CN208516744U - Escalator lubricating status monitors system and the voice data collection device for it - Google Patents
Escalator lubricating status monitors system and the voice data collection device for it Download PDFInfo
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- CN208516744U CN208516744U CN201721904267.9U CN201721904267U CN208516744U CN 208516744 U CN208516744 U CN 208516744U CN 201721904267 U CN201721904267 U CN 201721904267U CN 208516744 U CN208516744 U CN 208516744U
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Abstract
The utility model discloses escalator lubricating status monitoring system and for its voice data collection device.It includes voice data collection device that escalator lubricating status, which monitors system, is arranged near the component that needs of escalator monitor, the voice data of collecting part sending；Data sending device sends data relevant to the voice data that component issues；Cloud processor receives data relevant to the voice data that component issues, the voice data threshold value of the component of the normal operation in its database with cloud processor is compared, compared result responds.Voice data collection device includes circuit box, arranges that circuit board and digital microphone therein, at least one of roof and bottom wall of circuit box are provided with voice pickup hole.The utility model can be in any environment; it obtains data, data is analyzed, and do not depend on the subjective judgement of manpower, accurately look-ahead gets rusty, lacks the failures such as lubricating oil without shutting down; maintenance time and money are saved, elevator safety and riding comfort are improved.
Description
Technical field
The utility model relates to escalator lubricating status monitoring system and for its sound collection means, more specifically
Ground is related to collecting voice data by sound collection means to judge the escalator lubricating status prison of escalator lubricating status
Examining system and sound collection means for it.
Background technique
Escalator is widely used in a variety of occasions, such as department stores, office building and communal facility and various interiors
Or outdoor environment, escalator need to its mechanical drives and it is relevant to the relative motion of escalator even running its
Its pairs of metal contact element carries out lubrication appropriate.And the occasion and environment of escalator lubricating status and escalator application
Temperature, humidity and dust it is closely related, escalator at department stores and communal facility since the number used is more, because
The speed of this lubricating status possible deviation is relatively fast, and the frequency for needing to safeguard is relatively high, and outdoor environment is due to opposite
Badly, therefore escalator lubricating status may also be deteriorated soon, and the frequency for needing to safeguard is also just relatively high, therefore each
The lubricating status of staircase is different.It is often necessary to maintenance personnel continually goes site inspection equipment and checks its lubricating status,
It is largely worked, and the manufacturer of escalator or user are also difficult uniformly to grasp and understand all or its institute for using
There is the lubricating status of escalator.
And the lubricating status of escalator be the safety of escalator, passenger comfort an important factor for one of.?
The information age of information prosperity needs the lubricating status of improved escalator to monitor system, is capable of providing escalator profit
The long-range monitoring and initial data relevant to staircase lubricating status of sliding state, and the initial data can be handled
And analysis, the information of the lubricating status of escalator can be provided to the property of escalator or manufacturer rapidly in real time, and
Manpower can not depended on to give warning in advance to the lubrication trouble of escalator, prevent ahead of time and avoid occurring, and can be to system
It makes quotient and user provides the reference data of escalator operation.
Utility model content
The purpose of the utility model is to provide a kind of monitorings of the lubricating status of escalator that can satisfy the demand
The voice data collection device that system and the monitoring system use.
According to the utility model in a first aspect, providing a kind of escalator lubricating status monitoring system, including voice data
Collection device is arranged near the component that the needs of escalator monitor, the sound issued for collecting the component for needing to monitor
Data；Data sending device, for sending data relevant to the voice data that component issues；Cloud processor, for connecing
Data relevant to the voice data that component issues are received, and will be at data relevant to the voice data that component issues and cloud
The voice data threshold value for managing the component of the normal operation in the database of device compares, and cloud processor compared result makes sound
It answers.
Preferably, staircase lubricating status monitoring system further includes local data processing unit, the sound issued with component
The relevant data of data are by local data processing unit treated voice data.
Preferably, data relevant to the voice data that component issues are the voice data of voice data collection device, cloud
It holds processor after receiving the voice data, voice data is handled, it then again will be at the voice data and cloud
The voice data threshold value for managing the component of the normal operation in the database of device compares.
Preferably, book data processing equipment is obtained by bandpass filter in [FIt is low, FIt is high] being issued with component in range
The relevant data of voice data.
Preferably, cloud processor is obtained by bandpass filter in [FIt is low, FIt is high] sound issued with component in range
The relevant data of data, then again by the sound of the component of the normal operation in the voice data and the database of cloud processor
Data threshold compares.
