CN115557349B - Intelligent home elevator based on Internet of things and detection method - Google Patents
Intelligent home elevator based on Internet of things and detection method Download PDFInfo
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- CN115557349B CN115557349B CN202211547378.4A CN202211547378A CN115557349B CN 115557349 B CN115557349 B CN 115557349B CN 202211547378 A CN202211547378 A CN 202211547378A CN 115557349 B CN115557349 B CN 115557349B
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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
- B66B5/0037—Performance analysers
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- Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
- Y02B50/00—Energy efficient technologies in elevators, escalators and moving walkways, e.g. energy saving or recuperation technologies
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Abstract
The invention relates to the technical field of intelligent home elevators, in particular to an intelligent home elevator based on the Internet of things and a detection method, wherein the intelligent home elevator comprises a setting module, a detection module and a detection module, wherein the setting module is used for detecting real-time data of a plurality of running elevators in a detection period; the receiving module is used for receiving elevator fault data in any detection period; the analysis module is used for carrying out data analysis on the fault data so as to determine an elevator health index; the evaluation module is used for evaluating the running state of the elevator according to the elevator health index; the statistical module is used for counting the minimum time interval between adjacent faults of the running elevator; and the adjusting module is used for adjusting the duration of the detection period. According to the invention, the elevator health index is determined by carrying out data analysis on the elevator fault data, and the running state of the elevator is evaluated according to the elevator health index, so that the detection precision is improved, and the identification degree of the health condition and the potential safety hazard of the elevator is improved.
Description
Technical Field
The invention relates to the technical field of intelligent home elevators, in particular to an intelligent home elevator based on the Internet of things and a detection method.
Background
With the improvement of the living standard of people and the pursuit of high-income people on the living quality, the use range of the home elevator installed in a family is gradually improved, but the home elevator in the current market still has some problems in the aspect of intelligent detection.
Chinese patent publication no: CN111071889B discloses an elevator state identification system based on the internet of things, which compares the acceleration data running a complete day before with the set acceleration data by analyzing the complete acceleration data of the day before, and evaluates the health condition and the potential safety hazard of the elevator. Although the health of the elevator can be evaluated whether the acceleration is normal or not, the health and safety hazards of the elevator are not only reflected in the acceleration, and thus, the elevator state recognition system has the following problems: the detection precision is low, so that the health condition and potential safety hazard recognition degree of the elevator are low.
Disclosure of Invention
Therefore, the invention provides an intelligent household elevator based on the Internet of things and a detection method, which are used for solving the problems of low detection precision and low identification degree of health conditions and potential safety hazards of the elevator in the prior art.
In order to achieve the above objects, in one aspect, the present invention provides an intelligent home elevator based on the internet of things, comprising,
the device comprises a setting module, a detection module and a control module, wherein the setting module is used for setting a detection period and detecting real-time data of a plurality of running elevators in the detection period;
the system comprises a receiving module, a judging module and a judging module, wherein the receiving module is used for receiving elevator fault data in any detection period, and the elevator fault data comprises a fault name, fault times, fault frequency and fault repairing duration;
the analysis module is used for carrying out data analysis on the fault data to determine an elevator health index, and comprises a classification unit, a calculation unit, an adjustment unit and a correction unit, wherein the classification unit is used for dividing fault types according to fault names, the calculation unit is used for calculating the elevator health index according to fault times, the adjustment unit is used for adjusting the elevator health index according to fault frequencies, and the correction unit is used for correcting the adjusted elevator health index according to fault restoration duration;
the evaluation module is connected with the analysis module and used for evaluating the running state of the elevator according to the health index of the elevator;
the statistical module is used for counting the minimum time interval between adjacent faults of the running elevator which has any fault in the current detection period;
and the adjusting module is connected with the counting module and used for adjusting the duration of the detection period according to the relation between the minimum time interval and a preset time interval.
Further, the classification unit acquires a fault name when classifying the fault type, matches the fault name with a preset fault name, and classifies the fault type into a minor fault and a major fault according to a matching result.
