Abnormality detection system, method, and storage medium

Abstract

This processing circuit is configured to: acquire a plurality of first images captured while a vehicle is traveling so as to include two-dimensional codes of a plurality of wheels; acquire a plurality of second images captured while the vehicle is traveling at a predetermined time interval from capturing of the first images so as to include the two-dimensional codes of the plurality of wheels; calculate, for each wheel, a rotational displacement of the direction of a corresponding two-dimensional code of the second image with respect to the direction of a corresponding two-dimensional code of the first image; calculate, for each wheel, an angular velocity of the wheel on the basis of the corresponding rotational displacement and the time interval; and determine whether or not the tires of the plurality of wheels include a tire with abnormal internal pressure on the basis of the angular velocities of the plurality of wheels.

Description

Anomaly detection system, method, and storage medium

[0001] The present disclosure relates to a system, method, and storage medium for detecting abnormal tire pressure in a vehicle.

[0002] Conventionally, methods for detecting abnormalities in the internal pressure of vehicle tires have been proposed. Patent Document 1 discloses a method for detecting deflated tires on a vehicle with four wheels. This detection method detects the angular velocities of the four wheels, generates signals proportional to the angular velocities, and determines whether some or all of the four tires are deflated by processing the four signals. Patent Document 1 also describes measuring the angular velocities of the vehicle wheels using digital pulse oscillators arranged in association with each wheel.

[0003] Japanese Unexamined Patent Publication No. 63-305011

[0004] The method of detecting abnormal tire pressure in Patent Document 1 requires that a sensor for measuring the angular velocity of each wheel be mounted on the vehicle.

[0005] The present disclosure aims to provide an abnormality detection system, method, and storage medium that can detect abnormalities in the internal pressure of a vehicle's tires by obtaining the angular velocity of the wheels without using sensors mounted on the vehicle.

[0006] An abnormality detection system according to one aspect of the present disclosure is an abnormality detection system for detecting an internal pressure abnormality in a tire of a vehicle having a tire, a tire wheel on which the tire is mounted, and a plurality of wheels including two-dimensional codes disposed on the side of the tire wheel, the abnormality detection system including a processing circuit configured to: acquire a plurality of first images taken while the vehicle is traveling, the first images including the two-dimensional codes of the plurality of wheels; acquire a plurality of second images taken while the vehicle is traveling at a predetermined time interval from the time the first images are taken, the second images including the two-dimensional codes of the plurality of wheels; calculate, for each wheel, an amount of rotational displacement of the orientation of the corresponding two-dimensional code in the second image relative to the orientation of the corresponding two-dimensional code in the first image; calculate, for each wheel, the angular velocity of each wheel based on the corresponding amount of rotational displacement and the time interval; and determine, based on the angular velocities of the plurality of wheels, whether or not a tire with an internal pressure abnormality is present among the tires of the plurality of wheels.

[0007] An abnormality detection method according to one aspect of the present disclosure is an abnormality detection method for detecting an internal pressure abnormality in a tire of a vehicle having a tire, a tire wheel on which the tire is mounted, and a plurality of wheels including two-dimensional codes disposed on the side of the tire wheel, the abnormality detection method including: acquiring a plurality of first images taken while the vehicle is traveling, the first images including the two-dimensional codes of the plurality of wheels; acquiring a plurality of second images taken while the vehicle is traveling at a predetermined time interval from the time the first images are taken, the second images including the two-dimensional codes of the plurality of wheels; calculating, for each of the wheels, an amount of rotational displacement of the orientation of the corresponding two-dimensional code in the second image relative to the orientation of the corresponding two-dimensional code in the first image; calculating, for each of the wheels, the angular velocity of each of the wheels based on the corresponding amount of rotational displacement and the time interval; and determining, based on the angular velocities of the plurality of wheels, whether or not a tire with an internal pressure abnormality is present among the tires of the plurality of wheels.

[0008] A storage medium according to one aspect of the present disclosure is a storage medium having recorded thereon an anomaly detection program that causes at least one processor to execute the anomaly detection method. The storage medium is a non-transitory, tangible, non-volatile medium. The storage medium may be built into or externally attached to a computer (e.g., a mobile information terminal, a personal computer, a server, etc.). The storage medium may include RAM, ROM, EEPROM, storage, etc., and may be, for example, a hard disk, flash memory, optical disk, etc. The program stored in the storage medium may be executed on a computer to which the storage medium is directly connected, or on a computer connected to the storage medium via a communication network (e.g., the Internet).

[0009] According to one aspect of the present disclosure, an abnormality in the internal pressure of a vehicle tire can be detected by obtaining the angular velocity of the wheel without using a sensor mounted on the vehicle.

[0010] FIG. 1 is a schematic diagram of an anomaly detection system according to an embodiment. FIG. 2 is a diagram showing an example of the arrangement of multiple cameras, in which a moving vehicle and multiple cameras capturing images of the vehicle are viewed from the front. FIG. 3 is a diagram showing an example of the arrangement of multiple cameras, in which a moving vehicle and multiple cameras capturing images of the vehicle are viewed from above. FIG. 4 is a side view of a wheel. FIG. 5 is a block diagram of various devices included in the anomaly detection system of FIG. 1. FIG. 6 is a flowchart illustrating the processing of the anomaly detection system of FIG. 1. FIG. 7 is a diagram showing an example of a first image captured while the vehicle is traveling. FIG. 8 is a diagram showing a second image captured a predetermined time interval after the first image is captured.

[0011] Hereinafter, an embodiment will be described with reference to the drawings.

[0012] <Overall System Configuration> Fig. 1 is a schematic diagram of an anomaly detection system 1 according to an embodiment. The anomaly detection system 1 is for detecting an abnormality in the internal pressure of a tire of a vehicle 2. The vehicle 2 (hereinafter, also referred to as the vehicle under inspection 2) to be inspected for the presence of an abnormality in the internal pressure of the tire includes four or more wheels 10. The multiple wheels 10 of the vehicle under inspection 2 include, for example, two front wheels 10 facing each other in the left-right direction, and two rear wheels 10 facing each other in the left-right direction behind the two front wheels 10. The vehicle under inspection 2 is, for example, a passenger car, a truck, a bus, or the like.

[0013] The anomaly detection system 1 includes a plurality of vehicle inspection systems 3 that may be distributed across multiple locations that are distant from one another. The anomaly detection system 1 also includes a server 4 and a plurality of information processing terminals 5. The vehicle inspection systems 3, the server 4, and the plurality of information processing terminals 5 are connected to a communication network N such as the Internet. The communication network N is not limited to the Internet, and may be any other network such as a LAN, a WAN, a satellite communication line, or a mobile phone network.

[0014] Each vehicle inspection system 3 acquires images of the wheels 10 of the vehicle 2 to be inspected. In this embodiment, the vehicle inspection system 3 determines whether any of the tires on the plurality of wheels 10 has an abnormal internal pressure from the images of the plurality of wheels 10. The server 4 receives the determination results regarding the abnormal internal pressure of the tire from each vehicle inspection system 3 via the communication network N and stores them as inspection data for the vehicle 2 to be inspected. The server 4 may be, for example, a cloud server.

