CN106219342B - Elevator self diagnosis and pre- diagnostic system and method based on time-frequency convert algorithm - Google Patents
Elevator self diagnosis and pre- diagnostic system and method based on time-frequency convert algorithm Download PDFInfo
- Publication number
- CN106219342B CN106219342B CN201610692327.9A CN201610692327A CN106219342B CN 106219342 B CN106219342 B CN 106219342B CN 201610692327 A CN201610692327 A CN 201610692327A CN 106219342 B CN106219342 B CN 106219342B
- Authority
- CN
- China
- Prior art keywords
- elevator
- failure
- frequency domain
- control system
- algorithm
- 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
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
- B66B5/0018—Devices monitoring the operating condition of the elevator system
-
- 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
-
- 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
- B66B5/02—Applications of checking, fault-correcting, or safety devices in elevators responsive to abnormal operating conditions
Landscapes
- Maintenance And Inspection Apparatuses For Elevators (AREA)
- Indicating And Signalling Devices For Elevators (AREA)
Abstract
The invention discloses a kind of elevator self diagnosis based on time-frequency convert algorithm and pre- diagnostic system and methods, the elevator self diagnosis and pre- diagnostic system include sensor and elevator control system, or including frequency converter and elevator control system, the sensor is connect with elevator control system, the frequency converter is connect with elevator control system, and the elevator control system includes data conversion module, data fusion module, judgment module, anomaly analysis module, exception/fault cancellation module and exception/fault information sending module.The present invention greatly reduces the human cost of company; reduce elevator stops echelon number; improve the experience and elevator service efficiency of passenger; simultaneously because diagnosing and solving exception or failure in advance; greatly improve Products technology content; industrial competition is improved, is conducive to company and popularization and brand foundation is carried out to lift product.
Description
Technical field
The present invention relates to a kind of elevator self diagnosis and pre- diagnostic system and methods, especially a kind of to be based on time-frequency convert algorithm
Elevator self diagnosis and pre- diagnostic system and method, belong to elevator diagnostic techniques field.
Background technique
Due to carrying out the continuous development of IT technology this year, the operational capability of computer or processor is more and more stronger, data storage
Space and mode also constantly expanding, simultaneously as the continuous transparence of information, the continuous improvement of the degree of social concern, now
To the safety of elevator device, stability etc., more stringent requirements are proposed.And the aggravation of current industry competition, skill in industry
The continuous improvement of art level, we are also required to propose the industry competition of higher elevator controlling, optimisation technique to promote our company
Power and core competitiveness.
However, existing major part solution is all based on the self diagnosis or remote monitoring system of the failure occurred,
More excellent has the scheme being automatically corrected to the partial fault occurred, or long-range cloud adjustment or technological guidance, but several
It is all based on the solution of the failure occurred.
Summary of the invention
The purpose of the present invention is to solve the defects of above-mentioned existing diagnostic techniques, provide a kind of based on time-frequency convert calculation
The elevator self diagnosis and pre- diagnostic system of method, the system greatly reduce the human cost of company, and reduce elevator stops echelon
Number, the experience and elevator service efficiency for improving passenger greatly mention simultaneously because diagnosing and solving exception or failure in advance
The high technology content of lift product, improves industrial competition, is conducive to that lift product promote and brand is established.
Another object of the present invention is to provide a kind of elevator self diagnosis and pre- diagnostic method based on time-frequency convert algorithm.
The purpose of the present invention can be achieved through the following technical solutions:
Elevator self diagnosis and pre- diagnostic system based on time-frequency convert algorithm, including sensor and elevator control system, institute
Sensor is stated to connect with elevator control system；
The sensor for acquiring the operation data of current elevator, and sends the data to elevator control system；
The elevator control system includes:
Data conversion module, for passing through time-frequency domain transfer algorithm logarithm after the data for receiving sensor transmission
According to time domain is carried out to the conversion of frequency domain, the frequency domain character value or indicatrix of current state of elevator are obtained；
Data fusion module, for passing through Intelligent Fusion algorithm, constantly to collected frequency domain character value or indicatrix
Carry out self study, and reduce the deviation range of frequency domain character value or indicatrix, then by after optimization frequency domain character value or spy
Sign curve is combined or gathers, and obtains current elevator operation value or condition curve；
Judgment module, for by judging whether current elevator operation value or condition curve generate outside setting range
Variation, judges whether current elevator has exception or failure to generate, and realizes the self-diagnostic function of exception or failure；
Anomaly analysis module, for when judging that current elevator has abnormal generate, whether analysis exception, which has, to lead to failure
Risk, to realize the pre- diagnostic function of failure.
As a kind of embodiment, for the sensor integration in elevator control system, which passes through internal communication
Mode is connect with elevator control system；
Or the sensor is placed outside outside elevator control system, the sensor by external wired or wireless communication mode with
Elevator control system connection；
The sensor obtains carriage running state data by moving up and down together with carriage.
As a kind of embodiment, the sensor includes six axis gyroscopes and weight sensor, the current elevator
Operation data includes the angular velocity data, acceleration information and weighing data of lift car.
As a kind of embodiment, the elevator control system further include:
Exception/fault cancellation module, for adjusting or repairing when having the risk for leading to failure or faulty generation extremely
Change operating status value or condition curve, so that controlling elevator eliminates exception or failure；
Exception/fault information sending module, for extremely have the risk for leading to failure or faulty generation when, will be different
Often or fault message is sent to mobile device or cloud, and notifies related personnel or relevant departments, by related personnel or correlation
Department eliminates exception or failure.
