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

Abstract

SOLUTION: An apparatus includes: a device database connection section connected to a device database for recording a position of each of multiple devices in a facility and sound characteristic data corresponding to characteristics of sound as an object of abnormality detection; and a schedule determination section for determining a schedule of collecting the sound in the facility by each of a plurality of acoustic sensors on the basis of sound collection characteristics of each of the multiple acoustic sensors, the position of each of the multiple devices in the facility, and the sound characteristic data.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 in a facility.

Background Art

[0002] Patent Document 1 describes that "the patrol route scheduler 4 arranges, in the order of the on-site patrol route, the monitoring point numbers that are the individual recognition numbers of the respective monitoring devices, the position coordinates of the site where the monitoring device is installed, and the specific device item names for the device items to be monitored on the on-site patrol route according to the patrol route table 4a shown in FIG. 2" (paragraph 0025) and the like. [Prior Art Document] [Patent Document] [Patent Document 1] Japanese Unexamined Patent Application Publication No. 2000-39914

Summary of the Invention

[0003] In a first aspect of the present invention, there is provided an apparatus including: a device database connection unit connected to a device database that records, for each of a plurality of devices in a facility, position data within the facility and sound characteristic data corresponding to characteristics of sounds to be detected for abnormality; and a schedule determination unit that determines a schedule for collecting sounds within the facility by each of the plurality of acoustic sensors based on the sound collection characteristics of each of the plurality of acoustic sensors, the position data within the facility, and the sound characteristic data for each of the plurality of devices.

[0004] In the above apparatus, at least one of the plurality of acoustic sensors may have different sound collection characteristics from at least one other acoustic sensor.

[0005] In the above apparatus, each of the plurality of acoustic sensors may be mounted on each of a plurality of robots capable of moving within the facility.

[0006] In the above-described apparatus, the schedule determination unit may determine a schedule for collecting the sound of the one area by the one acoustic sensor based on at least one of the number or density of devices installed in one area within the facility and targeted for abnormality detection by one acoustic sensor.

[0007] Any of the above apparatuses may include a sound collection characteristic data adjustment unit that adjusts sound collection characteristic data indicating the sound collection characteristics of each acoustic sensor based on the result of abnormality detection using the acoustic data collected by each acoustic sensor.

[0008] In the above-described apparatus, the sound collection characteristic data adjustment unit may adjust the sound collection characteristic data according to the accuracy of abnormality detection of each device using the acoustic data collected by each of the acoustic sensors.

[0009] Any of the above apparatuses may include an abnormal device identification unit that identifies an abnormality of at least one of the plurality of devices based on the acoustic data collected by at least one of the plurality of acoustic sensors according to the schedule determined by the schedule determination unit.

[0010] The above-described apparatus may include 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 within the facility in response to the identification of the abnormality of the one device.

[0011] In a second aspect of the present invention, there is provided a method including a schedule determination step of determining a schedule for collecting the sound within the facility by each of the plurality of acoustic sensors based on the sound collection characteristics of each of the plurality of acoustic sensors, the positions within the facility of each of the plurality of devices within the facility, and sound characteristic data corresponding to the characteristics of the sound targeted for abnormality detection.

[0012] In a third aspect of the present invention, there is provided a program for causing a computer to function as a device database connection unit connected to a device database that records, for each of a plurality of devices in a facility, a location within the facility and sound characteristic data corresponding to characteristics of sound to be subjected to abnormality detection, and a schedule determination unit that determines a schedule for collecting sound within the facility by each of the plurality of acoustic sensors based on the sound collection characteristics of each of the plurality of acoustic sensors, the location within the facility, and the sound characteristic data for each of the plurality of devices.

[0013] 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 can also be inventions.

Brief Description of the Drawings

[0014]

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

Figure 7

Figure 8

Figure 9

Figure 10

Figure 11

Figure 12

Figure 13

Figure 14

Figure 15

Embodiments for Carrying Out the Invention

[0015] 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.

[0016] FIG. 1 shows a schematic configuration of the facility 1 according to this 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 wells and their surroundings in 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 facility 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.

[0017] A 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 under the control of 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, other devices, or an operator. Also, at least some of the devices 10 may be the field devices themselves.

[0018] 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 that capture objects such as the status of plants or facilities, acoustic devices such as microphones or speakers that collect abnormal sounds or emit alarm sounds in plants or facilities, position detection devices that output the position information of the devices possessed by the facility 1, or other devices. Also, the other devices 10 among the plurality of devices 10 may be structures such as pipes, storage tanks, supports, partition walls, or others that are not under the control of the control system 20.

[0019] The control system 20 is connected to at least one of the plurality of devices 10 that is to be controlled. The control system 20 may be, for example, a distributed control system (DCS). The control system 20 controls each device 10 according to the status of each device 10 measured by sensors or the like provided in each device 10 to be controlled.

[0020] Each of the one or more robots 30 is used to monitor at least some of the plurality of devices 10 within the facility 1. Each robot 30 can move within the facility 1 to collect sound and capture images and so on.

[0021] 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 wired Ethernet (registered trademark). The monitoring device 40 according to the present embodiment is installed inside the facility 1. Alternatively, the monitoring device 40 may be provided outside the facility 1 and remotely monitor each device 10 inside the facility 1. For example, the monitoring device 40 may be installed inside another facility, or may be realized by a cloud server on the Internet, for example.

[0022] The monitoring device 40 receives from each robot 30 the collected data such as acoustic data and image data collected by each robot 30 inside the facility 1, 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.

[0023] The monitoring device 40 uses a collected information database 50, a device database 60, and a robot database 70 to monitor each device 10 inside the facility 1 using the one or more robots 30. The collected information database 50 records the collected data collected from each robot 30. The device database 60 records device data about each device 10 inside 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, or may be temporarily stored in the memory of the monitoring device 40 or the like.

[0024] FIG. 2 shows the configuration of the control system 20 according to the present embodiment together with the display device 240 and the input device 250. The display device 240 displays a display screen output by the control system 20. The input device 250 inputs instructions to the control system 20 from a user such as an operator, a worker, or a maintenance staff of the facility 1 and supplies them 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 connected to the control system 20.

[0025] 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 in the computer. Instead of this, the control system 20 may be a dedicated computer designed for monitoring 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.

[0026] 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 from each device 10, such as internal state values of each device 10 and measurement values measured by sensors provided in each device 10. The state acquisition unit 210 may receive the device state data of each device 10 by using communication according to a communication protocol such as HART (registered trademark), BRAIN, Foundation Fieldbus (registered trademark), ISA100.11a. The state acquisition unit 210 may receive the device state data of the device 10 detected by the monitoring device 40 from the monitoring device 40 by using the collected data collected by the robot 30.

[0027] 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 normality or abnormality of the devices 10 determined by the monitoring device 40 using the collection data collected by the robot 30.

[0028] 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.

