Information processing apparatus

Abstract

To improve a specification accuracy of an abnormal point in a conveyance route.SOLUTION: A computer 70 acquires drawing data in which a plurality of curve positions are set on a conveyance route in which a communication unit 71 is configured by a conveyor device 50 and tracking data that is the shape of the conveyance route obtained by conveying on the conveyance route. Then, a processing unit 72 detects a curve position in the tracking data, the curve position in the drawing data and the curve position in the tracking data corresponding to the curve position are superimposed to correct a path between the curve positions in the tracking data.SELECTED DRAWING: Figure 7

Description

Technical Field

[0001] The present invention relates to an information processing apparatus that corrects data collected about a conveying apparatus installed in, for example, a warehouse or the like.

Background Art

[0002] Conventionally, a conveyor apparatus is often used as a conveying apparatus for loading and unloading in a warehouse or the like. In this type of conveyor apparatus, a detection unit such as a sensor is fixedly installed around the components constituting the conveyor apparatus and the conveyor apparatus to detect failures.

[0003] When a detection unit such as a sensor is fixedly installed, there is a problem that the detection range is limited. Therefore, the applicant has proposed an abnormality detection system that can detect an abnormality in the entire conveying path at low cost by conveying a container equipped with a camera, a sensor module, or the like as a conveyed object on the conveyor apparatus as described in Patent Document 1.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] By the way, the accumulated information collected by the system described in Patent Document 1 is analyzed by a computer or the like so that, for example, where an abnormality is detected in the conveying path can be displayed on a terminal device or the like held by an operator or the like.

[0006] However, there are problems such that it is difficult to install a guide such as a guide pole as described in Patent Document 1, and the method of counting the number of rollers cannot be applied to a belt conveyor.

[0007] When not using a guide, there is a method of generating a conveyance route (also referred to as layout information or map information) based on an image captured by a camera and identifying an abnormal location based on the conveyance route. In such a method, due to the influence of image blur caused by vibrations during container conveyance, etc., the recognition accuracy of the route may decrease, resulting in a deviation from the actual layout, and it was not always possible to accurately identify abnormal locations.

[0008] The present invention aims to solve the above problems and aims to improve the accuracy of identifying abnormal locations.

Means for Solving the Problems

[0009] The invention according to claim 1 made to solve the above problems includes a first acquisition unit that acquires drawing data in which a plurality of reference positions are set on a conveyance route configured by a conveyance device, a second acquisition unit that acquires measured data which is the shape of the conveyance route obtained by being conveyed on the conveyance route, a detection unit that detects the reference positions in the measured data, and a correction unit that overlaps the reference positions in the drawing data with the reference positions in the measured data corresponding to the reference positions in the drawing data and corrects the route between the reference positions in the measured data. It is an information processing apparatus characterized by comprising these.

Effects of the Invention

[0010] As described above, according to the present invention, the reference positions in the drawing data are overlapped with the reference positions in the measured data corresponding to the reference positions in the drawing data, and the route between the reference positions in the measured data is corrected. Therefore, even when there is a deviation between the drawing data which is the actual layout and the measured data, it can be corrected, and the accuracy of identifying abnormal locations can be improved.

Brief Description of the Drawings

[0011]

Figure 1

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Figure 16

Embodiments for Carrying Out the Invention

[0012] An information processing apparatus and an information display apparatus according to an embodiment of the present invention will be described with reference to FIGS. 1 to 16. FIG. 1 is a top view of a container that collects data processed by the information processing apparatus according to an embodiment of the present invention. FIG. 2 is a cross-sectional view taken along line A-A of the container shown in FIG. 1.

[0013] The container 1 is placed on a conveyor device 50 as a conveying device and is conveyed by the conveyor device 50. In FIG. 1, it is conveyed in the direction of the arrow. Although a roller conveyor is shown as the conveying device in FIGS. 1 and 2, other conveying devices such as a belt conveyor may be used. Also, in FIGS. 1 and 2, only a part of the conveyor device 50 is shown, but the conveyor device 50 is installed, for example, inside a warehouse and has a conveying path composed of a straight line, a curve, or an inclined path. Therefore, the conveyor device 50 may be composed of a plurality of conveyor devices.

