Operation monitoring and early warning method and system for electric shovel

Abstract

The invention discloses an operation monitoring and early warning method and system for an electric shovel, and aims to monitor the operation of the electric shovel in the whole process. An infrared camera is arranged right in front of a cab and close to the lower portion of a lifting arm of a head sheave, and a millimeter-level radar is installed on the top of a machine shed of the cab, so that the whole operation process is monitored, meanwhile, material conditions are comprehensively judged, and when it is recognized that large materials exist on an operation face or blasting difference exists on a step face, the operation face is subjected to blasting. The system sends out early warning information and immediately sends out a shutdown signal to the control system once finding that the electric shovel is too close to the step surface, so that safe operation of the electric shovel is guaranteed.

Description

Technical Field

[0001] The invention relates to an operation monitoring and early warning method and system for an electric shovel, and belongs to the field of mining electric shovel monitoring. Background Art

[0002] With the advancement of technology, video image processing technology is being used more and more widely in all walks of life. Mining electric shovels are the main mining equipment in large open-pit mines. At present, the application of video image processing technology on electric shovels is reflected in two aspects: one is bucket tooth shedding detection, and the other is blind spot monitoring around the equipment and early warning of pedestrians and vehicles entering.

[0003] In actual operation of electric shovels, some dangerous operating behaviors often occur due to the driver's inaccurate judgment of operating conditions, such as collision between the working device and the step surface during rotation operation, forced excavation of materials with poor blasting conditions, and jamming caused by excavation of large pieces of materials. These behaviors will cause irreversible damage to the equipment, leading to premature damage to parts and components, and even causing major safety accidents. After a serious failure of the electric shovel or major equipment damage, it is difficult to fully understand the actual situation at the time of the incident because it happened suddenly or the driver tried to evade responsibility, which is very unfavorable for the cause analysis and responsibility determination of the failure. Summary of the invention

[0004] The purpose of the present invention is to provide an operation monitoring and early warning method and system for an electric shovel, so as to monitor the operation of the electric shovel throughout the whole process. The method arranges an infrared camera in front of the cab and below the crane arm close to the sheave, and installs a millimeter-level radar on the top of the shed of the cab, so as to monitor the operation process throughout the whole process and make a comprehensive judgment on the material conditions. When it is identified that there are large pieces of material on the working surface or the blasting of the step surface is poor, the system sends out an early warning message. Once the electric shovel is found to be too close to the step surface, a stop signal is immediately sent to the control system to ensure the safe operation of the electric shovel.

[0005] In order to achieve the above technical objectives, the present invention will adopt the following technical solutions:

[0006] A method for monitoring and warning an operation of an electric shovel comprises the following steps:

[0007] Step 1: Obtain the distance value L between the working step surface and the electric shovel;

[0008] Step 2: Compare the distance value L with the maximum rotation dimension L of the working device max , and the comparison results show that L <L max When the control system fails, the system goes to step 3; otherwise, the control system sends a first warning signal and a shutdown signal to the control system;

[0009] Step 3: Collect images of the shovel working surface and the shovel bucket:

[0010] Image acquisition is performed on the working surface of the electric shovel and the bucket of the electric shovel to obtain images of the working surface of the electric shovel and the bucket of the electric shovel respectively;

[0011] Step 4: Get the real-time parameters of the motor:

[0012] The real-time parameters of the motor include: increasing the motor current I H , increase the motor voltage U H and the pushing motor current I C , Pushing motor voltage U C ;

[0013] Step 5: Image processing:

[0014] The shovel working surface image and the shovel bucket image collected in step 3 are processed, specifically including:

[0015] The shovel working surface area image and the shovel bucket area image obtained in step 3 are superimposed with the motor real-time parameters obtained in step 4 to obtain and store the first and second video images correspondingly, wherein: the first video image is an image of the shovel working surface that can display the motor real-time parameters, and the second video image is an image of the shovel bucket that can display the motor real-time parameters;

[0016] The electric shovel working surface image obtained in step 3 is subjected to a region segmentation process to extract an image including only the electric shovel working surface, which is recorded as a working surface region image;