The purpose of the present invention can also be achieved through the following technical solutions:
Elevator self diagnosis and pre- diagnostic system based on time-frequency convert algorithm, including frequency converter and elevator control system, institute
Frequency converter is stated to connect with elevator control system；
The frequency converter for obtaining frequency conversion or the logical data of current elevator operation, and sends the data to elevator control
System processed；
The elevator control system includes:
Data conversion module, for passing through time-frequency domain transfer algorithm logarithm after the data for receiving frequency converter transmission
According to time domain is carried out to the conversion of frequency domain, the frequency domain character value or indicatrix of current state of elevator are obtained；
Data fusion module, for passing through Intelligent Fusion algorithm, constantly to collected frequency domain character value or indicatrix
Carry out self study, and reduce the deviation range of frequency domain character value or indicatrix, then by after optimization frequency domain character value or spy
Sign curve is combined or gathers, and obtains current elevator operation value or condition curve；
Judgment module, for by judging whether current elevator operation value or condition curve generate outside setting range
Variation, judges whether current elevator has exception or failure to generate, and realizes the self-diagnostic function of failure；
Anomaly analysis module, for when judging that current elevator has abnormal generate, whether analysis exception, which has, to lead to failure
Risk, to realize the pre- diagnostic function of failure.
As a kind of embodiment, the frequency converter is arranged in elevator control system, which passes through internal bus
Mode and elevator control system obtain the operation data or bottom status data of elevator control system.
As a kind of embodiment, the elevator control system further include:
Exception/fault cancellation module, for adjusting or repairing when having the risk for leading to failure or faulty generation extremely
Change operating status value or condition curve, so that controlling elevator eliminates exception or failure；
Exception/fault information sending module, for extremely have the risk for leading to failure or faulty generation when, will be different
Often or fault message is sent to mobile device or cloud, and notifies related personnel or relevant departments, by related personnel or correlation
Department eliminates exception or failure.
Another object of the present invention can be achieved through the following technical solutions:
Elevator self diagnosis and pre- diagnostic method based on time-frequency convert algorithm, the method pass through sensor and elevator controlling
System is realized, comprising:
The sensor acquires the operation data of current elevator, and sends the data to elevator control system；
The elevator control system passes through time-frequency domain transfer algorithm logarithm after the data for receiving sensor transmission
According to time domain is carried out to the conversion of frequency domain, the frequency domain character value or indicatrix of current state of elevator are obtained；
The elevator control system by Intelligent Fusion algorithm, constantly to collected frequency domain character value or indicatrix into
Row self study, and the deviation range of frequency domain character value or indicatrix is reduced, then by the frequency domain character value or feature after optimization
Curve is combined or gathers, and obtains current elevator operation value or condition curve；
The elevator control system is by judging whether current elevator operation value or condition curve generate setting range
Outer variation, judges whether current elevator has exception or failure to generate, and realizes the self-diagnostic function of exception or failure；
For the elevator control system when judging that current elevator has abnormal generate, whether analysis exception, which has, leads to failure
Risk, to realize the pre- diagnostic function of failure.
As a kind of embodiment, the method also includes:
The elevator control system is when having the risk for leading to failure or faulty generation extremely, adjustment or modification operation
State value or condition curve, so that controlling elevator eliminates exception or failure；
Or the elevator control system extremely have the risk for leading to failure or faulty generation when, by exception or failure
Information is sent to mobile device or cloud, and notifies related personnel or relevant departments, is eliminated by related personnel or relevant departments
Exception or failure.
As a kind of embodiment, the time-frequency domain transfer algorithm carries out the conversion of time domain to frequency domain to data, specifically
Are as follows:
By carrying out time domain to frequency to data based on Laplace transform algorithm, Fourier Transform Algorithm or Wavelet Packet Algorithm
The conversion in domain；
It is described to be merged frequency domain character value or indicatrix by Intelligent Fusion algorithm, specifically:
Operation is carried out by D-S argumentation theory algorithm, clustering algorithm or neural network algorithm, by frequency domain character value or feature
Curve is merged.
Another object of the present invention can also be achieved through the following technical solutions:
Elevator self diagnosis and pre- diagnostic method based on time-frequency convert algorithm, the method pass through frequency converter and elevator controlling
System is realized, comprising:
The frequency converter obtains frequency conversion or the logical data of current elevator operation, and sends the data to elevator controlling system
System；
The elevator control system passes through time-frequency domain transfer algorithm logarithm after the data for receiving frequency converter transmission
According to time domain is carried out to the conversion of frequency domain, the frequency domain character value or indicatrix of current state of elevator are obtained；
The elevator control system by Intelligent Fusion algorithm, constantly to collected frequency domain character value or indicatrix into
Row self study, and the deviation range of frequency domain character value or indicatrix is reduced, then by the frequency domain character value or feature after optimization
Curve is combined or gathers, and obtains current elevator operation value or condition curve；
The elevator control system is by judging whether current elevator operation value or condition curve generate setting range
Outer variation, judges whether current elevator has exception or failure to generate, and realizes the self-diagnostic function of exception or failure；
For the elevator control system when judging that current elevator has abnormal generate, whether analysis exception, which has, leads to failure
Risk, to realize the pre- diagnostic function of failure.
As a kind of embodiment, the method also includes:
The elevator control system is when having the risk for leading to failure or faulty generation extremely, adjustment or modification operation
State value or condition curve, so that controlling elevator eliminates exception or failure；
Or the elevator control system extremely have the risk for leading to failure or faulty generation when, by exception or failure
Information is sent to mobile device or cloud, and notifies related personnel or relevant departments, is eliminated by related personnel or relevant departments
Exception or failure.
