Apparatus, method, and program for processing acoustic data detected in facility

Abstract

SOLUTION: An apparatus includes: an acoustic data acquisition section for acquiring acoustic data detected in a facility; an image data acquisition section for acquiring data of an image taken in the facility; a source identification section for identifying which device among at least one device whose image has been taken in the image data is a source of each sound component among at least one sound component included in the acoustic data; and a device database connection section for associating sound component data of each sound component among at least the one sound component with the device as the source among at least the one device, so as to record them in a device database.SELECTED DRAWING: Figure 10

Description

Technical Field

[0001] The present invention relates to an apparatus, a method, and a program for processing acoustic data detected within a facility.

Background Art

[0002] Patent Document 1 describes that "the inspection support system 1 shown in FIG. 1 enables an inspector 4 at a monitoring location 3 remote from an inspection site 2 to inspect the equipment at the inspection site 2" (paragraph 0010), that "the sound information from the unmanned mobile body 10 includes the sound information acquired by each of a plurality of microphones 131 to 13m, and the sound determination unit 72 can determine the sound source direction, the sound source position, and the sound volume based on this sound information" (paragraph 0037), and that "the graphic addition unit 73 adds, based on the determination result by the sound determination unit 72, to the captured image acquired from the unmanned mobile body 10, a graphic representing at least one of the graphic representing the position of the sound source and the graphic representing the sound volume" (paragraph 0038). [Prior Art Document] [Patent Document] [Patent Document 1] Japanese Patent Application Laid-Open No. 2020-149349

Summary of the Invention

[0003] In a first aspect of the present invention, there is provided an apparatus including: an acoustic data acquisition unit that acquires acoustic data detected within a facility; an image data acquisition unit that acquires image data captured within the facility; a sound source identification unit that identifies, for each sound component among at least one sound component included in the acoustic data, which device among at least one device captured in the image data is the sound source; and a device database connection unit that records, in a device database, sound component data regarding each sound component among the at least one sound component in association with the device that is the sound source among the at least one device.

[0004] The above apparatus may include a sound source separation unit that separates the acoustic data into sound sources and extracts the at least one sound component.

[0005] In any of the above devices, the sound source separation unit may extract at least one sound component whose sound source directions are different from each other.

[0006] Any of the above devices may include a device detection unit that detects at least one device imaged in the image data by performing image recognition on the image data.

[0007] In any of the above devices, the device detection unit may detect each of the at least one device included in the image data by matching with a predetermined template.

[0008] In any of the above devices, for each of the at least one sound component, the sound source specifying unit may specify, as the sound source device, a device located in a region corresponding to the sound source direction in the image data among the at least one device.

[0009] Any of the above devices may include an input processing unit that receives input of information from a user for specifying a device in response to the fact that a device located in a region corresponding to the sound source direction in the image data cannot be specified for any of the at least one sound component.

[0010] In any of the above devices, the acoustic data acquisition unit and the image data acquisition unit may acquire the acoustic data and the image data from a robot that can move within the facility to collect sound and capture images.

[0011] Any of the above devices may include a robot command unit that instructs the robot to perform at least one of changing the imaging direction of the image, changing the imaging magnification of the image, or changing the position of the robot in response to the fact that the sound source device among the at least one device cannot be specified for any of the at least one sound component.

[0012] Any of the above devices may include a sound abnormality detection unit that detects the degree of abnormality of a sound component using the sound component data, and an abnormal device identification unit that identifies an abnormality of a device that is the source of the sound component based on the degree of abnormality of the sound component.

[0013] Any of the above devices may include a device control unit that performs control for dealing with an abnormality of one device among the one device or other devices in the facility in response to the identification of an abnormality of the one device that is the source of the sound component.

[0014] In a second aspect of the present invention, there is provided a method including: acquiring acoustic data detected in a facility; acquiring image data captured in the facility; identifying, for each sound component among at least one sound component included in the acoustic data, which device among at least one device captured in the image data is the sound source; and recording sound component data regarding each sound component among the at least one sound component in a device database in association with the device that is the sound source among the at least one device.

[0015] In a third aspect of the present invention, there is provided a program that is executed by a computer and causes the computer to function as an acoustic data acquisition unit that acquires acoustic data detected in a facility, an image data acquisition unit that acquires image data captured in the facility, a sound source identification unit that identifies, for each sound component among at least one sound component included in the acoustic data, which device among at least one device captured in the image data is the sound source, and a device database connection unit that records sound component data regarding each sound component among the at least one sound component in a device database in association with the device that is the sound source among the at least one device.

[0016] Note that the above summary of the invention does not list all the features of the present invention. Also, sub-combinations of these feature groups may also be inventions.

Brief Description of the Drawings

[0017]

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Modes for Carrying Out the Invention

[0018] Hereinafter, the present invention will be described through embodiments of the invention. However, the following embodiments do not limit the invention according to the claims. Also, not all combinations of features described in the embodiments are essential for the solution means of the invention.

[0019] FIG. 1 shows a schematic configuration of a facility 1 according to the present embodiment. The facility 1 may be an entire or partial segment such as a factory or a plant, and a plurality of devices 10 are arranged therein. Such a factory or plant may be, for example, a factory for producing various industrial products, an industrial plant such as a chemical or metal plant, a plant for managing and controlling a wellhead and its surroundings such as a gas field or an oil field, a plant for managing and controlling power generation such as hydraulic, thermal, or nuclear power, a plant for managing and controlling environmental power generation such as solar or wind power, a plant for managing and controlling water supply and drainage or a dam, etc. Also, the facility 1 may be an entire or partial part of a building or a transportation vehicle that includes a plurality of devices 10 to be controlled and monitored. The facility 1 includes a plurality of devices 10, a control system 20, one or more robots 30, a monitoring device 40, a collected information database 50, a device database 60, and a robot database 70.

[0020] The plurality of devices 10 are provided at various locations within the facility 1. Each of the plurality of devices 10 may be installed either indoors or outdoors within the area of the facility 1. At least some of the plurality of devices 10 may be a process device, a power generation device, or any other arbitrary device (or equipment) that is controlled by the control system 20, or may be a part of such a device. At least some of the devices 10 may be provided with field devices that operate under the control of the control system 20 or other devices, or an operator. Also, at least some of the devices 10 may be the field devices themselves.

[0021] Such field devices may be, for example, sensor devices such as pressure gauges, flow meters, temperature sensors, valve devices such as flow control valves and on-off valves, actuator devices such as fans and motors, imaging devices such as cameras or videos for photographing objects such as the situation of a plant or equipment, acoustic devices such as microphones or speakers for collecting abnormal sounds or the like in a plant or equipment or emitting alarm sounds, position detection devices for outputting the position information of the devices possessed by Facility 1, or other devices. Further, the other devices 10 among the plurality of devices 10 may be structures such as pipes, storage tanks, supports, partition walls, or others that do not receive control by the control system 20.

[0022] The control system 20 is connected to at least one of the plurality of devices 10 that is a control target. The control system 20 may be, for example, a distributed control system (DCS: Distributed Control System). The control system 20 controls each device 10 according to the state of each device 10 measured by sensors or the like provided in each device 10 that is a control target.

[0023] Each of the one or more robots 30 is used to monitor at least a part of the plurality of devices 10 in Facility 1. Each robot 30 can move within Facility 1 to collect sound and capture images and the like.

[0024] The monitoring device 40 is communicably connected to each of the one or more robots 30. The monitoring device 40 may be connected to each robot 30 via a wireless network such as a mobile phone network, a wireless WAN, a wireless LAN, or Bluetooth (registered trademark), or may be connected to each robot 30 via a wired network such as a wired Ethernet (registered trademark). The monitoring device 40 according to the present embodiment is installed within Facility 1. Alternatively, the monitoring device 40 may be provided outside Facility 1 to remotely monitor each device 10 within Facility 1. For example, the monitoring device 40 may be installed in another facility or may be realized by, for example, a cloud server on the Internet.

[0025] The monitoring device 40 receives the collected data such as acoustic data and image data collected by each robot 30 in the facility 1 from each robot 30, and monitors the state of each device 10 using the collected data. When the monitoring device 40 identifies an abnormality in any of the devices 10, it may instruct the control system 20 to perform control to address the abnormality.

[0026] The monitoring device 40 uses a collection information database 50, a device database 60, and a robot database 70 to monitor each device 10 in the facility 1 using one or more robots 30. The collection information database 50 records the collected data collected from each robot 30. The device database 60 records device data for each device 10 in the facility 1. The robot database 70 stores data related to each robot 30. These databases may be storage devices such as a hard disk connected to the monitoring device 40 by wire or wirelessly, or cloud storage on the Internet, and may be temporarily stored in the memory of the monitoring device 40 or the like.

[0027] FIG. 2 shows the configuration of the control system 20 according to the present embodiment together with a display device 240 and an input device 250. The display device 240 displays a display screen output by the control system 20. The input device 250 inputs an instruction to the control system 20 from a user such as an operator, worker, or maintenance staff of the facility 1 and supplies it to the control system 20. The display device 240 and the input device 250 may be provided in a monitoring console or a user terminal or the like connected to the control system 20.

[0028] The control system 20 may be a computer such as a workstation, a server computer, a general-purpose computer, or other computers, or may be a computer system to which a plurality of computers are connected. Such a computer system is also a computer in a broad sense. Further, the control system 20 may be implemented by one or more executable virtual computer environments within the computer. Alternatively, the control system 20 may be a dedicated computer designed for controlling each device 10, or may be dedicated hardware realized by a dedicated circuit. In the present embodiment, the control system 20 is installed in the facility 1, but the control system 20 may be provided outside the facility 1 by a cloud computing system or the like on the Internet.