[0017] The image of the electric shovel bucket obtained in step 3 is subjected to region limitation processing to extract an image including the electric shovel bucket and a preset area around it, which is recorded as the electric shovel bucket area image;

[0018] Step 6: Identify warnings:

[0019] Perform recognition and early warning processing on the working surface area image obtained in step 5 to determine whether the material size on the working surface of the electric shovel meets the preset requirements, and determine whether to alarm based on the determination result;

[0020] Perform recognition and early warning processing on the image of the electric shovel bucket area obtained in step 5 to determine whether the material size at the excavation point meets the preset requirements, and determine whether to alarm based on the determination result;

[0021] The image of the working surface area obtained in step five is processed for identification and early warning to determine whether the step surface state meets the requirements of the electric shovel excavation operation, and whether to alarm and whether to limit the output power of the current push motor are determined based on the judgment result.

[0022] Preferably, in step six, identification and early warning processing is performed on the work surface area image obtained in step five, which specifically includes the following steps:

[0023] Step 601, performing edge recognition on the work surface area image obtained in step 5, and extracting the maximum diagonal size K of the boundary of each part of the image;

[0024] Step 602, comparing the maximum diagonal dimension K with the maximum material diameter dimension Dmax allowed to be loaded by the electric shovel;

[0025] Step 603: If the judgment result shows that K>Dmax, a second warning message is issued.

[0026] Preferably, in step 6, the image of the electric shovel bucket area obtained in step 5 is subjected to identification and early warning processing, which specifically includes the following steps:

[0027] Step 611, performing edge recognition processing on the shovel bucket area image obtained in step 5, and extracting the maximum diagonal size K-DIPPER of each part of the image boundary;

[0028] Step 612, comparing K-DIPPER with the maximum material diameter Dmax allowed to be loaded by the electric shovel;

[0029] Step 613: If the determination result shows that K-DIPPER>Dmax, a third warning message is issued.

[0030] Preferably, the image of the working surface area obtained in step 5 is subjected to identification and early warning processing, which specifically includes the following steps:

[0031] Step 621, performing edge recognition processing on the work surface area image obtained in step 5;

[0032] Step 622, determining whether there are multiple vertical strip images;

[0033] Step 623: When the judgment result shows that there are multiple vertical strip images, it indicates that the step surface state of the current shovel working surface area is poor, a fourth warning message is issued, and the process goes to step 624;

[0034] Step 624: According to the real-time parameters of the motor obtained in step 4, the output power of the current pushing motor is limited to match the step surface state of the current electric shovel working surface area.

[0035] Preferably, in step one, the distance value L between the working step surface and the electric shovel is obtained by collecting data using a millimeter-level radar; the millimeter-level radar is installed at the front left corner of the top of the shed of the electric shovel cab.

[0036] Preferably, in step 3, the image of the electric shovel working surface is acquired by a first infrared camera, and the image of the electric shovel bucket is acquired by a second infrared camera;

[0037] The first infrared camera is installed in front of the electric shovel cab, and the second infrared camera is installed below the electric shovel boom and close to the crown sheave.

[0038] Another technical purpose of the present invention is to provide an operation monitoring and early warning system for an electric shovel, comprising a data acquisition device and an early warning device, wherein the data acquisition device comprises a first infrared camera, a second infrared camera and a millimeter-level radar; the early warning device comprises a motor parameter extraction module, an image processing module and an identification module; wherein:

[0039] The first infrared camera is installed on the electric shovel and is used to detect an image of a target area including the electric shovel working surface, which is recorded as an electric shovel working surface image; and can transmit the detected electric shovel working surface image to the data processing module;

[0040] The second infrared camera is installed on the electric shovel and is used to detect the image of the target area including the electric shovel bucket, which is recorded as the electric shovel bucket image; and can transmit the detected electric shovel bucket image to the image processing module;

[0041] The millimeter-level radar is installed on the electric shovel, and is used to detect the distance value L between the working step surface and the electric shovel, and can transmit the detected distance value L to the image processing module;