As a kind of embodiment, the time-frequency domain transfer algorithm carries out the conversion of time domain to frequency domain to data, specifically
Are as follows:
The time-frequency domain transfer algorithm carries out the conversion of time domain to frequency domain to data, specifically:
By carrying out time domain to frequency to data based on Laplace transform algorithm, Fourier Transform Algorithm or Wavelet Packet Algorithm
The conversion in domain；
It is described that self study is constantly carried out to collected frequency domain character value or indicatrix by Intelligent Fusion algorithm, and
Reduce the deviation range of frequency domain character value or indicatrix, then by after optimization frequency domain character value or indicatrix be combined
Or set, specifically:
Operation is carried out by D-S argumentation theory algorithm, clustering algorithm or neural network algorithm, constantly to collected frequency domain
Characteristic value or indicatrix carry out self study, and reduce the deviation range of frequency domain character value or indicatrix, after then optimizing
Frequency domain character value or indicatrix be combined or gather；
Whether the analysis has the risk for leading to failure extremely, specifically:
When elevator is run up and down, detect that some range appearance one of speed of service curve is small in the process of running
Pulse, the pulse beyond allow speed of service error range, then judge there may be steel cable skidding risk, prompting maintenance
Personnel are note that and eliminate the potential security risk when safeguarding next time.
The present invention have compared with the existing technology it is following the utility model has the advantages that
1, the present invention acquires the operation data of current elevator by sensor, or obtains current elevator by frequency converter and run
Frequency conversion or logical data, elevator control system pass through the continuous self study to daily car movement data, accurate optimization elevator
Database when normal condition does not need a large amount of additional data space, saves cost；Elevator control system passes through
Time-frequency domain transfer algorithm carries out time domain to the conversion of frequency domain to data, obtains frequency domain character value or the spy of current state of elevator
Curve is levied, and is merged frequency domain character value or indicatrix by Intelligent Fusion algorithm, obtains current elevator operation
Precise information judge whether current elevator has exception or failure to generate according to the precise information of current elevator operation,
The self-diagnostic function of realization exception or failure, when judging that current elevator has abnormal generate, whether analysis exception, which has, leads to event
The risk of barrier, to realize the pre- diagnostic function of failure.
2, elevator control system of the invention adjusts immediately when having the risk for leading to failure or faulty generation extremely
Or operating status value or condition curve are modified, so that controlling elevator eliminates exception or failure, or exception or fault message are sent
It to mobile device or cloud, and notifies related personnel or relevant departments, eliminates abnormal or event by related personnel or relevant departments
Barrier, due to diagnosing and solving exception or failure in advance, greatly improves the technology content of lift product, it is competing to improve industry
Power is striven, is conducive to lift product and promote and brand foundation.
3, the present invention abnormal conditions basic or small by analysis, can sensed in advance failure generation, can be immediately
Adjustment, or notify related personnel or be adjusted operation have stronger intelligence in time；Simultaneously as being fast failure
Self diagnosis even fault pre-diagnosing, so elevator maintenance staff completely can be in each example diagnosing to after exception or failure
Operation is maintained or replaced etc. to elevator associated components when row maintenance, the human cost of company is greatly reduced, reduces electricity
Ladder stops echelon number, improves the experience and elevator service efficiency of passenger.
Detailed description of the invention
Fig. 1 be the embodiment of the present invention 1 elevator self diagnosis based on time-frequency convert algorithm and pre- diagnostic system structural block diagram.
Fig. 2 be the embodiment of the present invention 2 elevator self diagnosis based on time-frequency convert algorithm and pre- diagnostic system structural block diagram.
Fig. 3 is the elevator self diagnosis and pre- diagnostic method flow chart based on time-frequency convert algorithm of the embodiment of the present invention 3.
Fig. 4 is the elevator self diagnosis and pre- diagnostic method flow chart based on time-frequency convert algorithm of the embodiment of the present invention 4.
Fig. 5 is the elevator self diagnosis and pre- diagnostic method flow chart based on time-frequency convert algorithm of the embodiment of the present invention 5.
Specific embodiment
Present invention will now be described in further detail with reference to the embodiments and the accompanying drawings, but embodiments of the present invention are unlimited
In this.
Embodiment 1:
As shown in Figure 1, the elevator self diagnosis and pre- diagnostic system of the present embodiment include sensor and elevator control system, institute
Stating sensor can integrate in elevator control system, or be placed outside outside elevator control system, and the present embodiment is external by sensor
In outside elevator control system, which is connect by external wired or wireless communication mode with elevator control system, by with
Carriage moves up and down together obtains carriage running state data；Wherein:
The sensor for acquiring the operation data of current elevator, and sends the data to elevator control system；The biography
Sensor includes six axis gyroscopes and weight sensor, therefore the operation data of current elevator includes the elevator of six axis gyroscopes acquisition
The lift car weighing data of carriage angular velocity data, acceleration information and weight sensor acquisition.
