JP7447373B2 - Crane monitoring device and method and overhead crane - Google Patents

Description

The present invention relates to a crane monitoring device and method for monitoring a person involved in an overhead crane, and an overhead crane equipped with the crane monitoring device.

For example, in factories, warehouses, etc., overhead cranes are often used to move heavy objects. In such an overhead crane, when the suspended load is raised or lowered, the suspended load may shake and pose a danger to workers. In particular, the suspended load shakes greatly during so-called ground cutting, which poses a great danger. Therefore, a system for avoiding such a danger has been proposed, and is disclosed in Patent Document 1, for example.

The crane suspended load monitoring system disclosed in Patent Document 1 uses a camera installed at a position where the crane can photograph the suspended load, and detects the presence of people in dangerous areas around the suspended load based on the image data of the camera. The device is equipped with a calculation device that determines whether or not the suspended load is present by image analysis, and outputs at least one of an alarm signal and an emergency stop signal when it is determined that a person is present in a dangerous area around the suspended load. The arithmetic device is configured in . Paragraph [0024] of Patent Document 1 states, ``Furthermore, in the next step S3, the moving objects extracted from the background are identified by their respective unique shape patterns, etc. A dangerous area is set around the suspended load 8 in the next step S4, and it is determined in the next step S5 whether or not there is a person in the set dangerous area. ”.

JP 2020-7134 Publication

By the way, in order to accurately determine the safety of a person to be monitored, such as a worker, it is necessary to accurately measure the distance between the suspended load and the person. Since there are various shapes and sizes of suspended loads, it is necessary to recognize the shape and size of the suspended loads in order to accurately measure the distance. In the crane suspended load monitoring system disclosed in Patent Document 1, as described above, moving objects extracted from the background are distinguished into a suspended load 8 and a person (ground worker 9) based on their unique shape patterns, etc. A dangerous area is set around the suspended load 8, and the crane suspended load monitoring system disclosed in Patent Document 1 does not recognize the shape or size of the suspended load.

The present invention was made in view of the above-mentioned circumstances, and its purpose is to provide a crane monitoring device and crane that can recognize the shape of a suspended load and more accurately measure the distance between the suspended load and a subject. An object of the present invention is to provide a monitoring method and an overhead crane equipped with the crane monitoring device.

As a result of various studies, the present inventors have found that the above object can be achieved by the following present invention. That is, the crane monitoring device according to one aspect of the present invention is a device for monitoring a person involved in an overhead crane, which is equipped with an elevating cart that has a movable gutter and suspends a hook such that it can be raised and lowered. and a suspended load detection unit that detects the shape of the suspended load, a target person detection unit that detects the shape of the target person and the target person, and a suspended load detected by the suspended load detection unit and the target person detection unit. a distance processing section that calculates a minimum distance between the detected subject based on the shape of the suspended load detected by the suspended load detection section and the shape of the subject detected by the subject detection section; and a warning processing section that notifies the outside of a warning when the obtained minimum interval is less than or equal to a predetermined threshold, and the hanging load detection section specifies the hook and detects a predetermined range including the specified hook. A detection area is set, and the suspended load and the shape of the suspended load are detected within the set detection area.

Such a crane monitoring device detects a suspended load by setting a detection area including the hook. Since the suspended load is a load hung on a hook, the crane monitoring device can more accurately detect the suspended load even if there is a load that is not a suspended load within the detection range of the suspended load detection section. Since the crane monitoring device described above also detects the shape of the suspended load, which can be detected more accurately, the minimum distance between the suspended load and the subject can be determined more accurately. Therefore, the crane monitoring device can recognize the shape of the suspended load and more accurately measure the distance between the suspended load and the subject.

In the above-mentioned crane monitoring device, the suspended load detection unit is disposed at the end of the gutter so that the detection direction faces the hook side, and the first point generates three-dimensional point group data in the detection direction. a group data generation unit; and a first detection processing unit that detects the suspended load and the shape of the suspended load based on the three-dimensional point cloud data generated by the first point cloud data generation unit, a second point cloud data generation section that is disposed at an end of the gutter so as to face the detection direction toward the hook, and that generates three-dimensional point cloud data in the detection direction; a second detection processing section that detects the subject and the shape of the subject based on the three-dimensional point cloud data generated by the generation section, the first point cloud data generation section and the second point cloud data generation section; The parts may be separate or integrated. Furthermore , in the crane monitoring device described above, from the viewpoint of covering each other's blind spots, the first point cloud data generation unit is configured to generate a set of two points 1A and 1B provided at both ends of the gutter. The first detection processing unit includes a group data generation unit, and the first detection processing unit detects the suspended load and the shape of the suspended load based on each three-dimensional point cloud data generated by the first A and first B point cloud data generation units, respectively. The second point cloud data generation section includes a set of two 2A and 2B point cloud data generation sections disposed at each end of the gutter, and the second detection processing section includes: The shapes of the subject and the subject are detected based on each three-dimensional point cloud data generated by the second A and second B point cloud data generation units.

In such a crane monitoring device, the suspended load detection unit and the target person detection unit each generate three-dimensional point cloud data representing the shape of the object surface, so it is easy to detect the suspended load and the target person from the three-dimensional point cloud data. can. The hook moves in a plane perpendicular to the lifting direction by movement of the gutter relative to the traveling rail and movement of the lifting cart relative to the gutter. Therefore, it is presumed that the vibration of the gutter is smaller than the vibration of the lifting truck. In the above-mentioned crane monitoring device, since the suspended load detection section and the subject detection section are respectively disposed on the gutter, the influence of vibration on each detection of the suspended load detection section and the subject detection section can be reduced more than in the case of an elevating cart. In addition, since it is easier for the operator to access (approach) the gutter than the elevating cart, the crane monitoring device allows easier maintenance of the suspended load detection section and the subject detection section.

In the crane monitoring device described above , the suspended load detection section is arranged at the end of the gutter so that the detection direction faces the hook side, and the point cloud data that generates three-dimensional point cloud data in the detection direction. a generation unit; and a first detection processing unit that detects the suspended load and the shape of the suspended load based on the three-dimensional point cloud data generated by the point cloud data generation unit; an imaging section that is disposed at the end of the gutter so as to face the imaging direction toward the hook and generates an image in the imaging direction; and a shape of the subject and the subject based on the image generated by the imaging section. and a second detection processing section that detects. Furthermore , in the crane monitoring device described above, from the viewpoint of covering each other's blind spots, the point cloud data generation section generates a set of A and B point cloud data arranged at each end of the gutter. the first detection processing unit detects the suspended load and the shape of the suspended load based on each three-dimensional point cloud data generated by the A-th and B-th point cloud data generation units, respectively; The imaging section includes a set of two A-th and B-th imaging sections disposed at each end of the gutter, and the second detection processing section is configured to perform a process on each of the A-th and B-th imaging sections. The subject and the shape of the subject are detected based on each generated image.

Such a crane monitoring device preferentially uses the point cloud data generation section for the suspended load detection section that detects the shape, and uses the imaging section for the subject detection section, so that the point cloud data generation section with uneven resolution can be used preferentially. Even in this case, the suspended load and its shape can be accurately detected by the point cloud data generation section, and the subjects scattered around the suspended load can be detected by the imaging section.

In another aspect, these above-described crane monitoring devices further include a start/end control section that controls the start of the monitoring and the end of the monitoring.

Such a crane monitoring device can automate the start and end of monitoring.

In another aspect, the crane monitoring device described above further includes a stop processing unit that stops the operation of the overhead crane when the minimum interval determined by the interval processing unit is less than or equal to a predetermined second threshold. Be prepared.

Since such a crane monitoring device further includes a stop processing section, it is possible to avoid problems caused by the operation of the overhead crane.

A crane monitoring method according to one aspect of the present invention is a crane monitoring method for monitoring a target person involved in an overhead crane that has a movable girder that extends in one direction and is equipped with an elevating truck that suspends a hook such that it can be raised and lowered. a hanging load detection step of detecting a hanging load and the shape of the hanging load; a target person detection step of detecting the target person and the shape of the target person; and a hanging load detected in the hanging load detection step and the target. a distance processing step of determining a minimum distance between the person and the person detected in the person detection step based on the shape of the hanging load detected in the hanging load detection step and the shape of the person detected in the person detection step; and a warning processing step of notifying a warning to the outside when the minimum interval determined in the spacing processing step is less than or equal to a predetermined threshold, and the hanging load detection step identifies the hook, and the hanging load detection step includes: A detection area of a predetermined range including the detection area is set, and the hanging load and the shape of the hanging load are detected within the set detection area , and the hanging load detection step includes detecting the hanging load so that the detection direction is toward the hook side. detecting the suspended load and the shape of the suspended load based on three-dimensional point cloud data generated by a first point cloud data generation unit disposed at the end and generating three-dimensional point cloud data in the detection direction; The target person detection step is performed using a second point cloud data generation unit that is disposed at the end of the gutter so as to face the detection direction toward the hook side, and generates three-dimensional point cloud data in the detection direction. The subject and the shape of the subject are detected based on dimensional point cloud data, and the first point cloud data generation unit and the second point cloud data generation unit are separate or integrated. , the first point cloud data generation section includes two sets of 1A and 1B point cloud data generation sections disposed at both ends of the gutter, and the suspended load detection step includes The suspended load and the shape of the suspended load are detected based on each three-dimensional point cloud data generated by the 1A and 1B point cloud data generation units, and the second point cloud data generation unit detects the shape of the suspended load, A set of two 2A and 2B point cloud data generation units are provided, and the target person detection step includes a set of 2A and 2B point cloud data generation units disposed respectively, and the target person detection step includes each of the three-dimensional data generated by the 2A and 2B point cloud data generation units, respectively. The subject and the shape of the subject are detected based on point cloud data . A crane monitoring method according to one aspect of the present invention is a crane monitoring method for monitoring a target person involved in an overhead crane that has a movable girder that extends in one direction and is equipped with an elevating truck that suspends a hook such that it can be raised and lowered. a hanging load detection step of detecting a hanging load and the shape of the hanging load; a target person detection step of detecting the target person and the shape of the target person; and a hanging load detected in the hanging load detection step and the target. a distance processing step of determining a minimum distance between the person and the person detected in the person detection step based on the shape of the hanging load detected in the hanging load detection step and the shape of the person detected in the person detection step; and a warning processing step of notifying a warning to the outside when the minimum interval determined in the spacing processing step is less than or equal to a predetermined threshold, and the hanging load detection step identifies the hook, and the hanging load detection step includes: A detection area of a predetermined range including the detection area is set, and the hanging load and the shape of the hanging load are detected within the set detection area, and the hanging load detection step includes detecting the hanging load so that the detection direction is toward the hook side. The suspended load and the shape of the suspended load are detected based on the three-dimensional point cloud data generated by a point cloud data generation unit that is disposed at the end and generates three-dimensional point cloud data in the detection direction, and the suspended load and the shape of the suspended load are detected. The person detection step includes detecting the target person and the target person based on an image generated by an imaging unit that is disposed at the end of the gutter so as to face the hook side in the imaging direction, and generates an image in the imaging direction. Detecting the shape, the point cloud data generating section includes a pair of A-th and B-th point group data generating sections disposed at each end of the gutter, and the suspended load detecting step includes: The suspended load and the shape of the suspended load are detected based on each three-dimensional point cloud data generated by the A-th and B-th point cloud data generation units, and the imaging unit is disposed at each end of the gutter. The target person detection step includes a set of two A-th and B-th imaging units, and the target person detection step detects the target person and the target person based on each image generated by the A-th and B-th imaging units, respectively. Detect the shape of .