[0029] The control system 20 includes a state acquisition unit 210, a state determination unit 220, a display processing unit 230, an instruction input unit 260, and a control unit 270. The state acquisition unit 210 acquires device state data indicating the state of each device 10, such as the internal state value of each device 10 and the measurement value measured by a sensor provided in each device 10, from each device 10. The state acquisition unit 210 may receive the device state data of each device 10 by using communication based on a communication protocol such as HART (registered trademark), BRAIN, Foundation Fieldbus (registered trademark), ISA100.11a. The state acquisition unit 210 may receive from the monitoring device 40 the device state data of the device 10 detected by the monitoring device 40 by using the collection data collected by the robot 30.

[0030] The state determination unit 220 is connected to the state acquisition unit 210. The state determination unit 220 determines whether each device 10 is normal or abnormal using the device state data acquired by the state acquisition unit 210. The state determination unit 220 may calculate a health index indicating the soundness of the operation in the entire facility 1 or a specific range within the facility 1 from at least one of the internal state values or measured values of two or more devices 10, and determine whether the operation is normal or not. The state determination unit 220 may determine the normality or abnormality of at least some of the devices 10 by receiving from the monitoring device 40 the determination result of the normality or abnormality of the device 10 determined by the monitoring device 40 using the collection data collected by the robot 30.

[0031] The display processing unit 230 is connected to the state acquisition unit 210 and the state determination unit 220. The display processing unit 230 performs display control to cause the display device 240 to display a display screen including device state data such as the internal state value and measured value of each device 10, a soundness index for the entire facility 1 or a specific range within the facility 1, and the occurrence status of abnormalities of each device 10.

[0032] The instruction input unit 260 receives an instruction from the user for the control system 20 from the input device 250. Such an instruction may be, for example, an instruction from the user who has seen the display screen displayed on the display device 240 to change the operation of at least one device 10. The instruction input unit 260 may be connected to the monitoring device 40 and may be communicable with the monitoring device 40 by wire or wirelessly. The instruction input unit 260 may receive from the monitoring device 40 an instruction to perform control for dealing with an abnormality in response to the detection of an abnormality in at least one device 10 by the monitoring device 40.

[0033] The control unit 270 is connected to the state acquisition unit 210 and the instruction input unit 260. The control unit 270 controls each device 10 according to the device state data acquired by the state acquisition unit 210. The control unit 270 may control each device 10 according to the instruction in response to receiving an instruction from the user or an instruction from the monitoring device 40.

[0034] Figure 3 shows the processing flow of the control system 20 according to this embodiment. In step 300 (S300), the state acquisition unit 210 acquires device state data indicating the state of each device 10 from each device 10. The state acquisition unit 210 may receive device data indicating the state of at least one device 10 from the monitoring device 40.

[0035] In S310, the state determination unit 220 determines whether each device 10 is normal or abnormal. The state determination unit 220 may determine whether the device 10 is normal (not abnormal) according to whether at least one of the internal state value or the measured value of the device 10 is within a predetermined normal range corresponding to the value. Further, the state determination unit 220 calculates a health index indicating the soundness of the operation in the entire facility 1 or a specific range within the facility 1 from at least one of the internal state values or the measured values of two or more devices 10 using a pre-defined calculation formula or the like, and determines whether the operation of the entire facility 1 or a specific range within the facility 1 is normal according to whether the value of the health index is within the normal range.

[0036] In S320, the display processing unit 230 performs display control to cause the display device 240 to display a display screen including the internal state values and measured values of each device 10, the health index for the entire facility 1 or a specific range within the facility 1, and the abnormality occurrence status of each device 10. The display processing unit 230 may generate a video output of the display screen and supply it to the display device 240, or may generate html or a script for generating the display screen and transmit it to the display device 240.

[0037] In S330, the instruction input unit 260 receives an instruction from the user for the control system 20 from the input device 250. The instruction input unit 260 may receive an instruction for performing control for dealing with an abnormality transmitted by the monitoring device 40 that has detected an abnormality in at least one device 10.

[0038] In S340, the control unit 270 controls each device 10 according to a predetermined control algorithm, control model, or the like, using the device state data acquired by the state acquisition unit 210. The control unit 270 may calculate a control value for each device 10 by PI control, PID control, or the like. The control unit 270 may also calculate a control value for each device 10 according to the device state data acquired by the state acquisition unit 210, using various machine learning models or the like. The control unit 270 may change the control content for each device 10 in response to an instruction from the instruction input unit 260.

[0039] The control system 20 repeats the processes from S300 to S340. Thereby, the control system 20 can adaptively control each device 10 according to the state of each device 10.

[0040] FIG. 4 shows the configuration of the robot 30 according to the present embodiment. The robot 30 includes one or more sensors 400, one or more sensors 410, one or more actuators 420, a state acquisition unit 430, a communication unit 440, and a control unit 450.

[0041] Each of the one or more sensors 400 detects or measures the state within the facility 1. In the example of this figure, the sensor 400a is an acoustic sensor that detects sound within the facility 1 and outputs it as acoustic data. The sensor 400b is an image sensor that captures an image within the facility 1 and outputs it as image data. The sensor 400c is a LiDAR sensor. The sensor 400c measures at least one of the shape of each object within the irradiation range of light or laser or the distance to each irradiation point by irradiating light or laser externally and detecting the reflected light, and outputs the measurement result as LiDAR data. The robot 30 may not include at least one of the sensors 400a to 400c. The robot 30 may also include at least one of a temperature sensor, a humidity sensor, a gas sensor, or other various sensors.

[0042] Each of the one or more sensors 410 detects or measures the state of the robot 30. In the example of this figure, the sensor 410a is a position sensor that detects the position of the robot 30 and outputs it as position data. The sensor 410a may be a GPS, specifically, a GPS (Global Positioning System) receiver that receives signals from GPS satellites to identify the position of the robot 30. Alternatively, the sensor 410a may be a sensor for identifying the position of the robot 30 using any position detection system capable of detecting the position of the robot 30 within the facility 1.

[0043] The sensor 410b is an azimuth sensor such as a geomagnetic sensor, for example. The sensor 410b measures the azimuth of the robot 30 or the azimuth of the detection direction of each sensor 400. The sensor 410c is an angle sensor or an elevation angle sensor or the like for measuring the detection direction of each sensor 400. The sensor 410b and the sensor 410c output direction data indicating at least one of the azimuth of the robot 30 or the detection direction of each sensor 400 to the state acquisition unit 430. Note that the robot 30 may not include at least one of the sensors 410a to 410c. The robot 30 may include at least one of a speed sensor, an acceleration sensor, or other various sensors.

[0044] Each of the one or more actuators 420 is a motor or the like for driving each part of the robot 30. The robot 30 may include various actuators 420 such as an actuator 420 for movement by traveling or flying, an actuator 420 for changing the orientation of the entire robot 30 or a part thereof, and an actuator 420 for operating equipment such as an arm.

[0045] The state acquisition unit 430 is connected to one or more sensors 400 and one or more sensors 410. The state acquisition unit 430 acquires the state inside the facility 1 measured by the one or more sensors 400 and the state of the robot 30 measured by the one or more sensors 410. The state acquisition unit 430 may acquire the state inside the facility 1 by receiving various measurement data such as acoustic data, image data, and LiDAR data from the one or more sensors 400. The state acquisition unit 430 may acquire the state of the robot 30 by receiving various measurement data such as position data and direction data from the one or more sensors 410.

[0046] The communication unit 440 is connected to the state acquisition unit 430. The communication unit 440 communicates wirelessly or by wire with the monitoring device 40. The communication unit 440 transmits the various measurement data acquired by the state acquisition unit 430 to the monitoring device 40. Also, the communication unit 440 receives various instructions for the robot 30 from the monitoring device 40.

[0047] The control unit 450 controls each actuator 420 according to the various measurement data acquired by the state acquisition unit 430 and the instructions from the monitoring device 40. Thereby, the robot 30 can perform operations corresponding to the state inside the facility 1, the state of the robot 30, and the instructions from the monitoring device 40.

[0048] Note that some robots 30 may be fixedly installed inside the facility 1, and such robots 30 do not need to be provided with actuators for movement. Also, inside the facility 1, there may be provided monitoring devices (such as surveillance cameras and surveillance microphones) that are equipped with one or more sensors 400 but are not classified as robots. Such monitoring devices will have some functions and configurations of the robot 30. Therefore, in this specification, for the sake of convenience of explanation, at least one of the robots 30 may be such a monitoring device, and such a monitoring device shall perform the following-described processing and the like within the scope of the implemented functions.

[0049] FIG. 5 shows the processing flow of the robot 30 according to the present embodiment. In S500, one or more sensors 400 observe the state of the facility 1 in the vicinity of the robot 30. One or more sensors 410 observe the state of the robot 30. The state acquisition unit 430 acquires various measurement data indicating the state of the facility 1 from one or more sensors 400. The state acquisition unit 430 acquires various measurement data indicating the state of the robot 30 from one or more sensors 410.

