CN118125257A - Construction elevator operation risk monitoring and early warning system based on data analysis - Google Patents
Construction elevator operation risk monitoring and early warning system based on data analysis Download PDFInfo
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
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- B—PERFORMING OPERATIONS; TRANSPORTING
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- 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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- 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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Abstract
The invention relates to the field of risk early warning, which is used for solving the problem that the operation safety of a construction elevator cannot be guaranteed due to the lack of comprehensive analysis on environmental factors and maintenance frequency of the construction elevator, in particular to a construction elevator operation risk monitoring early warning system based on data analysis, and comprises an operation environment analysis unit, an operation load analysis unit, an equipment operation early warning unit, a maintenance management unit and a peripheral risk analysis unit; in the invention, when the load condition of the construction hoist is analyzed, the construction hoist operation jitter condition in the operation process is analyzed, the discovery capability of hidden faults is improved, and the operation environment, the load condition, the maintenance condition and the peripheral risks of the construction hoist are collected in a comprehensive way, so that the comprehensive operation risk early warning for the construction hoist is realized, the accuracy of operation risk monitoring early warning is improved, and the safety of the construction hoist in use is improved.
Description
Technical Field
The invention relates to the field of risk early warning, in particular to a construction lifter operation risk monitoring early warning system based on data analysis.
Background
The construction hoist is also called a construction elevator for a building, and can also be called an outdoor elevator, and the construction site lifts a cage. The construction hoist is mainly used in various buildings of urban high-rise and super high-rise, because the building height is very difficult to finish the operation by using the derrick and the portal frame. The construction machine is a man-carrying and cargo-carrying construction machine which is frequently used in a building, is mainly used for the construction of buildings such as internal and external decoration of high-rise buildings, bridges, chimneys and the like, has complex use conditions, needs to be provided with an overload detection device, and can prevent the normal operation of a suspension cage when the load in the suspension cage exceeds the rated load capacity. However, the overload detection device is artificially short-circuited, and cannot be prevented from running above overload. When overload running occurs, if the motor is insufficient in output, the risk of sliding the vehicle exists;
At present, the use safety monitoring of the construction hoist in the prior art only depends on an overload limiting function, however, in the actual use process, environmental factors and maintenance frequency are also important influencing factors for ensuring the safe and effective operation of mechanical equipment, so that the operation safety of the construction hoist is ensured by performing more comprehensive supervision and early warning measures on the construction hoist;
the application provides a solution to the technical problem.
Disclosure of Invention
In the invention, when the load condition of the construction hoist is analyzed, the construction hoist operation jitter condition in the operation process is analyzed, the discovery capability of hidden faults is improved, the operation environment, the load condition, the maintenance condition and the peripheral risks of the construction hoist are collected in a comprehensive way, so that the comprehensive operation risk early warning of the construction hoist is realized, the accuracy of operation risk monitoring early warning is improved, the safety of the construction hoist in use is improved, the problem that the operation safety of the construction hoist cannot be guaranteed due to the lack of the comprehensive analysis of environmental factors and maintenance frequency of the construction hoist is solved, and the operation risk monitoring early warning system of the construction hoist based on data analysis is provided.
The aim of the invention can be achieved by the following technical scheme:
The construction elevator operation risk monitoring and early warning system based on data analysis comprises an operation environment analysis unit, wherein the operation environment analysis unit can carry out accumulated monitoring on the operation environment of the elevator and generate a mechanical normal signal and a mechanical abnormal signal according to a monitoring result;
The operation load analysis unit can count the implementation operation load of the elevator and classify the statistical result into a dynamic load and a static load, and the operation load analysis unit analyzes the dynamic load and the static load to obtain a load proportion, a dynamic load variation and a dynamic load variation rate;
The maintenance management unit can collect and analyze the maintenance work of the lifter and judge whether the lifter needs to carry out the maintenance work according to the collection result;
The peripheral risk analysis unit can count peripheral information and acquire peripheral risk values of the elevator during operation through cloud analysis;
The equipment operation early warning unit can carry out comprehensive operation on the results analyzed by the operation environment analysis unit, the operation load analysis unit, the maintenance management unit and the peripheral risk analysis unit, and the operation risk of the elevator is judged according to the comprehensive operation result.