Such a crane monitoring method detects a suspended load by setting a detection area including the hook. Since a suspended load is a load hung on a hook, the crane monitoring method described above can more accurately detect a suspended load even if there is a load that is not a suspended load within the detection range of the suspended load detection step. Since the crane monitoring method described above also detects the shape of the suspended load, which can be detected more accurately, the minimum distance between the suspended load and the subject can be determined more accurately. Therefore, the crane monitoring method described above can recognize the shape of the suspended load and more accurately measure the distance between the suspended load and the subject.

An overhead crane according to another aspect of the present invention includes any of the crane monitoring devices described above.

According to this, an overhead crane equipped with any one of the crane monitoring devices described above can be provided. Since such an overhead crane is equipped with any of the crane monitoring devices described above, it is possible to recognize the shape of the suspended load and more accurately measure the distance between the suspended load and the subject.

The crane monitoring device and crane monitoring method according to the present invention can recognize the shape of a suspended load and more accurately measure the distance between the suspended load and the subject. According to the present invention, an overhead crane equipped with such a crane monitoring device can be provided.

It is a block diagram showing the composition of the crane monitoring device in a 1st embodiment. FIG. 2 is a schematic diagram showing the configuration of an overhead crane monitored by the crane monitoring device of the first embodiment. FIG. 2 is a diagram for explaining an example of three-dimensional point group data, a method of detecting a suspended load and a subject, and a method of calculating a minimum interval. 3 is a flowchart showing the operation of the crane monitoring device. It is a block diagram showing the composition of the crane monitoring device in a 2nd embodiment. It is a schematic diagram which shows the structure of the overhead crane monitored by the crane monitoring apparatus of the said 2nd Embodiment. FIG. 6 is a diagram for explaining a process of combining the detection result of the suspended load detection unit and the detection result of the subject detection unit in the second embodiment. It is a block diagram showing the composition of the crane monitoring device in a 3rd embodiment. It is a schematic diagram which shows the structure of the overhead crane monitored by the crane monitoring apparatus of the said 3rd Embodiment. FIG. 7 is a diagram for explaining a first calculation form for detecting the position of a hook in the third embodiment. FIG. 7 is a diagram for explaining a second calculation form for detecting the position of a hook in the third embodiment. It is a block diagram showing the composition of the crane monitoring device in a 4th embodiment. It is a schematic diagram which shows the structure of the overhead crane monitored by the crane monitoring apparatus of the said 4th Embodiment.

Hereinafter, one or more embodiments of the present invention will be described with reference to the drawings. However, the scope of the invention is not limited to the disclosed embodiments. It should be noted that structures with the same reference numerals in each figure indicate the same structure, and the description thereof will be omitted as appropriate. In this specification, when referring to a general term, a reference numeral without a subscript is used, and when referring to an individual configuration, a reference numeral with a suffix is used.

The crane monitoring device according to the embodiment is a device that monitors a person involved in an overhead crane that is configured to have movable girders and includes a lifting cart that suspends a hook such that it can be raised and lowered. This crane monitoring device includes a suspended load detection section that detects a suspended load and the shape of the suspended load, a subject detection section that detects the subject and the shape of the subject, and a suspended load detected by the suspended load detection section. Interval processing for determining the minimum distance between the load and the target person detected by the target person detection unit based on the shape of the suspended load detected by the suspended load detection unit and the shape of the target person detected by the target person detection unit and a warning processing section that notifies the outside of a warning when the minimum interval determined by the interval processing section is less than or equal to a predetermined threshold. In the present embodiment, the hanging load detection unit identifies the hook, sets a detection area of a predetermined range including the identified hook, and detects the hanging load and the hanging load within the set detection area. Detect shapes. Hereinafter, the first to fourth embodiments will be described in more detail, taking as an example an overhead crane equipped with this crane monitoring device.

(First embodiment)
FIG. 1 is a block diagram showing the configuration of a crane monitoring device in a first embodiment. FIG. 2 is a schematic diagram showing the configuration of an overhead crane monitored by the crane monitoring device of the first embodiment. FIG. 2A is a top view and FIG. 2B is a side view. FIG. 3 is a diagram for explaining an example of three-dimensional point cloud data, a method of detecting a suspended load and a subject, and a method of calculating a minimum interval. FIG. 3A is a diagram for explaining an example of three-dimensional point cloud data and a method for detecting a hanging load and a subject, and FIG. 3B is a diagram for explaining a method for calculating the minimum interval.

The crane monitoring device according to the first embodiment is a device that monitors a person involved in an overhead crane that is configured to have a movable girder and includes an elevating cart that suspends a hook such that it can be raised and lowered. The target persons include, for example, a worker who handles a load suspended by the overhead crane, a worker who operates the overhead crane, and the like. For example, as shown in FIG. 2, the overhead crane CRa includes a pair of first and second traveling rails RL-1 and RL-2, a gutter GT, and a lifting truck LT.

The first and second traveling rails RL-1 and RL-2 are arranged so as to extend in one direction (first direction, Y direction), respectively, on both side walls of a building such as a factory or warehouse. It is a rod-shaped member that guides the first and second wheels of the vehicle.

The gutter GT is a member that guides and supports the elevating cart LT, and for example, the gutter GT is a member that is spaced apart in the one direction so as to extend in a direction (second direction, X direction) orthogonal to the one direction (first direction). a pair of first and second main girders that are rod-shaped members arranged in the same direction; first and second connecting members that connect the first and second main girders at both ends thereof; First and second wheels rotatably attached to each of the two connecting members and guided by the first and second traveling rails RL-1 and RL-2, for example, the first and second wheels are driven synchronously. A first drive unit such as a motor, and a rod-shaped third wheel disposed on the first and second main girders to extend in the second direction and guide third and fourth wheels (described later) of the lifting truck LT. 3 and 4 travel rails.

The lifting trolley LT suspends the hook HK so as to be able to rise and fall along the one direction (first direction) and the direction (third direction, Z direction) orthogonal to the second direction, and This is a device that is guided by the fourth running rail. The lifting truck LT includes third and fourth wheels that are rotatably attached and guided by the third and fourth traveling rails, and a second wheel such as a motor that drives the third and fourth wheels in synchronization. It includes a drive section, a wire rope attached to the hook HK, a wire winder that winds up the wire rope, and a third drive section such as a motor that drives the wire winder.

In the overhead crane CR, an operation pendant HP for operating the overhead crane CR is attached to the lifting truck LT via a cable CV. The operation pendant HP includes a north button that moves the Gata GT (hook HK) in one of the first directions (north direction), and a south button that moves the Gata GT (hook HK) in the other direction (south direction). , an eastward button that moves the elevating cart LT (hook HK) in one of the second directions (eastward direction), a westward button that moves the elevating cart LT (hook HK) in the other direction (westward) of the second direction, and a hook. A rise button that moves the hook HK in one of the third directions (upward), and a drop button that moves the hook HK in the other direction (downward) of the third direction. When the operator (user) operates (for example, presses) the north button, the first drive unit rotates the first and second wheels in the normal direction, thereby moving the Gata GT in the north direction. As a result, the hook HK moves northward. When the operator (user) stops operating the north button (for example, by stopping the pressing), this northward movement is stopped. When the operator (user) operates (for example, presses) the south button, the first and second wheels are reversed by the first drive unit, thereby moving the Gata GT in the south direction, and accordingly Hook HK moves south. This southward movement is stopped when the operator (user) stops operating the southward button (for example, by stopping the pressing). When the operator (user) operates (for example, presses) the east button, the third and fourth wheels are rotated in the normal direction by the second drive unit, thereby moving the elevating trolley LT in the east direction. Hook HK moves eastward. When the operator (user) stops operating the eastward button (for example, by stopping the pressing), this eastward movement is stopped. When the operator (user) operates (for example, presses) the westward button, the third and fourth wheels are reversed by the second drive unit, thereby moving the lifting trolley LT in the westward direction. Accordingly, the hook HK moves westward. When the operator (user) stops operating the westward button (for example, by stopping the pressing), this westward movement is stopped. When the operator (user) operates (for example, presses) the lift button, the wire winding machine is rotated in the forward direction by the third drive unit, thereby lifting the hook HK. This raising is stopped when the operator (user) stops operating the raise button (for example, by ceasing to press the button). When the operator (user) operates (for example presses) the lowering button, the third drive causes the wire winder to be reversed, thereby lowering the hook HK. This lowering is stopped when the operator (user) stops operating the lowering button (for example, by ceasing said push).

For example, as shown in FIG. 1, the crane monitoring device D includes first and second imaging units 1-1, 1-2, a control processing unit 2, an input unit 3, an output unit 4, and an interface unit ( IF unit) 5 and a storage unit 6.

The crane monitoring device Da in the first embodiment includes, for example, as shown in FIG. 1, a suspended load detection section 1a, a subject detection section 2a, a control processing section 3a, an input section 4, an output section 5, It includes an interface section (IF section) 6 and a storage section 7.

