CN113184650B - Elevator safety operation and maintenance monitoring method and system for smart city - Google Patents
Elevator safety operation and maintenance monitoring method and system for smart city Download PDFInfo
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- CN113184650B CN113184650B CN202110357237.5A CN202110357237A CN113184650B CN 113184650 B CN113184650 B CN 113184650B CN 202110357237 A CN202110357237 A CN 202110357237A CN 113184650 B CN113184650 B CN 113184650B
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- 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
- B66B5/0031—Devices monitoring the operating condition of the elevator system for safety reasons
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- 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
- B66B5/0012—Devices monitoring the users of the elevator system
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- 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
Abstract
The invention discloses a method and a system for monitoring the safe operation and maintenance of an elevator in a smart city, wherein stress data are collected in real time through a strain sensor arranged on a cable of the elevator; preprocessing the stress data; constructing an elevator safety early warning model; the early warning value of the elevator cable is calculated in real time through an elevator safety early warning model, and risk judgment is intelligently carried out through comparison between the early warning value and a threshold value; can all-weather carry out safety inspection and early warning to the elevator hawser to through the intelligent judgement of stress analog value or true collection value, reach intelligent judgement elevator fast and whether be in safe state, and propelling movement early warning information gives maintainer, can appear ageing or metal fatigue risk in the elevator hawser and send the early warning in advance, improved the security that the elevator hawser detected.
Description
Technical Field
The disclosure belongs to the technical field of smart cities and elevator operation and maintenance, and particularly relates to an elevator safety operation and maintenance monitoring method and system for a smart city.
Background
At present, various problems of occasional maintenance faults and people injury and trapping caused by power failure exist in an elevator, and the technical means for preventing the problems is to perform maintenance and monitoring manually and perform alarm through a button type alarm bell in the elevator. The elevator safety monitoring method comprises the steps that a user needs to stay on a floor for a long time or mistakenly touches the elevator, a false alarm is frequently triggered, or the user on duty is not noticed or is absent, so that the user of the elevator is trapped in a long time to cause danger, the interference or intelligent warning signal is difficult to identify through the current technical means, the elevator can be confirmed to be in fault through the means of inquiring the trapped person through an interphone in the elevator, and the like.
Disclosure of Invention
The invention aims to provide a method and a system for monitoring the safety operation and maintenance of an elevator in a smart city, which are used for solving one or more technical problems in the prior art and at least providing a beneficial choice or creation condition.
In order to achieve the above object, according to an aspect of the present disclosure, there is provided an elevator safety operation and maintenance monitoring method for a smart city, the method including the steps of:
s100, collecting real-time stress data of a cable of the elevator;
s200, preprocessing stress data;
s300, constructing an elevator safety early warning model;
s400, calculating an early warning value of a cable of the elevator in real time through an elevator safety early warning model;
s500, when the early warning value is lower than a set threshold value, judging whether a living body exists in the elevator through a sensor, if the living body does not exist, directly closing an elevator door, and pushing elevator fault information to a maintainer;
s600, if the living body exists in the elevator, the elevator stops and pushes elevator fault information to a maintainer, the elevator door is opened to carry out voice prompt, namely 'elevator fault, please leave the elevator', and the elevator door is closed after the living body in the elevator leaves.
Further, in S200, the method for preprocessing the stress data includes: mean interpolation is performed on missing values and data smoothing or bayesian parameter smoothing is performed based on historical data.
Further, in S300, the method for constructing the elevator safety precaution model includes the following steps:
s301, calculating the stress ratio of the elevator rope: h ═ B × kEt÷(1-W)，EtE1+ E2-E3, wherein: h is the stress ratio to which the elevator rope is subjected, B is the rope spring coefficient of the elevator rope specified according to GBT8903-2018, k is the temperature linear expansion coefficient of the elevator ropeGenerally 12X 10-12，EtFor the load factor of the average tension experienced by the elevator rope during the most recent time interval t, E1 is the maximum tension of the elevator rope during the most recent time interval t calculated according to GB12141-2008, E2 is the average tension of the elevator rope during the most recent time interval t, E3 is the specific gravity of the rope, W is the poisson's ratio of the elevator rope material, t is the set time interval, t is in the range of [10,60 ] values]The method comprises the following steps of (1) taking minutes;
s302, an elevator safety early warning model is constructed as
Wherein, max { HT-t,HTMin { H } is the maximum value of the stress ratio H to which the elevator rope is subjected in the time period from the time T-T to the time TT-t,HTAnd the value is the minimum value of the stress ratio H borne by the elevator cable in the time period from the time T-T to the time T, the time T is the current time, and the time G is an early warning value obtained by the calculation of the elevator safety early warning model.
