CN115352977A - High-rise elevator operation abnormity alarming method - Google Patents

High-rise elevator operation abnormity alarming method Download PDF

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Publication number
CN115352977A
CN115352977A CN202211205497.1A CN202211205497A CN115352977A CN 115352977 A CN115352977 A CN 115352977A CN 202211205497 A CN202211205497 A CN 202211205497A CN 115352977 A CN115352977 A CN 115352977A
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Prior art keywords
value
acceleration deviation
elevator
cluster
deviation value
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Inventor
万典华
王耿
万伏初
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Xigemai Elevator Technology Nantong Co ltd
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Xigemai Elevator Technology Nantong Co ltd
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    • BPERFORMING OPERATIONS; TRANSPORTING
    • B66HOISTING; LIFTING; HAULING
    • B66BELEVATORS; ESCALATORS OR MOVING WALKWAYS
    • B66B5/00Applications of checking, fault-correcting, or safety devices in elevators
    • B66B5/02Applications of checking, fault-correcting, or safety devices in elevators responsive to abnormal operating conditions
    • B66B5/04Applications of checking, fault-correcting, or safety devices in elevators responsive to abnormal operating conditions for detecting excessive speed
    • B66B5/06Applications of checking, fault-correcting, or safety devices in elevators responsive to abnormal operating conditions for detecting excessive speed electrical
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B66HOISTING; LIFTING; HAULING
    • B66BELEVATORS; ESCALATORS OR MOVING WALKWAYS
    • B66B5/00Applications of checking, fault-correcting, or safety devices in elevators
    • B66B5/0006Monitoring devices or performance analysers
    • B66B5/0012Devices monitoring the users of the elevator system
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B66HOISTING; LIFTING; HAULING
    • B66BELEVATORS; ESCALATORS OR MOVING WALKWAYS
    • B66B5/00Applications of checking, fault-correcting, or safety devices in elevators
    • B66B5/0006Monitoring devices or performance analysers
    • B66B5/0018Devices monitoring the operating condition of the elevator system
    • B66B5/0031Devices monitoring the operating condition of the elevator system for safety reasons

Abstract

The invention discloses a high-rise elevator operation abnormity alarm method, which relates to the technical field of abnormity detection and comprises the following steps: acquiring horizontal direction acceleration deviation values and vertical direction acceleration deviation values of an elevator at a plurality of moments in a time period; acquiring a resultant acceleration deviation value of the elevator at each moment; acquiring a plurality of clusters of the resultant acceleration deviation value in a time period; acquiring a jitter value of the elevator in each clustering time period; acquiring a horizontal influence value of the human body action on the acceleration deviation value in the horizontal direction and a vertical influence value of the acceleration deviation value in the vertical direction in each cluster; acquiring an abnormal value of the elevator in each cluster time period, and judging whether the elevator runs abnormally in each cluster time period; the invention solves the technical problem that the elevator has misjudgment in the alarm process in the related technology.

Description

High-rise elevator operation abnormity alarm method
Technical Field
The invention relates to the technical field of anomaly detection, in particular to a high-rise elevator operation anomaly alarm method.
Background
Nowadays, more and more high-rise buildings are pulled up, and most of the high-rise buildings need to be provided with elevators; in connection with elevator maintenance, special equipment like elevators, according to the relevant regulations, requires maintenance and service by the relevant units once every half month. The maintenance is divided into weekly, quarterly and annual inspections according to a time period, related personnel are required to overhaul equipment in detail each time, major structures and accessories are subjected to professional inspection and evaluation, more detailed inspection and nursing are required after three months of use, and after one year of operation, each part is inspected according to inspection standards and is responsible for the inspection by experienced technicians; because the running environment of the elevator is complex, the flow of people is large, and maintenance personnel are insufficient, the elevator has great hidden danger.
The high-rise elevator has the characteristics of high running speed and large running amplitude of the car, so that the deviation of speed and acceleration is easy to occur in the running process of the high-rise elevator, the running stability of the elevator is reduced, potential safety hazards exist in the elevator, meanwhile, the fault of the high-rise elevator is more serious to the loss of passengers, and abnormal detection and alarm are required to be carried out in the running process of the elevator.
The abnormal detection of the elevator operation in the prior art mainly aims at the stability of the elevator operation, the shake or vibration of the elevator is directly judged according to the magnitude of single acceleration, the shake of the elevator can cause deviation of the acceleration in multiple directions and multiple moments, the shake degree of the elevator cannot be accurately reflected according to the magnitude of the single acceleration, and in addition, the influence of the action amplitude of a human body in an elevator car on the elevator acceleration is not considered in the prior art, so that a lot of misjudgments are caused in the alarm process of the elevator.
Disclosure of Invention
In order to solve the technical problems that deviation of acceleration in multiple directions and multiple moments is not considered in the prior art, influence of action amplitude of a human body on the acceleration of an elevator is not considered, and misjudgment of the elevator in the alarm process is caused. In view of the above, the present invention is achieved by the following technical solutions.
A high-rise elevator operation abnormity warning method comprises the following steps:
acquiring horizontal direction acceleration deviation values and vertical direction acceleration deviation values of an elevator at a plurality of moments in a time period, and acquiring an elevator car video of the elevator in the time period;
acquiring a combined acceleration deviation value of the elevator at each moment according to the horizontal direction acceleration deviation value and the vertical direction acceleration deviation value;
clustering the multiple combined acceleration deviation values according to the magnitude of the combined acceleration deviation values to obtain multiple clusters of the combined acceleration deviation values in the time period;
acquiring a jitter value of the elevator in the clustering time period according to the horizontal direction acceleration deviation value and the vertical direction acceleration deviation value corresponding to each combined acceleration deviation value in the cluster; sequentially acquiring the jitter value of the elevator in each clustering time period;
detecting the motion amplitude of a human body in the elevator car video in each cluster time period by using an optical flow method, and acquiring the entropy value of angular point optical flow information in each cluster time period according to the motion amplitude of the human body; acquiring a horizontal influence value of the human body action on the horizontal direction acceleration deviation value and a vertical influence value of the vertical direction acceleration deviation value in each cluster according to the entropy of the angular point optical flow information;
acquiring an abnormal value of the elevator in each cluster time period according to the horizontal influence value, the vertical influence value and the jitter value corresponding to each cluster; and judging whether the elevator operates abnormally in each clustering time period according to the abnormal value, and sending out early warning alarm when the operation is judged to be abnormal.
Further, in the process of acquiring horizontal direction acceleration deviation values and vertical direction acceleration deviation values of the elevator at a plurality of moments in a time period, the method also comprises the step of only installing a three-axis sensor in the elevator, so that an x axis and a y axis of the three-axis sensor are in the horizontal direction of the operation of the elevator car, and a z axis of the three-axis sensor is in the vertical direction of the horizontal direction of the operation of the elevator car; and acquiring an acceleration deviation value of the elevator in the x-axis direction, an acceleration deviation value in the y-axis direction and an acceleration deviation value in the z-axis direction according to the three-axis sensor.
Further, the horizontal direction acceleration deviation value is an x-axis direction speed deviation value and a y-axis direction speed deviation value of the three-axis sensor; the vertical direction acceleration deviation value is a z-axis direction speed deviation value of the three-axis sensor.
Further, the resultant acceleration deviation value of the elevator at each time instant is determined by:
Figure 788117DEST_PATH_IMAGE001
in the formula (I), the compound is shown in the specification,
Figure 150965DEST_PATH_IMAGE002
is at the same time
Figure 859158DEST_PATH_IMAGE003
The total acceleration deviation values of the elevator in the x-axis direction, the y-axis direction and the z-axis direction at the moment;
Figure 16470DEST_PATH_IMAGE004
is at the same time
Figure 544535DEST_PATH_IMAGE003
The acceleration deviation value of the elevator in the x-axis direction at the moment;
Figure 445494DEST_PATH_IMAGE005
is at the same time
Figure 273773DEST_PATH_IMAGE003
The acceleration deviation value of the elevator in the y-axis direction at the moment;
Figure 477352DEST_PATH_IMAGE006
is at least
Figure 617347DEST_PATH_IMAGE003
And the acceleration deviation value of the elevator in the z-axis direction at the moment.
