Detection device, detection program, and detection system

Abstract

This method allows for the detection of tire separation on mining vehicles at a lower cost compared to using thermography to detect tire separation from temperature changes. [Solution] The detection device 10 either uses a microphone as a detection sensor 5 to collect sound generated from the tires of the vehicle 6 as collected data, or uses an odor sensor as a detection sensor 5 to collect odor generated from the tires of the vehicle 6 as collected data, and uses the collected data to detect whether or not separation has occurred in the tires.

Description

Technical Field

[0001] The present disclosure relates to a detection device, a detection program, and a detection system.

Background Art

[0002] Patent Document 1 discloses a management system for managing a mining machine traveling in a mine by determining whether a damage operation that damages a tire has been performed.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Unlike paved roads, the roadways provided in mines where minerals are mined are often rough roads with depressions and rocks scattered everywhere. In the tires used on such roadways, for example, when the tire repeatedly rides over rocks, fine separation, that is, separation may occur at the joint surface between the rubber and rubber or between the rubber and steel cord that make up the tire. As the occurrence of separation progresses, the temperature of the tire may locally rise due to the friction between the objects that were joined at the joint surface until then, and a peculiar odor may occur. Furthermore, if the vehicle continues to travel in this state, an excessive load may be applied to the tire.

[0005] When the separation of the tire progresses in this way, for example, the need to replace the tire without waiting for the next regular inspection of the tire arises, increasing the economic burden on the mineral mining operator.

[0006] Therefore, when tire separation occurs, the tire temperature rises, and a method is sometimes used to measure the tire surface temperature using thermography and detect the occurrence of separation from the change in tire surface temperature. However, thermography with measurement accuracy sufficient to detect separation by temperature is very expensive compared to commonly available thermography used to measure, for example, human body temperature. Moreover, in mines, multiple vehicles travel through various locations, requiring the introduction of multiple thermography cameras according to the vehicle's driving conditions, and the adoption of separation detection systems using thermography has not progressed.

[0007] This disclosure aims to provide a detection device, detection program, and detection system that can detect tire separation on mining vehicles at a lower cost compared to detecting tire separation on mining vehicles from temperature changes using thermography. [Means for solving the problem]

[0008] The detection device according to the first embodiment includes a data collection unit that uses a microphone as a detection sensor to collect sound generated from the tires of a mining vehicle as collected data, or uses an odor sensor as the detection sensor to collect odor generated from the tires of a mining vehicle as collected data, and a detection unit that uses the collected data collected by the data collection unit to detect whether or not separation has occurred in the tires.

[0009] The detection device according to the second embodiment, in the detection device according to the first embodiment, detects that separation has occurred in the tire when the loudness of the sound or the intensity of the odor represented by the collected data exceeds a predetermined threshold.

[0010] The detection device according to the third embodiment is the detection device according to the second embodiment, wherein the detection sensor is installed on a mining vehicle.

[0011] The detection device according to the fourth embodiment is the detection device according to the third embodiment, wherein the detection sensor is installed at each mounting position of the tire, and the detection unit detects whether or not separation has occurred in the tire at each mounting position.

[0012] The detection device according to the fifth embodiment is the detection device according to the third embodiment, wherein, when the detection sensor is the odor sensor, the odor sensor is installed in the air conditioning duct connected to the interior of the mining vehicle.

[0013] The detection device according to the sixth embodiment further comprises, in the case of the detection device according to the fourth embodiment, an identification unit that identifies a mining vehicle in which separation has occurred in the tire, using the audio data which is the collected data collected by the data collection unit, when the detection unit is the microphone, and when the detection unit detects that separation has occurred in the tire, the identification unit identifies that separation has occurred in the tire of the mining vehicle on which the microphone is installed if the loudness of the sound represented by the audio data is above the threshold for a specified period of time, and identifies that separation has occurred in the tire of a mining vehicle other than the mining vehicle on which the microphone is installed if the period during which the loudness of the sound represented by the audio data is above the threshold is less than the specified period.

[0014] The detection device according to the seventh embodiment further comprises, in the case of the detection device according to the fourth embodiment, an identification unit that identifies a mining vehicle in which separation has occurred in the tire, using the audio data which is the collected data collected by the data collection unit, when the detection unit is the microphone, and when the detection unit detects that separation has occurred in the tire, the identification unit identifies that separation has occurred in the tire of the mining vehicle on which the microphone is installed if the frequency of the sound in a time series represented by the audio data falls within a predetermined frequency range, and identifies that separation has occurred in the tire of a different mining vehicle from the mining vehicle on which the microphone is installed if the frequency of the sound in a time series represented by the audio data exceeds the frequency range.

[0015] The detection device according to the eighth embodiment further includes an output unit that, when the detection unit detects that separation has occurred in the tire, outputs an alarm along with additional information indicating whether the mining vehicle in which separation has occurred is the mining vehicle on which the microphone is installed or another mining vehicle.

[0016] The detection device according to the ninth embodiment further comprises an information acquisition unit that acquires position information of each mining vehicle traveling on the same mine track, and when the identification unit identifies that separation has occurred in the tires of the other mining vehicle, it identifies the other mining vehicle whose position changes are consistent with the change in sound volume, based on the change in sound volume over time represented by the audio data and the change in position of the other mining vehicle over time represented by the position information.

[0017] The detection device according to the tenth embodiment further comprises an output unit that, when the detection unit detects that separation has occurred in the tire, outputs an alarm along with identification information that identifies the other mining vehicle identified by the identification unit.

[0018] The detection device according to the 11th embodiment further comprises an information acquisition unit that acquires position information of each mining vehicle traveling on the same mine track, and when the identification unit identifies that separation has occurred in the tires of the other mining vehicle, at the inflection point time when an inflection point appears in which the frequency of the sound represented by the audio data changes from rising to falling, the identification unit identifies the mining vehicle that shows movement that approaches the mining vehicle on which the microphone is installed, among the mining vehicles whose position is represented by the position information, as the other mining vehicle on which separation has occurred in the tires.

[0019] The detection device according to the 12th embodiment further comprises an output unit that, when the detection unit detects that separation has occurred in the tire, outputs an alarm along with identification information that identifies the other mining vehicle identified by the identification unit.

[0020] The detection device according to the 13th embodiment further comprises, in the detection device according to the 5th embodiment, an identification unit that identifies a mining vehicle in which separation has occurred in the tire using the odor data, which is the collected data, collected by the data collection unit, and when the detection unit detects that separation has occurred in the tire, the identification unit identifies that separation has occurred in the tire of the mining vehicle on which the odor sensor is installed if the intensity of the odor represented by the odor data is above the threshold for a specified period of time, and identifies that separation has occurred in the tire of a mining vehicle other than the mining vehicle on which the odor sensor is installed if the period during which the intensity of the odor represented by the odor data is above the threshold is less than the specified period.