Further, the calculation unit sets H =0.7 × Z/Z0+0.3 × Q/Q0 when calculating the elevator health index H, where Z is the major failure frequency, Z0 is the preset major failure frequency, Q is the minor failure frequency, and Q0 is the preset minor failure frequency.
Further, when the adjusting unit adjusts the elevator health index H, the adjusting unit acquires the failure frequency F, compares the failure frequency F with each preset failure frequency, and adjusts the elevator health index H according to the comparison result, wherein,
when F is less than or equal to F1, the adjusting unit does not adjust;
when F1 is more than F and less than F2, the adjusting unit selects an adjusting coefficient t1 to adjust the elevator health index H so as to reduce the elevator health index H, and t1 is more than 0.95 and less than 1;
when F is larger than or equal to F2, the adjusting unit selects an adjusting coefficient t2 to adjust the elevator health index H so as to reduce the elevator health index H, and t2= t1-t1 x (F-F2)/F is set;
when the ith adjusting coefficient ti is selected to adjust the elevator health index H, the adjusted elevator health index is set to be H ', and H' = H × ti is set.
Further, when the correction unit corrects the adjusted elevator health index H ', the correction unit acquires the fault repair time length S, compares the fault repair time length S with the preset fault repair time length S0, and corrects the adjusted elevator health index H' according to the comparison result, wherein,
when S is less than S0, the correcting unit does not perform correction;
and when S is larger than or equal to S0, the correction unit selects a correction coefficient m to correct the adjusted elevator health index H ' so as to reduce the adjusted elevator health index H ', sets the value of 0.88 < m < 1, sets the corrected elevator health index as H ' ', and sets the value of H ' ' = H ' × m.
Further, the evaluation module acquires the corrected elevator health index H '' when evaluating the elevator running state, compares the corrected elevator health index H '' with the preset elevator health index H0, and judges the elevator running state according to the comparison result, wherein,
when H '' is more than or equal to H0, the evaluation module judges the elevator to run safely;
when H "< H0, the evaluation module determines that the elevator is running at risk.
Further, the statistical module counts a minimum time interval between adjacent faults of any faulty running elevator within the current detection period, including,
presetting a time interval j1 between first adjacent faults and a time interval j2 between second adjacent faults, wherein j1 is less than j2;
if the time interval between adjacent faults of the running elevator is not less than j2, setting a first detection period JCT1;
if j1 is smaller than the time interval between adjacent faults of the running elevator and smaller than j2, setting a second detection period JCT2;
if the time interval between adjacent faults of the running elevator is less than or equal to j1, setting a third detection period JCT3;
wherein JCT3 is more than JCT2 and less than JCT1.
Further, when the time interval between adjacent faults of the running elevator is less than or equal to
When the detection time is multiplied by j1, the statistical module selects an adjusting coefficient a to adjust a third detection period JCT3, the setting is that a is more than 0.9 and less than 1, the adjusted third detection period is JCT3', and JCT3' = JCT3 × a is set.
Further, when the time interval between adjacent faults of the running elevator is less than or equal to
When the detection time is multiplied by j1, the statistical module selects a correction coefficient b to correct the adjusted third detection period JCT3', sets b to be more than 0.8 and less than 0.9, sets the corrected third detection period to be JCT3' ', and sets JCT3' '= JCT3' × b.
On the other hand, the invention provides a detection method of an intelligent home elevator based on the Internet of things, which comprises the following steps,
s1, setting a detection period, and detecting real-time data of a plurality of running elevators in the detection period;
s2, receiving elevator fault data in any detection period;
s3, performing data analysis on the fault data to determine an elevator health index, dividing fault types according to fault names through a classification unit, calculating the elevator health index through a calculation unit according to fault times after classification is completed, adjusting the elevator health index through an adjustment unit according to fault frequency after calculation is completed, and correcting the adjusted elevator health index through a correction unit according to fault repair duration after adjustment is completed;
s4, evaluating the running state of the elevator according to the health index of the elevator;
s5, counting the minimum time interval between adjacent faults of the running elevator which has faults randomly in the current detection period;
and S6, adjusting the duration of the detection period according to the relation between the minimum time interval and a preset time interval.
