CN215666701U - Auxiliary arm working condition detection system and crane - Google Patents
Auxiliary arm working condition detection system and crane Download PDFInfo
- Publication number
- CN215666701U CN215666701U CN202122057624.5U CN202122057624U CN215666701U CN 215666701 U CN215666701 U CN 215666701U CN 202122057624 U CN202122057624 U CN 202122057624U CN 215666701 U CN215666701 U CN 215666701U
- Authority
- CN
- China
- Prior art keywords
- working condition
- auxiliary arm
- condition detection
- image
- detection result
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Landscapes
- Jib Cranes (AREA)
Abstract
The utility model provides a working condition detection system of an auxiliary arm and a crane, wherein the system comprises: the camera device is connected with the controller; the camera device is used for acquiring an auxiliary arm area image and inputting the auxiliary arm area image to the controller; the controller is used for obtaining a working condition detection result of the auxiliary arm based on the auxiliary arm area image. According to the utility model, the image of the auxiliary arm region is obtained through the camera device, and the controller accurately and quickly determines the detection result of the working condition of the auxiliary arm based on the image of the auxiliary arm region.
Description
Technical Field
The utility model relates to the technical field of working condition detection, in particular to an auxiliary arm working condition detection system and a crane.
Background
The crane is used as a special vehicle, is widely applied to traffic transportation, civil construction and large-scale infrastructure construction sites, and plays an important role in engineering construction.
At present, the safe operation of the crane is mostly carried out through a moment limiter, for example, whether a performance table of the moment limiter is used by an auxiliary arm or not, whether the auxiliary arm 2-joint arm is used or not and the installation angle of the auxiliary arm are closely related, under a general condition, the auxiliary arm is installed firstly, then the working condition of the auxiliary arm of the crane is set on a display screen, so that a corresponding performance table is called by a controller, in the actual working process, after an operator starts the auxiliary arm, the operator possibly forgets to set the working condition of the auxiliary arm on the display screen or makes mistakes in setting, so that the condition that the performance table is inconsistent with the actual working condition is caused, and further safety accidents are caused.
In the prior art, an angle sensor is generally installed on an auxiliary arm, the angle of the auxiliary arm is detected according to data transmitted back by the angle sensor, a position sensor/proximity switch is installed on a main arm to judge whether the auxiliary arm is used, the position sensor/proximity switch is installed between a first-section arm of the auxiliary arm and a second-section arm of the auxiliary arm to detect whether the second-section arm of the auxiliary arm is used, the working condition of the auxiliary arm is comprehensively determined according to the information, and the working condition of the auxiliary arm is input to a torque limiter, so that a corresponding performance table is automatically called. However, the number of sensors to be installed for detecting the working condition of the auxiliary arm is large, the circuit is complex, and faults are easy to occur.
SUMMERY OF THE UTILITY MODEL
The utility model provides an auxiliary arm working condition detection system and a crane, which are used for solving the defects that in the prior art, the number of sensors required for auxiliary arm working condition detection is large, the circuit is complex and faults are easy to occur.
The utility model provides a working condition detection system for an auxiliary arm, which comprises:
the camera device is connected with the controller;
the camera device is used for acquiring an auxiliary arm area image and inputting the auxiliary arm area image to the controller;
the controller is used for obtaining a working condition detection result of the auxiliary arm based on the auxiliary arm area image.
According to the auxiliary arm working condition detection system provided by the utility model, the auxiliary arm area image comprises a plurality of image frames; the controller comprises an initial detection unit and a detection result judgment unit;
the initial detection unit is used for obtaining an initial working condition detection result corresponding to each image frame based on each image frame; the detection result judging unit is used for determining the auxiliary arm working condition detection result based on the initial working condition detection result corresponding to each image frame.
According to the auxiliary arm working condition detection system provided by the utility model, the detection result judgment unit comprises a result statistics module and a result determination module;
the result counting module is used for counting the number of image frames with the same initial working condition detection result, and the result determining module is used for taking the initial working condition detection result corresponding to the maximum number of the image frames as the working condition detection result of the auxiliary arm.