[0042] The motor parameter extraction module is used to capture the real-time parameters of the motor through the control system of the electric shovel. The real-time parameters of the motor include: H , increase the motor voltage U H and the pushing motor current I C , Pushing motor voltage U C ; And can transmit the captured real-time parameters of the motor to the image processing module and the recognition module respectively;

[0043] The image processing module includes three submodules, corresponding to the first to third image processing submodules;

[0044] The first image processing submodule can perform superposition and fusion processing on the received shovel working surface image and shovel bucket image with the motor real-time parameters respectively, so as to generate and store the first and second video images correspondingly, wherein: the first video image is an image of the shovel working surface that can display the motor real-time parameters, and the second video image is an image of the shovel bucket that can display the motor real-time parameters;

[0045] The second image processing submodule can perform region segmentation processing on the received electric shovel working surface image to extract an image including only the electric shovel working surface, which is recorded as the working surface area image; and can transmit the extracted working surface area image to the recognition module;

[0046] The third image processing submodule can perform area limitation processing on the received image of the electric shovel bucket to extract an image including the electric shovel bucket and a preset area around it, which is recorded as the electric shovel bucket area image; and can transmit the extracted electric shovel bucket area image to the recognition module;

[0047] The identification module includes a bulk material identification module, a step surface state identification module and a bucket material identification module;

[0048] The bulk material recognition module can perform recognition and early warning processing on the received working surface area image to determine whether the material size of the current electric shovel working surface meets the preset requirements, and determine whether to alarm according to the judgment result;

[0049] The bucket material recognition module can perform recognition and early warning processing on the received shovel bucket area image to determine whether the material size at the excavation point meets the preset requirements, and determine whether to alarm according to the determination result;

[0050] The step surface state recognition module can identify and warn the received working surface area image to determine whether the step surface state meets the requirements of the electric shovel excavation operation, and determine whether to alarm and whether to limit the output power of the current pushing motor based on the judgment result.

[0051] Preferably, the first infrared camera is installed in front of the electric shovel cab.

[0052] Preferably, the second infrared camera is installed below the lifting arm of the electric shovel and is arranged close to the crown sheave.

[0053] Preferably, the millimeter-level radar is installed at the left front corner of the top of the shed of the electric shovel cab.

[0054] Based on the above technical objectives, the present invention has the following advantages over the prior art:

[0055] The present invention arranges infrared cameras in front of the cab and below the crane arm sheave, and installs a millimeter-level radar on the top of the shed. While monitoring the entire operation process, it makes a comprehensive judgment on the material conditions. When it is identified that there are large pieces of material on the working surface or poor blasting on the step surface, the system issues a warning message. Once it is found that the electric shovel is too close to the step surface, a shutdown signal is immediately sent to the control system to ensure the safe operation of the electric shovel.

[0056] Advantages of the present invention:

[0057] 1. The video recording files are superimposed to display the real-time parameters of the lifting motor current, voltage and the pushing motor current, voltage, which can clearly determine the driver's operating behavior at the time, which is very helpful for the analysis of the cause of the fault and the determination of responsibility for major accidents.

[0058] 2. Monitor and warn the operation process of the electric shovel to reduce the risk of accidents and the probability of failure, which is beneficial to mine safety production. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 It is a structural schematic diagram of the operation monitoring and early warning system of the electric shovel according to the present invention;

[0060] Figure 2 yes Figure 1 A top view of

[0061] Figure 3 It is a flow chart of the operation monitoring and early warning method of the electric shovel described in the present invention.

[0062] In the figure: 1-electric shovel cab; 2-millimeter-level radar; 3-first infrared camera; 4-electric shovel lifting arm; 5-second infrared camera; 6-sky wheel; 7-electric shovel bucket. DETAILED DESCRIPTION

[0063] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. The following description of at least one exemplary embodiment is actually only illustrative and is by no means any limitation to the present invention and its application or use. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention. Unless otherwise specified, the relative arrangement, expressions and numerical values ​​of the components and steps described in these embodiments do not limit the scope of the present invention. The techniques, methods and equipment known to ordinary technicians in the relevant fields may not be discussed in detail, but in appropriate cases, the techniques, methods and equipment should be regarded as part of the specification. In all examples shown and discussed here, any specific value should be interpreted as merely exemplary, rather than as a limitation. Therefore, other examples of the exemplary embodiments may have different values.