Compared with the prior art, the elevator running state detection method has the advantages that the detection period is set through the setting module, real-time data of a plurality of running elevators are detected in the detection period, the detection precision is improved through the setting of the detection period, elevator fault data are received through the receiving module in any detection period to ensure the precision of the elevator fault data, the fault data are subjected to data analysis through the analysis module to determine the elevator health index, the precision of the elevator health index is ensured, the elevator running state is evaluated through the evaluation module according to the elevator health index, the precision of the elevator running state judgment is improved, and the identification degree of the health condition and the potential safety hazard of the elevator is improved. The method comprises the steps that a counting module is used for counting the minimum time interval between adjacent faults of an operating elevator which has faults randomly in the current detection period, the minimum time interval between the adjacent faults of the operating elevator is obtained by counting the time interval between the adjacent faults of the operating elevator, the setting precision of the detection period is guaranteed, the detection precision is guaranteed, the duration of the detection period is adjusted by an adjusting module according to the relation between the minimum time interval and the preset time interval, the precision of the duration of the detection period is improved, the detection precision is improved, and the identification degree of the health condition and the potential safety hazard of the elevator is improved.
In particular, the fault types are divided by the classification unit to classify the fault degrees, so that the precision of fault data is improved.
Particularly, the elevator health index is calculated by assigning 0.7 times of weight to the ratio of the major fault frequency to the preset major fault frequency and assigning 0.3 times of weight to the ratio of the minor fault frequency to the preset minor fault frequency, different weights are assigned according to the fault weight, and the calculation mode of the ratio of each fault type frequency to the preset fault type frequency is adopted, so that the calculation precision of the elevator health index is improved.
Particularly, the elevator health index is adjusted through an adjusting unit to improve the accuracy of the elevator health index, the fault frequency F is obtained and compared with each preset fault frequency, and if the F is less than or equal to F1, the adjusting unit does not adjust; if the F1 is more than the F1 and less than the F2, the adjusting unit selects an adjusting coefficient t1 to adjust the elevator health index H so as to reduce the elevator health index H, and the t1 is more than 0.95 and less than 1; if F is larger than or equal to F2, the adjusting unit selects an adjusting coefficient t2 to adjust the elevator health index H so as to reduce the elevator health index H, and t2= t1-t1 x (F-F2)/F is set; different adjusting coefficients are selected according to different failure frequencies, and the adjusting precision is guaranteed, so that the precision of the elevator health index is improved.
Particularly, the adjusted elevator health index is corrected through a correction unit to improve the precision of the elevator health index, the fault repair time length S is obtained and is compared with the preset fault repair time length S0, and if S is less than S0, the correction unit does not perform correction; if S is larger than or equal to S0, the correction unit selects the correction coefficient m to correct the adjusted elevator health index H ' so as to reduce the adjusted elevator health index H ', sets the m to be more than 0.88 and less than 1, sets the corrected elevator health index to be H ' ', and sets H ' ' = H ' × m, thereby improving the precision of the elevator health index.
Particularly, the running state of the elevator is evaluated through an evaluation module so as to judge whether the elevator runs safely, the corrected health index H '' of the elevator is obtained and compared with a preset health index H0 of the elevator, and if the H '' is more than or equal to H0, the evaluation module judges that the elevator runs safely; if H '' is less than H0, the evaluation module judges that the elevator runs at risk, so that the evaluation precision is ensured.
Particularly, a statistical module is used for counting the minimum time interval between adjacent faults of an operating elevator which has faults randomly in the current detection period, a time interval j1 between first adjacent faults and a time interval j2 between second adjacent faults are preset, and j1 is smaller than j2; if the time interval between adjacent faults of the running elevator is not less than j2, setting a first detection period JCT1, if j1 is less than the time interval between adjacent faults of the running elevator and is less than j2, setting a second detection period JCT2, and if the time interval between adjacent faults of the running elevator is not more than j1, setting a third detection period JCT3, wherein JCT3 is less than JCT2 and is less than JCT1. Different detection periods are set through the size relation between the time interval between the adjacent faults of the running elevator and the time interval between the preset adjacent faults, so that the precision of the detection periods is ensured, and the detection precision is improved.