Preferably, local data processing unit calculates the characteristic value of voice data, as the voice data issued with component
Relevant data.
Preferably, cloud processor calculates the characteristic value of voice data, as relevant to the voice data that component issues
Data, then again by the voice data threshold value phase of the voice data and the component of the normal operation in the database of cloud processor
Compare.
Preferably, if comparison result is greater than the threshold value, cloud processor issues the report that escalator needs to lubricate
Alert signal, and trigger customer service system or directly contact maintenance personal.
Preferably, cloud processor includes staircase database, and storage staircase operation history data, staircase parameter and maintenance are gone through
History.
Preferably, cloud processor is compared by the methods of statistics, analysis, artificial intelligence and machine learning and is issued with component
The relevant data of voice data and threshold value.
Preferably, cloud processor stores data relevant to the voice data that component issues.
Preferably, voice data collection device is digital microphone component.
Preferably, the setting of digital microphone component is contacted in driving device with drive chain contact position, driving chain and sprocket
Near position or step bootstrap block and skirtboard contact position.
Preferably, local data processing unit is microcomputer or dsp chip.
Preferably, microcomputer transfers data to cloud processor by wireless network.
Preferably, if one group staircase of the voice data from same client position, and have similar voice data mould
Formula, then local data processing unit can only select one voice data in this group of staircase to be handled.
On the other hand according to the utility model, a kind of escalator lubricating status detection system, including voice data are provided
Collection device is arranged near the component that the needs of escalator monitor, the sound issued for collecting the component for needing to monitor
Data；Local data processing unit, in processing locality voice data, audio data transmitting is sent to cloud processor or at this
Result is responded after ground processing voice data.
According to the another aspect of the utility model, a kind of escalator lubricating status detection system, including cloud processing are provided
Device, the sound number sent for receiving the remote data collection entity being arranged near the component that the needs of escalator monitor
According to handling the voice data, and responded to processing result.
According to the another aspect of the utility model, a kind of sound for aforementioned escalator lubricating status monitoring system is provided
Transacter, wherein the voice data collection device includes circuit board, one or more digital microphones, and closing electricity
The circuit box of road plate and digital microphone, circuit box include roof, bottom wall and side wall, the setting of at least one of roof and bottom wall
There is voice pickup hole.
Preferably, voice pickup hole is provided with waterproof membrane on the inside or outside of the wall at place, prevents outside water or moisture
Into digital microphone component.
Preferably, the inside of the wall where voice pickup hole is arranged in digital microphone, and below waterproof membrane, or setting exists
On circuit board.
The monitoring system of the lubricating status of the escalator of each embodiment according to the present utility model can in any environment,
It including indoor or outdoor, quiet and noisy environment, obtains data and data is analyzed, and the subjectivity for not depending on manpower is sentenced
Disconnected, accurately look-ahead gets rusty, lacks the failures such as lubricating oil without shutting down, and saves maintenance time and money,
Improve safety and the riding comfort of elevator.
Detailed description of the invention
Fig. 1 is the flow chart of the first embodiment of escalator lubricating status monitoring system according to the present utility model.
Each in Fig. 2 (a), Fig. 2 (b) and Fig. 2 (c) is to pass through bandpass filter in first embodiment shown in Fig. 1
The Spectrogram function for filtering out the process of low-frequency noise and high-frequency noise draws spectrogram.
Fig. 3 is that the root-mean-square value of the voice data calculated in first embodiment shown in Fig. 1 and the relationship of threshold value are illustrated
Figure.
Fig. 4 is the flow chart of the second embodiment of escalator lubricating status monitoring system according to the present utility model.
Fig. 5 (a), 5 (b) and 5 (c) each show one of knocking noise data pattern of different classifications.
Fig. 6 is the analysis process schematic diagram of classifier 8.
Fig. 7 is the flow chart of the 3rd embodiment of escalator lubricating status monitoring system according to the present utility model.
Fig. 8 is the flow chart of the fourth embodiment of escalator lubricating status monitoring system according to the present utility model.
Fig. 9 is the flow chart of the 5th embodiment of escalator lubricating status monitoring system according to the present utility model.
Figure 10 is the flow chart of the sixth embodiment of escalator lubricating status monitoring system according to the present utility model.
Figure 11 is that the voice data of the escalator lubricating status monitoring system for various embodiments of the utility model is collected
The first embodiment of device 1.