[0014] The container 1 shown in FIGS. 1 and 2 is formed in a substantially rectangular parallelepiped box shape and constitutes a storage portion 11. The storage portion 11 has an opening formed upward to enable the entry and exit of articles and the like. The storage portion 11 is composed of four side faces 11a, 11b, 11c, 11d and a bottom face 11e.

[0015] As shown in FIGS. 1 and 2, the side faces 11a and 11b are the side faces in the short side direction of the rectangular parallelepiped, and the side faces 11c and 11d are the side faces in the long side direction of the rectangular parallelepiped. In the present embodiment, the side face 11a is the front side, that is, the conveying direction (advancing direction) side. Therefore, the side face 11b is the rear side, the side face 11c is on the left side in the advancing direction, and the side face 11d is on the right side in the advancing direction.

[0016] The container 1 includes a camera 2, a control unit 3, sensor modules 4L and 4R, and a battery 5.

[0017] The camera 2 is a camera module having an imaging device such as a CCD (Charge Coupled Device) image sensor or a CMOS (Complementary Metal Oxide Semiconductor) image sensor.

[0018] The camera 2 is composed of cameras 2a, 2b, 2c, 2d, and 2e. Cameras 2a to 2c are provided on the side surface portion 11a and photograph the front of the container 1. Cameras 2a to 2c are provided so as to photograph the lower front side of the container 1 (see FIG. 2). The camera 2d is provided on the side surface portion 11c. The camera 2e is provided on the side surface portion 11d.

[0019] The camera 2a photographs the left front in the conveyance direction of the container 1. The camera 2b photographs the center front in the conveyance direction of the container 1. The camera 2c photographs the right front in the conveyance direction of the container 1. The camera 2d photographs the left side in the conveyance direction of the container 1. The camera 2e photographs the right side in the conveyance direction of the container 1. In addition, the cameras 2a and 2c are well-known thermal cameras (infrared thermography). Also, the cameras 2b, 2d, and 2e are wide-angle cameras.

[0020] In the present embodiment, the temperatures of the conveyor device 50 in the conveyance direction can be detected by the cameras 2a and 2c. That is, the cameras 2a and 2c function as state detection units that detect the state in the forward direction with respect to the traveling direction of the conveyance device. Also, the camera 2b may be a stereo camera.

[0021] The control unit 3 is provided further below the bottom surface portion 11e. That is, the container 1 has a double bottom. The control unit 3 is directly or indirectly installed on a member 8 that absorbs vibration such as a vibration absorption mat. By the member 8 that absorbs vibration, it is possible to make it difficult for the control unit 3 etc. to be affected by the vibration generated by being conveyed.

[0022] The control unit 3 estimates the current position (self-position) of the container 1 based on the image captured by the camera 2. In addition, the control unit 3 learns the results detected by the sensor modules 4L and 4R by deep learning, and determines whether there is an abnormality by determining whether the results detected by the sensor modules 4L and 4R are within the normal range based on the learning results. Details will be described later.

[0023] The sensor module 4L includes a sound sensor 4a and a vibration sensor 4c. The sensor module 4L is provided closer to the side surface portion 11c side. Further, the sound sensor 4a is directly or indirectly installed on the member 8 that absorbs vibration, and the vibration sensor 4c is directly installed on the bottom surface of the container 1 below the member 8 that absorbs vibration.

[0024] The configuration of the sensor module 4R is basically the same as that of the sensor module 4L. The difference between the sensor module 4R and the sensor module 4L is that the sensor module 4R is provided closer to the side surface portion 11d side. That is, the sensor module 4L detects the state on the left side in the traveling direction of the container 1, and the sensor module 4R detects the state on the right side in the traveling direction of the container 1.

[0025] The sound sensor 4a collects external sounds and detects the sounds emitted by a predetermined conveyor device 50. The sound sensor 4a can be composed of, for example, a single-directional microphone and a frequency filter. The vibration sensor 4c detects the vibration applied to the container 1. The vibration sensor 4c can be composed of an acceleration sensor or the like. As the acceleration sensor, a three-axis acceleration sensor is preferable, but a single-axis or two-axis acceleration sensor may also be used. Further, the vibration sensor 4c does not necessarily need to be provided for each sensor module, and one vibration sensor 4c may be provided for each container 1. In this embodiment, the sensor module is composed of two types of sensors, but other sensors such as an optical sensor and a magnetic sensor may be used. That is, the sensor modules 4L and 4R function as a state detection unit that detects the state of the conveyor device 50.