[0050] In S510, the communication unit 440 transmits various measurement data indicating the state in the facility 1 and the state of the robot 30 observed by one or more sensors 400 and one or more sensors 410 to the monitoring device 40. Here, when the central direction of measurement of each sensor 400 coincides with the direction of the robot 30, that is, for example, when the sensor unit or the like on which each sensor 400 is mounted faces the front of the robot 30, the measurement direction (central direction of measurement) of each sensor 400 coincides with the direction of the robot 30. In such a case, if the robot 30 transmits its own direction to the monitoring device 40, the monitoring device 40 can obtain the measurement direction of each sensor 400.

[0051] When the direction of the sensor unit on which each sensor 400 is mounted is variable with respect to the robot 30 main body, the central direction of measurement of each sensor 400 does not necessarily coincide with the direction of the robot 30. In this case, the robot 30 may transmit direction data including its own direction and the measurement direction of each sensor 400 to the monitoring device 40. Alternatively, the robot 30 may transmit direction data including its own direction and the difference or offset of the measurement direction of each sensor 400 with respect to its own direction to the monitoring device 40. In this case, the monitoring device 40 can obtain the measurement direction of each sensor 400 by adding the difference or offset of the measurement direction of each sensor 400 to its own direction.

[0052] In S520, the communication unit 440 receives an instruction from the monitoring device 40. In S530, the control unit 450 performs an operation according to the instruction from the monitoring device 40. The control unit 450 drives at least one actuator 420 according to an instruction for movement, an instruction for changing direction, an instruction for changing the direction of an acoustic sensor and an image sensor, etc. received from the monitoring device 40, thereby operating the robot 30 as instructed. Further, the control unit 450 may set various parameters in the robot 30 according to an instruction from the monitoring device 40.

[0053] The robot 30 repeats the processes from S500 to S530. Thereby, the robot 30 can move inside the facility 1 according to an instruction from the monitoring device 40, and perform sound collection by the sensor 400a, image capturing by the sensor 400b, acquisition of LiDAR data by the sensor 400c, etc.

[0054] FIG. 6 shows the configuration of the monitoring device 40 according to the present embodiment together with the collected information database 50, the device database 60, the robot database 70, the input device 680, and the display device 690. The input device 680 inputs an instruction for the monitoring device 40 from a user such as an operator, a worker, or a maintenance worker of the facility 1 and supplies it to the monitoring device 40. The display device 690 displays a display screen output by the monitoring device 40. The input device 680 and the display device 690 may be provided in a monitoring console or a user terminal etc. connected to the monitoring device 40. The display device 690 and the input device 680 may be shared with the display device 240 and the input device 250 shown in FIG. 2.

[0055] The monitoring device 40 may be a facility management device that manages each device 10 in the facility 1, or may be a device that realizes some functions included in the facility management device. The monitoring device 40 may be a computer such as a workstation, a server computer, a general-purpose computer, or other computers, or may be a computer system to which a plurality of computers are connected. Such a computer system is also a computer in a broad sense. Further, the monitoring device 40 may be implemented by one or more executable virtual computer environments in the computer. Such a computer functions as the monitoring device 40 by executing a program for monitoring each device 10 using the robot 30. Instead of this, the monitoring device 40 may be a dedicated computer designed for monitoring each device 10, or may be dedicated hardware realized by a dedicated circuit.

[0056] In the present embodiment, the monitoring device 40 is installed in the facility 1. Instead of this, the monitoring device 40 may be provided outside the facility 1 by a cloud computing system or the like on the Internet. Further, in the present embodiment, the monitoring device 40 remotely operates each robot 30. Instead of this, the monitoring device 40 may be mounted on at least one robot 30, and directly operate each robot 30 or a robot group including two or more robots 30 on site.

[0057] The monitoring device 40 includes a communication unit 600, a collected information database connection unit 620, a device database connection unit 630, a robot database connection unit 640, a monitoring processing unit 650, an input processing unit 660, a display processing unit 665, and a communication unit 670. The communication unit 600 performs wireless or wired communication with the robot 30. The communication unit 600 includes an acoustic data acquisition unit 602, an image data acquisition unit 604, a LiDAR data acquisition unit 606, a position data acquisition unit 608, a direction data acquisition unit 610, and an instruction transmission unit 612.

[0058] The acoustic data acquisition unit 602 acquires acoustic data detected within Facility 1. The acoustic data acquisition unit 602 may acquire acoustic data by receiving the acoustic data transmitted by the robot 30. The image data acquisition unit 604 acquires image data captured within Facility 1. The image data acquisition unit 604 may acquire image data by receiving the image data transmitted by the robot 30. The LiDAR data acquisition unit 606 acquires LiDAR data detected by the sensor 400c of the robot 30 within Facility 1. The LiDAR data acquisition unit 606 may acquire LiDAR data by receiving the LiDAR data transmitted by the robot 30.

[0059] The position data acquisition unit 608 acquires position data indicating the position of the robot 30. The position data acquisition unit 608 may acquire position data by receiving the position data transmitted by the robot 30. The direction data acquisition unit 610 acquires direction data indicating the directions of the robot 30 and each sensor 400. The direction data acquisition unit 610 may acquire direction data by receiving the direction data transmitted by the robot 30. The instruction transmission unit 612 transmits an instruction for the robot 30 determined within the monitoring device 40 to the robot 30.

[0060] The collected information database connection unit 620 is connected to the collected information database 50, the communication unit 600, and the monitoring processing unit 650. The collected information database connection unit 620 records various measurement data obtained by the acoustic data acquisition unit 602, the image data acquisition unit 604, the LiDAR data acquisition unit 606, the position data acquisition unit 608, and the direction data acquisition unit 610 in the communication unit 600 as collected data in the collected information database 50. Further, the collected information database connection unit 620 accesses the collected information database 50 in response to a request from the monitoring processing unit 650. Note that the monitoring device 40 may not include the collected information database connection unit 620 if it is not necessary to record the history of the collected data, and the measurement data obtained by the communication unit 600 may be supplied to the monitoring processing unit 650 without passing through the collected information database connection unit 620. In this case, the collected information database 50 is unnecessary.

[0061] The device database connection unit 630 is connected to the device database 60 and the monitoring processing unit 650. The device database connection unit 630 accesses the device database 60 in response to a request from the monitoring processing unit 650. The robot database connection unit 640 is connected to the robot database 70 and the monitoring processing unit 650. The robot database connection unit 640 accesses the robot database 70 in response to a request from the monitoring processing unit 650.

[0062] The monitoring processing unit 650 is connected to the collected information database connection unit 620, the device database connection unit 630, the robot database connection unit 640, the input processing unit 660, and the communication unit 670. The monitoring processing unit 650 reads out the robot data of each robot 30 via the robot database connection unit 640, and determines the monitoring actions in the facility 1 to be performed by each robot 30 using the robot data. The monitoring processing unit 650 instructs each robot 30 to perform each operation included in the determined monitoring action via the instruction transmission unit 612 in the communication unit 600.

[0063] Further, the monitoring processing unit 650 reads out the collection data collected by one or more robots 30 and recorded in the collection information database 50 via the collection information database connection unit 620. Then, the monitoring processing unit 650 uses the collection data to detect the state of each device 10 monitored by each robot 30. The monitoring processing unit 650 determines whether each device 10 is normal or not using the collection data. The monitoring processing unit 650 may read out the device data of each device 10 via the device database connection unit 630 and determine whether each device 10 is normal or abnormal based on the information registered in the device data.

[0064] The monitoring processing unit 650 may cause the display processing unit 665 to generate a display screen for displaying the state of each device 10 and the determination result of normal or abnormal, and display it on the display device 690. The monitoring processing unit 650 may transmit the state of each device 10 and the determination result of normal or abnormal to the control system 20 via the communication unit 670.

[0065] The monitoring processing unit 650 may generate an instruction to perform control for dealing with an abnormality in response to the detection of an abnormality in at least one device 10 as a result of monitoring each device 10 using one or more robots 30. The monitoring processing unit 650 may transmit an instruction to perform control for dealing with the abnormality of the device 10 to the control system 20 via the communication unit 670.

[0066] The input processing unit 660 is connected to the input device 680. The input processing unit 660 receives an input of information to the input device 680 from the user and supplies it to the monitoring processing unit 650. The display processing unit 665 is connected to the monitoring processing unit 650. The display processing unit 665 performs display processing to generate a display screen according to an instruction from the monitoring processing unit 650 and display it on the display device 690.

[0067] The communication unit 670 is connected to the monitoring processing unit 650. The communication unit 670 may be connected to the control system 20 and may be capable of communicating with the control system 20 wirelessly or by wire. The communication unit 670 may transmit the device status data of each device 10 detected by the monitoring processing unit 650 to the control system 20. The communication unit 670 may transmit the determination result of normal or abnormal of each device 10 determined by the monitoring processing unit 650 to the control system 20. The communication unit 670 may transmit an instruction to perform control for dealing with an abnormality to the control system 20 in response to an abnormality being detected in at least one device 10. Note that the communication unit 670 may not have a function of transmitting at least one of the device status data of the device 10, the determination result of normal or abnormal of the device 10, or the instruction to perform control for dealing with an abnormality to the control system 20. When the monitoring device 40 does not have any of these functions, the communication unit 670 may not be provided.

[0068] According to the monitoring device 40 described above, by monitoring the inside of the facility 1 using one or a plurality of robots 30 that can move inside the facility 1, a large number of devices 10 can be monitored using a relatively small number of robots 30. Further, since the monitoring device 40 can control the robot 30 according to the situation at each observation point and collect necessary information, it is possible to detect the state of each device 10 that cannot be collected by sensors or the like installed in advance in each device 10.