Figure 12 is that the voice data of the escalator lubricating status monitoring system for various embodiments of the utility model is collected
The second embodiment of device 1.
Figure 13 is that the voice data of the escalator lubricating status monitoring system for various embodiments of the utility model is collected
The 3rd embodiment of device 1.
Figure 14 is that the voice data of the escalator lubricating status monitoring system for various embodiments of the utility model is collected
The fourth embodiment of device 1.
Specific embodiment
The utility model relates to escalator lubricating status to monitor system, and the critical component of escalator, which needs to lubricate, to be come really
The safety and normal operation of escalator are protected, related component mainly includes drive chain of escalator and drive chain of escalator
Wheel and step bootstrap block and skirtboard.The component is relative to the pairs of metal parts moved each other, is normally lubricating
Under state, smooth motion and the uniform lesser sound of sending between pairs of metal parts, and lacking lubricating oil state
Or get rusty, be covered with dust all under state, then the movement between metal parts will appear clamping stagnation, pause phenomena such as, and issue more
Ear-piercing noise.
The escalator lubricating status monitoring system of the utility model is collected metal parts by transacter and is issued
Voice data, and analyze the voice data, whether the lubricating status to judge escalator normal.Transacter is logical
Often it is digital microphone component, the drive chain of escalator and drive chain of escalator wheel phase of the gear-box of escalator is set
Near contact position, or setting near step bootstrap block and skirtboard touching position, can also be set as needed below the step band front shroud
It sets on truss close near motor and drive chain touching position, or the component of any required monitoring to contact with each other.The Mike
The microphone that wind component uses can be common mobile microphone, be also possible to ultrasonic microphone, can recorde sound wave
File, and support playback function.Digital microphone component constantly collects voice data, and stores audio files, the sound
Sound file can be played when needed.
The basic conception of the utility model is described below by specific embodiment according to the present utility model.
Fig. 1 is the flow chart of the first embodiment of escalator lubricating status monitoring system according to the present utility model.
In the first embodiment, 1 be voice data collection device, digit collection device 1 collect drive chain of escalator and
The voice data of step bootstrap block and skirtboard touching position below drive chain of escalator wheel touching position or step band front shroud, should
The wave file of voice data is stored in the local data processing unit 2 of local device 6, and passes through bandpass filter 3
It is handled.Then by audio data transmitting device 4, audio data transmitting is sent to cloud processor 5.
At bandpass filter 3, voice data is by carry out noise filtering, to obtain in particular frequency range [FIt is low,FIt is high]
Between voice data FIt is lowUsually in 1000~5000Hz, FIt is highTypically larger than 10000Hz, because most have can for the portion of sound data
It can be related to the frictional noise between metal and metal.This can be by drawing frequency using Spectrogram function for voice data
Spectrogram carries out.
The process that low-frequency noise and high-frequency noise are filtered out by bandpass filter is schematically shown in Fig. 2
Spectrogram function draws spectrogram.Fig. 2 (a) is voice signal when the normal chain not got rusty is in contact with sprocket wheel,
It is concentrated mainly on low-frequency range.Fig. 2 (b) is the voice signal when chain to get rusty is in contact with sprocket wheel, is low-frequency noise
With the mixing of high frequency peaks.Fig. 2 (c) be by applying frequency range be [5000,15000] bandpass filter only reservation with
The relevant isolated acoustic pattern of situation of getting rusty.
Then, the Key Performance Indicator (KPI) of the voice data through filtering is calculated.It is contacted between metalwork-metalwork
The relevant KPI of the noise of sending can be the root-mean-square value of voice data peak value, in this embodiment, calculate the sound through filtering
The root-mean-square value of data peaks.
The root-mean-square value is sent to cloud processor 5 via audio data transmitting device 4, beyond the clouds in processor 5, by this
Root-mean-square value is compared with the threshold value of setting, if the root-mean-square value is higher than threshold value, cloud processor is responded, and issues report
The alarm signal is transferred to client service center by alert signal, or directly liaison maintenance personnel carry out escalator lubricated maintenance.This ratio
It is schematically shown in Fig. 3 compared with relationship.
The KPI threshold value can be obtained by the experiment of different lubrication states in the lab, or be obtained based on experiment.
Fig. 4 is the flow chart of the second embodiment of escalator lubricating status monitoring system according to the present utility model.