According to the auxiliary arm working condition detection system provided by the utility model, the controller is used for inputting the auxiliary arm area image into the working condition detection model to obtain the auxiliary arm working condition detection result output by the working condition detection model;
the working condition detection model is obtained by training based on the sample auxiliary arm region image and the sample auxiliary arm working condition detection result.
According to the auxiliary arm working condition detection system provided by the utility model, the sample auxiliary arm area image comprises an auxiliary arm one-joint arm 0-degree angle image, an auxiliary arm 1-joint arm 15-degree angle image, an auxiliary arm one-joint arm 30-degree angle image, an auxiliary arm one-joint arm and auxiliary arm two-joint arm 0-degree angle image, an auxiliary arm one-joint arm and auxiliary arm two-joint arm 15-degree angle image and an auxiliary arm one-joint arm and auxiliary arm two-joint arm 30-degree angle image.
According to the working condition detection system of the auxiliary arm provided by the utility model, the controller further comprises:
and the parameter acquisition unit is used for acquiring the crane performance parameters under the working condition of the corresponding auxiliary jib based on the working condition detection result of the auxiliary jib.
According to the auxiliary arm working condition detection system provided by the utility model, the controller is a torque limiter or is in communication connection with the torque limiter.
According to the utility model, the working condition detection system of the auxiliary arm is provided,
if the controller is in communication connection with the torque limiter, the parameter obtaining unit is further configured to:
and sending the detection result of the working condition of the auxiliary arm to the torque limiter so as to receive the crane performance parameters under the corresponding working condition of the auxiliary arm sent by the torque limiter.
According to the auxiliary arm working condition detection system provided by the utility model, the camera device is arranged on the arm head of the main arm.
The present invention also provides a crane comprising: the auxiliary arm working condition detection system is described above.
According to the auxiliary arm working condition detection system and the crane, the image of the auxiliary arm area is obtained through the camera device, the controller accurately and quickly determines the auxiliary arm working condition detection result based on the image of the auxiliary arm area, and compared with the traditional method that a large number of sensors need to be installed to cause a complex circuit and easily cause faults, the auxiliary arm working condition detection system provided by the embodiment of the utility model is simple in structure and high in auxiliary arm working condition detection efficiency.
Drawings
In order to more clearly illustrate the technical solutions of the present invention or the prior art, the drawings needed for the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.
FIG. 1 is a schematic structural diagram of a system for detecting the working condition of an auxiliary arm provided by the utility model;
fig. 2 is a schematic flow chart of detecting the working condition of the auxiliary arm provided by the utility model.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is obvious that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
At present, the safe operation of the crane is mostly carried out through a moment limiter, for example, whether a performance table of the moment limiter is used by an auxiliary arm or not, whether the auxiliary arm 2-joint arm is used or not and the installation angle of the auxiliary arm are closely related, under a general condition, the auxiliary arm is installed firstly, then the working condition of the auxiliary arm of the crane is set on a display screen, so that a corresponding performance table is called by a controller, in the actual working process, after an operator starts the auxiliary arm, the operator possibly forgets to set the working condition of the auxiliary arm on the display screen or makes mistakes in setting, so that the condition that the performance table is inconsistent with the actual working condition is caused, and further safety accidents are caused.
In the prior art, an angle sensor is generally installed on an auxiliary arm, the angle of the auxiliary arm is detected according to data transmitted back by the angle sensor, a position sensor/proximity switch is installed on a main arm to judge whether the auxiliary arm is used, the position sensor/proximity switch is installed between a first-section arm of the auxiliary arm and a second-section arm of the auxiliary arm to detect whether the second-section arm of the auxiliary arm is used, the working condition of the auxiliary arm is comprehensively determined according to the information, and the working condition of the auxiliary arm is input to a torque limiter, so that a corresponding performance table is automatically called. However, the number of sensors to be installed for detecting the working condition of the auxiliary arm is large, the circuit is complex, and faults are easy to occur.
In view of the above, the utility model provides a working condition detection system for an auxiliary arm. Fig. 1 is a schematic structural diagram of an auxiliary arm working condition detection system provided by the present invention, and as shown in fig. 1, the system includes: the camera device 110 and the controller 120, wherein the camera device 110 is connected with the controller 120;
the camera device 110 is configured to capture an image of the forearm area, and input the image of the forearm area to the controller. The camera device can comprise a camera, and when the crane works, the camera collects images in front of the main arm to obtain images of the auxiliary arm area. In addition, the image capturing device may capture an image in front of the main arm in real time to obtain an image of the sub-arm area, which is not particularly limited in this embodiment.