The elevator control system include data conversion module, data fusion module, judgment module, anomaly analysis module,
Exception/fault cancellation module and exception/fault information sending module, the concrete function of modules are as follows:
The data conversion module, for passing through time-frequency domain transfer algorithm after the data for receiving sensor transmission
Time domain is carried out to the conversion of frequency domain to data, obtains the frequency domain character value or indicatrix of current state of elevator；Wherein, time domain-
Frequency domain transfer algorithm can be for based on Laplace transform algorithm, Fourier Transform Algorithm or Wavelet Packet Algorithm, these three algorithms
All it is currently used time-frequency domain transfer algorithm, the conversion of time domain to frequency domain, the present embodiment can be realized by substituting into formula
It is preferred that using Wavelet Packet Algorithm, since Wavelet Packet Algorithm has adaptive characteristic, therefore elevator number of run is more, acquired number
According to more, the data that Wavelet Packet Algorithm obtains are more accurate；
The data fusion module, for passing through Intelligent Fusion algorithm, constantly to collected frequency domain character value or feature
Curve carries out self study, and reduces the deviation range of frequency domain character value or indicatrix, then by the frequency domain character value after optimization
Or indicatrix is combined or gathers, and obtains current elevator operation value or condition curve；Wherein, Intelligent Fusion algorithm can
Think D-S argumentation theory algorithm, clustering algorithm or neural network algorithm, it is preferred to use neural network algorithm；
The judgment module, for by judging whether current elevator operation value or condition curve generate setting range
Outer variation, judges whether current elevator has exception or failure to generate, and realizes the self-diagnostic function of exception or failure；
For the angular velocity data of six axis gyroscopes acquisition, in running process of elevator constantly and normal data is to score
Analysis will generate an abnormity diagnosis when detecting that data and normal data are different or deviation is larger, prompt guide rail there may be
The case where out-of-flatness or serious wear；
For the acceleration information of six axis gyroscopes acquisition, the rate curve of acquisition and normal speed curve are compared
Analysis then generates abnormity diagnosis, elevator is prompted there may be velocity anomaly or to tremble when the speed data exception for detecting certain period
The case where innervation aggravation；
For the weighing data of weight sensor acquisition, by the weighing curve and normalized curve data comparison point after operation
Analysis prompts to be likely to occur steel rope breaking or steel cable skids if the somewhere of the curve there are data exception, generates an exception
Situation or elevator shake aggravation, need to be adjusted elevator or overhaul；
Anomaly analysis module, for when judging that current elevator has abnormal generate, whether analysis exception, which has, to lead to failure
Risk, to realize the pre- diagnostic function of failure；
In the present embodiment, whether analysis is abnormal the risk for leading to failure, specifically:
When elevator is run up and down, detect that some range appearance one of speed of service curve is small in the process of running
Pulse, the pulse beyond allow speed of service error range, then judge there may be steel cable skidding risk, prompting maintenance
Personnel are note that and eliminate the potential security risk when safeguarding next time.
Exception/fault cancellation module, for adjusting or repairing when having the risk for leading to failure or faulty generation extremely
Change operating status value or condition curve, so that controlling elevator eliminates exception or failure；
Exception/fault information sending module, for extremely have the risk for leading to failure or faulty generation when, will be different
Often or fault message is sent to mobile device or cloud, and notifies related personnel or relevant departments, by related personnel or correlation
Department eliminates exception or failure.
Embodiment 2:
As shown in Fig. 2, the elevator self diagnosis and pre- diagnostic system of the present embodiment include frequency converter and elevator control system, institute
It states frequency converter to connect with elevator control system, the frequency converter is arranged in elevator control system, which passes through internal total
Line mode and elevator control system obtain the operation data or bottom status data of elevator control system；Wherein:
The frequency converter, for obtaining frequency conversion or the logical data of current elevator operation, such as the input and output electricity of master control borad
Stream, voltage value, inductance value, temperature value of certain particular module etc., and send the data to elevator control system；
The elevator control system include data conversion module, data fusion module, judgment module, anomaly analysis module,
Exception/fault cancellation module and exception/fault information sending module, the concrete function of modules are as follows:
Data conversion module, for passing through time-frequency domain transfer algorithm logarithm after the data for receiving frequency converter transmission
According to time domain is carried out to the conversion of frequency domain, the frequency domain character value or indicatrix of current state of elevator are obtained；
Data fusion module, for passing through Intelligent Fusion algorithm, constantly to collected frequency domain character value or indicatrix
Carry out self study, and reduce the deviation range of frequency domain character value or indicatrix, then by after optimization frequency domain character value or spy
Sign curve is combined or gathers, and obtains current elevator operation value or condition curve；
Judgment module, for by judging whether current elevator operation value or condition curve generate outside setting range
Variation, judges whether current elevator has exception or failure to generate, and realizes the self-diagnostic function of exception or failure；
The data such as master control borad electric current, voltage, induction reactance for acquisition will compare and analyze after its operation with normal value,
If its variation range is more than agreement range, an abnormity diagnosis is generated, prompting elevator master control, there may be poor contacts, element
Situations such as aging, device failure；
Power or energy consumption data are run for the elevator of acquisition, compared after operation with normal power or energy consumption data point
Analysis generates an abnormity diagnosis, there may be ageing equipment or damages for prompt if the data variation range is more than agreement range
Situation needs to replace relevant device or overhauled；
For the elevator heat dissipation data of acquisition, the data after operation are compared analysis with normal value, in conjunction with practical feelings
Condition prompts the possible temperature of elevator(lift) machine room excessively high or may have component old if the data generate abnormity diagnosis beyond agreement range
Change, damaged condition, needs to be checked in maintenance next time；
Anomaly analysis module, for when judging that current elevator has abnormal generate, whether analysis exception, which has, to lead to failure
Risk, to realize the pre- diagnostic function of failure.
In the present embodiment, whether analysis is abnormal the risk for leading to failure, specifically:
When elevator is run up and down, detect that some range appearance one of speed of service curve is small in the process of running
Pulse, the pulse beyond allow speed of service error range, then judge there may be steel cable skidding risk, prompting maintenance
Personnel are note that and eliminate the potential security risk when safeguarding next time.
Exception/fault cancellation module, for adjusting or repairing when having the risk for leading to failure or faulty generation extremely
Change operating status value or condition curve, so that controlling elevator eliminates exception or failure；
Exception/fault information sending module, for extremely have the risk for leading to failure or faulty generation when, will be different
Often or fault message is sent to mobile device or cloud, and notifies related personnel or relevant departments, by related personnel or correlation
Department eliminates exception or failure.