[0026] The battery 5 is installed directly or indirectly on the member 8 that absorbs vibration. The battery 5 supplies power to the above-described camera 2, control unit 3, and sensor modules 4L and 4R. The container 1 also has a terminal (not shown) for charging the battery 5. Alternatively, the battery 5 may be detachable for charging.

[0027] FIG. 3 shows a block diagram of the container (abnormality detection system) 1 according to the present embodiment. As shown in FIG. 3, the control unit 3 includes a processing unit 3a and a storage unit 3b.

[0028] The processing unit 3a is composed of, for example, a microprocessor or the like, and acquires detection values of the various sensors described above, estimates its own position, performs deep learning, determines the presence or absence of an abnormality, and the like. That is, the processing unit 3a functions as a current position detection unit together with the camera 2.

[0029] The storage unit 3b is composed of a storage device such as an SSD (Solid State Drive), for example, and stores and stores the detection results of the sensor modules 4L and 4R in association with the position information where the self-position is estimated. The storage unit 3b also stores layout (map) information of the transport route for self-position estimation.

[0030] Next, the operation of the container 1 having the above-described configuration will be described with reference to the flowcharts of FIGS. 4 to 6. FIG. 4 is a flowchart for generating map information for estimating the self-position from the image captured by the camera 2.

[0031] First, a captured image is collected from the camera 2b (step S11), and the processing unit 3a extracts feature points from the collected captured image (step S12). Then, the processing unit 3a generates a three-dimensional map (map information) of the transport route formed by the conveyor device 50 based on the extracted feature points (step S13). This three-dimensional map is formed by extracting feature points from a plurality of images captured when the camera 2b is transported by the conveyor device 50 and connecting them together, and contains information including the feature points on the transport route.

[0032] Note that the map information does not have to be a 3D map. For example, it may be 2D information of a path composed of straight lines and curves (see, for example, FIG. 8). In this case, curves may be detected as feature points.

[0033] FIG. 5 is a flowchart for generating a learned model by deep learning based on the detection results detected by the sensor modules 4L and 4R and the cameras 2a and 2c which are thermal cameras.

[0034] First, the detection results detected by the sensor modules 4L and 4R and the cameras 2a and 2c are collected (step S21), and the processing unit 3a learns the normal detection results of each sensor by well-known deep learning (step S22). That is, the detection results of the sensors in a state where the conveyor device 50 is operating normally are learned. At this time, there may be a certain range of values in the normal state. Also, in this step, the normal state (detection result) is learned for each position of the conveyor device 50. This is because the normal ranges of sound, temperature, and vibration often differ depending on the position of the conveyor device 50. That is, learning is performed in association with the position with reference to the 3D map information. Then, the processing unit 3a generates a learned model that has learned a predetermined amount of detection results (step S23).

[0035] FIG. 6 is a flowchart for detecting an abnormality using the map information generated in the flowchart of FIG. 4 and the learned model generated in the flowchart of FIG. 5.

[0036] First, the detection results detected by the sensor modules 4L and 4R and the cameras 2a and 2c are collected (step S31). The processing unit 3a estimates the self-position of the container 1 based on the image captured by the camera 2b and the map information stored in the storage unit 3b (step S32). Then, the processing unit 3a determines whether the detection results collected in step S31 are within the normal range according to the learned model at the self-position estimated in step S32 (step S33). If it is not within the normal range (step S33: NO), it may be notified as an abnormal detection by, for example, a notification device (not shown), and the abnormal detected position information is stored in the storage unit 3b (step S34). On the other hand, if it is within the normal range (step S33: YES), the process returns to step S31.

[0037] Here, step S33 is determined for each sensor. That is, it is determined for each sensor whether the detection result is within the normal range, and it is considered normal when the detection results of all sensors are within the normal range. Therefore, if the detection result of one sensor is outside the normal range, it is determined as abnormal.

[0038] By doing so, for example, the following signs of failure can be captured. However, it is not necessary to identify the following failure details in the container 1, and it is only necessary to detect that there is some abnormality at least at that position. The identification of the failure details may be performed by another measuring device or operator inspection, etc.

