CN115941734A - Intelligent detection system for automobile outer rear-view mirror folder - Google Patents
Intelligent detection system for automobile outer rear-view mirror folder Download PDFInfo
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- CN115941734A CN115941734A CN202211520859.6A CN202211520859A CN115941734A CN 115941734 A CN115941734 A CN 115941734A CN 202211520859 A CN202211520859 A CN 202211520859A CN 115941734 A CN115941734 A CN 115941734A
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Abstract
The invention discloses an intelligent detection system for an automobile outside rearview mirror folder. The invention realizes the acquisition of real-time operation data of the folder by using a multi-source sensor; carrying out compression sampling on the acquired data by utilizing the ARM at the edge end, and sending the compressed data to a cloud management platform by utilizing WiFi; judging the real-time state of the folder and predicting the service life by using a data calculation model on a cloud management platform; and performing corresponding various protection operations and monitoring result display on the system by using the data obtained by analysis, thereby realizing intelligent detection of the folder. The system disclosed by the invention realizes the reliability detection of the automobile rearview mirror folder through embedded control and cloud platform management.
Description
Technical Field
The invention relates to a detection system of an automobile rearview mirror, in particular to an intelligent detection system of an automobile outer rearview mirror folder.
Background
As important parts of an automobile, rear view mirrors are classified into an exterior rear view mirror and an interior rear view mirror, wherein the exterior rear view mirror is installed at both left and right sides of the exterior of the automobile for expanding a visual field range of a driver. The rearview mirror facilitates the driver to observe and judge the situation behind the vehicle, and plays roles in assisting driving, judging the distance between vehicles and guaranteeing safety. The current rear-view mirror for the automobile market comprises: mechanical, network, and electronic types, wherein electronic type is widely used for its reliability.
The electronic rearview mirror adopts a mature embedded technology to realize automatic opening and closing when vehicles start and stop, meet or avoid obstacles. Firstly, the folder is frequently started and stopped in the using process, and a control circuit of the folder is required to have higher reliability; secondly, when the rearview mirror is in obstacle avoidance, overcurrent and overvoltage occur to the control circuit due to the fact that the motor is locked, electronic components are damaged, and the control circuit is required to have a certain protection effect.
This requires the folder manufacturer to carefully test the rearview mirror before shipping. However, the existing folder testing system has the problems of single function, missing process data, low reliability and the like.
Therefore, a multifunctional, high-efficiency and high-precision automobile rearview mirror folder testing system is needed to be designed for improving the testing efficiency and precision.
Disclosure of Invention
In order to overcome the defect that the performance of the rearview mirror is measured by the existing testing system, the invention provides the intelligent detecting system for the automobile outer rearview mirror folder.
The technical scheme of the invention is as follows:
the system comprises a motor, a control module, a data acquisition module, a data processing module and a man-machine interaction module;
the folder is internally provided with a motor, and the output end of the motor is connected to a rearview mirror outside the automobile and used for controlling the rotation of the rearview mirror;
the data acquisition module is arranged near the rearview mirror, connected to the motor, and used for acquiring data of the motor and data of the environment in real time as sensing data and sending the sensing data to the data processing module;
the output end of the control module is connected to a rearview mirror outside the automobile and used for controlling the rotation of the rearview mirror; meanwhile, the data acquisition module is connected to the control module and is used for controlling the work of the data acquisition module;
the data processing module is connected to the data acquisition module and used for receiving the sensing data, analyzing and processing the sensing data for detection, generating a control signal according to a detection result and sending the detection result and the control signal to the man-machine interaction module;
the human-computer interaction module is connected to the data processing module and the control module, is used for receiving a detection result from the data processing module for displaying, is used for receiving a control signal from the data processing module and feeding back the control signal to the control module, and is also used for receiving a control signal from external input and feeding back the control signal to the control module.