Further, the process of obtaining a plurality of clusters of the combined acceleration deviation value in the time period is as follows:
acquiring a resultant acceleration deviation value of a first moment and a second moment in the plurality of moments, and acquiring the aggregation degree of the resultant acceleration deviation values of the first moment and the second moment;
setting a threshold value of the aggregation degree, and judging whether the combined acceleration deviation values at the first moment and the second moment belong to the same cluster according to the threshold value and the aggregation degree; when the combined acceleration deviation values at the first moment and the second moment belong to the same cluster, judging whether the combined acceleration deviation value at the third moment belongs to the current cluster according to the cluster degree, when the combined acceleration deviation value at the third moment belongs to the current cluster, continuously judging whether the combined acceleration deviation value at the fourth moment belongs to the current cluster, and sequentially judging whether the combined acceleration deviation values at the other moments belong to the current cluster; when the combined acceleration deviation values at the first moment and the second moment do not belong to the same cluster, the combined acceleration deviation value at the first moment is taken as the first cluster, the combined acceleration deviation value at the second moment is taken as the second cluster, whether the combined acceleration deviation value at the third moment and the combined acceleration deviation value at the second moment belong to the same cluster or not is judged, whether the combined acceleration deviation values at the other moments belong to the second cluster or not is judged in sequence, when the combined acceleration deviation value at one moment does not belong to the second cluster or not is judged, clustering of the second cluster is completed, clustering of the third cluster is started until all the combined acceleration deviation values at each moment are clustered, and a plurality of clusters of the combined acceleration deviation values in the time period are obtained.
Further, the aggregation degree of the combined acceleration deviation values at the first time and the second time is determined by the following formula:
Figure 197364DEST_PATH_IMAGE007
in the formula (I), the compound is shown in the specification,
Figure 880149DEST_PATH_IMAGE008
the degree of aggregation of the combined acceleration deviation values at the first time and the second time;
Figure 379264DEST_PATH_IMAGE009
The total acceleration deviation value at the first moment is obtained;
Figure 881920DEST_PATH_IMAGE010
the combined acceleration deviation value at the second moment;
Figure 124683DEST_PATH_IMAGE011
is the time interval value between the second time and the first time,
Figure 659045DEST_PATH_IMAGE012
which indicates the time of the second moment in time,
Figure 329060DEST_PATH_IMAGE013
indicating a first time instant.
Further, the jitter value of the elevator in each cluster time period is determined by:
Figure 319013DEST_PATH_IMAGE014
in the formula (I), the compound is shown in the specification,
Figure 365467DEST_PATH_IMAGE015
is an elevator at
Figure 491686DEST_PATH_IMAGE016
Jitter values over a number of clustering time periods;
Figure 332603DEST_PATH_IMAGE017
is as follows
Figure 75431DEST_PATH_IMAGE016
In a clustering period
Figure 535362DEST_PATH_IMAGE018
A plurality of x-axis direction velocity offset values;
Figure 906300DEST_PATH_IMAGE019
is as follows
Figure 793485DEST_PATH_IMAGE016
In a clustering period
Figure 148243DEST_PATH_IMAGE018
A y-axis direction velocity deviation value;
Figure 146286DEST_PATH_IMAGE020
is as follows
Figure 371731DEST_PATH_IMAGE016
In a clustering period
Figure 695396DEST_PATH_IMAGE018
A z-axis direction velocity offset value;
Figure 6292DEST_PATH_IMAGE021
is as follows
Figure 64816DEST_PATH_IMAGE016
A total number of resultant acceleration deviation values within a number of clustering time periods;
Figure 285713DEST_PATH_IMAGE022
representing the clustering of acceleration deviation values in the x-axis direction;
Figure 639334DEST_PATH_IMAGE023
representing the clustering of acceleration deviation values in the y-axis direction;
Figure 312892DEST_PATH_IMAGE024
indicating the convergence of acceleration deviation values in the z-axis direction.
Further, the process of acquiring the entropy of the angular point optical flow information in each cluster time period further comprises setting a threshold of the entropy of the angular point optical flow information, and when the entropy of the angular point optical flow information is larger than the threshold of the entropy, acquiring a horizontal influence value and a vertical influence value of the human body action on a horizontal direction acceleration deviation value and a vertical direction acceleration deviation value in each cluster.
Further, the abnormal value of the elevator in each cluster time period is determined by the following formula:
Figure 42950DEST_PATH_IMAGE025
in the formula (I), the compound is shown in the specification,
Figure 383933DEST_PATH_IMAGE026
is as follows
Figure 908455DEST_PATH_IMAGE016
Abnormal values of elevators in a cluster time period;
Figure 334888DEST_PATH_IMAGE027
is as follows
Figure 478425DEST_PATH_IMAGE016
Horizontal influence values of human body actions on the speed deviation value in the x-axis direction in each clustering time period;
Figure 532968DEST_PATH_IMAGE028
is a first
Figure 369337DEST_PATH_IMAGE016
Horizontal influence values of human body actions on the speed deviation value in the y-axis direction in each clustering time period;
Figure 407701DEST_PATH_IMAGE029
is as follows
Figure 89349DEST_PATH_IMAGE016
Vertical influence values of human body actions on speed deviation values in the z-axis direction in each clustering time period;
Figure 263978DEST_PATH_IMAGE017
is as follows
Figure 268319DEST_PATH_IMAGE016
In a clustering period
Figure 403765DEST_PATH_IMAGE018
A plurality of x-axis direction velocity deviation values;
Figure 13738DEST_PATH_IMAGE019
is a first
Figure 918240DEST_PATH_IMAGE016
In a clustering period
Figure 486625DEST_PATH_IMAGE018
A y-axis direction velocity deviation value;
Figure 843788DEST_PATH_IMAGE020
is a first
Figure 398397DEST_PATH_IMAGE016
In a clustering period
Figure 282039DEST_PATH_IMAGE018
A z-axis direction velocity offset value;
Figure 631112DEST_PATH_IMAGE022
representing the aggregative property of the acceleration deviation value in the x-axis direction;
Figure 865784DEST_PATH_IMAGE023
representing the clustering of acceleration deviation values in the y-axis direction;
Figure 692926DEST_PATH_IMAGE024
representing the aggregability of acceleration deviation values in the z-axis direction;
Figure 837600DEST_PATH_IMAGE021
is a first
Figure 482208DEST_PATH_IMAGE016
Total number of resultant acceleration deviation values within the respective cluster time period.
Further, the process of judging whether the elevator runs abnormally in each cluster time period according to the abnormal value also comprises the steps of setting a threshold value of the abnormal value, wherein the threshold value of the abnormal value is 0.8, when the abnormal value is larger than the threshold value of the abnormal value, the elevator runs abnormally in the cluster time period corresponding to the abnormal value, and starting an elevator abnormity alarm system.
Compared with the prior art, the invention has the beneficial effects that:
the invention provides a high-rise elevator operation abnormity warning method, which comprises the steps of obtaining horizontal direction acceleration deviation values and vertical direction acceleration deviation values of an elevator at a plurality of moments in a time period; acquiring a resultant acceleration deviation value of the elevator at each moment according to the horizontal direction acceleration deviation value and the vertical direction acceleration deviation value; clustering the multiple combined acceleration deviation values according to the magnitude of the combined acceleration deviation values, and further obtaining the jitter value of the elevator in each clustering time period after multiple clusters of the combined acceleration deviation values in the time period are obtained; the method analyzes the acceleration of the elevator in the horizontal direction and the acceleration of the elevator in the vertical direction when acquiring the jitter value in each clustering time period, the acquired jitter value of the elevator in each clustering time period is more accurate, meanwhile, the method performs clustering of the combined acceleration deviation value in one time period according to the similarity of the combined acceleration deviation value corresponding to each moment in the time period, obtains a plurality of clusters consisting of similar combined acceleration deviation values, and ensures that the elevator performs abnormal segmented alarm for a plurality of times in the time period by acquiring the jitter value of the elevator in each clustering time period.