[0039] For example, based on the detection result of the sound sensor 4a, it is possible to detect damage to the roller or shaft of the conveyor device 50, non-transmission of driving force to the carrier roller, idling of the roller, etc. Also, based on the detection result of the vibration sensor 4c, it is possible to detect damage to the roller or shaft of the conveyor device 50, inclination of the roller surface, non-transmission of driving force to the carrier roller, idling of the roller, etc. Based on the detection results of the cameras 2a and 2c, it is possible to detect abnormal heat generation of the power supply of the conveyor device 50.

[0040] Further, by combining the detection result of the sound sensor 4a and the determination result of the vibration sensor 4c, it is possible to detect a failure of the power supply of the conveyor device 50. Further, by combining the detection result of the sound sensor 4a, the detection results of the cameras 2a and 2c, and the determination result of the vibration sensor 4c, it is possible to detect a failure of the motor of the conveyor device 50.

[0041] For example, by the detection result of the sound sensor 4a alone, it is possible to detect whether any of the breakage of the roller or shaft of the conveyor device 50, the non - transmission of the driving force to the carrier roller, or the idling of the roller has occurred. By associating with the position information based on the self - position estimation result, it is possible to specify where such a sign of failure was present.

[0042] By the way, the control unit 3 of the container 1 can specify an abnormal location by the above - mentioned method. However, for example, when displaying the conveyance path as a map and displaying the abnormal location on the map, the conveyance path (map information) created from the information collected by the container 1 may have a reduced recognition accuracy of the path due to the influence of video blurring caused by vibrations during container conveyance, etc., resulting in a deviation from the layout of the actual conveyance path. Therefore, in the present embodiment, the map information (measured data) created from the data collected by the container 1 is corrected using the drawing (drawing data) of the conveyance path prepared in advance, so that a map display that matches the actual conveyance path can be achieved. Note that what will be described hereinafter targets the two - dimensional map information as the measured data.

[0043] FIG. 7 shows the functional configuration of the computer 70 as an information processing apparatus that performs the above - described correction process. The computer 70 may be installed in the vicinity of the conveyor device 50, or may be installed in a separate room or the like from the conveyance device. The computer 70 may be configured as a server computer or a personal computer, and may be a desktop type, a notebook type, a tablet type, or the like.

[0044] The computer 70 includes a communication unit 71, a processing unit 72, and a storage unit 73. The communication unit 71 performs wireless communication by a communication method such as Wi-Fi (registered trademark). The communication unit 71 receives the abnormal locations where the container 1 is collected, the measured data, and the like. Of course, in this case, the container 1 also has a communication function. Also, in FIG. 7, abnormal information (abnormal locations, abnormal contents, etc.) and measured data are received by wireless communication, but they may be acquired by wired connection using USB (Universal Serial Bus), LAN (Local Access Network), etc. after transportation, or may be acquired via a storage medium such as a memory card.

[0045] The processing unit 72 is composed of, for example, a microprocessor or the like, and performs correction processing of the above-described measured data. The storage unit 73 is composed of a storage device such as an SSD, and stores various data received by the communication unit 71.

[0046] In the present embodiment, first, drawing data indicating a transportation route is prepared in advance. This drawing data is not based on measured data, but is created from design data or the like used when constructing the transportation route. Therefore, the drawing data has accuracy along the actual transportation route in terms of the angle of the curve, the length of the straight line, etc. described later.

[0047] FIG. 8 shows a diagram when a deviation occurs between the drawing data and the measured data. In FIG. 8, the solid line indicates the measured data (hereinafter also referred to as tracking data), and the broken line indicates the drawing data. That is, the measured data also includes information on the shape of the transportation route. Reference numerals t1 to t10 indicate the curve positions on the route in the tracking data, and reference numerals d1 to d10 indicate the curve positions on the route in the drawing data. Note that reference numerals t0 and d0 indicate the start point of the route, and reference numerals t11 and d11 indicate the end point of the route.

[0048] The drawing data has a curve position registered as a reference position (the registration may be manually detected and set). A curve is a connection between one straight line and another straight line in a different direction. The curve position may be, for example, the vertex position of the curve, but may also be the starting point or the ending point of the curve. On the other hand, in the tracking data, curves can also be detected by detecting straight lines from the camera image through image recognition or the like. The curve position detected in the tracking data becomes the corresponding position of the reference position. Since the positions recognized as curves may vary depending on the size of the curves, the curve positions in the drawing data and the curve positions in the tracking data shall use the same judgment criteria (vertex position, starting point, ending point, etc.).

