Remote control excavator peripheral personnel safety early warning system

Abstract

The application discloses a kind of remote control excavator peripheral personnel safety early warning system, it is related to remote control excavator safety technical field, including: signal sending module sends waveform signal to around and signal receiving module receives the waveform signal of rebound, install multiple infrared radiation detection modules around the excavator, detect the infrared radiation of the environment around the excavator, and through alarm module, when there is staff close to excavator, selective alarm is carried out, when staff is in dangerous range, warning surrounding staff away from excavator is sent, the position of the person close to is evaluated by dangerousness evaluation module, excavator continues to work when dangerousness is lower, avoid that personnel pass through low-danger area causes operator to dare not continue to operate and influence work efficiency, when there is staff close to high-danger area, emergency brake excavator, guarantee the personal safety of the person close to.

Description

Technical Field

[0001] This invention belongs to the field of remote-controlled excavator safety technology, specifically a safety early warning system for people around a remote-controlled excavator. Background Technology

[0002] Remote-controlled excavators are modified or customized excavators that allow them to operate in hazardous environments and complex terrains. When remotely controlling the excavator, operators only need to send remote control commands via remote control software on a computer or mobile phone to operate the excavator. This not only effectively improves work efficiency but also maximizes the safety of the operators.

[0003] When a remotely controlled excavator is in operation, the operator is far from the machine and there are blind spots. If others approach the excavator while it is working, they are easily injured by the machine, posing a safety hazard. The remotely controlled excavator does not automatically provide warnings when people are approaching, reminding them to leave quickly and alerting the operator. Therefore, this paper proposes a safety warning system for people around a remotely controlled excavator that alerts nearby personnel to leave quickly and reminds the operator to pay attention when operating the machine. Summary of the Invention

[0004] The present invention aims to at least solve one of the technical problems existing in the prior art; to this end, the present invention proposes a safety early warning system for personnel around a remotely controlled excavator. To solve the above-mentioned problem, the present invention adopts the following technical solution.

[0005] A remote-controlled excavator surrounding personnel safety early warning system includes: a data processing unit, and

[0006] Signal transmission module: Multiple signal transmission modules are installed around the excavator to send multiple sets of waveform signals to the surrounding area. The transmitted signals spread outward in a fan shape. The transmitted signals bounce back after being blocked or colliding with the surrounding area.

[0007] Signal receiving module: Multiple signal receiving modules are installed at the positions corresponding to the signal transmitting module. The signal receiving module receives the reflected waveform signal and transmits the received waveform signal to the data processing unit.

[0008] Infrared radiation detection module: Multiple infrared radiation detection modules are installed around the excavator to detect the infrared radiation in the environment around the excavator and convert the infrared radiation into a visible light image.

[0009] The data processing unit performs filtering processing on the waveform signal received by the signal receiving module;

[0010] The infrared radiation detection module transmits the detected infrared radiation data to the data processing unit. Based on the signal detected by the infrared radiation detection module, the temperature information is filtered and analyzed to determine whether the detected temperature is within the range of human body temperature. The unit also analyzes the visible light image to determine whether the infrared radiation is produced by the human body.

[0011] The data processing unit compares the information received by the signal receiving module with the information detected by the infrared radiation detection module, and determines the distance between the surrounding workers and the excavator through waveform signals;

[0012] Alarm module: Selectively alarms when workers approach the excavator, and issues an alarm when workers are within the danger zone to remind surrounding workers to stay away from the excavator.

[0013] As a further aspect of the present invention: the data processing unit includes a data analysis module and a data calculation module.

[0014] The data analysis module trains a deep learning model using a large number of waveform signals and an infrared radiation detection module to train a CNN model, enabling it to learn to extract features from waveform signals and infrared radiation signals. The trained CNN model is then used to extract features from new waveform signals and infrared radiation signals. PCA or other dimensionality reduction methods are then used to reduce the dimensionality of the extracted features to obtain low-dimensional feature vectors. The dimensionality-reduced feature vectors are then used as data to create spider diagrams using matplotlib or other plotting libraries.

[0015] The YOLO target detection model is trained to detect objects in visible light images and determine whether the target is a human body.

[0016] Train a convolutional neural network to learn the correspondence between signals in two spider web images. When a human body is detected in the vicinity, compare the two spider web images. When it is confirmed that the infrared radiation detection module has detected a human body, extract the waveform signal information of the corresponding position.

[0017] The data calculation module calculates the waveform of the selected human body location.

[0018] As a further aspect of the present invention: the data calculation module calculates the distance between the surrounding workers and the excavator based on the data filtered by the data analysis module using the following formula:

[0019] ;

[0020] Where L is the distance between the surrounding workers and the excavator, S is the speed at which the waveform signal emitted by the signal transmitting module travels through the air, and T is the time taken from when the signal transmitting module emits the signal to when the signal receiving module receives the signal.