The method also comprises the steps of detecting the action amplitude of a human body in the elevator car video in each clustering time period by using an optical flow method, and acquiring the entropy value of angular point optical flow information in each clustering time period according to the action amplitude of the human body; acquiring a horizontal influence value of the human body action on the horizontal direction acceleration deviation value and a vertical influence value of the vertical direction acceleration deviation value in each cluster according to the entropy of the angular point optical flow information; the invention considers the influence value of the action amplitude of passengers in the elevator on the horizontal direction acceleration deviation value and the vertical direction acceleration deviation value of the elevator, eliminates the influence of human body action on the abnormal value of the elevator on the basis of the jitter value, can judge the abnormal degree of the elevator in the running process according to the abnormal value of the elevator, and improves the accuracy and the use safety of the abnormal alarm of the elevator.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
Fig. 1 is a flow chart of an elevator operation abnormality alarm method provided by an embodiment of the invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Examples
The embodiment provides a high-rise elevator operation abnormity warning method, as shown in fig. 1, the warning method comprises the following steps:
s101, acquiring horizontal direction acceleration deviation values and vertical direction acceleration deviation values of the elevator at multiple moments in a time period; acquiring a combined acceleration deviation value of the elevator at each moment according to the horizontal direction acceleration deviation value and the vertical direction acceleration deviation value;
in this embodiment, the process of obtaining the horizontal direction acceleration deviation value and the vertical direction acceleration deviation value of the elevator at a plurality of times in a time period is as follows: installing a three-axis acceleration sensor in the elevator; the x-axis and the y-axis of the three-axis acceleration sensor are in the horizontal direction of the elevator car, and the z-axis of the three-axis acceleration sensor is in the electric stateThe vertical direction of the elevator car; firstly, the acceleration change of the elevator in the uniform deceleration running stage is analyzed, the self acceleration is mainly reflected in the vertical direction when the elevator is accelerated and decelerated, namely the acceleration exists in the z axis, the specific numerical value of the acceleration is set by a dispatching system of the elevator, and meanwhile, the value of the acceleration can change along with the time, so that the elevator is subjected to the acceleration change in the uniform deceleration running stage
Figure 816893DEST_PATH_IMAGE003
The acceleration at the moment is expressed as
Figure 837938DEST_PATH_IMAGE030
The elevator itself is
Figure 571539DEST_PATH_IMAGE003
Acceleration of time of day
Figure 527994DEST_PATH_IMAGE030
Is set to a system value, wherein
Figure 471679DEST_PATH_IMAGE031
Indicating the acceleration at which the speed of the elevator set by the system changes,
Figure 906203DEST_PATH_IMAGE032
which represents the direction of the z-axis,
Figure 618944DEST_PATH_IMAGE003
represent
Figure 215141DEST_PATH_IMAGE003
Time of day;
the acceleration in the x-axis direction detected by the three-axis acceleration sensor of the elevator car is
Figure 787068DEST_PATH_IMAGE033
In which
Figure 149916DEST_PATH_IMAGE033
Indicating an elevator at
Figure 123688DEST_PATH_IMAGE003
Acceleration in the x-axis direction at time; acceleration in the y-axis direction of
Figure 890787DEST_PATH_IMAGE034
In which
Figure 809065DEST_PATH_IMAGE034
Indicating an elevator at
Figure 848040DEST_PATH_IMAGE003
Acceleration in the y-axis direction at the moment; acceleration in the z-axis direction of
Figure 676319DEST_PATH_IMAGE035
In which
Figure 145478DEST_PATH_IMAGE035
Indicating an elevator at
Figure 691997DEST_PATH_IMAGE003
Acceleration in the z-axis direction at the moment; the deviation value of the acceleration of the elevator in the X-axis direction at any moment is regulated to
Figure 662227DEST_PATH_IMAGE036
In which
Figure 345012DEST_PATH_IMAGE036
Indicating an elevator at
Figure 985072DEST_PATH_IMAGE003
Acceleration deviation value in the x-axis direction at the moment; acceleration deviation value in the y-axis direction of
Figure 753308DEST_PATH_IMAGE037
In which
Figure 261649DEST_PATH_IMAGE037
Indicating an elevator at
Figure 798941DEST_PATH_IMAGE003
Acceleration in y-axis direction at timeA deviation value; the z-axis direction acceleration deviation value is
Figure 702630DEST_PATH_IMAGE038
(ii) a Wherein
Figure 567949DEST_PATH_IMAGE038
Indicating an elevator at
Figure 614402DEST_PATH_IMAGE003
Acceleration deviation value in the direction of the z axis at the moment; because the elevator moves in the horizontal direction and is balanced, namely the acceleration of the elevator per se in the directions of the x axis and the y axis is 0; therefore, the method comprises the following steps: the deviation value of the acceleration in the x-axis direction is
Figure 6200DEST_PATH_IMAGE039
(ii) a Wherein
Figure 847118DEST_PATH_IMAGE036
Indicating an elevator at
Figure 589946DEST_PATH_IMAGE003
The acceleration deviation value in the x-axis direction at the moment,
Figure 49877DEST_PATH_IMAGE033
indicating an elevator at
Figure 686395DEST_PATH_IMAGE003
Acceleration in the x-axis direction at time; acceleration deviation value in the y-axis direction of
Figure 573579DEST_PATH_IMAGE040
(ii) a Wherein
Figure 397179DEST_PATH_IMAGE037
Indicating an elevator at
Figure 923450DEST_PATH_IMAGE003
The acceleration deviation value in the y-axis direction at the time,
Figure 24262DEST_PATH_IMAGE034
indicating an elevator at
Figure 472561DEST_PATH_IMAGE003
Acceleration in the y-axis direction at time; the z-axis direction acceleration deviation value is
Figure 189981DEST_PATH_IMAGE041
(ii) a Wherein
Figure 257294DEST_PATH_IMAGE038
Indicating an elevator at
Figure 337245DEST_PATH_IMAGE003
The z-axis direction acceleration deviation value at the time,
Figure 831812DEST_PATH_IMAGE035
indicating an elevator at
Figure 630004DEST_PATH_IMAGE003
The acceleration in the z-axis direction at the time,
Figure 235428DEST_PATH_IMAGE030
for elevators themselves
Figure 310832DEST_PATH_IMAGE003
Acceleration at the moment;
then analyzing the acceleration change of the elevator at a constant speed stage; when the elevator ascends or descends stably, the motion reaches balance, so the acceleration in three directions is 0, the acceleration of the elevator car detected by the sensor is the deviation value of the acceleration, and the deviation value of the acceleration in the x-axis direction is
Figure 100933DEST_PATH_IMAGE039
(ii) a Wherein
Figure 527366DEST_PATH_IMAGE036
Indicating an elevator at
Figure 795537DEST_PATH_IMAGE003
The acceleration deviation value in the x-axis direction at the moment,
Figure 728376DEST_PATH_IMAGE033
indicating an elevator at
Figure 689379DEST_PATH_IMAGE003
Acceleration in the x-axis direction at time; the deviation value of the acceleration in the y-axis direction is
Figure 71950DEST_PATH_IMAGE037
In which
Figure 143811DEST_PATH_IMAGE037
Indicating an elevator at
Figure 459386DEST_PATH_IMAGE003
Acceleration deviation value in the y-axis direction at the moment; the z-axis direction acceleration deviation value is
Figure 466656DEST_PATH_IMAGE042
(ii) a Wherein
Figure 726736DEST_PATH_IMAGE038
Indicating an elevator at
Figure 477655DEST_PATH_IMAGE003
The z-axis direction acceleration deviation value at the time,
Figure 647736DEST_PATH_IMAGE035
indicating an elevator at
Figure 684962DEST_PATH_IMAGE003
Acceleration in the z-axis direction at time;
thereby obtaining the horizontal direction acceleration deviation value and the vertical direction acceleration deviation value of the elevator at any time in a time period; the acceleration deviation value in the horizontal direction is an acceleration deviation value in the x-axis direction and an acceleration deviation value in the y-axis direction, the acceleration deviation value in the vertical direction is an acceleration deviation value in the z-axis direction, and the acceleration deviation value in any one of the directions
Figure 573284DEST_PATH_IMAGE003
Time of day, xThe axial direction acceleration deviation value is
Figure 393472DEST_PATH_IMAGE036
The deviation value of acceleration in the y-axis direction is
Figure 415130DEST_PATH_IMAGE037
The z-axis direction acceleration deviation value is
Figure 29782DEST_PATH_IMAGE038
Finally, the deviation value of the acceleration in the direction of the x axis is
Figure 264455DEST_PATH_IMAGE036
The deviation value of the acceleration in the y-axis direction is
Figure 357176DEST_PATH_IMAGE037