[0029] The instruction input unit 260 receives an instruction from a user to the control system 20 from the input device 250. Such an instruction may be, for example, an instruction from a 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 able to communicate 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.

[0030] 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.

[0031] Figure 3 shows the processing flow of the control system 20 according to the present 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.

[0032] 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.

[0033] 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 value and the measured value of each device 10, the health index for the entire facility 1 or a specific range within the facility 1, and the abnormal 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.

[0034] 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.

[0035] 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.

[0036] 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.

[0037] 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.

[0038] 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 the 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 to the outside 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.

[0039] 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 receiver that receives signals from GPS (Global Positioning System) 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.

[0040] 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.

[0041] 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.

[0042] 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.

[0043] The communication unit 440 is connected to the state acquisition unit 430. The communication unit 440 performs wireless or wired communication with the monitoring device 40. The communication unit 440 transmits 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.

[0044] The control unit 450 controls each actuator 420 according to various measurement data acquired by the state acquisition unit 430 and 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 instructions from the monitoring device 40.

[0045] 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 processes and the like within the scope of the implemented functions.

[0046] 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.

[0047] In S510, the communication unit 440 transmits various measurement data indicating the state inside 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.

[0048] 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 and the direction of the robot 30 do not necessarily coincide. 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.

[0049] 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 to move, an instruction to change direction, an instruction to change the direction of an acoustic sensor, 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.

[0050] 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.

[0051] 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 to 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.

[0052] 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.

[0053] 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 a robot group including each robot 30 or two or more robots 30 on site.

[0054] The monitoring device 40 may be an example of a device, and 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.

[0055] The acoustic data acquisition unit 602 acquires acoustic data detected by each of a plurality of acoustic sensors within Facility 1. Each of the plurality of acoustic sensors may be an acoustic sensor 400a mounted on each of a plurality of robots 30 that can move within the facility. Each acoustic sensor 400a may be mounted on a separate robot 30. Alternatively, two or more acoustic sensors 400a may be mounted on a common robot 30. The acoustic data acquisition unit 602 may acquire acoustic data by receiving the acoustic data transmitted by the robot 30.

[0056] Here, each acoustic sensor 400a may be a sensor that detects sound and may output acoustic data corresponding to the detected sound. Each acoustic sensor may be a piezoelectric sensor such as a microphone, or may be another sensor. At least one of the plurality of acoustic sensors 400a may have different sound collection characteristics from at least one other acoustic sensor 400a. The sound collection characteristic may be a characteristic of how much sound can be collected, and may be, for example, at least one of directivity, sensitivity, frequency characteristic, or dynamic range. The directivity may indicate the relationship between the orientation of the acoustic sensor 400a with respect to the sound source and the sound collection performance. The sensitivity may indicate the ratio of the sound pressure to the output value. The sensitivity may also indicate the area of the collectible sound. The frequency characteristic may indicate the relationship between the frequency and the sound collection performance. The dynamic range may indicate the range of the magnitude of the detectable sound. Among the plurality of acoustic sensors 400a, at least one acoustic sensor 400a may have different other characteristics (for example, at least one of durability, accuracy, temperature characteristic, and noise characteristic) from at least one other acoustic sensor 400a.

[0057] The image data acquisition unit 604 acquires the image data captured within Facility 1. The image data acquisition unit 604 may acquire the image data by receiving the image data transmitted by the robot 30. The LiDAR data acquisition unit 606 acquires the LiDAR data detected by the sensor 400c of the robot 30 within Facility 1. The LiDAR data acquisition unit 606 may acquire the LiDAR data by receiving the LiDAR data transmitted by the robot 30.

[0058] The position data acquisition unit 608 acquires the position data indicating the position of the robot 30. The position data acquisition unit 608 may acquire the position data by receiving the position data transmitted by the robot 30. The direction data acquisition unit 610 acquires the direction data indicating the directions of the robot 30 and each sensor 400. The direction data acquisition unit 610 may acquire the direction data by receiving the direction data transmitted by the robot 30. The instruction transmission unit 612 transmits the instruction for the robot 30 determined within the monitoring device 40 to the robot 30.

[0059] 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 the various measurement data acquired 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 within the communication unit 600 as collected data in the collected information database 50. Also, 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 if the monitoring device 40 does not need to record the history of the collected data, it may not be provided with the collected information database connection unit 620, and the measurement data acquired 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.

[0060] 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.

[0061] 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 that each robot 30 should execute using the robot data. The monitoring processing unit 650 instructs each robot 30 to perform each operation included in the determined monitoring actions via the instruction transmission unit 612 in the communication unit 600.

[0062] Also, the monitoring processing unit 650 reads out the collected data collected by one or more robots 30 and recorded in the collected information database 50 via the collected information database connection unit 620. Then, the monitoring processing unit 650 detects the state of each device 10 monitored by each robot 30 using the collected data. The monitoring processing unit 650 determines whether each device 10 is normal or not using the collected 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.

[0063] 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.

[0064] When the monitoring processing unit 650 monitors each device 10 using one or a plurality of robots 30 and detects an abnormality in at least one device 10, it may generate an instruction to perform control for dealing with the abnormality. 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.

[0065] The input processing unit 660 is connected to the input device 680. The input processing unit 660 receives input of information from the user to the input device 680 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.

[0066] 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. When an abnormality is detected in at least one device 10, the communication unit 670 may transmit an instruction to perform control for dealing with the abnormality to the control system 20. 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 the 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.

[0067] According to the monitoring device 40 shown above, by monitoring the inside of the facility 1 using one or more 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 pre-installed in each device 10.

[0068] 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".

[0069] "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 direction" is a field that records at least one of the position and direction of the robot 30 or each sensor 400 at the timing when the measurement data of the corresponding record was acquired. The collected information database 50 may record, as "position and direction", 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".

[0070] "Robot identification information" is a field that records data values such as an identification number, serial number, or other unique number or character string that can identify the robot 30 that acquired the measurement data of the corresponding record. "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 measurement data acquired by the robot 30, such as at least one of acoustic data, image data, or LiDAR data.

[0071] 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 the measurement data by the robot 30, the robot identification information of the robot 30, and the measurement data regarding the position and orientation of the robot 30, and data including the acquisition date and time of the measurement data by the robot 30, the robot identification information of the robot 30, and the measurement data regarding the state within the facility 1. In this case, each time the communication unit 600 receives the measurement data regarding 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 the measurement data regarding 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.

[0072] 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 in 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", "location", "template", "acoustic data", and "acoustic characteristic data".

[0073] "Device identification information" is a field for recording data values such as identification numbers, serial numbers, or other unique numbers or character strings that can identify the corresponding device 10 within the facility 1. "Device name" is a field for recording the device name assigned to the corresponding device 10 by a user or the like.