[0064] For ease of description, spatially relative terms such as "above", "above", "on the upper surface of", "above", etc. may be used here to describe the spatial positional relationship between a device or feature and other devices or features as shown in the figure. It should be understood that spatially relative terms are intended to include different orientations of the device in use or operation in addition to the orientation described in the figure. For example, if the device in the accompanying drawings is inverted, the device described as "above other devices or structures" or "above other devices or structures" will be positioned as "below other devices or structures" or "below other devices or structures". Thus, the exemplary term "above" can include both "above" and "below". The device can also be positioned in other different ways (rotated 90 degrees or in other orientations).

[0065] Example 1

[0066] like Figure 1 , Figure 2 As shown, this embodiment discloses an operation monitoring and early warning system for an electric shovel, including a data acquisition device and an early warning device, wherein the data acquisition device includes a first infrared camera 3, a second infrared camera 5 and a millimeter-level radar 2; the early warning device includes a motor parameter extraction module, an image processing module, and a recognition module; wherein:

[0067] The first infrared camera 3 is installed on the electric shovel and is used to detect the target area image including the electric shovel working surface, which is recorded as the electric shovel working surface image; and can transmit the detected electric shovel working surface image to the data processing module; in the accompanying drawings, the first infrared camera 3 is installed directly in front of the electric shovel cab 1.

[0068] The second infrared camera 5 is installed on the electric shovel and is used to detect the image of the target area including the electric shovel bucket 7, which is recorded as the image at the electric shovel bucket; and can transmit the detected image at the electric shovel bucket to the image processing module; in the accompanying drawings, the second infrared camera 5 is installed below the electric shovel lifting arm 4 and is set close to the crown wheel 6.

[0069] The millimeter-level radar 2 is installed on the electric shovel, and is used to detect the distance value L between the working step surface and the electric shovel, and can transmit the detected distance value L to the image processing module; in the accompanying drawing, the millimeter-level radar 2 is installed at the left front corner of the top of the shed of the electric shovel cab 1.

[0070] The motor parameter extraction module is used to capture the real-time parameters of the motor through the control system of the electric shovel. The real-time parameters of the motor include: H , increase the motor voltage U H and the pushing motor current I C , Pushing motor voltage U C; and can transmit the captured motor real-time parameters to the image processing module and the recognition module respectively. In common electric shovels, the control system generally adopts a PLC controller.

[0071] The image processing module includes three submodules, corresponding to the first to third image processing submodules;

[0072] The first image processing submodule can perform superposition and fusion processing on the received shovel working surface image and shovel bucket image with the motor real-time parameters, so as to generate and store the first and second video images correspondingly, wherein: the first video image is the shovel working surface image that can display the motor real-time parameters, and the second video image is the shovel bucket image that can display the motor real-time parameters. It can be seen that this embodiment can obtain the key real-time parameters such as voltage and current of the lifting motor and the pushing motor from the shovel PLC, and display them synchronously in the video screen, so as to obtain a video record file for event review and cause analysis.

[0073] The second image processing submodule can perform region segmentation processing on the received electric shovel working surface image to extract an image including only the electric shovel working surface, which is recorded as the working surface area image; and can transmit the extracted working surface area image to the recognition module;

[0074] The third image processing submodule can perform area limitation processing on the received electric shovel bucket image to extract an image including the electric shovel bucket 7 and a preset area around it, which is recorded as an electric shovel bucket area image; and can transmit the extracted electric shovel bucket area image to the recognition module;

[0075] The identification module includes a bulk material identification module, a step surface status identification module and a bucket material identification module; this embodiment uses the bulk material identification module, the step surface status identification module and the bucket material identification module to identify the video image and perform all-round monitoring and early warning of the operation of the electric shovel.

