CN110626904B - Elevator safety detection method and device, electronic equipment and readable storage medium - Google Patents
Elevator safety detection method and device, electronic equipment and readable storage medium Download PDFInfo
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- CN110626904B CN110626904B CN201910897440.4A CN201910897440A CN110626904B CN 110626904 B CN110626904 B CN 110626904B CN 201910897440 A CN201910897440 A CN 201910897440A CN 110626904 B CN110626904 B CN 110626904B
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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
- B66B5/02—Applications of checking, fault-correcting, or safety devices in elevators responsive to abnormal operating conditions
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- Indicating And Signalling Devices For Elevators (AREA)
Abstract
The application provides a safety detection method and device for an elevator, electronic equipment and a readable storage medium, and the method comprises the following steps: acquiring a pressure measurement value measured by each pressure sensor in at least one pressure sensor; analyzing and processing at least one pressure measurement value by using the trained neural network model to obtain a predicted inclination angle of the elevator; and determining whether the elevator is in a safe operation state or not according to the angle value of the predicted inclination angle. The pressure sensor arranged at the connecting point of the elevator can send a pressure measurement value measured by the pressure sensor to the electronic equipment, and the electronic equipment can predict the inclination angle of the elevator according to the pressure measurement value by utilizing a trained neural network model, so as to detect whether the elevator can run safely. The electronic equipment can receive the pressure measurement value sent by the pressure sensor at any time and carry out safety detection on the elevator, so that the running state of the elevator can be evaluated in time, and the safety of the elevator is improved.
Description
Technical Field
The application relates to the field of measurement, in particular to a method and a device for detecting safety of an elevator, electronic equipment and a readable storage medium.
Background
With the rapid development of economy in China, more and more high-rise buildings are built. In the construction process of high-rise buildings, the elevator plays an increasingly important role. During the operation of the elevator, dangerous conditions such as overload or loss of load, inclination of the elevator and the like may occur. When these dangerous situations occur, they can occur if they cannot be known in time, causing property damage on a light basis and endangering the life safety of people on a heavy basis. Therefore, how to effectively detect and evaluate the state of the elevator is of great significance to safe production.
Disclosure of Invention
An object of the embodiments of the present application is to provide a method and an apparatus for detecting elevator safety, an electronic device, and a readable storage medium, so as to solve a problem that an operation state of an elevator in the prior art cannot be known in time.
In a first aspect, an embodiment of the present application provides a safety detection method for an elevator, where at least one connection point of the elevator is provided with a pressure sensor, the method includes: acquiring a pressure measurement value measured by each pressure sensor in at least one pressure sensor; analyzing and processing at least one pressure measurement value by using the trained neural network model to obtain a predicted inclination angle of the elevator; and determining whether the elevator is in a safe operation state or not according to the angle value of the predicted inclination angle.
In the above embodiment, the pressure sensor disposed at the connection point of the elevator may send the pressure measurement value measured by the pressure sensor to the electronic device, and the electronic device may predict the inclination angle of the elevator according to the pressure measurement value by using the trained neural network model, so as to detect whether the elevator can operate safely. The electronic equipment can receive the pressure measurement value sent by the pressure sensor at any time and carry out safety detection on the elevator, so that the running state of the elevator can be evaluated in time, and the safety of the elevator is improved.
In one possible design, the determining whether the elevator is in a safe operating state based on the angle value of the predicted tilt angle includes: if the angle value of the predicted inclination angle is smaller than or equal to a preset threshold value, determining that the elevator is in a safe running state; and if the angle value of the predicted inclination angle is larger than a preset threshold value, determining that the elevator is not in a safe running state.
In the above embodiment, the electronic device determines whether the elevator is in the safe operation state according to the magnitude relation between the predicted inclination angle and the angle threshold, the determination process is simple, the speed of determining whether the elevator is in the safe operation state is increased, and the timeliness of the operation state evaluation of the elevator is further ensured.
In one possible design, after determining that the elevator is not in a safe operating state, the method further includes: and sending safety warning information representing that the elevator is not in a safe running state to the elevator so as to enable the elevator to play an alarm prompt.