[0074] "Device information" is a field for recording various information regarding the corresponding device 10. "Location" is a field for recording the location of the device 10 within the facility 1. The location of the device 10 recorded in the "location" field may further indicate the area to which the device 10 belongs among the plurality of areas (for example, floors, rooms, and sections within a building) included in the facility 1.

[0075] "Template" is a field for recording image data of the appearance of the corresponding device 10 (template image data) 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. "Sound characteristic data" is a field for recording sound characteristic data corresponding to the characteristics of the sound to be detected for abnormalities of the corresponding device 10. The sound to be detected for abnormalities of the device 10 may be the operating sound when the device 10 is at least one of normal or abnormal, and may be the sound recorded in the "acoustic data". The characteristics of the sound may be sound pressure, pitch, and timbre, and the sound characteristic data may indicate at least one of these. The sound pressure may be the variation of the pressure generated by the sound wave from the static pressure, and may be the magnitude of the amplitude of the sound waveform. The pitch of the sound may be the height of the frequency of the sound waveform. The timbre may be determined by the shape of the sound waveform.

[0076] FIG. 9 shows an example of the data structure of the robot database 70 according to the present 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, a 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 Orientation" is a field that records the position and orientation of the corresponding robot 30 within Facility 1, and, if necessary, the orientation of each sensor 400 (absolute orientation or offset with respect to the orientation of robot 30). "Acoustic Sensor Identification Information" is a field that records data values such as an identification number, serial number, or other unique number or character string that can identify the acoustic sensor 400a mounted on the corresponding robot 30 within Facility 1. "Sound Collection Characteristics" is a field that records the sound collection characteristics of the acoustic sensor 400a mounted on the corresponding robot 30. The sound collection characteristics may be characteristics such as how much sound the acoustic sensor 400a can collect, and may be at least one of directivity, sensitivity, or frequency characteristics. "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] Figure 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, a robot command unit 1060, a schedule determination unit 1065, and a sound collection characteristic data adjustment unit 1070.

[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 orientation 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. Thereby, 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. When 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 components using the sound component data associated with each device 10. The abnormal sound detection unit 1030 may detect the degree of abnormality of the sound components of the acoustic data detected by the selected acoustic sensor 440a among a plurality of acoustic sensors (in this embodiment, a plurality of acoustic sensors 400a as an example). The abnormal sound detection unit 1030 may detect the degree of abnormality of the sound components of the acoustic data detected by the acoustic sensor 400a pre-selected in the schedule determined by the robot command unit 1060 described later.

[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 at least one of the plurality of devices 10 based on the acoustic data detected by at least one of the plurality of acoustic sensors (in this embodiment, a plurality of acoustic sensors 400a as an example) according to a pre-determined schedule. The abnormal device identification unit 1040 may identify 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. Identifying the abnormality of the device 10 may mean identifying whether the device 10 is abnormal, or identifying the abnormal device 10 as abnormal. The schedule may be determined by the robot command unit 1060 described later. 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. In response to the identification of an abnormality in any one of the devices 10 that is the sound component generation source, the device control unit 1050 performs control for dealing with the abnormality of the one device 10 on at least one of the one device 10 or other devices 10 in the facility 1. The device control unit 1050 transmits an instruction to perform 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 generation source identification unit 1020. The robot command unit 1060 determines the operations to be performed by each robot 30 and instructs each robot 30 to perform the determined operations.

[0087] In response to the generation source identification unit 1020 being unable to identify the device 10 that is the sound generation source, 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. The robot command unit 1060 may refer to the data recorded in the collection information database 50 and instruct the robot 30 to change the imaging direction or the like. The robot command unit 1060 may record the determined robot-specific schedule in the robot database 70 via the robot database connection unit 640. The robot command unit 1060 may read the schedule from the robot database 70 and instruct each robot 30 about the content of the schedule corresponding to the current time.

[0088] The schedule determination unit 1065 is connected to the device database connection unit 630 and the robot database connection unit 640. Based on the sound collection characteristics of each of the plurality of acoustic sensors 400a and the position and sound characteristic data of each of the plurality of devices 10 within the facility 1, the schedule determination unit 1065 determines a schedule for each of the plurality of acoustic sensors 400a to collect sound within the facility 1. The schedule determination unit 1065 may determine a schedule (also referred to as a robot-specific schedule) for each robot 30, and may determine a schedule (also referred to as an overall schedule) for the entire robots 30 within the facility 1 by determining the robot-specific schedule for each robot 30. The robot-specific schedule may include information necessary to determine the operation of the robot 30, such as the position of each observation point where the target robot 30 should observe the state (e.g., sound collection) within the facility 1, the time to arrive at each observation point, the movement path between the observation points, or the observation direction at each observation point. The schedule determination unit 1065 may obtain the position and sound characteristic data of each device 10 from the device database 60 via the device database connection unit 640.

[0089] The sound collection characteristic data adjustment unit 1070 is connected to the abnormal device identification unit 1040 and the input processing unit 660. Based on the result of abnormality detection by the acoustic data collected by each acoustic sensor 400a, the sound collection characteristic data adjustment unit 1070 adjusts the sound collection characteristic data indicating the sound collection characteristics of each acoustic sensor 400a. The sound collection characteristic data adjustment unit 1070 may adjust the sound collection characteristics stored in the robot database 70.

[0090] The sound collection characteristic data adjustment unit 1070 may adjust the sound collection characteristic data according to the accuracy of abnormality detection of each device 10 based on the acoustic data collected by each acoustic sensor 400a. The sound collection characteristic data adjustment unit 1070 may adjust any value of the sound collection characteristics stored in the robot database 70 for a certain acoustic sensor 400a to be lower than the current value according to the low accuracy of abnormality detection by the certain acoustic sensor 400a. As an example, the sound collection characteristic data adjustment unit 1070 may adjust to lower the sensitivity, or may adjust the frequency characteristics to lower the sound collection performance for the frequency components included in the sound at the time of abnormality. The accuracy of abnormality detection may be the accuracy rate (Accuracy, the ratio of how many of the detection results are correct out of the number of times of detecting normal and abnormal), or may be the precision rate (Precision, the ratio of actually being abnormal out of the number of times detected as abnormal), or may be the recall rate (Recall, the ratio of being correctly detected as abnormal out of the number of times actually being abnormal), or may be a value combining these.

[0091] The sound collection characteristic data adjustment unit 1070 may obtain from the user whether an abnormality has actually occurred or not via the input processing unit 660. Note that the initial value of the sound collection characteristics stored in the robot database 70 may be a value obtained from the manufacturer of the acoustic sensor 400a, or may be a value arbitrarily set by the user. The sound collection characteristic data adjustment unit 1070 may update the sound collection characteristic data based on the accuracy within the period each time the reference period elapses, or may update the sound collection characteristic data based on the accuracy of the previous period according to a user operation.