[0021] The detection device according to the 14th aspect is the detection device according to the 13th aspect, and when it is detected by the detection unit that separation has occurred in the tire, together with an alarm, it outputs additional information indicating whether the mining vehicle in which separation has occurred in the tire is the mining vehicle on which the odor sensor is installed or the other mining vehicle.

[0022] The detection device according to the 15th aspect is the detection device according to the 1st aspect or the 2nd aspect, and the detection sensor is installed on the travel path of the mining vehicle.

[0023] The detection device according to the 16th aspect is the detection device according to the 15th aspect, and the detection sensor is installed along the travel path on which the mining vehicle travels from the bottom of the pit, which is a depression formed by mineral mining, to above the pit.

[0024] The detection device according to the 17th aspect is the detection device according to the 15th aspect, and the detection sensor is installed at an intersection where a plurality of travel paths intersect.

[0025] The detection device according to the 18th aspect is the detection device according to the 15th aspect, and the detection sensor is installed at the entrance and exit of a supply station that supplies a power source to the mining vehicle.

[0026] The detection device according to the 19th aspect is the detection device according to the 15th aspect, and the detection sensor is installed at the entrance and exit of a unloading site where the mining vehicle unloads the mined minerals.

[0027] The detection device according to the 20th aspect is the detection device according to the 15th aspect, and the detection sensor is installed at the entrance and exit of a loading site where minerals are loaded onto the mining vehicle.

[0028] The detection device according to the 21st aspect is the detection device according to the 15th aspect, and the detection sensor is set at the entrance and exit of a rest area where the driver of the mining vehicle takes a rest.

[0029] The detection device according to the 22nd embodiment is a detection device according to the 1st or 2nd embodiment in which the detection sensor is installed on equipment operating in a mine other than mining vehicles.

[0030] The detection device according to the 23rd embodiment is one in which the detection sensor is installed in the unloading equipment of an unloading area where mining vehicles unload the mined minerals, as described in the detection device according to the 22nd embodiment.

[0031] The detection device according to the 24th embodiment is a detection device according to the 22nd embodiment in which the detection sensor is installed in the loading equipment of a loading area where minerals are loaded onto mining vehicles.

[0032] The detection device according to the 25th embodiment is a detection device according to any one of the 15th to 24th embodiments, further comprising: an information acquisition unit that acquires location information of each mining vehicle traveling on the same mine track when the detection sensor is the microphone; and an identification unit that identifies a mining vehicle in which tire separation has occurred using the location information acquired by the information acquisition unit and the collected data, which is the audio data, collected by the data collection unit. When the detection unit detects that tire separation has occurred, the identification unit identifies a mining vehicle in which tire separation has occurred based on the change in sound volume over time as represented by the audio data and the change in the position of the mining vehicle over time as represented by the location information, by identifying a mining vehicle whose change in position matches the change in sound volume.

[0033] In the detection device according to the 26th embodiment, if there are multiple mining vehicles that show a change in position that matches the change in the loudness of the sound, the identification unit identifies, among the multiple mining vehicles whose driving status is represented by the change in position information, a mining vehicle that shows a change in position that matches the approach of the mining vehicle to the microphone obtained from the change in the frequency of the sound represented by the audio data, as a mining vehicle in which separation has occurred in the tires.

[0034] The detection device according to the 27th embodiment outputs an alarm and identification information identifying the mining vehicle identified by the identification unit when the detection unit in the detection device according to the 25th embodiment or the 26th embodiment detects that separation has occurred in the tire.

[0035] The detection device according to the 28th embodiment is a detection device according to any one of the 15th to 24th embodiments, further comprising: an information acquisition unit that acquires position information of each mining vehicle traveling on the same mine track, and an identification unit that identifies a mining vehicle in which tire separation has occurred, using the position information acquired by the information acquisition unit and the collected data, which is audio data, collected by the data collection unit, when the detection unit detects that tire separation has occurred, the identification unit identifies the mining vehicle in which tire separation has occurred as the mining vehicle in which tire separation has occurred, at the inflection point time when an inflection point appears in which the frequency of the sound represented by the audio data changes from rising to falling, among the mining vehicles whose position is represented by the position information, the mining vehicle that shows movement that is closest to the microphone.

[0036] In the detection device according to the 29th embodiment, if there are multiple mining vehicles about to pass in front of the microphone, the identification unit identifies, from the changes in sound volume along the time series represented by the audio data and the changes in the position of the mining vehicles along the time series represented by the position information, one of the multiple mining vehicles that shows a change in position that matches the changes in sound volume, as a mining vehicle in which separation has occurred in the tires.

[0037] In the detection device according to the 30th embodiment, if the detection unit in the detection device according to the 28th or 29th embodiment detects that separation has occurred in the tire, it outputs an alarm along with identification information that identifies the mining vehicle identified by the identification unit.

[0038] The detection device according to the 31st embodiment is a detection device according to any one of the 15th to 24th embodiments, further comprising, when the detection sensor is the odor sensor, an information acquisition unit that acquires position information of each mining vehicle traveling on the same mine road, and an identification unit that identifies a mining vehicle in which tire separation has occurred using the odor data, which is the collected data, collected by the data collection unit, and when the detection unit detects that tire separation has occurred, the identification unit identifies a mining vehicle in which tire separation has occurred among the mining vehicles whose driving status is represented by the change in position information, and which shows a change in position that matches the approach status of the mining vehicle to the odor sensor obtained from the change in the intensity of the odor represented by the odor data.

[0039] In the detection device according to the 32nd embodiment, if the detection unit in the detection device according to the 31st embodiment detects that separation has occurred in the tire, it outputs an alarm along with identification information that identifies the mining vehicle identified by the identification unit.

[0040] The detection device according to the 33rd embodiment includes an estimation unit that estimates the level of separation in the tire based on the collected data when the detection unit detects that separation has occurred in the tire, in a detection device according to any one of the 1st to 32nd embodiments.

[0041] The detection device according to the 34th embodiment further comprises an output unit that, when the detection unit detects that separation has occurred in the tire, outputs an alarm along with the level of separation estimated by the estimation unit to at least one of a notification device for the driver of the mining vehicle where separation has occurred and a control device in a control room that manages the operation of the mining vehicle.

[0042] The detection device according to the 35th embodiment is a detection device according to the 34th embodiment, wherein the output unit outputs to at least one of the notification device and the management device a method of action that the mining vehicle can take, depending on the level of separation occurrence.