As a preferred embodiment of the present invention, the process of detecting the operating environment by the operating environment analysis unit is:
The operation environment analysis unit is used for detecting the environment temperature, the environment humidity and the dust concentration of the elevator, analyzing the operation environment of the elevator through a finite element algorithm, acquiring the operation behaviors of a plurality of mechanical structures in the elevator, combining the operation behaviors of the plurality of structures, carrying out predictive analysis on the failure rate of the mechanical equipment through the combined model, comparing the predicted failure rate of the mechanical equipment with a failure rate safety standard required by construction, generating a mechanical normal signal if the predicted failure rate is smaller than the failure rate safety standard, generating a mechanical abnormal signal if the predicted failure rate is greater than or equal to the failure rate safety standard, simultaneously calculating the ratio of the predicted failure rate to the failure rate safety standard, recording the ratio as an abnormal coefficient, and sending the abnormal coefficient, the mechanical normal signal and the mechanical abnormal signal to the equipment operation early warning unit and the maintenance management unit.
As a preferred embodiment of the present invention, the process of classifying the statistical result into the dynamic load and the static load by the operation load analysis unit is as follows: the load born by the lifter when the transported goods do not start to rise is recorded as static load, and the load born by the lifter when the transported goods are rising and falling is recorded as dynamic load;
The process of the operation load analysis unit for analyzing the dead load is as follows:
The operation load analysis unit compares the static load with a preset elevator load, if the static load is larger than or equal to the preset elevator load, an overweight signal is generated, if the static load is smaller than the preset elevator load, a load qualified signal is generated, the ratio of the static load to the preset elevator load is calculated, the ratio is recorded as a load ratio, and the load ratio is sent to the equipment operation early warning unit;
The analysis process of the running load analysis unit on the running load is as follows:
The operation load analysis unit records the process from the starting of the elevator to the stopping of the elevator as a transportation process, the operation load analysis unit calculates the movable load of the elevator in the transportation process, the operation load analysis unit draws an elevator load variation curve by taking time as a horizontal axis and the movable load as a vertical axis, the operation load analysis unit selects the highest point on the elevator load variation curve, records the highest point as a movable load peak value, records a line segment which is not horizontal on the elevator load variation curve as a movable load variation section, the operation load analysis unit calculates the slope of each section of the movable load variation section, averages the obtained absolute values of the slopes of all the movable load variation sections to obtain the movable load variation rate, sums the absolute values of the slopes of all the movable load variation sections to obtain the movable load variation quantity, and the operation load analysis unit sends the movable load variation rate and the movable load variation quantity to the maintenance management unit.
As a preferred embodiment of the present invention, the maintenance management unit determines maintenance work of the elevator as follows:
After the maintenance management unit obtains the dynamic load change rate, comparing the dynamic load change rate with a preset change rate threshold, generating a change normal signal if the dynamic load change rate is smaller than the preset change rate threshold, and generating a change abnormal signal if the dynamic load change rate is larger than or equal to the preset change rate threshold;
After the maintenance management unit acquires the mechanical normal signal, the mechanical abnormal signal and the abnormal coefficient are not reacted, after the maintenance management unit acquires the dynamic load variation, the maintenance management unit calculates the difference value between the dynamic load variation and a preset dynamic load variation threshold, the maintenance management unit acquires a maintenance characteristic value through formula analysis, the maintenance management unit compares the maintenance characteristic value with a preset weight coefficient, if the maintenance characteristic value is greater than or equal to the preset weight coefficient, a maintenance requirement signal is generated, if the maintenance characteristic value is less than the preset weight coefficient, a maintenance normal signal is generated, and the maintenance management unit sends the maintenance requirement signal and the maintenance normal signal to the equipment operation early warning unit.