[0076] Specifically, the bulk material recognition module can perform recognition and early warning processing on the received working surface area image to determine whether the material size of the current electric shovel working surface meets the preset requirements, and determine whether to alarm according to the judgment result;

[0077] The bucket material recognition module can perform recognition and early warning processing on the received shovel bucket area image to determine whether the material size at the excavation point meets the preset requirements, and determine whether to alarm according to the determination result;

[0078] The step surface state recognition module can identify and warn the received working surface area image to determine whether the step surface state meets the requirements of the electric shovel excavation operation, and determine whether to alarm and whether to limit the output power of the current pushing motor based on the judgment result.

[0079] In this embodiment, the specific process of data acquisition and image preprocessing is:

[0080] (1) The first infrared camera 3 installed above the shovel cab 1 collects images of the shovel working surface, and the second infrared camera 5 installed below the shovel boom 4 and the shovel bucket 6 collects images of the shovel.

[0081] (2) Obtaining the boost motor current I H , voltage U H and the pushing motor current I C , voltage U C Real-time parameters are used to pre-process the collected images of the shovel working surface and the shovel bucket.

[0082] (3) Generate a first video image and a second video image that overlay and display the real-time parameters of the motor, and archive them.

[0083] In this embodiment, the specific process of determining the step surface distance is:

[0084] (1) Obtain the distance L between the working step surface and the electric shovel detected by two groups of millimeter-level radars;

[0085] (2) Compare L with the maximum rotation dimension Lmax of the working device;

[0086] (3) If L<Lmax, a warning message is issued that "the electric shovel is too close to the step surface and there is a risk of collision", and a stop signal is sent to the control system.

[0087] In this embodiment, the specific process of image processing and recognition is:

[0088] (1) The first infrared camera 3 above the shovel cab 1 collects the shovel working surface image, and performs regional segmentation processing, which is divided into two parts: the equipment body area and the working surface area. Subsequent processing and recognition are only for the working surface area.

[0089] (2) The second infrared camera 5 under the shovel arm 4 sheave 6 collects the shovel working surface image and performs area limitation processing. The subsequent processing and recognition are only for the shovel bucket 7 and the images within a certain area around it (for example, the shovel bucket 7 and the area within 3 meters around it) as the processing object.

[0090] In this embodiment, the specific process of the bulk material identification module is:

[0091] (1) performing edge recognition on the work surface area image processed in step 2, and extracting the maximum diagonal size K of the boundary of each part of the image;

[0092] (2) Compare K with the maximum material diameter Dmax allowed to be loaded by the shovel;

[0093] (3) If K>Dmax, a warning message is issued indicating that “large pieces of material exceeding the allowable loading size exist on the working surface”.

[0094] In this embodiment, the specific process of the bucket material identification module is:

[0095] (1) During the process of excavating materials with an electric shovel, edge recognition processing is performed on the bucket area image processed in step 2, and the maximum diagonal size K-DIPPER of the boundary of each part of the image is extracted;

[0096] (2) Compare the maximum material diameter Dmax allowed to be loaded by K-DIPPER and electric shovel;

[0097] (3) If K-DIPPER>Dmax, a warning message is issued: "There is a large piece of material exceeding the allowable loading size at the excavation point, please do not load it."

[0098] In this embodiment, the specific process of the step surface state recognition module is:

[0099] (1) performing edge recognition on the work surface area image processed in step 2;

[0100] (2) determining whether there are multiple vertical strip images;

[0101] (3) If a strip image exists, a warning message is issued stating that “the blasting situation on the step surface is poor, please do not force excavation.”

[0102] (4) To increase the motor current I H , voltage U H and the pushing motor current I C , voltage U C The real-time parameters are monitored and a signal is sent to the control system to limit the output power of the push motor, prevent the electric shovel bucket 7 from being inserted too deeply into the material, and avoid forced excavation.

[0103] Example 2

[0104] This embodiment discloses a method for monitoring and warning the operation of an electric shovel, such as Figure 3 As shown, the following steps are included:

[0105] Step 1, obtain the distance value L between the working step surface and the electric shovel; the distance value L between the working step surface and the electric shovel is obtained by collecting the millimeter-level radar 2; the millimeter-level radar 2 is installed at the left front corner of the top of the shed of the electric shovel cab 1.