[0015] The information processing terminal 5 receives and outputs the inspection data of the vehicle 2 to be inspected from the server 4. The user of the information processing terminal 5 may be, for example, an administrator of the server 4, an administrator of the vehicle 2 to be inspected, a passenger such as the driver of the vehicle 2 to be inspected, or the owner of the vehicle 2 to be inspected. The user of the information processing terminal 5 can check the inspection data of the vehicle 2 to be inspected via the information processing terminal 5. For example, the information processing terminal 5 may be an in-vehicle terminal mounted on the vehicle 2 to be inspected. The information processing terminal 5 may be a mobile terminal of a passenger of the vehicle 2 to be inspected. The information processing terminal 5 may be a smartphone, a laptop computer, or a tablet terminal. The information processing terminal 5 may be a personal computer installed in a management company that manages the vehicle 2 to be inspected.

[0016] The vehicle inspection system 3 includes a data processing device 6 and a plurality of cameras 7 communicably connected to the data processing device 6. The plurality of cameras 7 and the data processing device 6 may be connected by wire or wirelessly.

[0017] <Camera Arrangement> Figures 2 and 3 show examples of the arrangement of multiple cameras 7. Figure 2 is a view from the front of a vehicle 2 to be inspected while it is traveling, and multiple cameras 7 that capture images of the vehicle 2. Figure 3 is a view from above of a vehicle 2 to be inspected while it is traveling, and multiple cameras 7 that capture images of the vehicle 2. Note that in Figure 3, the body 14 of the vehicle 2 is indicated by a two-dot chain line. As shown in Figure 2, the multiple cameras 7 can be installed at a height approximately equal to the height of the wheels 10, for example, so that they can capture images of at least a portion of the wheels 10. The multiple cameras 7 are installed at a location where the vehicle 2 travels in a straight line at a low speed. For example, the multiple cameras 7 may be installed in a location such as the entrance to a garage, but the installation location is not particularly limited.

[0018] In FIG. 3 , the vehicle 2 to be inspected includes four wheels 10, and the vehicle inspection system 3 includes the same number of cameras 7 as the vehicle 2 to be inspected. Specifically, the vehicle inspection system 3 includes a first camera 7a for imaging the left front wheel 10a of the vehicle 2 to be inspected, a second camera 7b for imaging the right front wheel 10b of the vehicle 2 to be inspected, a third camera 7c for imaging the left rear wheel 10c of the vehicle 2 to be inspected, and a fourth camera 7d for imaging the left rear wheel 10d of the vehicle 2 to be inspected. The four cameras 7 shown in FIG. 3 are positioned so as to simultaneously image the four wheels 10 of the vehicle 2 to be inspected. That is, the longitudinal distance between the first camera 7a and the second camera 7b and the third camera 7c and the fourth camera 7d is approximately the same as the distance between the front wheels 10a, 10b and the rear wheels 10c, 10d of the vehicle 2 to be inspected.

[0019] 2 and 3 is merely an example. For example, the number of cameras 7 included in the vehicle inspection system 3 may be more or less than the number of wheels 10 of the vehicle 2 to be inspected.

[0020] FIG. 4 is a side view of a wheel 10. The wheel 10 of the vehicle 2 to be inspected includes a tire 11 and a tire wheel 12 to which the tire 11 is attached. At least one two-dimensional code 13 is disposed on the side of the tire wheel 12. The two-dimensional code 13 may be a sticker attached to the side of the tire wheel 12, or may be formed directly on the side of the tire wheel 12 using a laser or the like. In the example shown in FIG. 4, a first two-dimensional code 13a and a second two-dimensional code 13b are disposed on the side of the tire wheel 12. The first two-dimensional code 13a is disposed slightly away from the axle in a direction perpendicular to the axle. The second two-dimensional code 13b is disposed on an extension of the axle. The two-dimensional codes 13a and 13b are, for example, QR Codes (registered trademark), but other types of two-dimensional codes may be used as long as the angle of the two-dimensional code can be detected on an image.

[0021] 4, the imaging area R of the camera 7 is indicated by a two-dot chain line. The camera 7 is installed so that the wheel 10 is included in the imaging area R of the camera 7 when the vehicle 2 passes through a predetermined location such as the entrance to a garage. The imaging area R may include the entire wheel 10, rather than just a portion of the wheel 10.

[0022] <Hardware Configuration> FIG. 5 is a block diagram of various devices included in the anomaly detection system 1 of FIG. 1. FIG. 5 includes a block diagram of one of the multiple vehicle inspection systems 3 included in the anomaly detection system 1. As shown in FIG. 5, the data processing device 6 includes a processing circuit 20, a user interface 24, and a communication interface 25. The processing circuit 20 includes a processor 21, a system memory 22, and a storage memory 23. The processor 21 may include a CPU. The system memory 22 may include RAM. The storage memory 23 may include a hard disk, a flash memory, or a combination thereof. The storage memory 23 stores a program 23a. A configuration in which the processor 21 executes the program 23a read from the storage memory 23 to the system memory 22 is an example of the processing circuit 20, and the program 23a is an example of an anomaly detection program.

[0023] The user interface 24 includes an input interface and an output interface. The input interface includes at least one of a touch panel, a keyboard, a mouse, a microphone, etc. The output interface includes at least one of a display, a projector, a lamp, a speaker, etc. The communication interface 25 includes an interface for communicatively connecting to the communication network N via a wired or wireless connection. The communication interface 25 also includes a communication interface for connecting to the camera 7. The camera 7 is a digital optical machine for capturing digital images.

[0024] 5 includes a block diagram of the server 4 included in the anomaly detection system 1. The server 4 has a processing circuit 30 and a communication interface 34. The processing circuit 30 includes a processor 31, a system memory 32, and a storage memory 33. The processor 31 may include a CPU. The system memory 32 may include RAM. The storage memory 33 may include a hard disk, a flash memory, or a combination thereof. The storage memory 33 stores a program 33a. The communication interface 34 includes a communication interface that is communicatively connected to the communication network N via wire or wirelessly.

[0025] 5 includes a block diagram of one of the multiple information processing terminals 5 included in the anomaly detection system 1. The information processing terminal 5 includes a processing circuit 40, a user interface 44, and a communication interface 45. The processing circuit 40 includes a processor 41, a system memory 42, and a storage memory 43. The processor 41 may include a CPU. The system memory 42 may include RAM. The storage memory 43 may include a hard disk, a flash memory, or a combination thereof. The storage memory 43 stores a program 43a.

[0026] The user interface 44 includes an input interface and an output interface. The input interface includes at least one of a touch panel, a keyboard, a mouse, a microphone, etc. The output interface includes at least one of a display, a projector, a speaker, etc. The communication interface 45 includes a communication interface that is communicatively connected to the communication network N via a wired or wireless connection.

[0027] <Abnormality Detection Process> Fig. 6 is a flowchart illustrating the abnormality detection process in the abnormality detection system 1 of Fig. 1. In this embodiment, the entire abnormality detection process shown in Fig. 6 is executed by the processing circuitry 20 of the data processing device 6. However, part or all of the abnormality detection process may be executed by the processing circuitry 30 of the server 4, or by the processing circuitry 40 of the information processing terminal 5.