[0021] As a further aspect of the present invention: it includes,

[0022] Hazard assessment module: The data calculation module transmits the distance data between the workers and the excavator to the hazard assessment module. The hazard assessment module assesses the safety of the surrounding workers based on the excavator's moving speed and the distance between the workers and the excavator.

[0023] As a further aspect of the present invention: the hazard assessment module assesses the safety of the surrounding workers' location using the following formula:

[0024] ;

[0025] Where Q is the safety assessment value of the surrounding staff's location, and V max V represents the maximum horizontal moving speed of the excavator, M is the time it takes for the excavator to move within a safe range (10 seconds), and V is the maximum moving speed of the excavator. max ×M represents the distance the excavator moves within a specified safe time, and K represents the boom length of the excavator.

[0026] As a further aspect of the present invention: when Q≥0, this is a safe distance, and the hazard assessment module will not send a signal to the alarm module;

[0027] when ≤Q≤ When M is 10, the risk level is low. The risk assessment module sends a signal to the alarm module. After receiving the signal, the alarm module sends a low-risk alarm to remind nearby workers to stay away from the excavator and to remind the excavator operator to pay attention.

[0028] As a further aspect of the present invention: when Q < When M is 10, it is considered a high-risk situation. The risk assessment module sends a signal to the alarm module, which then issues a high-risk alarm to remind nearby workers to stay away from the excavator and to alert the excavator operator.

[0029] As a further aspect of the present invention: it includes,

[0030] Control module: The control module is connected to the excavator's emergency fuel switch. The control module controls the opening and closing of the emergency fuel switch based on the assessment results of the hazard assessment module.

[0031] When Q < When M is 10, the hazard assessment module sends a signal to the control module, which then controls the emergency fuel switch to close, forcibly stopping the excavator from operation.

[0032] When the hazard assessment module reassesses and Q> When this happens, the control module will activate the emergency fuel switch again, allowing the excavator operator to restart the excavator for work.

[0033] Compared with the prior art, the beneficial effects of the present invention are:

[0034] The excavator's surrounding environment is monitored. When a worker approaches the excavator, an alarm is triggered to alert both the approaching worker and the operator. The location of the approaching worker is assessed. If the danger is low, the excavator will continue to work to prevent the operator from being hesitant to continue operating the machine due to workers passing through low-risk areas, thus affecting work efficiency. When a worker approaches a high-risk area, the excavator is brought to an emergency stop to ensure the safety of the approaching worker. Attached Figure Description

[0035] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0036] Figure 1 This is a schematic diagram of the system framework of the present invention;

[0037] Figure 2 This is a schematic diagram of the process of the present invention. Detailed Implementation

[0038] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0039] Please see Figure 1 - Figure 2 The first aspect of this invention provides a remote-controlled excavator surrounding personnel safety early warning system, comprising: a data processing unit installed inside the excavator, and...

[0040] Signal transmission module: Multiple signal transmission modules are installed around the excavator to send multiple sets of waveform signals to the surrounding area. The transmitted signals spread outward in a fan shape. The transmitted signals bounce back after being blocked or colliding with the surrounding area. The signal transmission modules are bolted to the outer wall of the excavator and protected by a perforated protective cover to prevent them from being damaged by flying rocks.

[0041] Signal receiving module: Multiple signal receiving modules are installed at positions corresponding to the signal transmitting modules. The signal receiving modules receive the reflected waveform signals and transmit the received waveform signals to the data processing unit. The signal receiving modules are fixed to the outer wall of the excavator in the same way as the signal transmitting modules. They are also protected by perforated protective covers. The signal receiving modules are installed on the upper or lower side of the signal transmitting modules. The number of signal receiving modules is the same as that of the signal transmitting modules, and they are installed in a one-to-one correspondence.

[0042] Infrared radiation detection module: Multiple infrared radiation detection modules are installed around the excavator to detect the infrared radiation in the surrounding environment and convert it into a visible light image. The number of infrared radiation detection modules is the same as the number of signal receiving modules and signal transmitting modules. They are also installed around the outer wall of the excavator and protected by a perforated protective cover. The infrared radiation detection modules can be thermal imagers, which collect and save the infrared radiation signals from the surrounding area.

[0043] The data processing unit performs filtering processing on the waveform signal received by the signal receiving module;

[0044] The infrared radiation detection module transmits the detected infrared radiation data to the data processing unit. Based on the signal detected by the infrared radiation detection module, the temperature information is filtered and analyzed to determine whether the detected temperature is within the range of human body temperature. The unit also analyzes the visible light image to determine whether the infrared radiation is produced by the human body.

[0045] Alarm module: emits alarm sounds and alarm signals to alert nearby personnel to stay away, and at the same time alerts the operator that someone is approaching the excavator.