[0092] In order to realize each function such as specifying the device 10 that is the generation source of each sound component, specifying the abnormality of the device 10 of the generation source based on the abnormality degree of the sound component, instructing control for coping with the abnormality of the device 10, and instructing the operation for each robot 30, the monitoring processing unit 650 shown above has each component shown in FIG. 10. Instead of this, the monitoring processing unit 650 may adopt a configuration that does not have some of the components shown in FIG. 10.

[0093] For example, the monitoring processing unit 650 may not have the device control unit 1050 and may not issue an instruction for control to address 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 sound abnormality detection unit 1030 and the abnormal device identification unit 1040 and may not identify an abnormality of the device 10 that is the 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 the 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.

[0094] 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 in various locations in the facility 1, and can promptly address the abnormalities of the devices 10.

[0095] Also, for each of the plurality of devices 10, the position in the facility 1 and the sound characteristic data are recorded, and based on the sound collection characteristics of each of the plurality of acoustic sensors 400a and the position and sound characteristic data for each device 10, a schedule for collecting the sound in the facility 1 by each of the plurality of acoustic sensors 400a is determined. Therefore, it is possible to determine a schedule in which the sound of the device 10 can be measured by the acoustic sensor 400a suitable for the position and sound characteristic data of each device 10, and perform abnormality detection with high accuracy.

[0096] In addition, since at least one of the plurality of acoustic sensors 400a has different sound collection characteristics from at least one other acoustic sensor 400a, therefore, a schedule for measuring the sound of the device 10 with the acoustic sensor 400a suitable for sound collection can be determined, and abnormality detection can be performed with high accuracy.

[0097] In addition, each of the plurality of acoustic sensors 400a is mounted on each of the plurality of robots 30 that can move within the facility 1. Therefore, by moving the robot 30 equipped with the selected acoustic sensor 400a within the facility 1 to collect sound, an abnormality can be specified based on the acoustic data detected by the appropriate acoustic sensor 400a.

[0098] In addition, since the sound collection characteristic data indicating the sound collection characteristics of each acoustic sensor 400a is adjusted based on the result of abnormality detection using the acoustic data collected by each acoustic sensor 400a, a schedule can be determined based on the actual sound collection characteristics.

[0099] In addition, since the sound collection characteristic data is adjusted according to the accuracy of abnormality detection of each device 10 using the acoustic data collected by each acoustic sensor 400a, a schedule for measuring the sound of the device 10 with the acoustic sensor 400a that can perform abnormality detection more accurately can be determined, and abnormality detection can be performed with high accuracy.

[0100] In addition, since an abnormality of at least one device 10 is specified based on the acoustic data collected by at least one of the plurality of acoustic sensors 400a according to the determined schedule, it is possible to prevent the target device 10 from being left in an abnormal state.

[0101] In addition, in response to the specification of an abnormality of one device 10, control for dealing with the abnormality of the one device 10 is performed on at least one of the one device 10 or other devices 10, so that the abnormality occurring in the one device 10 can be promptly dealt with.

[0102] FIG. 11 shows a processing flow for determining an overall schedule. Note that the schedule determination unit 1065 may start the operation of this processing flow according to a user operation, may perform it for each reference interval, or may perform it each time the sound collection characteristic data is updated by the sound collection characteristic data adjustment unit 1070 by a reference number of times.

[0103] In S1000, the schedule determination unit 1065 extracts one or more robots 30 in the facility 1 as the robots 30 to be used in the schedule. Note that if the processing after S1000 is repeated and the processing of S1000 is performed multiple times, the schedule determination unit 1065 may select different robots 30 in each S1000, or may select a common robot 30 in two or more S1000s. The schedule determination unit 1065 may select the robots 30 randomly.

[0104] In S1005, the schedule determination unit 1065 selects any one of the extracted robots 30 as the robot 30 for sound collection. Note that if the processing after S1005 is repeated and the processing of S1005 is performed multiple times, the schedule determination unit 1065 may select different robots 30 in each S1005.

[0105] In S1010, the schedule determination unit 1065 selects at least one of the plurality of devices 10 in the facility 1 as a sound collection target. The schedule determination unit 1065 may select at least one device 10 randomly.

[0106] Instead, the schedule determination unit 1065 may select at least one device 10 based on the position and sound characteristic data in the facility 1 recorded in the device database 60 for each of the plurality of devices 10, and the sound collection characteristics recorded in the robot database 70 for the acoustic sensor 400a (also referred to as the acoustic sensor 400a for sound collection) mounted on the sound collection robot 30. For example, the schedule determination unit 1065 may exclude each device 10 that generates a sound that cannot be detected by the acoustic sensor 400a for sound collection from among the plurality of devices 10, and select at least one other device 10 as the sound collection target. As an example, the schedule determination unit 1065 may exclude the device 10 that generates a sound of a magnitude that cannot be detected by the acoustic sensor 400a for sound collection based on the sensitivity of the acoustic sensor 400a for sound collection, the position of each device 10, and the loudness of the sound. The schedule determination unit 1065 may also exclude the device 10 that generates a sound of a pitch that cannot be detected by the acoustic sensor 400a for sound collection based on the frequency characteristics of the acoustic sensor 400a for sound collection and the pitch of the sound of each device 10. When a plurality of acoustic sensors 400a for sound collection are mounted on the sound collection robot 30, the schedule determination unit 1065 may exclude the device 10 that generates a sound that cannot be detected by any of the acoustic sensors 400a for sound collection from among the plurality of devices 10, and select at least one other device 10 as the sound collection target.

[0107] Note that when the processes after S1005 are repeated and the process of S1010 is performed multiple times, different devices 10 may be selected in each process of S1010, or at least one device 10 may be commonly selected in the processes of S1010 two or more times.

[0108] In S1020, the schedule determination unit 1065 determines the patrol route of the sound collection robot 30. The schedule determination unit 1065 may determine the patrol route so that the sound collection robot 30 for sound collection collects the sounds of each device 10 to be sound-collected. Based on the positions of each device 10 recorded in the device database 60, the schedule determination unit 1065 determines the sound collection position (also referred to as the observation point) for each device 10, and may determine the movement route between the sound collection positions so as to connect the sound collection positions. The schedule determination unit 1065 may determine the movement route between the sound collection positions so that the patrol route is the shortest as a whole. The schedule determination unit 1065 may determine the patrol route including these sound collection positions and movement routes. The schedule determination unit 1065 may preferably set the patrol route as an annular route as a whole, and may set the starting point and the return point of the sound collection robot 30 as the charging position of the robot 30.

[0109] In S1030, the schedule determination unit 1065 determines the sound collection time for each device 10 to be sound-collected, that is, the stay time of the robot 30 at the sound collection position, and the movement speed between the sound collection positions. Thereby, the time required for the sound collection robot 30 to circle the patrol route (also referred to as the patrol required time) is determined, and a temporary schedule (also referred to as a temporary robot-specific schedule) for the sound collection robot 30 to perform sound collection is determined. The temporary robot-specific schedule may include the identification information of the acoustic sensor 400a for sound collection, the identification information of the device 10 to be sound-collected, the patrol route, the stay time at each sound collection position, the movement speed between the sound collection positions, the patrol required time, and the charging position of the sound collection robot 30. The temporary robot-specific schedule may not include time information.