[0069] FIG. 7 shows an example of the data structure of the collected information database 50 according to the present embodiment. The collected information database 50 records the measurement data collected from each robot 30 as collected data. The collected information database 50 may record one or more records, each of which is a unit of collected data. In the data structure of the collected information database 50 shown in this figure, each record of the collected data is arranged in the row direction, and the collected data of each record includes fields of "date and time", "position and direction", "robot identification information", and "measurement data".

[0070] "Date and Time" is a field that records the date and time when the measurement data of the corresponding record was acquired by the robot 30. "Position and Orientation" is a field that records at least one position and orientation of the robot 30 or each sensor 400 at the timing when the measurement data of the corresponding record was acquired. The collection information database 50 may record, as "Position and Orientation", at least one of the position detected by the sensor 410a of the robot 30, the orientation of the robot 30 detected by the sensor 410b, or the direction of the robot 30 or each sensor 400 detected by the sensor 410c at the timing indicated by "Date and Time".

[0071] "Robot Identification Information" is a field that records data values such as an identification number, a serial number, or other unique number or character string that can identify the robot 30 that acquired the measurement data of the corresponding record, or can specify the robot 30 that acquired the measurement data within Facility 1. "Measurement Data" is a field that records the measurement data acquired by the robot 30 at the timing indicated by "Date and Time". The data recorded as "Measurement Data" may be various types of measurement data acquired by the robot 30, such as at least one of acoustic data, image data, or LiDAR data.

[0072] The communication unit 600 in the monitoring device 40 may receive, as separate packets or packet groups, etc., data including the acquisition date and time of measurement data by the robot 30, the robot identification information of the robot 30, and measurement data related to the position and orientation of the robot 30, and data including the acquisition date and time of measurement data by the robot 30, the robot identification information of the robot 30, and measurement data related to the state within the facility 1. In this case, each time the communication unit 600 receives measurement data related to the position and orientation of the robot 30, it updates the position and orientation of the robot 30 managed by the monitoring device 40. When the communication unit 600 receives measurement data related to the state within the facility 1, it generates a record of the collected data by associating the measurement data with the position and orientation of the robot 30 at the acquisition date and time of the measurement data. Alternatively, when the communication unit 440 in the robot 30 transmits various measurement data indicating the state within the facility 1 and the state of the robot 30 observed by each sensor 400 and each sensor 410 to the monitoring device 40 (see S510 in FIG. 5), it may assemble the collected data for one record from these measurement data, encode it into one or two or more packets, and transmit it to the monitoring device 40.

[0073] FIG. 8 shows an example of the data structure of the device database 60 according to the present embodiment. The device database 60 records device data for each of the plurality of devices 10 within the facility 1. The device database 60 may record records, each of which is device data for one device, for the number of devices 10. In the data structure of the device database 60 shown in this figure, each record of the device data is arranged in the row direction, and the device data of each record includes fields of "device identification information", "device name", "device information", "position", "template", and "acoustic data".

[0074] The "device identification information" is a field for recording data values such as an identification number, a serial number, or other unique numbers or character strings that can identify the corresponding device 10 within the facility 1. The "device name" is a field for recording the device name assigned by a user or the like to the corresponding device 10.

[0075] "Device information" is a field for recording various information about the corresponding device 10. "Location" is a field for recording the location of the device 10 within the facility 1. "Template" is a field for recording image data (template image data) of the appearance of the corresponding device 10 for use in identifying the device 10 by image matching. "Acoustic data" is a field for recording at least one of the acoustic data collected from the corresponding device 10 or the acoustic data emitted by the device 10 when the corresponding device 10 is normal.

[0076] Figure 9 shows an example of the data structure of the robot database 70 according to this embodiment. The robot database 70 records robot data for each of one or more robots 30 in the facility 1. The robot database 70 may record records, each of which is robot data for one robot, for the number of robots 30. In the data structure of the robot database 70 shown in this figure, each record of the robot data is arranged in the row direction, and the robot data of each record includes fields of "robot identification information", "robot name", "robot information", "position / direction", and "schedule information".

[0077] "Robot identification information" is a field for recording data values such as an identification number, serial number, or other unique number or character string that can identify the corresponding robot 30 within the facility 1. "Robot name" is a field for recording the robot name assigned to the corresponding robot 30 by a user or the like.

[0078] "Robot Information" is a field that records various information about the corresponding robot 30. "Position and Direction" is a field that records the position and direction of the corresponding robot 30 within Facility 1, and, if necessary, the direction of each sensor 400 (absolute direction or offset relative to the direction of robot 30). "Schedule Information" is a field that records the schedule for the corresponding robot 30 to patrol within Facility 1 to collect sounds within Facility 1 or sounds of each device 10, etc.

[0079] FIG. 10 shows the configuration of the monitoring processing unit 650 of the monitoring device 40 according to the present embodiment. The monitoring processing unit 650 includes a sound source separation unit 1000, a device detection unit 1010, a sound source identification unit 1020, a sound anomaly detection unit 1030, an abnormal device identification unit 1040, a device control unit 1050, and a robot command unit 1060.

[0080] The sound source separation unit 1000 is connected to the collection information database connection unit 620. The sound source separation unit 1000 reads out, via the collection information database connection unit 620, the collection data in which acoustic data is recorded as measurement data among the collection data registered in the collection information database 50. Thereby, the sound source separation unit 1000 acquires the acoustic data, the date and time when the acoustic data was acquired, and the position and direction where the acoustic data was observed within Facility 1. The sound source separation unit 1000 extracts at least one sound component by performing sound source separation and the like on the acquired acoustic data.

[0081] The device detection unit 1010 is connected to the collection information database connection unit 620. The device detection unit 1010 reads out, via the collection information database connection unit 620, the collection data in which image data is recorded as measurement data among the collection data registered in the collection information database 50. As a result, the device detection unit 1010 acquires the image data, the date and time when the image data was acquired, and the position and direction where the image data was observed within Facility 1. The device detection unit 1010 detects at least one device 10 imaged in the image data by performing image recognition or the like on the image data. The device detection unit 1010 may search for the device 10 within Facility 1 corresponding to the device imaged in the image data by accessing the device database 60 via the device database connection unit 630 and referring to each record of the device data.

[0082] The sound source identification unit 1020 is connected to the sound source separation unit 1000 and the device detection unit 1010. The sound source identification unit 1020 identifies which of the at least one device 10 imaged in the image data is the sound source of each sound component among the at least one sound component included in the acoustic data. The sound source identification unit 1020 according to the present embodiment identifies which of the devices 10 detected from the image data by the device detection unit 1010 is the sound source of each sound component extracted from the acoustic data by the sound source separation unit 1000. The sound source identification unit 1020 instructs the device database connection unit 630 to record the sound component data regarding each sound component in the device database 60 in association with the device 10 that is the sound source among the at least one device 10 imaged in the image data. If the device 10 corresponding to any sound component cannot be identified, the sound source identification unit 1020 may receive the designation of the corresponding device 10 or the like by receiving the input of information from the user via the input processing unit 660.

[0083] The abnormal sound detection unit 1030 is connected to the sound source identification unit 1020. The abnormal sound detection unit 1030 detects the degree of abnormality of the sound component using the sound component data associated with each device 10.

[0084] The abnormal device identification unit 1040 is connected to the abnormal sound detection unit 1030. The abnormal device identification unit 1040 identifies the abnormality of the device 10 that is the sound source of the sound component based on the degree of abnormality of the sound component detected by the abnormal sound detection unit 1030. The abnormal device identification unit 1040 may cause the display processing unit 665 to generate a display screen for displaying the state of each device 10 detected by the robot 30 on the display device 690 and display it on the display device 690. Further, the abnormal device identification unit 1040 may cause the display processing unit 665 to generate a display screen for displaying the determination result of normal or abnormal of each device 10 on the display device 690 and display it on the display device 690.

[0085] The device control unit 1050 is connected to the abnormal device identification unit 1040. When an abnormality of any device 10 that is the sound source of the sound component is identified, the device control unit 1050 performs control for dealing with the abnormality of the device 10 on at least one of the device 10 in which the abnormality is identified or other devices 10 in the facility 1. The device control unit 1050 transmits an instruction for performing control for dealing with the abnormality of the device 10 to the instruction input unit 260 in the control system 20 via the communication unit 670.

[0086] The robot command unit 1060 is connected to the collection information database connection unit 620, the robot database connection unit 640, and the sound source identification unit 1020. The robot command unit 1060 determines the operation to be performed by each robot 30 and instructs each robot 30 to perform the determined operation.

[0087] The monitoring processing unit 650 shown above has each component shown in FIG. 10 in order to realize each function such as identification of the device 10 that is the sound source of each sound component, identification of the abnormality of the device 10 of the sound source based on the degree of abnormality of the sound component, instruction of control for dealing with the abnormality of the device 10, and instruction of the operation for each robot 30. Instead of this, the monitoring processing unit 650 may adopt a configuration that does not have some of the components shown in FIG. 10.

[0088] For example, the monitoring processing unit 650 may not have the device control unit 1050 and may not issue an instruction for control to handle an abnormality of the device 10. Further, the monitoring processing unit 650 may not have the robot command unit 1060 and may not issue an instruction for an operation to each robot 30. Further, the monitoring processing unit 650 may not have the abnormal sound detection unit 1030 and the abnormal device identification unit 1040 and may not identify an abnormality of the device 10 that is a sound source based on the degree of abnormality of the sound component. Even when the monitoring device 40 does not have some of the functions exemplified herein, the monitoring device 40 can cause the user to receive information output or displayed by the monitoring device 40, discover an abnormality of the device 10, and take technical measures to be taken in response to the abnormality of the device 10 for at least one device 10 in the facility 1.