The data acquisition module comprises a voltage acquisition unit, a current acquisition unit, a torque acquisition unit, a temperature acquisition unit and a time monitoring unit;
the voltage acquisition unit and the current acquisition unit are connected to a hardware circuit of the motor in the folder and used for monitoring whether the hardware circuit of the motor in the folder is overloaded or overcurrent or not;
the temperature acquisition unit is arranged near a hardware circuit of a motor in the folder and used for monitoring whether the hardware circuit has a fault of overhigh temperature;
the torque acquisition unit is connected to an output shaft of a motor in the folder and is used for monitoring whether the motor in the folder is overloaded or not;
the time monitoring unit is connected to the voltage acquisition unit, the current acquisition unit, the torque acquisition unit and the temperature acquisition unit and is used for monitoring and recording the time of data generation.
The control module comprises a time monitoring unit and a sensor control unit;
the time monitoring unit is connected to the motor and used for controlling the operation of the motor;
and the sensor control unit is connected to the data acquisition module and is used for controlling the acquisition time and the acquisition duration of each acquisition unit of the data acquisition module.
The data processing module comprises a compression sampling unit, a data transmission unit, a data analysis unit and a service life prediction unit;
the compression sampling unit is used for transmitting the sensing data acquired by the data acquisition module to the data transmission unit after sampling and compressing;
the data transmission unit is used for receiving the sensing data sampled and compressed by the compression and sampling unit and sending the sensing data to the data analysis unit;
the data analysis unit is positioned on the cloud platform and used for training and predicting the model;
and the prediction model unit is positioned on the cloud platform and used for realizing the prediction of the service life of the folder.
The human-computer interaction module comprises a data display unit and a system control unit;
the data display unit is in wireless communication with the data control module and the data processing module respectively and is used for receiving the detection result from the data processing module and displaying the detection result in real time;
and the system control unit is used for receiving a control signal from external input and feeding the control signal back to the control module.
The service life prediction unit in the data processing module predicts the service life of the folder on the cloud platform, and the training process of the prediction model is as follows:
(1): reconstructing sensing data in the aspects of current, voltage, temperature and torque received from a data acquisition module by using a multi-source data receiving port of the data acquisition module to obtain reconstructed data;
(2): normalizing the reconstruction data, and connecting all the normalized reconstruction data in series to form sample data to construct a multi-source data set;
(3): processing the multi-source data set by using a depth self-encoder to extract multi-source data characteristics;
(4): predicting the service life of the folder by using the extracted multi-source data characteristics to obtain a prediction result;
(5): and comparing the predicted result with the folder degradation process of the whole life cycle to obtain a preventive maintenance scheme.
The invention has the beneficial effects that:
1) The compressed sensing technology is adopted to carry out data acquisition on temperature, illumination, current and voltage, so that the loss of the system to hardware equipment is reduced; the power spent on sampling becomes smaller; less information needs to be transferred; reducing the bandwidth limitation in special environment; the loss and hardware overhead for storage are reduced, and the comprehensive performance of the system is greatly improved.
2) The intelligent whole-process monitoring and fault backtracking are realized by depending on the big data storage, transmission and analysis capability of the cloud technology. Through the fault information push technology of the mobile terminal, early warning at the first time is achieved, relevant personnel are scheduled in time to carry out troubleshooting, and the fault backtracking capability is greatly improved.
3) The service life prediction is carried out by using the characteristics extracted from the multi-source data, the accuracy and the prediction speed of the service life prediction of the folder are improved, and the service life prediction method has the characteristics of multiple functions, high efficiency and high precision.
Drawings
FIG. 1 is a flow chart of the operation of the system of the present invention;
FIG. 2 is a schematic diagram of the overall architecture of the system of the present invention.
Detailed Description
The present invention is further described below.
As shown in fig. 1, the specific embodiment of the present invention is as follows:
firstly, manually determining whether to enter a working state, and under the condition of determining to enter the working state, realizing the control of a motor and a sensor by using a control module; then, after the motor and the sensor enter the state to work, the data acquisition module is used for acquiring voltage, current, torque, temperature and time; then, realizing compressed transmission of data by using compressed sensing, realizing prediction of a service life result of the folder by using a data processing module, and displaying the result to a human-computer interaction interface; finally, the required result is obtained through parameter adjustment. The real-time state detection and the service life prediction of the automobile outside rear-view mirror folder are realized, the detection precision is improved, the maintenance cost is reduced, and the economic benefit is increased.