[0110] The scheduling determination unit 1065 may set the same sound collection time for each device 10 to be sound-collected, or may set different sound collection times for at least two devices 10. Based on the positions of the devices 10 to be sound-collected recorded in the device database 60, the scheduling determination unit 1065 may calculate the number or density of the devices 10 to be sound-collected in each area within the facility 1, and may determine the sound collection time within the area by the sound collection robot 30 based on the calculation result. For example, the scheduling determination unit 1065 may determine to make the sound collection time for each device 10 longer in an area with a large number of devices 10 or a high density, and may determine to make the sound collection time for each device 10 shorter in an area with a small number of devices 10 or a low density. Thereby, based on the number or density of the devices 10 installed in one area within the facility 1 and targeted for abnormality detection by the acoustic sensor 400a for sound collection, a temporary schedule for the acoustic sensor 400a to collect the sound of the one area is determined.

[0111] The scheduling determination unit 1065 may set the same moving speed for each section between the sound collection positions, or may set different moving speeds for at least two sections. The scheduling determination unit 1065 may determine the moving speed between the sound collection positions to be equal to or lower than the maximum speed of the sound collection robot 30.

[0112] The scheduling determination unit 1065 may determine the stay time and the moving speed so that the total tour time satisfies formula (1) or formula (2). Thereby, the sound collection of the devices 10 to be sound-collected can be periodically performed by a single sound collection robot 30.

[0113] Total tour time ≤ Allowable confirmation period (1) Total tour time ≤ Allowable confirmation period - Charging time required (2)

[0114] The allowable confirmation period in formulas (1) and (2) may be the longest period allowed to confirm the state of device 10, and may be the same among each device 10, but may also be different among at least two devices 10. When the allowable confirmation periods are different among the devices 10, the shortest allowable confirmation period among the allowable confirmation periods of each device 10 selected as the sound collection target in S1010 may be used in formulas (1) and (2). The charging time required in formula (2) may be the time required to charge the sound collection robot 30, and may be the same among each robot 30, or may also be different among at least two robots 30. When the charging times required are different among the robots 30, the charging time required for the sound collection robot 30 selected in S1005 may be used in formula (2).

[0115] In addition, when the process after S1005 is repeated and the process of S1030 is performed multiple times, the residence time, moving speed, and round-trip time determined in each process of S1030 may be the same as each other, or at least one of the residence time, moving speed, or round-trip time determined in at least two processes of S1030 may be different from each other.

[0116] Depending on the device 10 selected as the sound collection target in S1010, there may be a case where the schedule determination unit 1065 cannot determine the residence time and moving speed such that the moving speed between the sound collection positions is less than or equal to the maximum speed of the sound collection robot 30 and the round-trip time satisfies formula (1) or formula (2). In this case, the schedule determination unit 1065 may determine a temporary robot-specific schedule by associating an error code.

[0117] In S1040, the schedule determination unit 1065 determines whether all the robots 30 extracted in S1000 have been selected. If there are still unselected robots 30 (\"N\" in S1040), the schedule determination unit 1065 returns the process to S1005. As a result, in S1005, the unselected robots 30 are selected as the sound collection robots 30, and a temporary schedule for each robot 30 is determined. Consequently, a temporary schedule (also referred to as a temporary overall schedule) for all the extracted robots 30 is determined. If not all the robots 30 in Facility 1 have been extracted in S1000 described above, the temporary overall schedule may not include the temporary robot-specific schedules for all the robots 30. If all the robots 30 have been selected in S1040 (\"Y\" in S1040), that is, if the temporary overall schedule has been determined, the schedule determination unit 1065 advances the process to S1050.

[0118] In S1050, the schedule determination unit 1065 calculates an evaluation value of the determined temporary overall schedule based on a preset evaluation function. The schedule determination unit 1065 may associate the content of the temporary overall schedule with the calculated evaluation value and store it in a storage unit (not shown).

[0119] The schedule determination unit 1065 may calculate the evaluation value of the temporary overall schedule based on the sound collection characteristics of each of the plurality of acoustic sensors 400a, the positions within Facility 1 of each of the plurality of devices 10 in Facility 1, and the sound characteristic data corresponding to the characteristics of the sound to be subject to abnormality detection. The schedule determination unit 1065 may extract each combination of the device 10 to be the sound collection target and the acoustic sensor 440a for sound collection from the temporary overall schedule, and calculate an evaluation value corresponding to the position within Facility 1 and the sound characteristic data of each of the devices 10 to be the sound collection target and the sound collection characteristics of the acoustic sensor 400a for sound collection.

[0120] In this case, the evaluation function may be a function in which the evaluation value increases as the degree of compatibility between the position and sound characteristics of the device 10 to be sound-collected and the sound-collecting characteristics of the acoustic sensor 400a for sound collection increases. The degree of compatibility may be the detection accuracy of the sound of the device 10 estimated based on the position and sound characteristics of the device 10 and the sound-collecting characteristics of the acoustic sensor 400a. The degree of compatibility may be a value corresponding to the sensitivity of each frequency indicated by the frequency characteristics of the acoustic sensor 400a for the sensitivity of each frequency component of the sound of the device 10. When the sound of the device 10 includes a plurality of frequency components, the degree of compatibility may increase as the sum of the sensitivities for each frequency component increases. The degree of compatibility may also be a value corresponding to the magnitude of the output value output in response to the acoustic sensor 400a arranged at the sound collection position detecting the sound of the device 10. The magnitude of the output value may be calculated from the distance between the sound collection position of the acoustic sensor 400a and the position of the device 10, the sensitivity of the acoustic sensor 400a for sound collection, and the magnitude of the sound of the device 10. The degree of compatibility may also be a value corresponding to whether or not the magnitude of the sound of the device 10 is included in the dynamic range of the acoustic sensor 400a. As an example, it may be a value corresponding to the distance between the magnitude of the sound of the device 10 and the upper and lower limit values of the dynamic range. The position and sound characteristic data of the device 10 may be read from the device database 60, and the sound-collecting characteristics of the acoustic sensor 400a may be read from the robot database 70. When a plurality of acoustic sensors 400a are mounted on the sound-collecting robot 30, the schedule determination unit 1065 may calculate an evaluation value by excluding the degrees of compatibility that are the second highest and lower among the degrees of compatibility of these plurality of acoustic sensors 400a. The evaluation function may also be a function in which the evaluation value increases as the total movement distance of each robot 30 when the temporary overall schedule is executed is shorter. The total movement distance of each robot 30 may be calculated from the tour route of each temporary robot-specific schedule, and the tour route may be determined from the positions of each device 10 to be sound-collected.