The suspended load detection unit 1a is a device that is connected to the control processing unit 3a by wire or wirelessly, and detects a suspended load and the shape of the suspended load under the control of the control processing unit 3a. More specifically, in the present embodiment, the suspended load detection unit 1a includes a first point cloud data generation unit 11a that generates three-dimensional point cloud data in the detection direction, and a first point cloud data generation unit 11a that generates three-dimensional point cloud data in the detection direction. The first detection processing unit 12a detects the suspended load and the shape of the suspended load based on three-dimensional point group data. As shown in FIG. 2B, the first point group data generation unit 11a is disposed on the lifting truck LT so as to face the detection direction toward the hook so as to be able to detect the hanging load PK hung on the hook HK. In this embodiment, the first point group data generation section 11a is disposed at the lower part of the lifting truck LT so that its detection direction is parallel to the third direction (Z direction). Note that the first point group data generation unit 11a may be disposed at the lower part of the elevating trolley LT so that the detection direction is oblique (so as to intersect with the third direction). The three-dimensional point group data is three-dimensional coordinates of each point on the surface of an object existing in the detection direction, and is usually expressed as coordinate values (x, y, z) of an XYZ orthogonal coordinate system. Therefore, the presence or absence of an object and the shape of the object can be recognized using the three-dimensional point group data. Examples of devices that generate such three-dimensional point cloud data include LiDAR (Light Detection and Ranging), stereo cameras, and TOF (Time of Flight) cameras (TOF sensors). LiDAR may have a biased resolution, for example, the resolution in the central region of the detection range is relatively high and the resolution in the surrounding region relatively low, or it may have a relatively uniform resolution with no bias in the detection range. There is something. As the former LiDAR, for example, Velodyne Lidar inc. Examples include VLP-32MR manufactured by the company. This VLP-32MR has a detection range of 360° in the horizontal direction and 40° in the vertical direction (+15° to -25°) using 32 TOF laser sensors, and the resolution in the central area is relatively high in the surrounding area. resolution is relatively low. Examples of the latter LiDAR include YVT-35LX-FO manufactured by Hokuyo Electric Co., Ltd. This YVT-35LX-FO has a detection range of 210° horizontally and 40° vertically (+35° to -5°) by scanning pulsed laser light, and has a resolution of approximately 2590 points. There is no bias and the resolution is approximately uniform. The first point cloud data generation unit 11a may be configured to include, for example, any one of LiDAR, a stereo camera, and a TOF camera, and in this embodiment, it is configured to include LiDAR. For example, point group data RSa shown in FIG. 3A is generated by the first point group data generation unit 11a, and the coordinate values of each point are stored in the storage unit 7. In this embodiment, the first detection processing section 12a (32a) is functionally configured in the control processing section 3a, and the first detection processing section 12a (32a) will be described later.

The subject detection unit 2a is a device that is connected to the control processing unit 3a by wire or wirelessly, and detects the subject and the shape of the subject under the control of the control processing unit 3a. More specifically, in the present embodiment, the subject detection unit 2a includes a second point cloud data generation unit 21a that generates three-dimensional point cloud data in the detection direction, and a second point cloud data generation unit 21a that generates three-dimensional point cloud data in the detection direction. The second detection processing unit 22a detects the subject and the shape of the subject based on three-dimensional point cloud data. Like the first point cloud data generating section 11a, the second point cloud data generating section 21a sets the detection direction to the hook HK side, as shown in FIG. 2B, so that the hanging load PK hung on the hook HK can be detected. It is arranged on the elevating trolley LT so that it faces the same direction. In this embodiment, the second detection processing section 22a (33a) is functionally configured in the control processing section 3a, and the second detection processing section 22a (33a) will be described later.

The first point cloud data generation section 11a of the hanging load detection section 1a and the second point cloud data generation section 21a of the subject detection section 2a may be separate bodies, but in this embodiment, they are used together. It is one thing. That is, the first point cloud data generation section 11a of the suspended load detection section 1a and the second point cloud data generation section 21a of the subject detection section 2a are configured to include, for example, one LiDAR.

The input unit 4 is connected to the control processing unit 3a, and outputs various commands such as a command to start monitoring, and a predetermined threshold value (first threshold value) for determining whether a warning is necessary or not to the crane monitoring device Da. This is a device that inputs various data necessary for operation to the crane monitoring device Da, and is, for example, a plurality of input switches assigned with predetermined functions. The output unit 5 is a device that is connected to the control processing unit 3a and outputs commands, data, warnings, etc. input from the input unit 4 under the control of the control processing unit 3a, and is, for example, a CRT display, a liquid crystal display, and an organic EL display. These include a display device that displays information such as a display, and a sound output device that outputs sound such as a speaker or a buzzer.

The IF section 6 is a circuit that is connected to the control processing section 3a and performs input/output of data with an external device under the control of the control processing section 3a, and is, for example, an interface circuit for RS-232C, which is a serial communication method. , and an interface circuit using the USB (Universal Serial Bus) standard. Further, the IF section 6 is a circuit that performs communication with an external device, and may be, for example, a data communication card, a communication interface circuit according to the IEEE802.11 standard, or the like.

The storage section 7 is a circuit that is connected to the control processing section 3a and stores various predetermined programs and various predetermined data under the control of the control processing section 3a. The various predetermined programs include, for example, a control processing program, and the control processing program controls each section 1a, 2a, 4 to 7 of the crane monitoring device Da according to the function of each section, A control program that controls the start of monitoring and the end of the monitoring, a first detection processing program that detects the suspended load and the shape of the suspended load based on the three-dimensional point cloud data generated by the first point cloud data generation section 11a; , a second detection processing program that detects the subject and the shape of the subject based on the three-dimensional point cloud data generated by the second point cloud data generation unit 21a, and a hanging load detected by the first detection processing program and the Interval processing that calculates the minimum distance between the object and the subject detected by the second detection processing program based on the shape of the hanging load detected by the first detection processing program and the shape of the subject detected by the second detection processing program. A warning processing program that notifies the outside of a warning when the minimum interval determined by the interval processing program is less than or equal to a predetermined threshold value is included. The various kinds of predetermined data include data necessary for executing each of these programs, such as the threshold value and the detection area (shape and size). Such a storage unit 7 includes, for example, a ROM (Read Only Memory) that is a nonvolatile storage element, an EEPROM (Electrically Erasable Programmable Read Only Memory) that is a rewritable nonvolatile storage element, and the like. The storage unit 7 includes a RAM (Random Access Memory), which serves as a so-called working memory of the control processing unit 3a that stores data generated during execution of the predetermined program.

The control processing section 3a is a circuit for controlling each section 1a, 2a, 4 to 7 of the crane monitoring device Da according to the function of each section, and monitoring a target person related to the overhead crane CRa. The control processing unit 3a includes, for example, a CPU (Central Processing Unit) and its peripheral circuits. By executing the control processing program, the control processing section 3a includes a control section 31, a first detection processing section 32a (12a), a second detection processing section 33a (22a), an interval processing section 34a, and a warning processing section. 35 is functionally configured.

The control section 31 controls each section 1a, 2a, 4 to 7 of the crane monitoring device Da according to the function of each section, and controls the entire crane monitoring device Da.

In this embodiment, the control unit 31 controls the start of monitoring and the end of the monitoring. Normally, when working with an overhead crane, in order to ensure safety, the worker (target person) performs work such as slinging a load with the power of the operating pendant HP turned off, and then With the power turned on, operate the buttons for driving the overhead crane, such as the up button and north button on the operation pendant. After the overhead crane is driven (after moving to a predetermined position), the suspended load is lowered using the lowering button, and the operator stops operating the button that is being operated in order to remove the suspended load from the hook. Therefore, the control unit 31 monitors the operation pendant HP, starts monitoring when the operation pendant HP is powered on, and ends the monitoring when the operation pendant HP is powered off. Alternatively, for example, since the load applied to the hook changes depending on the presence or absence of a suspended load, a load sensor for measuring the load on the hook HK is provided on the hook HK, and the control unit 31 controls the load on the hook HK measured by the load sensor. Monitoring is started when the load exceeds a preset start determination threshold, and ends when the load of the hook HK measured by the load sensor falls below a preset end determination threshold. The start determination threshold and the end determination threshold may be the same value or may be different values. In the case of the different value, from the viewpoint of safety, the start determination threshold is preferably smaller than the end determination threshold.

The first detection processing unit 32a (12a) detects the suspended load and the shape of the suspended load based on the three-dimensional point cloud data generated by the first point cloud data generation unit 11a. In this embodiment, the first detection processing unit 32a identifies the hook, sets a detection area in a predetermined range including the identified hook, and detects the shape of the suspended load and the suspended load within the set detection area. Detect. More specifically, the first point cloud data generation section 11a is disposed on the lifting trolley LT that suspends the hook so as to be able to rise and fall, so that the detection direction faces toward the hook. The position X0 of the hook HK in the three-dimensional point group data generated in step 11a is known in advance. Therefore, the position X0 of the hook HK in the three-dimensional point group data is stored in advance in the storage unit 7 as one of the various data. For example, as shown in FIG. 3A, the first detection processing unit 32a detects the hook at the position X0 of the hook HK stored in the storage unit 7 in the three-dimensional point cloud data RSa generated by the first point cloud data generation unit 11a. The hook HK is specified, and a detection area SA of a predetermined range including the specified hook HK is set. For example, a rectangular (prismatic) detection area SA indicated by a broken line is set such that the intersection of diagonals of the detection area SA coincides with the position X0 of the hook HK. Then, the first detection processing unit 32a detects, as a suspended load PK, a point group having a height (Z coordinate value) greater than or equal to a preset suspended load determination threshold within this detection area SA, and detects the point group as a suspended load PK. As shown, the contour PP is determined as the shape PP of the suspended load PK from this detected point group. The shape and size of the detection area SA and the suspended load determination threshold are each appropriately set in advance by considering, for example, the intended use of the overhead crane CRa. Note that the shape of the detection area SA is not limited to a rectangular shape (prismatic shape), and may be arbitrary, for example, a circular shape (cylindrical shape).

The second detection processing unit 33a (22a) detects the target based on the three-dimensional point cloud data generated by the second point cloud data generation unit 21a (the first point cloud data generation unit 11a as it is also used in this embodiment). This is to detect the person and the shape of the subject. Various person detection techniques for detecting people from three-dimensional point cloud data have been developed, and for example, the well-known PointPillars, VoxelNet, Vote3Deep, etc. that use deep learning models can be used. The second detection processing unit 33a (22a) detects the target person Ob from the three-dimensional point cloud data generated by the first point cloud data generation unit 11a using one of these person detection techniques, for example PointPillars, From this detected point group of the target person Ob, its outline is determined as the shape of the target person Ob. In the example shown in FIG. 3A, three first to third subjects Oba, Obb, and Obc are detected around the hanging load PK, and as shown in FIG. 3B, these first to third subjects Oba, The shapes POa, POb, and POc of Obb and Obc are obtained.