[0043] The detection device according to the 36th embodiment is a detection device according to the 35th embodiment in which the countermeasures are predetermined for each level of separation occurrence, and the period until the tire is inspected is shortened for each level of separation occurrence that is more severe.

[0044] The detection device according to the 37th embodiment is defined in the detection device according to the 36th embodiment as a countermeasure corresponding to the most serious occurrence level of separation in the tire among a plurality of predetermined occurrence levels, which is to interrupt the scheduled work on the mining vehicle and drive the mining vehicle to the tire cooling facility.

[0045] The detection device according to the 38th embodiment further comprises a control unit that controls the mining vehicle on behalf of the driver, in addition to the detection device according to the 37th embodiment, and the control unit executes control on the mining vehicle in accordance with the countermeasure method.

[0046] In the detection device according to the 39th embodiment, the control unit, based on instructions from the management device according to the aforementioned response method, executes control on the mining vehicle in accordance with the aforementioned response method.

[0047] The detection program according to the 40th embodiment is a program that causes a computer to collect sound generated from the tires of a mining vehicle as data using a microphone as a detection sensor, or to collect odor generated from the tires of a mining vehicle as data using an odor sensor as the detection sensor, and to perform a process to detect whether or not separation has occurred in the tires using the collected data.

[0048] A detection system according to the 41st embodiment includes a detection sensor using a microphone that converts the loudness of sound generated from the tires of a mining vehicle into an electrical signal, or an odor sensor that converts the intensity of odor generated from the tires into an electrical signal, a data collection unit that collects the data obtained by the detection sensor, and a detection device that uses the collected data collected by the data collection unit to detect whether or not separation has occurred in the tires. [Effects of the Invention]

[0049] According to this disclosure, the method has the advantage of being able to detect tire separation on mining vehicles at a lower cost compared to detecting tire separation on mining vehicles from temperature changes using thermography. [Brief explanation of the drawing]

[0050] [Figure 1] This is a diagram showing an example of a mining vehicle. [Figure 2] This figure shows an example of the functional configuration of the detection device according to the first embodiment. [Figure 3] This figure shows an example of the main components of the electrical system of a detection device. [Figure 4] This flowchart shows an example of the detection process flow using a microphone according to the first embodiment. [Figure 5] This flowchart shows an example of the flow of detection processing using an odor sensor according to the first embodiment. [Figure 6] This figure shows an example of the functional configuration of the detection device according to the second embodiment. [Figure 7] This flowchart shows an example of the detection process flow using a microphone according to the second embodiment. [Figure 8] This flowchart shows an example of the flow of the detection process using the odor sensor according to the second embodiment. [Figure 9] This figure shows an example of the functional configuration of the detection device according to the third embodiment. [Figure 10]This flowchart shows an example of the detection process flow according to the third embodiment, which individually identifies other vehicles experiencing tire separation based on changes in sound intensity. [Figure 11] This flowchart shows an example of the detection process flow according to a modified version of the third embodiment, which individually identifies other vehicles experiencing tire separation based on changes in the center frequency of the sound. [Figure 12] This flowchart shows an example of the detection process flow according to the fourth embodiment, which individually identifies vehicles in which tire separation has occurred based on changes in the volume of sound from a microphone installed in a location different from the vehicle. [Figure 13] This flowchart shows an example of the detection process flow according to the fourth embodiment, in which, when there are multiple candidate vehicles with tire separation, a vehicle with tire separation is identified from among multiple candidate vehicles based on the changes in the center frequency of the sound. [Figure 14] This flowchart shows an example of the detection process flow according to the fourth embodiment, which individually identifies vehicles in which tire separation has occurred based on changes in the center frequency of sound from microphones installed in locations other than the vehicle. [Figure 15] This flowchart shows an example of the detection process flow according to the fourth embodiment, in which, when there are multiple candidate vehicles with tire separation, the system identifies the vehicle with tire separation from among the multiple candidate vehicles based on the changes in sound intensity. [Figure 16] This flowchart shows an example of the detection process flow according to the fourth embodiment, which individually identifies vehicles in which tire separation has occurred based on changes in odor intensity detected by odor sensors installed in locations other than the vehicle. [Figure 17] This figure shows an example of the functional configuration of the detection device according to the fifth embodiment. [Figure 18] This flowchart shows an example of the flow of the detection process according to the fifth embodiment, which outputs the level of separation occurrence. [Figure 19]This figure shows an example of the functional configuration of the detection device according to the sixth embodiment. [Figure 20] This flowchart shows an example of the detection process flow according to the sixth embodiment for controlling a vehicle performing autonomous driving. [Figure 21] This is an example of the functional configuration of a detection device that controls vehicles based on instructions from a management device regarding how to handle such situations. [Modes for carrying out the invention]

[0051] This embodiment will be described below with reference to the drawings. The same reference numerals are used throughout the drawings for the same components and processes, and redundant explanations are omitted. The dimensional ratios in the drawings are exaggerated for illustrative purposes and may differ from actual ratios.

[0052] <First Embodiment> Figure 1 shows an example of a vehicle traveling on a track in a mine, i.e., a mining vehicle 6. A mine is a place where minerals existing underground are extracted. Therefore, a mine does not necessarily have to be a raised area like a mountain; any place where minerals are extracted, even on flat land, is called a mine. Furthermore, a mine does not refer to a limited area where minerals are extracted using heavy machinery. For example, it can refer to the entire site managed by a mining company for the purpose of mineral extraction, including a deposit area for extracted minerals, a processing plant for minerals, a rest area for the drivers of the mining vehicles 6, and a management building for managing the entire mine.

[0053] Mining vehicles 6 include various types, such as shovels and wheel loaders. In the technology of this disclosure, mining vehicles 6 refer to all vehicles that travel on mine tracks using the tires they are equipped with. Therefore, a dump truck that transports mined minerals, as shown in Figure 1, is an example of a mining vehicle 6. In this disclosure, mining vehicles 6 are simply referred to as "vehicle 6".

[0054] Vehicle 6 is equipped with a detection sensor 5 for detecting whether or not separation occurs in the tires. There are no restrictions on the location of the detection sensor 5 on vehicle 6, and the location is determined according to the characteristics of the detection sensor 5 used. This disclosure describes an example in which a microphone or an odor sensor is used as the detection sensor 5. A microphone is a sensor that converts the magnitude of air vibrations caused by sound into an electrical signal, and an odor sensor is a sensor that converts the intensity of the odor of a specific component into an electrical signal. Hereafter, the electrical signal obtained from the microphone will be referred to as "sound data," and the electrical signal obtained from the odor sensor will be referred to as "odor data."