[0121] The schedule determination unit 1065 may calculate an evaluation value corresponding to the number of robots 30 used in the temporary overall schedule. In this case, the evaluation function may be a function in which the evaluation value increases as the number of robots 30 is smaller (or larger).

[0122] The schedule determination unit 1065 may extract devices 10 that are redundantly sound-collected by a plurality of robots 30 when the provisional overall schedule is executed, and calculate an evaluation value according to the number thereof. In this case, the evaluation function may be a function in which the evaluation value increases as the number of devices 10 that are redundantly sound-collected decreases (or increases).

[0123] The schedule determination unit 1065 may extract the number of devices 10 that are not sound-collected when the provisional overall schedule is executed, and calculate an evaluation value according to the number thereof. In this case, the evaluation function may be a function that sets the evaluation value to zero according to the fact that the number of devices that are not sound-collected is 1 or more.

[0124] The schedule determination unit 1065 may calculate an evaluation value according to the number of provisional robot-specific schedules associated with error codes among the provisional robot-specific schedules included in the provisional overall schedule. In this case, the evaluation function may be a function that sets the evaluation value to zero according to the fact that the number of provisional robot-specific schedules associated with error codes is 1 or more.

[0125] In S1060, the schedule determination unit 1065 determines whether the creation end condition of the temporary overall schedule is satisfied. The creation end condition may be, for example, that among all combinations of each device 10 in facility 1 and each robot 30, there is no combination that has not been selected as the device 10 to be sound-collected and the sound-collecting robot 30 in the determined temporary overall schedule. The creation end condition may further include that the number of determined temporary overall schedules with a non-zero evaluation value is equal to or greater than a reference number. The reference number may be set arbitrarily. The creation end condition may be that a preset time for creating the schedule has elapsed since the start of the operation. The creation end condition may be that as a result of repeatedly performing the processes of S1000 to S1060 over a reference time, the maximum value of the evaluation value calculated in S1050 is no longer updated. If the creation end condition is not satisfied (''N'' in S1060), the schedule determination unit 1065 returns the process to S1000. In this case, the schedule determination unit 1065 may reset the selection history of the robot 30 in S1000. Thereby, a new robot 30 is selected in S1000, and a new temporary overall schedule is determined. The schedule determination unit 1065 may perform S1000 to S1050 so that at least part of the content is different from the determined temporary overall schedule, and determine a new temporary overall schedule. If the creation end condition is satisfied in S1060 (''Y'' in S1060), the schedule determination unit 1065 advances the process to S1070.

[0126] In S1070, the schedule determination unit 1065 determines, as the target for use, a provisional overall schedule that satisfies predetermined conditions among the determined provisional overall schedules. The schedule determination unit 1065 may determine, based on the evaluation value calculated in S1050, any one of the provisional overall schedules as the target for use. Thereby, based on the respective sound collection characteristics of the plurality of acoustic sensors 400a, the positions within the facility 1 for each of the plurality of devices 10 within the facility 1, and the sound characteristic data corresponding to the characteristics of the sound to be the target of abnormality detection, a schedule for collecting the sound within the facility 1 by each of the plurality of acoustic sensors 400a is determined. The schedule determination unit 1065 may use, as the target for use, the provisional overall schedule with the largest evaluation value, or may use, as the target for use, the provisional overall schedule whose evaluation value is equal to or greater than the reference value and whose total moving distance of each robot 30 when the provisional overall schedule is executed is the shortest.

[0127] In S1080, for each provisional robot-specific schedule included in the provisional overall schedule determined as the target for use, the schedule determination unit 1065 sets the departure time of the robot 30 at a period equal to or shorter than the allowable confirmation period, and determines it as the robot-specific schedule. The schedule determination unit 1065 may align the departure times among the respective robot-specific schedules, or may make the departure times different between at least two robot-specific schedules. When there is a robot 30 among the robots 30 within the facility 1 for which the provisional robot-specific schedule has not been determined within the provisional overall schedule, the schedule determination unit 1065 may determine, for the robot 30, a robot-specific schedule for waiting at a charging position or the like. Thereby, the overall schedule is determined by the plurality of determined robot-specific schedules. The schedule determination unit 1065 may record the determined respective robot-specific schedules in the robot database 70 via the robot database connection unit 640.

[0128] According to the above operation, based on at least one of the number or density of the devices 10 installed in one area within the facility 1 and targeted for abnormality detection by one acoustic sensor 400a, a schedule for collecting the sound of the one area by the one acoustic sensor 400a is determined. Therefore, since the schedule can be determined according to the ease of sound collection within the area, the accuracy of abnormality detection in an area with many devices 10 or an area where the devices 10 are concentrated can be improved, and the sound collection time in an area with few devices 10 or an area where the devices 10 are sparse can be shortened.

[0129] In addition, in the above operation, the schedule determination unit 1065 is described as performing processes such as determining to increase the sound collection time for each device 10 in an area with a large number of devices 10 to be collected or an area with a high density in S1030 in order to determine the sound collection schedule within the one area based on the number or density of the devices 10 installed in the one area and targeted for sound collection by the one acoustic sensor 400a, but other processes may be performed. For example, in S1080, the schedule determination unit 1065 may shorten the cycle of the departure time in the robot-specific schedule passing through an area with a large number of devices 10 to be collected or an area with a high density compared to other robot-specific schedules.

[0130] Also, in the above operation, the case where one or more acoustic sensors 400a are mounted on each robot 30 has been described, but a single acoustic sensor 400a may be mounted on each robot 30. In this case, in S1005, the schedule determination unit 1065 may select the acoustic sensor 400a instead of selecting the robot 30.

[0131] Figures 12 and 13 show the processing flow of the monitoring device 40 according to the present embodiment. The processing flows of FIGS. 12 and 13 may be the processing flows when instructions are given to the robot 30 according to the schedule determined by the schedule determination unit 1065. Note that the processing flows of FIGS. 12 and 13 show the case where the monitoring device 40 performs monitoring in the facility 1 using one robot 30 for convenience of explanation. The monitoring device 40 may execute the processing flows of FIGS. 12 and 13 for each of the plurality of robots 30.

[0132] 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. In this operation, 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 be processed to patrol within the facility 1. 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 perform observation at the next observation point to the robot 30. In response to this, the robot 30 moves to the next observation point (see S520 and S530 in FIG. 5).

[0133] In S1110, the robot 30 observes the state inside 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 inside 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 in the monitoring device 40 acquires acoustic data from among the measurement data transmitted from the robot 30. When a plurality of acoustic sensors 400a are mounted on the robot 30, the acoustic data acquisition unit 602 may acquire the acoustic data detected by each of the plurality of acoustic sensors 400a, or may acquire the acoustic data detected by the acoustic sensor 400a having the highest above-described fitness for the device 10 to be sound-collected at the observation point. 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.