And a z-axis direction acceleration deviation value of
Figure 501849DEST_PATH_IMAGE038
Acquiring a resultant acceleration deviation value of the elevator at each moment, wherein the resultant acceleration deviation value is determined by the following formula:
Figure 21823DEST_PATH_IMAGE043
in the formula (I), the compound is shown in the specification,
Figure 743792DEST_PATH_IMAGE002
is an elevator
Figure 640203DEST_PATH_IMAGE003
The resultant acceleration deviation value at the moment;
Figure 639383DEST_PATH_IMAGE036
the elevator is at
Figure 595838DEST_PATH_IMAGE003
The acceleration deviation value in the x-axis direction of the moment;
Figure 539523DEST_PATH_IMAGE037
the elevator is at
Figure 965258DEST_PATH_IMAGE003
Acceleration deviation value in the y-axis direction of the moment;
Figure 818944DEST_PATH_IMAGE038
the elevator is at
Figure 805355DEST_PATH_IMAGE003
A z-axis direction acceleration deviation value of the time;
Figure 377282DEST_PATH_IMAGE044
a combined acceleration deviation value representing an acceleration deviation value in the x-axis direction, an acceleration deviation value in the y-axis direction and an acceleration deviation value in the z-axis direction of the elevator, wherein the acceleration deviation value is used for representing a deviation value of the acceleration of the whole elevator;
s102, clustering the multiple combined acceleration deviation values according to the magnitude of the combined acceleration deviation values to obtain multiple clusters of the combined acceleration deviation values in a time period; acquiring a jitter value of the elevator in the clustering time period according to the horizontal direction acceleration deviation value and the vertical direction acceleration deviation value corresponding to each combined acceleration deviation value in the cluster; sequentially acquiring the jitter value of the elevator in each clustering time period; the method comprises the steps of acquiring a plurality of clusters of the combined acceleration deviation values in a time period, namely acquiring the combined acceleration deviation values at a first moment and a second moment in a plurality of moments, and acquiring the aggregation degrees of the combined acceleration deviation values at the first moment and the second moment; the degree of aggregation of the resultant acceleration deviation values is determined by the following equation:
Figure 881075DEST_PATH_IMAGE007
in the formula (I), the compound is shown in the specification,
Figure 448323DEST_PATH_IMAGE008
the aggregation degree of the combined acceleration deviation values at the first time and the second time;
Figure 746580DEST_PATH_IMAGE009
the deviation value of the resultant acceleration at the first moment is taken as a deviation value of the resultant acceleration at the first moment;
Figure 805803DEST_PATH_IMAGE010
the combined acceleration deviation value at the second moment;
Figure 441184DEST_PATH_IMAGE011
is the time interval value between the second time and the first time,
Figure 269463DEST_PATH_IMAGE012
which indicates the time of the second moment in time,
Figure 738621DEST_PATH_IMAGE013
representing a first time instant;
Figure 878615DEST_PATH_IMAGE045
indicating the resultant acceleration deviation value at the first time
Figure 721282DEST_PATH_IMAGE009
At the time interval between the second time and the first time
Figure 138488DEST_PATH_IMAGE011
Internal time-to-time
Figure 903182DEST_PATH_IMAGE012
And the time interval between the second time and the first time
Figure 936997DEST_PATH_IMAGE011
The larger the resultant acceleration deviation value at the first time
Figure 55125DEST_PATH_IMAGE009
To time of day
Figure 592417DEST_PATH_IMAGE012
The smaller the degree of influence of (c);
Figure 528012DEST_PATH_IMAGE046
indicating the resultant acceleration deviation value at the second time
Figure 783544DEST_PATH_IMAGE010
At the time interval between the second time and the first time
Figure 439785DEST_PATH_IMAGE011
Internal time-setting device
Figure 221796DEST_PATH_IMAGE013
The degree of influence of (c);
Figure 203658DEST_PATH_IMAGE047
indicating the resultant acceleration deviation value at the first moment
Figure 683837DEST_PATH_IMAGE009
Combined acceleration deviation value from second time
Figure 533981DEST_PATH_IMAGE010
The aggregability of (a);
setting a first threshold, and judging whether the combined acceleration deviation values at the first moment and the second moment belong to the same cluster according to the threshold and the aggregation degree; when the aggregation degree of the combined acceleration deviation values at the first moment and the second moment is greater than a first threshold value, the combined acceleration deviation values at the first moment and the second moment belong to the same cluster, and the cluster is marked as a first cluster; judging whether the resultant acceleration deviation value at the third moment belongs to the first cluster or not according to the cluster degree, wherein the cluster degree is determined by the following formula:
Figure 780286DEST_PATH_IMAGE048
in the formula (I), the compound is shown in the specification,
Figure 933050DEST_PATH_IMAGE049
the cluster degree of the combined acceleration deviation value at the third moment and the first cluster is obtained;
Figure 22228DEST_PATH_IMAGE050
the resultant acceleration deviation value at the third moment;
Figure 551430DEST_PATH_IMAGE010
the combined acceleration deviation value at the second moment;
Figure 917820DEST_PATH_IMAGE051
the time interval value of the third time and the second time is obtained;
Figure 241485DEST_PATH_IMAGE052
acquiring the total acceleration deviation value of the third moment and the clustering degree of the first cluster for the number of all the moments in the time period from the first moment to the third moment of the first cluster
Figure 83539DEST_PATH_IMAGE049
Time of flight
Figure 150852DEST_PATH_IMAGE053
Figure 637329DEST_PATH_IMAGE054
Indicating the resultant acceleration deviation value at the second time
Figure 394544DEST_PATH_IMAGE010
Combined acceleration deviation value from third time
Figure 333682DEST_PATH_IMAGE050
The aggregation of (a) and (b),
Figure 204686DEST_PATH_IMAGE054
the larger the value of (D), the larger the resultant acceleration deviation value at the third time
Figure 811248DEST_PATH_IMAGE050
The greater the degree of aggregation in the first cluster;
Figure 866928DEST_PATH_IMAGE055
indicating the time interval between the third time and the second time
Figure 762203DEST_PATH_IMAGE051
Combined acceleration deviation value at the third time
Figure 436898DEST_PATH_IMAGE050
A relative aggregation density of aggregates in the first cluster;
setting a second threshold value, and when the combined acceleration deviation value at the third moment and the clustering degree of the first cluster
Figure 897966DEST_PATH_IMAGE049
When the acceleration is larger than the second threshold value, the combined acceleration deviation value at the third moment
Figure 593390DEST_PATH_IMAGE050
Aggregating in a first cluster;
then, continuously judging whether the combined acceleration deviation value at the fourth moment belongs to the first cluster or not, and sequentially judging whether the combined acceleration deviation values at the other moments belong to the first cluster or not;
when the combined acceleration deviation values at the first moment and the second moment do not belong to the same cluster, taking the combined acceleration deviation value at the first moment as the first cluster, taking the combined acceleration deviation value at the second moment as the second cluster, judging whether the combined acceleration deviation value at the third moment and the combined acceleration deviation value at the second moment belong to the same cluster, sequentially judging whether the combined acceleration deviation values at the other moments belong to the second cluster, finishing clustering on the second cluster when the combined acceleration deviation value at one moment does not belong to the second cluster, starting to acquire the third cluster until all the combined acceleration deviation values at each moment are clustered, and acquiring a plurality of clusters of the acceleration deviation values in a time period;
acquiring a jitter value of the elevator in the clustering time period according to the horizontal direction acceleration deviation value and the vertical direction acceleration deviation value corresponding to each combined acceleration deviation value in the cluster; sequentially acquiring the jitter value of the elevator in each clustering time period; the jitter value of the elevator in each cluster time period is determined by:
Figure 507119DEST_PATH_IMAGE014
in the formula (I), the compound is shown in the specification,
Figure 734574DEST_PATH_IMAGE015
is an elevator at
Figure 909204DEST_PATH_IMAGE016
Jitter values over a number of clustering time periods;
Figure 182053DEST_PATH_IMAGE017
is as follows
Figure 583079DEST_PATH_IMAGE016
Within a cluster time period