Further, in S300, the method for constructing the elevator safety precaution model may further include:
s303, constructing an elevator safety early warning model as
Wherein, max { FT-t,FTMin { F } is the maximum value of the stress data F borne by the elevator rope in the time period from the moment T-T to the moment TT-t,FTThe stress data F of the elevator cable in the time period from the T-T moment to the T moment is the minimum value, T is the current moment, wherein each moment is the duration or 1 second of data collected by the sensor once, T is a set time interval, and the value range of T is [10,60 ]]And G is an early warning value calculated by the elevator safety early warning model in minutes.
Further, in S500, the method for calculating the set threshold value is: taking [1,2] times of the average value of the early warning values obtained by calculation within the latest time interval t as a threshold value; if the acquisition time for starting to acquire the stress data is less than t, the threshold value is 1,2 times of the early warning value obtained by first calculation or is fixedly set to be 1 ton; there may also be the following: if the acquisition time for starting to acquire the stress data is less than t, the threshold value is not set at the beginning temporarily, and when the acquisition time for acquiring the stress data is more than or equal to t, the threshold value is set as [1,2] times of the average value of the early warning values calculated within the latest time interval t.
Further, in S500, the sensors used for determining whether or not there is a living body in the elevator by the sensors are: one of pyroelectric infrared sensor, thermal infrared human body inductor, radar response module RCWL-0516 when judging whether have the live body in the elevator, whether have the passenger in detecting the elevator car with the sensor promptly.
The invention also provides an elevator safety operation and maintenance monitoring system of the smart city, which comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, the processor executing the computer program to run in the units of the following system:
the network initialization unit is used for acquiring stress data in real time through a strain type sensor arranged on a cable of the elevator;
the stress preprocessing unit is used for preprocessing the stress data;
the early warning model building unit is used for building an elevator safety early warning model;
the early warning value calculating unit is used for calculating the early warning value of the cable rope of the elevator in real time through the safety early warning model of the elevator;
the living body detection unit is used for judging whether a living body exists in the elevator or not through the sensor when the early warning value is lower than a set threshold value, and if the living body does not exist, the elevator door is directly closed, and elevator fault information is pushed to a maintainer;
the elevator fault alarm unit is used for stopping the elevator and pushing elevator fault information to a maintainer if a living body exists in the elevator, opening the elevator door to perform voice prompt, namely 'elevator fault and please leave the elevator', and closing the elevator door after the living body in the elevator leaves.
The beneficial effect of this disclosure does: the invention provides an elevator safety operation and maintenance monitoring method and system for a smart city, which can carry out safety detection and early warning on an elevator cable all weather, can quickly and intelligently judge whether an elevator is in a safety state or not through intelligent judgment of a stress simulation value or a real acquisition value, can push early warning information to maintenance personnel, can send out early warning in advance before the elevator cable is aged or metal fatigue risks, and improves the safety of elevator cable detection.
Drawings
The foregoing and other features of the present disclosure will become more apparent from the detailed description of the embodiments shown in conjunction with the drawings in which like reference characters designate the same or similar elements throughout the several views, and it is apparent that the drawings in the following description are merely some examples of the present disclosure and that other drawings may be derived therefrom by those skilled in the art without the benefit of any inventive faculty, and in which:
fig. 1 is a flow chart of a method for monitoring the safety operation and maintenance of an elevator in a smart city;
fig. 2 is a structural diagram of an elevator safety operation and maintenance monitoring system in a smart city.
Detailed Description
The conception, specific structure and technical effects of the present disclosure will be clearly and completely described below in conjunction with the embodiments and the accompanying drawings to fully understand the objects, aspects and effects of the present disclosure. It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict.