[0055] When separation occurs in a tire, the tire may emit a sound different from road noise as it rotates. Therefore, when using a microphone as the detection sensor 5, it is preferable to attach the microphone around the tire's mounting position, for example. Also, since the tires are mounted in multiple locations, such as the left front and right rear of the vehicle 6, it is preferable to install a microphone at each tire mounting position to detect tires that have separated. In the case of a dual-wheel configuration where multiple tires are mounted at the same mounting position on the vehicle 6, a microphone may be installed for each tire, or one microphone may be installed for each tire that makes up the dual-wheel configuration.

[0056] Similarly, when separation occurs in a tire, a characteristic odor is emitted from the tire as the temperature of the affected area rises. Therefore, when using an odor sensor as the detection sensor 5, it is preferable to install the odor sensor around the tire mounting position, for example. Also, since the tires are mounted at multiple locations on the vehicle 6, it is preferable to install an odor sensor at each tire mounting position in order to detect tires that have separated. If the vehicle 6 has a dual-wheel configuration, similar to the microphone installation configuration, an odor sensor may be installed for each tire, or one odor sensor may be installed for each tire that makes up the dual-wheel configuration.

[0057] Furthermore, odors generated by the tires are easily transported into the vehicle through the air conditioning ducts connected to the interior of vehicle 6. Therefore, an odor sensor may be installed in the air conditioning ducts connected to the interior of vehicle 6.

[0058] In the first embodiment, an example will be described in which the detection sensor 5 is installed around the tire at each tire mounting position.

[0059] Figure 2 shows an example of the functional configuration of a detection device 10 that detects whether or not separation occurs in the tires of a vehicle 6. The detection device 10 includes a data acquisition unit 11, a detection unit 12, and an output unit 13.

[0060] The data collection unit 11 collects data from the detection sensor 5, which is data collected by the detection sensor 5. When a microphone is used as the detection sensor 5, the data collection unit 11 collects sound generated from the tires of the vehicle 6 as data. When an odor sensor is used as the detection sensor 5, the data collection unit 11 collects odor generated from the tires of the vehicle 6 as data. The data collection unit 11 notifies the detection unit 12 of the data collected using the detection sensor 5.

[0061] When the detection unit 12 receives the collected data from the data acquisition unit 11, it uses the collected data to detect whether or not separation has occurred in the tires of the vehicle 6. The specific method for detecting the presence or absence of separation in the detection unit 12 will be explained later. The detection unit 12 notifies the output unit 13 of the detection result regarding the presence or absence of separation in the tires.

[0062] The output unit 13 outputs an alarm when it receives a detection result from the detection unit 12 indicating that tire separation has occurred. In this case, the output unit 13 outputs an alarm to at least one of the following: a notification device 6A installed in the driver's seat of the vehicle 6 where tire separation has occurred, and a management device 7A installed in the control room 7 that manages the operation of the vehicle 6. Hereafter, the notification device 6A and the management device 7A will be collectively referred to as the "alarm output device." That is, the alarm output device refers to at least one of the notification device 6A and the management device 7A. The control room 7 is a space located in a different location from the driver's seat of the vehicle 6.

[0063] If a driver is in the vehicle 6, it is preferable that the output unit 13 outputs an alarm from at least the notification device 6A to notify the driver that tire separation has occurred. Furthermore, if the vehicle 6 is operating autonomously and an operator in the control room 7 is monitoring the vehicle's status, it is preferable that the output unit 13 outputs an alarm from at least the control device 7A to notify the vehicle 6 operator that tire separation has occurred.

[0064] Furthermore, since the detection device 10 only needs to be connected to the detection sensor 5, notification device 6A, and management device 7A by wire or wireless, there are no restrictions on the installation location of the detection device 10. Therefore, for example, the detection device 10 may be installed in the vehicle 6, in the control room 7, or in a location other than the vehicle 6 and the control room 7. In addition, the detection device 10 does not necessarily need to include an output unit 13; it is sufficient if the detection unit 12 can only detect whether or not separation has occurred.

[0065] The system including the detection sensor 5 and the detection device 10 is called the detection system 100.

[0066] The detection device 10 having the functional configuration shown in Figure 2 is configured, for example, using a computer 1. Figure 3 shows an example of the main components of the electrical system of the detection device 10 configured using the computer 1.

[0067] Computer 1 comprises a CPU (Central Processing Unit) 1A, which is an example of a processor; RAM (Random Access Memory) 1B, which is used as a temporary workspace for CPU 1A; non-volatile memory 1C; and an input / output interface (I / O) 1D. CPU 1A, RAM 1B, non-volatile memory 1C, and I / O 1D are connected to each other via bus 1E to transfer data.

[0068] CPU 1A reads, for example, the detection program stored in the non-volatile memory 1C and executes the processing of each functional unit in the detection device 10 shown in Figure 2.

[0069] Non-volatile memory 1C is an example of a storage device that retains stored information even when the power supplied to it is cut off. For example, semiconductor memory (Solid State Drive: SSD) is used. Information that should not be lost each time the power to the detection device 10 is cut off, such as a detection program, is stored in non-volatile memory 1C. Note that non-volatile memory 1C does not necessarily have to be built into computer 1; for example, it may be a portable storage device that can be attached to or detached from computer 1.

[0070] On the other hand, I / O1D is connected to, for example, a communication unit 2, an input unit 3, an output unit 4, and a detection sensor 5.

[0071] Communication unit 2 is connected to a communication line (not shown) and is equipped with a communication protocol for sending and receiving data with external devices connected to the communication line. For example, communication unit 2 is connected to notification device 6A and management device 7A.

[0072] The input unit 3 is a device that receives user instructions and notifies the CPU 1A, and includes, for example, buttons and a touch panel. The user refers to the operator of the detection device 10. Therefore, the driver of vehicle 6 and the operator who manages the driving status of vehicle 6 are examples of users.

[0073] Output unit 4 is an example of an output device that outputs information processed by CPU 1A to the outside, and includes, for example, a liquid crystal display, an organic EL (Electro Luminescence) display, and a speaker.

[0074] Figure 4 is a flowchart showing an example of the flow of the detection process executed by the CPU 1A of the detection device 10 when it receives a start command from the user to begin separation detection. The CPU 1A of the detection device 10 reads the detection program stored in the non-volatile memory 1C and executes the detection process.

[0075] Note that the detection process shown in Figure 4 is the detection process when a microphone is used as the detection sensor 5.

[0076] In step S10 of Figure 4, CPU 1A starts collecting audio data in chronological order through each microphone and stores the collected audio data in, for example, RAM 1B.