[0106] Step 2: Determine the step distance: Compare the distance value L with the maximum rotation size L of the working device max , and the comparison results show that L <L max When the electric shovel is too close to the step surface, the process goes to step three. Otherwise, a first warning signal is sent through the control system, and a stop signal is sent to the control system. The first warning signal may be: the electric shovel is too close to the step surface and there may be a risk of collision.

[0107] Step 3: Collect images of the shovel working surface and the shovel bucket:

[0108] Image acquisition is performed on the shovel working surface and the shovel bucket at 7 locations to obtain images of the shovel working surface and the shovel bucket accordingly;

[0109] Specifically, in this step, the image of the electric shovel working surface is acquired by the first infrared camera 3, and the image of the electric shovel bucket is acquired by the second infrared camera 5; the first infrared camera 3 is installed in front of the electric shovel cab 1, and the second infrared camera 5 is installed below the electric shovel lifting arm 4 and is set close to the sheave 6.

[0110] Step 4: Get the real-time parameters of the motor:

[0111] The real-time parameters of the motor include: increasing the motor current I H , increase the motor voltage U H and the pushing motor current I C , Pushing motor voltage U C ;

[0112] In this step, the real-time parameters of the motor are obtained from the electric shovel PLC controller.

[0113] Step 5: Image processing:

[0114] The shovel working surface image and the shovel bucket image collected in step 3 are processed, specifically including:

[0115] The shovel working surface area image and the shovel bucket area image obtained in step 3 are superimposed with the motor real-time parameters obtained in step 4 to obtain and store the first and second video images correspondingly, wherein: the first video image is an image of the shovel working surface that can display the motor real-time parameters, and the second video image is an image of the shovel bucket that can display the motor real-time parameters;

[0116] The electric shovel working surface image obtained in step 3 is subjected to a region segmentation process to extract an image including only the electric shovel working surface, which is recorded as a working surface region image;

[0117] The image of the electric shovel bucket obtained in step 3 is subjected to region limitation processing to extract an image including the electric shovel bucket and a preset area around it, which is recorded as the electric shovel bucket area image;

[0118] Step 6: Identify warnings:

[0119] The image of the working surface area obtained in step 5 is processed for recognition and early warning to determine whether the material size of the working surface of the electric shovel meets the preset requirements, and whether to alarm is determined according to the determination result; specifically, the following steps are included:

[0120] Step 601, performing edge recognition on the work surface area image obtained in step 5, and extracting the maximum diagonal size K of the boundary of each part of the image;

[0121] Step 602, comparing the maximum diagonal dimension K with the maximum material diameter dimension Dmax allowed to be loaded by the electric shovel;

[0122] Step 603: If the determination result indicates that K>Dmax, a second warning message is issued. The second warning message may be: there are large pieces of material exceeding the allowable loading size on the working surface.

[0123] The image of the shovel bucket area obtained in step 5 is processed for recognition and early warning to determine whether the material size at the excavation point meets the preset requirements, and whether to alarm is determined according to the determination result; specifically, the following steps are included:

[0124] Step 611, performing edge recognition processing on the shovel bucket area image obtained in step 5, and extracting the maximum diagonal size K-DIPPER of each part of the image boundary;

[0125] Step 612, comparing K-DIPPER with the maximum material diameter Dmax allowed to be loaded by the electric shovel;

[0126] Step 613: If the determination result shows that K-DIPPER>Dmax, a third warning message is issued. The third warning message may be: there is a large piece of material exceeding the allowable loading size at the excavation point, please do not load it.

[0127] The image of the working surface area obtained in step 5 is processed for identification and early warning to determine whether the step surface state meets the requirements of the electric shovel excavation operation, and whether to alarm and whether to limit the output power of the current push motor are determined according to the judgment result. The specific steps include the following:

[0128] Step 621, performing edge recognition processing on the work surface area image obtained in step 5;

[0129] Step 622, determining whether there are multiple vertical strip images;

[0130] Step 623: When the judgment result shows that there are multiple vertical strip images, it indicates that the step surface condition of the current electric shovel working surface area is poor, a fourth warning message is issued, and the process proceeds to step 624; the fourth warning message may be: the step surface blasting condition is poor, please do not force excavation.