[0089] According to the monitoring device 40 described above, it is possible to collect the acoustic data detected in the facility 1 and the image data captured in the facility 1, and identify the device 10 that is the sound source of each sound component included in the acoustic data. Thereby, the monitoring device 40 can analyze the potential state of each device 10 that may not be detected from the state of each device 10 collected by the control system 20 from the sound component having the device 10 as the sound source. Further, the monitoring device 40 can promptly collect abnormal sounds emitted by the devices 10 installed at various locations in the facility 1, and can promptly take measures against the abnormality of the device 10.

[0090] FIG. 11 and FIG. 12 show the processing flow of the monitoring device 40 according to the present embodiment. The processing flows of FIG. 11 and FIG. 12 show the case where the monitoring device 40 monitors the facility 1 using one robot 30 for convenience of explanation. The monitoring device 40 may execute the processing flows of FIG. 11 and FIG. 12 for each of the plurality of robots 30.

[0091] In S1100, the robot command unit 1060 instructs the robot 30 to be processed to move within the facility 1 via the instruction transmission unit 612. Here, the robot command unit 1060 may refer to the schedule information recorded in the robot database 70 in association with the robot 30 to be processed, and acquire the schedule for the robot 30 to tour within the facility 1. This schedule may include information necessary to determine the operations of the robot 30, such as the positions of the respective observation points where the robot 30 should observe the state within the facility 1, the times when the robot 30 should arrive at each observation point, the movement routes between the observation points, or the observation directions at each observation point. The robot command unit 1060 moves the robot 30 to the next observation point according to the designation in this schedule, and supplies an instruction to the robot 30 to perform an observation at the next observation point. In response to this, the robot 30 moves to the next observation point (see S520 and S530 in FIG. 5). If an area where an abnormality may have occurred within the facility 1 has been specified, the robot command unit 1060 may instruct at least one robot 30 to head towards that area and move to various positions within that area to acquire acoustic data and image data, etc.

[0092] In S1110, the robot 30 observes the state within the facility 1 and the state of the robot 30 using each sensor 400 at the observation point (see S500 in FIG. 5). The robot 30 transmits various measurement data indicating the observed state within the facility 1 and the state of the robot 30 to the monitoring device 40 (see S510 in FIG. 5). The acoustic data acquisition unit 602 within the monitoring device 40 acquires the acoustic data from among the measurement data transmitted from the robot 30. The collection information database connection unit 620 may add the position data acquired by the position data acquisition unit 608, the direction data acquired by the direction data acquisition unit 610, etc. to the acoustic data acquired by the acoustic data acquisition unit 602, and record it in the collection information database 50 as collection data.

[0093] In S1120, the sound source separation unit 1000 extracts at least one sound component by performing sound source separation or the like on the acoustic data from the robot 30. The sound source separation unit 1000 may perform sound source separation by extracting at least one sound component having different directions of sound sources as seen from the robot 30 from the acoustic data. The sound source separation unit 1000 may specify the direction of each sound component as seen from the robot 30 (sound source localization).

[0094] Here, since each sensor 400a collects sound from a predetermined range of directions other than the central direction of measurement of the sensor 400a according to the directivity, the sensor 400a collects sound that is a synthesis of sounds from various sound sources. The sound source separation unit 1000 performs a process of separating or decomposing the sound collected by each sensor 400a into the sounds generated by each sound source. In this specification, for convenience of explanation, the sound obtained by extracting at least a part of the sound collected by the sensor 400a is referred to as a "sound component", but the "sound component" itself is also a sound. Therefore, the acoustic data, which is the data of the sound collected by the sensor 400a, and the sound component data, which is the data of the sound component, may be in the same data format.

[0095] The sound source separation unit 1000 may utilize various sound source separation and sound source localization techniques. For example, the robot 30 may have two or more sensors 400a, and the acoustic data received by the monitoring device 40 may include acoustic data for each channel that records the sound collected by each sensor 400a.

[0096] The sound source separation unit 1000 may calculate the direction of the sound source of each sound component with respect to the robot 30 from the time difference at which each sound component included in the acoustic data reaches each sensor 400a. Here, the sound source separation unit 1000 may calculate the relative direction of the sound source of each sound component with respect to the measurement direction of the sensor unit including two or more sensors 400a, and add it to the absolute direction (the central direction of measurement) in which the sensor unit itself is facing, thereby calculating the absolute direction of the sound source of each sound component at the observation point. Here, the absolute direction means an angle represented starting from at least a common reference direction (such as north) within the facility 1, such as the horizontal and vertical angles based on north. The relative direction means an angle represented starting from an arbitrarily selected reference direction (such as the traveling direction of the robot 30).

[0097] Further, the robot 30 may have a sensor 400a such as a directional microphone, and acquire acoustic data while changing the orientation of the sensor 400a within a predetermined direction range with respect to the robot 30. For example, the robot 30 may acquire acoustic data while changing the orientation of the sensor 400a within the angular range of the image data imaged by the sensor 400b. The sound source separation unit 1000 may use such acoustic data to specify the orientation of the sensor 400a when the magnitude (sound pressure) of each sound component is maximized as the direction of the sound source of that sound component.

[0098] By separating the acoustic data into sound sources in this way, the monitoring device 40 can identify the sound components generated from each device 10 even when it acquires acoustic data in which sounds from two or more devices 10 are superimposed. Thereby, the monitoring device 40 can increase the detection rate of abnormalities in the device 10 and can execute appropriate countermeasures against the abnormalities in the device 10.

[0099] In S1130, the image data acquisition unit 604 in the monitoring device 40 acquires image data from among the measurement data transmitted from the robot 30. The collection information database connection unit 620 may add the position data acquired by the position data acquisition unit 608, the direction data acquired by the direction data acquisition unit 610, etc. to the image data acquired by the image data acquisition unit 604, and record it in the collection information database 50 as collection data.

[0100] In S1140, the device detection unit 1010 detects one or more devices 10 imaged in the image data by performing image recognition or the like on the image data transmitted from the robot 30. The device detection unit 1010 may extract one or more objects imaged in the image data, search the device database 60 for the device 10 corresponding to each object, and detect the device 10 corresponding to each object. Here, the device detection unit 1010 may search the device database 60 for the device 10 located in the direction of the robot 30 or the sensor 400b at this timing from the position of the robot 30 at the timing when the image data was acquired.

[0101] The device detection unit 1010 may recognize each device 10 included in the image data using vision-based AR (Augmented Reality) technology. For example, the device detection unit 1010 may recognize each device 10 in the image data using markerless AR technology. The device detection unit 1010 may detect each of at least one device 10 included in the image data by matching it with a predetermined template. For example, the device detection unit 1010 extracts one or more objects imaged in the image data, and searches the device database 60 for the device 10 associated with the template image data that matches or is most similar to the image of each object. The device detection unit 1010 may detect the device 10 retrieved for each object as the device 10 located in the image range including that object in the image data. When the template image data associated with the device 10 retrieved from the device database 60 using the position of the robot 30 and the direction of the robot 30 or the sensor 400b at the timing when the image data was acquired is the same as or similar to the image of the object in the image range corresponding to the direction of the sensor 400b with respect to the position of the robot 30 in the image data with a similarity equal to or higher than a predetermined threshold, the device detection unit 1010 may determine that the device 10 corresponds to that object.

[0102] The device detection unit 1010 may also recognize each device 10 included in the image data using AR technology that uses markers. In this case, the device data stored in the device database 60 may store, for example in the device information field, the identification information of the marker attached to the corresponding device 10. The device detection unit 1010 may search the device database 60 for the device 10 associated with the device data in which the identification information matching the identification information of the marker attached to the device 10 included in the image data is stored.

[0103] The device detection unit 1010 may detect a device 10 that is not registered in the device database 60. For example, the device detection unit 1010 may detect, as an unregistered device 10, a device 10 newly installed in the facility 1 or a part of a device 10 that is already registered in the device database 60. The device detection unit 1010 may estimate the type (e.g., reactor, measuring instrument, pipe, or flange, etc.) or model of the device 10 corresponding to the object from the appearance shape of the object extracted from the image data. The device detection unit 1010 may detect an unknown device 10 included in the image data by matching it with a template or the like predetermined for each type or model of the device, and identify the type or model of the device. The monitoring device 40 can extract, from the image data, an unregistered device 10 installed in the facility 1 and a part of a device 10 that has not been recognized as a failure unit capable of generating abnormal sounds and has not been registered as an individual device 10 by performing image recognition on the image data using template matching or the like, and make it possible to detect the sound source.

[0104] The device detection unit 1010 may calculate the relative direction of the device 10 with respect to the center direction of the image from the position of the device 10 in the image corresponding to the image data. The device detection unit 1010 may calculate the absolute direction of each device 10 as seen from the observation point by adding the relative direction of the device 10 with respect to the center direction of the image to the absolute direction of the sensor 400b at the time of imaging the image data.