It should be noted that, because the acquired image of the region of the auxiliary boom requires that the auxiliary boom is not shielded, the embodiment may preferably install the camera device on the head of the main boom, so that the acquired image of the region of the auxiliary boom is not shielded, and the image acquisition efficiency is improved. As another optional embodiment, after the camera device collects the initial auxiliary arm area image, the initial auxiliary arm image can be screened, the blocked initial auxiliary arm area image is filtered out, and the auxiliary arm area image is obtained, so that the controller can be ensured to accurately obtain the auxiliary arm working condition detection result based on the auxiliary arm area image.
After acquiring the image of the forearm area, the controller 120 may obtain a result of detecting the working condition of the forearm based on the information, which includes the angle information of the forearm, whether to use the first-joint forearm and the second-joint forearm, and the corresponding angle information when to use the first-joint forearm and the second-joint forearm. It can be understood that the controller 120 may pre-store sample forearm area images under different conditions, compare the forearm area images with the sample forearm area images, determine a sample forearm area image with the highest similarity to the forearm area image, and use the condition corresponding to the sample forearm area image as the result of detecting the forearm condition. If the existing similarity calculation algorithm can be adopted, the similarity between the auxiliary arm area image and the sample auxiliary arm area image is calculated, and the auxiliary arm working condition corresponding to the sample auxiliary arm area image with the maximum similarity is used as the auxiliary arm working condition detection result.
According to the auxiliary arm working condition detection system provided by the embodiment of the utility model, the auxiliary arm area image is obtained through the camera device, and the controller accurately and quickly determines the auxiliary arm working condition detection result based on the auxiliary arm area image.
Based on the above embodiment, the forearm area image includes a plurality of image frames; the controller 120 includes an initial detection unit and a detection result determination unit;
the initial detection unit is used for obtaining an initial working condition detection result corresponding to each image frame based on each image frame; the detection result judging unit is used for determining the auxiliary arm working condition detection result based on the initial working condition detection result corresponding to each image frame.
Specifically, the forearm region image may include a plurality of image frames, such as a plurality of consecutive image frames taken within a preset period. Considering that the working condition of the crane is complex during working, if the working condition detection result of the auxiliary arm is determined only based on a single image, errors can be caused, the working condition detection result of the auxiliary arm cannot be accurately obtained, and the safety operation of the crane is further influenced.
Therefore, the initial detection unit in this embodiment detects the working condition corresponding to each image frame to obtain the initial working condition detection result corresponding to each image frame. Then, the final detection result, namely the detection result of the working condition of the auxiliary arm is determined by the detection result judging unit.
Optionally, the detection result determining unit may take the initial working condition detection result as the auxiliary arm working condition detection result when it is determined that the initial working condition detection results corresponding to the image frames are all consistent; or counting the number of image frames with the same initial working condition detection result, and taking the initial working condition detection result corresponding to the maximum image frame number as the auxiliary arm working condition detection result.
As shown in fig. 2, 10 images are obtained by the high-definition camera at intervals of 1s, the working condition of the fly jib corresponding to each image is determined, if the working conditions of the fly jib corresponding to the 10 images are consistent, the working condition of the fly jib corresponding to the 10 images is used as a final detection result of the working condition of the fly jib, and the detection result is sent to the torque limiter, so that a corresponding crane performance table under the working condition detection result is obtained. And if the working conditions of the auxiliary arms corresponding to the 10 images are inconsistent, adopting a high-definition camera to acquire the 10 images again for detection.
Therefore, the initial working condition detection results corresponding to the image frames are integrated, the accuracy of the working condition detection results of the auxiliary arm is improved, and the safe operation of the crane is further guaranteed.
Based on any one of the above embodiments, the detection result determination unit includes a result statistic module and a result determination module;
the result counting module is used for counting the number of image frames with the same initial working condition detection result, and the result determining module is used for taking the initial working condition detection result corresponding to the maximum image frame number as the working condition detection result of the auxiliary arm.