[0046] Hazard Assessment Module: Assess the hazard of the surrounding workers' location. The data calculation module transmits the distance data between the workers and the excavator to the hazard assessment module, which then assesses the safety of the surrounding workers based on the excavator's moving speed and the distance between the workers and the excavator.

[0047] The hazard assessment module evaluates the safety of the surrounding workers' location using the following formula:

[0048] ;

[0049] Where Q is the safety assessment value of the surrounding staff's location, and V max V represents the maximum horizontal moving speed of the excavator, M represents the time the excavator takes to move within a safe range (this time can be 10 seconds), and V...max ×M represents the distance the excavator travels within a specified safe time, and K represents the excavator's boom length. M can be manually adjusted; in areas where pedestrian traffic is difficult, the value of M can be increased to expand the warning range and give pedestrians more time to move away. When the excavator is working on a sloping surface, V... max ×M can be set to , where a is the maximum acceleration of the excavator as it moves downhill on the slope.

[0050] When Q≥0, this is a safe distance, and the hazard assessment module will not send a signal to the alarm module to trigger the alarm.

[0051] when ≤Q≤ When M is 10, the risk level is low. The risk assessment module sends a signal to the alarm module. After receiving the signal, the alarm module sends a low-risk alarm to remind nearby workers to stay away from the excavator and to remind the excavator operator to pay attention.

[0052] The data processing unit includes a data analysis module and a data calculation module:

[0053] The data analysis module trains a deep learning model using a large number of waveform signals and an infrared radiation detection module to train a CNN model, enabling it to learn to extract features from waveform signals and infrared radiation signals. The trained CNN model is then used to extract features from new waveform signals and infrared radiation signals. PCA or other dimensionality reduction methods are then used to reduce the dimensionality of the extracted features to obtain low-dimensional feature vectors. The dimensionality-reduced feature vectors are then used as data to create spider diagrams using matplotlib or other plotting libraries.

[0054] The YOLO target detection model is trained to detect objects in visible light images and determine whether the target is a human body.

[0055] Train a convolutional neural network to learn the correspondence between signals in two spider web images. When a human body is detected in the vicinity, compare the two spider web images. When it is confirmed that the infrared radiation detection module has detected a human body, extract the waveform signal information of the corresponding position.

[0056] The data calculation module calculates the waveform of the selected human body location.

[0057] The data calculation module calculates the distance between the surrounding workers and the excavator based on the data filtered by the data analysis module using the following formula:

[0058] ;

[0059] Where L is the distance between the surrounding workers and the excavator, S is the speed at which the waveform signal emitted by the signal transmitting module travels through the air, and T is the time taken from when the signal transmitting module emits the signal to when the signal receiving module receives the signal.

[0060] Specifically, in this embodiment, the distance between the excavator and the surrounding workers is determined by the waveform signal reflection combined with the human body information detected by the infrared radiation detection module. When workers approach the excavator or the excavator approaches workers nearby, the alarm module will issue an alarm in time when the distance reaches the danger distance, reminding the workers around the excavator to quickly move away from the excavator. At the same time, it will remind the excavator operator that there are workers in the danger zone around the excavator and that they should pay attention to the operation to ensure the safety of the surrounding workers.

[0061] Where, when Q < When M is 10, it is considered a high-risk situation. The risk assessment module sends a signal to the alarm module, which then issues a high-risk alarm to remind nearby workers to stay away from the excavator and to alert the excavator operator.

[0062] Control module: The control module is connected to the excavator's emergency fuel switch. The control module controls the opening and closing of the emergency fuel switch based on the assessment results of the hazard assessment module.

[0063] When Q < When M is 10, the hazard assessment module sends a signal to the control module, which then controls the emergency fuel switch to close, forcibly stopping the excavator from operation.

[0064] When the hazard assessment module reassesses and Q> When this happens, the control module will activate the emergency fuel switch again, allowing the excavator operator to restart the excavator for work.

[0065] In this embodiment, the safety of the location of the workers around the excavator is assessed by the hazard assessment module. When the location of the workers around the excavator is low-risk, the excavator can continue to work normally, maintain its working state and ensure work efficiency, and will not be affected by the movement of workers. When the location of the workers around the excavator is high-risk, the alarm module will issue a high-risk signal to sound an alarm, and the hazard assessment module will send a signal to the control module, thereby controlling the excavator's emergency fuel switch to shut off, forcing the excavator to stop working and preventing the excavator from continuing to work and threatening the safety of the surrounding workers.

[0066] The above embodiments are only used to illustrate the technical methods of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical methods of the present invention without departing from the spirit and scope of the technical methods of the present invention.