Fig. 1 is a flow chart of a method for monitoring the safety operation and maintenance of an elevator in a smart city, and the following describes a method for monitoring the safety operation and maintenance of an elevator in a smart city according to an embodiment of the present invention with reference to fig. 1, the method includes the following steps:
s100, acquiring stress data in real time through a strain sensor arranged on an elevator cable, an ASMC1-9 dynamic strain gauge or an ASMB6-60 stress strain acquisition device;
s200, preprocessing the stress data;
s300, constructing an elevator safety early warning model;
s400, calculating an early warning value of a cable of the elevator in real time through an elevator safety early warning model;
s500, when the early warning value is lower than a set threshold value, judging whether a living body exists in the elevator through a sensor, if the living body does not exist, directly closing an elevator door, and pushing elevator fault information to a maintainer;
s600, if the living body exists in the elevator, the elevator stops and pushes elevator fault information to a maintainer, the elevator door is opened to carry out voice prompt, namely 'elevator fault, please leave the elevator', and the elevator door is closed after the living body in the elevator leaves.
Further, in S200, the method for preprocessing the stress data includes: mean interpolation is performed on missing values and data smoothing or bayesian parameter smoothing is performed based on historical data.
Further, in S300, the method for constructing the elevator safety precaution model includes the following steps:
s301, calculating the stress ratio of the elevator rope: h ═ B × kEt÷(1-W)，EtE1+ E2-E3, wherein: h is the stress ratio to which the elevator rope is subjected, B is the rope spring coefficient of the elevator rope specified according to GBT8903-2018, k is the temperature linear expansion coefficient of the elevator rope, and k is generally 12 x 10-12，EtFor the load factor of the average tension experienced by the elevator rope during the most recent time interval t, E1 is the maximum tension of the elevator rope during the most recent time interval t calculated according to GB12141-2008, E2 is the average tension of the elevator rope during the most recent time interval t, E3 is the specific gravity of the rope, W is the poisson's ratio of the elevator rope material, t is the set time interval, t is in the range of [10,60 ] values]The method comprises the following steps of (1) taking minutes;
s302, an elevator safety early warning model is constructed as
Wherein, max { HT-t,HTMin { H } is the maximum value of the stress ratio H to which the elevator rope is subjected in the time period from the time T-T to the time TT-t,HTAnd the value is the minimum value of the stress ratio H borne by the elevator cable in the time period from the time T-T to the time T, the time T is the current time, and the time G is an early warning value obtained by the calculation of the elevator safety early warning model.
Further, in S300, the method for constructing the elevator safety precaution model may further include:
s303, constructing an elevator safety early warning model as
Wherein, max { FT-t,FTMin { F } is the maximum value of the stress data F borne by the elevator rope in the time period from the moment T-T to the moment TT-t,FTThe stress data F of the elevator cable in the time period from the T-T moment to the T moment is the minimum value, T is the current moment, wherein each moment is the duration or 1 second of data collected by the sensor once, T is a set time interval, and the value range of T is [10,60 ]]And G is an early warning value calculated by the elevator safety early warning model in minutes.
Further, in S500, the method for calculating the set threshold value is: taking [1,2] times of the average value of the early warning values obtained by calculation within the latest time interval t as a threshold value; if the acquisition time for starting to acquire the stress data is less than t, the threshold value is 1,2 times of the early warning value obtained by first calculation or is fixedly set to be 1 ton; there may also be the following: if the acquisition time for starting to acquire the stress data is less than t, the threshold value is not set at the beginning temporarily, and when the acquisition time for acquiring the stress data is more than or equal to t, the threshold value is set as [1,2] times of the average value of the early warning values calculated within the latest time interval t.
Further, in S500, the sensors used for determining whether or not there is a living body in the elevator by the sensors are: one of pyroelectric infrared sensor, thermal infrared human body inductor, radar response module RCWL-0516 when judging whether have the live body in the elevator, whether have the passenger in detecting the elevator car with the sensor promptly.
The elevator safety operation and maintenance monitored control system in wisdom city that this disclosed embodiment provided, it is this the elevator safety operation and maintenance monitored control system structure picture in wisdom city as shown in figure 2, the elevator safety operation and maintenance monitored control system in wisdom city of this embodiment includes: the elevator safety operation and maintenance monitoring system comprises a processor, a memory and a computer program which is stored in the memory and can run on the processor, wherein the processor executes the computer program to realize the steps in the elevator safety operation and maintenance monitoring system embodiment of the smart city.