[0131] Step 624: According to the real-time parameters of the motor obtained in step 4, the output power of the current pushing motor is limited to match the step surface state of the current electric shovel working surface area.

Claims

1. A method for monitoring and early warning of electric shovel operation, characterized in that: The steps include: Step 1: Obtain the distance value L between the working step surface and the electric shovel; Step 2: Compare the distance value L with the maximum rotation dimension L of the working device max , and the comparison results show that L <L max When the control system fails, the system goes to step 3; otherwise, the control system sends a first warning signal and a shutdown signal to the control system; Step 3: Collect images of the shovel working surface and the shovel bucket: Image acquisition is performed on the working surface of the electric shovel and the bucket of the electric shovel to obtain images of the working surface of the electric shovel and the bucket of the electric shovel respectively; Step 4: Get the real-time parameters of the motor: The real-time parameters of the motor include: increasing the motor current I H , increase the motor voltage U H and the pushing motor current I C , Pushing motor voltage U C ; Step 5: Image processing: The shovel working surface image and the shovel bucket image collected in step 3 are processed, specifically including: The shovel working surface area image and the shovel bucket area image obtained in step 3 are superimposed with the motor real-time parameters obtained in step 4 to obtain and store the first and second video images correspondingly, wherein: the first video image is an image of the shovel working surface that can display the motor real-time parameters, and the second video image is an image of the shovel bucket that can display the motor real-time parameters; The electric shovel working surface image obtained in step 3 is subjected to a region segmentation process to extract an image including only the electric shovel working surface, which is recorded as a working surface region image; The image of the electric shovel bucket obtained in step 3 is subjected to region limitation processing to extract an image including the electric shovel bucket and a preset area around it, which is recorded as the electric shovel bucket area image; Step 6: Identify warnings: Perform recognition and early warning processing on the working surface area image obtained in step 5 to determine whether the material size on the working surface of the electric shovel meets the preset requirements, and determine whether to alarm based on the determination result; Perform recognition and early warning processing on the image of the electric shovel bucket area obtained in step 5 to determine whether the material size at the excavation point meets the preset requirements, and determine whether to alarm based on the determination result; The image of the working surface area obtained in step five is processed for identification and early warning to determine whether the step surface state meets the requirements of the electric shovel excavation operation, and whether to alarm and whether to limit the output power of the current push motor are determined based on the judgment result.

2. The method for monitoring and early warning of electric shovel operation according to claim 1, characterized in that: In step 6, the image of the working surface area obtained in step 5 is subjected to recognition and early warning processing, which specifically includes the following steps: Step 601, performing edge recognition on the work surface area image obtained in step 5, and extracting the maximum diagonal size K of the boundary of each part of the image; Step 602, comparing the maximum diagonal dimension K with the maximum material diameter dimension Dmax allowed to be loaded by the electric shovel; Step 603: If the judgment result shows that K>Dmax, a second warning message is issued.

3. The method for monitoring and early warning of electric shovel operation according to claim 1, characterized in that: In step 6, the image of the shovel bucket area obtained in step 5 is identified and early-warning processed, which specifically includes the following steps: Step 611, performing edge recognition processing on the shovel bucket area image obtained in step 5, and extracting the maximum diagonal size K-DIPPER of each part of the image boundary; Step 612, comparing K-DIPPER with the maximum material diameter Dmax allowed to be loaded by the electric shovel; Step 613: If the determination result shows that K-DIPPER>Dmax, a third warning message is issued.

4. The method for monitoring and early warning of electric shovel operation according to claim 1, characterized in that: In step 6, the image of the working surface area obtained in step 5 is subjected to recognition and early warning processing, which specifically includes the following steps: Step 621, performing edge recognition processing on the work surface area image obtained in step 5; Step 622, determining whether there are multiple vertical strip images; Step 623: When the judgment result shows that there are multiple vertical strip images, it indicates that the step surface state of the current shovel working surface area is poor, a fourth warning message is issued, and the process goes to step 624; Step 624: According to the real-time parameters of the motor obtained in step 4, the output power of the current pushing motor is limited to match the step surface state of the current electric shovel working surface area.