[0134] In S1120, the sound source separation unit 1000 extracts at least one sound component by performing sound source separation etc. 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 mutually different directions of the sound source 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).

[0135] Here, 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, so that it collects the sound synthesized from 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 that is the data of the sound collected by the sensor 400a and the sound component data that is the data of the sound component may be in the same data format.

[0136] 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.

[0137] 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 calculates 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 adds it to the absolute direction (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 angles in the horizontal and vertical directions with north as a reference. The relative direction means an angle represented starting from an arbitrarily selected reference direction (such as the traveling direction of the robot 30).

[0138] In addition, the robot 30 may have a sensor 400a such as a directional microphone, and may 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 captured 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.

[0139] By separating the acoustic data into sound sources in this way, the monitoring device 40 can identify the sound components originating from each device 10 even when it acquires acoustic data in which sounds from two or more devices 10 are superimposed. As a result, 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.

[0140] 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.

[0141] In S1140, the device detection unit 1010 detects one or two or more devices 10 imaged in the image data by performing image recognition or the like on the image data from the robot 30. The device detection unit 1010 may extract one or two or more objects imaged in the image data and search the device database 60 for the device 10 corresponding to each object to 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.

[0142] 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 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.

[0143] 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.

[0144] 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, piping, or flange, etc.) or model of the device 10 corresponding to the object from the external 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 specify the type or model of the device. The monitoring device 40 can extract, from the image data, a device 10 that is installed in the facility 1 but not registered and a part of a device 10 that has not been recognized as a failure unit that can emit abnormal sounds and is not registered as an individual device 10, by performing image recognition on the image data using template matching or the like, and make it detectable as the sound source.

[0145] 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 viewed 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.

[0146] 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 in 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 may determine 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 as seen 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 the device 10 is located in the absolute direction of the sound component as seen from the observation point of the acoustic data.

[0147] 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 may determine 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, the sound source identification unit 1020 may determine that the sound source of this sound component is this device 10 when the distance from the observation point of the image data to this intersection position is within the calculated distance range. The monitoring device 40 can identify the device 10 that is the sound source of each sound component by using the local acoustic data and image data observed by the robot 30 at the observation point, so that 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 manifest as information usable for the management of each device 10.

[0148] 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 appending the acquisition date and time of the sound component data and the sound component data to the acoustic data field.

[0149] 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.

[0150] In S1200, the sound abnormality detection unit 1030 detects the abnormality degree of the sound component using the sound component data associated with each device 10. Here, the abnormality degree 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.

[0151] When 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 abnormality degree, 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 abnormality degree according to the comparison result between the acoustic data during normal times and the sound component data of the target.

[0152] 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 abnormality degree. In this case, the sound abnormality detection unit 1030 may adjust the amplitude so that, for example, the average amplitudes match in order to match the loudness of the sound of the acoustic data and the sound component data of the target.

[0153] 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 the difference (such as the absolute value of the difference) for each frequency 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.

[0154] 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 with the device 10 as the sound source is from the one or more pieces of 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 way 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 times described above.

[0155] 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, etc. for each of a predetermined number of pieces of acoustic data with 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, dissimilarity, similarity, or degree of deviation, etc. between two sounds.

[0156] 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.

[0157] 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 the 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.

[0158] Note that the machine learning model may output the degree of abnormality of the sound component in response to input of 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, instead of being prepared for each individual device 10, the machine learning model may be prepared for each type or model of the device 10. Further, the machine learning model may be common to all the devices 10.

[0159] 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 degree of abnormality. The sound abnormality detection unit 1030 may calculate the degree of abnormality based on the difference between the normal acoustic data and the target sound component data using any other method.

[0160] 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 degree of abnormality 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.

[0161] 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 degree of abnormality of the sound component associated with the device 10. For example, when the degree of abnormality 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. When the degree of abnormality of the sound component is equal to or less than the predetermined threshold, the abnormal device identification unit 1040 may identify that the device 10 that is the sound source of the sound component is normal.

[0162] 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, and image) about one or more devices 10 that have been identified as the source of a 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. If there is an error in the status of each device 10 displayed on the display device 690, an input indicating that the displayed status is incorrect may be made via the input processing unit 660 for at least one device 10.

[0163] 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 (''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.

[0164] 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 to address the abnormality of the device 10 for at least one of the device 10 in which the abnormality is identified or other devices 10. The device control unit 1050 transmits an instruction to perform control to address the abnormality of the device 10 to the control system 20 via the communication unit 670.

[0165] 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 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 content of the control instructed to the control system 20 may be preset for each device 10, and the device control unit 1050 may instruct the control system 20 to perform the control corresponding 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 in the facility 1 by the robot 30.

[0166] 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.

[0167] 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, when 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.

[0168] 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 information that has already been determined, in the device database 60.

[0169] In addition, the input processing unit 660 may receive an input of information specifying 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 specified device 10.

[0170] 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 process flow of this figure, the robot command unit 1060 performs the process 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, or the like.

[0171] 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. Also, 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.

[0172] FIG. 14 shows an example of the image data 1300 captured by the robot 30 according to the present embodiment. The image data 1300 captures devices 10 such as a plurality of pipes 1305a to 1305h, a valve 1310, a reactor 1320, and a flow meter 1330. In the example of this figure, there is an abnormality in the valve 1310 and it is emitting abnormal noise.

[0173] The monitoring device 40 receives the collected data including the image data 1300 and the acoustic data obtained by collecting the sound within the viewing angle range of the image data 1300 (corresponding to S1110 and S1130 in FIG. 12). The sound source separation unit 1000 separates the acoustic data into sound sources and extracts the 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).

[0174] 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 part 1020 may specify that the sound source of the sound component is the device 10 (corresponding to S1150). The sound anomaly detection part 1030 detects the degree of anomaly 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 anomaly detection part 1030 detects a high degree of anomaly for the sound component from the valve 1310 that is emitting abnormal noise. As a result, the abnormal device specification part 1040 can specify that the valve 1310 is abnormal based on the degree of anomaly of the sound component.

[0175] Here, when the pipes 1305a to c and the valve 1310 are newly installed in the facility 1 and are not registered in the device database 60, the device detection part 1010 may estimate from the appearance shape etc. of the object extracted from the image data 1300 that the pipes 1305a to c are pipes and the valve 1310 is a valve. The sound anomaly detection part 1030 may detect the degree of anomaly 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 a plurality of other valves in the facility 1 in the past.

[0176] Note that depending on the type of the sensor 400a used by the robot 30, the sound source separation part 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 part 1020 may specify the device 10 that is the sound source of each sound component while appropriately changing the imaging direction and position etc. of the robot 30 (S1270 in FIG. 13) using the horizontal position of each device 10 in the image data 1300 and the direction of each sound component in the horizontal direction.