In a second embodiment, 1 be voice data collection device, digit collection device 1 collect drive chain of escalator and
The voice data of step bootstrap block and skirtboard touching position below drive chain of escalator wheel touching position or step band front shroud, should
The wave file of voice data is stored in the local data processing unit 2 of local device 6.Then local data processing unit
2 calculate the characteristic value of the voice data, send cloud processor 5 by data sending device 4 for the characteristic value of calculating.
Fig. 5 is the comparison of the knocking noise data pattern of different classifications, sound number when wherein a is step dislocation failure
According to mode, voice data mode when b gets rusty for drive chain, c is voice data mode when operating normally.It can be seen that not
It is different with classification knocking noise data pattern, therefore characteristic value is also different.
In this embodiment, characteristic value calculating is carried out to voice data using local data processing unit 2.Characteristic value can be with
It is zero-crossing rate, energy, Energy-Entropy, spectral centroid, frequency spectrum entropy, spectral flux, spectral roll-off, frequency spectrum cepstrum coefficient, chroma vector
Or chromaticity distortion etc..
Then pass through data sending device 4 is sent to cloud processor 5 to the characteristic value of the calculating, beyond the clouds at processor 5,
By using history or the sound fault data of storage training classifier 8, classifier 8 uses neural network algorithm, by spy
The adjustment of vector is levied, preferably to indicate the characteristic of different faults classification.
Fig. 6 is the analysis process schematic diagram of classifier 8, and the characteristic value being computed received is transmitted to three by classifier 8
A neuron carries out analytical calculation for different failure modes by each neuron, and output is directed to each failure modes
Prediction confidence intervals, according to the confidence interval export analysis as a result, the result instruction may occur or not occur that failure
Classification.
Fig. 7 is the flow chart of the 3rd embodiment of escalator lubricating status monitoring system according to the present utility model.
In the third embodiment, 1 be voice data collection device, digit collection device 1 collect drive chain of escalator and
The voice data of step bootstrap block and skirtboard touching position below drive chain of escalator wheel touching position or step band front shroud, should
The wave file of voice data directly passes through data sending device 4 and is sent to cloud processor 5, beyond the clouds at processor 5, passes through
Bandpass filter 3 carries out noise filtering to voice data, to obtain in particular frequency range [FIt is low,FIt is high] between sound number
According to FIt is lowUsually in 1000~5000Hz, FIt is highTypically larger than 10000Hz, then, cloud processor 5 calculate the sound number through filtering
According to Key Performance Indicator (KPI), and the root-mean-square value is compared with the threshold value of setting.It is indirectly with metalwork-metalwork
The relevant KPI of the noise triggered out can be the root-mean-square value of voice data peak value, in this embodiment, calculate the sound through filtering
The root-mean-square value of sound data peaks.If the root-mean-square value is higher than threshold value, cloud processor is responded, and issues alarm signal
Number, which is transferred to client service center, or directly liaison maintenance personnel carry out escalator lubricated maintenance.This compared
Journey is schematically shown in Fig. 3.The KPI threshold value can be obtained by the experiment of different lubrication states in the lab, or based on real
Test acquisition.
Fig. 8 is the flow chart of the fourth embodiment of escalator lubricating status monitoring system according to the present utility model.
In the fourth embodiment, 1 be voice data collection device, digit collection device 1 collect drive chain of escalator and
The voice data of step bootstrap block and skirtboard touching position below drive chain of escalator wheel touching position or step band front shroud, should
The wave file of voice data directly passes through data sending device 4 and is sent to cloud processor 5, beyond the clouds at processor 5, calculates
Then the characteristic value of the voice data is adopted by using history or the sound fault data of storage training classifier 8, classifier 8
With neural network algorithm, by the adjustment to feature vector, preferably to indicate the characteristic of different faults classification.
In this embodiment, characteristic value calculating is carried out using voice data of the cloud processor 5 to different classifications.Characteristic value
It can be zero-crossing rate, energy, Energy-Entropy, spectral centroid, frequency spectrum entropy, spectral flux, spectral roll-off, frequency spectrum cepstrum coefficient, coloration
Vector or chromaticity distortion etc..
Fig. 5 is the comparison of the knocking noise data pattern of different classifications, sound number when wherein a is step dislocation failure
According to mode, voice data mode when b gets rusty for drive chain, c is voice data mode when operating normally.It can be seen that not
It is different with classification knocking noise data pattern, therefore characteristic value is also different.