Particularly, by comparing the time interval between the adjacent faults of the running elevator with the preset time interval j1 between the first adjacent faults, if the time interval between the adjacent faults of the running elevator is less than or equal to two thirds of the preset time interval j1 between the first adjacent faults, the adjusting coefficient a is selected to adjust the third detection period JCT3, so that the precision of the detection period is ensured, and the detection precision is improved.
Particularly, by comparing the time interval between the adjacent faults of the running elevator with the preset time interval j1 between the first adjacent faults, if the time interval between the adjacent faults of the running elevator is less than or equal to one third of the preset time interval j1 between the first adjacent faults, the correction coefficient b is selected to correct the adjusted third detection period JCT3', so that the precision of the detection period is ensured, and the detection precision is improved.
Drawings
Fig. 1 is a schematic structural diagram of an intelligent home elevator based on the internet of things in the embodiment of the invention;
fig. 2 is another schematic structural diagram of an intelligent home elevator based on the internet of things in the embodiment of the invention;
fig. 3 is a schematic flow chart of an intelligent home elevator detection method based on the internet of things in the embodiment of the invention.
Detailed Description
In order that the objects and advantages of the invention will be more clearly understood, the invention is further described below with reference to examples; it should be understood that the specific embodiments described herein are merely illustrative of the invention and do not delimit the invention.
Preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only for explaining the technical principles of the present invention, and do not limit the scope of the present invention.
It should be noted that in the description of the present invention, the terms of direction or positional relationship indicated by the terms "upper", "lower", "left", "right", "inner", "outer", etc. are based on the directions or positional relationships shown in the drawings, which are only for convenience of description, and do not indicate or imply that the device or element must have a specific orientation, be constructed in a specific orientation, and be operated, and thus, should not be construed as limiting the present invention.
Furthermore, it should be noted that, in the description of the present invention, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be, for example, fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
Referring to fig. 1 to 2, which are schematic structural views of an intelligent home elevator based on the internet of things in the embodiment of the present invention, an intelligent home elevator based on the internet of things is disclosed, including,
the device comprises a setting module 10, a detecting module and a control module, wherein the setting module is used for setting a detection period and detecting real-time data of a plurality of running elevators in the detection period;
the receiving module 20 is used for receiving elevator fault data in any detection period, wherein the elevator fault data comprise fault names, fault times, fault frequency and fault repair duration;
the analysis module 30 is used for performing data analysis on the fault data to determine an elevator health index, and comprises a classification unit, a calculation unit, an adjustment unit and a correction unit, wherein the classification unit is used for classifying fault types according to fault names, the calculation unit is used for calculating the elevator health index according to fault times, the adjustment unit is used for adjusting the elevator health index according to fault frequencies, and the correction unit is used for correcting the adjusted elevator health index according to fault restoration duration;
the evaluation module 40 is connected with the analysis module and used for evaluating the running state of the elevator according to the elevator health index;
a statistical module 50 for counting the minimum time interval between adjacent faults of any fault-occurred running elevator in the current detection period;
and an adjusting module 60, connected to the counting module, for adjusting the duration of the detection period according to the relationship between the minimum time interval and a preset time interval.
Specifically, in the embodiment of the present invention, the receiving module 20 is connected to the setting module 10, the analyzing module 30 is connected to the receiving module 20, the evaluating module 40 is connected to the analyzing module 30, the counting module 50 is connected to the evaluating module 40, and the adjusting module 60 is connected to the counting module 50, as shown in fig. 2, the analyzing module 30 includes a classifying unit 31, a calculating unit 32, an adjusting unit 33, and a correcting unit 34, the calculating unit 32 is connected to the classifying unit 31, the adjusting unit 33 is connected to the calculating unit 32, and the correcting unit 34 is connected to the adjusting unit 33.