As shown in fig. 2, the system comprises four modules of a motor, a control module 1, a data acquisition module 2, a data processing module 3 and a human-computer interaction module 4;
the folder is internally provided with a motor, and the output end of the motor is connected to a rearview mirror outside the automobile and used for controlling the rotation angle of the rearview mirror;
the data acquisition module 2 is arranged near the rearview mirror, connected to the motor, and used for acquiring data of the motor and data of the environment in real time as sensing data and sending the sensing data to the data processing module 3;
the output end of the control module 1 is connected to a rearview mirror outside the automobile and used for controlling the rotation angle of the rearview mirror; meanwhile, the data acquisition module 2 is connected to control the work of the data acquisition module 2;
the data processing module 3 is connected to the data acquisition module 2 and used for receiving the sensing data, analyzing and processing the sensing data for detection, generating a control signal according to a detection result and sending the detection result and the control signal to the man-machine interaction module 4;
and the human-computer interaction module 4 is connected to the data processing module 3 and the control module 1, is used for receiving the detection result from the data processing module 3 for displaying, is used for receiving the control signal from the data processing module 3 and feeding back the control signal to the control module 1, and is also used for receiving the control signal from the external input and feeding back the control signal to the control module 1 for feedback control.
The data acquisition module 2 comprises a voltage acquisition unit 2-1, a current acquisition unit 2-2, a torque acquisition unit 2-3, a temperature acquisition unit 2-4 and a time monitoring unit 2-5;
the voltage acquisition unit 2-1 and the current acquisition unit 2-2 are connected to a hardware circuit of the motor in the folder and used for monitoring whether the hardware circuit of the motor in the folder is overloaded or over-current or not;
the temperature acquisition unit 2-4 is arranged near a hardware circuit of a motor in the folder and used for monitoring whether the hardware circuit has a fault of overhigh temperature;
the torque acquisition unit 2-3 is connected to an output shaft of a motor in the folder and used for monitoring whether the motor in the folder is overloaded or not;
and the time monitoring unit 2-5 is connected to the voltage acquisition unit 2-1, the current acquisition unit 2-2, the torque acquisition unit 2-3 and the temperature acquisition unit 2-4 and is used for monitoring and recording the time of data generation so as to trace back the later fault.
If the overload condition occurs, or the conditions such as overcurrent, overhigh and overload occur, the control module 1 performs corresponding protection operation.
The control module 1 comprises a time monitoring unit 1-1 and a sensor control unit 1-2;
the time monitoring unit 1-1 is connected to the motor and used for controlling the operation of the motor;
the sensor control unit 1-2 is connected to the voltage acquisition unit 2-1, the current acquisition unit 2-2, the torque acquisition unit 2-3, the temperature acquisition unit 2-4 and the time monitoring unit 2-5 of the data acquisition module 2, and is used for controlling the acquisition time and the acquisition duration of each acquisition unit of the data acquisition module 2.
Further, the control module 1 plays several roles in the system:
in a first aspect: the starting and stopping, the positive rotation, the reverse rotation and the locked rotation of the motor of the folder are realized according to preset parameters, and the method is used for simulating the actual operation condition of the folder to the maximum extent.
In a second aspect: and controlling the start-stop time, the acquisition time interval and the data volume of various sensor units and data acquisition.
In a third aspect: the folder detection system is used for controlling the communication process of each interface in the folder detection system.
The data processing module 3 comprises a compression sampling unit 3-1, a data transmission unit 3-2, a data analysis unit 3-3 and a service life prediction unit 3-4; the data processing module 3 realizes the judgment of the state of the folder through the analysis of the collected data.