Fig. 6 is the analysis process schematic diagram of classifier 8, and the characteristic value being computed received is transmitted to three by classifier 8
A neuron carries out analytical calculation for different failure modes by each neuron, and output is directed to each failure modes
Prediction confidence intervals, according to the confidence interval export analysis result.
The difference of 3rd embodiment and fourth embodiment and first embodiment and second embodiment essentially consists in, real first
It applies the data processing in the local device 6 carried out in example and second embodiment to carry out in processor 5 beyond the clouds, but in this way may be used
The expense carried out data transmission from local device 6 to cloud processor 5 can be will increase.
Fig. 9 is the flow chart of the 5th embodiment of escalator lubricating status monitoring system according to the present utility model.
In the 5th embodiment, 1 be voice data collection device, digit collection device 1 collect drive chain of escalator and
The voice data of step bootstrap block and skirtboard touching position below drive chain of escalator wheel touching position or step band front shroud, should
The wave file of voice data is locally carrying out noise filtering to voice data by bandpass filter 3, to obtain specific
Frequency range [FIt is low,FIt is high] between voice data, FIt is lowUsually in 1000~5000Hz, FIt is highTypically larger than 10000Hz, then, this
Ground data processing equipment 2 calculates the Key Performance Indicator (KPI) of the voice data through filtering, and by the root-mean-square value and is arranged
Threshold value compare.The relevant KPI of the noise of sending is contacted between metalwork-metalwork can be the equal of voice data peak value
Root value calculates the root-mean-square value of the voice data peak value through filtering in this embodiment.Local data processing unit 2 can be with
Further the root-mean-square value is compared with a threshold value of setting, which schematically shows in Fig. 3, if this is square
Root is higher than threshold value, then local data processing unit 2 responds 7, which can be sending alarm signal, by the alarm
Signal is transferred to client service center, or directly liaison maintenance personnel carry out escalator lubricated maintenance.Local data processing unit 2
Can cloud processor only be sent by the root-mean-square value.The KPI threshold value can be real by different lubrication states in the lab
Acquisition is tested, or is obtained based on experiment.
Figure 10 is the flow chart of the sixth embodiment of escalator lubricating status monitoring system according to the present utility model.
In the sixth embodiment, 1 be voice data collection device, digit collection device 1 collect drive chain of escalator and
The voice data of step bootstrap block and skirtboard touching position below drive chain of escalator wheel touching position or step band front shroud, should
The wave file of voice data directly calculates the characteristic value of voice data local 6 by local data processing unit 2, then leads to
The sound fault data training classifier 8 of usage history or storage is crossed, classifier 8 uses neural network algorithm, by feature
The adjustment of vector, preferably to indicate the characteristic of different faults classification.In this embodiment, characteristic value can be zero-crossing rate, energy
Amount, Energy-Entropy, spectral centroid, frequency spectrum entropy, spectral flux, spectral roll-off, frequency spectrum cepstrum coefficient, chroma vector or chromaticity distortion
Deng.
Fig. 5 is the comparison of the knocking noise data pattern of different classifications, sound number when wherein a is step dislocation failure
According to mode, voice data mode when b gets rusty for drive chain, c is voice data mode when operating normally.It can be seen that not
It is different with classification knocking noise data pattern, therefore characteristic value is also different.
Fig. 6 is the analysis process schematic diagram of classifier 8, and the characteristic value being computed received is transmitted to three by classifier 8
A neuron carries out analytical calculation for different failure modes by each neuron, and output is directed to each failure modes
Prediction confidence intervals, according to the confidence interval export analysis result.Local data processing unit can respond the result,
The response is that can be sending alarm signal, which is transferred to client service center, or directly liaison maintenance personnel carry out
Escalator lubricated maintenance is also possible to directly send the result to cloud processor.
Each embodiment according to the present utility model escalator lubricating status monitoring system can in any environment, including
Indoor or outdoor, quiet and noisy environment obtains data and analyzes data, and do not depend on the subjective judgement of manpower,
Accurately look-ahead gets rusty, lacks the failures such as lubricating oil without shutting down, and saves maintenance time and money, improves
The safety of elevator and riding comfort.