Specifically, the detection period is set through the setting module, real-time data of a plurality of running elevators are detected in the detection period, the detection precision is improved through the setting of the detection period, elevator fault data are received through the receiving module in any detection period to ensure the precision of the elevator fault data, the fault data are subjected to data analysis through the analysis module to determine the elevator health index, so that the precision of the elevator health index is ensured, the running state of the elevator is evaluated through the evaluation module according to the elevator health index, the precision of judging the running state of the elevator is improved, and the identification degree of the health condition and the potential safety hazard of the elevator is improved. The method comprises the steps that a statistical module is used for counting the minimum time interval between adjacent faults of an operating elevator which randomly breaks down in the current detection period, the minimum time interval between the adjacent faults of the operating elevator is obtained by counting the time interval between the adjacent faults of the operating elevator, the setting precision of the detection period is guaranteed, the detection precision is guaranteed, the duration of the detection period is adjusted by an adjusting module according to the relation between the minimum time interval and a preset time interval, the precision of adjusting the duration of the detection period is improved, the detection precision is improved, and the identification degree of the health condition and the potential safety hazard of the elevator is improved.
Specifically, the classification unit acquires a fault name when classifying the fault type, matches the fault name with a preset fault name, and classifies the fault type into a minor fault and a major fault according to a matching result.
Specifically, in the embodiment of the present invention, the classification unit is preset with a fault type list, the fault type list corresponds to a fault name, a fault name matching method is not specifically limited in this embodiment, and a person skilled in the art can freely set the fault type list, for example, a method of searching in the preset fault type list through a fault name keyword, and other matching methods can be set, which only needs to meet requirements.
Specifically, the fault types are divided through the classification unit to classify the fault degrees, and the precision of fault data is improved.
Specifically, the calculation means sets H =0.7 × Z/Z0+0.3 × Q/Q0 when calculating the elevator health index H, where Z is the major failure frequency, Z0 is the preset major failure frequency, Q is the minor failure frequency, and Q0 is the preset minor failure frequency.
Specifically, the embodiment of the invention calculates the health index of the elevator by assigning 0.7 times of weight to the ratio of the major failure frequency to the preset major failure frequency and assigning 0.3 times of weight to the ratio of the minor failure frequency to the preset minor failure frequency, assigns different weights according to the weight of the failure, and improves the calculation precision of the health index of the elevator by a calculation mode of the ratio of the frequency of each failure type to the frequency of each preset failure type. Specifically, when the adjusting unit adjusts the elevator health index H, the adjusting unit acquires the failure frequency F, compares the failure frequency F with each preset failure frequency, and adjusts the elevator health index H according to the comparison result, wherein,
when F is less than or equal to F1, the adjusting unit does not adjust;
when F1 is more than F and less than F2, the adjusting unit selects an adjusting coefficient t1 to adjust the elevator health index H so as to reduce the elevator health index H, and t1 is more than 0.95 and less than 1;
when F is larger than or equal to F2, the adjusting unit selects an adjusting coefficient t2 to adjust the elevator health index H so as to reduce the elevator health index H, and t2= t1-t1 x (F-F2)/F is set;
when the ith adjusting coefficient ti is selected to adjust the elevator health index H, the adjusted elevator health index is set to be H ', and H' = H × ti is set.
Specifically, the elevator health index is adjusted through the adjusting unit to improve the accuracy of the elevator health index, the fault frequency F is obtained and compared with each preset fault frequency, and if the frequency F is less than or equal to F1, the adjusting unit does not adjust; if the F1 is more than the F1 and less than the F2, the adjusting unit selects an adjusting coefficient t1 to adjust the elevator health index H so as to reduce the elevator health index H, and the t1 is more than 0.95 and less than 1; if F is larger than or equal to F2, the adjusting unit selects an adjusting coefficient t2 to adjust the elevator health index H so as to reduce the elevator health index H, and t2= t1-t1 x (F-F2)/F is set; different adjusting coefficients are selected according to different failure frequencies, and the adjusting precision is guaranteed, so that the precision of the elevator health index is improved.