[0049] Due to the influence of vibrations and the like described above, as shown in FIG. 8, the tracking data may be acquired with differences in direction, curve angle, straight line length, etc. from the drawing data. Therefore, in the present embodiment, the curve position in the drawing data and the curve position in the tracking data are superimposed, and the straight lines between the curves are linearly interpolated, for example, to correct the tracking data.

[0050] Specifically, first, the starting point t0 is superimposed on d0, and then the curve positions are superimposed on each other. For example, t1, which is the first curve position in the tracking data, is superimposed on d1, which is the first curve position in the corresponding drawing data. Similarly, the superimposition of each curve position is performed up to the ending point. This superimposition is performed so that the tracking data matches the drawing data. Then, linear interpolation is performed on the straight line portions between the superimposed curve positions of the tracking data. In this way, the tracking data is corrected.

[0051] The correction operation described above is summarized in the flowchart of FIG. 9. First, the communication unit 71 acquires the drawing data and the tracking data (steps S41, S42). Note that the order of steps S41 and S42 may be reversed. Then, the processing unit 72 performs the superimposition process of the curve positions (step S43), and further performs linear interpolation (step S44).

[0052] As is clear from the above description, the communication unit 71 functions as a first acquisition unit that acquires drawing data in which a plurality of reference positions are set on a transport path configured by a transport device, and a second acquisition unit that acquires measured data that is the shape of the transport path obtained by being transported on the transport path. Further, the processing unit 72 functions as a detection unit that detects corresponding positions of the reference positions in the measured data, and a correction unit that overlays the reference positions in the drawing data and the corresponding positions of the reference positions in the measured data, and corrects the path between the reference positions in the measured data.

[0053] FIG. 10 shows a map in which abnormal locations based on tracking data after performing the above-described correction operation are displayed on a transport path based on drawing data. In FIG. 10, the dashed line indicates a roller conveyor, the solid line indicates a belt conveyor, "+" indicates a connection part, "□" indicates an elevator, "◇" indicates an in-loading sensor, "〇" indicates an inspection port, and "☆" indicates the position of an emergency stop switch. Further, "×" indicates an abnormal location. The abnormal locations may be colored differently depending on the type of abnormality such as temperature abnormality, vibration abnormality, and sound abnormality.

[0054] The above-described dashed line, solid line, "+", "□", "◇", "〇", and "☆" are information regarding facilities and can be registered in advance in the drawing data. "×" is obtained from the tracking data (data acquired from Container 1) and its position has been corrected by the above-described correction process. Since FIG. 10 is based on drawing data, the accuracy as a transport path is high. Further, since the abnormal locations have also been corrected by the above-described method, the positions where the abnormalities occurred are displayed with higher accuracy.

[0055] The map shown in FIG. 10 may be displayed alone on a terminal device or the like, but when displayed together with other information, it becomes easier to identify the cause of the abnormality. FIG. 12 shows a display example in the information display device according to the present embodiment. In the following description, the information display device will be described as a device (such as a tablet terminal or a smartphone) provided with a display having a touch panel, but it may also be a monitor screen of a notebook computer or a desktop computer.

[0056] FIG. 11 shows the functional configuration of the tablet terminal 80 as an information display device. The tablet terminal 80 includes a communication unit 81, a processing unit 82, a storage unit 83, and a display unit 84. The communication unit 71 performs wireless communication by a communication method such as Wi-Fi (registered trademark). The communication unit 81 receives data such as the data corrected by the computer 70, the abnormal information collected by the container 1, and the imaging image information of the camera 2. The abnormal information includes abnormal locations and the content of the abnormality (sound abnormality, temperature abnormality, vibration abnormality). The data collected by the container 1 may be received via the computer 70 or directly received. Also, it may be a wired connection not limited to wireless communication, such as USB or LAN, or may be acquired via a storage medium such as a memory card.

[0057] The processing unit 82 is composed of, for example, a microprocessor and controls the overall operation of the above-described tablet terminal 80. The storage unit 83 is composed of a storage device such as an SSD and stores various data received by the communication unit 81. The display unit 84 is composed of, for example, a liquid crystal display having a touch panel and performs various displays and display switching described later.