In the above embodiment, when the elevator is not in the safe operation state, the electronic device may send the safety warning information to the elevator, so that an operator near the elevator may eliminate the safety risk of the elevator as soon as possible, thereby improving the safety of the elevator.
In one possible design, before the analyzing at least one pressure measurement using the trained neural network model, the method further includes: obtaining historical pressure measurements taken by each of the at least one pressure sensor; obtaining a historical inclination angle of the elevator corresponding to the historical pressure measurement value measured by at least one angle sensor; and taking a plurality of historical pressure measurement values as independent variables, taking the historical inclination angles as dependent variables, and training an initial neural network model to obtain a trained neural network model, wherein the trained neural network model comprises an incidence relation between at least one pressure measurement value and the inclination angle of the elevator.
In the above embodiment, the initial neural network model is trained using the historical pressure measurements and the historical tilt angles, so that the trained neural network model includes the association between at least one pressure measurement and the tilt angle of the elevator, and then the trained neural network model is used to predict the tilt angle of the elevator according to the pressure measurements.
In one possible design, the at least one connection point provided with a pressure sensor comprises a connection point of a bearing surface bearing the elevator and the bottom of the elevator, a connection point of a bracket connection with the lifting cage and a connection point of a bracket connection with the support wall.
In a second aspect, an embodiment of the present application provides an elevator safety detection apparatus, where the apparatus includes: the pressure measurement value obtaining module is used for obtaining the pressure measurement value measured by each pressure sensor in the at least one pressure sensor; the predicted inclination angle obtaining module is used for analyzing and processing at least one pressure measurement value by using the trained neural network model to obtain a predicted inclination angle of the elevator; and the running state determining module is used for determining whether the elevator is in a safe running state or not according to the angle value of the predicted inclination angle.
In one possible design, the operating condition determining module is further configured to determine that the elevator is in a safe operating condition when the angle value of the predicted inclination angle is less than or equal to a preset threshold value; and the controller is used for determining that the elevator is not in a safe running state when the angle value of the predicted inclination angle is larger than a preset threshold value.
In one possible design, the apparatus further includes: and the alarm reminding module is used for sending safety warning information for representing the running state of the elevator which is not in a safe state to the elevator so as to enable the elevator to play an alarm reminding.
In one possible design, the apparatus further includes: the historical measured value acquisition module is used for acquiring the historical pressure measured value measured by each pressure sensor in the at least one pressure sensor; the historical inclination angle acquisition module is used for acquiring the historical inclination angle of the elevator, which is measured by at least one angle sensor and corresponds to the historical pressure measurement value; and the model training module is used for training an initial neural network model by taking the plurality of historical pressure measurement values as independent variables and the historical inclination angles as dependent variables to obtain a trained neural network model, and the trained neural network model comprises the incidence relation between at least one pressure measurement value and the inclination angle of the elevator.
In a third aspect, the present application provides an electronic device, comprising: a processor, a memory and a bus, the memory storing machine-readable instructions executable by the processor, the processor and the memory communicating via the bus when the electronic device is running, the machine-readable instructions when executed by the processor performing the method of the first aspect or any of the alternative implementations of the first aspect.
In a fourth aspect, the present application provides a readable storage medium having stored thereon a computer program which, when executed by a processor, performs the method of the first aspect or any of the optional implementations of the first aspect.
In a fifth aspect, the present application provides a computer program product which, when run on a computer, causes the computer to perform the method of the first aspect or any possible implementation manner of the first aspect.
In order to make the aforementioned and other objects, features and advantages of the present invention comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments of the present application will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and that those skilled in the art can also obtain other related drawings based on the drawings without inventive efforts.
Fig. 1 is a schematic structural diagram of an elevator corresponding to an elevator safety detection method provided in an embodiment of the present application;
FIG. 2 is an enlarged view of a portion corresponding to region I of FIG. 1;
FIG. 3 shows a corresponding enlarged view of region II of FIG. 1;
fig. 4 is a schematic flow chart illustrating a method for detecting safety of an elevator according to an embodiment of the present disclosure;
fig. 5 is a partial schematic flow chart of a method for detecting safety of an elevator according to an embodiment of the present disclosure;
fig. 6 shows a schematic structural block diagram of an elevator safety detection device provided in an embodiment of the present application.