[0028] The abnormality detection process of this embodiment is executed every time the inspection target vehicle 2 passes in a predetermined direction through a location where the vehicle inspection system 3 is installed. For example, if the camera 7 is installed at the entrance to a garage, the abnormality detection process may be executed every time the inspection target vehicle 2 enters the garage.

[0029] The vehicle inspection system 3 may include a vehicle detection sensor 8. For example, the vehicle detection sensor 8 may be installed at a predetermined location such as the entrance to a garage, and the data processing device 6 may start the abnormality detection process when it receives information from the vehicle detection sensor 8 that a vehicle 2 has been detected. In this case, the multiple cameras 7 may be in a stopped state until the vehicle detection sensor 8 detects the vehicle 2, and the data processing device 6 may start the operation of the multiple cameras 7 when it receives information from the vehicle detection sensor 8 that a vehicle 2 has been detected. For example, the vehicle detection sensor 8 may be a well-known vehicle detection sensor that uses infrared rays or microwaves.

[0030] Furthermore, the vehicle inspection system 3 does not need to include the vehicle detection sensor 8. For example, the camera 7 may be constantly operating, and the data processing device 6 may start the abnormality detection process when it determines, using a known two-dimensional code recognition technology, that the two-dimensional code 13 is included in the image captured by the camera 7.

[0031] In the abnormality detection process, first, the data processing device 6 acquires, from the multiple cameras 7, multiple first images captured while the vehicle 2 is traveling at a low speed, so as to include the two-dimensional codes 13 on the multiple wheels 10 (step S1). The data processing device 6 acquires multiple second images captured while the vehicle 2 is traveling at a low speed at predetermined time intervals from the time the first images are captured, so as to include the two-dimensional codes 13 on the multiple wheels 10 (step S2). For example, each of the first image P1 and the second image P2 may be a frame constituting a moving image captured by the camera 7 at a predetermined frame rate.

[0032] The data processing device 6 reads the recorded information of the two-dimensional code 13 in the first image and the second image for each wheel 10 by image processing (step S3). The recorded information of the two-dimensional code 13 includes code ID information that indicates the identification information of the two-dimensional code itself. The recorded information of the two-dimensional code 13 may also include wheel identification information that is the identification information of the wheel 10 that includes the two-dimensional code 13. The recorded information of the two-dimensional code 13 may also include vehicle identification information that is the identification information of the vehicle to be inspected that is equipped with the wheel 10 that includes the two-dimensional code 13.

[0033] After step S3, the data processing device 6 calculates, for each wheel 10, the amount of rotational displacement of the orientation of the corresponding two-dimensional code 13 in the second image relative to the orientation of the corresponding two-dimensional code 13 in the first image (step S4). For example, the data processing device 6 calculates the orientation (i.e., posture) of the two-dimensional code 13 in the first image using a known two-dimensional code recognition technique, and calculates the orientation (i.e., posture) of the two-dimensional code 13 in the second image. The data processing device 6 calculates the amount of rotational displacement of the orientation of the two-dimensional code 13 by comparing the orientations of these two-dimensional codes 13.

[0034] The data processing device 6 calculates the angular velocity of each wheel 10 based on the rotational displacement amount corresponding to the wheel 10 and the time interval between the time the first image is captured and the time the second image is captured (step S5).

[0035] Steps S1 to S5 will be described in detail with reference to Figures 7 and 8. Figure 7 is a diagram showing an example of a first image P1 captured while the vehicle 2 is traveling. Figure 8 is a diagram showing a second image P2 captured a predetermined time interval t after the first image P1 in Figure 7 was captured.

[0036] 7 and 8, the first image P1 and the second image P2 include a two-dimensional code 13. The two-dimensional code 13 is a QR Code (registered trademark), and the position, size, and angle (tilt) of the two-dimensional code 13 on the image can be detected by identifying finder patterns at three of the four corners of the square. This makes it possible to know the orientation of the two-dimensional code 13 relative to a predetermined reference plane.

[0037] For example, a two-dimensional code 13 such as a QR code (registered trademark) may have finder patterns at three of the four corners of a square, and the basic orientation may be when the finder patterns are located at the upper right, upper left, and lower left corners. For example, the data processing device 6 calculates the angle θ1 formed by the top edge of the two-dimensional code 13 in the first image P1 (the edge connecting the finder patterns in the upper left and upper right corners) and the horizontal axis X on the first image P1 as the orientation of the two-dimensional code 13 in the first image P1, and calculates the angle θ2 formed by the top edge of the two-dimensional code 13 in the second image P2 and the horizontal axis X on the second image P2 as the orientation of the two-dimensional code 13 in the second image P2. Note that the method for calculating the angle of the two-dimensional code 13 in the QR code (registered trademark) is not limited to this, and other known methods (e.g., angle calculation based on a change in the width of the finder pattern) may also be used.

[0038] The data processing device 6 calculates the relative angle (θ2-θ1) between the two-dimensional code 13 in the first image P1 and the two-dimensional code 13 in the second image P2 as the amount of rotational displacement in the orientation of the two-dimensional code 13. The data processing device 6 also calculates the angular velocity ω of each wheel 10 by dividing the relative angle (θ2-θ1) by the time interval t between the capture of the first image P1 and the capture of the second image P2. For example, if the first image P1 and the second image P2 are two consecutive frames that make up a moving image captured by the camera 7 at a predetermined frame rate, the time interval t is a time indicated by the reciprocal of the frame rate.

[0039] 6 , the data processing device 6 determines whether any of the tires 11 on the plurality of wheels 10 has an abnormal internal pressure, based on the angular velocities of the plurality of wheels 10 (step S6). There are several possible methods for determining whether any of the tires 11 on the plurality of wheels 10 has an abnormal internal pressure using the angular velocities of the wheels 10. Depending on the determination method, determining whether any of the tires 11 on the plurality of wheels 10 has an abnormal internal pressure may include identifying which of the tires 11 on the plurality of wheels 10 has an abnormal internal pressure.

[0040] The following describes several examples of methods for determining whether an internal pressure of a tire 11 is abnormal using the angular velocity of the wheel 10. For ease of explanation, the description will be made on the assumption that the vehicle 2 to be inspected, for which an internal pressure abnormality of the tire 11 is determined using the following determination method, is a four-wheeled vehicle including a left front wheel 10a, a right front wheel 10b, a left rear wheel 10c, and a left rear wheel 10d, and that in step S5, the data processing device 6 calculates the angular velocity ωa of the left front wheel 10a, the angular velocity ωb of the right front wheel 10b, the angular velocity ωc of the left rear wheel 10c, and the angular velocity ωd of the left rear wheel 10d.

[0041] (Determination Method 1) Determination Method 1 is a method for determining whether or not a tire 11 with abnormal internal pressure is present on either of the two wheels 10 by comparing the angular velocities of two wheels 10 among the plurality of wheels 10 included in the vehicle 2 to be inspected. Determination Method 1 utilizes the difference in angular velocities between a wheel 10 including a tire 11 with no abnormal internal pressure and a wheel 10 including a tire 11 with abnormal internal pressure, and therefore can determine in a simple manner whether or not a tire 11 with abnormal internal pressure is present.