Figure 11 is that the voice data of the escalator lubricating status monitoring system for various embodiments of the utility model is collected
The first embodiment of device 1.In the embodiment, voice data collection device 1 includes sensor circuit box 11, the sensor circuit
Box 11 includes roof 12, bottom wall 13 and side wall 14, and voice pickup hole 15 is defined in roof 12, which is through-hole.Sound
Transacter 1 further includes setting in the indoor sound transducer 16 of chamber, which is supported on by bracket 17
On the bottom wall 13 of sensor circuit box.The opening towards chamber in voice pickup hole, on sound transducer 16, setting
There is waterproof membrane 18, which prevents water or moisture from entering in voice data collection device 1, and has good sound
Transmission performance.
Figure 12 is that the voice data of the escalator lubricating status monitoring system for various embodiments of the utility model is collected
The second embodiment of device 1.It in the embodiment, is different from the first embodiment in, sound transducer 16 is directly attached to
The roof 12 of sensor circuit box 11, below voice pickup hole 15, also below waterproof membrane 18.
Figure 13 is that the voice data of the escalator lubricating status monitoring system for various embodiments of the utility model is collected
The 3rd embodiment of device 1.It in the embodiment, is different from the first embodiment in, which is double
Side voice data collection device, the sound that promising through-hole is arranged in sensor circuit box 11 on roof 12 and bottom wall 13 respectively pick up
Hole 15 and 19 and two sound transducers 16 and 20 are taken, each sound transducer passes through bracket 17 and 21 respectively and is supported on top
On wall 12 and bottom wall 13, each voice pickup hole 15 and 19 is attached with waterproof membrane 18 and 22 in the opening towards chamber respectively.
Figure 14 is that the voice data of the escalator lubricating status monitoring system for various embodiments of the utility model is collected
The fourth embodiment of device 1.In the embodiment, the difference is that, which is double with second embodiment
Side voice data collection device, the sound that promising through-hole is arranged in sensor circuit box 11 on roof 12 and bottom wall 13 respectively pick up
Hole 15 and 19 and two sound transducers 16 and 20, each sound transducer is taken to be directly attached to roof 12 and bottom wall respectively
On 13, each voice pickup hole 15 and 19 is attached with waterproof membrane 18 and 22,18 He of waterproof membrane in the opening towards chamber respectively
22 between the sound transducer being attached towards the opening of chamber and corresponding opening in voice pickup hole 15 and 19.
It should be noted that the embodiment is merely exemplary, not should be is limitations of the present invention, more
Feature in a embodiment can be used in combination to obtain more embodiments of the utility model, the scope of the utility model
It is defined solely by the appended claims.Various deformation form and improved form can be made to the embodiment without departing from this reality
With novel range.
Claims (21)
1. a kind of escalator lubricating status monitors system, which is characterized in that including voice data collection device, be arranged automatic
Near the component that the needs of staircase monitor, for collecting the voice data of the component for needing to monitor sending；Data sending device is used
It is sent in by data relevant to the voice data that component issues；Cloud processor, for receiving the sound number issued with component
According to relevant data, and will be normal in the database of data relevant to the voice data that component issues and cloud processor
The voice data threshold value of the component of operating compares, and cloud processor compared result responds.
2. staircase lubricating status according to claim 1 monitors system, which is characterized in that staircase lubricating status monitoring system
System further includes local data processing unit, and data relevant to the voice data that component issues are by local data processing unit
Voice data after reason.
3. staircase lubricating status according to claim 1 monitors system, which is characterized in that the voice data issued with component
Relevant data are the voice data of voice data collection device, and cloud processor is after receiving the voice data, to sound
Sound data are handled, then again by the sound of the component of the normal operation in the voice data and the database of cloud processor
Data threshold compares.
4. staircase lubricating status according to claim 2 monitors system, which is characterized in that local data processing unit passes through
Bandpass filter is obtained in [FIt is low, FIt is high] the relevant data of the voice data issued to component in range.
5. staircase lubricating status according to claim 3 monitors system, which is characterized in that cloud processor is filtered by band logical
Wave device is obtained in [FIt is low, FIt is high] the relevant data of the voice data issued to component in range, then again by the voice data with
The voice data threshold value of the component of normal operation in the database of cloud processor compares.
6. staircase lubricating status according to claim 2 monitors system, which is characterized in that local data processing unit calculates
The characteristic value of voice data, as data relevant to the voice data that component issues.
7. staircase lubricating status according to claim 3 monitors system, which is characterized in that cloud processor calculates sound number
According to characteristic value, as data relevant to the voice data that component issues, then again by the voice data and cloud processor
Database in the voice data threshold value of component of normal operation compare.