Icon: an elevator 100; a first pressure sensor 110; a second pressure sensor 120; a third pressure sensor 130; a fourth pressure sensor 140; a bracket 150; a connecting member 160; a lifting cage 200; the support wall 300.
Detailed Description
The technical solutions in the embodiments of the present application will be described below with reference to the drawings in the embodiments of the present application.
Referring to fig. 1 and 2, fig. 1 and 2 collectively illustrate an elevator 100 to be tested by the safety testing method for the elevator 100 according to an embodiment of the present application, in which the elevator 100 is formed by stacking a plurality of supports 150 in a direction perpendicular to the ground, adjacent supports 150 are detachably connected to each other, and the support 150 at the bottom of the elevator 100 is detachably connected to the ground. One side of the elevator 100 is fixedly connected to the support wall 300 by the connection member 160, and one side of the elevator 100 not connected to the support wall 300 is movably connected to the lifting cage 200, so that the lifting cage 200 can be raised or lowered in the extending direction of the support 150.
Referring to fig. 1 and 2, a first pressure sensor 110 is disposed between the bottom of the elevator 100 and the ground, and a second pressure sensor 120 is disposed at a joint of two adjacent brackets 150 of the elevator 100. Referring to fig. 1 and 3, a third pressure sensor 130 is disposed between the support 150 of the elevator 100 and the elevator cage 200, and a fourth pressure sensor 140 is disposed at a connection point between the support 150 of the elevator 100 and the support wall 300.
Alternatively, the number of the first pressure sensors 110 may be four, and referring to fig. 2, the bottom of the elevator 100 contacts with the ground at four positions, and one first pressure sensor 110 may be disposed at each of the four positions.
The number of the second pressure sensors 120 is related to the number of the brackets 150, four positions are in contact between every two adjacent brackets 150, one second pressure sensor 120 can be arranged at each position, and if the number of the brackets 150 is not m, the number of the second pressure sensors 120 is (m-1) × 4.
The number of the third pressure sensors 130 is related to the number of the lifting cages 200, and referring to fig. 1 and 3, each lifting cage 200 has four connecting positions with the support 150 of the elevator 100, and each connecting position can be provided with one third pressure sensor 130, and if the number of the lifting cages 200 is n, the number of the third pressure sensors 130 is n × 4.
The number of the fourth pressure sensors 140 is related to the number of the connection members 160, and referring to fig. 3, there are two connection positions between each connection member 160 and the support wall 300 of the elevator 100, and each connection position may be provided with two fourth pressure sensors 140, and if the number of the connection members 160 is p, the number of the fourth pressure sensors 140 is p 2 x 2.
Fig. 4 is a schematic flowchart of a specific implementation of a method for detecting safety of an elevator 100 according to an embodiment of the present application, where the method may be executed by an electronic device, where the electronic device may be a user terminal or a server, and the method specifically includes the following steps S110 to S130:
step S110, obtaining a pressure measurement value measured by each pressure sensor of the at least one pressure sensor.
The pressure sensors include the first pressure sensor 110, the second pressure sensor 120, the third pressure sensor 130, and the fourth pressure sensor 140, and the four pressure sensors can respectively measure the pressure measurement values corresponding to the pressure sensors and transmit the measured pressure measurement values to the electronic device.
Step S120, analyzing and processing at least one pressure measurement value by using the trained neural network model to obtain a predicted tilt angle of the elevator 100.
The electronics can input the pressure measurements into a trained neural network model that outputs a predicted tilt angle of elevator 100, the neural network model being trained to output a predicted tilt angle of elevator 100 based on the pressure measurements of elevator 100.
Step S130, determining whether the elevator 100 is in a safe operation state according to the angle value of the predicted inclination angle.
A safe operating state refers to an operating state without dangerous conditions such as overload, load loss, or tilting of the elevator 100, wherein both overload and load loss may cause the elevator 100 to tilt in its entirety or the elevator 100 to tilt in its part. After obtaining the angle value of the predicted tilt angle, the electronic device may determine whether the elevator 100 is in a safe operation state according to the angle value of the predicted tilt angle.