Specifically, when the correction unit corrects the adjusted elevator health index H ', the correction unit acquires the fault repair duration S, compares the fault repair duration S with the preset fault repair duration S0, and corrects the adjusted elevator health index H' according to the comparison result, wherein,
when S is less than S0, the correcting unit does not perform correction;
and when S is larger than or equal to S0, the correction unit selects a correction coefficient m to correct the adjusted elevator health index H ' so as to reduce the adjusted elevator health index H ', sets the value of 0.88 < m < 1, sets the corrected elevator health index as H ' ', and sets the value of H ' ' = H ' × m.
Specifically, the embodiment of the invention corrects the adjusted elevator health index through the correction unit to improve the accuracy of the elevator health index, obtains the fault repairing time length S and compares the fault repairing time length S with the preset fault repairing time length S0, and if S is less than S0, the correction unit does not correct the fault repairing time length S; and if S is larger than or equal to S0, the correction unit selects a correction coefficient m to correct the adjusted elevator health index H ' so as to reduce the adjusted elevator health index H ', sets the m to be more than 0.88 and less than 1, sets the corrected elevator health index to be H ' ', and sets H ' ' = H ' × m. Thereby improving the accuracy of the elevator health index.
Specifically, when the evaluation module evaluates the running state of the elevator, the evaluation module acquires a corrected elevator health index H '', compares the corrected elevator health index H '' with a preset elevator health index H0, and judges the running state of the elevator according to the comparison result, wherein,
when H '' is more than or equal to H0, the evaluation module judges the elevator to run safely;
when H "< H0, the evaluation module determines that the elevator is running at risk.
Specifically, the embodiment of the invention evaluates the running state of the elevator through an evaluation module so as to judge whether the elevator runs safely, and judges the running safety of the elevator by acquiring the corrected health index H '' of the elevator and comparing the health index H '' with a preset health index H0 of the elevator, if the H '' is more than or equal to H0, the evaluation module judges that the elevator runs safely; if H '' < H0, the assessment module determines that the elevator is at risk for operation. Thereby ensuring the accuracy of the evaluation.
Specifically, the statistical module counts the minimum time interval between adjacent faults of any fault-occurred running elevator in the current detection period, including,
presetting a time interval j1 between first adjacent faults and a time interval j2 between second adjacent faults, wherein j1 is less than j2;
if the time interval between adjacent faults of the running elevator is not less than j2, setting a first detection period JCT1;
if j1 is smaller than the time interval between adjacent faults of the running elevator and smaller than j2, setting a second detection period JCT2;
if the time interval between adjacent faults of the running elevator is less than or equal to j1, setting a third detection period JCT3;
wherein JCT3 is more than JCT2 and less than JCT1.
Specifically, the embodiment of the invention counts the minimum time interval between adjacent faults of the running elevator with any fault in the current detection period through a counting module, wherein the time interval j1 between the first adjacent faults and the time interval j2 between the second adjacent faults are preset, and j1 is more than j2; if the time interval between adjacent faults of the running elevator is not less than j2, a first detection period JCT1 is set, if j1 is less than the time interval between adjacent faults of the running elevator and is less than j2, a second detection period JCT2 is set, and if the time interval between adjacent faults of the running elevator is not more than j1, a third detection period JCT3 is set, wherein JCT3 is less than JCT2 and is less than JCT1. Different detection periods are set through the size relationship between the time interval between the adjacent faults of the running elevator and the time interval between the preset adjacent faults, so that the precision of the detection periods is ensured, and the detection precision is improved.
In particular when the time interval between adjacent faults of the operating elevator is ≦
When the detection time is multiplied by j1, the statistical module selects an adjusting coefficient a to adjust a third detection period JCT3, the setting is that a is more than 0.9 and less than 1, the adjusted third detection period is JCT3', and JCT3' = JCT3 × a is set.
Specifically, the embodiment of the invention compares the time interval between adjacent faults of the running elevator with the preset time interval j1 between first adjacent faults, and selects the adjustment coefficient a to adjust the third detection period JCT3 when the time interval between adjacent faults of the running elevator is less than or equal to two thirds of the preset time interval j1 between first adjacent faults, so as to ensure the precision of the detection period and improve the detection precision.