The interval processing section 34a calculates the minimum distance between the hanging load detected by the first detection processing section 32a (12a) and the subject detected by the second detection processing section 33a (22a). ) and the shape of the subject detected by the second detection processing section 33a (22a). More specifically, the interval processing unit 34a calculates the outline shape PP of the suspended load PK for each subject Ob extracted by the second detection processing unit 33a, as viewed from the suspended load PK detected by the first detection processing unit 32a. and the contour shape PO of the subject Ob are determined, and the smallest (shortest) interval among the determined intervals is determined as the minimum interval. For example, as shown in FIG. 3B, the interval processing unit 34a stores the hanging loads detected by the first detection processing unit 32a for each of the first to third subjects Oba, Obb, and Obc extracted by the second detection processing unit 33a. Obtain the interval SD between the outline shape PP of the hanging load PK and the outline shape PO of the subject Ob when viewed from the PK, and calculate the smallest (shortest) interval SDc among the determined intervals SDa, SDb, and SDc. It is determined as the minimum interval (SDc<SDb<SDa). Note that when only one subject Ob is extracted by the second detection processing unit 33a, the interval between this one subject Ob and the suspended load PK becomes the minimum interval.

The warning processing unit 35 is configured to issue a warning to the outside via the output unit 5 when the minimum interval determined by the interval processing unit 34a is less than or equal to a predetermined threshold (first threshold). The threshold value is appropriately set, for example, to 1 m, 2 m, etc. in consideration of safety and the like. For example, the output unit 5 is a sound output device, and the warning processing unit 35 notifies the outside of the warning by outputting a warning sound such as a siren sound or a buzzer sound from the sound output device. Alternatively, for example, the output unit 5 is a display device, and the warning processing unit 35 displays a warning message such as “This is dangerous. Please stay away from the suspended load” on the display device. Notify the outside of the warning. Note that the output unit 5 may be a light emitting device such as a revolving patrol light, and the warning processing unit 35 may notify the outside of the warning by causing the light emitting device to emit light. Moreover, these may be combined.

In the present embodiment, the threshold value can be input by an operator (user) from the input unit 4, but it may also be set in advance by a designer and stored in the storage unit 7.

These control processing unit 3a, input unit 4, output unit 5, IF unit 6, and storage unit 7 can be configured by, for example, a desktop computer, a notebook computer, or the like. Further, the control processing section 3a, the input section 4, the output section 5, the IF section 6, and the storage section 7 may be constituted by, for example, a board type or one-chip type computer, and may be mounted on the lifting trolley LT.

Next, the operation of this embodiment will be explained. FIG. 4 is a flowchart showing the operation of the crane monitoring device.

When the crane monitoring device Da having such a configuration is turned on, it initializes the necessary parts and starts operating. The control processing section 3a includes a control section 31, a first detection processing section 32a (12a), a second detection processing section 33a (22a), an interval processing section 34a, and a warning processing section 35 by executing the control processing program. It is composed of Here, it is assumed that the threshold value is input by the operator (user) from the input unit 4 and is stored in the storage unit 7.

In FIG. 4, the crane monitoring device Da determines whether monitoring is to be started by the control unit 31 of the control processing unit 3a (S1). As described above, this determination is performed based on the operation status of the operation pendant HP and the load on the hook HK. As a result of this determination, if monitoring has not started (No), the control unit 31 returns the process to process S1. On the other hand, if the result of the determination is that monitoring is to be started (Yes), the control processing unit 3a next executes processing S2. Therefore, the control processing unit 3a repeatedly executes the process S1 until it is determined that monitoring is to start.

In this process S2, the crane monitoring device Da uses the control processing unit 3a to acquire each three-dimensional point cloud data generated by the first and second point cloud data generation units 11a and 21a. In the present embodiment, the control processing section 3a acquires the three-dimensional point cloud data generated by the first point cloud data generation section 11a, since the control processing section 3a is used in combination as described above.

Next, the crane monitoring device Da uses the first detection processing unit 32a (12a) of the control processing unit 3a to detect the suspended load PK and its shape based on the three-dimensional point cloud data generated by the first point cloud data generation unit 11a. PP is detected, and the second detection processing unit 33a (22a) of the control processing unit 3a generates three-dimensional point cloud data (in this embodiment, the first point cloud data generation unit 11a) generated by the second point cloud data generation unit 21a. The subject Ob and its shape PO are detected based on the three-dimensional point cloud data (generated in ).

Next, the crane monitoring device Da uses the distance processing unit 34a of the control processing unit 3a to determine the minimum distance between the suspended load detected by the first detection processing unit 32a and the subject detected by the second detection processing unit 33a. It is determined based on the shape of the hanging load detected by the first detection processing section 32a and the shape of the subject detected by the second detection processing section 33a (S4).

Next, the crane monitoring device Da determines whether or not a warning is necessary by the warning processing unit 35 of the control processing unit 3a (S5). In this embodiment, the warning processing unit 35 determines whether a warning is necessary by determining whether the minimum interval determined by the interval processing unit 34a is less than or equal to a predetermined threshold. As a result of this determination, if the first period minimum interval is less than or equal to the predetermined threshold value, the warning processing unit 35 determines that a warning is necessary (Yes), and notifies the outside of the warning by the output unit 5 (S6). , Next, process S7 is executed. On the other hand, if the result of the determination is that the first-period minimum interval is not less than or equal to the predetermined threshold, the warning processing unit 35 determines that a warning is unnecessary (No), and then executes processing S7.

In this process S7, the crane monitoring device Da determines whether or not the monitoring is finished by the control unit 31 of the control processing unit 3a. As described above, this determination is performed based on the operation status of the operation pendant HP and the load on the hook HK. If the result of this determination is that the monitoring has not ended (No), the control unit 31 returns the process to process S2. Therefore, during monitoring, each process from process S2 to process S7 is repeatedly executed. On the other hand, if the result of the determination is that the monitoring has ended (Yes), the control processing unit 3a ends this process.

As described above, the crane monitoring device Da, the crane monitoring method implemented therein, and the overhead crane CRa in the first embodiment detect the suspended load PK by setting the detection area SA including the hook. Since the suspended load PK is a load hung on a hook, the crane monitoring device Da, the crane monitoring method, and the overhead crane CRa detect whether there is a load other than the suspended load PK within the detection range of the suspended load detector 1a. The suspended load PK can also be detected more accurately. The above-mentioned crane monitoring device Da, crane monitoring method, and overhead crane CRa can also detect the shape of the suspended load PK, which can be detected more accurately, so that the minimum distance between the suspended load PK and the subject Ob can be determined more accurately. can. Therefore, the crane monitoring device Da, the crane monitoring method, and the overhead crane CRa can recognize the shape of the suspended load and more accurately measure the distance between the suspended load PK and the subject Ob.

The above crane monitoring device Da, crane monitoring method, and overhead crane CRa each generate three-dimensional point cloud data representing the shape of the object surface, so that the suspended load detection unit 1a and the subject detection unit 2a each generate three-dimensional point cloud data. The hanging load PK and the subject Ob can be easily detected. The crane monitoring device Da, the crane monitoring method, and the overhead crane CRa have the hanging load detection unit 1a and the subject detection unit 2a each disposed on the lifting trolley LT that suspends the hook HK in a manner that allows the hook HK to be raised and lowered. Easy to specify and set detection area SA. The suspended load detection unit 1a and the subject detection unit 2a detect the suspended load PK and the subject Ob from approximately directly above, respectively, so that the shadow area is reduced, so that the crane monitoring device Da and the crane The monitoring method as well as the overhead crane CRa can more accurately determine the minimum spacing.

The above crane monitoring device Da, crane monitoring method, and overhead crane CRa can automate the start and end of monitoring.

Next, another embodiment will be described.
(Second embodiment)
Although the suspended load detection unit 1a and the subject detection unit 2a in the overhead crane CRa and the crane monitoring device Da in the first embodiment are configured to include LiDAR that generates three-dimensional point cloud data of objects within the detection range, As mentioned above, LiDAR includes devices with biased resolution and devices without bias. For example, in the example shown in FIG. 3A, the resolution in the central region of the detection range is relatively high and the resolution in the surrounding region is relatively low. For this reason, the suspended load PK is mostly detectable since it is present in the central region. On the other hand, in the example shown in FIG. 3A, the target person Ob (Oba, Obb, Obc) such as a worker also exists relatively near the central area and can be detected. However, if the target person Ob exists in the peripheral area, Hard to detect. Therefore, in the overhead crane CRb and the crane monitoring device Db in the second embodiment, the suspended load detection section 1b is configured to include a point cloud data generation section that generates three-dimensional point cloud data, as in the first embodiment. On the other hand, the subject detection section 2b is configured to include an imaging section that generates an image of the subject in the detection range in order to more reliably detect the subject Ob over the entire detection range.

FIG. 5 is a block diagram showing the configuration of a crane monitoring device in the second embodiment. FIG. 6 is a schematic diagram showing the configuration of an overhead crane monitored by the crane monitoring device of the second embodiment. FIG. 6A is a top view and FIG. 6B is a side view. FIG. 7 is a diagram for explaining a process of combining the detection result of the suspended load detection unit and the detection result of the subject detection unit in the second embodiment. FIG. 7A shows the detection result of the subject detection section, FIG. 7B shows the detection result of the hanging load detection section, and FIG. 7C shows the result of combining these.

As shown in FIG. 6, the overhead crane CRb equipped with the crane monitoring device Db in the second embodiment is equipped with the crane monitoring device Db in the second embodiment instead of the crane monitoring device Da in the first embodiment. This is the same as the overhead crane CRa in the first embodiment. That is, as shown in FIG. 6, for example, the overhead crane CRb includes a pair of first and second traveling rails RL-1 and RL-2, a gutter GT, and a lifting truck LT. Since these are the same as in the case of the overhead crane CRa, the explanation thereof will be omitted.

The crane monitoring device Db in the second embodiment includes, for example, as shown in FIG. 5, a suspended load detection section 1b, a subject detection section 2b, a control processing section 3b, an input section 4, an output section 5, It includes an interface section (IF section) 6 and a storage section 7. The input section 4, the output section 5, the IF section 6, and the storage section 7 in the crane monitoring device Db of the second embodiment are respectively the input section 4, the output section 5, the IF section in the crane monitoring device Da of the first embodiment. 6 and storage unit 7, so the explanation thereof will be omitted.

The suspended load detection unit 1b is a device that is connected to the control processing unit 3b by wire or wirelessly, and detects the suspended load and the shape of the suspended load under the control of the control processing unit 3b. More specifically, the hanging load detection unit 1b includes a point cloud data generation unit 11b that generates three-dimensional point cloud data in the detection direction, and a hanging load detection unit 1b based on the three-dimensional point cloud data generated by the point cloud data generation unit 11b. It includes a first detection processing section 12b that detects the shape of the load and the suspended load. The point cloud data generation section 11b and the first detection processing section 12b in the suspended load detection section 1b are respectively the first point cloud data generation section 11a and the first detection processing section 12a in the suspended load detection section 1a of the first embodiment. Since it is the same as that, the explanation thereof will be omitted.