[0042] For example, a case will be described in which determination of whether or not there is an abnormality in one of the tires 11, the left front wheel 10a or the right front wheel 10b, is made using determination method 1. The data processing device 6 calculates the difference |ωa - ωb| between the angular velocity ωa of the left front wheel 10a and the angular velocity ωb of the right front wheel 10b. The data processing device 6 then divides this difference |ωa - ωb| by the angular velocity ωa of the left front wheel 10a and the angular velocity ωb of the right front wheel 10b, respectively, to calculate two evaluation values ​​(i.e., |ωa - ωb| / ωa and |ωa - ωb| / ωb). The data processing device 6 then determines whether or not each of the two evaluation values ​​exceeds a predetermined limit value L1. If the data processing device 6 determines that either of the two evaluation values ​​exceeds the predetermined limit value L1, it determines that there is an abnormality in the internal pressure of either the tire 11, the left front wheel 10a or the right front wheel 10b.

[0043] Furthermore, if the data processing device 6 determines that either of the two evaluation values ​​exceeds a predetermined limit value L1, it can identify that the tire 11 having the larger angular velocity out of the left front wheel 10a and the right front wheel 10b has an internal pressure abnormality. The reason for determining that the tire 11 having the larger angular velocity has an internal pressure abnormality is that the angular velocity of a tire with an internal pressure abnormality is larger than the angular velocity of a normal tire without an internal pressure abnormality.

[0044] The above-described determination method 1 can be expressed in another way as follows. That is, in order to determine whether the tire 11 on the left front wheel 10a has an internal pressure abnormality, the data processing device 6 sets the value |ωa-ωb| / ωb obtained by dividing the angular velocity difference |ωa-ωb| by the angular velocity ωb of the right front wheel 10b as an evaluation value, and determines whether the evaluation value |ωa-ωb| / ωb satisfies the following formula (1): |ωa-ωb| / ωb>L1 (1) If the data processing device 6 determines that formula (1) is satisfied, it identifies that the tire 11 on the left front wheel 10a has an internal pressure abnormality. The evaluation value exceeding the limit value L1, that is, formula (1), is an abnormality determination condition for determining whether the tire 11 on the left front wheel 10a has an internal pressure abnormality.

[0045] Similarly, to determine whether the tire 11 on the right front wheel 10b has an internal pressure abnormality, the data processing device 6 sets the value |ωa-ωb| / ωa obtained by dividing the angular velocity difference |ωa-ωb| by the angular velocity ωa of the left front wheel 10a as an evaluation value, and determines whether the evaluation value |ωa-ωb| / ωa satisfies the following equation (2): |ωa-ωb| / ωa>L1 (2) If the data processing device 6 determines that equation (2) is satisfied, it identifies that the tire 11 on the right front wheel 10b has an internal pressure abnormality. The evaluation value exceeding the limit value L1, in other words, equation (2), is an abnormality determination condition for determining whether the tire 11 on the right front wheel 10b has an internal pressure abnormality.

[0046] The above describes judgment method 1 using the example of determining whether there is an abnormality in one of the tires 11 on the left front wheel 10a and the right front wheel 10b, but the same method can also be used to determine whether there is an abnormality in one of the tires 11 on the left rear wheel 10c and the right rear wheel 10d.

[0047] Furthermore, in the above-described determination method 1, the angular velocities of two wheels 10 facing each other in the left-right direction are compared, but the combination of wheels 10 whose angular velocities are compared is not limited to this. For example, the angular velocities of two wheels 10 aligned in the front-rear direction may be compared. For example, when determining whether or not there is an internal pressure abnormality in one tire 11 of either the left front wheel 10a or the left rear wheel 10c using determination method 1, |ωa-ωc| / ωa and |ωa-ωc| / ωc are set as evaluation values ​​instead of |ωa-ωb| / ωa and |ωa-ωb| / ωb. Furthermore, the angular velocities of two wheels 10 arranged diagonally may be compared. For example, when determining whether or not there is an internal pressure abnormality in one tire 11 of either the left front wheel 10a or the right rear wheel 10d using determination method 1, |ωa-ωd| / ωa and |ωa-ωd| / ωd are set as evaluation values ​​instead of |ωa-ωb| / ωa and |ωa-ωb| / ωb.

[0048] (Determination Method 2) Determination Method 2 is a method for determining whether or not the tire 11 of the wheel 10 to be inspected has an abnormal internal pressure by comparing the angular velocity of the wheel 10 to be inspected with the average angular velocity of the plurality of wheels 10. By using Determination Method 2, it is possible to determine whether the angular velocity of the wheel 10 to be inspected significantly deviates from the average value of the angular velocities of the plurality of wheels 10, and therefore it is possible to easily identify the tire 11 with an abnormal internal pressure.

[0049] For example, a case will be described in which it is determined whether or not there is an abnormality in the tire 11 of the left front wheel 10a using the determination method 2. First, the data processing device 6 calculates the average angular velocities ωave of the left front wheel 10a, right front wheel 10b, left rear wheel 10c, and left rear wheel 10d using the following equation (3): ωave=(ωa+ωb+ωc+ωd) / 4 (3)

[0050] Next, the data processing device 6 calculates an evaluation value, ωa / ωave, by dividing the angular velocity ωa of the left front wheel 10a by the average angular velocity ωave. The data processing device 6 then determines whether the evaluation value ωa / ωave exceeds a predetermined limit value L2. That is, the data processing device 6 determines whether the evaluation value ωa / ωave satisfies the following equation (4): ωa / ωave>L2 (4) If the data processing device 6 determines that equation (4) is satisfied, it identifies that the tire 11 of the left front wheel 10a has an internal pressure abnormality. The evaluation value exceeding the limit value L2, i.e., equation (4), is an abnormality determination condition for determining whether the tire 11 of the left front wheel 10a has an internal pressure abnormality.

[0051] While the determination method 2 has been described above using an example of determining whether or not there is an abnormality in the tire 11 of the left front wheel 10a, the same method can be used to determine whether or not there is an abnormality in each of the tires 11 of the other wheels 10b, 10c, and 10d. For example, when determining whether or not there is an abnormality in the tire 11 of the right front wheel 10b, the left side of equation (4) is replaced with the evaluation value ωb / ωave.

[0052] (Determination Method 3) Determination Method 3 is a method for determining whether or not there is an internal pressure abnormality in the tire 11 of the wheel 10 being inspected by comparing the angular velocity of the wheel 10 being inspected with an absolute reference value that is unrelated to the angular velocities of the other wheels 10. By using Determination Method 3, it is possible to make a determination that is appropriate for the characteristics and state of the vehicle 2, and it is possible to accurately determine whether or not there is an internal pressure abnormality in the tire 11.

[0053] First, the data processing device 6 acquires vehicle-related information indicating the characteristics of the vehicle 2, the state of the vehicle 2, or a combination of the characteristics and state of the vehicle 2. Next, the data processing device 6 sets an evaluation value or an abnormality determination condition according to the acquired vehicle-related information. The evaluation value is the angular velocity of the wheel 10 itself, or a value based on the angular velocity, for determining whether or not there is an internal pressure abnormality. The data processing device 6 then determines whether or not the evaluation value satisfies the abnormality determination condition, and if it determines that the evaluation value satisfies the abnormality determination condition, it determines that there is an internal pressure abnormality in the tire 11 of the wheel 10 corresponding to the evaluation value.

