elevator, and judging whether the audio data acquired within a set time period or/and at a set time point meets a preset rule or not.
In an embodiment of the present invention, in step S1, the audio data during the operation of the elevator is collected in real time. The method further comprises: when the collected audio data reaches the set number, fourier transform is performed on the collected audio data to obtain frequency spectrum information corresponding to the audio data, and in step S2, the operation condition of the elevator can be evaluated according to the frequency spectrum information.
In one embodiment of the present invention, the elevator operation evaluation method includes: and detecting whether the audio signals with the frequency values higher than the set threshold exist in the frequency spectrum information, and counting the frequency of the audio signals with the frequency values higher than the set threshold in the set time or/and the duration or/and the proportion of the duration to the corresponding running time. In one embodiment, whether an audio signal with a frequency value higher than 4000 exists in the spectrum information is detected, and if so, N1 accumulates 1; then, whether the elevator runs abnormally can be judged according to the value of N1 in the set time (after the judgment is completed, N1 can be reset, for example, to 0). If the N1 is more than 10 within a certain time, the elevator is considered to be abnormal in operation; of course, other settings may be made as desired.
In another embodiment of the present invention, the elevator operation evaluating method includes: and detecting whether audio signals with volume loudness values higher than a set threshold (the set threshold can be set to 80db, and can be other values) exist in the spectrum information, and counting the number of times or/and duration or/and the proportion of the duration to the corresponding running time when the audio signals with the volume loudness values higher than the set threshold appear in the set time. In one embodiment, if an audio signal with a volume loudness value higher than a set threshold is detected, N2 accumulates 1; then, whether the elevator runs abnormally can be judged according to the value of N2 in the set time (after the judgment is completed, N2 can be reset, for example, to 0).
In another embodiment of the invention, the method can comprehensively judge whether the elevator runs abnormally by simultaneously utilizing the frequency detection and loudness detection modes.
In one embodiment, two evaluation parameters are set: frequency band and loudness of sound when the elevator is running. The audio data is classified into two types according to the frequency range, the audio data with frequency < ═ 4000hz is classified as one type (frequency is normal), and the audio data with frequency >4000hz is classified as one type (frequency is abnormal). The audio data are classified into two categories according to their loudness differences, audio data with loudness < ═ 80db is classified as one category (loudness normal), and audio data with loudness >80db is classified as one category (loudness abnormal). The audio data are divided into two types according to the proportion of the frequency anomaly duration or/and the proportion of the loudness anomaly duration (the proportion of the audio data occupying the running time), the audio data are divided into two types according to the proportion value, the audio data with the duration proportion of 50% are taken as one type (the duration proportion of frequency anomaly is larger than 50%, the duration proportion of loudness anomaly is larger than 50%, and the duration proportion of frequency anomaly is larger than 50% and the duration proportion of loudness anomaly is larger than 50%) (the audio data are normal), and the audio data with the duration proportion of larger than 50% are taken as one type (the audio data are abnormal).
The health status of the corresponding elevator can be marked according to the audio data of the elevator (the health status can be automatically set by a system and also can be judged by a professional), and the running health status of the elevator can be divided into very poor, good and excellent. The elevator operation evaluation method comprises the following steps: carrying out deep learning on the existing data by using an svm support vector machine so as to obtain an evaluation model; the more data, the more accurate the evaluation model; therefore, the classification result obtained according to the input elevator parameters (which can comprise the frequency information or/and the loudness information of the collected audio data when the elevator runs or/and the duration reaching the set frequency or/and the duration reaching the set loudness) is used as the judgment result for evaluating the health state of the elevator.
In one embodiment of the present invention, the elevator operation evaluation method further includes: and identifying the running health state of the elevator (the running health state of the elevator can comprise a health state, a semi-health state and an unhealthy state) according to the collected audio data during the running of the elevator and the condition corresponding to the running health state of the elevator. In another embodiment of the present invention, the elevator operation evaluating method further comprises: and comparing the acquired frequency spectrum of the audio data with the frequency spectrum of the audio data in the database, which represents normal operation or/and abnormal operation of the elevator, so as to evaluate whether the operation state of the elevator is normal. In one embodiment, the database stores the operation data of the elevator in a normal state and the abnormal operation data of the elevator in various fault types.