The system comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, the processor executing the computer program to run in the units of the following system:
the network initialization unit is used for acquiring stress data in real time through a strain type sensor arranged on a cable of the elevator;
the stress preprocessing unit is used for preprocessing the stress data;
the early warning model building unit is used for building an elevator safety early warning model;
the early warning value calculation unit is used for calculating the early warning value of the elevator cable in real time through the elevator safety early warning model;
the living body detection unit is used for judging whether a living body exists in the elevator or not through the sensor when the early warning value is lower than a set threshold value, and if the living body does not exist, the elevator door is directly closed, and elevator fault information is pushed to a maintainer;
the elevator fault alarm unit is used for stopping the elevator and pushing elevator fault information to a maintainer if a living body exists in the elevator, opening the elevator door to perform voice prompt, namely 'elevator fault, please leave the elevator', and closing the elevator door after the living body in the elevator leaves.
The elevator safety operation and maintenance monitoring system for the smart city can operate in computing equipment such as a desktop computer, a notebook computer, a palm computer and a cloud server. The elevator safety operation and maintenance monitoring system for the smart city can operate by a system comprising, but not limited to, a processor and a memory. It will be understood by those skilled in the art that the example is only an example of the elevator safety operation and maintenance monitoring system of a smart city, and does not constitute a limitation of the elevator safety operation and maintenance monitoring system of a smart city, and may include more or less components than the elevator safety operation and maintenance monitoring system of a smart city, or combine some components, or different components, for example, the elevator safety operation and maintenance monitoring system of a smart city may further include an input-output device, a network access device, a bus, and the like.
The Processor may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component, or the like. The general processor can be a microprocessor or the processor can be any conventional processor and the like, the processor is a control center of the elevator safety operation and maintenance monitoring system operation system of the smart city, and various interfaces and lines are used for connecting all parts of the elevator safety operation and maintenance monitoring system operable system of the whole smart city.
The memory can be used for storing the computer program and/or the module, and the processor realizes various functions of the elevator safety operation and maintenance monitoring system of the smart city by operating or executing the computer program and/or the module stored in the memory and calling the data stored in the memory. The memory may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data (such as audio data, a phonebook, etc.) created according to the use of the cellular phone, and the like. In addition, the memory may include high speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), at least one magnetic disk storage device, a Flash memory device, or other volatile solid state storage device.
Although the description of the present disclosure has been rather exhaustive and particularly described with respect to several illustrated embodiments, it is not intended to be limited to any such details or embodiments or any particular embodiments, so as to effectively encompass the intended scope of the present disclosure. Furthermore, the foregoing description of the present disclosure has been presented in terms of embodiments foreseen by the inventors for purposes of providing a useful description, and enabling one of ordinary skill in the art to devise equivalent variations of the present disclosure that are not presently foreseen.
Claims (7)
1. The elevator safety operation and maintenance monitoring method for the smart city is characterized by comprising the following steps:
s100, collecting real-time stress data of a cable of the elevator;
s200, preprocessing stress data;
s300, constructing an elevator safety early warning model;
s400, calculating an early warning value of a cable of the elevator in real time through an elevator safety early warning model;
the method for constructing the elevator safety early warning model comprises the following steps:
s301, calculating the stress ratio of the elevator rope: h = -B × kEt÷(1-W)，Et= E1+ E2-E3 wherein: h is the stress ratio of the elevator rope, B is the elastic coefficient of the steel wire rope of the elevator rope, k is the temperature linear expansion coefficient of the elevator rope, E is the load factor of the average tension of the elevator rope in the latest time interval t, E1 is the maximum tension of the elevator rope in the latest time interval t, E2 is the average value of the tension of the elevator rope in the latest time interval t, E3 is the unit gravity of the steel wire rope, W is the Poisson ratio of the elevator rope material, t is the set time interval, and t has the value range of [10,60 ]]The method comprises the following steps of (1) taking minutes;
s302, an elevator safety early warning model is constructed as
Wherein, max { HT-t,HTMin { H } is the maximum value of the stress ratio H to which the elevator rope is subjected in the time period from the time T-T to the time TT-t,HTAnd the value is the minimum value of the stress ratio H borne by the elevator cable in the time period from the time T-T to the time T, the time T is the current time, and the time G is an early warning value obtained by the calculation of the elevator safety early warning model.