5. The method for monitoring and early warning of electric shovel operation according to claim 1, characterized in that: In step 1, the distance value L between the working step surface and the electric shovel is obtained by collecting the millimeter-level radar; the millimeter-level radar is installed at the left front corner of the top of the shed of the electric shovel cab.

6. The method for monitoring and early warning of electric shovel operation according to claim 1, characterized in that: In step 3, the image of the electric shovel working surface is acquired by the first infrared camera, and the image of the electric shovel bucket is acquired by the second infrared camera; The first infrared camera is installed in front of the electric shovel cab, and the second infrared camera is installed below the electric shovel boom and close to the crown sheave.

7. An operation monitoring and early warning system for an electric shovel, characterized in that: It includes a data acquisition device and an early warning device, wherein the data acquisition device includes a first infrared camera, a second infrared camera and a millimeter-level radar; the early warning device includes a motor parameter extraction module, an image processing module and a recognition module; wherein: The first infrared camera is installed on the electric shovel and is used to detect an image of a target area including the electric shovel working surface, which is recorded as an electric shovel working surface image; and can transmit the detected electric shovel working surface image to the data processing module; The second infrared camera is installed on the electric shovel and is used to detect the image of the target area including the electric shovel bucket, which is recorded as the electric shovel bucket image; and can transmit the detected electric shovel bucket image to the image processing module; The millimeter-level radar is installed on the electric shovel, and is used to detect the distance value L between the working step surface and the electric shovel, and can transmit the detected distance value L to the image processing module; The motor parameter extraction module is used to capture the real-time parameters of the motor through the control system of the electric shovel. The real-time parameters of the motor include: H , increase the motor voltage U H and the pushing motor current I C , Pushing motor voltage U C ; And can transmit the captured real-time parameters of the motor to the image processing module and the recognition module respectively; The image processing module includes three submodules, corresponding to the first to third image processing submodules; The first image processing submodule can perform superposition and fusion processing on the received shovel working surface image and shovel bucket image with the motor real-time parameters respectively, so as to generate and store the first and second video images correspondingly, wherein: the first video image is an image of the shovel working surface that can display the motor real-time parameters, and the second video image is an image of the shovel bucket that can display the motor real-time parameters; The second image processing submodule can perform region segmentation processing on the received electric shovel working surface image to extract an image including only the electric shovel working surface, which is recorded as the working surface area image; and can transmit the extracted working surface area image to the recognition module; The third image processing submodule can perform area limitation processing on the received image of the electric shovel bucket to extract an image including the electric shovel bucket and a preset area around it, which is recorded as the electric shovel bucket area image; and can transmit the extracted electric shovel bucket area image to the recognition module; The identification module includes a bulk material identification module, a step surface state identification module and a bucket material identification module; The bulk material recognition module can perform recognition and early warning processing on the received working surface area image to determine whether the material size of the current electric shovel working surface meets the preset requirements, and determine whether to alarm according to the judgment result; The bucket material recognition module can perform recognition and early warning processing on the received shovel bucket area image to determine whether the material size at the excavation point meets the preset requirements, and determine whether to alarm according to the determination result; The step surface state recognition module can identify and warn the received working surface area image to determine whether the step surface state meets the requirements of the electric shovel excavation operation, and determine whether to alarm and whether to limit the output power of the current pushing motor based on the judgment result.

8. The operation monitoring and early warning system for an electric shovel according to claim 7, characterized in that: The first infrared camera is installed in front of the electric shovel cab.

9. The operation monitoring and early warning system for an electric shovel according to claim 7, characterized in that: The second infrared camera is installed below the lifting arm of the electric shovel and is arranged close to the head sheave.

10. The operation monitoring and early warning system for an electric shovel according to claim 7, characterized in that: The millimeter-level radar is installed on the left front corner of the top of the shed of the electric shovel cab.

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