In another embodiment of the invention, whether the compared audio data represents the abnormal operation of the elevator can be judged only by whether the audio data meets the set conditions without a database.
In one embodiment of the present invention, the elevator operation evaluation method further includes: acquiring acceleration data when the elevator runs; simultaneously acquiring audio data and elevator acceleration data during elevator operation at the same time; and comprehensively considering the audio data and the acceleration data during the operation of the elevator so as to evaluate whether the operation state of the elevator is normal.
In another embodiment of the present invention, the elevator operation evaluating method further comprises: acquiring real-time position data of an elevator in operation; simultaneously acquiring audio data and real-time position data of the elevator in operation at the same time; and comprehensively considering the audio data and the real-time position data during the operation of the elevator so as to evaluate whether the operation state of the elevator is normal. In one embodiment, a method of obtaining real-time position data while an elevator is in operation includes: and acquiring real-time position data during the operation of the elevator (such as the floor where the elevator is located or a floor interval can be acquired) according to the real-time acceleration data during the operation of the elevator.
In still another embodiment of the present invention, the elevator operation evaluating method further includes: acquiring acceleration data and real-time position data during elevator operation; simultaneously acquiring audio data, elevator acceleration data and real-time position data during elevator operation at the same time; and comprehensively considering the audio data, the acceleration data and the real-time position data during the operation of the elevator, thereby evaluating whether the operation state of the elevator is normal.
In one embodiment, the elevator operation evaluation method further comprises: and comparing the audio data, the acceleration data or/and the real-time position data of the elevator in operation with the corresponding data of the elevator in a normal state or/and an abnormal whole state, thereby judging whether the elevator is abnormal in operation.
In one embodiment of the invention, the audio data, the acceleration data or/and the real-time position data during the operation of the elevator are compared with the data in the database to judge whether the operation of the elevator is abnormal; the database stores the operation data of the elevator in a normal state and the abnormal operation data of the elevator in various fault types. In addition, after the elevator is judged to be abnormal, the data with the highest similarity to the elevator running data in the database can be obtained, so that the fault type of the elevator is judged.
In one embodiment of the method, the acceleration data of the elevator can be detected through the acceleration sensor so as to judge whether the elevator runs, and after the elevator runs, the audio acquisition module is started to acquire the audio data of the elevator in running; when the acceleration sensor detects that the elevator stops running, the audio acquisition module is controlled to stop acquiring audio data; this can reduce power consumption.
In one embodiment of the invention, the audio data of several elevators is counted and an elevator evaluation related to the audio detection is calculated.
In a use scene of the invention, the invention monitors the noise emitted during the operation of the elevator by collecting the audio frequency during the operation of the elevator, and evaluates the noise, for example, a sharp sound indicates that severe friction may exist during the operation of the elevator to a certain extent, and a loud sound indicates that impact may exist during the operation of the elevator.
The invention also discloses an apparatus for an elevator operation assessment method, the apparatus comprising a memory for storing computer program instructions and a processor for executing the computer program instructions, wherein the computer program instructions, when executed by the processor, trigger the apparatus to perform the method described above.
The invention further discloses a computer readable medium having stored thereon computer program instructions executable by a processor to implement the method as described above.
In conclusion, the elevator operation evaluation method, the elevator operation evaluation equipment and the computer readable medium provided by the invention can be used for evaluating the health state of the elevator more comprehensively, improving the evaluation accuracy, and improving the better guarantee for the elevator safety with low cost.
It should be noted that the present application may be implemented in software and/or a combination of software and hardware; for example, it may be implemented using Application Specific Integrated Circuits (ASICs), general purpose computers, or any other similar hardware devices. In some embodiments, the software programs of the present application may be executed by a processor to implement the above steps or functions. As such, the software programs (including associated data structures) of the present application can be stored in a computer-readable recording medium; such as RAM memory, magnetic or optical drives or diskettes, and the like. In addition, some steps or functions of the present application may be implemented using hardware; for example, as circuitry that cooperates with the processor to perform various steps or functions.
The technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The description and applications of the invention herein are illustrative and are not intended to limit the scope of the invention to the embodiments described above. Effects or advantages referred to in the embodiments may not be reflected in the embodiments due to interference of various factors, and the description of the effects or advantages is not intended to limit the embodiments. Variations and modifications of the embodiments disclosed herein are possible, and alternative and equivalent various components of the embodiments will be apparent to those skilled in the art. It will be clear to those skilled in the art that the present invention may be embodied in other forms, structures, arrangements, proportions, and with other components, materials, and parts, without departing from the spirit or essential characteristics thereof. Other variations and modifications of the embodiments disclosed herein may be made without departing from the scope and spirit of the invention.
Claims (13)
1. An elevator operation evaluation method, characterized by comprising:
collecting audio data of the elevator in operation within a set time period or/and at a set time point; and judging whether the collected audio data during the operation of the elevator meets a preset rule or not, thereby evaluating the operation condition of the elevator.
2. The elevator operation evaluation method according to claim 1, characterized in that:
the elevator operation evaluation method comprises the following steps: and acquiring frequency information or/and loudness information of the acquired audio data during the operation of the elevator, and judging whether the audio data acquired within a set time period or/and at a set time point meets a preset rule or not.
3. The elevator operation evaluation method according to claim 1, characterized in that:
the elevator operation evaluation method further includes: collecting audio data in real time when the elevator runs; and when the collected audio data reach the set number, carrying out Fourier transform on the collected audio data to obtain frequency spectrum information corresponding to the audio data, and evaluating the running condition of the elevator according to the frequency spectrum information.
4. The elevator operation evaluation method according to claim 3, characterized in that:
the elevator operation evaluation method comprises the following steps: detecting whether the frequency spectrum information has audio signals with frequency values higher than a set threshold value, and counting the frequency of the audio signals with the frequency values higher than the set threshold value in set time or/and the duration or/and the proportion of the duration to corresponding running time; or,
the elevator operation evaluation method comprises the following steps: and detecting whether the audio signals with the volume loudness values higher than a set threshold exist in the frequency spectrum information, and counting the frequency or/and the duration of the audio signals with the volume loudness values higher than the set threshold in the set time or/and the proportion of the duration to the corresponding running time.
5. The elevator operation evaluation method according to claim 4, characterized in that:
the elevator operation evaluation method comprises the following steps: detecting whether an audio signal with a frequency value higher than 4000 exists in the frequency spectrum information.
6. The elevator operation evaluation method according to any one of claims 1 to 5, characterized in that:
the elevator operation evaluation method comprises the following steps: carrying out deep learning on the existing data by using an svm support vector machine so as to obtain an evaluation model; and taking a classification result obtained according to the input elevator parameters as a judgment result for evaluating the health state of the elevator, wherein the input elevator parameters comprise frequency information or/and loudness information of collected audio data during the operation of the elevator or/and duration reaching the set frequency or/and duration reaching the set loudness.
7. The elevator operation evaluation method according to any one of claims 1 to 5, characterized in that:
the elevator operation evaluation method comprises the following steps: identifying the running health state of the elevator according to the collected audio data of the running elevator and the conditions corresponding to the running health state of the elevator; or/and the light source is arranged in the light path,
the elevator operation evaluation method further includes: and comparing the acquired frequency spectrum of the audio data with the frequency spectrum of the audio data in the database, which represents normal operation or/and abnormal operation of the elevator, so as to evaluate whether the operation state of the elevator is normal.
8. The elevator operation evaluation method according to any one of claims 1 to 5, characterized in that:
the elevator operation evaluation method further includes: acquiring acceleration data or/and real-time position data during the operation of the elevator; simultaneously acquiring audio data during the operation of the elevator and elevator acceleration data or/and real-time position data at the same time; and comprehensively considering the audio data during the operation of the elevator, and the acceleration data or/and the real-time position data so as to evaluate whether the operation state of the elevator is normal.
9. The elevator operation evaluation method according to claim 8, characterized in that:
the elevator operation evaluation method further includes: comparing the audio data, the acceleration data or/and the real-time position data of the elevator in operation with the corresponding data of the elevator in a normal state or/and an abnormal whole so as to judge whether the elevator is abnormal in operation; or/and the light source is arranged in the light path,
the elevator operation evaluation method further includes: comparing the audio data, the acceleration data or/and the real-time position data of the elevator in operation with the data in the database, and judging whether the elevator is abnormal in operation; the database stores the operation data of the elevator in a normal state and the abnormal operation data of the elevator in various fault types; and after the elevator is judged to be abnormal, acquiring the data with the highest similarity to the elevator running data in the database so as to judge the fault type of the elevator.