The pressure sensor arranged at the connecting point of the elevator 100 can send the pressure measurement value measured by the pressure sensor to the electronic device, and the electronic device can predict the inclination angle of the elevator 100 according to the pressure measurement value by using the trained neural network model, so as to detect whether the elevator 100 can run safely. The electronic device can receive the pressure measurement value sent by the pressure sensor at any time and perform safety detection on the elevator 100, so that the running state of the elevator 100 can be evaluated in time, and the safety of the elevator 100 is improved.
Wherein, step S130 specifically includes: if the angle value of the predicted inclination angle is less than or equal to the preset threshold value, determining that the elevator 100 is in a safe operation state; if the angle value of the predicted tilt angle is greater than the preset threshold value, it is determined that the elevator 100 is not in a safe operation state.
The preset threshold is a critical value defining whether the elevator 100 is safe, and if the inclination angle of the elevator 100 exceeds the preset threshold, it may be determined that the elevator 100 is not in a safe operation state; if the tilt angle of the elevator 100 does not exceed or equal to the preset threshold, it may be determined that the elevator 100 is in a safe operation state.
The preset threshold may be 0.5 degrees, that is, if the inclination angle of the elevator 100 is greater than 0.5 degrees, it may be determined that the operation state of the elevator 100 is unsafe, and there may be problems of overload, loss of load, or inclination of the elevator 100; if the inclination angle of the elevator 100 is less than or equal to 0.5 degrees, the operation state of the elevator 100 may be considered safe. The predetermined threshold may be 0.5 degrees, or may be other values, such as 0.3 degrees, and the specific value of the predetermined threshold should not be construed as limiting the application.
The electronic device can compare the predicted inclination angle with a preset angle threshold value, and then determine whether the elevator 100 is in a safe operation state according to the magnitude relation between the predicted inclination angle and the angle threshold value, so that the determination process is simple, the speed of determining whether the elevator 100 is in the safe operation state is increased, and the timeliness of the operation state evaluation of the elevator 100 is further ensured.
After determining that the elevator 100 is not in a safe operating state, the method further comprises: sending safety warning information indicating that the elevator 100 is not in a safe running state to the elevator 100, so that the elevator 100 plays an alarm prompt.
Optionally, the safety warning information may carry identification information of the elevators 100, so that when the electronic device is connected to multiple elevators 100, the multiple elevators 100 are distinguished by the identification information. The alarm reminder may be a light reminder, a sound reminder, or an audible and visual reminder, and the specific form of the alarm reminder should not be construed as limiting the application.
When the elevator 100 is not in a safe operation state, the electronic device may send safety warning information to the elevator 100, so that an operator near the elevator 100 may eliminate safety risks of the elevator 100 as soon as possible, thereby improving safety of the elevator 100.
Referring to fig. 5, fig. 5 shows a part of steps before step S120, and specifically includes the following steps S101 to S103:
step S101, obtaining historical pressure measurement values measured by each pressure sensor in at least one pressure sensor.
The historical pressure measurements include historical pressure measurements for each of the first pressure sensor 110, the second pressure sensor 120, the third pressure sensor 130, and the fourth pressure sensor 140 described above.
Step S102, obtaining a historical inclination angle of the elevator 100 corresponding to the historical pressure measurement value measured by at least one angle sensor.
The angle sensor may be placed on top of the elevator 100 and the angle sensor may be placed on top of the elevator 100 such that the angle sensor can measure the tilt angle of the elevator 100 when any position of the elevator 100 is tilted. Alternatively, the angle sensor may be a gyroscope.
And S103, training an initial neural network model by taking the plurality of historical pressure measurement values as independent variables and the historical inclination angles as dependent variables to obtain the trained neural network model.
The trained neural network model includes an association between at least one pressure measurement and a tilt angle of the lift 100. The initial neural network model is trained using the historical pressure measurements and the historical tilt angles such that the trained neural network model includes an association between at least one pressure measurement and the tilt angle of the elevator 100, and then the trained neural network model is used to predict the tilt angle of the elevator 100 based on the pressure measurements.