The subject detection unit 2b is a device that is connected to the control processing unit 3b by wire or wirelessly, and detects the subject and the shape of the subject under the control of the control processing unit 3b. More specifically, in the second embodiment, the subject detection unit 2b detects the subject and the shape of the subject based on the imaging unit 21b that generates an image in the imaging direction and the image generated by the imaging unit 21b. and a second detection processing section 22b. The imaging unit 21b includes, for example, an imaging optical system that forms an optical image of a subject on a predetermined imaging plane, is arranged with a light-receiving surface aligned with the imaging plane, and converts the optical image of the subject into an electrical system. The digital camera is equipped with an image sensor that converts the image sensor into a signal, and an image processing section that generates image data representing an image of the subject by performing image processing on the output of the image sensor. As shown in FIG. 6B, the imaging unit 21b is disposed on the lifting truck LT so as to face the imaging direction toward the hook so as to be able to monitor the subject Ob related to the overhead crane CRb. In this embodiment, the imaging unit 21b is disposed at the lower part of the lifting truck LT so that its imaging direction is parallel to the third direction (Z direction). Therefore, the imaging section 21b is arranged in parallel to the point cloud data generating section 11b (first point cloud data generating section 11a). Note that the imaging unit 21b may be disposed at the lower part of the lifting truck LT so that the imaging direction is oblique (so as to intersect with the third direction). In this embodiment, the second detection processing section 22b (33b) is functionally configured in the control processing section 3b, and the second detection processing section 22b (33b) will be described later.

The control processing section 3b is a circuit for controlling each section 1b, 2b, 4 to 7 of the crane monitoring device Db according to the function of each section, and monitoring a target person related to the overhead crane CRb. The control processing unit 3b includes, for example, a CPU and its peripheral circuits. By executing the control processing program, the control processing section 3b includes a control section 31, a first detection processing section 32b (12b), a second detection processing section 33b (22b), an interval processing section 34b, and a warning processing section. 35 is functionally configured. The control unit 31, the first detection processing unit 32b (12b), and the warning processing unit 35 in the control processing unit 3b of the second embodiment are the control unit 31, the first detection processing unit 32, and the first detection processing unit 35 in the control processing unit 3a of the first embodiment, respectively. Since it is the same as the processing section 32a (12a) and the warning processing section 35, the explanation thereof will be omitted.

The second detection processing section 33b (22b) detects the subject and the shape of the subject based on the image generated by the imaging section 21b. Various person detection techniques for detecting people from three-dimensional point cloud data have been developed, and R-CNN, YOLO, SSD, etc. can be used. In the present embodiment, the second detection processing unit 33b (22b) uses one of these person detection techniques, for example, Mask R-CNN, which is one of the R-CNNs, from the image generated by the imaging unit 21b. The subject Ob is detected, and its outline is determined as the shape of the subject Ob from a pixel group of the detected subject Ob (a set of pixels determined to be the subject Ob).

The distance processing section 34b calculates the minimum distance between the hanging load detected by the first detection processing section 32b (12b) and the subject detected by the second detection processing section 33b (22b). ) and the shape of the subject detected by the second detection processing section 33b (22b). More specifically, in the second embodiment, the interval processing unit 34b, for example, identifies the subject and its shape RO (ROa, ROb, ROc) detected by the second detection processing unit 33b (22b) shown in FIG. 7A. , the suspended load detected by the first detection processing section 32b (12b) shown in FIG. 7B and its shape RP are combined as shown in FIG. 7C, and in this combined detection result CD, the second detection processing section 33b For each subject extracted in , the interval between the outline shape RP of the suspended load and the outline shape RO of the subject person is determined from the perspective of the suspended load detected by the first detection processing unit 32b, Find the smallest (shortest) interval as the minimum interval. Since the image does not have information in the Z direction (third direction), the synthesis is performed on the XY plane, and the spacing is determined on the XY plane. In the example shown in FIG. 7C, the interval processing unit 34b determines whether the hanging load is detected by the first detection processing unit 32b for each of the first to third subjects extracted by the second detection processing unit 33b. The interval SD between the outline shape RP of the subject and the subject's outline shape RO is determined, and the smallest (shortest) interval SDa among the determined intervals SDa, SDb, and SDc is determined as the minimum interval (SDa<SDb< SDc). Note that R-CNN determines object detection in a rectangular area, as shown by the broken line in FIG. The interval between is calculated.

The crane monitoring device Db in the second embodiment executes the same processes S1 to S7 shown in FIG. 4 as in the crane monitoring device Da in the first embodiment.

The crane monitoring device Db, the crane monitoring method implemented therein, and the overhead crane CRb in the second embodiment are similar to the crane monitoring device Da, the crane monitoring method implemented therein, and the overhead crane CRa in the first embodiment, By recognizing the shape of the suspended load, the distance between the suspended load and the subject can be measured more accurately.

The above crane monitoring device Db, crane monitoring method, and overhead crane CRb preferentially use the point cloud data generation unit 11b as the suspended load detection unit 1b that detects the shape, and use the imaging unit 21b as the subject detection unit 2b. Even if the point cloud data generation unit 11b has biased resolution, the suspended load and its shape can be accurately detected by the point cloud data generation unit 11b based on the high resolution area in the detection range, while the point cloud data generation unit 11b can accurately detect the suspended load and its shape. The subject Ob can be detected by the imaging unit 21b.

The above crane monitoring device Db, crane monitoring method, and overhead crane CRb can automate the start and end of monitoring.

Next, another embodiment will be described.
(Third embodiment)
In the overhead cranes CRa, CRb and the crane monitoring devices Da, Db in the first and second embodiments, the hanging load detection units 1a, 1b and the subject detection units 2a, 2b are disposed on the lifting cart LT, but in the third embodiment The overhead crane CRc and the crane monitoring device Dc in this embodiment have a hanging load detection section 1c and a subject detection section 2c disposed in the gutter GT.

FIG. 8 is a block diagram showing the configuration of a crane monitoring device in the third embodiment. FIG. 9 is a schematic diagram showing the configuration of an overhead crane monitored by the crane monitoring device of the third embodiment. FIG. 9A is a top view, and FIG. 9B is a side view. FIG. 10 is a diagram for explaining the first calculation mode for detecting the position of the hook in the third embodiment. FIG. 11 is a diagram for explaining a second calculation form for detecting the position of a hook in the third embodiment.

As shown in FIG. 9, the overhead crane CRc equipped with the crane monitoring device Dc in the third embodiment is equipped with the crane monitoring device Dc in the third embodiment instead of the crane monitoring device Da in the first embodiment. This is the same as the overhead crane CRa in the first embodiment. That is, as shown in FIG. 9, for example, the overhead crane CRc includes a pair of first and second traveling rails RL-1 and RL-2, a gutter GT, and a lifting truck LT. Since these are the same as in the case of the overhead crane CRa, the explanation thereof will be omitted.

The crane monitoring device Dc in the third embodiment includes, for example, as shown in FIG. 8, a suspended load detection section 1c, a subject detection section 2c, a control processing section 3c, an input section 4, an output section 5, It includes an interface section (IF section) 6, a storage section 7, and a hook detection section 8ca. The input section 4, output section 5, IF section 6, and storage section 7 in the crane monitoring device Dc of the third embodiment are respectively the input section 4, the output section 5, the IF section in the crane monitoring device Da of the first embodiment. 6 and storage unit 7, so the explanation thereof will be omitted.

The suspended load detection unit 1c is a device that is connected to the control processing unit 3c by wire or wirelessly, and detects the suspended load and the shape of the suspended load under the control of the control processing unit 3c. More specifically, the hanging load detection unit 1c includes a first point cloud data generation unit 11c (11c-A, 11c-B) that generates three-dimensional point cloud data in the detection direction, and a first point cloud data generation unit The first detection processing unit 12c (32c) detects a suspended load and the shape of the suspended load based on the three-dimensional point group data generated in step 11c. In the third embodiment, the first point group data generation unit 11c is disposed at the end of the gutter GT so as to face the detection direction toward the hook. More specifically, from the viewpoint of covering each other's blind spots, the first point cloud data generation unit 11c generates a set of two points, a first A and a first point group, which are arranged at both ends of the gutter GT, respectively, as shown in FIG. 9B. The first detection processing unit 12c (32c) includes 1B point cloud data generation units 11c-A and 11c-B, and the first detection processing unit 12c (32c) detects each data generated by the 1A and 1B point cloud data generation units 11c-A and 11c-B, respectively. A suspended load and a shape of the suspended load are detected based on three-dimensional point group data. The 1A point cloud data generation section 11c-A is arranged at one end of the gutter GT so that the detection direction faces the hook side, and the 1B point cloud data generation section 11c-B is arranged so that the detection direction faces the hook side. It is arranged at the other end of the garter GT so as to face. That is, the 1A and 1B point group data generation units 11c-A and 11c-B are arranged at each end of the gutter GT so that the respective detection directions are directed diagonally downward from above and intersect with each other. be done. For this reason, the 1A point cloud data generation section 11c-A (or the 1B point cloud data generation section 11c-B) has a blind spot where the back side of the wire rope, hook HK, luggage, etc. is blocked by these and becomes a blind spot. The blind spot is covered by the 1B point group data generation section 11c-B (or the 1A point group data generation section 11c-A). In this embodiment, the first detection processing section 12c (32c) is functionally configured in the control processing section 3c, and the first detection processing section 12c (32c) will be described later.