[0105] In S1150, the sound source identification unit 1020 identifies which device 10 imaged in the image data is the sound source of each sound component included in the acoustic data. The sound source identification unit 1020 may identify, for each sound component extracted from the acoustic data, among the devices 10 detected from the image data, the device 10 located in the region corresponding to the direction of the sound source within the image data as the sound source device 10. As an example, for a certain sound component and a certain device 10 detected from the acoustic data and the image data observed by the robot 30 at the same position at the same timing or different timings, the sound source identification unit 1020 determines that the sound source of this sound component is this device 10 when the absolute direction of the sound component and the absolute direction of the device 10 viewed from the observation point are the same, or when the difference between these absolute directions is within a predetermined error range. For the device 10 already registered in the device database 60, the sound source identification unit 1020 may determine that the sound source of this sound component is this device 10 on the condition that this device 10 is located in the absolute direction of the sound component viewed from the observation point of the acoustic data.

[0106] Also, for a certain sound component and a certain device 10 obtained from acoustic data and image data observed by the robot 30 at different positions at the same timing or different timings, the sound source identification unit 1020 determines that the sound source of this sound component is this device 10 on the condition that the absolute direction of the sound component as seen from the observation point of the acoustic data and the absolute direction of the device 10 as seen from the observation point of the image data intersect or substantially intersect within a predetermined error range. Here, the device detection unit 1010 may calculate an approximate distance range from the observation point of the image data to each device 10 based on the size etc. of each device 10 in the image corresponding to the image data. In this case, in addition to the absolute direction of the sound component as seen from the observation point of the acoustic data and the absolute direction of the device 10 as seen from the observation point of the image data intersecting or substantially intersecting within a predetermined error range, when the distance from the observation point of the image data to this intersection position is within the calculated distance range, the sound source identification unit 1020 may determine that the sound source of this sound component is this device 10. Since the monitoring device 40 can identify the device 10 that is the sound source of each sound component using the local acoustic data and image data observed by the robot 30 at the observation point, the sound information of each device 10 that could not be detected by the measurement by the control system 20 and was buried in the facility 1 can be made apparent as information usable for the management of each device 10.

[0107] In S1160, the sound source identification unit 1020 instructs the device database connection unit 630 to record the sound component data regarding each sound component in the device database 60 in association with the device 10 that is the sound source. The device database connection unit 630, upon receiving the instruction from the sound source identification unit 1020, records the sound component data regarding each sound component in the acoustic data field in the record of the device data corresponding to the device 10 that is the sound source in the device database 60. The device database connection unit 630 may record a plurality of sound component data obtained at different dates and times in the acoustic data field by adding the acquisition date and time of the sound component data and the sound component data to the acoustic data field.

[0108] In addition, when the sound source of a certain sound component is device 10 that is included in the image data but not registered in the device database 60, the sound source identification unit 1020 may register this device 10 in the device database 60 through the input of information from the user by the input processing unit 660, and record the sound component data in association with this device 10 in the device database 60. This process will be described later in relation to S1250.

[0109] In S1200, the sound abnormality detection unit 1030 detects the degree of abnormality of the sound component using the sound component data associated with each device 10. Here, the degree of abnormality may be represented by a real number or an integer within a predetermined range such as from 0 to 1 or from 0 to 100%, or may be a binary value such as normal or abnormal.

[0110] If the acoustic data emitted by device 10 when device 10 is normal is recorded in the device database 60, the sound abnormality detection unit 1030 may calculate, as the degree of abnormality, a value indicating how different the sound component data of the target with device 10 as the sound source is from the acoustic data emitted by device 10 during normal times. For example, the sound abnormality detection unit 1030 may determine the degree of abnormality according to the comparison result between the acoustic data during normal times and the sound component data of the target.

[0111] The sound abnormality detection unit 1030 may perform the comparison between the acoustic data during normal times and the sound component data of the target in either the time domain or the frequency domain. When performing the comparison in the time domain, the sound abnormality detection unit 1030 adjusts the phase difference so that the time integral of the difference (such as the absolute value of the difference) between the acoustic data during normal times and the sound component data of the target is minimized, and may use the time integral of the difference between the acoustic data and the sound component data of the target at the adjusted phase difference as the degree of abnormality. In this case, the sound abnormality detection unit 1030 may adjust the amplitude so that, for example, the average amplitude matches, in order to match the loudness of the sound of the acoustic data and the sound component data of the target.

[0112] When comparing the normal acoustic data with the target sound component data in the frequency domain, the sound anomaly detection unit 1030 may calculate the degree of anomaly by integrating, for each frequency, the difference (such as the absolute value of the difference) between the frequency spectrum of the normal acoustic data and the frequency spectrum of the target sound component data in the frequency direction. In this case, the sound anomaly detection unit 1030 may perform an adjustment to match the sound volume so as to make the acoustic data and the target sound component data comparable.

[0113] When the acoustic data collected from the device 10 in the past is recorded as one or more histories in the acoustic data field in the device database 60, the sound anomaly detection unit 1030 may calculate, as the degree of anomaly, a value indicating how different the target sound component data having the device 10 as the sound source is from the one or more acoustic data collected from the device 10 in the past. The sound anomaly detection unit 1030 may calculate the degree of anomaly of the target sound component data with respect to the acoustic data collected in the past in the same manner as the calculation method when calculating the degree of anomaly of the target sound component data with respect to the acoustic data emitted by the device 10 during normal operation described above.

[0114] The sound anomaly detection unit 1030 may determine the degree of anomaly according to the degree of deviation of the target sound component data from the distribution of the acoustic data collected from the device 10 in the past. Also, the sound anomaly detection unit 1030 may calculate, as the degree of anomaly, the sum of the degrees of difference for each of a predetermined number of acoustic data having the smallest difference from the target sound component data among the acoustic data collected from the device 10 in the past (k-nearest neighbor method). In addition to the above, the sound anomaly detection unit 1030 may calculate the degree of anomaly of the acoustic data and the target sound component data using various methods for calculating the difference, similarity, or degree of deviation between two sounds.

[0115] The abnormal sound detection unit 1030 may detect the degree of abnormality of the sound component using AI technology. The abnormal sound detection unit 1030 may receive the sound components emitted by each device 10 from the sound source identification unit 1020 and train them using a machine learning model for each device 10. The abnormal sound detection unit 1030 may store the machine learning model of each device 10 or the learned parameters representing the machine learning model in the device information field of the device database 60 or the like, and update the machine learning model each time it newly receives the sound components emitted by the device 10. Further, the abnormal sound detection unit 1030 may receive the determination result of normal or abnormal for each sound component. In this case, the abnormal sound detection unit 1030 may generate or update the machine learning model by learning so that the correct determination result is output when the sound component is input to the machine learning model.

[0116] The abnormal sound detection unit 1030 may use a neural network, statistical learning, or other machine learning algorithms. The abnormal sound detection unit 1030 may use the time-series data of the sound component as the input to the machine learning model, and may use the frequency spectrum of the sound component as the input to the machine learning model. The abnormal sound detection unit 1030 updates the parameters of the machine learning model so as to reduce the error between the output of the model when the sample of each sound component serving as learning data is input to the machine learning model and the learning label indicating whether the sound component is normal or abnormal. For example, when using a neural network, the abnormal sound detection unit 1030 inputs the data value at each time or the data value at each frequency in the sound component to each input node of the input layer of the neural network. The abnormal sound detection unit 1030 uses the error between the output value output by the neural network in response to the input of each sample and the label, and adjusts the weights between the neurons of the neural network and the biases of each neuron by a method such as backpropagation.

[0117] Note that the machine learning model may output the abnormality degree of the sound component in response to inputting the acoustic data collected in the past from the device 10 or the normal acoustic data and the sound component data from the device 10. Further, the machine learning model may be prepared for each type or model of the device 10 instead of being prepared for each individual device 10. Also, the machine learning model may be common to all the devices 10.

[0118] For example, by using the machine learning model learned in this way, in response to receiving the sound component having the device 10 as the sound source, the sound abnormality detection unit 1030 reads out the machine learning model corresponding to the device 10 from the device database 60, inputs the sound component, and can use the determination result of normal or abnormal output by the machine learning model as the abnormality degree. The sound abnormality detection unit 1030 may calculate the abnormality degree based on the difference between the normal acoustic data and the target sound component data using any other method.

[0119] Note that when the device 10 is not registered in the device database 60 but the type or model of the device 10 has been estimated, the sound abnormality detection unit 1030 may determine the abnormality degree of the target sound component data based on the acoustic data normally emitted by the device 10 of the same type or model as the estimated type or model or the acoustic data that has occurred in the past.

[0120] In S1210, the abnormal device identification unit 1040 identifies the abnormality of the device 10 that is the sound source of the sound component based on the abnormality degree of the sound component associated with the device 10. For example, when the abnormality degree of the sound component exceeds a predetermined threshold, the abnormal device identification unit 1040 may identify that the device 10 that is the sound source of the sound component is abnormal.

[0121] In S1220, the abnormal device identification unit 1040 may cause the display processing unit 665 to display on the display device 690 a display screen that shows the status of each device 10 detected by the robot 30. The abnormal device identification unit 1040 may cause the display processing unit 665 to display on the display device 690 a display screen that shows information (such as the observation location, direction, image, etc.) regarding one or more devices 10 that were identified as the source of certain sound component data but are not registered in the device database 60. Further, the abnormal device identification unit 1040 may cause the display processing unit 665 to display on the display device 690 a display screen that shows the observation location, the direction of the sound component data, etc. for sound component data that is not associated with any of the devices 10.