10. The elevator operation evaluation method according to claim 9, characterized in that:
the method for acquiring the real-time position data during the operation of the elevator comprises the following steps: and acquiring real-time position data of the elevator in operation according to the real-time acceleration data of the elevator in operation.
11. The elevator operation evaluation method according to claim 1, characterized in that:
and counting the audio data of a plurality of elevators, and calculating elevator evaluation related to audio detection.
12. An apparatus for an elevator operation assessment method, the apparatus comprising a memory for storing computer program instructions and a processor for executing the computer program instructions, wherein the computer program instructions, when executed by the processor, trigger the apparatus to perform the method of any of claims 1 to 11.
13. A computer readable medium having stored thereon computer program instructions executable by a processor to implement the method of any one of claims 1 to 11.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110168335.4A CN112777443A (en) | 2021-02-07 | 2021-02-07 | Elevator operation evaluation method, device and computer readable medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110168335.4A CN112777443A (en) | 2021-02-07 | 2021-02-07 | Elevator operation evaluation method, device and computer readable medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112777443A true CN112777443A (en) | 2021-05-11 |
Family
ID=75761164
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110168335.4A Pending CN112777443A (en) | 2021-02-07 | 2021-02-07 | Elevator operation evaluation method, device and computer readable medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112777443A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117056711A (en) * | 2023-10-11 | 2023-11-14 | 深圳正实自动化设备有限公司 | Multi-source data-based solder paste printer performance evaluation method, system and storage medium |
Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2007308257A (en) * | 2006-05-18 | 2007-11-29 | Mitsubishi Electric Corp | Elevator device |
| CN101580198A (en) * | 2008-05-14 | 2009-11-18 | 株式会社日立制作所 | Elevator abnormity detector |
| CN103145014A (en) * | 2011-12-06 | 2013-06-12 | 株式会社日立制作所 | Elevator remote monitoring device |
| JP2014114111A (en) * | 2012-12-10 | 2014-06-26 | Hitachi Ltd | Elevator with abnormality diagnosis function |
| CN107522053A (en) * | 2017-07-11 | 2017-12-29 | 浙江新再灵科技股份有限公司 | A kind of elevator platform detecting system and method based on audio analysis |
| CN107973206A (en) * | 2017-12-29 | 2018-05-01 | 通力电梯有限公司 | Escalator lubricating status monitors system and the sound collection means for it |
| CN108455394A (en) * | 2017-02-20 | 2018-08-28 | 株式会社安川电机 | Elevator rolling inspection method and device, management server and elevator control system |
| CN109155086A (en) * | 2016-05-26 | 2019-01-04 | 三菱电机株式会社 | access management system |
| CN109650209A (en) * | 2019-01-16 | 2019-04-19 | 日立电梯（中国）有限公司 | Elevator drags lock fault detection system, method, apparatus, equipment and storage medium |
| CN109748170A (en) * | 2019-01-18 | 2019-05-14 | 西人马(西安)测控科技有限公司 | Elevator faults alarm method, device, equipment and medium |
| CN110371815A (en) * | 2019-07-04 | 2019-10-25 | 安徽中科福瑞科技有限公司 | A kind of on-demand maintenance system of elevator based on Internet of Things |
| CN111727164A (en) * | 2017-12-29 | 2020-09-29 | 通力电梯有限公司 | Escalator monitoring system, escalator monitoring method, sound data collection device and clamp used for escalator monitoring device |
| CN112193959A (en) * | 2020-09-25 | 2021-01-08 | 浙江新再灵科技股份有限公司 | Method and system for detecting abnormal sound of elevator |
-
2021
- 2021-02-07 CN CN202110168335.4A patent/CN112777443A/en active Pending
Patent Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2007308257A (en) * | 2006-05-18 | 2007-11-29 | Mitsubishi Electric Corp | Elevator device |
| CN101580198A (en) * | 2008-05-14 | 2009-11-18 | 株式会社日立制作所 | Elevator abnormity detector |
| CN103145014A (en) * | 2011-12-06 | 2013-06-12 | 株式会社日立制作所 | Elevator remote monitoring device |