The subject detection unit 2c is a device that is connected to the control processing unit 3c by wire or wirelessly, and detects the subject and the shape of the subject under the control of the control processing unit 3c. More specifically, the subject detection unit 2c includes a second point cloud data generation unit 21c (21c-A, 21c-B) that generates three-dimensional point cloud data in the detection direction, and a second point cloud data generation unit The second detection processing section 22c (33c) detects the subject and the shape of the subject based on the three-dimensional point group data generated in step 21c. In the third embodiment, the second point group data generation unit 21c is disposed at the end of the gutter GT so as to face the detection direction toward the hook. More specifically, from the viewpoint of covering each other's blind spots, the second point cloud data generation unit 21c generates a set of two point cloud data, a second point group data generator and a second point group data generator, which are arranged at both ends of the gutter GT, respectively, as shown in FIG. 9B. The second detection processing unit 22c (33c) includes 2B point cloud data generation units 21c-A and 21c-B, and the second detection processing unit 22c (33c) detects each data generated by the 2A and 2B point cloud data generation units 21c-A and 21c-B, respectively. A subject and the shape of the subject are detected based on three-dimensional point cloud data. The 2nd A point cloud data generation section 21c-A is arranged at one end of the gutter GT so that the detection direction faces the hook side, and the 2nd B point cloud data generation section 21c-B is arranged so that the detection direction faces the hook side. It is arranged at the other end of the garter GT so as to face. That is, the second A and second B point group data generation units 21c-A and 21c-B are arranged at each end of the gutter GT so that the respective detection directions are directed diagonally downward from above and intersect with each other. be done. For this reason, the 2nd A point cloud data generation unit 21c-A (or the 2nd B point cloud data generation unit 21c-B) is required to avoid the wire rope, the hook HK, the back side of the baggage, etc. being blocked by these and becoming a blind spot. The blind spot is covered by the second B point group data generation section 21c-B (or the second A point group data generation section 21c-A). In this embodiment, the second detection processing section 22c (33c) is functionally configured in the control processing section 3c, and the second detection processing section 22c (33c) will be described later.

The first point cloud data generation section 11c of the suspended load detection section 1c and the second point cloud data generation section 21c of the subject detection section 2c may be separate bodies, but in this embodiment, they are used together. It is one thing. That is, the first A point cloud data generation section 11a-A of the hanging load detection section 1a and the second A point cloud data generation section 21a-A of the subject detection section 2a are configured with, for example, one LiDAR, The first B point cloud data generation section 11a-B of the hanging load detection section 1a and the second B point cloud data generation section 21a-B of the subject detection section 2a are configured to include, for example, one other LiDAR. .

The hook detection section 8ca is a device that is connected to the control processing section 3c by wire or wirelessly, and detects the position of the hook HK under the control of the control processing section 3c. More specifically, as shown in FIG. 10A, for example, the hook detection unit 8ca is located at a predetermined height from the floor that exceeds the height of the subject (for example, 2 m, etc.) and below the gutter GT. A range on the side (hook detection range, a three-dimensional area of a predetermined size where the X size is x0 [mm], the Y size is y0 [mm], and the Z size is z0 [mm]) 3-dimensional point cloud data in DA to the third point cloud data generation unit 81ca that generates in the detection direction along the first direction (Y direction) (from the side) and the three-dimensional point cloud data generated by the third point cloud data generation unit 81ca. A third detection processing section 82ca (37ca) that detects the position of the hook HK based on the detection processing section 82ca (37ca) is provided. In this embodiment, the third detection processing section 82ca (37ca) is functionally configured in the control processing section 3c, and the third detection processing section 82ca (37ca) will be described later.

The control processing unit 3c is a circuit for controlling each unit 1c, 2c, 4 to 7 of the crane monitoring device Dc according to the function of each unit, and monitoring a target person related to the overhead crane CRc. The control processing unit 3c includes, for example, a CPU and its peripheral circuits. By executing the control processing program, the control processing section 3c includes a control section 31, a first detection processing section 32c (12c), a second detection processing section 33c (22c), an interval processing section 34c, and a warning processing section. 35 and a third detection processing section 37ca (82ca) are functionally configured. The control unit 31 and warning processing unit 35 in the control processing unit 3c of the third embodiment are the same as the control unit 31 and warning processing unit 35 in the control processing unit 3a of the first embodiment, so the description thereof will be omitted. Omitted.

The third detection processing section 37ca (82ca) detects the position of the hook HK based on the three-dimensional point cloud data generated by the third point cloud data generation section 81ca. The hook HK is attached to the wire rope as described above. In the hook detection range DA, for example, as shown in FIG. 10A, three-dimensional point group data of this wire rope is predominantly generated. For this reason, the third detection processing section 37ca (82ca), for example, as shown in FIG. A frequency distribution diagram (histogram) is obtained along the second direction), and the position of the peak with the largest frequency is determined as the position of the hook HK.

Note that the position of the hook HK may be determined by measuring the position of the lifting trolley LT that suspends the hook so that the hook can be raised and lowered, as shown in FIG. In this case, as shown in FIG. 8, the crane monitoring device Dc includes a hook detection section 8cb instead of the hook detection section 8ca. The hook detection unit 8cb is a device that is connected to the control processing unit 3c by wire or wirelessly and detects the position of the hook HK under the control of the control processing unit 3c, and is a distance measurement unit that measures the distance to the lifting truck LT. 81cb, and a third detection processing section 37cb (82cb) that determines the position of the hook HK based on the distance to the lifting trolley LT measured by the distance measuring section 81cb. The distance measurement unit 81cb is disposed at a preset reference position for distance measurement (for example, the position of one end of the gutter GT), and measures the distance from the reference position to the lifting truck LT along the X direction (the second direction). Measure distance. The distance measuring section 81cb includes, for example, a laser distance meter. The correspondence between the distance from the reference position to the lifting trolley LT and the position of the hook HK along the X direction (the second direction) is determined in advance and stored in the storage unit 7 as one of the various data. , the third detection processing section 37cb (82cb) determines the position of the hook HK from the distance to the lifting truck LT measured by the distance measuring section 81cb and the correspondence relationship.

Returning to FIG. 8, the first detection processing unit 32c (12c) detects the suspended load and The shape of the image is detected. More specifically, in the third embodiment, since a set of 1A and 1B point cloud data generation units 11c-A and 11c-B is provided, the first detection processing unit 32c (12c) The three-dimensional point cloud data generated by the group data generation unit 11c-A and the three-dimensional point cloud data generated by the 1B point cloud data generation unit 11c-B are added, and from the added three-dimensional point cloud data, Similar to the first embodiment, the suspended load and its shape are determined.

The second detection processing unit 33c (22c) is the second point cloud data generation unit 21c (21c-A, 21c-B) (in this embodiment, they are also used, so the 1A and 1B point cloud data generation units 11c- The target person and the shape of the target person are detected based on the three-dimensional point cloud data generated in steps A and 11c-B). More specifically, in the third embodiment, the second detection processing unit 33c (22c) uses the three-dimensional data generated by the second A point cloud data generation unit 21c-A (first A point cloud data generation unit 11c-A) The point cloud data and the three-dimensional point cloud data generated by the second B point cloud data generation section 21c-B (the first B point cloud data generation section 11c-B) are added, and from the added three-dimensional point cloud data, , similarly to the first embodiment, find the subject and its shape.

The interval processing section 34c calculates the minimum distance between the hanging load detected by the first detection processing section 32c (12c) and the subject detected by the second detection processing section 33c (22c). ) and the shape of the subject detected by the second detection processing section 33c (22c). More specifically, in the third embodiment, the interval processing unit 34c first calculates the first A point from the position of the hook HK out of the three-dimensional point cloud data generated by the first A point cloud data generation unit 11c-A. The suspended load and its shape determined by the first detection processing unit 32c from the three-dimensional point cloud data on the arrangement side of the group data generation unit 11c-A, and the second A point cloud data generation unit 21c-A (first A point cloud A second detection processing unit uses the three-dimensional point cloud data generated by the data generation unit 11c-A) on the side where the second A point cloud data generation unit 11c-A is arranged from the position of the hook HK. 33c, the minimum distance between the hanging load and the target person (A-side minimum distance) is determined by processing the same as the distance processing unit 34a of the first embodiment. To detect. Next, the interval processing unit 34c calculates, from among the three-dimensional point cloud data generated by the first B point cloud data generation unit 11c-B, the position of the hook HK on the side where the first B point cloud data generation unit 11c-B is arranged. The suspended load and its shape determined by the first detection processing section 32c from the three-dimensional point cloud data of Among the dimensional point cloud data, the subject and its shape determined by the second detection processing section 33c from the 3D point cloud data on the side where the second B point cloud data generation section 11c-B is arranged from the position of the hook HK. In this step, the minimum distance (B-side minimum distance) between the hanging load and the subject is detected by performing the same processing as the distance processing section 34a of the first embodiment. Then, the interval processing unit 34c determines the smaller of the A-th side minimum interval and the B-th side minimum interval as the final minimum interval.

Note that for the same subject, the distance between the suspended load and the subject based on the three-dimensional point cloud data on the side where the first A point cloud data generation unit 11c-A is arranged from the position of the hook HK, and the distance between the subject and the hook HK. The distance between the suspended load and the subject based on the three-dimensional point cloud data on the side where the first B point cloud data generation unit 11c-B is disposed may be determined to be a different value based on the position. However, since the minimum interval is ultimately determined, the result will be the same even in such a case, so there is no problem.

The crane monitoring device Dc in the third embodiment executes processes S1 to S7 shown in FIG. 4, which are similar to those in the crane monitoring device Da in the first embodiment.

The crane monitoring device Dc, the crane monitoring method implemented therein, and the overhead crane CRc in the third embodiment are similar to the crane monitoring device Da, the crane monitoring method implemented therein, and the overhead crane CRa in the first embodiment, By recognizing the shape of the suspended load, the distance between the suspended load and the subject can be measured more accurately.

The above-mentioned crane monitoring device Dc, crane monitoring method, and overhead crane CRc each generate three-dimensional point cloud data representing the shape of the object surface, so that the suspended load detection section 1c and the subject detection section 2c each generate three-dimensional point cloud data. Hanging loads and people can be easily detected.

The hook HK moves in a plane perpendicular to the lifting direction by the movement of the garter GT with respect to the running rails RL-1 and RL-2 and the movement of the lifting cart LT with respect to the garter GT. Therefore, it is presumed that the vibration of the gutter GT is smaller than the vibration of the lifting truck LT. In the crane monitoring device Dc, crane monitoring method, and overhead crane CRc, each of the suspended load detection section 1c and the subject detection section 2c is disposed in the gutter GT, so that each detection of the suspended load detection section 1c and the subject detection section 2c is performed. The influence of vibration on the lift truck LT can be reduced more than in the case of the lifting trolley LT. In addition, since it is easier for the worker to access (approach) the gutter GT than the lifting trolley LT, the crane monitoring device Dc, the crane monitoring method, and the overhead crane CRc have the following advantages: Easy to maintain and manage.

The above crane monitoring device Dc, crane monitoring method, and overhead crane CRc can automate the start and end of monitoring.