[0122] In S1230, the monitoring device 40 determines whether there is any sound component data that is not associated with any of the devices 10. If all the sound component data is associated with one of the devices 10 (the "N" in S1230), the monitoring device 40 advances the process to S1240. The monitoring device 40 may advance the process to S1240 when all the sound component data is associated with one of the devices 10 registered in the device database 60.

[0123] In S1240, when an abnormality of one of the devices 10 that is the source of the sound component is identified, the device control unit 1050 performs control for dealing with the abnormality of the device 10 on at least one of the device 10 in which the abnormality was identified or other devices 10. The device control unit 1050 transmits an instruction to perform control for dealing with the abnormality of the device 10 to the control system 20 via the communication unit 670.

[0124] As an example, the device control unit 1050 may instruct the control system 20 to perform control to stop the operation of the device 10 in which an abnormality has been identified. The device control unit 1050 may instruct the control system 20 to perform control to stop other devices 10 related to the device 10 in which an abnormality has been identified (for example, devices 10 in the upstream or downstream processes of the device 10 in which an abnormality has been identified, etc.). The device control unit 1050 may also instruct the control system 20 to perform control to stop the operations of both the device 10 in which an abnormality has been identified and other devices 10 related to the device 10 in which an abnormality has been identified. The monitoring device 40 proceeds with the process to S1100 and continues the monitoring of the facility 1 by the robot 30.

[0125] If there is sound component data not associated with any device 10 in S1230 (''Y'' in S1230), the monitoring device 40 proceeds with the process to S1250. Here, the monitoring device 40 may also proceed with the process to S1250 even when the sound component data is associated with a device 10 not registered in the device database 60.

[0126] In S1250, in response to the fact that the input processing unit 660 cannot identify the device 10 located in the image area corresponding to the direction of the sound source in the acoustic data for any of the sound components, the input processing unit 660 accepts input of information from the user for identifying the device 10. Here, if the device 10 associated with the sound component is unregistered and its presence in the facility 1 has not been confirmed, the input processing unit 660 accepts input of information about at least a part of the device data regarding the unregistered device 10, and the sound source identification unit 1020 may register the device data of the device 10 corresponding to the received information in the device database 60. In response to such input of information (''Y'' in S1260), the monitoring device 40 proceeds with the process to S1150. Thereby, the sound source identification unit 1020 can identify the sound source of each sound component including the newly registered device 10.

[0127] When the device 10 associated with the sound component is unregistered, the input processing unit 660 may receive an input of information indicating whether to register the device 10 in the device database 60. The sound source identification unit 1020 may register the device data of the device 10 corresponding to the type or model of the device 10 detected from the image data, the position or approximate position, or other already known information in the device database 60.

[0128] In addition, the input processing unit 660 may receive an input of information designating the device 10 of the sound source for the sound component data not associated with any device 10. In response to such an input of information (''Y'' in S1260), the monitoring device 40 advances the process to S1150. Thereby, the sound source identification unit 1020 can identify that the sound source of the sound component data is the designated device 10.

[0129] In S1270, in response to the fact that the sound source device 10 of each device 10 cannot be identified for any sound component, the robot command unit 1060 instructs the robot 30 to perform at least one of changing the imaging direction of the image, changing the imaging magnification of the image, or changing the position of the robot 30. In the processing flow of this figure, the robot command unit 1060 performs the processing of S1270 when there is no input of information regarding the device 10 corresponding to the sound component (''N'' in S1260). Alternatively, when the sound source device 10 of any sound component cannot be identified, the robot command unit 1060 may automatically instruct the robot 30 to change the imaging direction of the image, change the imaging magnification of the image, change the position of the robot 30, etc.

[0130] For example, when it is impossible to identify whether the sound source of a certain sound component is one of the two devices 10, the robot command unit 1060 may instruct the robot 30 to move closer to one of the two devices 10. Further, when there is a sound component from outside the viewing angle of the image data, the robot command unit 1060 may instruct the robot 30 to move the imaging direction of the image closer to the direction of the sound component, reduce the imaging magnification of the image to image the range including the direction of the sound component, or move toward the sound component outside the viewing angle. After instructing the robot 30, the monitoring device 40 proceeds with the process to S1110 and performs the processes from S1110 to S1220 on the acoustic data and image data newly acquired by the robot 30. Thereby, even in a situation where the monitoring device 40 cannot determine which device 10 is the sound source of the sound component in the observation from one observation point or under one observation condition, by changing the observation point or observation condition and repeating the observation, the accuracy of associating the sound component with the device 10 of the sound source can be further improved.

[0131] FIG. 13 shows an example of image data 1300 captured by the robot 30 according to the present embodiment. In the image data 1300, devices 10 such as a plurality of pipes 1305a to 1305h, a valve 1310, a reactor 1320, and a flow meter 1330 are imaged. In the example of this figure, there is an abnormality in the valve 1310 and it is emitting abnormal noise.

[0132] The monitoring device 40 receives collection data including the image data 1300 and acoustic data obtained by collecting sounds within the viewing angle range of the image data 1300 (corresponding to S1110 and S1130 in FIG. 11). The sound source separation unit 1000 separates the acoustic data by sound source and extracts sound components from each direction within the viewing angle range of the image data 1300 (corresponding to S1120). The device detection unit 1010 detects each device 10 imaged in the image data 1300 by performing image recognition or the like on the image data 1300 (corresponding to S1140).

[0133] When the direction of a certain sound component coincides with (or coincides within a predetermined error range) the direction corresponding to the area where a certain device 10 is located in the image data 1300, the sound source generation location specifying unit 1020 may specify that the sound source of the sound component is the device 10 (corresponding to S1150). The sound abnormality detection unit 1030 detects the degree of abnormality of the sound component using the sound component data associated with each device 10 (corresponding to S1200). In the example of this figure, the sound abnormality detection unit 1030 detects a high degree of abnormality for the sound component from the valve 1310 that is making an abnormal sound. As a result, the abnormal device specifying unit 1040 can specify that the valve 1310 is abnormal based on the degree of abnormality of the sound component.

[0134] Here, when the pipes 1305a to 1305c and the valve 1310 are newly installed in the facility 1 and are not registered in the device database 60, the device detection unit 1010 may estimate that the pipes 1305a to 1305c are pipes and the valve 1310 is a valve from the external shape and the like of the object extracted from the image data 1300. The sound abnormality detection unit 1030 may detect the degree of abnormality of the sound component based on the result of comparing the sound component data from the valve 1310 with the acoustic data emitted when the valve is normal or the acoustic data emitted by one or more other valves in the facility 1 in the past.

[0135] Note that depending on the type of the sensor 400a used by the robot 30, the sound source separation unit 1000 may be able to separate the sound source in the horizontal direction, for example, but may not be able to separate the sound source in the vertical direction. In such a case, the sound source generation location specifying unit 1020 may specify the device 10 that is the sound source of each sound component while appropriately changing the imaging direction and position of the robot 30 (S1270 in FIG. 12) using the horizontal position of each device 10 in the image data 1300 and the direction of each sound component in the horizontal direction.

[0136] Various embodiments of the present invention may be described with reference to flowcharts and block diagrams, where the blocks may represent (1) stages of a process in which an operation is performed or (2) sections of an apparatus having a role of performing an operation. Specific stages and sections may be implemented by a dedicated circuit, a programmable circuit supplied with computer-readable instructions stored on a computer-readable medium, and / or a processor supplied with computer-readable instructions stored on a computer-readable medium. The dedicated circuit may include digital and / or analog hardware circuits, and may include integrated circuits (ICs) and / or discrete circuits. The programmable circuit may include a reconfigurable hardware circuit including memory elements such as logical AND, logical OR, logical XOR, logical NAND, logical NOR, and other logical operations, flip-flops, registers, field programmable gate arrays (FPGAs), programmable logic arrays (PLAs), etc.

[0137] The computer-readable medium may include any tangible device capable of storing instructions executable by an appropriate device, such that a computer-readable medium having instructions stored therein will comprise a product including instructions executable to create means for performing the operations specified in the flowchart or block diagram. Examples of the computer-readable medium may include electronic storage media, magnetic storage media, optical storage media, electromagnetic storage media, semiconductor storage media, etc. More specific examples of the computer-readable medium may include floppy (registered trademark) disks, diskettes, hard disks, random access memory (RAM), read only memory (ROM), erasable programmable read only memory (EPROM or flash memory), electrically erasable programmable read only memory (EEPROM), static random access memory (SRAM), compact disk read only memory (CD-ROM), digital versatile disk (DVD), Blu-ray (registered trademark) disk, memory stick, integrated circuit card, etc.

[0138] Computer-readable instructions may include any combination of one or more programming languages, including assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state-setting data, or source code or object code written in object-oriented programming languages such as Smalltalk®, JAVA®, C++, and conventional procedural programming languages such as the "C" programming language or similar programming languages.

[0139] Computer-readable instructions may be provided locally or via a wide area network (WAN) such as a local area network (LAN), the Internet, etc., to a processor or programmable circuit of a programmable data processing apparatus such as a general-purpose computer, a special-purpose computer, or other computer, and may be executed to create means for performing the operations specified in a flowchart or block diagram. Examples of processors include computer processors, processing units, microprocessors, digital signal processors, controllers, microcontrollers, etc.