[0077] In step S20, CPU 1A analyzes each of the audio data collected in step S10. There are no restrictions on the method of analyzing the audio data, but one method is to analyze the waveform of the audio data. By pre-collecting the waveform of audio data when vehicle 6 is running with tires in a normal state and comparing it with the audio data collected in step S10, changes can be detected. Through this method of analyzing audio data, the condition of the tires can be determined from, for example, the frequency at which changes occur, the magnitude of the change, and the shape of the waveform. Alternatively, by pre-collecting the waveform of audio data when vehicle 6 is running with tires that have separated, and recognizing that tire separation has occurred when a waveform identical or with a similar tendency occurs, the system can recognize that tire separation has occurred. By storing the audio data acquired in step S10 in non-volatile memory 1C in association with the degree of separation, the accuracy of the analysis can be further improved. In addition to human judgment, the comparison and judgment of waveforms can also be performed using AI (Artificial Intelligence). There is also a method that uses the loudness of the sound. The audio data may be acquired at a specific time, or it may be audio data acquired at multiple times or in a time series. The following describes an example in which CPU1A analyzes audio data to measure the loudness of sound in a time series. In this disclosure, the loudness of sound is represented by a predetermined type of index value. Examples of loudness index values ​​include average, minimum, and maximum values, but CPU1A measures one or more of these index values ​​from the audio data. The type of loudness index value measured by CPU1A can be changed by the user.

[0078] CPU1A measures the loudness of the sound emitted from each tire by measuring the loudness of the sound in a time-series manner from each audio data.

[0079] In step S30, the CPU 1A determines whether at least one of the sound levels measured in step S20 for each tire is equal to or greater than a first threshold. The first threshold is, for example, a threshold pre-stored in the non-volatile memory 1C, and is pre-set to a value such that if the sound level is equal to or greater than this threshold, separation can be considered to have occurred in the tires of the vehicle 6.

[0080] If the loudness of at least one sound is above the first threshold, the process proceeds to step S40. In this case, there is a high probability that separation has occurred in the tire corresponding to the location where the microphone was installed from which the audio data with a loudness above the first threshold was obtained. Therefore, in step S40, the CPU 1A outputs an alarm from the alarm output device to notify of the occurrence of separation. It is preferable that the CPU 1A outputs the mounting location of the tire where separation may have occurred along with the alarm from the alarm output device. After outputting the alarm from the alarm output device, the process proceeds to step S50.

[0081] On the other hand, if the determination process in step S30 determines that the loudness of all measured sounds is below the first threshold, it is highly likely that no separation has occurred in the tires of vehicle 6. In this case, CPU 1A does not need to output an alarm from the alarm output device. Therefore, the process in step S40 is not executed, and the system proceeds to step S50.

[0082] In step S50, CPU 1A determines whether it has received a termination command from the user to end the separation detection. If no termination command has been received, it proceeds to step S10 and continues the detection process. On the other hand, if a termination command has been received, it terminates the detection process as shown in Figure 4.

[0083] As described above, the detection device 10, which performs the detection process shown in Figure 4, detects whether or not separation has occurred in the tires of the vehicle 6 on which the microphone is installed, and if separation is suspected to have occurred, an alarm is output from the alarm output device.

[0084] Next, we will explain the detection process when an odor sensor is used as the detection sensor 5.

[0085] Figure 5 is a flowchart showing an example of the flow of detection processing executed by the CPU 1A of a detection device 10 that uses an odor sensor as the detection sensor 5 when it receives a start command from the user to start detecting separation. The CPU 1A of the detection device 10 reads the detection program stored in the non-volatile memory 1C and executes the detection processing.

[0086] In step S100 of Figure 5, the CPU 1A starts collecting odor data in a time-series manner through each odor sensor and stores the collected odor data in, for example, RAM 1B.

[0087] In step S110, CPU1A measures the odor intensity from each odor data collected in step S100. In this disclosure, the odor intensity is expressed using a predetermined type of index value representing the odor intensity. Examples of index values ​​representing odor intensity include the average value, minimum value, and maximum value, but CPU1A measures one or more of these index values ​​from the odor data. The type of odor intensity index value measured by CPU1A can be changed, for example, by the user.

[0088] In step S120, the CPU 1A determines whether the odor intensity of at least one of the odors emitted from each tire measured in step S110 is equal to or greater than a second threshold. The second threshold is, for example, a threshold pre-stored in the non-volatile memory 1C, and is pre-set to a value such that if the odor intensity is equal to or greater than this threshold, separation can be considered to have occurred in the tires of the vehicle 6.

[0089] If the intensity of at least one odor is above the second threshold, the process proceeds to step S130. In this case, there is a high probability that separation has occurred in the tire corresponding to the installation location of the odor sensor from which odor data with an odor intensity above the second threshold was obtained. Therefore, in step S130, the CPU 1A outputs an alarm from the alarm output device to notify of the occurrence of separation. It is preferable that the CPU 1A outputs the mounting location of the tire where separation may have occurred along with the alarm from the alarm output device. After outputting the alarm from the alarm output device, the process proceeds to step S140.

[0090] On the other hand, if the determination process in step S120 determines that the intensity of any of the measured odors is below the second threshold, it is highly likely that separation has not occurred in the tires of vehicle 6. In this case, CPU 1A does not need to output an alarm from the alarm output device. Therefore, the process in step S130 is not executed, and the system proceeds to step S140.

[0091] In step S140, CPU 1A determines whether or not it has received a termination command from the user. If it has not received a termination command, it proceeds to step S100 and continues the detection process. On the other hand, if it has received a termination command, it terminates the detection process shown in Figure 5.

[0092] As described above, the detection device 10, which performs the detection process shown in Figure 5, detects whether or not separation has occurred in the tires of the vehicle 6 on which the odor sensor is installed, and if separation is deemed to have occurred, an alarm is output from the alarm output device.

[0093] <Second Embodiment> In the first embodiment, a detection device 10 was described that detects whether or not separation has occurred in the tires of a vehicle 6 on which a detection sensor 5 is installed. In the second embodiment, a detection device 10A will be described that determines whether the vehicle 6 on which separation has occurred in the tires is the vehicle 6 on which the detection sensor 5 is installed, or a vehicle 6 other than the vehicle 6 on which the detection sensor 5 is installed.

[0094] For the sake of explanation, the vehicle 6 on which the detection sensor 5 is installed will be referred to as "our vehicle 6," and other vehicles 6 will be referred to as "other vehicles 6." In the second embodiment as well, there are no restrictions on the installation location of the detection sensor 5; it is sufficient that at least one detection sensor 5 is installed on our vehicle 6. In the second embodiment as well, an example will be described in which the detection sensors 5 are installed around the tires at each tire mounting position.

[0095] Figure 6 shows an example of the functional configuration of the detection device 10A. The difference between the example of the functional configuration of the detection device 10A shown in Figure 6 and the example of the functional configuration of the detection device 10 shown in Figure 2 is the addition of the identification unit 14. Therefore, the example of the functional configuration of the detection device 10A will be explained focusing on the function of the identification unit 14.