[0054] For example, a case will be described in which determination of whether or not there is an abnormality in the tire 11 of the left front wheel 10a using determination method 3. The data processing device 6 sets the angular velocity ωa of the left front wheel 10a as the evaluation value. The data processing device 6 sets a limit value L3 included in the abnormality determination condition according to the acquired vehicle-related information. The data processing device 6 determines whether or not the angular velocity ωa, which is the evaluation value, exceeds the limit value L3. That is, the data processing device 6 determines whether or not the evaluation value ωa satisfies the following equation (5): ωa > L3 (5) If the data processing device 6 determines that equation (5) is satisfied, it identifies that there is an internal pressure abnormality in the tire 11 of the left front wheel 10a. The evaluation value exceeding the limit value L3, that is, equation (5), is the abnormality determination condition for determining whether or not there is an internal pressure abnormality in the tire 11 of the left front wheel 10a.

[0055] The setting of the limit value L3 according to the vehicle-related information will be described in detail below. A correspondence relationship between the vehicle-related information and the limit value L3 is pre-stored in the memory of the data processing device 6. The data processing device 6 sets the limit value L3 corresponding to the acquired vehicle-related information in accordance with the correspondence relationship.

[0056] For example, the vehicle-related information may include at least one of size information indicating the size of the wheels 10 equipped on the vehicle 2 to be inspected, speed information indicating the traveling speed of the vehicle 2 to be inspected, vehicle model information indicating the model of the vehicle 2 to be inspected, and load information indicating the weight of the cargo carried by the vehicle 2 to be inspected. For example, if the memory of the data processing device 6 stores a correspondence relationship between the size and traveling speed of the wheels 10 and the limit value L3, the data processing device 6 sets the limit value L3 corresponding to the acquired size information and speed information in accordance with the correspondence relationship.

[0057] For example, if the vehicle-related information includes size information, the data processing device 6 acquires the size information by reading the recorded information of the two-dimensional code 13 of the wheel 10. For example, the size information may be included in the recorded information of the two-dimensional code 13 of the wheel 10. The size information does not have to be included in the recorded information of the two-dimensional code 13. In this case, a correspondence between the code ID information and the size information of the wheel 10 may be stored in advance in the memory of the data processing device 6 or an external memory, and the data processing device 6 may acquire the size information associated with the code ID information of the read two-dimensional code 13 by referring to the correspondence.

[0058] Furthermore, for example, if the vehicle-related information includes speed information, the vehicle inspection system 3 may include equipment capable of measuring or calculating the traveling speed of the inspection target vehicle 2. For example, the vehicle inspection system 3 may include a speedometer such as a laser speedometer installed near the camera 7, and the data processing device 6 may receive the traveling speed measured by the speedometer.

[0059] Alternatively, the vehicle inspection system 3 may include a camera that captures an image of a two-dimensional code placed on the side of the vehicle body 14 of the vehicle 2 to be inspected at predetermined time intervals. The two-dimensional code placed on the side of the vehicle body 14 may be, for example, a QR code (registered trademark). The data processing device 6 may calculate the traveling speed by calculating the horizontal displacement per unit time of the two-dimensional code on the side of the vehicle body 14 from moving images or multiple still images received from the camera. Note that instead of including a camera that captures the two-dimensional code on the side of the vehicle body 14 separately from the camera 7 for capturing the two-dimensional code 13, the vehicle inspection system 3 may capture images of both the two-dimensional code 13 on the wheel 10 and the two-dimensional code placed on the side of the vehicle body 14 using the camera 7.

[0060] Alternatively, the data processing device 6 may receive from the vehicle 2 information relating to the traveling speed measured by a speedometer mounted on the vehicle 2 .

[0061] Furthermore, for example, if the vehicle-related information includes loading information, the vehicle inspection system 3 may include equipment capable of measuring or calculating the weight of the vehicle 2 to be inspected. For example, the vehicle inspection system 3 may include a weighing scale next to the camera 7, and the data processing device 6 may calculate the weight of the cargo carried by the vehicle 2 to be inspected based on the weight received from the weighing scale.

[0062] Alternatively, the data processing device 6 may receive information from the vehicle 2 regarding the weight of the cargo carried by the vehicle 2 to be inspected.

[0063] The above-described determination methods 1, 2, and 3 are merely examples. Evaluation values ​​and abnormality determination conditions can be set as appropriate. Two or more of the determination methods 1, 2, and 3 may be used in step S6.

[0064] As shown in FIG. 4 , when each wheel 10 includes two two-dimensional codes 13 (13a, 13b), the data processing device 6 executes steps S3 to S6 for each two-dimensional code 13. By using the multiple two-dimensional codes on the wheel 10 to determine whether or not the internal pressure of the tire 11 is abnormal, the accuracy of the determination can be improved. Furthermore, there may be cases where one of the multiple two-dimensional codes 13 included in the wheel 10 cannot be image-recognized due to some factor, such as dirt or scratches. Even in such cases, the internal pressure of the tire 11 can be determined to be abnormal using another two-dimensional code 13.

[0065] After step S6, the data processing device 6 outputs the determination result of step S6 (step S7). Specifically, the data processing device 6 transmits the determination result to the server 4. The determination result is transmitted together with the code ID information. The determination result may be transmitted together with at least one of the wheel identification information and the vehicle identification information so that the tire 11 with the abnormal internal pressure and the vehicle 2 equipped with the tire 11 can be immediately identified. For example, if the determination result indicates that there is no abnormality in any of the tires 11 on the multiple wheels 10, the data processing device 6 does not need to transmit the determination result to the server 4.

[0066] The server 4 stores the determination result that the tire 11 has an abnormal internal pressure in the storage memory 33 in association with the code ID information of the two-dimensional code 13 corresponding to the tire 11 identified as having an abnormal internal pressure.

[0067] The server 4 associates the determination result that there is an internal pressure abnormality with the code ID information of the two-dimensional code 13 corresponding to the tire 11 identified as having an internal pressure abnormality, and transmits the result to a pre-designated information processing terminal 5. For example, the server 4 may transmit the determination result to a destination indicated by the destination information associated with the code ID information of the two-dimensional code 13. For example, if the determination result indicates that there is no abnormality in any of the tires 11 of the multiple wheels 10, the server 4 does not need to transmit the determination result to the information processing terminal 5.

[0068] As described above, in the abnormality detection system 1 according to this embodiment, the angular velocity of each wheel 10 is calculated from an image captured to include the two-dimensional codes 13 of multiple wheels 10, and therefore, the angular velocity of the wheels 10 can be obtained without using a sensor mounted on the vehicle 2, thereby detecting an abnormality in the internal pressure of the tires 11 of the vehicle 2.

[0069] In this embodiment, the determination result that there is an abnormal internal pressure is stored in association with the code ID information of the two-dimensional code 13 corresponding to the tire 11 identified as having an abnormal internal pressure. This makes it possible to immediately identify the tire 11 having an abnormal internal pressure.

[0070] Other Embodiments The present disclosure is not limited to the above-described embodiments, and the configurations thereof may be changed, added, or deleted.