Referring to fig. 6, fig. 6 shows a specific implementation manner of the elevator safety detection apparatus provided in the embodiment of the present application, where the apparatus 600 includes:
a pressure measurement value obtaining module 610 for obtaining a pressure measurement value measured by each of the at least one pressure sensor.
And a predicted inclination obtaining module 620, configured to analyze and process at least one pressure measurement value by using the trained neural network model, so as to obtain a predicted inclination of the elevator.
And an operation state determining module 630, configured to determine whether the elevator is in a safe operation state according to the angle value of the predicted tilt angle.
The operation state determining module 630 is further configured to determine that the elevator is in a safe operation state when the angle value of the predicted inclination angle is less than or equal to a preset threshold; and the controller is also used for determining that the elevator is not in a safe running state when the angle value of the predicted inclination angle is larger than a preset threshold value.
The device further comprises:
and the alarm reminding module is used for sending safety warning information for representing the running state of the elevator which is not in a safe state to the elevator so as to enable the elevator to play an alarm reminding.
And the historical measured value acquisition module is used for acquiring the historical pressure measured value measured by each pressure sensor in the at least one pressure sensor.
And the historical inclination angle acquisition module is used for acquiring the historical inclination angle of the elevator, which is measured by at least one angle sensor and corresponds to the historical pressure measurement value.
And the model training module is used for training an initial neural network model by taking the plurality of historical pressure measurement values as independent variables and the historical inclination angles as dependent variables to obtain a trained neural network model, and the trained neural network model comprises the incidence relation between at least one pressure measurement value and the inclination angle of the elevator.
The elevator safety detection device provided in the embodiment of the present application corresponds to the elevator safety detection method described above, and is not described herein again.
The present application also provides a readable storage medium having stored thereon a computer program which, when executed by a processor, performs the method of the method embodiments.
The present application also provides a computer program product which, when run on a computer, causes the computer to perform the method of the method embodiments.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one logical division, and there may be other divisions when actually implemented, and for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of devices or units through some communication interfaces, and may be in an electrical, mechanical or other form.
In addition, units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
Furthermore, the functional modules in the embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
In this document, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions.
The above description is only an example of the present application and is not intended to limit the scope of the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Claims (8)
1. A method for elevator safety inspection, wherein at least one connection point of the elevator is provided with a pressure sensor, the method comprising:
acquiring a pressure measurement value measured by each pressure sensor in at least one pressure sensor;
obtaining historical pressure measurements taken by each of the at least one pressure sensor;
obtaining a historical inclination angle of the elevator corresponding to the historical pressure measurement value measured by at least one angle sensor;
taking a plurality of historical pressure measurement values as independent variables and historical inclination angles as dependent variables, and training an initial neural network model to obtain a trained neural network model, wherein the trained neural network model comprises an incidence relation between at least two pressure measurement values and the inclination angle of the elevator;
analyzing and processing at least two pressure measurement values by using the trained neural network model to obtain a predicted inclination angle of the elevator;
determining whether the elevator is in a safe operation state or not according to the angle value of the predicted inclination angle;
wherein, be provided with pressure sensor at least one tie point is including bearing the bearing surface of lift and the tie point of lift bottom, the tie point of the leg joint department of lift, the tie point of the junction of support and lift cage and the tie point of the junction of support and knee wall.
2. The method of claim 1, wherein said determining whether the elevator is in a safe operating condition based on the angle value of the predicted tilt angle comprises:
if the angle value of the predicted inclination angle is smaller than or equal to a preset threshold value, determining that the elevator is in a safe running state;
and if the angle value of the predicted inclination angle is larger than a preset threshold value, determining that the elevator is not in a safe running state.
3. The method of claim 2, wherein after determining that the elevator is not in a safe operating state, the method further comprises:
and sending safety warning information representing that the elevator is not in a safe running state to the elevator so as to enable the elevator to play an alarm prompt.