[0096] The identification unit 14 uses the collected data gathered by the data collection unit 11 to identify the vehicle 6 in which tire separation has occurred.

[0097] The detection sensor 5 can detect not only the tires of its own vehicle 6, but also sounds or odors emanating from the tires of other vehicles 6 traveling around its own vehicle 6. Therefore, the identification unit 14 determines whether the vehicle 6 experiencing tire separation is its own vehicle 6 or another vehicle 6, based on the differences in characteristics obtained from the collected data when separation occurs in the tires of its own vehicle 6 and the tires of other vehicles 6, respectively. The specific method by which the identification unit 14 identifies the vehicle 6 experiencing tire separation will be explained later.

[0098] The system including the detection sensor 5 and the detection device 10A is called the detection system 100A.

[0099] The detection device 10A is also configured using computer 1, similar to the detection device 10. The example of the main components of the electrical system of the detection device 10A configured using computer 1 is the same as the example of the main components of the electrical system of the detection device 10 shown in Figure 3.

[0100] Figure 7 is a flowchart showing an example of the flow of detection processing executed by the CPU 1A of the detection device 10A, which uses a microphone as the detection sensor 5, when the CPU 1A of the detection device 10A receives a start command from the user to begin separation detection. The CPU 1A of the detection device 10A reads the detection program stored in the non-volatile memory 1C and executes the detection processing.

[0101] The detection process shown in Figure 7 differs from the detection process shown in Figure 4 in that steps S31 to S33 are added, and the process in step S40 is replaced by the process in step S40A; all other processes are the same. Therefore, the detection process shown in Figure 7 will be explained focusing on the differences between the detection process shown in Figure 4 and the detection process shown in Figure 7.

[0102] If the determination process in step S30 determines that at least one of the measured sound levels is equal to or greater than the first threshold, the process proceeds to step S31.

[0103] If separation occurs in the tires of vehicle 6, the sound caused by the contact between the rubber or steel cords will be continuously collected through the microphone installed on vehicle 6. On the other hand, if separation occurs in the tires of another vehicle 6 that is moving, the distance between the microphone installed on vehicle 6 and vehicle 6 will change. Therefore, as vehicle 6 approaches vehicle 6, the sound caused by the contact between the rubber or steel cords in the tires will increase, but as vehicle 6 moves away from vehicle 6, the sound of this contact will decrease.

[0104] Therefore, in step S31, the CPU 1A determines whether the sound level, which was determined to be above the first threshold by the determination process in step S30, has continued for a first specified period or longer. The first specified period is, for example, an example of a specified period pre-stored in the non-volatile memory 1C. The first specified period is pre-set to a period during which separation can be considered to have occurred in the tires of the vehicle 6 if the sound level remains above the first threshold for that period or longer. The first specified period can be changed by the user.

[0105] If the sound level remains above the first threshold for a specified period of time or longer, the process proceeds to step S32.

[0106] Since the sound level is above the first threshold and persists for a period longer than the first specified period, in step S32, CPU 1A identifies that separation has occurred in the tires of its own vehicle 6 and proceeds to step S40A.

[0107] On the other hand, if the determination process in step S31 determines that the duration of the sound level being above the first threshold is less than the first specified period, the process proceeds to step S33.

[0108] Since the sound level above the first threshold persists for less than the first specified period, in step S33, CPU 1A identifies that separation has occurred in the tires of other vehicle 6 and proceeds to step S40A.

[0109] In step S40A, the CPU 1A performs the process of outputting an alarm and additional information from the alarm output device. The additional information according to the second embodiment is information indicating whether the vehicle 6 in which tire separation has occurred is the own vehicle 6 or another vehicle 6. If tire separation has occurred in the own vehicle 6 and microphones are installed at each mounting position of the tire, the CPU 1A may output the mounting position of the tire in which separation may have occurred from the alarm output device.

[0110] Thus, the detection device 10A, which performs the detection process shown in Figure 7, identifies whether the vehicle 6 in which tire separation has occurred is its own vehicle 6 or another vehicle 6, based on the duration of the sound level being above a first threshold.

[0111] Furthermore, the detection device 10A may determine whether the vehicle 6 in which tire separation has occurred is its own vehicle 6 or another vehicle 6, based on the changes in the center frequency of the audio data.

[0112] If separation occurs in the tires of vehicle 6, the relative distance between the microphone and the tires, which are the sound source, does not change. Therefore, when CPU 1A performs frequency analysis on the audio data obtained in a time series using known frequency analysis methods such as the Fast Fourier Transform, the center frequency of the sound at each time point will fall within a predetermined frequency range.

[0113] The center frequency is the frequency at the center of the frequency distribution of audio data. CPU1A may calculate the center frequency based on any calculation method, as long as the same calculation method is used to calculate the center frequency at each time point. For example, CPU1A calculates the center frequency as the frequency at which the integral value of the audio spectrum of frequency components lower than that frequency is equal to the integral value of the audio spectrum of frequency components higher than that frequency.

[0114] On the other hand, if separation occurs in the tires of other vehicle 6, the relative distance between the microphone and the tires, which are the sound source, changes. If the relative position of the tires with respect to the microphone changes, the center frequency changes due to the Doppler effect. For example, if other vehicle 6 moves closer to the microphone, the center frequency increases, and if other vehicle 6 moves further away from the microphone, the center frequency decreases. Therefore, if CPU 1A performs frequency analysis on the audio data obtained in a time series using known frequency analysis methods such as the Fast Fourier Transform, the center frequency of the sound at each time point will exceed a predetermined frequency range.

[0115] The above findings may be applied to determine whether the vehicle 6 in which tire separation has occurred is the own vehicle 6 or another vehicle 6.

[0116] Specifically, in step S31 of Figure 7, CPU 1A performs frequency analysis on the audio data in the time series that has been determined to be above the first threshold by the judgment process in step S30, and calculates the center frequency of the sound for each time point. Then, CPU 1A determines whether the center frequencies of the sound in the time series fall within a predetermined frequency range. If the center frequencies of the sound in the time series fall within the predetermined frequency range, the process proceeds to step S32; if the center frequencies of the sound in the time series exceed the predetermined frequency range, the process proceeds to step S33.

[0117] In this way, CPU1A can also determine whether the vehicle 6 in which tire separation has occurred is its own vehicle 6 or another vehicle 6, based on the changes in the center frequency of the audio data.

[0118] Next, we will explain the detection process in the detection device 10A when an odor sensor is used as the detection sensor 5.