Embodiment 3:
As shown in figure 3, the elevator self diagnosis and pre- diagnostic method of the present embodiment are real by sensor and elevator control system
It is existing, comprising the following steps:
S1, the sensor acquire operation data (angular velocity data, the acceleration information of such as lift car of current elevator
And weighing data), and send the data to elevator control system；
S2, the elevator control system carry out the conversion of time domain to frequency domain to data by time-frequency domain transfer algorithm；
S3, the elevator control system are constantly bent to collected frequency domain character value or feature by Intelligent Fusion algorithm
Line carries out self study, and reduces the deviation range of frequency domain character value or indicatrix, then by after optimization frequency domain character value or
Indicatrix is combined or gathers, and obtains the frequency domain character value or indicatrix of current elevator operation；
S4, the elevator control system pass through judge current elevator operation frequency domain character value or indicatrix whether
The variation outside setting range is generated, judges whether current elevator has exception or failure to generate, realizes the autodiagnosis of exception or failure
Disconnected function；
When judging that current elevator has abnormal generate, whether analysis exception, which has, leads to event for S5, the elevator control system
The risk of barrier, to realize the pre- diagnostic function of failure；
S6, the elevator control system are when having the risk for leading to failure or faulty generation extremely, adjustment or modification fortune
Row state value or condition curve, so that controlling elevator eliminates exception or failure.
Embodiment 4:
As shown in figure 4, the elevator self diagnosis and pre- diagnostic method of the present embodiment equally pass through sensor and elevator controlling system
System is realized, is with the difference place of embodiment 3:
S6, the elevator control system are when having the risk for leading to failure or faulty generation extremely, by exception or failure
Information is sent to mobile device or cloud, and notifies related personnel or relevant departments, is eliminated by related personnel or relevant departments
Exception or failure；Wherein, the mobile device can be smart phone, PDA handheld terminal, tablet computer etc..
Embodiment 5:
As shown in figure 4, the elevator self diagnosis and pre- diagnostic method of the present embodiment are real by frequency converter and elevator control system
It is existing, it is with the difference place of embodiment 3:
S1, the frequency converter obtain the operation of current elevator frequency conversion or logical data (input and output electric current of such as master control borad,
Voltage value, inductance value, temperature value of certain particular module etc., and send the data to elevator control system), and send the data to
Elevator control system.
In conclusion the present invention acquires the operation data of current elevator by sensor, or obtained currently by frequency converter
The frequency conversion of elevator operation or logical data, elevator control system is by the intelligence learning to daily car movement data, constantly essence
Really database when optimization elevator normal condition does not need a large amount of additional data space, saves cost；Elevator control
System processed carries out time domain to the conversion of frequency domain to data by time-frequency domain transfer algorithm, obtains the frequency domain of current state of elevator
Characteristic value or indicatrix, and merged frequency domain character value or indicatrix by Intelligent Fusion algorithm, obtain current electricity
The precise information of terraced operating status judges whether current elevator has exception according to the precise information of current elevator operation
Or failure generates, and realizes the self-diagnostic function of exception or failure, when judging that current elevator has abnormal generate, analysis is abnormal to be
It is no to have the risk for leading to failure, to realize the pre- diagnostic function of failure；Extremely there are the risk for leading to failure or faulty production
When raw, adjust immediately or modify operating status value or condition curve, so that controlling elevator eliminates exception or failure, or will it is abnormal or
Fault message is sent to mobile device or cloud, and notifies related personnel or relevant departments, by related personnel or relevant departments
Exception or failure are eliminated, due to diagnosing and solving exception or failure in advance, greatly improves the technology content of lift product,
Industrial competition is improved, is conducive to lift product and promote and brand foundation.
The above, only the invention patent preferred embodiment, but the scope of protection of the patent of the present invention is not limited to
This, anyone skilled in the art is in the range disclosed in the invention patent, according to the present invention the skill of patent
Art scheme and its inventive concept are subject to equivalent substitution or change, belong to the scope of protection of the patent of the present invention.
Claims (12)
1. elevator self diagnosis and pre- diagnostic system based on time-frequency convert algorithm, including sensor and elevator control system, described
Sensor is connect with elevator control system, it is characterised in that:
The sensor for acquiring the operation data of current elevator, and sends the data to elevator control system；
The elevator control system includes:
Data conversion module, for receive sensor transmission data after, by time-frequency domain transfer algorithm to data into
Row time domain obtains the frequency domain character value or indicatrix of current state of elevator to the conversion of frequency domain；
Data fusion module, for constantly being carried out to collected frequency domain character value or indicatrix by Intelligent Fusion algorithm
Self study, and the deviation range of frequency domain character value or indicatrix is reduced, then by the frequency domain character value or feature song after optimization
Line is combined or gathers, and obtains current elevator operation value or condition curve；
Judgment module, for by judging whether current elevator operation value or condition curve generate the change outside setting range
Change, judge whether current elevator has exception or failure to generate, realizes the self-diagnostic function of exception or failure；
Anomaly analysis module, for when judging that current elevator has abnormal generate, whether analysis is abnormal the wind for leading to failure
Danger, to realize the pre- diagnostic function of failure；Wherein, whether analysis is abnormal the risk for leading to failure, specifically:
When elevator is run up and down, detect that a small arteries and veins occurs in some range of speed of service curve in the process of running
Punching, the pulse then judge that there may be the risk that steel cable skids, prompting maintenance personnel beyond the speed of service error range allowed
Note that and eliminating potential security risk when safeguarding next time.
2. the elevator self diagnosis and pre- diagnostic system according to claim 1 based on time-frequency convert algorithm, it is characterised in that:
In elevator control system, which is connected the sensor integration by internal communication mode and elevator control system
It connects；
Or the sensor is placed outside outside elevator control system, which passes through external wired or wireless communication mode and elevator
Control system connection；
The sensor obtains carriage running state data by moving up and down together with carriage.