[0071] For example, in the above embodiment, the anomaly detection process is executed by the processing circuitry 20 of the data processing device 6, but part or all of the anomaly detection process may be executed by the processing circuitry 30 of the server 4. For example, the data processing device 6 may transmit information including the first image and the second image captured by the camera 7 to the server 4. The processing circuitry 30 of the server 4 may execute the anomaly detection process based on the image information received from the data processing device 6, etc.

[0072] A part or all of the anomaly detection process may be executed by the processing circuitry 40 of the information processing terminal 5. For example, the server 4 may store information including the first image and the second image sent from the data processing device 6, and the information processing terminal 5 that accesses the server 4 may receive the information including the first image and the second image from the server 4 and execute the anomaly detection process. The information processing terminal 5 may receive the information including the first image and the second image from the data processing device 6 and execute the anomaly detection process.

[0073] Two or more of the processing circuit 20 of the data processing device 6, the processing circuit 30 of the server 4, and the processing circuit 40 of the information processing terminal 5 may share and execute the abnormality detection process. For example, the processing circuit 20 of the data processing device 6 may execute the processes from steps S1 to S5, and the processing circuit 30 of the server 4 may receive the angular velocity information obtained in step S5 from the data processing device 6 and execute the process of step S6 based on the angular velocity information.

[0074] For example, the number of wheels provided on the inspection target vehicle 2 does not have to be four. For example, the number of wheels provided on the inspection target vehicle 2 may be six or eight.

[0075] The multiple cameras 7 are preferably positioned so as to simultaneously capture images of the multiple wheels 10 of the vehicle 2 to be inspected. In the above embodiment, the number of cameras 7 provided in the vehicle inspection system 3 and the number of wheels 10 of the vehicle 2 to be inspected do not have to be the same as or may be different from each other. Furthermore, the vehicle inspection system 3 may be provided with a different number of cameras 7. The number of cameras 7 provided in the vehicle inspection system 3 does not have to be four, and may be, for example, one, two, or six or more. When the vehicle inspection system 3 is provided with two cameras 7, the two cameras 7 are preferably positioned so as to simultaneously capture images of the two front wheels 10 of the wheels 10 of the vehicle 2 to be inspected.

[0076] An image of one camera 7 may include multiple wheels 10. For example, a six-wheeled truck has two front wheels and four rear wheels, and the four rear wheels are arranged at close distances in the front-to-rear direction. Therefore, for example, two rear wheels arranged in a row on one side (left or right) may be imaged by one camera.

[0077] The anomaly detection system 1 does not need to include a server 4. In this case, the data processing device 6 may directly transmit the determination result to the information processing terminal 5. Furthermore, the anomaly detection system 1 does not need to include multiple information processing terminals 5. For example, the data processing device 6 may output the determination result to the user interface 24. The vehicle inspection system 3 may also be provided with a separate output device that receives the determination result from the data processing device 6 and outputs the determination result or information corresponding to the determination result. The number of vehicle inspection systems 3 included in the anomaly detection system 1 does not need to be multiple, and may be one.

[0078] The determination methods 1, 2, and 3 described in the above embodiments can be modified as appropriate. For example, the limit value L1 of the determination method 1 may be a fixed value or a variable value that changes depending on the vehicle-related information. For example, the limit value L2 of the determination method 2 may be a fixed value or a variable value that changes depending on the vehicle-related information. For example, the limit value L3 of the determination method 3 may be a fixed value. In this case, the evaluation value may be a value that is set based on the angular velocity and the vehicle-related information, rather than the angular velocity of the wheel 10 itself.

[0079] Furthermore, in the above embodiment, the angular velocity of the wheel is calculated using a first image and a second image taken at a predetermined time interval from each other, but the accuracy of calculating the angular velocity of the wheel can be improved by using not only an image set consisting of a plurality of first images and a plurality of second images, but also another image set taken at a predetermined time interval from each other.

[0080] More specifically, in addition to acquiring the image sets made up of a plurality of first images and a plurality of second images in steps S1 and S2, the processing circuit may also acquire (N-1) image sets, where N is an integer greater than or equal to 2. Each of the (N-1) image sets is made up of a plurality of k-th images and a plurality of (k+1)-th images taken while the vehicle is running at a time interval from each other so as to include the two-dimensional codes of a plurality of wheels, where k is any integer greater than or equal to 2 and less than or equal to N. In this way, N image sets are obtained, including the image sets made up of a plurality of first images and a plurality of second images.

[0081] Such a set of N images can be easily obtained, for example, by capturing a moving image at a predetermined frame rate using the camera 7. In this case, each of the N sets of images includes two consecutive frames from among the multiple frames that make up the moving image.

[0082] Furthermore, the processing circuit may calculate, for each image set, a rotational displacement amount of the orientation of the corresponding two-dimensional code in the (k+1)th image relative to the orientation of the corresponding two-dimensional code in the kth image.The processing circuit may then calculate the angular velocity of each wheel by calculating an average value of the calculated N rotational displacement amounts and dividing the average value by the time interval.Alternatively, the processing circuit may use, from the N rotational displacement amounts, values ​​that deviate from the average value by a difference equal to or greater than a predetermined threshold to calculate the angular velocity.

[0083] As described above, the above embodiments have been described as examples of the technology disclosed in this application. However, the technology of the present disclosure is not limited to these and can be applied to embodiments in which modifications, substitutions, additions, omissions, etc. are made as appropriate. Furthermore, the components described in the above embodiments can be combined to create new embodiments. For example, some configurations or methods in one embodiment may be applied to other embodiments, and some configurations in an embodiment may be separated and arbitrarily extracted from other configurations in that embodiment. Furthermore, the components described in the accompanying drawings and detailed description include not only components essential for solving the problem, but also components that are not essential for solving the problem, and are used to illustrate the technology. Two blocks shown in a sequential order in a flowchart may be executed simultaneously or in reverse order, depending on the circumstances.

[0084] The functions of the elements disclosed herein can be performed using circuits or processing circuits, including general-purpose processors, special-purpose processors, integrated circuits, application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), conventional circuits, and / or combinations thereof, configured or programmed to perform the disclosed functions. Processors are considered processing circuits or circuits because they include transistors and other circuitry. In this disclosure, a circuit, unit, or means is hardware that performs the recited functions or hardware that is programmed to perform the recited functions. The hardware may be hardware disclosed herein or other known hardware that is programmed or configured to perform the recited functions. Where the hardware is a processor, which is considered a type of circuit, the circuit, means, or unit is a combination of hardware and software, and the software is used to configure the hardware and / or processor.

[0085] Each of the following aspects is a disclosure of a preferred embodiment.

[0086] [Aspect 1] An abnormality detection system for detecting an abnormality in the internal pressure of a tire of a vehicle having a tire, a tire wheel on which the tire is mounted, and a plurality of wheels each including a two-dimensional code disposed on a side of the tire wheel, the abnormality detection system comprising a processing circuit configured to: acquire a plurality of first images captured while the vehicle is traveling, the first images including the two-dimensional codes of the plurality of wheels; acquire a plurality of second images captured while the vehicle is traveling at a predetermined time interval from the time the first images are captured, the second images including the two-dimensional codes of the plurality of wheels; calculate, for each of the wheels, an amount of rotational displacement of the orientation of the corresponding two-dimensional code in the second image relative to the orientation of the corresponding two-dimensional code in the first image; calculate, for each of the wheels, the angular velocity of each of the wheels based on the corresponding amount of rotational displacement and the time interval; and determine whether or not any tire of the plurality of wheels has an abnormal internal pressure based on the angular velocities of the plurality of wheels.

