CN116700198B - Intelligent identification-based operation safety control system for overhead working truck - Google Patents
Intelligent identification-based operation safety control system for overhead working truck Download PDFInfo
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- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
- G05B19/4183—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM] characterised by data acquisition, e.g. workpiece identification
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- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
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Abstract
The invention discloses an overhead working truck operation safety control system based on intelligent identification, and particularly relates to the field of safety control. According to the invention, through collecting the load weight, the inclination angle and the rotation angle of the operation vehicle and environmental parameters such as wind speed, weather, temperature and humidity, the parameters are processed, pose characteristic values and environmental influence values are calculated, and the pose characteristic values and the environmental influence values are imported into an intelligent algorithm identification model to calculate a comprehensive safety coefficient; and comparing the calculated comprehensive safety coefficient with a preset comprehensive safety coefficient, and outputting an instruction. And finally, feeding back an output instruction of the operation early warning module to equipment operators so as to ensure the safety of the operators of the operation vehicle.
Description
Technical Field
The invention relates to the technical field of safety control, in particular to an overhead working truck operation safety control system based on intelligent identification.
Background
With the development of technology, compared with the traditional scaffold type aerial work, the aerial work vehicle gradually becomes a mainstream aerial work mode at present due to extremely high safety, environmental adaptability and work efficiency.
Traditional scaffold type high-altitude operations require the construction of scaffold structures to support workers and equipment for operation. This approach presents some potential risks, such as unstable structure, long construction time, inconvenient operation, etc., which greatly limit the efficiency and safety of the overhead work.
In contrast, the overhead working truck provides a safer and more stable working platform for workers, and does not need to rely on a complex building structure. An overhead working truck is a machine that is dedicated to performing various operations in an overhead environment. The telescopic boom or the working platform is generally arranged, so that workers and equipment can be lifted to a higher height, and thus building, maintenance, installation, cleaning and other high-altitude work tasks can be conveniently carried out.
However, when the intelligent high-altitude operation vehicle is actually used, the operation of the traditional high-altitude operation vehicle mainly depends on the observation of naked eyes of a driver to command the high-altitude operation vehicle, certain limitations and risks exist, and the intelligent obstacle avoidance and the accurate judgment of faults encountered during operation cannot be performed, so that an intelligent-identification-based high-altitude operation vehicle operation safety control system is generated.
Disclosure of Invention
In order to overcome the above-mentioned drawbacks of the prior art, an embodiment of the present invention provides an operation safety control system for an overhead working truck based on intelligent recognition, so as to solve the problems set forth in the above-mentioned background art.
In order to achieve the above purpose, the present invention provides the following technical solutions:
the operation vehicle parameter acquisition module: the system comprises a working vehicle parameter processing module, a working vehicle load acquisition module, a working vehicle parameter processing module and a working vehicle load acquisition module, wherein the working vehicle load acquisition module is used for acquiring the working load of the working vehicle, the working vehicle parameter processing module is used for acquiring the working vehicle load of the working vehicle;
the operation vehicle parameter processing module: the system is used for receiving the parameters acquired from the operation vehicle parameter collecting module, effectively extracting the parameters, and calculating to obtain pose characteristic values;
the environmental parameter acquisition module: the system is used for collecting the wind speed, weather, temperature and humidity of the overhead working truck during operation and transmitting the environmental parameters to the environmental parameter processing module;
the environment parameter processing module is used for: the environment parameter acquisition module is used for acquiring environment parameters from the environment parameter acquisition module, processing the parameters and calculating to obtain environment influence values;
intelligent algorithm identification module: is used for analyzing the calculated pose characteristic values and environment influence values, importing the data into an intelligent algorithm recognition model, calculating a comprehensive safety coefficient, identifying obstacles and safety areas around the operation vehicle during operation, and finally transmitting the comprehensive safety coefficient to an operation early-warning module;
the operation early warning module of the operation vehicle: the safety control system is used for comparing the comprehensive safety coefficient calculated by analysis with a preset comprehensive safety coefficient threshold value and judging whether the current operation vehicle is safe or not according to different output instructions;
and a safety control module: and the device is used for feeding back to equipment operators according to different instructions output in the operation early warning module.