3. the elevator self diagnosis and pre- diagnostic system according to claim 1 based on time-frequency convert algorithm, it is characterised in that:
The sensor includes six axis gyroscopes and weight sensor, and the operation data of the current elevator includes the angle speed of lift car
Degree evidence, acceleration information and weighing data.
4. elevator self diagnosis and pre- diagnostic system based on time-frequency convert algorithm, including frequency converter and elevator control system, described
Frequency converter is connect with elevator control system, it is characterised in that:
The frequency converter for obtaining frequency conversion or the logical data of current elevator operation, and sends the data to elevator controlling system
System；
The elevator control system includes:
Data conversion module, for receive frequency converter transmission data after, by time-frequency domain transfer algorithm to data into
Row time domain obtains the frequency domain character value or indicatrix of current state of elevator to the conversion of frequency domain；
Data fusion module, for constantly being carried out to collected frequency domain character value or indicatrix by Intelligent Fusion algorithm
Self study, and the deviation range of frequency domain character value or indicatrix is reduced, then by the frequency domain character value or feature song after optimization
Line is combined or gathers, and obtains current elevator operation value or condition curve；
Judgment module, for by judging whether current elevator operation value or condition curve generate the change outside setting range
Change, judge whether current elevator has exception or failure to generate, realizes the self-diagnostic function of exception or failure；
Anomaly analysis module, for when judging that current elevator has abnormal generate, whether analysis is abnormal the wind for leading to failure
Danger, to realize the pre- diagnostic function of failure；Wherein, whether analysis is abnormal the risk for leading to failure, specifically:
When elevator is run up and down, detect that a small arteries and veins occurs in some range of speed of service curve in the process of running
Punching, the pulse then judge that there may be the risk that steel cable skids, prompting maintenance personnel beyond the speed of service error range allowed
Note that and eliminating potential security risk when safeguarding next time.
5. the elevator self diagnosis and pre- diagnostic system according to claim 4 based on time-frequency convert algorithm, it is characterised in that:
The frequency converter is arranged in elevator control system, which obtains electricity by internal bus mode and elevator control system
The operation data or bottom status data of terraced control system.
6. the elevator self diagnosis and pre- diagnostic system according to claim 1-5 based on time-frequency convert algorithm,
It is characterized in that: the elevator control system further include:
Exception/fault cancellation module, for when having the risk for leading to failure or faulty generation extremely, adjustment or modification to be transported
Row state value or condition curve, so that controlling elevator eliminates exception or failure；
Exception/fault information sending module, for when having the risk for leading to failure or faulty generation extremely, will it is abnormal or
Fault message is sent to mobile device or cloud, and notifies related personnel or relevant departments, by related personnel or relevant departments
Eliminate exception or failure.
7. elevator self diagnosis and pre- diagnostic method based on time-frequency convert algorithm, it is characterised in that: the method passes through sensor
It is realized with elevator control system, comprising:
The sensor acquires the operation data of current elevator, and sends the data to elevator control system；
The elevator control system receive sensor transmission data after, by time-frequency domain transfer algorithm to data into
Row time domain obtains the frequency domain character value or indicatrix of current state of elevator to the conversion of frequency domain；
The elevator control system constantly carries out certainly collected frequency domain character value or indicatrix by Intelligent Fusion algorithm
Study, and the deviation range of frequency domain character value or indicatrix is reduced, then by the frequency domain character value or indicatrix after optimization
It is combined or gathers, obtain current elevator operation value or condition curve；
The elevator control system is by judging whether current elevator operation value or condition curve generate outside setting range
Variation, judges whether current elevator has exception or failure to generate, and realizes the self-diagnostic function of exception or failure；
For the elevator control system when judging that current elevator has abnormal generate, whether analysis is abnormal the wind for leading to failure
Danger, to realize the pre- diagnostic function of failure；Wherein, whether analysis is abnormal the risk for leading to failure, specifically:
When elevator is run up and down, detect that a small arteries and veins occurs in some range of speed of service curve in the process of running
Punching, the pulse then judge that there may be the risk that steel cable skids, prompting maintenance personnel beyond the speed of service error range allowed
Note that and eliminating potential security risk when safeguarding next time.
8. the elevator self diagnosis and pre- diagnostic method according to claim 7 based on time-frequency convert algorithm, it is characterised in that:
The method also includes:
The elevator control system is when having the risk for leading to failure or faulty generation extremely, adjustment or modification operating status
Value or condition curve, so that controlling elevator eliminates exception or failure；
Or the elevator control system extremely have the risk for leading to failure or faulty generation when, by exception or fault message
It is sent to mobile device or cloud, and notifies related personnel or relevant departments, is eliminated by related personnel or relevant departments abnormal
Or failure.
9. the elevator self diagnosis and pre- diagnostic method according to claim 7 based on time-frequency convert algorithm, it is characterised in that:
The time-frequency domain transfer algorithm carries out the conversion of time domain to frequency domain to data, specifically:
Frequency domain is arrived by carrying out time domain to data based on Laplace transform algorithm, Fourier Transform Algorithm or Wavelet Packet Algorithm
Conversion；
It is described by Intelligent Fusion algorithm, self study constantly is carried out to collected frequency domain character value or indicatrix, and reduce
The deviation range of frequency domain character value or indicatrix, then by after optimization frequency domain character value or indicatrix be combined or collect
It closes, specifically:
Operation is carried out by D-S argumentation theory algorithm, clustering algorithm or neural network algorithm, constantly to collected frequency domain character
Value or indicatrix carry out self study, and reduce the deviation range of frequency domain character value or indicatrix, then by the frequency after optimization
Characteristic of field value or indicatrix are combined or gather.