As a preferred embodiment of the present invention, the method for obtaining the peripheral risk value when the elevator is running by the peripheral risk analysis unit includes:
the peripheral risk analysis unit obtains the peripheral environment through a manual input mode, the peripheral environment is the personnel density degree and the personnel passing probability, the peripheral risk analysis unit calculates the personnel density degree and the personnel passing probability through a Bayesian network model simulation, simulates the personnel probability distribution of the area nearby the elevator under the condition of the given personnel density degree, obtains the risk value according to the personnel number in the personnel probability distribution, and sends the risk value to the equipment operation early warning unit.
As a preferred embodiment of the invention, after the equipment operation early warning unit obtains the mechanical abnormality signal, the abnormality coefficient, the load proportion, the maintenance requirement signal and the risk value, the equipment operation early warning unit carries out assignment on the maintenance requirement signal, amplifies the assignment of the maintenance requirement signal through the abnormality coefficient, the load proportion and the risk value, generates an equipment alarm signal if the amplified assignment is larger than a preset value, generates an equipment high-risk early warning signal if the amplified assignment is smaller than the preset value, and generates an equipment normal signal if the mechanical abnormality signal and the maintenance requirement signal are not present.
Compared with the prior art, the invention has the beneficial effects that:
In the invention, when the operation of the construction hoist is monitored, the operation environment, the load condition, the maintenance condition and the peripheral risk of the construction hoist are collected in all aspects, so that the comprehensive operation risk early warning for the construction hoist is realized, the accuracy and the comprehensiveness of early warning are ensured, and the safety of the construction hoist in use is improved.
According to the invention, when the load condition of the construction hoist is analyzed, not only is the overload condition before starting monitored, but also the shaking condition of the construction hoist in the running process is analyzed, so that the hidden faults of the construction hoist in the running process are more accurately found, and the accuracy of monitoring and early warning of the running risk is improved.
According to the invention, when the construction elevator is maintained and managed, the load condition and the running environment of the elevator are comprehensively analyzed to replace the conventional regular maintenance, so that the maintenance frequency of the construction elevator in a severe environment can be increased, the actual use condition of the elevator is more loaded in the maintenance frequency of the elevator, and the maintenance timeliness of the elevator is ensured.
Drawings
The present invention is further described below with reference to the accompanying drawings for the convenience of understanding by those skilled in the art.
FIG. 1 is a system block diagram of the present invention;
fig. 2 is a flow chart of the system of the present invention.
Detailed Description
The technical solutions of the present invention will be clearly and completely described in connection with the embodiments, and it is obvious that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1
Referring to fig. 1-2, the construction elevator operation risk monitoring and early warning system based on data analysis includes an operation environment analysis unit, an operation load analysis unit, an equipment operation early warning unit, a maintenance management unit and a peripheral risk analysis unit, wherein the operation environment analysis unit detects the operation environment of the elevator, the operation environment of the elevator comprises the environment temperature, the environment humidity and the dust concentration of the operation environment where the elevator is located, the operation environment analysis unit uploads the operation environment to a cloud end through a network, the operation environment of the elevator is analyzed through a finite element algorithm at the cloud end, operation behaviors which possibly occur in a plurality of mechanical structures in the elevator are obtained, the operation behaviors of the plurality of structures are combined in a model, the failure rate of the mechanical equipment is predicted and analyzed according to the combined model, if the predicted failure rate is smaller than the failure rate safety standard, a mechanical normal signal is generated, if the predicted failure rate is greater than or equal to the failure rate safety standard, a mechanical abnormal signal is generated, meanwhile, the ratio of the predicted failure rate and the failure rate safety standard is calculated, the mechanical abnormal signal is recorded as the abnormal operation coefficient and the abnormal operation safety standard is recorded by the operation environment analysis unit, and the abnormal operation management unit is used for the abnormal operation of the mechanical equipment;