Preferably, the method for collecting load weight in the parameter collecting module of the working vehicle comprises the following steps:
by mounting the bend sensor within the work vehicle structure and then connecting the bend sensor to the data acquisition
The equipment is used for recording the load change of the operation vehicle in real time and storing data;
the method for collecting the gradient in the parameter collecting module of the operation vehicle comprises the following steps:
the gyroscope is arranged at the top of the structure of the working vehicle, then connected to the data acquisition equipment, and used for reading the inclination angle of the working vehicle through data output by the gyroscope, and recording and storing the change of the inclination angle of the working vehicle in real time.
The method for collecting the rotation angle in the operation vehicle parameter collecting module comprises the following steps:
the rotation angle is determined by measuring the change of the geomagnetic field by installing the magnetometer on the rotation part of the operation vehicle, and then the magnetometer is connected to the data acquisition equipment, and the change of the rotation angle of the operation vehicle is recorded and stored in real time.
Preferably, in the operation parameter processing module, the collected data is preprocessed, effective data is extracted, abnormal values are removed, the abnormal values are determined that the difference between the numerical value of each sensor and the numerical value collected in the history sensor is greater than n, the collected numerical value is greater than a preset abnormal threshold value, the data with the abnormal values removed is filled with missing values, the missing values take the median of the data, and larger deviation is prevented.
The method for calculating the pose characteristic value in the operation parameter processing module specifically comprises the following steps:
wherein Z is expressed as a pose characteristic value, G is expressed as a load weight, θ is expressed as an inclination angle, μ is expressed as a rotation angle, and a1 and a2 are expressed as weight factors.
Preferably, in the environmental parameter acquisition module, the method for acquiring the wind speed is as follows;
the wind speed is acquired by an optical interferometry method, wherein the measuring steps are as follows:
a1: a laser light source, which may be a laser or a laser diode, is prepared. The light source is directed to the area to be measured, so that the light source can irradiate into the air flow; preparing a Fresnel tile interferometer;
a2: the laser beam is split into two beams by an optical element. One beam irradiates on a fixed reference surface or a reflector, and the other beam irradiates in the airflow to be measured;
a3: the reflected beams from the reference plane and the air flow are re-intersected and the change in interference fringes is observed.
A4: the magnitude of the wind speed can be deduced by utilizing the movement or deformation condition of the interference fringes. The relevant data of wind speed can be obtained by measuring and analyzing parameters such as the shape, displacement, intensity and the like of the interference fringes.
In the environment parameter acquisition module, the temperature acquisition method comprises the following steps:
the temperature of the object is measured using a thermal imager imaging method, the thermal radiation of the object is measured by an infrared sensor, and then converted into a visible image, and the difference in temperature distribution and heat flow is detected from the image.
In the environment parameter module, the humidity acquisition method comprises the following steps:
the sensor acquires humidity data from the high altitude through a remote sensing technology. The system is communicated with high-altitude equipment such as unmanned aerial vehicle and the like, and the humidity condition in the atmosphere is monitored in real time through a remote sensing instrument.
Preferably, in the environmental parameter processing module, the collected data are sequenced from large to small, and the median value of each parameter data is taken for calculation, so that the error is reduced, wherein the calculating method of the environmental impact value specifically comprises the following steps:
wherein Y is an environmental impact value, F is a measured wind speed value, T is a measured temperature, S is a measured humidity value, eta is a weather index, 3 is taken when weather is sunny, 2 is taken when weather is cloudy, and 1 is taken when other weather is cloudy.
Preferably, in the intelligent algorithm identification module, the algorithm for synthesizing the safety coefficient is specifically:
wherein Q is a comprehensive safety coefficient, Z is a pose characteristic value, Y is an environmental influence value, lambda 1 and lambda 2 are weight factors, and omega is other influence factors.