Next, another embodiment will be described.
(Fourth embodiment)
Just as the second embodiment is configured with respect to the configuration of the first embodiment, the fourth embodiment is configured with respect to the configuration of the third embodiment. That is, in the overhead crane CRd and the crane monitoring device Dd in the fourth embodiment, the suspended load detection unit 1d is configured to include a point cloud data generation unit that generates three-dimensional point cloud data, as in the third embodiment. On the other hand, the subject detection section 2d is configured to include an imaging section that generates an image of the subject in the detection range in order to more reliably detect the subject Ob over the entire detection range.

FIG. 12 is a block diagram showing the configuration of a crane monitoring device in the fourth embodiment. FIG. 13 is a schematic diagram showing the configuration of an overhead crane monitored by the crane monitoring device of the fourth embodiment. FIG. 13A is a top view and FIG. 13B is a side view.

As shown in FIG. 13, the overhead crane CRd equipped with the crane monitoring device Dd in the fourth embodiment is equipped with the crane monitoring device Dd in the fourth embodiment instead of the crane monitoring device Da in the first embodiment. This is similar to the overhead crane CRa in the first embodiment. That is, for example, as shown in FIG. 13, the overhead crane CRd includes a pair of first and second traveling rails RL-1 and RL-2, a gutter GT, and a lifting truck LT. Since these are the same as in the case of the overhead crane CRa, the explanation thereof will be omitted.

The crane monitoring device Dd in the fourth embodiment includes, for example, as shown in FIG. 12, a suspended load detection section 1d, a subject detection section 2d, a control processing section 3d, an input section 4, an output section 5, It includes an interface section (IF section) 6, a storage section 7, and a hook detection section 8da. The input section 4, output section 5, IF section 6, and storage section 7 in the crane monitoring device Dd of the fourth embodiment are respectively the input section 4, the output section 5, the IF section in the crane monitoring device Da of the first embodiment. 6 and storage unit 7, the explanation thereof will be omitted. The hook detection unit 8da in the crane monitoring device Dd of the fourth embodiment is the same as the hook detection unit 8ca in the crane monitoring device Dc of the third embodiment, so the description thereof will be omitted.

The suspended load detection unit 1d is a device that is connected to the control processing unit 3d by wire or wirelessly, and detects the suspended load and the shape of the suspended load under the control of the control processing unit 3d. More specifically, the hanging load detection unit 1d includes a point cloud data generation unit 11d (11d-A, 11d-B) that generates three-dimensional point cloud data in the detection direction, and a point cloud data generation unit 11d that generates three-dimensional point cloud data in the detection direction. The first detection processing unit 12d detects the suspended load and the shape of the suspended load based on three-dimensional point cloud data. The point cloud data generation section 11d and the first detection processing section 12d in the suspended load detection section 1d are respectively the first point cloud data generation section 11c and the first detection processing section 12c in the suspended load detection section 1c of the third embodiment. It is similar to That is, as shown in FIGS. 12 and 13B, the point cloud data generation section 11d is a set of two A-th and B-th point cloud data generation sections 11d-A disposed at both ends of the gutter GT. , 11d-B, and the first detection processing unit 12c (32c) detects the suspension based on each three-dimensional point cloud data generated by the A-th and B-th point cloud data generation units 11d-A and 11d-B, respectively. Detecting the shape of the load and the suspended load.

The subject detection section 2d is a device that is connected to the control processing section 3d by wire or wirelessly, and detects the subject and the shape of the subject under the control of the control processing section 3d. More specifically, the target person detection unit 2d uses an imaging unit 21d (21d-A, 21d-B) that generates an image in the imaging direction, and detects the target person and the target person based on the image generated by the imaging unit 21d. It also includes a second detection processing section 22d that detects the shape. In the fourth embodiment, the imaging unit 21d is disposed at the end of the gutter GT so as to face the detection direction toward the hook. More specifically, from the viewpoint of covering each other's blind spots, the imaging section 21d is a set of two A-th and B-th imaging sections 21d- disposed at each end of the gutter GT, as shown in FIG. 13B. A, 21d-B, and the second detection processing unit 22dc (33d) detects the subject and the shape of the subject based on each image generated by the A and the imaging units 21d-A and 21d-B. To detect. The A-th imaging section 21d-A is arranged at one end of the garter GT so that the imaging direction faces the hook side, and the B-th imaging section 21d-B is arranged at one end of the garter GT so that the imaging direction faces the hook side. is arranged at the other end of the That is, the A-th and B-th imaging sections 21d-A and 21d-B are arranged at each end of the garter GT so that their imaging directions are directed diagonally downward from above and intersect with each other. Therefore, the A-th and B-th imaging units 21d-A and 21d-B in the subject detection unit 2d are the A-th and B-th point cloud data generation units 11d-A and 11d-B, respectively, in the suspended load detection unit 1d). are arranged so that they are juxtaposed to each other. Therefore, the back side of the A-th imaging section 21d-A (or the B-th imaging section 21d-B) is blocked by wire ropes, hooks HK, luggage, etc., resulting in a blind spot. It is covered by the section 21d-B (or the A-th imaging section 21d-A).

The control processing section 3d is a circuit for controlling each section 1d, 2d, 4 to 7 of the crane monitoring device Dd according to the function of each section, and for monitoring a target person related to the overhead crane CRd. The control processing unit 3d includes, for example, a CPU and its peripheral circuits. By executing the control processing program, the control processing section 3d includes a control section 31, a first detection processing section 32d (12d), a second detection processing section 33d (22d), an interval processing section 34d, and a warning processing section. 35 and the third detection processing section 37da (82da) are functionally configured. The control section 31 and the warning processing section 35 in the control processing section 3d of the fourth embodiment are the same as the control section 31 and the warning processing section 35 in the control processing section 3a of the first embodiment, so the description thereof will be omitted. Omitted. The first detection processing section 32d (12d) and the third detection processing section 37da (82da) in the control processing section 3d of the fourth embodiment are the first detection processing section 32c of the control processing section 3c of the third embodiment, respectively. (12c) and the third detection processing section 37ca (82ca), so the explanation thereof will be omitted.

The second detection processing section 33d (22d) detects the subject and the shape of the subject based on the image generated by the imaging section 21d (21d-A, 21d-B). More specifically, in the fourth embodiment, the second detection processing unit 33d (22d) detects the image generated by the A-th imaging unit 21d-A from the position of the hook HK. In the image on the side where the hook HK is arranged (on the front side from the position of the hook HK), the subject is detected by processing in the same manner as the second detection processing unit 33b of the second embodiment, and its shape is determined, and the B imaging unit Of the images generated by 21d-B, in the image on the side where the B-imaging unit 21d-B is disposed from the position of the hook HK (on the nearer side of the position of the hook HK), the second detection processing unit of the second embodiment The target person is detected by the same processing as in step 33b, and its shape is determined. More specifically, the second detection processing unit 33d detects the target person from the image on the side where the A-th imaging unit 21d-A is disposed from the position of the hook HK, and identifies a pixel group of the detected target (identified as the target person). The outline of the object is determined as the shape of the subject from the set of pixels (set of pixels), the subject is detected from the image on the side where the B imaging unit 21d-B is disposed from the position of the hook HK, and the pixel group of this detected subject is (a set of pixels determined to be the target person), its outline is determined as the shape of the target person.

The distance processing unit 34d determines the minimum distance between the hanging load detected by the first detection processing unit 32d (12d) and the subject detected by the second detection processing unit 33d (22d). ) and the shape of the subject detected by the second detection processing section 33d (22d). More specifically, in the fourth embodiment, the interval processing unit 34d first calculates the A-th point from the position of the hook HK out of the three-dimensional point cloud data generated by the A-th point cloud data generation unit 11d-A. Among the hanging load and its shape determined by the first detection processing unit 32d from the three-dimensional point cloud data on the arrangement side of the group data generation unit 11d-A, and the image generated by the A-th imaging unit 21d-A, the hook Processing is performed in the same manner as the interval processing section 34b of the second embodiment on the subject and its shape determined by the second detection processing section 33d from the image on the side where the A-th imaging section 21d-A is arranged from the HK position. By doing so, the minimum distance (A-side minimum distance) between the hanging load and the subject is detected. Next, the interval processing unit 34d processes the three-dimensional point cloud data generated by the B-th point cloud data generation unit 11d-B from the position of the hook HK to the side where the B-th point cloud data generation unit 11d-B is arranged. The suspended load and its shape determined by the first detection processing unit 32d from the three-dimensional point cloud data of Regarding the subject and its shape determined by the second detection processing section 33d from the image on the placement side of B, processing is performed in the same manner as the interval processing section 34b of the second embodiment to distinguish between the hanging load and the subject. Detect the minimum interval between the two (B-side minimum interval). Then, the interval processing unit 34c determines the smaller of the A-th side minimum interval and the B-th side minimum interval as the final minimum interval.

The crane monitoring device Dd in the fourth embodiment executes processes S1 to S7 shown in FIG. 4, which are similar to those in the crane monitoring device Dd in the first embodiment.

The crane monitoring device Dd, the crane monitoring method implemented therein, and the overhead crane CRd in the fourth embodiment are similar to the crane monitoring device Da, the crane monitoring method implemented therein, and the overhead crane CRa in the first embodiment, By recognizing the shape of the suspended load, the distance between the suspended load and the subject can be measured more accurately.

The above crane monitoring device Dd, crane monitoring method, and overhead crane CRd preferentially use the point cloud data generation unit 11d (11d-A, 11d-B) as the suspended load detection unit 1d that detects the shape, and By using the imaging unit 21d (21d-A, 21d-B) for the 2d, even if the point cloud data generation unit 11d has uneven resolution, the suspended load and its shape can be detected using a high resolution area in the detection range. While the group data generating section 11d can accurately detect the objects, the imaging section 21d can detect the subjects scattered around the hanging load.

In the above crane monitoring device Dd, crane monitoring method, and overhead crane CRd, each of the suspended load detection section 1d and the subject detection section 2d is disposed in the gutter GT, so that each detection of the suspended load detection section 1d and the subject detection section 2d is performed. The influence of vibration on the lift truck LT can be reduced more than in the case of the lifting trolley LT. In addition, since it is easier for the worker to access (approach) the gutter GT than the lifting trolley LT, the crane monitoring device Dd, the crane monitoring method, and the overhead crane CRd have the following advantages: Easy to maintain and manage.

The above crane monitoring device Dd, crane monitoring method, and overhead crane CRd can automate the start and end of monitoring.

Note that in the above-described embodiment, the start of monitoring was determined based on the operation status of the operation pendant HP and the load of the hook HK, but an imaging unit that generates an image is provided, and the control unit 31 The monitoring may be started when it is detected from the captured image that the worker (target person) is standing near the hook HK and moving his arm. For example, the skeleton of a worker is detected from an image using a well-known open pose technology using a deep learning model, and it is determined whether the worker is standing still based on the legs of the detected skeleton. In this case, it is determined whether the arm is moving based on the detected arm of the skeleton.