the operation load analysis unit can acquire real-time operation load of the elevator and respectively record the real-time operation load as static load or dynamic load according to the current lifting position of the elevator, wherein the static load is load born by the elevator when the transported goods do not start to rise, the dynamic load is load born by the elevator when the transported goods are lifting, the operation load analysis unit compares the static load with preset elevator load, if the static load is greater than or equal to the preset elevator load, an overweight signal is generated, the elevator sends out an audible and visual alarm reminding, meanwhile, the goods are not lifted, if the static load is smaller than the preset elevator load, a load qualification signal is generated, the proportion of the static load to the preset lifting load is calculated, the load proportion is recorded, and the load proportion is sent to the equipment operation early warning unit;
The method comprises the steps that in the running process of an elevator, an operation load analysis unit records a transportation flow from the starting of the elevator to the stopping of the elevator, the operation load analysis unit counts the movable load of the elevator in the transportation flow, takes time as a horizontal axis, draws an elevator load variation curve with the movable load as a vertical axis, selects the highest point on the elevator load variation curve, records the highest point as a movable load peak value, records a line segment which is not horizontal on the elevator load variation curve as a movable load variation section, calculates the slope of each section of the movable load variation section, averages the obtained absolute values of the slopes of all movable load variation sections, obtains the movable load variation rate, sums the absolute values of the slopes of all movable load variation sections, obtains the movable load variation quantity, characterizes the occurrence times of jitter phenomena in the running process of the elevator by the movable load variation quantity, characterizes the jitter intensity in the running process of the elevator by the movable load variation rate, and is used for reflecting the jitter frequency and the jitter intensity in the running process of the elevator, and the operation load analysis unit sends the movable load variation rate and the movable load variation quantity to a maintenance unit;
The operation load analysis unit divides each non-horizontal straight line part into a dynamic load change section by straight lines when dividing the dynamic load change section, meanwhile, each straight line has a minimum length, if the length of the straight line on the elevator load change curve is smaller than the minimum length, a line segment with the length equal to the minimum length of the straight line is selected on the elevator load change curve, the start point and the end point of the line segment are connected with the straight line, and the slope is calculated as the slope of the curve of the segment.
Example two
Referring to fig. 1-2, after the maintenance management unit obtains the dynamic load change rate, comparing the dynamic load change rate with a preset change rate threshold, if the dynamic load change rate is smaller than the preset change rate threshold, generating a change normal signal, and if the dynamic load change rate is greater than or equal to the preset change rate threshold, generating a change abnormal signal;
After the maintenance management unit acquires the normal signal of the machine, the machine does not react, after the maintenance management unit acquires the abnormal signal and the abnormal coefficient of the machine, the abnormal coefficient is recorded as A, after the maintenance management unit acquires the dynamic load variation, the difference value between the dynamic load variation and a preset dynamic load variation threshold value is recorded as B, if the dynamic load variation is larger than the dynamic load variation threshold value, B is a positive value, if the dynamic load variation is smaller than or equal to the dynamic load variation threshold value, B is=0, the maintenance management unit acquires a maintenance characteristic value X through formula analysis, When a change normal signal is generated, the value range of q is 1.1-1.4, when a change abnormal signal is generated, the value range of q is 1.5-2.0, j is a preset threshold constant, j=1, the maintenance management unit compares the maintenance characteristic value X with the preset weight coefficient, if the maintenance characteristic value X is greater than or equal to the preset weight coefficient, a maintenance requirement signal is generated, if the maintenance characteristic value is smaller than the preset weight coefficient, a maintenance normal signal is generated, the maintenance management unit sends the maintenance requirement signal to a manager after generating the maintenance requirement signal, and reminds the manager to carry out maintenance and overhaul on the lifter, and meanwhile, the maintenance management unit also sends the maintenance requirement signal and the maintenance normal signal to the equipment operation early warning unit.
The peripheral risk analysis unit calculates the peripheral environment in a manual input mode of a manager, the peripheral environment is the personnel density and the personnel passing probability, the peripheral risk analysis unit calculates the personnel density and the personnel passing probability through a Bayesian network model simulation, the personnel probability distribution passing through the area near the elevator under the condition of the given personnel density is simulated, the risk value is obtained according to the personnel number in the personnel probability distribution, and the risk value is sent to the equipment operation early warning unit.