The compression sampling unit 3-1 is used for transmitting various sensing data acquired by the data acquisition module 2 to the data transmission unit 3-2 after sampling and compression so as to reduce the transmission quantity of wireless data;
the data transmission unit 3-2 is used for receiving the sensing data which are sampled and compressed by the compression and sampling unit 3-1 and sending the sensing data to the data analysis unit 3-3;
the data analysis unit 3-3 is positioned on the cloud platform and used for training and predicting the model;
and the prediction model unit is positioned on the cloud platform and used for realizing the prediction of the service life of the folder.
The data after compression sampling by the compression sampling unit 3-1 is transmitted to the cloud platform through a wifi or 4G interface, and the data analysis unit 3-3 is located on the cloud platform and used for increasing the computing efficiency, realizing real-time data feedback and reducing diagnosis errors.
The man-machine interaction module 4 comprises a data display unit 4-1 and a system control unit 4-2;
the data display unit 4-1 is in wireless communication with the data control module 1 and the data processing module 3 respectively and is used for receiving the detection result from the data processing module 3 to display and analyze the result and the system state in real time;
and the system control unit 4-2 is used for receiving a control signal from external input facing a worker and feeding the control signal back to the control module 1 to realize control over the folder.
The man-machine interaction module 4 is also provided with a mobile end, the system control unit 4-2 transmits control contents to be carried out to the control end by using the mobile end in the man-machine interaction module 4, and the control unit of the control module 1 is used for carrying out corresponding operation on the detection system.
Furthermore, the data acquisition module 2 sends the acquired various sensing data to the ARM processor through an RS485 bus, and a data down-sampling model is deployed on the ARM processor, so as to reduce the transmission amount of the data to the data processing module 3. And the data subjected to compression sampling is reconstructed at a data receiving end and is used for actual data analysis.
All the main units realize bidirectional wireless communication, and the communication distance and efficiency are improved.
In the folder testing system, the data acquisition module 2 needs to transmit acquired current and voltage data to the data processing module 3 in real time.
When the folder is locked, the current and the voltage of the control circuit are suddenly changed, and the sudden change value is monitored in time and fed back to the control module 1, so that the circuit is protected.
In specific implementation, an instantaneous current I and an instantaneous voltage V are set, when 10 continuously collected instantaneous voltages or currents are larger than a set threshold value, the circuit is considered to be overcurrent or overvoltage, otherwise, the circuit is set to be zero, and the circuit is considered to be normal.
The service life prediction unit 3-4 in the data processing module 3 predicts the service life of the folder on the cloud platform, and the training process of the prediction model is as follows:
1): reconstructing the sensing data in the aspects of current, voltage, temperature and torque received from the data acquisition module 2 by using a self multi-source data receiving port to obtain reconstructed data;
2): normalizing the reconstruction data, and connecting all the normalized reconstruction data in series to form sample data to construct a multi-source data set;
3): processing the multi-source data set by using a depth self-encoder to extract multi-source data characteristics;
4): predicting the service life of the folder by using the extracted multi-source data characteristics to obtain a prediction result;
5): and comparing the predicted result with the folder degradation process of the whole life cycle to obtain a preventive maintenance scheme.
In a specific implementation, the multi-source data set is calculated according to the following equation of 7: and 3, dividing the model into a training sample and a testing sample in proportion, wherein the training sample is used for training the original model, and the testing sample is used for detecting the training effect of the model.
In specific implementation, an SHT30 is selected as a temperature sensor in a data acquisition unit, a JNT-S is adopted as a torque sensor, the data acquisition frequency is 50Hz, the sampling time is 1min, the sampling interval is 30min, and the sampling mode adopts compressed sensing. The ARM processor in the data processing unit is selected to be STM32FZGT6, and the data processing capacity is improved.
The testing period of the data control system is 20000 times, the testing time of each period is 12.5s, wherein the motor forwards transmits 5s, reversely rotates 5s and stops for 1s, the threshold value of the locked-rotor current is 0.8A, and the locked-rotor time is 1s-1.5s.