[0058] FIG. 12 is a display example of a display unit such as a display of the information display device. In the display example of FIG. 12, the display area is, in order from the left, a timeline 101, a map area 102, and a video area 103.

[0059] The timeline 101 is a diagram showing the detection status of abnormalities when the container 1 moves along the transport path in chronological order (change over time). The timeline 101 includes a time display unit 101a and an information display unit 101b. The time display unit 101a shows the movement time from the starting point (in FIG. 12, time progresses from bottom to top). The information display unit 101b displays an abnormal part 101b1 and an absolute movement amount 101b2. The abnormal part 101b1 and the absolute movement amount 101b2 are displayed overlapping each other.

[0060] The abnormal part 101b1 indicates the time when an abnormality is detected and corresponds to the above-mentioned abnormal location. It is preferable that the abnormal part 101b1 has a display that is easy to distinguish, such as filling the abnormal location with red.

[0061] The absolute movement amount 101b2 is calculated by the processing unit 82 based on the detection value of the acceleration sensor included in the tracking data. Specifically, it is a value calculated by adding the absolute values of the accelerations of each axis (x, y, z) of the three-axis acceleration sensor. The absolute movement amount calculated in this way can indicate the magnitude of the vibration applied to the container 1. That is, it can be said that a large vibration is applied to a location with a large absolute movement amount.

[0062] That is, the tablet terminal 80 functions as an acceleration acquisition unit that acquires acceleration information during the conveyance of the conveyance path configured by the conveyor device 50 by the communication unit 81, the processing unit 82 functions as a calculation unit and an absolute movement amount acquisition unit that calculates the absolute movement amount indicating the magnitude of the vibration on the conveyance path based on the acceleration information, and the display unit 84 displays the absolute movement amount.

[0063] Note that the absolute movement amount may be calculated for each sampling period of the sensor, or may be calculated by aggregating a plurality of sampling periods. For example, when the sampling period is 1000 Hz, it will be calculated every 1 millisecond, but it may be calculated every 100 samples (0.1 second), for example. This may be, for example, by adding 100 samples, or may be used once for display for every 100 samples. Alternatively, it may be the average value of 100 samples.

[0064] Also, it is preferable that the absolute movement amount is calculated by adding the absolute values of the accelerations of each axis (x, y, z) of the three-axis acceleration sensor. However, when the acceleration sensor in use is two-axis or one-axis, it may be a value obtained by adding the absolute values of the accelerations of the two axes or the absolute value of the acceleration of one axis. Also, when there are a plurality of acceleration sensors, the detection values of all the acceleration sensors may be added, or may be an average value.

[0065] The timeline 101 can display the acceleration data 101c of each axis as shown in FIG. 13 by sliding that area to the right. In addition to acceleration, data obtained by the sensor modules 4L and 4R (such as sound) or temperature etc. determined from the video imaged by the cameras 2a and 2c which are thermal cameras may also be displayed. When sliding to the left in the state of displaying the acceleration data of each axis, it returns to the state of FIG. 12.

[0066] The map area 102 is displaying the map shown in FIG. 10. The map area 102 can enlarge and display the map as shown in FIG. 14 by sliding that area to the right. In FIG. 14, although the display of the timeline 101 is left, the map may be displayed in full screen. When sliding to the left in the state of enlarging and displaying the map, it returns to the state of FIG. 12.

[0067] The video area 103 is displaying the video (imaging image information) imaged by the camera 2. In FIG. 12, three videos can be displayed in the video area 103. Therefore, for example, the videos of the cameras 2b, 2d, and 2e can be displayed simultaneously. In FIG. 12, the video 103a is the video of the camera 2b, the video 103b is the video of the camera 2d, and the video 103c is the video of the camera 2e.

[0068] Also, the time of the video displayed in the video area 103 is displayed on the timeline 101. In FIG. 12, the video of the time indicating the position of the line indicated by the symbol L on the timeline 101 is displayed in the video area 103.

[0069] The video area 103 can enlarge and display any one of the videos as shown in FIG. 15 by sliding that area to the left. In FIG. 15, although the display of the timeline 101 is left, the video may be displayed in full screen. When sliding to the right in the state of enlarging and displaying the video, it returns to the state of FIG. 12.