Preferably, in the operation early warning module of the operation vehicle, the calculated comprehensive safety coefficient from the intelligent algorithm identification module is received, and the calculated comprehensive safety coefficient is compared with a preset comprehensive safety coefficient threshold; outputting a work safety instruction if the calculated comprehensive safety coefficient is greater than a preset comprehensive safety coefficient threshold value; and if the calculated comprehensive safety coefficient is smaller than a preset comprehensive safety coefficient threshold value, outputting an operation danger instruction to perform early warning.
Preferably, the safety control module receives different instructions output from the operation early warning module of the operation vehicle; if the input instruction is a work safety instruction, the work vehicle can continue to work; if the input instruction is an operation dangerous instruction, the operation vehicle immediately stops operation, and sends the instruction to equipment operators for timely correction.
The invention has the technical effects and advantages that:
the comprehensive safety coefficient is calculated according to the data by acquiring the load weight, the inclination angle, the rotation angle and the environmental parameters of the operation vehicle, judging whether the current working environment is safe or not according to the acquired comprehensive safety coefficient, discovering potential safety hazards in advance, improving the safety during operation, and reducing misoperation and judgment caused by personnel during operation.
Drawings
Fig. 1 is a schematic diagram of the overall structure of the present invention.
FIG. 2 is a schematic flow chart of the method of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but 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.
Referring to the figure, the invention provides an overhead working truck operation safety control system based on intelligent recognition, which comprises a working truck parameter acquisition module, a working truck parameter processing module, an environment parameter acquisition module, an environment parameter processing module, an intelligent algorithm recognition module, a working truck operation early warning module and a safety control module.
The operation parameter acquisition module is connected with the operation parameter processing module, the operation vehicle parameter processing module is connected with the environment parameter acquisition module, the environment parameter acquisition module is connected with the environment parameter processing module, the environment parameter processing module is connected with the intelligent algorithm identification module, the intelligent algorithm identification module is connected with the operation vehicle operation early warning module, and the operation vehicle operation early warning module is connected with the safety control module.
The working vehicle parameter acquisition module is used for acquiring the working vehicle load weight, the inclination angle and the rotation angle when the working vehicle works at high altitude, and transmitting the working vehicle parameters to the working vehicle parameter processing module; the method for collecting the load weight in the parameter collection module of the operation vehicle comprises the following steps:
by mounting the bend sensor within the work vehicle structure and then connecting the bend sensor to the data acquisition
The equipment is used for recording the load change of the operation vehicle in real time and storing data;
the method for collecting the gradient in the parameter collecting module of the operation vehicle comprises the following steps:
the gyroscope is arranged at the top of the structure of the working vehicle, then connected to the data acquisition equipment, and used for reading the inclination angle of the working vehicle through data output by the gyroscope, and recording and storing the change of the inclination angle of the working vehicle in real time.
The method for collecting the rotation angle in the operation vehicle parameter collecting module comprises the following steps:
the rotation angle is determined by measuring the change of the geomagnetic field by installing the magnetometer on the rotation part of the operation vehicle, and then the magnetometer is connected to the data acquisition equipment, and the change of the rotation angle of the operation vehicle is recorded and stored in real time.
The operation vehicle parameter processing module is used for receiving the parameters acquired from the operation vehicle parameter collecting module, effectively extracting the parameters, and calculating to obtain pose characteristic values; in the operation parameter processing module, the collected data are preprocessed, effective data are extracted, abnormal values are removed, the abnormal values are judged that the difference between the numerical value of each sensor and the numerical value collected in the history sensor is larger than n, the collected numerical value is larger than a preset abnormal threshold value, the data with the abnormal values removed are filled with missing values, the missing values are taken as the median of the data, and larger deviation is prevented.
The method for calculating the pose characteristic value in the operation parameter processing module specifically comprises the following steps:
wherein Z is expressed as a pose characteristic value, G is expressed as a load weight, θ is expressed as an inclination angle, μ is expressed as a rotation angle,alpha 1 and alpha 2 are denoted as weight factors.