[0119] Figure 8 is a flowchart showing an example of the flow of detection processing executed by the CPU 1A of a detection device 10A that uses an odor sensor as the detection sensor 5 when it receives a start command from the user to start separation detection. The CPU 1A of the detection device 10A reads the detection program stored in the non-volatile memory 1C and executes the detection processing.

[0120] The detection process shown in Figure 8 differs from the detection process shown in Figure 5 in that steps S121 to S123 are added, and the process in step S130 is replaced by the process in step S130A; all other processes are the same. Therefore, the detection process shown in Figure 8 will be explained focusing on the differences between the detection process shown in Figure 5 and the detection process shown in Figure 8.

[0121] If the determination process in step S110 determines that at least one of the measured odor intensities is equal to or greater than the second threshold, the process proceeds to step S121.

[0122] If separation occurs in the tires of vehicle 6, the odor sensor installed on vehicle 6 will continue to collect odors associated with the tire damage through the sensor. On the other hand, if separation occurs in the tires of another vehicle 6 that is driving by, the distance between the odor sensor installed on vehicle 6 and vehicle 6 will change. Therefore, as vehicle 6 approaches vehicle 6, the odor collected by the odor sensor will become stronger, but as vehicle 6 moves away from vehicle 6, the odor will become weaker.

[0123] Therefore, in step S121, CPU 1A determines whether the odor intensity, which was determined to be above the second threshold by the determination process in step S120, has continued for a second specified period or longer. The second specified period is, for example, an example of a specified period pre-stored in the non-volatile memory 1C. The second specified period is pre-set to a period during which separation can be considered to have occurred in the tires of the vehicle 6 if the odor intensity remains above the second threshold for that period or longer. The second specified period can be changed by the user.

[0124] If the odor intensity remains above the second threshold for a period longer than the second specified period, proceed to step S122.

[0125] Since the odor intensity remains above the second threshold for a period longer than the second specified period, in step S122, CPU 1A identifies that separation has occurred in the tires of its own vehicle 6 and proceeds to step S130A.

[0126] On the other hand, if the determination process in step S121 determines that the duration of odor intensity exceeding the second threshold is less than the second specified period, the process proceeds to step S123.

[0127] Since the odor intensity exceeding the second threshold persists for less than the second specified period, in step S123, CPU1A identifies that separation has occurred in the tires of other vehicle 6 and proceeds to step S130A.

[0128] In step S130A, CPU1A performs the process of outputting an alarm and additional information from the alarm output device. If separation has occurred in the tires of the vehicle 6 and odor sensors are installed at each mounting position of the tires, CPU1A may output the mounting position of the tire in which separation may have occurred from the alarm output device.

[0129] Thus, the detection device 10A, which performs the detection process shown in Figure 8, detects whether the vehicle 6 in which tire separation has occurred is its own vehicle 6 or another vehicle 6, based on the duration of the odor intensity being above the second threshold.

[0130] <Third Embodiment> In the second embodiment, a detection device 10A was described that identifies whether the vehicle 6 with tire separation is the own vehicle 6 or another vehicle 6. In the third embodiment, a detection device 10B will be described that, when a microphone is installed on the vehicle 6 as a detection sensor 5, identifies the other vehicle 6 with tire separation individually after it has been identified as another vehicle 6.

[0131] In the third embodiment, there are no restrictions on the placement of the microphone used as the detection sensor 5; it is sufficient that at least one microphone is installed in the vehicle 6.

[0132] Figure 9 shows an example of the functional configuration of the detection device 10B. The difference between the example of the functional configuration of the detection device 10B shown in Figure 9 and the example of the functional configuration of the detection device 10A shown in Figure 6 is the addition of an information acquisition unit 15. Therefore, the example of the functional configuration of the detection device 10B will be explained focusing on the functions of the information acquisition unit 15.

[0133] The information acquisition unit 15 acquires the location information of each vehicle 6 traveling on the same mine track. For example, the information acquisition unit 15 acquires the time-based latitude and longitude of each vehicle 6 obtained by GPS (Global Positioning System) as location information. Identification information that uniquely identifies each vehicle 6, such as a vehicle number, is added to the location information. The detection device 10B acquires the location information of each vehicle 6 individually through the information acquisition unit 15.

[0134] The system including the detection sensor 5 and the detection device 10B is called the detection system 100B.

[0135] Next, we will explain how to individually identify the other vehicle 6 that has tire separation when it has been identified as another vehicle 6.

[0136] Figure 10 is a flowchart showing an example of the flow of detection processing executed by the CPU 1A of the detection device 10B, which uses a microphone as the detection sensor 5, when the CPU 1A of the detection device 10B receives a start command from the user to begin separation detection. The CPU 1A of the detection device 10B reads the detection program stored in the non-volatile memory 1C and executes the detection processing. It is assumed that the position information of each vehicle 6 in chronological order is sequentially stored in, for example, RAM 1B by the processing of the information acquisition unit 15.

[0137] The difference between the detection process shown in Figure 10 and the detection process shown in Figure 7 is that step S33 is replaced by steps S34 to S36; the other processes are the same. Therefore, the detection process shown in Figure 10 will be explained focusing on the differences between it and the detection process shown in Figure 7.

[0138] If the determination process in step S31 determines that the duration of the sound intensity being above the first threshold is less than the first specified period, the process proceeds to step S34.

[0139] In step S34, CPU 1A obtains time-series position information for each vehicle 6, including its own vehicle 6, from RAM 1B. That is, CPU 1A obtains the changes in the position of each vehicle 6.

[0140] In step S35, CPU1A acquires the sound intensity along the time series measured in step S20. That is, CPU1A acquires the changes in the sound intensity emitted from the tire.

[0141] In step S36, using the changes in the position of each vehicle 6 obtained in step S34 and the changes in the volume of the sound obtained in step S35, the vehicle 6 in which tire separation has occurred is individually identified from among the other vehicles 6.

[0142] As already explained, the sound gets louder when another vehicle 6 approaches vehicle 6, and quieter when another vehicle 6 moves away from vehicle 6. In this case, the sound is loudest when another vehicle 6 is closest to the microphone installed on vehicle 6. Therefore, CPU 1A identifies the vehicle 6 among the multiple other vehicles 6 that is closest to vehicle 6 at the time when the sound is loudest, and whose position changes in accordance with the changes in sound volume—approaching vehicle 6 when the sound gets louder as time passes, and moving away from vehicle 6 when the sound gets quieter—as another vehicle 6 where tire separation is occurring. Hereafter, the time when the sound is loudest will be referred to as the "time of maximum sound."

[0143] CPU1A individually identifies the other 6 vehicles that have tire separation in step S36, and then proceeds to step S40A.