Specifically, because the working condition is complicated when the crane works, if the work condition detection result of the auxiliary boom is determined only based on a single image, an error may be caused, so that the work condition detection result of the auxiliary boom cannot be accurately obtained, and the safe operation of the crane is further influenced.
Therefore, in this embodiment, the result counting module counts the number of image frames having the same initial working condition detection result, and then the result determining module takes the initial working condition detection result corresponding to the maximum number of image frames as the working condition detection result of the auxiliary arm.
For example, the image of the forearm region includes 10 image frames, wherein 8 image frames correspond to the initial condition detection result 1, 1 image frame corresponds to the initial condition detection result 2, and 1 image frame corresponds to the initial condition detection result 3, that is, the number of image frames corresponding to the initial condition detection result 1 is the largest, so that the initial condition detection result 1 can be used as the forearm condition detection result.
Based on any of the above embodiments, the controller 120 is configured to input the auxiliary arm region image into the working condition detection model, and obtain an auxiliary arm working condition detection result output by the working condition detection model;
the working condition detection model is obtained by training based on the sample auxiliary arm region image and the sample auxiliary arm working condition detection result.
Specifically, after the auxiliary arm area image is obtained, the auxiliary arm area image is input into the working condition detection model, so that an auxiliary arm working condition detection result output by the working condition detection model can be quickly and accurately obtained.
Before the auxiliary arm area image is input into the working condition detection model, the working condition detection model can be obtained through training by using the existing neural network training method, and the working condition detection model can be trained specifically through the following steps: firstly, collecting a large number of sample auxiliary arm area images, and determining a sample auxiliary arm working condition detection result through manual marking. And then training the initial model based on the sample auxiliary arm area image and the sample auxiliary arm working condition detection result, thereby obtaining a working condition detection model.
Based on any of the above embodiments, the sample forearm region image includes a 0 ° image of the first forearm, a 15 ° image of the 1 st forearm, a 30 ° image of the first forearm, a 0 ° image of the first and second forearm, a 15 ° image of the first and second forearm, and a 30 ° image of the first and second forearm.
Specifically, in order to enable the working condition detection model to accurately output the working condition detection result of the auxiliary arm, the sample auxiliary arm region image needs to contain the following information: angle information of the fly jib, whether the fly jib one-joint arm and the fly jib two-joint arm are used, and corresponding angle information when the fly jib one-joint arm and the fly jib two-joint arm are used. The method specifically comprises the following steps: the sample forearm area images include a 0 ° angle image of the first forearm, a 15 ° angle image of the 1 st forearm, a 30 ° angle image of the first forearm, 0 ° angle images of the first and second forearm, 15 ° angle images of the first and second forearm, and 30 ° angle images of the first and second forearm.
Based on any of the above embodiments, the controller 120 further includes:
and the parameter acquisition unit is used for acquiring the crane performance parameters under the working condition of the corresponding auxiliary jib based on the working condition detection result of the auxiliary jib.
Specifically, the mapping relationship between the working condition detection result of the fly jib and the corresponding crane performance parameter may be pre-established in the controller 120, so that after the working condition detection result of the fly jib is determined, the parameter obtaining unit may quickly obtain and call the corresponding crane performance parameter (such as the current load of the crane) based on the mapping relationship, and thus may determine the safe operation of the crane based on the crane performance parameter.
Based on any of the above embodiments, the controller 120 is a torque limiter or the controller 120 is communicatively coupled to the torque limiter.
Specifically, the controller 120 may be a torque limiter, that is, a mapping relationship between the working condition detection result of the auxiliary jib and the performance parameter of the corresponding crane is stored in the torque limiter, so that after the working condition detection result of the auxiliary jib is determined, the torque limiter may quickly obtain the performance parameter of the corresponding crane based on the mapping relationship.
The controller 120 may also be in communication connection with the torque limiter, that is, the controller and the torque limiter are two different controllers, and the result sending unit may send the detection result of the working condition of the auxiliary arm to the torque limiter in a wired manner or a wireless manner, so as to receive the corresponding crane performance parameter sent by the torque limiter.
Optionally, the result sending unit may include a wired interface or a wireless interface, and the user may select a sending method according to actual requirements, which is not specifically limited in this embodiment.