[0070] Note that the display example shown in FIG. 12 may be a modified example such as that shown in FIG. 16. In the modified example shown in FIG. 16, the display area is the timeline 101, the map area 102, and the video area 103 in order from the left, similar to FIG. 12.

[0071] Similar to FIG. 12, the timeline 101 includes a time display section 101a and an information display section 101b. The information display section 101b displays an abnormal section 101b1 and an absolute movement amount 101b2. The abnormal section 101b1 and the absolute movement amount 101b2 are displayed overlapping each other.

[0072] In FIG. 16, the abnormal section 101b1 is displayed for each of the left and right cameras 2a and 2c which are thermal cameras. In FIG. 16, the abnormal section 101b1 indicating the temperature abnormality detected by the left camera 2a is displayed in the area indicated by the reference numeral 101c1, and the abnormal section 101b1 indicating the temperature abnormality detected by the right camera 2c is displayed in the area indicated by the reference numeral 101c2. By doing so, it is displayed which side the abnormality was detected on, making it easier to identify the abnormal location.

[0073] In addition, jump buttons 101d1 and 101d2 are added to the timeline 101 in FIG. 16. The jump buttons 101d1 and 101d2 are buttons that jump (transition) the position of line L to the next abnormal section 101b1. The jump button 101d1 jumps to the next abnormal section 101b1 in the upward direction in the figure, and the jump button 101d2 jumps to the next abnormal section 101b1 in the downward direction in the figure.

[0074] In addition, scroll buttons 101e1 and 101e2 are added to the timeline 101 in FIG. 16. The scroll buttons 101e1 and 101e2 are buttons that scroll the timeline 101 in the time axis direction (up and down directions). The scroll button 101e1 scrolls in the upward direction in the figure, and the scroll button 101e2 scrolls in the downward direction in the figure.

[0075] Furthermore, on the timeline 101 in FIG. 16, a temperature display section 101f and a total number of anomalies 101g are added respectively. The temperature display section 101f displays the temperature values detected by the cameras 2a and 2c, and is displayed corresponding to each anomaly section 101b1. The total number of anomalies 101g displays the total number of anomaly sections 101b1 detected by the camera 2a and the total number of anomaly sections 101b1 detected by the camera 2c respectively.

[0076] The map area 102 in FIG. 16 is basically the same as that in FIG. 12, but the numerical values at the time of anomaly are displayed beside the anomaly location "×". In the case of the display of "L52" in FIG. 16, it is an anomaly detected by the left camera 2a, indicating that the detected temperature was 52°C. Note that it is not necessary to display the numerical values at the time of anomaly for all anomaly locations "×", and for example, only one selected location may be sufficient. In the case of one selected location, it is preferable to make the anomaly location where the numerical value is displayed larger and thicker than others (the display color may also be changed).

[0077] Also, in the map area 102 of FIG. 16, the location corresponding to the line L of the timeline 101 is displayed as the preview point P. By doing so, it becomes possible to link and confirm the position and time. Of course, when the line L moves, the preview point P also moves, but this preview point P may always be displayed at the center of the map area 102. Furthermore, the preview point P may be linked to the time of the video displayed in the video area 103 (the video captured at the preview point P is displayed in the video area 103).

[0078] The video area 103 in FIG. 16 is basically the same as that in FIG. 12. Note that, different from FIG. 12, the video 103b may display the video of the camera 2a, and the video 103c may display the video of the camera 2c.

[0079] According to the present embodiment described above, the computer 70 acquires drawing data in which a plurality of curve positions are set on a transport path configured by the conveyor device 50 and tracking data which is the shape of the transport path obtained by transporting on the transport path. Then, the processing unit 72 detects the curve positions in the tracking data, overlaps the curve positions in the drawing data with the curve positions in the tracking data corresponding to the curve positions, and corrects the path between the curve positions in the tracking data.

[0080] By doing so, the curve positions in the drawing data are overlapped with the curve positions in the tracking data corresponding to the curve positions in the drawing data, and the path between the curve positions in the tracking data is corrected. Therefore, even when the drawing data and the tracking data, which are the actual layouts, are deviated, they can be corrected, and the identification of abnormal locations can be improved in accuracy.

[0081] In addition, since the curve positions are used as reference positions, it is easy to set the reference positions. Also, since the intervals between the reference positions are straight lines, linear interpolation can be performed, and the correction process becomes easy.