[0177] In the above embodiments, each of the plurality of acoustic sensors 400a has been described as being mounted on the movable robot 30. However, at least one acoustic sensor 400a may be mounted on the robot 30 whose position is fixed and whose orientation can be changed, or may be mounted on the robot 30 whose position and orientation are fixed.

[0178] 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 operations are performed or (2) sections of an apparatus having the role of performing the operations. Specific stages and sections may be implemented by dedicated circuits, programmable circuits supplied with computer-readable instructions stored on a computer-readable medium, and / or processors supplied with computer-readable instructions stored on a computer-readable medium. The dedicated circuits may include digital and / or analog hardware circuits, including integrated circuits (ICs) and / or discrete circuits. The programmable circuits may include reconfigurable hardware circuits 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.

[0179] A computer-readable medium may include any tangible device that can store instructions executable by an appropriate device. As a result, a computer-readable medium having instructions stored therein will comprise a product that includes instructions that can be executed to create means for performing the operations specified in a flowchart or block diagram. Examples of computer-readable media may include electronic memory media, magnetic memory media, optical memory media, electromagnetic memory media, semiconductor memory media, and the like. More specific examples of computer-readable media 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 disc read-only memory (CD-ROM), digital versatile disc (DVD), Blu-ray (registered trademark) disc, memory stick, integrated circuit card, and the like.

[0180] Computer-readable instructions may include any combination of one or more programming languages, including assembler 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 an object-oriented programming language such as Smalltalk (registered trademark), JAVA (registered trademark), C++, and a conventional procedural programming language such as the "C" programming language or a similar programming language.

[0181] Computer-readable instructions may be provided to a processor or programmable circuitry of a programmable data processing apparatus such as a general purpose computer, a special purpose computer, or other computers, locally or via a wide area network (WAN) such as a local area network (LAN), the Internet, etc., and the computer-readable instructions 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.

[0182] FIG. 15 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 to execute the operation or the one or more sections, 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 perform specific operations associated with some or all of the blocks of the flowcharts and block diagrams described herein.

[0183] 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.

[0184] 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.

[0185] 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 the IC card.

[0186] The ROM 2230 stores therein a boot program or the like executed by the computer 2200 at activation, and / or a program dependent on the hardware of the computer 2200. The input / output chip 2240 may also be connected to the 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.

[0187] The program is provided by a computer-readable medium such as a DVD-ROM 2201 or an IC card. The program is read from the computer-readable medium, installed in a hard disk drive 2224, a RAM 2214, or a ROM 2230, which are also examples of computer-readable media, and executed by the CPU 2212. The information processing described in these programs is read by the 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 the computer 2200.

[0188] For example, when communication is executed between the computer 2200 and an external device, the CPU 2212 may execute a communication program loaded in the RAM 2214 and instruct the communication interface 2222 to perform communication processing based on the processing described in the communication program. Under the control of the CPU 2212, the communication interface 2222 reads the transmission data stored in a transmission buffer processing area provided in a recording medium such as the RAM 2214, the hard disk drive 2224, the DVD-ROM 2201, or the IC card, 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.

[0189] Further, the CPU 2212 may cause all or a necessary part of a file or database stored in an external recording medium such as a hard disk drive 2224, a DVD-ROM drive 2226 (DVD-ROM 2201), or an IC card 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 medium.

[0190] Various types of information such as various types of programs, data, tables, and databases may be stored in the recording medium 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 medium. 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 medium, 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.

[0191] The programs or software modules described above may be stored on 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.

[0192] 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.

[0193] In the claims, the description, and the drawings, for the operations, procedures, steps, stages, and other processes in the devices, systems, programs, and methods shown, the execution order of each process, such as the operations, procedures, steps, and stages, is not explicitly stated as "earlier" or "preceding" etc., and it should be noted that it can be realized in any order as long as the output of the previous process is not used in the subsequent process. Regarding the operation flow in the claims, the description, and the drawings, even if it is described for convenience using "first," "next," etc., it does not mean that it is essential to be implemented in this order.

Description of Reference Numerals

[0194] 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 Determination 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 Sending 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 Sound Source Location Unit 1030 Abnormal Sound Detection Unit 1040 Abnormal Equipment Identification Unit 1050 Equipment Control Unit 1060 Robot Command Unit 1065 Schedule Determination Unit 1070 Sound Collection Characteristic Data Adjustment Unit 1300 Image Data 1305a~h Pipes 1310 Valve 1320 Reactor 1330 Flowmeter 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. For each of a plurality of devices in a facility, a device database connection unit connected to a device database that records the location within the facility and sound characteristic data corresponding to the characteristics of the sound to be subject to abnormality detection; A schedule determination unit that determines a schedule for collecting sound within the facility by each of the plurality of acoustic sensors based on the sound collection characteristics of each of the plurality of acoustic sensors and the location within the facility and the sound characteristic data for each of the plurality of devices; An apparatus comprising the same.

2. The apparatus according to claim 1, wherein at least one of the plurality of acoustic sensors has different sound collection characteristics from at least one other acoustic sensor.

3. The apparatus according to claim 2, wherein each of the plurality of acoustic sensors is mounted on each of a plurality of robots capable of moving within the facility.

4. The schedule determination unit is installed in an area within the facility, and determines a schedule for collecting sound in the area by the one acoustic sensor based on at least one of the number or density of devices that are the targets of abnormality detection by the one acoustic sensor. The apparatus according to claim 3.

5. The apparatus according to claim 1, further comprising a sound collection characteristic data adjustment unit that adjusts sound collection characteristic data indicating the sound collection characteristics of each acoustic sensor based on the result of abnormality detection using the acoustic data collected by each acoustic sensor.

6. The apparatus according to claim 5, wherein the sound collection characteristic data adjustment unit adjusts the sound collection characteristic data according to the accuracy of abnormality detection of each device using the acoustic data collected by each of the acoustic sensors.

7. An abnormality device identification unit that identifies an abnormality of at least one of the plurality of devices based on acoustic data collected by at least one of the plurality of acoustic sensors according to the schedule determined by the schedule determination unit. The apparatus according to claim 1.

8. The apparatus according to claim 7, further comprising 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 within the facility in response to the identification of the abnormality of the one device.

9. A method comprising a schedule determination step of determining a schedule for collecting sound in the facility by each of the plurality of acoustic sensors based on the sound collection characteristics of each of the plurality of acoustic sensors, the positions in the facility for each of the plurality of devices in the facility, and sound characteristic data corresponding to the characteristics of the sound to be subject to abnormality detection.

10. A program that causes a computer to function as a device database connection unit connected to a device database that records, for each of the plurality of devices in the facility, the position in the facility and sound characteristic data corresponding to the characteristics of the sound to be subject to abnormality detection, and a schedule determination unit that determines a schedule for collecting sound in the facility by each of the plurality of acoustic sensors based on the sound collection characteristics of each of the plurality of acoustic sensors, the positions in the facility for each of the plurality of devices, and the sound characteristic data. ​

Images