In particular when the time interval between adjacent faults of the operating elevator is ≦
When the detection time is multiplied by j1, the statistical module selects a correction coefficient b to correct the adjusted third detection period JCT3', sets the correction time to be 0.8 < b < 0.9, sets the corrected third detection period JCT3' as JCT3', and sets JCT3' = JCT3' × b.
Specifically, in the embodiment of the invention, the time interval between adjacent faults of the running elevator is compared with the preset time interval j1 between first adjacent faults, and if the time interval between adjacent faults of the running elevator is less than or equal to one third of the preset time interval j1 between first adjacent faults, the correction coefficient b is selected to correct the adjusted third detection period JCT3', so that the precision of the detection period is ensured, and the detection precision is improved.
Referring to fig. 3, which is a schematic flow chart of an intelligent home elevator detection method based on the internet of things in an embodiment of the present invention, discloses an intelligent home elevator detection method based on the internet of things, including,
step S1, setting a detection period, and detecting real-time data of a plurality of running elevators in the detection period;
s2, receiving elevator fault data in any detection period;
s3, performing data analysis on the fault data to determine an elevator health index, dividing fault types according to fault names through a classification unit, calculating the elevator health index through a calculation unit according to fault times after classification is completed, adjusting the elevator health index through an adjustment unit according to fault frequency after calculation is completed, and correcting the adjusted elevator health index through a correction unit according to fault repair duration after adjustment is completed;
s4, evaluating the running state of the elevator according to the health index of the elevator;
s5, counting the minimum time interval between adjacent faults of the running elevator which has any fault in the current detection period;
and S6, adjusting the duration of the detection period according to the relation between the minimum time interval and a preset time interval.
The intelligent home elevator detection method based on the internet of things is applied to the intelligent home elevator detection system based on the internet of things, can achieve the same technical effect, and is not repeated herein.
So far, the technical solutions of the present invention have been described in connection with the preferred embodiments shown in the drawings, but it is easily understood by those skilled in the art that the scope of the present invention is obviously not limited to these specific embodiments. Equivalent changes or substitutions of related technical features can be made by those skilled in the art without departing from the principle of the invention, and the technical scheme after the changes or substitutions can fall into the protection scope of the invention.
Claims (7)
1. An intelligent home elevator based on the Internet of things is characterized by comprising,
the device comprises a setting module, a detection module and a control module, wherein the setting module is used for setting a detection period and detecting real-time data of a plurality of running elevators in the detection period;
the system comprises a receiving module, a judging module and a judging module, wherein the receiving module is used for receiving elevator fault data in any detection period, and the elevator fault data comprises a fault name, fault times, fault frequency and fault repairing duration;
the analysis module is used for carrying out data analysis on the fault data to determine an elevator health index, and comprises a classification unit, a calculation unit, an adjustment unit and a correction unit, wherein the classification unit is used for dividing fault types according to fault names, the calculation unit is used for calculating the elevator health index according to fault times, the adjustment unit is used for adjusting the elevator health index according to fault frequencies, and the correction unit is used for correcting the adjusted elevator health index according to fault restoration time length;
the evaluation module is connected with the analysis module and used for evaluating the running state of the elevator according to the health index of the elevator;
the statistical module is used for counting the minimum time interval between adjacent faults of the running elevator which has any fault in the current detection period;
the adjusting module is connected with the counting module and used for adjusting the duration of the detection period according to the relation between the minimum time interval and a preset time interval;
when the calculation unit calculates the elevator health index H, setting H =0.7 xZ/Z0 +0.3 xQ/Q0, wherein Z is the major fault frequency, Z0 is the preset major fault frequency, Q is the slight fault frequency, and Q0 is the preset slight fault frequency;
when the adjusting unit adjusts the elevator health index H, the adjusting unit acquires the failure frequency F, compares the failure frequency F with each preset failure frequency and adjusts the elevator health index H according to the comparison result, wherein,
when F is less than or equal to F1, the adjusting unit does not adjust;
when F1 is larger than F and smaller than F2, the adjusting unit selects an adjusting coefficient t1 to adjust the elevator health index H so as to reduce the elevator health index H, and t1 is set to be larger than 0.95 and smaller than 1;
when F is larger than or equal to F2, the adjusting unit selects an adjusting coefficient t2 to adjust the elevator health index H so as to reduce the elevator health index H, and t2= t1-t1 x (F-F2)/F is set;
when an ith adjusting coefficient ti is selected to adjust the elevator health index H, the adjusted elevator health index is set to be H ', and H' = H × ti is set;
the correcting unit acquires the fault repairing time length S when correcting the adjusted elevator health index H ', compares the fault repairing time length S with the preset fault repairing time length S0, and corrects the adjusted elevator health index H' according to the comparison result, wherein,
when S is less than S0, the correction unit does not perform correction;
and when S is larger than or equal to S0, the correction unit selects a correction coefficient m to correct the adjusted elevator health index H ' so as to reduce the adjusted elevator health index H ', sets the m to be more than 0.88 and less than 1, sets the corrected elevator health index to be H ', and sets H ' = H ' × m.