The environment parameter acquisition module is used for acquiring wind speed, weather, temperature and humidity of the aerial working vehicle during operation and transmitting environment parameters to the environment parameter processing module; in the environment parameter acquisition module, the method for acquiring the wind speed is as follows;
the wind speed is acquired by an optical interferometry method, wherein the measuring steps are as follows:
a1: a laser light source, which may be a laser or a laser diode, is prepared. The light source is directed to the area to be measured, so that the light source can irradiate into the air flow; preparing a Fresnel tile interferometer;
a2: the laser beam is split into two beams by an optical element. One beam irradiates on a fixed reference surface or a reflector, and the other beam irradiates in the airflow to be measured;
a3: the reflected beams from the reference plane and the air flow are re-intersected and the change in interference fringes is observed.
A4: the magnitude of the wind speed can be deduced by utilizing the movement or deformation condition of the interference fringes. The relevant data of wind speed can be obtained by measuring and analyzing parameters such as the shape, displacement, intensity and the like of the interference fringes.
In the environment parameter acquisition module, the temperature acquisition method comprises the following steps:
the temperature of the object is measured using a thermal imager imaging method, the thermal radiation of the object is measured by an infrared sensor, and then converted into a visible image, and the difference in temperature distribution and heat flow is detected from the image.
In the environment parameter module, the humidity acquisition method comprises the following steps:
the sensor acquires humidity data from the high altitude through a remote sensing technology. The system is communicated with high-altitude equipment such as unmanned aerial vehicle and the like, and the humidity condition in the atmosphere is monitored in real time through a remote sensing instrument.
The environment parameter processing module is used for receiving the environment parameters acquired by the environment parameter acquisition module, processing the parameters and calculating to obtain environment influence values; in the environmental parameter processing module, collected data are sequenced from large to small, the median value of each parameter data is taken for calculation, and errors are reduced, wherein the calculation method of the environmental impact value specifically comprises the following steps:
wherein Y is an environmental impact value, F is a measured wind speed value, T is a measured temperature, S is a measured humidity value, eta is a weather index, 3 is taken when weather is sunny, 2 is taken when weather is cloudy, and 1 is taken when other weather is cloudy.
The intelligent algorithm recognition module is used for analyzing the calculated pose characteristic values and environment influence values, importing the data into the intelligent algorithm recognition model, calculating to obtain a comprehensive safety coefficient, recognizing obstacles and safety areas around the operation vehicle during operation, and finally transmitting the comprehensive safety coefficient to the operation early warning module; in the intelligent algorithm identification module, the algorithm for synthesizing the safety coefficient is specifically as follows:
wherein Q is a comprehensive safety coefficient, Z is a pose characteristic value, Y is an environmental influence value, lambda 1 and lambda 2 are weight factors, and omega is other influence factors.
The operation early warning module of the operation vehicle is used for comparing the comprehensive safety coefficient calculated by analysis with a preset comprehensive safety coefficient threshold value and judging whether the operation of the operation vehicle is safe or not according to different output instructions; the operation early warning module of the operation vehicle receives the calculated comprehensive safety coefficient from the intelligent algorithm identification module and compares the calculated comprehensive safety coefficient with a preset comprehensive safety coefficient threshold; outputting a work safety instruction if the calculated comprehensive safety coefficient is greater than a preset comprehensive safety coefficient threshold value; and if the calculated comprehensive safety coefficient is smaller than a preset comprehensive safety coefficient threshold value, outputting an operation danger instruction to perform early warning.
The safety control module is used for feeding back to equipment operators according to different instructions output by the operation early warning module; the safety control module receives different instructions output from the operation early warning module of the operation vehicle; if the input instruction is a work safety instruction, the work vehicle can continue to work; if the input instruction is an operation dangerous instruction, the operation vehicle immediately stops operation, and sends the instruction to equipment operators for timely correction.