[0087] According to the above configuration, it is possible to obtain the angular velocity of the wheels and detect an abnormality in the internal pressure of the vehicle's tires without using a sensor mounted on the vehicle.

[0088] [Aspect 2] The anomaly detection system according to Aspect 1, wherein determining whether any of the tires of the plurality of wheels has an abnormal internal pressure includes identifying which of the tires of the plurality of wheels has an abnormal internal pressure, and the processing circuit is further configured to, after identifying the tire with the abnormal internal pressure, store the determination result that there is an abnormal internal pressure in association with code ID information of the two-dimensional code corresponding to the tire identified as having the abnormal internal pressure.

[0089] According to the above configuration, the determination result that there is an abnormal internal pressure is associated with the code ID information, so that it is possible to immediately identify the tire that has an abnormal internal pressure.

[0090] [Aspect 3] The plurality of wheels include a first wheel and a second wheel, and determining whether any tire of the plurality of wheels has an abnormal internal pressure comprises: setting an evaluation value that changes according to a change in the difference between the angular velocity of the first wheel and the angular velocity of the second wheel; determining whether the evaluation value satisfies an abnormality determination condition; and determining that the tire of the first wheel or the tire of the second wheel has an abnormal internal pressure if it is determined that the evaluation value satisfies the abnormality determination condition.

[0091] According to the above configuration, it is possible to determine in a simple manner whether a tire has an abnormal internal pressure by utilizing the difference in angular velocity between a wheel having a tire with no abnormal internal pressure and a wheel having a tire with an abnormal internal pressure.

[0092] [Aspect 4] The anomaly detection system according to any one of Aspects 1 to 3, wherein determining whether or not a tire among the plurality of tires has an internal pressure abnormality includes: determining whether or not an evaluation value, which is the angular velocity itself or a value based on the angular velocity, satisfies an abnormality determination condition; and, if it is determined that the evaluation value satisfies the abnormality determination condition, determining that the tire corresponding to the evaluation value has an internal pressure abnormality.

[0093] According to the above configuration, an evaluation value corresponding to the angular velocity of each wheel is used to determine whether the tire internal pressure of that wheel is abnormal, so that the tire with the abnormal internal pressure can be easily identified.

[0094] [Aspect 5] The anomaly detection system according to Aspect 4, wherein determining whether the evaluation value satisfies the anomaly determination condition includes setting the evaluation value or the anomaly determination condition using an average value of the angular velocities of the plurality of wheels.

[0095] According to the above configuration, it is possible to grasp the angular velocity of a wheel that deviates significantly from the average value of the angular velocities of a plurality of wheels, and therefore it is possible to easily identify a tire with an abnormal internal pressure.

[0096] [Aspect 6] The anomaly detection system according to Aspect 4 or 5, wherein the processing circuit is further configured to: acquire vehicle-related information indicating a feature of the vehicle, a state of the vehicle, or a combination of the feature of the vehicle and the state of the vehicle; and set the evaluation value, the abnormality determination condition, or both the evaluation value and the abnormality determination condition, according to the acquired vehicle-related information.

[0097] According to the above configuration, the evaluation value or abnormality judgment conditions are set according to the characteristics and condition of the vehicle, so that judgment appropriate to the characteristics and condition of the vehicle can be made, and the presence or absence of an abnormality in the tire internal pressure can be accurately determined.

[0098] [Aspect 7] The anomaly detection system according to Aspect 6, wherein the vehicle-related information includes size information indicating the size of the wheels equipped on the vehicle, and acquiring the vehicle-related information includes: reading the recorded information of the two-dimensional code; and acquiring the size information included in or associated with the recorded information.

[0099] According to the above configuration, the evaluation value or abnormality determination condition can be set according to the wheel size. Furthermore, since the wheel size can be determined by reading the information recorded in the two-dimensional code, size information can be easily obtained.

[0100] [Aspect 8] The anomaly detection system according to Aspect 6 or 7, wherein the vehicle-related information includes speed information indicating a traveling speed of the vehicle, and setting the evaluation value or the abnormality determination condition includes setting the abnormality determination condition corresponding to the acquired vehicle-related information in accordance with a predetermined correspondence relationship between the traveling speed of the vehicle and the abnormality determination condition.

[0101] According to the above configuration, abnormality determination conditions suitable for the vehicle's traveling speed can be set, and abnormalities in tire internal pressure can be detected with high accuracy.

[0102] [Aspect 9] The anomaly detection system according to any one of Aspects 1 to 8, wherein a second two-dimensional code is arranged on the side of each of the tire wheels in addition to the first two-dimensional code, and the second two-dimensional code is included in both the first image and the second image, and the processing circuit is further configured to: calculate, for each of the wheels, a second rotational displacement amount of an orientation of the second two-dimensional code in the second image relative to an orientation of the second two-dimensional code in the first image; calculate, for each of the wheels, a second angular velocity of each of the wheels based on the corresponding second rotational displacement amount and the time interval; and determine whether or not any tire of the plurality of wheels has an abnormal internal pressure based on the second angular velocities of the plurality of wheels.

[0103] According to the above configuration, for example, when both the first two-dimensional code and the second two-dimensional code are recognized, the tire internal pressure abnormality can be determined using both the first angular velocity obtained based on the first two-dimensional code and the second angular velocity obtained based on the second two-dimensional code, thereby improving the determination accuracy. Furthermore, for example, there are cases where the first two-dimensional code cannot be image-recognized due to some factor, such as dirt or scratches. Even in such cases, the tire internal pressure abnormality can be determined using the image-recognizable two-dimensional code of the first two-dimensional code and the second two-dimensional code.

[0104] [Aspect 10] The anomaly detection system according to any one of Aspects 1 to 9, wherein the processing circuitry is further configured to: acquire (N-1) image sets other than an image set composed of the plurality of first images and the plurality of second images, where N is an integer greater than or equal to 2, and the (N-1) image sets are composed of a plurality of k-th images and a plurality of (k+1)-th images taken while the vehicle is running at the time intervals from each other so as to include the two-dimensional codes of the plurality of wheels, where k is an integer greater than or equal to 2 and less than or equal to N; and calculate, for each image set, an amount of rotational displacement of the orientation of the corresponding two-dimensional code in the (k+1)-th image relative to the orientation of the corresponding two-dimensional code in the k-th image; and calculate the angular velocity of each of the wheels by calculating the angular velocity of each of the wheels based on the calculated N amounts of rotational displacement.

[0105] According to the above configuration, the angular velocity of the wheel can be calculated with high accuracy using a plurality of image sets, and as a result, the accuracy of abnormality determination can be improved.