Further, the crane monitoring devices Da to Dd in the first to fourth embodiments stop the operation of the overhead cranes CRa to CRd when the minimum distance determined by the distance processing unit 34 is less than or equal to a predetermined second threshold. The system may further include a stop processing section. Such a stop processing unit 36 is functionally configured in the control processing units 3a to 3d, for example, as shown by broken lines in FIGS. 1, 5, 8, and 12. The second threshold value is, for example, 1 m, 2 m, etc., and is appropriately preset in consideration of safety and the like. The second threshold value may be the same value as the threshold value, or may be a different value. Since such crane monitoring devices Da to Dd further include a stop processing section 36, problems caused by the operation of the overhead crane can be avoided.

In order to express the present invention, the present invention has been adequately and fully described through embodiments with reference to the drawings in the above description, but those skilled in the art will easily be able to modify and/or improve the embodiments described above. It should be recognized that this is possible. Therefore, unless the modification or improvement made by a person skilled in the art does not depart from the scope of the claims stated in the claims, such modifications or improvements do not fall outside the scope of the claims. It is interpreted as encompassing.

Da-Dd Crane monitoring device CRa-CRd Overhead crane 1a-1d Hanging load detection section 2a-2d Subject detection section 3a-3d Control processing section 4 Output section 6 Storage section 8ca (8cb) Hook detection section 11a First point group data Generation unit 11b Point cloud data generation unit 11c-A 1A point cloud data generation unit 11c-B 1B point cloud data generation unit 11d-A A point cloud data generation unit 11d-B B point cloud data generation unit 21a 2-point cloud data generation unit 21b Imaging unit 21c-A 2A point cloud data generation unit 21c-B 2B point cloud data generation unit 21d-A A-th imaging unit 21d-B B-th imaging unit 31 Control units 32a to 32d ( 12a to 12d) First detection processing unit 33a to 33d (22a to 22d) Second detection processing unit 34a to 34d Interval processing unit 35 Warning processing unit 36 Stop processing unit 37ca (82ca), 37cb (82cb), 37da (82da) , 37db (82db) Third detection processing section 81ca, 81cb Third point group data generation section

Claims (7)

A crane monitoring device for monitoring a target person involved in an overhead crane, which is configured to be movable with a gutter extending in one direction and includes a lifting cart that suspends a hook so as to be able to rise and fall,
a suspended load detection unit that detects a suspended load and a shape of the suspended load;
a target person detection unit that detects the target person and the shape of the target person;
The minimum distance between the suspended load detected by the suspended load detection unit and the target person detected by the target person detection unit is determined by the shape of the suspended load detected by the suspended load detection unit and the target detected by the target person detection unit. an interval processing unit that calculates based on the shape of the person;
a warning processing unit that notifies an external person of a warning when the minimum interval determined by the interval processing unit is less than or equal to a predetermined threshold;
The hanging load detection unit identifies the hook, sets a detection area in a predetermined range including the identified hook, and detects the hanging load and the shape of the hanging load within the set detection area,
The hanging load detection unit is disposed at the end of the gutter so that the detection direction faces the hook side, and includes a first point cloud data generation unit that generates three-dimensional point cloud data in the detection direction; a first detection processing unit that detects the suspended load and the shape of the suspended load based on the three-dimensional point cloud data generated by the point cloud data generation unit;
The subject detection unit is disposed at an end of the gutter so as to face the detection direction toward the hook, and includes a second point cloud data generation unit that generates three-dimensional point cloud data in the detection direction; a second detection processing unit that detects the subject and the shape of the subject based on the three-dimensional point cloud data generated by the two-point cloud data generation unit;
The first point cloud data generation unit and the second point cloud data generation unit are separate units or are combined and integrated ,
The first point cloud data generation section includes two sets of 1A and 1B point cloud data generation sections disposed at both ends of the gutter, and the first detection processing section Detecting the suspended load and the shape of the suspended load based on each three-dimensional point cloud data generated by each of the 1A and 1B point cloud data generation units ,
The second point cloud data generation unit includes two sets of 2A and 2B point cloud data generation units disposed at both ends of the gutter, and the second detection processing unit includes detecting the shape of the subject and the subject based on each three-dimensional point cloud data generated by the 2A and 2B point cloud data generation units, respectively ;
Crane monitoring equipment. A crane monitoring device for monitoring a target person involved in an overhead crane, which is configured to be movable with a gutter extending in one direction and includes a lifting cart that suspends a hook so as to be able to rise and fall ,
a suspended load detection unit that detects a suspended load and a shape of the suspended load ;
a target person detection unit that detects the target person and the shape of the target person ;
The minimum distance between the suspended load detected by the suspended load detection unit and the target person detected by the target person detection unit is determined by the shape of the suspended load detected by the suspended load detection unit and the target detected by the target person detection unit. an interval processing unit that calculates based on the shape of the person ;
a warning processing unit that notifies an external person of a warning when the minimum interval determined by the interval processing unit is less than or equal to a predetermined threshold ;
The hanging load detection unit identifies the hook, sets a detection area in a predetermined range including the identified hook, and detects the hanging load and the shape of the hanging load within the set detection area,
The hanging load detection unit is disposed at the end of the gutter so that the detection direction faces the hook side, and includes a point cloud data generation unit that generates three-dimensional point cloud data in the detection direction, and a point cloud data generation unit that generates three-dimensional point cloud data in the detection direction. a first detection processing unit that detects the suspended load and the shape of the suspended load based on the three-dimensional point cloud data generated by the unit;
The subject detection unit is disposed at an end of the gutter so as to face the hook side in the imaging direction, and includes an imaging unit that generates an image in the imaging direction, and an imaging unit that generates an image in the imaging direction based on the image generated by the imaging unit. a second detection processing unit that detects a target person and a shape of the target person;
The point cloud data generation section includes two A-th and B-th point group data generation sections disposed at each end of the gutter, and the first detection processing section Detecting the suspended load and the shape of the suspended load based on each three-dimensional point cloud data generated by each B-th point cloud data generation unit ,
The imaging section includes a set of two A-th and B-th imaging sections disposed at each end of the gutter, and the second detection processing section is configured to perform a process on each of the A-th and B-th imaging sections. detecting the subject and the shape of the subject based on each generated image ;
Crane monitoring equipment. further comprising a start/end control unit that controls the start of the monitoring and the end of the monitoring;
A crane monitoring device according to claim 1 or claim 2 . further comprising a stop processing unit that stops the operation of the overhead crane when the minimum interval determined by the interval processing unit is less than or equal to a predetermined second threshold;
A crane monitoring device according to any one of claims 1 to 3 . A crane monitoring method for monitoring a target person involved in an overhead crane comprising an elevating cart configured to be able to move a gutter extending in one direction and suspending a hook such that it can be raised and lowered, the method comprising:
a suspended load detection step of detecting a suspended load and the shape of the suspended load;
a target person detection step of detecting the target person and the shape of the target person;
The minimum distance between the hanging load detected in the hanging load detection step and the target person detected in the target person detection step is the shape of the hanging load detected in the hanging load detection step and the target detected in the target person detection step. an interval processing step, which is determined based on the shape of the person;
a warning processing step of notifying a warning to the outside when the minimum interval determined in the interval processing step is less than or equal to a predetermined threshold;
The suspended load detection step identifies the hook, sets a detection area in a predetermined range including the identified hook, and detects the suspended load and the shape of the suspended load within the set detection area,
The hanging load detection step includes a three-dimensional point cloud data generation unit that is disposed at the end of the gutter so as to face the detection direction toward the hook side, and that generates three-dimensional point cloud data in the detection direction. detecting the suspended load and the shape of the suspended load based on point cloud data ;
The target person detection step is performed using a second point cloud data generation unit that is disposed at the end of the gutter so as to face the detection direction toward the hook side, and generates three-dimensional point cloud data in the detection direction. detecting the subject and the shape of the subject based on dimensional point cloud data ;
The first point cloud data generation unit and the second point cloud data generation unit are separate units or are combined and integrated ,
The first point cloud data generation section includes two sets of 1A and 1B point cloud data generation sections disposed at both ends of the gutter, and the hanging load detection step includes and detecting the suspended load and the shape of the suspended load based on each three-dimensional point cloud data generated by each of the first B point cloud data generation units ,
The second point cloud data generation section includes two sets of 2A and 2B point cloud data generation sections disposed at both ends of the gutter, and the subject detection step includes and detecting the subject and the shape of the subject based on each three-dimensional point cloud data generated by each of the second B point cloud data generation units ,
Crane monitoring method. A crane monitoring method for monitoring a target person involved in an overhead crane comprising an elevating cart configured to be able to move a gutter extending in one direction and suspending a hook such that it can be raised and lowered, the method comprising:
a suspended load detection step of detecting a suspended load and the shape of the suspended load ;
a target person detection step of detecting the target person and the shape of the target person ;
The minimum distance between the hanging load detected in the hanging load detection step and the target person detected in the target person detection step is the shape of the hanging load detected in the hanging load detection step and the target detected in the target person detection step. an interval processing step, which is determined based on the shape of the person ;
a warning processing step of notifying a warning to the outside when the minimum interval determined in the interval processing step is less than or equal to a predetermined threshold ;
The suspended load detection step identifies the hook, sets a detection area in a predetermined range including the identified hook, and detects the suspended load and the shape of the suspended load within the set detection area,
In the hanging load detection step, a three-dimensional point cloud is generated by a point cloud data generation section that is disposed at the end of the gutter so as to face the detection direction toward the hook, and generates three-dimensional point cloud data in the detection direction. detecting the suspended load and the shape of the suspended load based on data ;
The target person detection step includes detecting the target person and the object based on an image generated by an imaging unit that is disposed at the end of the gutter so as to face the hook side in the imaging direction, and generates an image in the imaging direction. detect the shape of the person ,
The point cloud data generation unit includes a set of two A-th and B-th point cloud data generation units disposed at both ends of the gutter, and the hanging load detection step includes Detecting the suspended load and the shape of the suspended load based on each three-dimensional point cloud data generated by each B point cloud data generation unit ,
The imaging unit includes a set of two A-th and B-th imaging units disposed at both ends of the gutter, and the target person detection step includes generating images in each of the A-th and B-th imaging units. detecting the subject and the shape of the subject based on each image ;
Crane monitoring method . An overhead crane comprising the crane monitoring device according to any one of claims 1 to 4 .

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