2. The method as claimed in claim 1, wherein the method further comprises the following steps:
s500, when the early warning value is lower than a set threshold value, judging whether a living body exists in the elevator through a sensor, if the living body does not exist, directly closing an elevator door, and pushing elevator fault information to a maintainer;
s600, if the living body exists in the elevator, the elevator stops and pushes elevator fault information to a maintainer, the elevator door is opened to carry out voice prompt, namely 'elevator fault, please leave the elevator', and the elevator door is closed after the living body in the elevator leaves.
3. The method for monitoring the safety operation and maintenance of the elevator in the smart city according to claim 1, wherein in S200, the method for preprocessing the stress data comprises the following steps: mean interpolation is performed on missing values and data smoothing or bayesian parameter smoothing is performed based on historical data.
4. The method of claim 1, wherein in S300, the method for constructing the elevator safety early warning model further comprises:
s303, constructing an elevator safety early warning model as
Wherein max { F }T-t,FTIs between T-T time and T timeMaximum value of the stress data F experienced by the elevator rope during the time period of (d), min { F }T-t,FTThe stress data F of the elevator cable in the time period from the T-T moment to the T moment is the minimum value, T is the current moment, wherein each moment is the duration or 1 second of data collected by the sensor once, T is a set time interval, and the value range of T is [10,60 ]]And G is an early warning value calculated by the elevator safety early warning model in minutes.
5. The method as claimed in claim 1, wherein the threshold is set in S500 by a method comprising: taking [1,2] times of the average value of the early warning values obtained by calculation within the latest time interval t as a threshold value; if the acquisition time for starting to acquire the stress data is less than t, taking the [1,2] times of the early warning value obtained by the first calculation as a threshold value; there may also be the following: if the acquisition time for starting to acquire the stress data is less than t, the threshold value is not set at the beginning temporarily, and when the acquisition time for acquiring the stress data is more than or equal to t, the threshold value is set to be [1,2] times of the average value of the early warning values calculated in the latest time interval t.
6. The method for monitoring the safety operation and maintenance of the elevator in the smart city according to claim 1, wherein in S500, the sensors used for judging whether the living body exists in the elevator through the sensors are as follows: one of pyroelectric infrared sensor, thermal infrared human body inductor, radar response module RCWL-0516 when judging whether have the live body in the elevator, whether have the passenger in detecting the elevator car with the sensor promptly.
7. The utility model provides an elevator safety operation and maintenance monitored control system in wisdom city which characterized in that, the system includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, the processor executing the computer program to run in the units of the following system:
the network initialization unit is used for acquiring stress data in real time through a strain type sensor arranged on a cable of the elevator;
the stress preprocessing unit is used for preprocessing the stress data;
the early warning model building unit is used for building an elevator safety early warning model;
the early warning value calculation unit is used for calculating the early warning value of the elevator cable in real time through the elevator safety early warning model;
the living body detection unit is used for judging whether a living body exists in the elevator or not through the sensor when the early warning value is lower than a set threshold value, and if the living body does not exist, the elevator door is directly closed, and elevator fault information is pushed to a maintainer;
the elevator fault alarm unit is used for stopping the elevator and pushing elevator fault information to a maintainer if a living body exists in the elevator, opening the elevator door to perform voice prompt, namely 'elevator fault please leave the elevator', and closing the elevator door after the living body in the elevator leaves;
the method for constructing the elevator safety early warning model comprises the following steps of:
s301, calculating the stress ratio of the elevator rope: h = -B × kEt÷(1-W)，Et= E1+ E2-E3 wherein: h is the stress ratio of the elevator rope, B is the elastic coefficient of the steel wire rope of the elevator rope, k is the temperature linear expansion coefficient of the elevator rope, E is the load factor of the average tension of the elevator rope in the latest time interval t, E1 is the maximum tension of the elevator rope in the latest time interval t, E2 is the average value of the tension of the elevator rope in the latest time interval t, E3 is the unit gravity of the steel wire rope, W is the Poisson ratio of the elevator rope material, t is the set time interval, and t has the value range of [10,60 ]]The method comprises the following steps of (1) taking minutes;
s302, an elevator safety early warning model is constructed as
Wherein, max { HT-t,HTMin { H } is the maximum value of the stress ratio H to which the elevator rope is subjected in the time period from the time T-T to the time TT-t,HTAnd the value is the minimum value of the stress ratio H borne by the elevator cable in the time period from the time T-T to the time T, the time T is the current time, and the time G is an early warning value obtained by the calculation of the elevator safety early warning model.
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