[0106] [Aspect 11] An abnormality detection method for detecting an abnormality in the internal pressure of a tire of a vehicle having a tire, a tire wheel on which the tire is mounted, and a plurality of wheels each including a two-dimensional code disposed on a side of the tire wheel, the abnormality detection method comprising: acquiring a plurality of first images captured while the vehicle is traveling, the first images including the two-dimensional codes of the plurality of wheels; acquiring a plurality of second images captured while the vehicle is traveling at predetermined time intervals from the time the first images are captured, the second images including the two-dimensional codes of the plurality of wheels; calculating, for each of the wheels, an amount of rotational displacement of the orientation of the corresponding two-dimensional code in the second image relative to the orientation of the corresponding two-dimensional code in the first image; calculating, for each of the wheels, the angular velocity of each of the wheels based on the corresponding amount of rotational displacement and the time interval; and determining whether or not any tire of the plurality of wheels has an abnormal internal pressure based on the angular velocities of the plurality of wheels.

[0107] According to the method, it is possible to obtain the angular velocity of the wheels without using a sensor mounted on the vehicle and detect an abnormality in the internal pressure of the vehicle's tires.

[0108] [Aspect 12] A storage medium having recorded thereon an anomaly detection program that causes at least one processor to execute the anomaly detection method according to aspect 11.

[0109] 1: Anomaly detection system 2: Vehicle 4: Server 5: Information processing terminal 6: Data processing device 7: Camera 10: Wheel 11: Tire 12: Tire wheel 13: Two-dimensional code 20: Processing circuit P1: First image P2: Second image

Claims

1. An abnormality detection system for detecting an abnormality in the internal pressure of a tire of a vehicle having a tire, a tire wheel on which the tire is mounted, and a plurality of wheels including a two-dimensional code placed on a side of the tire wheel, the abnormality detection system comprising a processing circuit, the processing circuit being configured to: acquire a plurality of first images taken while the vehicle is traveling, the first images including the two-dimensional codes of the plurality of wheels; acquire a plurality of second images taken while the vehicle is traveling at a predetermined time interval from the time when the first images are taken, the second images including the two-dimensional codes of the plurality of wheels; calculate, for each of the wheels, an amount of rotational displacement of an orientation of the corresponding two-dimensional code in the second image relative to an orientation of the corresponding two-dimensional code in the first image; calculate, for each of the wheels, an angular velocity of each of the wheels based on the corresponding amount of rotational displacement and the time interval; and determine whether or not a tire with an abnormal internal pressure is present among the tires of the plurality of wheels based on the angular velocities of the plurality of wheels.

2. The anomaly detection system of claim 1, wherein determining whether or not there is a tire with abnormal internal pressure among the tires of the plurality of wheels includes identifying which tire among the tires of the plurality of wheels has abnormal internal pressure, and the processing circuit is further configured to, after identifying the tire with abnormal internal pressure, store the determination result that there is an abnormal internal pressure in association with code ID information of the two-dimensional code corresponding to the tire identified as having abnormal internal pressure.

3. The abnormality detection system of claim 1 or 2, wherein the plurality of wheels include a first wheel and a second wheel, and determining whether or not a tire having an abnormal internal pressure is present among the tires of the plurality of wheels includes: setting an evaluation value that changes according to changes in the difference between the angular velocity of the first wheel and the angular velocity of the second wheel; determining whether or not the evaluation value satisfies an abnormality determination condition; and if it is determined that the evaluation value satisfies the abnormality determination condition, determining that the tire of the first wheel or the tire of the second wheel has an abnormal internal pressure.

4. The anomaly detection system of claim 1 or 2, wherein determining whether or not there is a tire among the plurality of tires that has an abnormal internal pressure includes: determining whether or not an evaluation value, which is the angular velocity itself or a value based on the angular velocity, satisfies an abnormality determination condition; and if it is determined that the evaluation value satisfies the abnormality determination condition, determining that the tire corresponding to the evaluation value has an abnormal internal pressure.

5. The abnormality detection system of claim 4, wherein determining whether the evaluation value satisfies the abnormality judgment condition includes setting the evaluation value or the abnormality judgment condition using an average value of the angular velocities of the multiple wheels.

6. The abnormality detection system of claim 4, wherein the processing circuit is further configured to: acquire vehicle-related information indicating the characteristics of the vehicle, the state of the vehicle, or a combination of the characteristics of the vehicle and the state of the vehicle; and set the evaluation value, the abnormality judgment condition, or both the evaluation value and the abnormality judgment condition according to the acquired vehicle-related information.

7. The anomaly detection system of claim 6, wherein the vehicle-related information includes size information indicating the size of the wheels equipped on the vehicle, and acquiring the vehicle-related information includes: reading the recorded information of the two-dimensional code; and acquiring the size information contained in or associated with the recorded information.

8. The abnormality detection system of claim 6, wherein the vehicle-related information includes speed information indicating a traveling speed of the vehicle, and setting the evaluation value or the abnormality judgment condition includes setting the abnormality judgment condition corresponding to the acquired vehicle-related information in accordance with a predetermined correspondence relationship between the traveling speed of the vehicle and the abnormality judgment condition.

9. The anomaly detection system described in claim 1 or 2, wherein a second two-dimensional code is arranged on the side of each of the tire wheels in addition to the first two-dimensional code which is the two-dimensional code, and both the first image and the second image include the second two-dimensional code, and the processing circuit is further configured to: calculate, for each of the wheels, a second rotational displacement amount of an orientation of the second two-dimensional code in the second image relative to an orientation of the second two-dimensional code in the first image; calculate, for each of the wheels, a second angular velocity of each of the wheels based on the corresponding second rotational displacement amount and the time interval; and determine whether or not there is a tire with abnormal internal pressure among the tires of the plurality of wheels based on the second angular velocities of the plurality of wheels.

10. The anomaly detection system according to claim 1 or 2, wherein the processing circuit is further configured to: acquire (N-1) image sets other than an image set composed of the plurality of first images and the plurality of second images, where N is an integer equal to or greater than 2, and the (N-1) image sets are composed of a plurality of k-th images and a plurality of (k+1)-th images taken while the vehicle is traveling with the time interval between each other so as to include the two-dimensional codes of the plurality of wheels, where k is all integers equal to or greater than 2 and equal to or less than N; and calculate, for each image set, an amount of rotational displacement of an orientation of the corresponding two-dimensional code in the (k+1)-th image relative to an orientation of the corresponding two-dimensional code in the k-th image; and calculating the angular velocity of each of the wheels comprises calculating the angular velocity of each of the wheels based on the calculated N amounts of rotational displacement.

11. An abnormality detection method for detecting an abnormality in the internal pressure of a tire of a vehicle having a tire, a tire wheel on which the tire is mounted, and a plurality of wheels including a two-dimensional code placed on a side of the tire wheel, the abnormality detection method comprising: acquiring a plurality of first images taken while the vehicle is traveling, the first images including the two-dimensional codes of the plurality of wheels; acquiring a plurality of second images taken while the vehicle is traveling at a predetermined time interval from the time when the first images are taken, the second images including the two-dimensional codes of the plurality of wheels; calculating, for each of the wheels, an amount of rotational displacement of the orientation of the corresponding two-dimensional code in the second image relative to the orientation of the corresponding two-dimensional code in the first image; calculating, for each of the wheels, the angular velocity of each of the wheels based on the corresponding amount of rotational displacement and the time interval; and determining whether or not a tire with an internal pressure abnormality is present among the tires of the plurality of wheels, based on the angular velocities of the plurality of wheels.

12. A storage medium having recorded thereon an anomaly detection program for causing at least one processor to execute the anomaly detection method according to claim 11.

Images