10. elevator self diagnosis and pre- diagnostic method based on time-frequency convert algorithm, it is characterised in that: the method passes through frequency converter
It is realized with elevator control system, comprising:
The frequency converter obtains frequency conversion or the logical data of current elevator operation, and sends the data to elevator control system；
The elevator control system receive frequency converter transmission data after, by time-frequency domain transfer algorithm to data into
Row time domain obtains the frequency domain character value or indicatrix of current state of elevator to the conversion of frequency domain；
The elevator control system constantly carries out certainly collected frequency domain character value or indicatrix by Intelligent Fusion algorithm
Study, and the deviation range of frequency domain character value or indicatrix is reduced, then by the frequency domain character value or indicatrix after optimization
It is combined or gathers, obtain current elevator operation value or condition curve；
The elevator control system is by judging whether current elevator operation value or condition curve generate outside setting range
Variation, judges whether current elevator has exception or failure to generate, and realizes the self-diagnostic function of exception or failure；
For the elevator control system when judging that current elevator has abnormal generate, whether analysis is abnormal the wind for leading to failure
Danger, to realize the pre- diagnostic function of failure；Wherein, whether analysis is abnormal the risk for leading to failure, specifically:
When elevator is run up and down, detect that a small arteries and veins occurs in some range of speed of service curve in the process of running
Punching, the pulse then judge that there may be the risk that steel cable skids, prompting maintenance personnel beyond the speed of service error range allowed
Note that and eliminating potential security risk when safeguarding next time.
11. the elevator self diagnosis and pre- diagnostic method, feature according to claim 10 based on time-frequency convert algorithm exists
In: the method also includes:
The elevator control system is when having the risk for leading to failure or faulty generation extremely, adjustment or modification operating status
Value or condition curve, so that controlling elevator eliminates exception or failure；
Or the elevator control system extremely have the risk for leading to failure or faulty generation when, by exception or fault message
It is sent to mobile device or cloud, and notifies related personnel or relevant departments, is eliminated by related personnel or relevant departments abnormal
Or failure.
12. the elevator self diagnosis and pre- diagnostic method, feature according to claim 10 based on time-frequency convert algorithm exists
In:
The time-frequency domain transfer algorithm carries out the conversion of time domain to frequency domain to data, specifically:
Frequency domain is arrived by carrying out time domain to data based on Laplace transform algorithm, Fourier Transform Algorithm or Wavelet Packet Algorithm
Conversion；
It is described by Intelligent Fusion algorithm, self study constantly is carried out to collected frequency domain character value or indicatrix, and reduce
The deviation range of frequency domain character value or indicatrix, then by after optimization frequency domain character value or indicatrix be combined or collect
It closes, specifically:
Operation is carried out by D-S argumentation theory algorithm, clustering algorithm or neural network algorithm, constantly to collected frequency domain character
Value or indicatrix carry out self study, and reduce the deviation range of frequency domain character value or indicatrix, then by the frequency after optimization
Characteristic of field value or indicatrix are combined or gather.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610692327.9A CN106219342B (en) | 2016-08-19 | 2016-08-19 | Elevator self diagnosis and pre- diagnostic system and method based on time-frequency convert algorithm |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610692327.9A CN106219342B (en) | 2016-08-19 | 2016-08-19 | Elevator self diagnosis and pre- diagnostic system and method based on time-frequency convert algorithm |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN106219342A CN106219342A (en) | 2016-12-14 |
| CN106219342B true CN106219342B (en) | 2019-02-01 |
Family
ID=57552703
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610692327.9A Active CN106219342B (en) | 2016-08-19 | 2016-08-19 | Elevator self diagnosis and pre- diagnostic system and method based on time-frequency convert algorithm |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106219342B (en) |
Families Citing this family (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP6693576B2 (en) * | 2016-12-26 | 2020-05-13 | 三菱電機株式会社 | Recovery system |
| CN107179717A (en) * | 2017-06-06 | 2017-09-19 | 江苏曼斯特风电科技有限公司 | A kind of wind-power tower exempts to climb device people's machine testing controller and control method |
| CN107168168A (en) * | 2017-06-06 | 2017-09-15 | 江苏曼斯特风电科技有限公司 | A kind of wind-power tower intelligently exempts to climb device control system and method |
| JP7125225B2 (en) * | 2017-11-24 | 2022-08-24 | トヨタ自動車株式会社 | Abnormality predictor notification system, method, and program |
| CN108483172A (en) * | 2018-02-28 | 2018-09-04 | 武汉大学 | A kind of Intelligent elevator car safety monitoring and evaluation system |
| CN108439111A (en) * | 2018-02-28 | 2018-08-24 | 武汉大学 | A kind of elevator motion exception real-time detection method based on wavelet transformation |
| CN108529380B (en) * | 2018-03-27 | 2021-01-19 | 深圳市永达电子信息股份有限公司 | Elevator safety prediction method and system |
| CN109552959A (en) * | 2018-11-26 | 2019-04-02 | 常熟理工学院 | A kind of towed elevator remotely monitors and fault diagnosis system and method |