[0082] In addition, since the tracking data is obtained by transporting the container 1 having the cameras 2a and 2c and the sensor modules 4L and 4R that detect the state of the conveyor device 50 on the transport path, the tracking data can be automatically acquired by transporting the container 1.

[0083] In addition, the tablet terminal 80 acquires acceleration information during the transport of the transport path configured by the conveyor device 50 by the communication unit 81, and the processing unit 82 calculates the absolute movement amount based on the acceleration information. Then, the display unit 84 displays the absolute movement amount. By doing so, it is possible to determine that a location with a large absolute movement amount is a location where there may be a large vibration and a serious failure has occurred, and to preferentially check it.

[0084] Further, the acceleration information is three-axis acceleration information, and the calculation unit calculates the absolute movement amount by adding the absolute values of the accelerations of the three axes. Therefore, the vibrations applied to the container 1 from the vertical, front-rear, and left-right directions can be reflected in the absolute movement amount, and abnormal locations can be detected with higher accuracy.

[0085] In addition, since the display unit 84 displays the absolute movement amount as a change over time, it is possible to specify at which point in time a large vibration was applied, and it is possible to quickly specify an abnormal location.

[0086] In addition, the tablet terminal 80 acquires abnormal occurrence information, which is information regarding an abnormal occurrence location on the conveyance path, and the display unit 84 overlays and displays the abnormal occurrence information and the absolute movement amount. Therefore, the relationship between the abnormal occurrence location and the location with a large vibration can be shown. Also, it is possible to easily distinguish between an abnormality in the vibration system and an abnormality other than the vibration system.

[0087] In addition, the abnormal occurrence information also includes imaging image information obtained by imaging the conveyance path with a camera. The display unit 84 displays a timeline 101 on which the abnormal occurrence information and the absolute movement amount are overlaid, a map area 102 on which the layout of the conveyance path is displayed, and a video area 103 on which the imaging image information is displayed. By doing so, three types of information can be displayed simultaneously. Also, it is possible to link and display the timeline, the map, and the imaging image information, which makes it easier to search for the cause of the abnormality and the like.

[0088] Note that for the information display device described above, if it can acquire data capable of displaying as shown in FIG. 12 and the like, the correction process performed by the computer 70 is not essential. Also, the information display device does not necessarily have to calculate the absolute movement amount, and it may acquire the one calculated externally. That is, the information display device only needs to acquire at least the absolute correction amount and the abnormal information and display them overlaid.

[0089] In addition, the timeline 101 may be displayed after being converted to distance instead of time. In this case, the distance from the start point of the path of the abnormal location becomes clear.

[0090] Further, the present invention is not limited to the above-described embodiments. That is, those skilled in the art can implement various modifications in accordance with conventionally known knowledge without departing from the gist of the present invention. As long as such modifications still include the configurations of the information processing apparatus and the information display apparatus of the present invention, of course, they are included in the scope of the present invention.

Explanation of Reference Numerals

[0091] 1 Container (carried object) 2a Camera (state detection unit) 2b Camera 2c Camera (state detection unit) 2d Camera 2e Camera 3 Control unit 4L Sensor module (state detection unit) 4R Sensor module (state detection unit) 50 Conveyor 70 Computer (information processing apparatus) 71 Communication unit (first acquisition unit, second acquisition unit) 72 Processing unit (detection unit, correction unit) 80 Tablet terminal (information display apparatus) 81 Communication unit (acquisition unit) 82 Processing unit (calculation unit) 84 Display unit 101 Timeline (timeline unit) 102 Map area (map unit) 103 Video area (video unit)

Claims

1. A first acquisition unit that acquires drawing data indicating the conveyance path, in which a plurality of reference positions are set on the conveyance path constituted by a conveyance device; A second acquisition unit that acquires measurement data which is the shape of the conveyance path obtained by conveying on the conveyance path; A detection unit that detects corresponding positions of the reference positions in the measurement data; A correction unit that overlaps the reference position in the drawing data and the corresponding position, and corrects the path between the reference positions in the measurement data; An information processing apparatus comprising the same.

2. The information processing apparatus according to claim 1, wherein the reference position is a curve position on the conveyance path.

3. The information processing apparatus according to claim 1 or 2, wherein the measurement data is obtained by conveying an object having a state detection unit for detecting the state of the conveyance device on the conveyance path.

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