In addition, the wired mode includes transmission through a CAN bus, and the wireless mode includes transmission through LoRa.
Specifically, the CAN bus is a serial communication network which effectively supports distributed control or real-time control, and compared with a plurality of distributed control systems constructed by RS-485 based on R lines, the real-time performance of data communication among nodes of the network based on the CAN bus is strong. The Long Range Radio (Long Range Radio) is characterized in that the Long Range Radio is longer than the Long Range Radio in other Radio modes under the same power consumption condition, and low power consumption and Long Range unification are realized.
Based on any of the above embodiments, if the controller 120 is communicatively connected to the torque limiter, the parameter obtaining unit is further configured to:
and sending the detection result of the working condition of the auxiliary arm to the torque limiter so as to receive the crane performance parameters which are sent by the torque limiter and correspond to the working condition of the auxiliary arm.
Specifically, if the controller 120 is in communication connection with the moment limiter, after the detection result of the working condition of the jib is obtained, the parameter obtaining unit is configured to send the detection result of the working condition of the jib to the moment limiter, and if the detection result of the working condition of the jib is sent to the moment limiter in a wired or wireless manner, the moment limiter may determine the crane performance parameter corresponding to the working condition of the jib based on the detection result of the working condition of the jib, and send the crane performance parameter corresponding to the working condition of the jib to the parameter obtaining unit, so as to ensure safe operation of the crane.
According to any of the embodiments, the imaging device is mounted on the main arm head.
Specifically, because the auxiliary boom is required to be free from shielding in the acquired auxiliary boom area image, the camera device can be installed on the main boom head in the embodiment, so that the acquired auxiliary boom area image is free from shielding, the image acquisition efficiency is improved, and the judgment efficiency of the working condition of the auxiliary boom is improved.
Based on any of the above embodiments, the present invention further provides a crane, including: the auxiliary arm working condition detection system of any one of the embodiments.
Specifically, in the prior art, an angle sensor is generally mounted on the auxiliary boom, the angle of the auxiliary boom is detected according to data transmitted back by the angle sensor, a position sensor/proximity switch is mounted on the main boom to determine whether the auxiliary boom is used, a position sensor/proximity switch is mounted between a first-joint arm of the auxiliary boom and a second-joint arm of the auxiliary boom to detect whether the second-joint arm of the auxiliary boom is used, and then the working condition of the auxiliary boom is comprehensively determined according to the above information. Therefore, the number of sensors required to be installed for detecting the working condition of the auxiliary arm in the prior art is large, the circuit is complex, and faults are easy to occur.
However, the crane in this embodiment includes fly jib operating mode detecting system, can acquire the regional image of fly jib through camera device to and the controller is based on regional image accuracy of fly jib and confirm fly jib operating mode testing result fast, compare and need install a large amount of sensors among the traditional approach and lead to the complicated easy trouble that easily breaks down of circuit, this embodiment is simple structure not only, and fly jib operating mode detection efficiency is higher moreover.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. An auxiliary arm working condition detection system is characterized by comprising:
the camera device is connected with the controller;
the camera device is used for acquiring an auxiliary arm area image and inputting the auxiliary arm area image to the controller;
the controller is used for obtaining a working condition detection result of the auxiliary arm based on the auxiliary arm area image.
2. The auxiliary arm operating condition detecting system according to claim 1, wherein the auxiliary arm area image includes a plurality of image frames; the controller comprises an initial detection unit and a detection result judgment unit;
the initial detection unit is used for obtaining an initial working condition detection result corresponding to each image frame based on each image frame; the detection result judging unit is used for determining the auxiliary arm working condition detection result based on the initial working condition detection result corresponding to each image frame.
3. The auxiliary arm working condition detection system according to claim 2, wherein the detection result judgment unit comprises a result statistics module and a result determination module;
the result counting module is used for counting the number of image frames with the same initial working condition detection result, and the result determining module is used for taking the initial working condition detection result corresponding to the maximum number of the image frames as the working condition detection result of the auxiliary arm.
4. The auxiliary arm working condition detection system according to claim 1, wherein the controller is configured to input the auxiliary arm area image into a working condition detection model to obtain the auxiliary arm working condition detection result output by the working condition detection model;
the working condition detection model is obtained by training based on the sample auxiliary arm region image and the sample auxiliary arm working condition detection result.