8. staircase lubricating status according to any one of claim 1-3 monitors system, which is characterized in that if comparing knot
Fruit is greater than the threshold value, then cloud processor issues escalator and needs the alarm signal that lubricates, and trigger customer service system or
Directly contact maintenance personal.
9. staircase lubricating status according to any one of claim 1-3 monitors system, which is characterized in that cloud processor
Including staircase database, staircase operation history data, staircase parameter and maintenance history are stored.
10. staircase lubricating status according to any one of claim 1-3 monitors system, which is characterized in that cloud processing
Device compares data relevant to the voice data of component sending and threshold by statistics, analysis, artificial intelligence and learning by rote
Value.
11. staircase lubricating status according to any one of claim 1-3 monitors system, which is characterized in that cloud processing
Device stores data relevant to the voice data that component issues.
12. staircase lubricating status according to any one of claim 1-3 monitors system, which is characterized in that voice data
Collection device is digital microphone component.
13. staircase lubricating status according to claim 12 monitors system, which is characterized in that the setting of digital microphone component
It is attached in driving device and drive chain contact position, driving chain and sprocket contact position or step bootstrap block and skirtboard contact position
Closely.
14. staircase lubricating status according to any one of claim 1-3 monitors system, which is characterized in that local data
Processing unit is microcomputer or dsp chip.
15. staircase lubricating status according to claim 14 monitors system, which is characterized in that microcomputer passes through wireless
Network transfers data to cloud processor.
16. staircase lubricating status according to any one of claim 1-3 monitors system, which is characterized in that if sound
One group staircase of the data from same client position, and there is similar voice data mode, then local data processing unit can
One in this group of staircase voice data is only selected to be handled.
17. a kind of escalator lubricating status monitors system, which is characterized in that including voice data collection device, setting is certainly
Near the component that the needs of dynamic staircase monitor, for collecting the voice data of the component for needing to monitor sending；Local data processing
Device, in processing locality voice data, audio data transmitting is sent to cloud processor or after processing locality voice data
Result is responded.
18. a kind of escalator lubricating status monitors system, which is characterized in that including cloud processor, exist for receiving setting
The voice data that remote data collection entity near the component that the needs of escalator monitor is sent, carries out the voice data
Processing, and processing result is responded.
19. a kind of voice data for the monitoring system of escalator lubricating status described in any one of preceding claims is received
Acquisition means, which is characterized in that the voice data collection device includes circuit board, one or more digital microphones, and closing electricity
The circuit box of road plate and digital microphone, circuit box include roof, bottom wall and side wall, the setting of at least one of roof and bottom wall
There is voice pickup hole.
20. voice data collection device according to claim 19, which is characterized in that wall of the voice pickup hole at place
Inner or outer side is provided with waterproof membrane, prevents outside water or moisture from entering digital microphone component.
21. voice data collection device according to claim 20, which is characterized in that digital microphone setting is picked up in sound
The inside for taking the wall where hole, below waterproof membrane, or setting is on circuit boards.
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| Application Number | Priority Date | Filing Date | Title |
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| CN201721904267.9U CN208516744U (en) | 2017-12-29 | 2017-12-29 | Escalator lubricating status monitors system and the voice data collection device for it |
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| CN201721904267.9U CN208516744U (en) | 2017-12-29 | 2017-12-29 | Escalator lubricating status monitors system and the voice data collection device for it |
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| CN201721904267.9U Active CN208516744U (en) | 2017-12-29 | 2017-12-29 | Escalator lubricating status monitors system and the voice data collection device for it |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| 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 |
| CN112811293A (en) * | 2019-11-15 | 2021-05-18 | 奥的斯电梯公司 | Using internet of things sensors and sensor position analysis component frequency on escalator |
| US11795034B2 (en) | 2017-12-29 | 2023-10-24 | Kone Corporation | Escalator monitoring system, method, sound data collection device and fixture therefor |
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2017
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| 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 |
| US11795034B2 (en) | 2017-12-29 | 2023-10-24 | Kone Corporation | Escalator monitoring system, method, sound data collection device and fixture therefor |
| CN112811293A (en) * | 2019-11-15 | 2021-05-18 | 奥的斯电梯公司 | Using internet of things sensors and sensor position analysis component frequency on escalator |
| CN112811293B (en) * | 2019-11-15 | 2023-09-29 | 奥的斯电梯公司 | Component frequency analysis using internet of things sensors and sensor locations on escalator |
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