Figure 865155DEST_PATH_IMAGE018
A plurality of x-axis direction velocity deviation values;
Figure 300816DEST_PATH_IMAGE019
is as follows
Figure 744567DEST_PATH_IMAGE016
In a clustering period
Figure 164047DEST_PATH_IMAGE018
A y-axis direction velocity deviation value;
Figure 122251DEST_PATH_IMAGE020
is as follows
Figure 412418DEST_PATH_IMAGE016
In a clustering period
Figure 27070DEST_PATH_IMAGE018
A z-axis direction velocity offset value;
Figure 402688DEST_PATH_IMAGE021
is as follows
Figure 26567DEST_PATH_IMAGE016
A total number of resultant acceleration deviation values within a number of clustering time periods;
Figure 171241DEST_PATH_IMAGE056
the larger the value of (A), the larger the change in the speed of the elevator, while the elevator is on the second
Figure 81428DEST_PATH_IMAGE016
Jitter values within a cluster time period
Figure 413183DEST_PATH_IMAGE015
The larger;
Figure 309595DEST_PATH_IMAGE022
is shown as
Figure 167830DEST_PATH_IMAGE016
In a clustering period
Figure 127214DEST_PATH_IMAGE018
The convergence of the speed deviation values in the x-axis direction, and
Figure 946266DEST_PATH_IMAGE057
wherein, in the step (A),
Figure 505423DEST_PATH_IMAGE058
denotes the first
Figure 359109DEST_PATH_IMAGE018
The number of acceleration deviation values within a range of the peripheral length r of each x-axis direction speed deviation value;
Figure 486465DEST_PATH_IMAGE023
is shown as
Figure 183026DEST_PATH_IMAGE016
In a clustering period
Figure 155661DEST_PATH_IMAGE018
The convergence of the speed deviation values in the y-axis direction, and
Figure 863854DEST_PATH_IMAGE059
wherein, in the process,
Figure 286745DEST_PATH_IMAGE060
is shown as
Figure 80389DEST_PATH_IMAGE018
The number of acceleration deviation values within a range of the circumferential length r of each y-axis direction speed deviation value;
Figure 856715DEST_PATH_IMAGE024
is shown as
Figure 213222DEST_PATH_IMAGE016
In a clustering period
Figure 541436DEST_PATH_IMAGE018
Aggregations of velocity deviations in the z-axis direction, and
Figure 822375DEST_PATH_IMAGE061
wherein, in the process,
Figure 402392DEST_PATH_IMAGE062
is shown as
Figure 350757DEST_PATH_IMAGE018
The number of acceleration deviation values within a range of the peripheral length r of each z-axis direction velocity deviation value;
it should be noted that, according to the implementation conditions of the present example, this exampleIn the embodiment, the first threshold is set to be 3, the second threshold is set to be 2, and an implementer can set other first thresholds and second thresholds according to specific implementation conditions; in determining the first
Figure 849871DEST_PATH_IMAGE016
In a clustering period
Figure 352528DEST_PATH_IMAGE018
Aggregation of individual x-axis direction velocity deviation values
Figure 736236DEST_PATH_IMAGE022
The first step
Figure 804686DEST_PATH_IMAGE016
Within a cluster time period
Figure 474702DEST_PATH_IMAGE018
Aggregations of velocity deviation values in the y-axis direction
Figure 464655DEST_PATH_IMAGE023
And a first
Figure 643264DEST_PATH_IMAGE016
In a clustering period
Figure 159696DEST_PATH_IMAGE018
Aggregative property of velocity deviation value in z-axis direction
Figure 141559DEST_PATH_IMAGE024
In the range of the length r, the value of the length r is 1/4 times
Figure 477862DEST_PATH_IMAGE016
The length of each cluster time period;
s103, obtaining the elevator car video in each cluster time period, and obtaining the entropy value of angular point light flow information in each cluster time period according to the motion amplitude of a human body in the elevator car video in each cluster time period by using a light flow method; acquiring a horizontal influence value of the human body action on the horizontal direction acceleration deviation value and a vertical influence value of the vertical direction acceleration deviation value in each cluster according to the entropy of the angular point optical flow information;
in the embodiment, in the running process of the elevator, because normal movement of personnel exists in the elevator car, the elevator car shakes normally, and at the moment, the shaking of the elevator is also detected through the sensor data of the elevator car, so in order to obtain abnormal shaking of the elevator, the influence of the normal movement of the personnel in the elevator car on the detected shaking needs to be eliminated; for the detected second
Figure 203373DEST_PATH_IMAGE016
Sub-dithering, i.e. corresponding to
Figure 980836DEST_PATH_IMAGE016
The acceleration deviation values of the clusters are judged, and the influence of the normal behavior of the personnel on the acceleration deviation values in the three directions is judged according to the car monitoring video;
firstly, get the first
Figure 133600DEST_PATH_IMAGE016
The cage monitoring video of the time period corresponding to each cluster is used for judging the human body action amplitude by using an optical flow method, namely, the entropy of angular point optical flow information is calculated through the characteristic angular points of the human body, the numerical value of the entropy is normalized, and the entropy of the angular point optical flow information is
Figure 363724DEST_PATH_IMAGE063
The larger the motion amplitude of the human body is, the larger the influence on the deviation value of the acceleration is; the motion amplitude of the human body is obtained by an optical flow method, and because the small-amplitude motion of the human body does not influence the running stability of the elevator in practice, a third threshold value is set according to practical experience
Figure 751980DEST_PATH_IMAGE064
In the scheme, the threshold is 0.4, and the threshold can be adjusted according to scenes in practice, and judgment is carried out at the moment
Figure 649529DEST_PATH_IMAGE065
The corresponding human body action does not influence the deviation of the acceleration of the elevator; then, entropy values of all corner point optical flow information are judged
Figure 973194DEST_PATH_IMAGE066
The influence of the corresponding action on the acceleration deviation value; at the moment, the entropy value of the angular point light stream information is judged
Figure 422105DEST_PATH_IMAGE066
The corresponding human body action influences the acceleration deviation values in the three directions, and the influence degrees of the acceleration deviation values in the x-axis direction, the y-axis direction and the z-axis direction are different due to different action positions in the car, so that the horizontal influence value of the human body action amplitude on the acceleration deviation values in the x-axis direction and the y-axis direction and the vertical influence value of the acceleration deviation value in the z-axis direction are judged according to the human body action amplitude and the position in the car;
for the first
Figure 489418DEST_PATH_IMAGE016
A cluster of
Figure 834949DEST_PATH_IMAGE016
A number of clusters
Figure 329515DEST_PATH_IMAGE018
The time corresponding to each x-axis direction speed deviation value is
Figure 268652DEST_PATH_IMAGE067
Has the first
Figure 264290DEST_PATH_IMAGE016
(ii) a number of clusters
Figure 339694DEST_PATH_IMAGE018
The time corresponding to the speed deviation value in the y-axis direction is
Figure 5161DEST_PATH_IMAGE068
Has the first
Figure 290649DEST_PATH_IMAGE016
(ii) a number of clusters
Figure 965344DEST_PATH_IMAGE018
The time corresponding to the speed deviation value in the z-axis direction is
Figure 160833DEST_PATH_IMAGE069
(ii) a Then the human body acts on
Figure 121836DEST_PATH_IMAGE016
In a cluster
Figure 38495DEST_PATH_IMAGE018
The horizontal influence value of the acceleration deviation value in the x-axis direction is determined by the following formula:
Figure 251302DEST_PATH_IMAGE070
in the formula (I), the compound is shown in the specification,
Figure 160352DEST_PATH_IMAGE027
is a first
Figure 433201DEST_PATH_IMAGE016
In a cluster
Figure 303068DEST_PATH_IMAGE018
Horizontal influence values of the acceleration deviation values in the x-axis direction;
Figure 585145DEST_PATH_IMAGE071
is the ith cluster
Figure 614281DEST_PATH_IMAGE018
The time corresponding to the speed deviation value in the x-axis direction;
Figure 58032DEST_PATH_IMAGE072
is a first
Figure 415195DEST_PATH_IMAGE016
In a cluster
Figure 94438DEST_PATH_IMAGE018
Acceleration deviation value in x-axis direction
Figure 119026DEST_PATH_IMAGE073
In the time range of
Figure 996328DEST_PATH_IMAGE074
The magnitude of the individual's body motion;
Figure 840787DEST_PATH_IMAGE075
is as follows
Figure 323721DEST_PATH_IMAGE016
In a cluster
Figure 874919DEST_PATH_IMAGE018
Time corresponding to acceleration deviation value in x-axis direction
Figure 660472DEST_PATH_IMAGE071
Has a length of
Figure 116861DEST_PATH_IMAGE073
The number of human body movements in the range of (1), the length in this embodiment is
Figure 747694DEST_PATH_IMAGE073
0.5 second;
Figure 871508DEST_PATH_IMAGE076
is as follows
Figure 296804DEST_PATH_IMAGE016