[0140] FIG. 14 shows an example of a computer 2200 in which multiple aspects of the present invention may be embodied in whole or in part. Programs installed on the computer 2200 can cause the computer 2200 to function as an operation associated with the apparatus according to an embodiment of the present invention or as one or more sections of the apparatus, or can cause the operation or the one or more sections to be executed, and / or can cause the computer 2200 to execute a process according to an embodiment of the present invention or a stage of the process. Such a program may be executed by the CPU 2212 to cause the computer 2200 to execute specific operations associated with some or all of the blocks of the flowcharts and block diagrams described herein.

[0141] The computer 2200 according to this embodiment includes a CPU 2212, a RAM 2214, a graphic controller 2216, and a display device 2218, which are mutually connected by a host controller 2210. The computer 2200 also includes an input / output unit such as a communication interface 2222, a hard disk drive 2224, a DVD-ROM drive 2226, and an IC card drive, which are connected to the host controller 2210 via an input / output controller 2220. The computer also includes legacy input / output units such as a ROM 2230 and a keyboard 2242, which are connected to the input / output controller 2220 via an input / output chip 2240.

[0142] The CPU 2212 operates according to programs stored in the ROM 2230 and the RAM 2214, thereby controlling each unit. The graphic controller 2216 acquires image data generated by the CPU 2212 in a frame buffer or the like provided in the RAM 2214 or in itself, and causes the image data to be displayed on the display device 2218.

[0143] The communication interface 2222 communicates with other electronic devices via a network. The hard disk drive 2224 stores programs and data used by the CPU 2212 in the computer 2200. The DVD-ROM drive 2226 reads a program or data from the DVD-ROM 2201 and provides the program or data to the hard disk drive 2224 via the RAM 2214. The IC card drive reads programs and data from an IC card and / or writes programs and data to an IC card.

[0144] ROM 2230 stores therein a boot program or the like executed by computer 2200 upon activation and / or a program dependent on the hardware of computer 2200. Input / output chip 2240 may also be connected to input / output controller 2220 via various input / output units through a parallel port, a serial port, a keyboard port, a mouse port, or the like.

[0145] The program is provided by a computer-readable medium such as DVD-ROM 2201 or an IC card. The program is read from the computer-readable medium, installed in hard disk drive 2224, RAM 2214, or ROM 2230, which are also examples of computer-readable media, and executed by CPU 2212. The information processing described in these programs is read by computer 2200, resulting in cooperation between the programs and the various types of hardware resources described above. The apparatus or method may be configured by realizing the operation or processing of information according to the use of computer 2200.

[0146] For example, when communication is executed between computer 2200 and an external device, CPU 2212 may execute a communication program loaded in RAM 2214 and instruct communication interface 2222 to perform communication processing based on the processing described in the communication program. Communication interface 2222 reads transmission data stored in a transmission buffer processing area provided in a recording medium such as RAM 2214, hard disk drive 2224, DVD-ROM 2201, or an IC card under the control of CPU 2212, transmits the read transmission data to the network, or writes the received data received from the network to a reception buffer processing area or the like provided on the recording medium.

[0147] Further, the CPU 2212 may cause all or necessary portions of files or databases stored in external recording media such as a hard disk drive 2224, a DVD-ROM drive 2226 (DVD-ROM 2201), an IC card, etc. to be read into the RAM 2214, and may execute various types of processing on the data on the RAM 2214. The CPU 2212 then writes back the processed data to the external recording media.

[0148] Various types of information such as various types of programs, data, tables, and databases may be stored in the recording media and may undergo information processing. The CPU 2212 may perform various types of processing on the data read from the RAM 2214, including various types of operations, information processing, conditional judgment, conditional branching, unconditional branching, information search / replacement, etc. described throughout this disclosure and specified by the instruction sequence of the program, and write back the results to the RAM 2214. Also, the CPU 2212 may search for information in files, databases, etc. within the recording media. For example, when a plurality of entries each having an attribute value of a first attribute associated with an attribute value of a second attribute are stored in the recording media, the CPU 2212 searches for an entry that matches the condition where the attribute value of the first attribute is specified from among the plurality of entries, reads the attribute value of the second attribute stored in the entry, and thereby may obtain the attribute value of the second attribute associated with the first attribute that satisfies a predetermined condition.

[0149] The programs or software modules described above may be stored in a computer-readable medium on or near the computer 2200. Also, a recording medium such as a hard disk or RAM provided within a server system connected to a dedicated communication network or the Internet can be used as a computer-readable medium, thereby providing the program to the computer 2200 via the network.

[0150] As described above, the present invention has been described using embodiments. However, the technical scope of the present invention is not limited to the scope described in the above embodiments. It is obvious to those skilled in the art that various changes or improvements can be made to the above embodiments. It is clear from the description of the claims that forms with such changes or improvements can also be included in the technical scope of the present invention.

[0151] It should be noted that the execution order of each process such as operations, procedures, steps, and stages in the apparatus, system, program, and method shown in the claims, the specification, and the drawings is not explicitly indicated as "earlier" or "preceding" etc., and can be realized in any order unless the output of the previous process is used in the subsequent process. Regarding the operation flow in the claims, the specification, and the drawings, even if it is described using "first," "next," etc. for convenience, it does not mean that it is essential to implement in this order.

Description of Reference Numerals

[0152] 1 Facility 10 Equipment 20 Control System 30 Robot 40 Monitoring Device 50 Collected Information Database 60 Equipment Database 70 Robot Database 210 State Acquisition Unit 220 State Judgment Unit 230 Display Processing Unit 240 Display Device 250 Input Device 260 Instruction Input Unit 270 Control Unit 400a~c Sensors 410a~b Sensors 420 Actuator 430 State Acquisition Unit 440 Communication Unit 450 Control Unit 600 Communication Unit 602 Acoustic Data Acquisition Unit 604 Image data acquisition unit 606 LiDAR data acquisition unit 608 Position data acquisition unit 610 Direction data acquisition unit 612 Instruction transmission unit 620 Collection information database connection unit 630 Equipment database connection unit 640 Robot database connection unit 650 Monitoring processing unit 660 Input processing unit 665 Display processing unit 670 Communication unit 680 Input device 690 Display device 1000 Sound source separation unit 1010 Equipment detection unit 1020 Generation source identification unit 1030 Abnormal sound detection unit 1040 Abnormal equipment identification unit 1050 Equipment control unit 1060 Robot command unit 1300 Image data 1305a~h Pipes 1310 Valve 1320 Reactor 1330 Flow meter 2200 Computer 2201 DVD-ROM 2210 Host controller 2212 CPU 2214 RAM 2216 Graphics controller 2218 Display device 2220 Input / output controller 2222 Communication interface 2224 Hard disk drive 2226 DVD-ROM drive 2230 ROM 2240 Input / output chip 2242 Keyboard

Claims

1. An acoustic data acquisition unit that acquires acoustic data detected within a facility, an image data acquisition unit that acquires image data captured within the facility, a sound source identification unit that identifies, for each sound component among at least one sound component included in the acoustic data, which device among at least one device imaged in the image data is the sound source, and a device database connection unit that records sound component data regarding each sound component among the at least one sound component in a device database in association with the device that is the sound source among the at least one device. A device comprising the above.

2. The device according to claim 1, further comprising a sound source separation unit that separates the acoustic data into sound sources and extracts the at least one sound component.

3. The device according to claim 2, wherein the sound source separation unit extracts the at least one sound component whose sound source directions are different from each other.

4. The device according to claim 3, further comprising a device detection unit that detects the at least one device imaged in the image data by performing image recognition on the image data.

5. The device according to claim 4, wherein the device detection unit detects each of the at least one device included in the image data by matching with a predetermined template.

6. The device according to claim 4, wherein the sound source identification unit identifies, for each of the at least one sound component, the device located in the region corresponding to the sound source direction in the image data among the at least one device as the device of the sound source.

7. The device according to claim 6, further comprising an input processing unit that receives input of information from a user for identifying a device in response to the fact that a device located in the region corresponding to the sound source direction in the image data cannot be identified for any of the at least one sound component.

8. The device according to claim 6, wherein the acoustic data acquisition unit and the image data acquisition unit acquire the acoustic data and the image data from a robot that can move within the facility to collect sound and capture images.

9. For any one of the at least one sound component, in response to the inability to identify the device that is the sound source among the at least one device, a robot command unit that instructs the robot to perform at least one of changing the imaging direction of the image, changing the imaging magnification of the image, or changing the position of the robot, according to the device according to claim 8.

10. A sound abnormality detection unit that detects the degree of abnormality of the sound component using the sound component data, and An abnormal device identification unit that identifies an abnormality of a device that is the sound source of the sound component based on the degree of abnormality of the sound component The device according to any one of claims 1 to 9, comprising.

11. In response to the identification of an abnormality of one device that is the sound source of the sound component, a device control unit that performs control for dealing with the abnormality of the one device on at least one of the one device or other devices in the facility, according to the device according to claim 10.

12. Obtaining acoustic data detected in the facility, Obtaining image data captured in the facility, Identifying which device among at least one device imaged in the image data is the sound source of each sound component among at least one sound component included in the acoustic data, Recording sound component data regarding each sound component among the at least one sound component in a device database in association with the device that is the sound source among the at least one device A method comprising.

13. Executed by a computer, the computer, An acoustic data acquisition unit that acquires acoustic data detected in the facility, An image data acquisition unit that acquires image data captured in the facility, A sound source identification unit that identifies which device among at least one device imaged in the image data is the sound source of each sound component among at least one sound component included in the acoustic data, A device database connection unit that records sound component data regarding each sound component among the at least one sound component in a device database in association with the device that is the sound source among the at least one device A program that causes it to function.

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