Claims

1. A remote-controlled excavator surrounding personnel safety early warning system, characterized in that, include: Data processing unit, and Signal transmission module: Multiple signal transmission modules are installed around the excavator to send multiple sets of waveform signals to the surrounding area. The transmitted signals spread outward in a fan shape. The transmitted signals bounce back after being blocked or colliding with the surrounding area. Signal receiving module: Multiple signal receiving modules are installed at the positions corresponding to the signal transmitting module. The signal receiving module receives the reflected waveform signal and transmits the received waveform signal to the data processing unit. Infrared radiation detection module: Multiple infrared radiation detection modules are installed around the excavator to detect the infrared radiation in the environment around the excavator and convert the infrared radiation into a visible light image. The data processing unit performs filtering processing on the waveform signal received by the signal receiving module; The infrared radiation detection module transmits the detected infrared radiation data to the data processing unit. Based on the signal detected by the infrared radiation detection module, the temperature information is filtered and analyzed to determine whether the detected temperature is within the range of human body temperature. The unit also analyzes the visible light image to determine whether the infrared radiation is produced by the human body. The data processing unit compares the information received by the signal receiving module with the information detected by the infrared radiation detection module, and determines the distance between the surrounding workers and the excavator through waveform signals; Alarm module: Selectively alarms when workers approach the excavator, and issues an alarm when workers are within the danger zone to warn nearby workers to stay away from the excavator; The data processing unit includes a data analysis module and a data calculation module; The data calculation module calculates the distance between the surrounding workers and the excavator based on the data filtered by the data analysis module using the following formula: ; Where L is the distance between the surrounding workers and the excavator, S is the speed at which the waveform signal emitted by the signal transmitting module travels through the air, and T is the time taken from when the signal transmitting module emits the signal to when the signal receiving module receives the signal. Hazard assessment module: The data calculation module transmits the distance data between the workers and the excavator to the hazard assessment module. The hazard assessment module assesses the safety of the surrounding workers based on the excavator's moving speed and the distance between the workers and the excavator. The hazard assessment module evaluates the safety of the surrounding workers' location using the following formula: ; Where Q is the safety assessment value of the surrounding workers' location, Vmax is the maximum moving speed of the excavator when it is moving horizontally, M is the time it takes for the excavator to move within the safe range, Vmax×M is the distance the excavator moves within the specified safe time, and K is the boom length of the excavator. M can be manually adjusted. When the road is difficult for nearby pedestrians to walk on, the value of M is increased, thus expanding the warning range and giving nearby people more time to move away. When the excavator is working on a sloping surface, Vmax×M is replaced with Vmax×M+. , where a is the maximum acceleration of the excavator as it moves downhill on the slope.

2. The remote-controlled excavator perimeter safety early warning system according to claim 1, characterized in that, The data analysis module trains a deep learning model using a large number of waveform signals and an infrared radiation detection module to train a CNN model, enabling it to learn to extract features from waveform signals and infrared radiation signals. The trained CNN model is then used to extract features from new waveform signals and infrared radiation signals. PCA or other dimensionality reduction methods are then used to reduce the dimensionality of the extracted features to obtain low-dimensional feature vectors. The dimensionality-reduced feature vectors are then used as data to draw spider diagrams using matplotlib or other plotting libraries. The YOLO target detection model is trained to detect objects in visible light images and determine whether the target is a human body. Train a convolutional neural network to learn the correspondence between signals in two spider web images. When a human body is detected in the vicinity, compare the two spider web images. When it is confirmed that the infrared radiation detection module has detected a human body, extract the waveform signal information of the corresponding position. The data calculation module calculates the waveform of the selected human body location.

3. The remote-controlled excavator perimeter safety early warning system according to claim 1, characterized in that, When Q≥0, this is a safe distance, and the hazard assessment module will not send a signal to the alarm module; when When M is 10, the risk level is low. The risk assessment module sends a signal to the alarm module. After receiving the signal, the alarm module sends a low-risk alarm to remind nearby workers to stay away from the excavator and to remind the excavator operator to pay attention.

4. The remote-controlled excavator perimeter safety early warning system according to claim 3, characterized in that, when When M is 10, it is considered a high-risk situation. The risk assessment module sends a signal to the alarm module, which then issues a high-risk alarm to remind nearby workers to stay away from the excavator and to alert the excavator operator.

5. A remote-controlled excavator perimeter safety early warning system according to claim 4, characterized in that, include, Control module: The control module is connected to the excavator's emergency fuel switch. The control module controls the opening and closing of the emergency fuel switch based on the assessment results of the hazard assessment module. when When M is 10, the hazard assessment module sends a signal to the control module, which then controls the emergency fuel switch to close, forcibly stopping the excavator from operation.

6. A remote-controlled excavator perimeter safety early warning system according to claim 5, characterized in that, When the hazard assessment module performs another assessment and When this happens, the control module will activate the emergency fuel switch again, at which point the excavator operator can restart the excavator to resume work.

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