| JP2014114111A (en) * | 2012-12-10 | 2014-06-26 | Hitachi Ltd | Elevator with abnormality diagnosis function |
| CN109155086A (en) * | 2016-05-26 | 2019-01-04 | 三菱电机株式会社 | access management system |
| CN108455394A (en) * | 2017-02-20 | 2018-08-28 | 株式会社安川电机 | Elevator rolling inspection method and device, management server and elevator control system |
| CN107522053A (en) * | 2017-07-11 | 2017-12-29 | 浙江新再灵科技股份有限公司 | A kind of elevator platform detecting system and method based on audio analysis |
| CN107973206A (en) * | 2017-12-29 | 2018-05-01 | 通力电梯有限公司 | Escalator lubricating status monitors system and the sound collection means for it |
| CN111727164A (en) * | 2017-12-29 | 2020-09-29 | 通力电梯有限公司 | Escalator monitoring system, escalator monitoring method, sound data collection device and clamp used for escalator monitoring device |
| CN109650209A (en) * | 2019-01-16 | 2019-04-19 | 日立电梯（中国）有限公司 | Elevator drags lock fault detection system, method, apparatus, equipment and storage medium |
| CN109748170A (en) * | 2019-01-18 | 2019-05-14 | 西人马(西安)测控科技有限公司 | Elevator faults alarm method, device, equipment and medium |
| CN110371815A (en) * | 2019-07-04 | 2019-10-25 | 安徽中科福瑞科技有限公司 | A kind of on-demand maintenance system of elevator based on Internet of Things |
| CN112193959A (en) * | 2020-09-25 | 2021-01-08 | 浙江新再灵科技股份有限公司 | Method and system for detecting abnormal sound of elevator |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117056711A (en) * | 2023-10-11 | 2023-11-14 | 深圳正实自动化设备有限公司 | Multi-source data-based solder paste printer performance evaluation method, system and storage medium |
| CN117056711B (en) * | 2023-10-11 | 2024-01-30 | 深圳正实自动化设备有限公司 | Multi-source data-based solder paste printer performance evaluation method, system and storage medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN112978531A (en) | Elevator operation evaluation system | |
| CN112698975B (en) | Fault root cause positioning method and system of micro-service architecture information system | |
| CN110031088B (en) | Electronic equipment fault detection method, device, equipment and range hood | |
| WO2020052147A1 (en) | Monitoring device fault detection method and apparatus | |
| US10115298B2 (en) | Method of trend analysis and automatic tuning of alarm parameters | |
| EP3731199A1 (en) | Smoke detector for event classification and methods of making and using same | |
| CN110275094A (en) | A kind of high-tension cable shelf depreciation acousto-optic associated detecting method and system | |
| US8805639B1 (en) | Idle detection for improving fuel consumption efficiency in a vehicle | |
| US7557728B1 (en) | Using audio to detect changes to the performance of an application | |
| US20150006972A1 (en) | Method for Detecting Anomalies in a Time Series Data with Trajectory and Stochastic Components | |
| EP2399104A1 (en) | Method and apparatus for monitoring and analyzing vibrations in rotary machines | |
| JP2012242214A (en) | Strange noise inspection method and strange noise inspection device | |
| CN102992129A (en) | Abnormity diagnosis device and method for elevator | |
| JP2010189100A (en) | Apparatus and method for diagnosis of abnormal condition | |
| RU2011151543A (en) | METHOD AND DEVICE FOR DETECTING LEAKS IN THE FUEL SUPPLY SYSTEM | |
| US20180131560A1 (en) | Content-aware anomaly detection and diagnosis | |
| US11777982B1 (en) | Multidimensional security situation real-time representation method and system and applicable to network security | |
| CN112777443A (en) | Elevator operation evaluation method, device and computer readable medium | |
| JP2012166935A (en) | Abnormal sound detection device for elevator | |
| US10742535B2 (en) | Monitoring a resource consumption of an application | |
| JP2011037525A (en) | Abnormal sound detection apparatus for elevator | |
| JP2001318031A (en) | Method for diagnosing abnormality of device | |
| WO2023053024A1 (en) | Method for identifying and characterizing, by using artificial intelligence, noises generated by a vehicle braking system | |
| US20150347213A1 (en) | Apparatus and method for system monitoring | |
| KR20160039078A (en) | Method for analyzing signal of power plant pipe |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20210511 |