In a cluster
Figure 647014DEST_PATH_IMAGE018
The position of the human body action of the acceleration deviation value in the x-axis direction in the elevator;
Figure 206171DEST_PATH_IMAGE077
half the length of the diagonal of the elevator car;
Figure 74506DEST_PATH_IMAGE078
is as follows
Figure 201862DEST_PATH_IMAGE016
In a cluster
Figure 508210DEST_PATH_IMAGE018
J time of occurrence of the personal body motion of the acceleration deviation value in the x-axis direction;
Figure 605479DEST_PATH_IMAGE079
is a natural constant;
Figure 844830DEST_PATH_IMAGE080
is shown as
Figure 877508DEST_PATH_IMAGE016
In a cluster
Figure 530207DEST_PATH_IMAGE018
Of deviation of acceleration in x-axis directionjThe influence degree of the acceleration deviation value in the x-axis direction of the personal body motion,
Figure 572112DEST_PATH_IMAGE081
to calculate the stability constant, the prevention denominator is 0; indicating the extent to which the location of the action approaches the edge of the elevator car,
Figure 259445DEST_PATH_IMAGE082
the larger the acceleration deviation value is, the larger the influence of the human body action on the x-axis acceleration deviation value is;
in the same way, the human bodyAction pair is
Figure 728604DEST_PATH_IMAGE016
The horizontal contribution to the acceleration deviation value in the first y-axis direction in the cluster is determined by:
Figure 743964DEST_PATH_IMAGE083
in the formula (I), the compound is shown in the specification,
Figure 586631DEST_PATH_IMAGE028
is as follows
Figure 394050DEST_PATH_IMAGE016
In a cluster
Figure 768530DEST_PATH_IMAGE018
Horizontal influence values of the acceleration deviation values in the y-axis direction;
Figure 536766DEST_PATH_IMAGE068
is a first
Figure 45108DEST_PATH_IMAGE016
(ii) a number of clusters
Figure 582400DEST_PATH_IMAGE018
The time corresponding to the speed deviation value in the y-axis direction;
Figure 393361DEST_PATH_IMAGE072
is as follows
Figure 914472DEST_PATH_IMAGE016
In a cluster
Figure 367450DEST_PATH_IMAGE018
The deviation value of acceleration in the y-axis direction is
Figure 24828DEST_PATH_IMAGE073
Within a time range of
Figure 275199DEST_PATH_IMAGE074
The magnitude of the individual's body motion;
Figure 549186DEST_PATH_IMAGE084
is as follows
Figure 540275DEST_PATH_IMAGE016
In a cluster
Figure 583318DEST_PATH_IMAGE018
The time corresponding to the acceleration deviation value in the y-axis direction
Figure 736081DEST_PATH_IMAGE068
Has a length of
Figure 966206DEST_PATH_IMAGE073
The number of human body movements in the range of (1), the length in this embodiment is
Figure 229828DEST_PATH_IMAGE073
0.5 second;
Figure 720852DEST_PATH_IMAGE076
is a first
Figure 575676DEST_PATH_IMAGE016
In a cluster
Figure 759008DEST_PATH_IMAGE018
The position of the human body action of the acceleration deviation value in the y-axis direction in the elevator;
Figure 826321DEST_PATH_IMAGE077
half the length of the diagonal of the elevator car;
Figure 171852DEST_PATH_IMAGE078
is as follows
Figure 400839DEST_PATH_IMAGE016
In a cluster
Figure 464610DEST_PATH_IMAGE018
Of acceleration deviation value in y-axis directionjThe time at which the individual action occurred;
Figure 601193DEST_PATH_IMAGE079
is a natural constant;
Figure 676596DEST_PATH_IMAGE085
denotes the first
Figure 201119DEST_PATH_IMAGE016
In a cluster
Figure 361973DEST_PATH_IMAGE018
Of acceleration deviation value in y-axis directionjThe degree of influence of the acceleration deviation value in the y-axis direction of the personal body motion,
Figure 771088DEST_PATH_IMAGE081
to calculate the stability constant, the prevention denominator is 0;
Figure 560053DEST_PATH_IMAGE082
indicating the extent to which the location of the action approaches the edge of the elevator car,
Figure 662001DEST_PATH_IMAGE082
the larger the acceleration deviation value is, the larger the influence of the human body action on the x-axis acceleration deviation value is;
in the same way, the human body acts on the second
Figure 434785DEST_PATH_IMAGE016
In a cluster
Figure 373223DEST_PATH_IMAGE018
Acceleration deviation value in z-axis directionIs determined by the following equation:
Figure 547853DEST_PATH_IMAGE086
in the formula (I), the compound is shown in the specification,
Figure 289544DEST_PATH_IMAGE029
is as follows
Figure 690569DEST_PATH_IMAGE016
In a cluster
Figure 300542DEST_PATH_IMAGE018
A vertical influence value of the z-axis direction acceleration deviation value;
Figure 205044DEST_PATH_IMAGE069
is as follows
Figure 773429DEST_PATH_IMAGE016
(ii) a number of clusters
Figure 130592DEST_PATH_IMAGE018
The time corresponding to the speed deviation value in the z-axis direction;
Figure 544256DEST_PATH_IMAGE072
is as follows
Figure 303264DEST_PATH_IMAGE016
In a cluster
Figure 776971DEST_PATH_IMAGE018
The deviation value of the acceleration in the z-axis direction is
Figure 887009DEST_PATH_IMAGE073
In the time range of
Figure 714151DEST_PATH_IMAGE074
The magnitude of the individual's body motion;
Figure 983458DEST_PATH_IMAGE087
is as follows
Figure 500503DEST_PATH_IMAGE016
In a cluster
Figure 956892DEST_PATH_IMAGE018
The time corresponding to the acceleration deviation value in the z-axis direction
Figure 587725DEST_PATH_IMAGE069
Has a length of
Figure 180380DEST_PATH_IMAGE073
The number of human body movements in the range of (1), the length in this embodiment is
Figure 136835DEST_PATH_IMAGE073
0.5 second;
Figure 955886DEST_PATH_IMAGE076
is as follows
Figure 515043DEST_PATH_IMAGE016
In a cluster
Figure 103151DEST_PATH_IMAGE018
The position of the human body action of the z-axis direction acceleration deviation value in the elevator;
Figure 89561DEST_PATH_IMAGE077
half the length of the diagonal of the elevator car;
Figure 395909DEST_PATH_IMAGE078
is as follows
Figure 493178DEST_PATH_IMAGE016
In a cluster
Figure 201371DEST_PATH_IMAGE018
Of deviation value of acceleration in z-axis directionjThe time at which the individual action occurred;
Figure 93104DEST_PATH_IMAGE079
is a natural constant;
Figure 886747DEST_PATH_IMAGE088
is shown as
Figure 931582DEST_PATH_IMAGE016
In a cluster
Figure 353336DEST_PATH_IMAGE018
Of deviation value of acceleration in z-axis directionjThe influence degree of the z-axis direction acceleration deviation value of the personal body motion,
Figure 556916DEST_PATH_IMAGE081
to calculate the stability constant, the prevention denominator is 0;
sequentially obtaining a horizontal influence value of the horizontal direction acceleration deviation value and a vertical influence value of the vertical direction acceleration deviation value in each cluster;
s104, acquiring abnormal values of the elevators in each cluster time period according to the horizontal influence value, the vertical influence value and the jitter value corresponding to each cluster; judging whether the elevator runs abnormally in each clustering time period according to the abnormal value; the abnormal value of the elevator in each cluster time period is determined by the following formula:
Figure 962489DEST_PATH_IMAGE089
in the formula (I), the compound is shown in the specification,
Figure 542506DEST_PATH_IMAGE026
is as follows
Figure 84346DEST_PATH_IMAGE016
Abnormal values of elevators in a cluster time period;
Figure 458827DEST_PATH_IMAGE027
is as follows
Figure 227063DEST_PATH_IMAGE016
Horizontal influence values of human body actions on the speed deviation value in the x-axis direction in each clustering time period;
Figure 876350DEST_PATH_IMAGE028
is as follows
Figure 944800DEST_PATH_IMAGE016
Horizontal influence values of human body actions on the speed deviation value in the y-axis direction in each clustering time period;
Figure 956094DEST_PATH_IMAGE029
is as follows
Figure 149309DEST_PATH_IMAGE016
Vertical influence values of human body actions on the speed deviation value in the z-axis direction in each clustering time period;
Figure 602287DEST_PATH_IMAGE017
is a first
Figure 259664DEST_PATH_IMAGE016
In a clustering period
Figure 835002DEST_PATH_IMAGE018
A plurality of x-axis direction velocity offset values;
Figure 436885DEST_PATH_IMAGE019
is as follows
Figure 162395DEST_PATH_IMAGE016
In a clustering period
Figure 674279DEST_PATH_IMAGE018
A y-axis direction velocity offset value;
Figure 686098DEST_PATH_IMAGE020
is a first
Figure 385063DEST_PATH_IMAGE016
Within a cluster time period
Figure 773319DEST_PATH_IMAGE018
A z-axis direction velocity offset value;
Figure 888779DEST_PATH_IMAGE022
is shown as
Figure 212444DEST_PATH_IMAGE016
In a clustering period
Figure 788919DEST_PATH_IMAGE018
The convergence of the speed deviation values in the x-axis direction, and
Figure 856232DEST_PATH_IMAGE057
wherein, in the step (A),
Figure 936183DEST_PATH_IMAGE058
is shown as
Figure 430750DEST_PATH_IMAGE018
The number of acceleration deviation values within a range of the peripheral length r of each x-axis direction speed deviation value;
Figure 228942DEST_PATH_IMAGE023
denotes the first
Figure 99946DEST_PATH_IMAGE016
In a clustering period
Figure 909770DEST_PATH_IMAGE018
The convergence of the velocity deviation values in the y-axis direction, and