| CN109726736A (en) * | 2018-11-27 | 2019-05-07 | 西人马(西安)测控科技有限公司 | The method and system of training elevator internal contracting brake fault diagnosis model, band-type brake fault diagnosis |
| CN109581109A (en) * | 2018-12-05 | 2019-04-05 | 辽宁工程技术大学 | A kind of state of elevator multi-information fusion diagnostic method |
| CN109720955A (en) * | 2018-12-28 | 2019-05-07 | 云南达诺智能科技发展有限公司 | Elevator safety monitoring method, device, terminal device and computer-readable medium |
| CN110040594B (en) * | 2019-01-08 | 2020-11-10 | 浙江新再灵科技股份有限公司 | Convolutional neural network-based elevator operation detection system and method |
| CN109941860B (en) * | 2019-03-22 | 2021-02-09 | 西人马(西安)测控科技有限公司 | Elevator brake fault monitoring method, device and system |
| CN110065874B (en) * | 2019-05-23 | 2024-03-19 | 广州广日电梯工业有限公司 | Elevator temperature control device and method based on semiconductor refrigeration |
| CN110550518B (en) * | 2019-08-29 | 2020-07-28 | 电子科技大学 | Elevator operation abnormity detection method based on sparse denoising self-coding |
| CN111646333A (en) * | 2020-05-26 | 2020-09-11 | 上海建工四建集团有限公司 | Elevator running state evaluation method and system based on hybrid data mining |
| CN113734929B (en) * | 2021-09-17 | 2023-05-05 | 猫岐智能科技（上海）有限公司 | Continuous elevator running acceleration data acquisition system and method |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO1999035076A1 (en) * | 1998-01-09 | 1999-07-15 | Kone Corporation | Maintenance method for an elevator installation and elevator installation |
| CN101941623A (en) * | 2010-09-30 | 2011-01-12 | 深圳技师学院 | Traction machine detection or diagnosis system |
| CN103048041A (en) * | 2012-12-20 | 2013-04-17 | 北京信息科技大学 | Fault diagnosis method of electromechanical system based on local tangent space and support vector machine |
| CN104044969A (en) * | 2014-06-20 | 2014-09-17 | 广州日滨科技发展有限公司 | Elevator fault early warning method and system |
| CN204689281U (en) * | 2015-05-12 | 2015-10-07 | 广州广日电梯工业有限公司 | For the lift management system that elevator faults is diagnosed in advance |
-
2016
- 2016-08-19 CN CN201610692327.9A patent/CN106219342B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO1999035076A1 (en) * | 1998-01-09 | 1999-07-15 | Kone Corporation | Maintenance method for an elevator installation and elevator installation |
| CN101941623A (en) * | 2010-09-30 | 2011-01-12 | 深圳技师学院 | Traction machine detection or diagnosis system |
| CN103048041A (en) * | 2012-12-20 | 2013-04-17 | 北京信息科技大学 | Fault diagnosis method of electromechanical system based on local tangent space and support vector machine |
| CN104044969A (en) * | 2014-06-20 | 2014-09-17 | 广州日滨科技发展有限公司 | Elevator fault early warning method and system |
| CN204689281U (en) * | 2015-05-12 | 2015-10-07 | 广州广日电梯工业有限公司 | For the lift management system that elevator faults is diagnosed in advance |
Non-Patent Citations (1)
| Title |
|---|
| 《基于遗传算法优化支持向量机的电梯故障诊断》;易士琳;《计算机与数字工程》;20160131;166-170 |
Also Published As
| Publication number | Publication date |
|---|---|
| CN106219342A (en) | 2016-12-14 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106219342B (en) | Elevator self diagnosis and pre- diagnostic system and method based on time-frequency convert algorithm | |
| CN109102189B (en) | Electrical equipment health management system and method | |
| CN103178615B (en) | Electrical equipment fault monitoring method and system thereof | |
| CN102158129B (en) | Solar photovoltaic system and fault detection method thereof | |
| CN204280939U (en) | A kind of elevator operational monitoring forewarn system | |
| AU2020103722A4 (en) | A Dynamic Early Warning System for Power Station Operating Parameters Based on Cloud Platform | |
| CN104925613A (en) | Online safety detection prewarning device of elevator and detection prewarning method thereof | |
| CN111898669B (en) | Abnormal event early warning system of direct-current submerged arc furnace based on machine learning | |
| CN108627720B (en) | Power equipment state monitoring method based on Bayesian algorithm | |
| CN104390657A (en) | Generator set operating parameter measuring sensor fault diagnosis method and system | |
| CN107010505A (en) | Elevator cab door state-detection warning device and method based on acceleration transducer | |
| CN105487530A (en) | Diesel low-exhaust-temperature fault prediction system and method | |
| CN104596656A (en) | Temperature early warning method of cable joint | |
| CN106946111A (en) | A kind of elevator safety intelligent monitoring and power control system | |
| CN104486101A (en) | On-line power telecontrol IEC (integrated ethernet chip) 104 transmission anomaly detection method | |
| CN104931836A (en) | Power grid monitoring and early warning system | |
| CN105472040B (en) | A kind of stamping equipment life cycle management cloud platform and application method | |
| CN112027841A (en) | Elevator system | |
| CN107416632A (en) | A kind of elevator safety monitoring system | |
| CN109254526B (en) | Multi-stage safety redundancy control system for suspended self-propelled conveying trolley | |
| CN208378122U (en) | A kind of elevator maintenance device | |
| CN117332252A (en) | Rotary equipment trend early warning method based on vibration growth speed | |
| CN108982988B (en) | Power failure early warning diagnosis method | |
| CN116022673A (en) | Tower crane driving assisting system based on cloud edge cooperative technology | |
| CN114476890A (en) | Non-contact elevator data acquisition method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| EE01 | Entry into force of recordation of patent licensing contract | ||
| EE01 | Entry into force of recordation of patent licensing contract |
Application publication date: 20161214 Assignee: GUANGZHOU GUANGRI ELEVATOR INDUSTRY Co.,Ltd. Assignor: GUANGZHOU GUANGRI ELEVATOR INDUSTRY Co.,Ltd. Contract record no.: X2022990000515 Denomination of invention: Elevator self-diagnosis and pre-diagnosis system and method based on time-frequency conversion algorithm Granted publication date: 20190201 License type: Common License Record date: 20220817 |