Referring to fig. two, in this embodiment, it needs to be specifically explained that the present invention provides an operation safety control system for an overhead working truck based on intelligent recognition, which includes the following steps:
s1: collecting the load weight, the inclination angle and the rotation angle of the working vehicle during working of the overhead working vehicle, and transmitting the working vehicle parameters to a working vehicle parameter processing module;
s2: receiving parameters acquired from a parameter collecting module of the operation vehicle, effectively extracting the parameters, and calculating to obtain pose characteristic values;
s3: the system is used for collecting the wind speed, weather, temperature and humidity of the overhead working truck during operation and transmitting the environmental parameters to the environmental parameter processing module;
s4: the environmental parameters acquired by the environmental parameter acquisition module are received, and the parameters are processed and calculated to obtain environmental impact values;
s5: analyzing the calculated pose characteristic values and environment influence values, importing the data into an intelligent algorithm identification model, calculating to obtain a comprehensive safety coefficient, identifying obstacles and safety areas around the operation vehicle during operation, and finally transmitting the comprehensive safety coefficient to an operation early warning module;
s6: comparing the analyzed and calculated comprehensive safety coefficient with a preset comprehensive safety coefficient threshold value, and judging whether the current operation vehicle is safe or not according to different output instructions;
s7: and feeding back the different instructions output by the operation early warning module to equipment operators, and timely correcting the equipment operators.
Finally: the foregoing description of the preferred embodiments of the invention is not intended to limit the invention to the precise form disclosed, and any such modifications, equivalents, and alternatives falling within the spirit and principles of the invention are intended to be included within the scope of the invention.
Claims (6)
1. An overhead working truck operation safety control system based on intelligent recognition, which is characterized in that:
the operation vehicle parameter acquisition module: the system comprises a working vehicle parameter processing module, a working vehicle load acquisition module, a working vehicle parameter processing module and a working vehicle load acquisition module, wherein the working vehicle load acquisition module is used for acquiring the working load of the working vehicle, the working vehicle parameter processing module is used for acquiring the working vehicle load of the working vehicle;
the operation vehicle parameter processing module: the system is used for receiving the parameters acquired from the operation vehicle parameter collecting module, effectively extracting the parameters, and calculating to obtain pose characteristic values;
the environmental parameter acquisition module: the system is used for collecting the wind speed, weather, temperature and humidity of the overhead working truck during operation and transmitting the environmental parameters to the environmental parameter processing module;
the environment parameter processing module is used for: the environment parameter acquisition module is used for acquiring environment parameters from the environment parameter acquisition module, processing the parameters and calculating to obtain environment influence values;
intelligent algorithm identification module: is used for analyzing the calculated pose characteristic values and environment influence values, importing the data into an intelligent algorithm recognition model, calculating a comprehensive safety coefficient, identifying obstacles and safety areas around the operation vehicle during operation, and finally transmitting the comprehensive safety coefficient to an operation early-warning module;
the operation early warning module of the operation vehicle: the safety control system is used for comparing the comprehensive safety coefficient calculated by analysis with a preset comprehensive safety coefficient threshold value and judging whether the current operation vehicle is safe or not according to different output instructions;
and a safety control module: the device is used for feeding back to equipment operators according to different instructions output in the operation early warning module;
the method for calculating the pose characteristic value in the parameter processing module of the working vehicle specifically comprises the following steps:
wherein Z is expressed as a pose characteristic value, G is expressed as load weight, θ is expressed as an inclination angle, μ is expressed as a rotation angle, and a1 and a2 are expressed as weight factors;
in the environmental parameter processing module, collected data are sequenced from large to small, the median value of each parameter data is taken for calculation, and errors are reduced, wherein the calculation method of the environmental impact value specifically comprises the following steps:
wherein Y is an environmental impact value, F is a measured wind speed value, T is a measured temperature, S is a measured humidity value, eta is a weather index, 3 is taken when weather is sunny, 2 is taken when weather is cloudy, and 1 is taken when other weather is cloudy;
in the intelligent algorithm identification module, the algorithm for synthesizing the safety coefficient is specifically as follows:
wherein Q is a comprehensive safety coefficient, Z is a pose characteristic value, Y is an environmental influence value, lambda 1 and lambda 2 are weight factors, and omega is other influence factors.