5. The system according to claim 4, wherein the sample forearm region image includes a 0 ° image of the forearm one-joint, a 15 ° image of the 1-joint, a 30 ° image of the forearm one-joint, a 0 ° image of the forearm one-joint and the two-joint, a 15 ° image of the forearm one-joint and the two-joint, and a 30 ° image of the forearm one-joint and the two-joint.
6. The working condition detection system of an auxiliary arm according to claim 1, wherein the controller further comprises:
and the parameter acquisition unit is used for acquiring the crane performance parameters under the working condition of the corresponding auxiliary jib based on the working condition detection result of the auxiliary jib.
7. The working condition detection system of the auxiliary arm according to claim 6, wherein the controller is a torque limiter or is in communication connection with the torque limiter.
8. The working condition detection system of an auxiliary arm according to claim 7, wherein if the controller is in communication connection with the torque limiter, the parameter obtaining unit is further configured to:
and sending the detection result of the working condition of the auxiliary arm to the torque limiter so as to receive the crane performance parameters under the corresponding working condition of the auxiliary arm sent by the torque limiter.
9. The auxiliary arm operating condition detecting system according to any one of claims 1 to 8, wherein the camera device is mounted to the main arm head.
10. A crane, comprising: the auxiliary arm operating condition detecting system according to any one of claims 1 to 9.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202122057624.5U CN215666701U (en) | 2021-08-27 | 2021-08-27 | Auxiliary arm working condition detection system and crane |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202122057624.5U CN215666701U (en) | 2021-08-27 | 2021-08-27 | Auxiliary arm working condition detection system and crane |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN215666701U true CN215666701U (en) | 2022-01-28 |
Family
ID=79958812
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202122057624.5U Active CN215666701U (en) | 2021-08-27 | 2021-08-27 | Auxiliary arm working condition detection system and crane |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN215666701U (en) |
-
2021
- 2021-08-27 CN CN202122057624.5U patent/CN215666701U/en active Active
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108731788B (en) | Visual detection device and method for low-frequency vibration of aerial work arm | |
| CN107203196B (en) | Industrial equipment detection system and method | |
| CN205158443U (en) | Iron tower structure system of patrolling and examining of power supply line | |
| CN101349919A (en) | Remote video diagnostic method and apparatus of pumping station controlling system fault | |
| CN112526917B (en) | Safety rope hook state detection device and method | |
| CN111879671A (en) | Environment monitoring method and device, electronic equipment and system | |
| CN111951225A (en) | PCB welding abnormity detection method and device and storage medium | |
| CN103713215A (en) | System and method for detecting X-ray tube running state | |
| CN215666701U (en) | Auxiliary arm working condition detection system and crane | |
| CN115576315A (en) | Abnormity inspection method and device of inspection unit and electronic equipment | |
| CN114799573A (en) | Die cutting device and method for lithium battery pole piece | |
| CN116030021A (en) | Automatic detection system for hidden crack characteristics of photovoltaic module | |
| CN114332713B (en) | Construction area operation monitoring method, device and system based on Internet of things | |
| CN205487272U (en) | Display screen fault handling system | |
| CN104104902B (en) | Holder direction fault detection method and device | |
| CN108805890A (en) | A kind of arc hammer measurement method based on power transmission line image characteristic point | |
| US10769767B2 (en) | Monitoring system and its control method | |
| CN109243179B (en) | Method and device for distinguishing dynamic capture frames | |
| CN211124085U (en) | People flow detection device based on image processing | |
| CN106841870B (en) | A kind of abnormal signal auxiliary positioning circuit and method | |
| CN111929042A (en) | Smoke exhaust window fault detection device, system and method based on Internet of things | |
| CN113361358B (en) | Monitoring and fault early warning system for high-voltage overhead line walking plate and guide wheel states | |
| CN115767074A (en) | Camera state detection method and device, vehicle and storage medium | |
| CN116708723B (en) | Camera exception handling method and system | |
| CN113601957A (en) | Screen printing machine system based on PLC control |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| GR01 | Patent grant | ||
| GR01 | Patent grant |