The cloud platform adopts an Ali cloud server, and the server has the advantages of short maintenance period, large data storage capacity, reliable data analysis result and strong computing power. The defects of unstable calculation, insufficient storage space and complicated maintenance process in the traditional neural network training and deployment are overcome, the system performance is improved, and the operation and maintenance cost of the system is reduced.
The implementation method of the system comprises the following steps: firstly, the multi-source sensor is utilized to realize the acquisition of the real-time operation data of the folder. And then, carrying out compression sampling on the acquired data by utilizing the ARM at the edge end, and sending the compressed data to the cloud management platform by utilizing the WiFi. And then, judging the real-time state of the folder and predicting the service life by using a data calculation model on the cloud management platform. And finally, performing corresponding various protection operations and monitoring result display on the system by using the data obtained by analysis, and realizing intelligent detection of the folder.
The operation flow and the overall monitoring process of the system are as follows:
1) A worker inputs preset parameters in the system control unit 4-2 and sends the control parameters to the folder control module 1 and the data acquisition module 2 through wifi;
2) The control module controls the folder control unit 1-1 to perform corresponding operation according to the instruction;
3) After the folder operates stably, the data acquisition module 2 acquires corresponding data according to a parameter instruction set by a worker, and a specific control instruction is executed by the sensor control unit 1-2;
4) The collected data is sent to an ARM end by utilizing the RS485 bus to carry out primary processing on the data;
5) In an ARM processor, a data sampling unit 3-1 is used for carrying out compressed sensing sampling on original data;
6) Compressing the sampled data, and sending the data to the cloud server by using a data transmission unit 3-2;
7) And the cloud server reconstructs the compressed data, and the reconstructed data is used for the data analysis unit 3-3, so that the running state of the folder is monitored in real time. Meanwhile, the data are used as the prediction data of a life prediction unit 3-4 for realizing the prediction analysis of the residual life of the folder;
8) All the finally analyzed data and the state of the whole test system are sent to a data display unit 4-1 for reference of workers. In the whole test flow, any fault can send out a corresponding alarm, and a corresponding decision is made on the fault autonomously, for example, the motor control unit 1-1 and the sensor control unit 1-2 are switched on and off when overcurrent and overvoltage occur; and when the components of the data acquisition module 2 are damaged, personnel is informed to replace the components, and the like.
The embodiments described in this specification are merely illustrative of implementations of the inventive concepts, which are intended for purposes of illustration only. The scope of the present invention should not be construed as being limited to the particular forms set forth in the embodiments, but is to be accorded the widest scope consistent with the principles and equivalents thereof as contemplated by those skilled in the art.
Claims (6)
1. The utility model provides an outside rear-view mirror scray intellectual detection system which characterized in that:
the system comprises a motor, a control module (1), a data acquisition module (2), a data processing module (3) and a man-machine interaction module (4);
the folder is internally provided with a motor, and the output end of the motor is connected to a rearview mirror outside the automobile and used for controlling the rotation of the rearview mirror;
the data acquisition module (2) is arranged near the rearview mirror, connected to the motor, and used for acquiring data of the motor and data of the environment in real time as sensing data and sending the sensing data to the data processing module (3);
the output end of the control module (1) is connected to a rearview mirror outside the automobile and used for controlling the rotation of the rearview mirror; meanwhile, the device is connected to the data acquisition module (2) and is used for controlling the work of the data acquisition module (2);
the data processing module (3) is connected to the data acquisition module (2) and used for receiving the sensing data, analyzing and processing the sensing data for detection, generating a control signal according to a detection result, and sending the detection result and the control signal to the man-machine interaction module (4);
the man-machine interaction module (4) is connected to the data processing module (3) and the control module (1), is used for receiving a detection result from the data processing module (3) for displaying, is used for receiving a control signal from the data processing module (3) and feeding back the control signal to the control module (1), and is also used for receiving a control signal input from the outside and feeding back the control signal to the control module (1).