Example III
Referring to fig. 1-2, after the device operation early warning unit obtains the mechanical anomaly signal, the anomaly coefficient, the load proportion, the maintenance requirement signal and the risk value, the maintenance requirement signal is assigned K, and the maintenance requirement signal is amplified through the anomaly coefficient, the load proportion and the risk value, if the amplified assigned K is greater than a preset value, a device alarm signal is generated, if the amplified assigned K is less than the preset value, a device high-risk early warning signal is generated, and if the mechanical anomaly signal and the maintenance requirement signal do not exist, a device normal signal is generated.
The preferred embodiments of the invention disclosed above are intended only to assist in the explanation of the invention. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise form disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best understand and utilize the invention. The invention is limited only by the claims and the full scope and equivalents thereof.
Claims (6)
1. The construction elevator operation risk monitoring and early warning system based on data analysis is characterized by comprising an operation environment analysis unit, wherein the operation environment analysis unit can carry out accumulated monitoring on the operation environment of the elevator and generate a mechanical normal signal and a mechanical abnormal signal according to a monitoring result;
The operation load analysis unit can count the implementation operation load of the elevator and classify the statistical result into a dynamic load and a static load, and the operation load analysis unit analyzes the dynamic load and the static load to obtain a load proportion, a dynamic load variation and a dynamic load variation rate;
The maintenance management unit can collect and analyze the maintenance work of the lifter and judge whether the lifter needs to carry out the maintenance work according to the collection result;
The peripheral risk analysis unit can count peripheral information and acquire peripheral risk values of the elevator during operation through cloud analysis;
The equipment operation early warning unit can carry out comprehensive operation on the results analyzed by the operation environment analysis unit, the operation load analysis unit, the maintenance management unit and the peripheral risk analysis unit, and the operation risk of the elevator is judged according to the comprehensive operation result.
2. The construction elevator operation risk monitoring and early warning system based on data analysis according to claim 1, wherein the operation environment analysis unit detects the operation environment by:
The operation environment analysis unit is used for detecting the environment temperature, the environment humidity and the dust concentration of the elevator, analyzing the operation environment of the elevator through a finite element algorithm, acquiring the operation behaviors of a plurality of mechanical structures in the elevator, combining the operation behaviors of the plurality of structures, carrying out predictive analysis on the failure rate of the mechanical equipment through the combined model, comparing the predicted failure rate of the mechanical equipment with a failure rate safety standard required by construction, generating a mechanical normal signal if the predicted failure rate is smaller than the failure rate safety standard, generating a mechanical abnormal signal if the predicted failure rate is greater than or equal to the failure rate safety standard, simultaneously calculating the ratio of the predicted failure rate to the failure rate safety standard, recording the ratio as an abnormal coefficient, and sending the abnormal coefficient, the mechanical normal signal and the mechanical abnormal signal to the equipment operation early warning unit and the maintenance management unit.
3. The construction elevator operation risk monitoring and early warning system based on data analysis according to claim 1, wherein the operation load analysis unit classifies the statistical result into a dynamic load and a static load: the load born by the lifter when the transported goods do not start to rise is recorded as static load, and the load born by the lifter when the transported goods are rising and falling is recorded as dynamic load;
The process of the operation load analysis unit for analyzing the dead load is as follows:
The operation load analysis unit compares the static load with a preset elevator load, if the static load is larger than or equal to the preset elevator load, an overweight signal is generated, if the static load is smaller than the preset elevator load, a load qualified signal is generated, the ratio of the static load to the preset elevator load is calculated, the ratio is recorded as a load ratio, and the load ratio is sent to the equipment operation early warning unit;
The analysis process of the running load analysis unit on the running load is as follows:
The operation load analysis unit records the process from the starting of the elevator to the stopping of the elevator as a transportation process, the operation load analysis unit calculates the movable load of the elevator in the transportation process, the operation load analysis unit draws an elevator load variation curve by taking time as a horizontal axis and the movable load as a vertical axis, the operation load analysis unit selects the highest point on the elevator load variation curve, records the highest point as a movable load peak value, records a line segment which is not horizontal on the elevator load variation curve as a movable load variation section, the operation load analysis unit calculates the slope of each section of the movable load variation section, averages the obtained absolute values of the slopes of all the movable load variation sections to obtain the movable load variation rate, sums the absolute values of the slopes of all the movable load variation sections to obtain the movable load variation quantity, and the operation load analysis unit sends the movable load variation rate and the movable load variation quantity to the maintenance management unit.