4. An elevator safety detection device, the device comprising:
the pressure measurement value obtaining module is used for obtaining the pressure measurement value measured by each pressure sensor in the at least one pressure sensor;
the historical measured value acquisition module is used for acquiring the historical pressure measured value measured by each pressure sensor in the at least one pressure sensor;
the historical inclination angle acquisition module is used for acquiring the historical inclination angle of the elevator, which is measured by at least one angle sensor and corresponds to the historical pressure measurement value;
the model training module is used for training an initial neural network model by taking the plurality of historical pressure measurement values as independent variables and the historical inclination angles as dependent variables to obtain a trained neural network model, and the trained neural network model comprises an incidence relation between at least two pressure measurement values and the inclination angle of the elevator;
the predicted inclination angle obtaining module is used for analyzing and processing at least two pressure measurement values by using the trained neural network model to obtain a predicted inclination angle of the elevator;
the running state determining module is used for determining whether the elevator is in a safe running state or not according to the angle value of the predicted inclination angle;
wherein, be provided with pressure sensor at least one tie point is including bearing the bearing surface of lift and the tie point of lift bottom, the tie point of the leg joint department of lift, the tie point of the junction of support and lift cage and the tie point of the junction of support and knee wall.
5. The apparatus of claim 4, wherein the operating condition determining module is further configured to determine that the elevator is in a safe operating condition when the angle value of the predicted tilt angle is less than or equal to a preset threshold;
and the controller is used for determining that the elevator is not in a safe running state when the angle value of the predicted inclination angle is larger than a preset threshold value.
6. The apparatus of claim 5, further comprising:
and the alarm reminding module is used for sending safety warning information for representing the running state of the elevator which is not in a safe state to the elevator so as to enable the elevator to play an alarm reminding.
7. An electronic device, comprising: a processor, a storage medium and a bus, the storage medium storing machine-readable instructions executable by the processor, the processor and the storage medium communicating over the bus when the electronic device is operating, the processor executing the machine-readable instructions to perform the method of any one of claims 1-3 when executed.
8. A readable storage medium, having stored thereon a computer program which, when executed by a processor, performs the method according to any one of claims 1-3.
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| Application Number | Priority Date | Filing Date | Title |
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| CN201910897440.4A CN110626904B (en) | 2019-09-20 | 2019-09-20 | Elevator safety detection method and device, electronic equipment and readable storage medium |
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| Application Number | Priority Date | Filing Date | Title |
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| CN201910897440.4A CN110626904B (en) | 2019-09-20 | 2019-09-20 | Elevator safety detection method and device, electronic equipment and readable storage medium |
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| CN110626904B true CN110626904B (en) | 2021-06-04 |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN202414916U (en) * | 2011-11-01 | 2012-09-05 | 大连科信起重电器有限公司 | Intelligent early warning system for construction hoister |
| CN103195109A (en) * | 2013-03-28 | 2013-07-10 | 中国地质大学（武汉） | Foundation pile inclination measuring device |
| CN206311100U (en) * | 2016-12-30 | 2017-07-07 | 山东交通学院 | A kind of verticality measuring instrument |
| CN108981650A (en) * | 2018-07-27 | 2018-12-11 | 中国矿业大学 | A kind of device and method for Hydraulic Support Posture detection |
| CN209019856U (en) * | 2018-09-30 | 2019-06-25 | 上海掌门科技有限公司 | A kind of futon equipment |
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2019
- 2019-09-20 CN CN201910897440.4A patent/CN110626904B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN202414916U (en) * | 2011-11-01 | 2012-09-05 | 大连科信起重电器有限公司 | Intelligent early warning system for construction hoister |
| CN103195109A (en) * | 2013-03-28 | 2013-07-10 | 中国地质大学（武汉） | Foundation pile inclination measuring device |
| CN206311100U (en) * | 2016-12-30 | 2017-07-07 | 山东交通学院 | A kind of verticality measuring instrument |
| CN108981650A (en) * | 2018-07-27 | 2018-12-11 | 中国矿业大学 | A kind of device and method for Hydraulic Support Posture detection |
| CN209019856U (en) * | 2018-09-30 | 2019-06-25 | 上海掌门科技有限公司 | A kind of futon equipment |
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