2. The intelligent identification-based overhead working truck operation safety control system according to claim 1, wherein: the method for collecting the load weight in the parameter collection module of the operation vehicle comprises the following steps:
by mounting the bend sensor within the work vehicle structure and then connecting the bend sensor to the data acquisition
The equipment is used for recording the load change of the operation vehicle in real time and storing data;
the method for collecting the gradient in the parameter collecting module of the operation vehicle comprises the following steps:
the gyroscope is arranged at the top of the structure of the operation vehicle, then connected to data acquisition equipment, and the inclination angle of the operation vehicle is read through data output by the gyroscope, and the change of the inclination angle of the operation vehicle is recorded and stored in real time;
the method for collecting the rotation angle in the operation vehicle parameter collecting module comprises the following steps:
the rotation angle is determined by measuring the change of the geomagnetic field by installing the magnetometer on the rotation part of the operation vehicle, and then the magnetometer is connected to the data acquisition equipment, and the change of the rotation angle of the operation vehicle is recorded and stored in real time.
3. The intelligent identification-based overhead working truck operation safety control system according to claim 1, wherein: in the operation parameter processing module, the collected data are preprocessed, effective data are extracted, abnormal values are removed, the abnormal values are judged that the difference between the numerical value of each sensor and the numerical value collected in the history sensor is larger than n, the collected numerical value is larger than a preset abnormal threshold value, the data with the abnormal values removed are filled with missing values, the missing values are taken as the median of the data, and larger deviation is prevented.
4. The intelligent identification-based overhead working truck operation safety control system according to claim 1, wherein: in the environment parameter acquisition module, the method for acquiring the wind speed is as follows;
the wind speed is acquired by an optical interferometry method, wherein the measuring steps are as follows:
a1: preparing a laser light source, which can be a laser or a laser diode, and directing the light source towards the area to be measured to ensure that the light source can irradiate into the air flow; preparing a Fresnel tile interferometer;
a2: dividing the laser beam into two beams through an optical element, wherein one beam irradiates on a fixed reference surface or a reflector, and the other beam irradiates in the airflow to be measured;
a3: re-intersecting the reflected beam from the reference plane and the air flow to observe the change of interference fringes;
a4: the movement or deformation condition of the interference fringes is utilized to infer the wind speed, and relevant data of the wind speed can be obtained by measuring and analyzing the shape, displacement, strength and other parameters of the interference fringes;
in the environment parameter acquisition module, the temperature acquisition method comprises the following steps:
measuring the temperature of an object by using a thermal imager imaging method, measuring the heat radiation of the object by an infrared sensor, converting the heat radiation into a visible image, and detecting the difference of temperature distribution and heat flow according to the image;
in the environment parameter module, the humidity acquisition method comprises the following steps:
the sensor acquires humidity data from the high altitude through a remote sensing technology, is communicated with high altitude equipment such as an unmanned plane and the like, and monitors the humidity condition in the atmosphere in real time through a remote sensing instrument.
5. The intelligent identification-based overhead working truck operation safety control system according to claim 1, wherein: the operation early warning module of the operation vehicle receives the calculated comprehensive safety coefficient from the intelligent algorithm identification module and compares the calculated comprehensive safety coefficient with a preset comprehensive safety coefficient threshold; outputting a work safety instruction if the calculated comprehensive safety coefficient is greater than a preset comprehensive safety coefficient threshold value; and if the calculated comprehensive safety coefficient is smaller than a preset comprehensive safety coefficient threshold value, outputting an operation danger instruction to perform early warning.
6. The intelligent identification-based overhead working truck operation safety control system according to claim 1, wherein: the safety control module receives different instructions output from the operation early warning module of the operation vehicle; if the input instruction is a work safety instruction, the work vehicle can continue to work; if the input instruction is an operation dangerous instruction, the operation vehicle immediately stops operation, and sends the instruction to equipment operators for timely correction.
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