Figure 965450DEST_PATH_IMAGE059
wherein, in the step (A),
Figure 126304DEST_PATH_IMAGE060
is shown as
Figure 394475DEST_PATH_IMAGE018
The number of acceleration deviation values within a range of the circumferential length r of each y-axis direction speed deviation value;
Figure 324385DEST_PATH_IMAGE024
is shown as
Figure 423403DEST_PATH_IMAGE016
Within a cluster time period
Figure 196187DEST_PATH_IMAGE018
Aggregations of velocity deviation values in the z-axis direction, and
Figure 408994DEST_PATH_IMAGE061
wherein, in the process,
Figure 990148DEST_PATH_IMAGE062
is shown as
Figure 731839DEST_PATH_IMAGE018
The number of acceleration deviation values within a range of the peripheral length r of each z-axis direction velocity deviation value;
Figure 257498DEST_PATH_IMAGE021
is as follows
Figure 742837DEST_PATH_IMAGE016
A total number of resultant acceleration deviation values within a number of clustering time periods;
Figure 771973DEST_PATH_IMAGE090
indicating the first to exclude the influence of human body actions
Figure 215724DEST_PATH_IMAGE016
(ii) a number of clusters
Figure 838466DEST_PATH_IMAGE018
The influence degree of the acceleration deviation value in the x-axis direction on the abnormal value of the elevator;
Figure 252130DEST_PATH_IMAGE091
indicating the first to exclude the influence of human body actions
Figure 109008DEST_PATH_IMAGE016
(ii) a number of clusters
Figure 127256DEST_PATH_IMAGE018
The influence degree of the acceleration deviation value in the y-axis direction on the abnormal value of the elevator;
Figure 502873DEST_PATH_IMAGE092
indicating the elimination of the influence of human body motion
Figure 392332DEST_PATH_IMAGE016
(ii) a number of clusters
Figure 802585DEST_PATH_IMAGE018
The influence degree of the z-axis direction acceleration deviation value on the abnormal value of the elevator;
Figure 322559DEST_PATH_IMAGE093
the larger the value of (A), the
Figure 919893DEST_PATH_IMAGE016
(ii) a number of clusters
Figure 940939DEST_PATH_IMAGE018
The larger the influence length of the individual resultant acceleration deviation value on the abnormal value of the elevator is, namely the larger the abnormal value of the elevator is;
obtaining abnormal values of the elevators in each cluster time period in sequence; each cluster corresponds to an abnormal value of an elevator; setting a fourth threshold value, and judging whether the elevator runs abnormally in each cluster time period according to the abnormal value of the elevator and the magnitude of the fourth threshold value; when the abnormal value of the elevator in a clustering time period is greater than a fourth threshold value, the elevator operates abnormally in the clustering time period, and an elevator abnormal alarm system is started;
it should be noted that, in this embodiment, the fourth threshold is set to be 0.8 according to the implementation conditions, when the abnormal value is greater than 0.8, the elevator operates abnormally in the cluster time period corresponding to the abnormal value, and the elevator abnormal alarm system is started; the implementer may set other values as the fourth threshold according to the implementation conditions.
In summary, the embodiment provides a high-rise elevator operation abnormity warning method, which includes: acquiring horizontal direction acceleration deviation values and vertical direction acceleration deviation values of an elevator at a plurality of moments in a time period, and acquiring an elevator car video of the elevator in the time period; acquiring a combined acceleration deviation value of the elevator at each moment according to the horizontal direction acceleration deviation value and the vertical direction acceleration deviation value; clustering the multiple combined acceleration deviation values according to the magnitude of the combined acceleration deviation values to obtain multiple clusters of the combined acceleration deviation values in a time period; acquiring a jitter value of the elevator in the clustering time period according to the horizontal direction acceleration deviation value and the vertical direction acceleration deviation value corresponding to each combined acceleration deviation value in the cluster; sequentially acquiring the jitter value of the elevator in each clustering time period; detecting the motion amplitude of a human body in the elevator car video in each cluster time period by using an optical flow method, and acquiring the entropy value of angular point optical flow information in each cluster time period according to the motion amplitude of the human body; acquiring a horizontal influence value of the human body action on the horizontal direction acceleration deviation value and a vertical influence value of the vertical direction acceleration deviation value in each cluster according to the entropy of the angular point optical flow information; acquiring an abnormal value of the elevator in each cluster time period according to the horizontal influence value, the vertical influence value and the jitter value corresponding to each cluster; judging whether the elevator runs abnormally in each clustering time period according to the abnormal value; the technical scheme of the invention can solve the technical problem that in the prior art, when the elevator runs, the elevator is misjudged in the alarming process because the deviation of the acceleration in a plurality of directions and moments is not considered and the influence of the action amplitude of a human body on the acceleration of the elevator is not considered.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.

Claims (10)

1. A high-rise elevator operation abnormity warning method is characterized by comprising the following steps:
acquiring horizontal direction acceleration deviation values and vertical direction acceleration deviation values of an elevator at a plurality of moments in a time period, and acquiring an elevator car video of the elevator in the time period;
acquiring a combined acceleration deviation value of the elevator at each moment according to the horizontal direction acceleration deviation value and the vertical direction acceleration deviation value;
clustering the multiple combined acceleration deviation values according to the magnitude of the combined acceleration deviation values to obtain multiple clusters of the combined acceleration deviation values in the time period;
acquiring a jitter value of the elevator in the clustering time period according to the horizontal direction acceleration deviation value and the vertical direction acceleration deviation value corresponding to each combined acceleration deviation value in the cluster; sequentially acquiring the jitter value of the elevator in each clustering time period;
detecting the motion amplitude of a human body in the elevator car video in each cluster time period by using an optical flow method, and acquiring the entropy value of angular point optical flow information in each cluster time period according to the motion amplitude of the human body; acquiring a horizontal influence value of the human body action on the horizontal direction acceleration deviation value and a vertical influence value of the vertical direction acceleration deviation value in each cluster according to the entropy of the angular point optical flow information;
acquiring an abnormal value of the elevator in each cluster time period according to the horizontal influence value, the vertical influence value and the jitter value corresponding to each cluster; and judging whether the elevator operates abnormally in each clustering time period according to the abnormal value, and sending out early warning alarm when the operation is judged to be abnormal.
2. The method for alarming abnormality in operation of a high-rise elevator according to claim 1, wherein in the process of obtaining the horizontal direction acceleration deviation value and the vertical direction acceleration deviation value of the elevator at a plurality of times within a period of time, the method further comprises installing only a three-axis sensor in the elevator so that the x-axis and the y-axis of the three-axis sensor are in the horizontal direction of the operation of the elevator car and the z-axis of the three-axis sensor is in the vertical direction of the horizontal direction of the operation of the elevator car; and acquiring an acceleration deviation value of the elevator in the x-axis direction, an acceleration deviation value in the y-axis direction and an acceleration deviation value in the z-axis direction according to the three-axis sensor.
3. The high-rise elevator operation abnormality warning method according to claim 2, characterized in that the horizontal direction acceleration deviation value is an x-axis direction speed deviation value and a y-axis direction speed deviation value of the three-axis sensor; the vertical direction acceleration deviation value is a z-axis direction speed deviation value of the three-axis sensor.