2. The intelligent home elevator based on the Internet of things of claim 1, wherein the classification unit acquires a fault name when the fault type is classified, matches the fault name with a preset fault name, and classifies the fault type into a minor fault and a major fault according to a matching result.
3. The intelligent home elevator based on the internet of things of claim 1, wherein the evaluation module acquires the corrected elevator health index H 'when evaluating the running state of the elevator, compares the corrected elevator health index H' with a preset elevator health index H0, and judges the running state of the elevator according to the comparison result, wherein,
when H' is more than or equal to H0, the evaluation module judges the elevator to run safely;
when H' < H0, the evaluation module determines that the elevator is running at risk.
4. The intelligent home elevator based on the internet of things of claim 3, wherein the statistical module counts a minimum time interval between adjacent faults of any failed running elevator in a current detection period, comprising,
presetting a time interval j1 between first adjacent faults and a time interval j2 between second adjacent faults, wherein j1 is less than j2;
if the time interval between adjacent faults of the running elevator is not less than j2, setting a first detection period JCT1;
if j1 is smaller than the time interval between adjacent faults of the running elevator and smaller than j2, setting a second detection period JCT2;
if the time interval between adjacent faults of the running elevator is not more than j1, setting a third detection period JCT3;
wherein JCT3 is more than JCT2 and less than JCT1.
5. Intelligent home elevator based on internet of things according to claim 4, characterized in that between adjacent faults of running elevator
And then, the statistical module selects an adjusting coefficient a to adjust the third detection period JCT3, the setting is that a is more than 0.9 and less than 1, the adjusted third detection period is JCT3', and JCT3' = JCT3 × a is set.
6. Intelligent home elevator based on internet of things according to claim 5, characterized in that between adjacent faults of running elevator
And then, the statistical module selects a correction coefficient b to correct the adjusted third detection period JCT3', sets 0.8 & lt b & lt 0.9, sets the corrected third detection period JCT3' as JCT3', and sets JCT3' = JCT3' × b.
7. An intelligent home elevator based on the Internet of things is characterized by comprising the following steps of according to any one of claims 1 to 6,
s1, setting a detection period, and detecting real-time data of a plurality of running elevators in the detection period;
s2, receiving elevator fault data in any detection period;
s3, performing data analysis on the fault data to determine an elevator health index, dividing fault types according to fault names through a classification unit, calculating the elevator health index through a calculation unit according to fault times after classification is completed, adjusting the elevator health index through an adjustment unit according to fault frequency after calculation is completed, and correcting the adjusted elevator health index through a correction unit according to fault repair duration after adjustment is completed;
s4, evaluating the running state of the elevator according to the health index of the elevator;
s5, counting the minimum time interval between adjacent faults of the running elevator which has faults randomly in the current detection period;
and S6, adjusting the duration of the detection period according to the relation between the minimum time interval and a preset time interval.
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