4. The system for monitoring and early warning of operation risk of construction hoist based on data analysis according to claim 1, wherein the maintenance management unit judges maintenance work of the hoist as follows:
After the maintenance management unit obtains the dynamic load change rate, comparing the dynamic load change rate with a preset change rate threshold, generating a change normal signal if the dynamic load change rate is smaller than the preset change rate threshold, and generating a change abnormal signal if the dynamic load change rate is larger than or equal to the preset change rate threshold;
After the maintenance management unit acquires the mechanical normal signal, the mechanical abnormal signal and the abnormal coefficient are not reacted, after the maintenance management unit acquires the dynamic load variation, the maintenance management unit calculates the difference value between the dynamic load variation and a preset dynamic load variation threshold, the maintenance management unit acquires a maintenance characteristic value through formula analysis, the maintenance management unit compares the maintenance characteristic value with a preset weight coefficient, if the maintenance characteristic value is greater than or equal to the preset weight coefficient, a maintenance requirement signal is generated, if the maintenance characteristic value is less than the preset weight coefficient, a maintenance normal signal is generated, and the maintenance management unit sends the maintenance requirement signal and the maintenance normal signal to the equipment operation early warning unit.
5. The construction elevator operation risk monitoring and early warning system based on data analysis according to claim 1, wherein the method for obtaining the peripheral risk value when the elevator operates by the peripheral risk analysis unit is as follows:
the peripheral risk analysis unit obtains the peripheral environment through a manual input mode, the peripheral environment is the personnel density degree and the personnel passing probability, the peripheral risk analysis unit calculates the personnel density degree and the personnel passing probability through a Bayesian network model simulation, simulates the personnel probability distribution of the area nearby the elevator under the condition of the given personnel density degree, obtains the risk value according to the personnel number in the personnel probability distribution, and sends the risk value to the equipment operation early warning unit.
6. The construction elevator operation risk monitoring and early warning system based on data analysis according to claim 1, wherein after the equipment operation early warning unit obtains a mechanical abnormality signal, an abnormality coefficient, a load proportion, a maintenance requirement signal and a risk value, the maintenance requirement signal is assigned, the assignment of the maintenance requirement signal is amplified through the abnormality coefficient, the load proportion and the risk value, if the amplified assignment is greater than a preset value, an equipment alarm signal is generated, if the amplified assignment is less than the preset value, an equipment high-risk early warning signal is generated, and if no mechanical abnormality signal and no maintenance requirement signal exist, an equipment normal signal is generated.
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|---|---|---|---|---|
| WO2019081801A1 (en) * | 2017-10-27 | 2019-05-02 | Kone Corporation | Hoisting arrangement in an elevator shaft |
| CN111108058A (en) * | 2017-08-03 | 2020-05-05 | 科尼起重机全球公司 | Method for lifting and/or lowering a load handling mechanism of a lift, in particular of a crane, and lift therefor |
| CN111483900A (en) * | 2020-04-21 | 2020-08-04 | 蚌埠高灵传感系统工程有限公司 | Construction elevator overload protection system based on big data |
| CN116715112A (en) * | 2023-06-30 | 2023-09-08 | 桂林电子科技大学 | Balanced operation and safety protection system for elevator |
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2024
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Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111108058A (en) * | 2017-08-03 | 2020-05-05 | 科尼起重机全球公司 | Method for lifting and/or lowering a load handling mechanism of a lift, in particular of a crane, and lift therefor |
| WO2019081801A1 (en) * | 2017-10-27 | 2019-05-02 | Kone Corporation | Hoisting arrangement in an elevator shaft |
| CN111483900A (en) * | 2020-04-21 | 2020-08-04 | 蚌埠高灵传感系统工程有限公司 | Construction elevator overload protection system based on big data |
| CN116715112A (en) * | 2023-06-30 | 2023-09-08 | 桂林电子科技大学 | Balanced operation and safety protection system for elevator |
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