2. The intelligent detection system for the folder of the automobile exterior rear-view mirror as claimed in claim 1, wherein:
the data acquisition module (2) comprises a voltage acquisition unit (2-1), a current acquisition unit (2-2), a torque acquisition unit (2-3), a temperature acquisition unit (2-4) and a time monitoring unit (2-5);
the voltage acquisition unit (2-1) and the current acquisition unit (2-2) are connected to a hardware circuit of a motor in the folder and used for monitoring whether the hardware circuit of the motor in the folder is overloaded or over-current or not;
the temperature acquisition unit (2-4) is arranged near a hardware circuit of the motor in the folder and used for monitoring whether the hardware circuit has an over-temperature fault;
the torque acquisition unit (2-3) is connected to an output shaft of a motor in the folder and is used for monitoring whether the motor in the folder is overloaded or not;
the time monitoring unit (2-5) is connected to the voltage acquisition unit (2-1), the current acquisition unit (2-2), the torque acquisition unit (2-3) and the temperature acquisition unit (2-4) and is used for monitoring and recording the time of data generation.
3. The intelligent detection system for the folder of the automobile exterior rear-view mirror as claimed in claim 1, wherein:
the control module (1) comprises a time monitoring unit (1-1) and a sensor control unit (1-2);
the time monitoring unit (1-1) is connected to the motor and used for controlling the operation of the motor;
and the sensor control unit (1-2) is connected to the data acquisition module (2) and is used for controlling the acquisition time and the acquisition duration of each acquisition unit of the data acquisition module (2).
4. The intelligent detection system for the folder of the exterior rearview mirror of the automobile as claimed in claim 1, wherein:
the data processing module (3) comprises a compression sampling unit (3-1), a data transmission unit (3-2), a data analysis unit (3-3) and a service life prediction unit (3-4);
the compression sampling unit (3-1) is used for transmitting the sensing data acquired by the data acquisition module (2) to the data transmission unit (3-2) after sampling and compression;
the data transmission unit (3-2) is used for receiving the sensing data which are sampled and compressed by the compression and sampling unit (3-1) and sending the sensing data to the data analysis unit (3-3);
the data analysis unit (3-3) is positioned on the cloud platform and used for training and predicting data;
and the prediction model unit is positioned on the cloud platform and used for realizing the prediction of the service life of the folder.
5. The intelligent detection system for the folder of the exterior rearview mirror of the automobile as claimed in claim 1, wherein:
the human-computer interaction module (4) comprises a data display unit (4-1) and a system control unit (4-2);
the data display unit (4-1) is in wireless communication with the data control module (1) and the data processing module (3) respectively and is used for receiving the detection result from the data processing module (3) and displaying the detection result in real time;
and the system control unit (4-2) is used for receiving a control signal from an external input and feeding back the control signal to the control module (1).
6. The intelligent detection system for the folder of the automobile exterior rear-view mirror as claimed in claim 4, wherein:
the service life prediction unit (3-4) in the data processing module (3) predicts the service life of the folder on the cloud platform, and the training process of the prediction model is as follows:
(1): reconstructing sensing data in the aspects of current, voltage, temperature and torque received from the data acquisition module (2) by using a multi-source data receiving port of the data acquisition module to obtain reconstructed data;
(2): normalizing the reconstruction data, and connecting all the normalized reconstruction data in series to form sample data to construct a multi-source data set;
(3): processing the multi-source data set by using a depth self-encoder to extract multi-source data characteristics;
(4): predicting the service life of the folder by using the extracted multi-source data characteristics to obtain a prediction result;
(5): and comparing the predicted result with the folder degradation process of the whole life cycle to obtain a preventive maintenance scheme.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117557660A (en) * | 2024-01-09 | 2024-02-13 | 北京集度科技有限公司 | Data processing method and device, electronic equipment and vehicle |
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| CN117557660A (en) * | 2024-01-09 | 2024-02-13 | 北京集度科技有限公司 | Data processing method and device, electronic equipment and vehicle |
| CN117557660B (en) * | 2024-01-09 | 2024-04-12 | 北京集度科技有限公司 | Data processing method and device, electronic equipment and vehicle |
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