4. The high-rise elevator operation abnormality warning method according to claim 3, characterized in that the resultant acceleration deviation value of the elevator at each time is determined by the following equation:
Figure 704013DEST_PATH_IMAGE001
in the formula (I), the compound is shown in the specification,
Figure 205401DEST_PATH_IMAGE002
is at the same time
Figure 419345DEST_PATH_IMAGE003
The total acceleration deviation values of the elevator in the x-axis direction, the y-axis direction and the z-axis direction at the moment;
Figure 465930DEST_PATH_IMAGE004
is at the same time
Figure 155537DEST_PATH_IMAGE003
The acceleration deviation value of the elevator in the x-axis direction at the moment;
Figure 335983DEST_PATH_IMAGE005
is at the same time
Figure 560027DEST_PATH_IMAGE003
The acceleration deviation value of the elevator in the y-axis direction at the moment;
Figure 167725DEST_PATH_IMAGE006
is at the same time
Figure 79050DEST_PATH_IMAGE003
And the acceleration deviation value of the elevator in the z-axis direction at the moment.
5. The method for alarming abnormality in operation of high-rise elevator according to claim 1, wherein the process of obtaining a plurality of clusters of the resultant acceleration deviation values in the time period is:
acquiring a combined acceleration deviation value of a first moment and a second moment in the plurality of moments, and acquiring the aggregation degree of the combined acceleration deviation value of the first moment and the second moment;
setting a threshold value of the aggregation degree, and judging whether the combined acceleration deviation values at the first moment and the second moment belong to the same cluster according to the threshold value and the aggregation degree; when the combined acceleration deviation values at the first moment and the second moment belong to the same cluster, judging whether the combined acceleration deviation value at the third moment belongs to the current cluster according to the cluster degree, when the combined acceleration deviation value at the third moment belongs to the current cluster, continuously judging whether the combined acceleration deviation value at the fourth moment belongs to the current cluster, and sequentially judging whether the combined acceleration deviation values at the other moments belong to the current cluster; when the combined acceleration deviation values at the first moment and the second moment do not belong to the same cluster, the combined acceleration deviation value at the first moment is taken as the first cluster, the combined acceleration deviation value at the second moment is taken as the second cluster, whether the combined acceleration deviation value at the third moment and the combined acceleration deviation value at the second moment belong to the same cluster or not is judged, whether the combined acceleration deviation values at the other moments belong to the second cluster or not is judged in sequence, when the combined acceleration deviation value at one moment does not belong to the second cluster, clustering of the second cluster is completed, clustering of the third cluster is started until all the combined acceleration deviation values at each moment are clustered, and a plurality of clusters of the combined acceleration deviation values in the time period are obtained.
6. The high-rise elevator operation abnormality warning method according to claim 5, characterized in that the degree of aggregation of the resultant acceleration deviation values at the first time and the second time is determined by the following formula:
Figure 63186DEST_PATH_IMAGE007
in the formula (I), the compound is shown in the specification,
Figure 392667DEST_PATH_IMAGE008
the aggregation degree of the combined acceleration deviation values at the first time and the second time;
Figure 30322DEST_PATH_IMAGE009
the deviation value of the resultant acceleration at the first moment is taken as a deviation value of the resultant acceleration at the first moment;
Figure 304309DEST_PATH_IMAGE010
the combined acceleration deviation value at the second moment;
Figure 701923DEST_PATH_IMAGE011
is the time interval value between the second time and the first time,
Figure 744965DEST_PATH_IMAGE012
which indicates the time of the second moment in time,
Figure 819101DEST_PATH_IMAGE013
indicating a first time instant.
7. The high-rise elevator operation abnormality warning method according to claim 1, characterized in that the jitter value of the elevator in each cluster time period is determined by the following formula:
Figure 845963DEST_PATH_IMAGE014
in the formula (I), the compound is shown in the specification,
Figure 781689DEST_PATH_IMAGE015
for elevators at first
Figure 69451DEST_PATH_IMAGE016
Jitter values over a number of clustering time periods;
Figure 189853DEST_PATH_IMAGE017
is as follows
Figure 310869DEST_PATH_IMAGE016
In a clustering period
Figure 909340DEST_PATH_IMAGE018
A plurality of x-axis direction velocity deviation values;
Figure 317188DEST_PATH_IMAGE019
is as follows
Figure 608492DEST_PATH_IMAGE016
Within a cluster time period
Figure 219733DEST_PATH_IMAGE018
A y-axis direction velocity deviation value;
Figure 887475DEST_PATH_IMAGE020
is as follows
Figure 884249DEST_PATH_IMAGE016
In a clustering period
Figure 221821DEST_PATH_IMAGE018
A z-axis direction velocity offset value;
Figure 179413DEST_PATH_IMAGE021
is as follows
Figure 775479DEST_PATH_IMAGE016
A total number of resultant acceleration deviation values within a number of clustering time periods;
Figure 377493DEST_PATH_IMAGE022
representing the clustering of acceleration deviation values in the x-axis direction;
Figure 745020DEST_PATH_IMAGE023
representing the clustering of acceleration deviation values in the y-axis direction;
Figure 314542DEST_PATH_IMAGE024
indicating the convergence of acceleration deviation values in the z-axis direction.
8. The method for alarming operation abnormality of a high-rise elevator according to claim 1, wherein the process of obtaining the entropy of angular point optical flow information in each cluster time period further includes setting a threshold value of the entropy of the angular point optical flow information, and when the entropy of the angular point optical flow information is larger than the threshold value of the entropy, obtaining a horizontal influence value and a vertical influence value of a human body action on a horizontal direction acceleration deviation value and a vertical direction acceleration deviation value in each cluster.
9. The high-rise elevator operation abnormality warning method according to claim 1, characterized in that the abnormality value of the elevator in each cluster time period is determined by the following formula:
Figure 936803DEST_PATH_IMAGE025
in the formula (I), the compound is shown in the specification,
Figure 783536DEST_PATH_IMAGE026
is as follows
Figure 977757DEST_PATH_IMAGE016
Abnormal values of elevators in a cluster time period;
Figure 909941DEST_PATH_IMAGE027
is as follows
Figure 332963DEST_PATH_IMAGE016
Horizontal influence values of human body actions on the speed deviation value in the x-axis direction in each clustering time period;
Figure 627678DEST_PATH_IMAGE028
is a first
Figure 743533DEST_PATH_IMAGE016
Horizontal influence values of human body actions on the speed deviation value in the y-axis direction in each clustering time period;
Figure 897434DEST_PATH_IMAGE029
is a first
Figure 107835DEST_PATH_IMAGE016
Human body action pair z-axis direction speed deviation in a cluster time periodVertical influence from value;
Figure 804527DEST_PATH_IMAGE017
is as follows
Figure 950338DEST_PATH_IMAGE016
In a clustering period
Figure 716168DEST_PATH_IMAGE018
A plurality of x-axis direction velocity deviation values;
Figure 478063DEST_PATH_IMAGE019
is as follows
Figure 153895DEST_PATH_IMAGE016
In a clustering period
Figure 595241DEST_PATH_IMAGE018
A y-axis direction velocity offset value;
Figure 599100DEST_PATH_IMAGE020
is as follows
Figure 151304DEST_PATH_IMAGE016
Within a cluster time period
Figure 947222DEST_PATH_IMAGE018
A z-axis direction velocity offset value;
Figure 310201DEST_PATH_IMAGE022
representing the clustering of acceleration deviation values in the x-axis direction;
Figure 925990DEST_PATH_IMAGE023
representing the clustering of acceleration deviation values in the y-axis direction;
Figure 281885DEST_PATH_IMAGE024
representing the aggregability of acceleration deviation values in the z-axis direction;
Figure 807676DEST_PATH_IMAGE021
is as follows
Figure 466190DEST_PATH_IMAGE016
A total number of resultant acceleration deviation values within the respective cluster time period.
10. The method of claim 9, wherein the determining whether the elevator is abnormally operated in each cluster time period according to the abnormal value further comprises setting a threshold of the abnormal value, wherein the threshold of the abnormal value is 0.8, and when the abnormal value is greater than the threshold of the abnormal value, the elevator is abnormally operated in the cluster time period corresponding to the abnormal value, and starting an elevator abnormal alarm system.
CN202211205497.1A 2022-09-30 2022-09-30 High-rise elevator operation abnormity alarming method Pending CN115352977A (en)

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