[0144] In step S40A, the CPU 1A performs the process of outputting an alarm and additional information from the alarm output device. The additional information according to the third embodiment is information indicating whether the vehicle 6 in which tire separation has occurred is the own vehicle 6 or another vehicle 6, and, if the vehicle 6 in which tire separation has occurred is another vehicle 6, identification information that uniquely identifies the other vehicle 6. If tire separation has occurred in the tires of the own vehicle 6 and microphones are installed at each mounting position of the tires, the CPU 1A may output the mounting position of the tire in which separation may have occurred from the alarm output device.

[0145] As described above, the detection device 10B, which performs the detection process shown in Figure 10, detects whether the vehicle 6 in which tire separation has occurred is its own vehicle 6 or another vehicle 6, based on the duration of the sound level being above a first threshold. Furthermore, if the vehicle 6 in which tire separation has occurred is another vehicle 6, the detection device 10B, which performs the detection process shown in Figure 10, uses the changes in the position of vehicle 6 and the changes in the sound level to individually identify the other vehicle 6 in which tire separation has occurred.

[0146] As described in the second embodiment, in step S31 of Figure 10, the CPU 1A of the detection device 10B may determine whether the vehicle 6 in which tire separation has occurred is its own vehicle 6 or another vehicle 6, based on the changes in the center frequency of the audio data.

[0147] <Modified form of the third embodiment> The detection device 10B described above individually identifies other vehicles 6 experiencing tire separation based on the correspondence between the changes in the position of vehicle 6 and the changes in the volume of sound. However, the method of individually identifying other vehicles 6 experiencing tire separation using audio data is not limited to the example shown in the third embodiment.

[0148] This modified example describes a detection device 10B that individually identifies other vehicles 6 in which tire separation has occurred based on changes in the center frequency of the audio data.

[0149] Figure 11 is a flowchart showing an example of the flow of detection processing executed by the CPU 1A of the detection device 10B, which uses a microphone as the detection sensor 5, when the CPU 1A of the detection device 10B receives a start command from the user to begin separation detection. The CPU 1A of the detection device 10B reads the detection program stored in the non-volatile memory 1C and executes the detection processing. It is assumed that the position information of each vehicle 6 in chronological order is sequentially stored in, for example, RAM 1B by the processing of the information acquisition unit 15.

[0150] The difference between the detection process shown in Figure 11 and the detection process shown in Figure 10 is that steps S35 and S36 are replaced by steps S37 and S38, respectively; all other processes are the same. Therefore, the detection process shown in Figure 11 will be explained focusing on the differences between it and the detection process shown in Figure 10.

[0151] After obtaining the time-series positional information of each vehicle 6, including the self-propelled vehicle 6, in step S34, the process proceeds to step S37.

[0152] In step S37, CPU1A performs frequency analysis on the obtained audio data and acquires the audio spectrum for each frequency component in a time-series manner.

[0153] Furthermore, CPU1A calculates the center frequency of the sound for each time point based on the frequency analysis results in a time series, and obtains the changes in the center frequency of the sound.

[0154] If the relative position of another vehicle 6 to vehicle 6 changes, the center frequency will change due to the Doppler effect. For example, if the other vehicle 6 approaches vehicle 6, the center frequency will rise, and if the other vehicle 6 moves away from vehicle 6, the center frequency will fall. In other words, if we define the time at which the inflection point occurs where the center frequency changes from rising to falling as the "inflection point time," then the other vehicle 6, which is experiencing tire separation, will be moving in a way that brings it closest to vehicle 6 at the inflection point time.

[0155] Therefore, in step S38, the CPU 1A uses the changes in the position of each vehicle 6 acquired in step S34 and the changes in the center frequency of the sound acquired in step S37 to individually identify the vehicle 6 from among the other vehicles 6 in which tire separation has occurred.

[0156] For example, CPU 1A identifies one of several other vehicles 6 that moves closest to its own vehicle 6 at the inflection point time as another vehicle 6 in which tire separation is occurring. CPU 1A may also identify one of several other vehicles 6 that moves closer to its own vehicle 6 during the period when the center frequency of the sound is rising, is closest to its own vehicle 6 at the inflection point time, and moves away from its own vehicle 6 during the period when the center frequency of the sound is falling as another vehicle 6 in which tire separation is occurring.

[0157] In this way, CPU1A identifies a vehicle 6 whose positional changes match those of the vehicle 6 approaching the microphone, which are determined from the changes in the center frequency of the sound, as another vehicle 6 in which tire separation is occurring.

[0158] Furthermore, CPU1A may identify the vehicle 6 in which tire separation is occurring by using changes in the lowest and highest frequencies of the sound, instead of the center frequency of the sound. In the technology of this disclosure, a predetermined change in a specific frequency is referred to as the "frequency change." For the sake of explanation, the technology of this disclosure describes an example in which the vehicle 6 in which tire separation is occurring is identified using changes in the center frequency of the sound.

[0159] After individually identifying the other 6 vehicles that have tire separation in step S38, CPU1A proceeds to step S40A.

[0160] As described above, the detection device 10B, which performs the detection process shown in Figure 11, detects whether the vehicle 6 in which tire separation has occurred is its own vehicle 6 or another vehicle 6, based on the duration of the sound intensity being above a first threshold. Furthermore, if the vehicle 6 in which tire separation has occurred is another vehicle 6, the detection device 10B, which performs the detection process shown in Figure 11, uses the changes in the position of vehicle 6 and the changes in the center frequency of the sound to individually identify the other vehicle 6 in which tire separation has occurred.

[0161] As described in the second embodiment, in step S31 of Figure 11, the CPU 1A of the detection device 10B may determine whether the vehicle 6 in which tire separation has occurred is its own vehicle 6 or another vehicle 6, based on the changes in the center frequency of the audio data.

[0162] <Fourth Embodiment> In the first to third embodiments, detection devices 10, 10A, and 10B were described, which are detection devices 10, 10A, and 10B that detect whether or not separation occurs in the tires of the vehicle 6 by installing a detection sensor 5 on the vehicle 6. However, the sound and odor of the tires associated with separation reach the area around the vehicle 6. Therefore, even if the detection sensor 5 is installed in a location other than the vehicle 6, it is possible to detect whether or not separation occurs in the tires.

[0163] In the fourth embodiment, an example of detecting the presence or absence of tire separation using a detection sensor 5 installed in a location different from the vehicle 6 will be described. The detection device 10 shown in the first embodiment and the detection device 10A shown in the second embodiment may be used, but in the fourth embodiment, the detection device 10B from the third embodiment will be used as an example.

[0164] As an example, the detection sensor 5 is installed on the track where the vehicle 6 travels. In order to detect the presence or absence of tire separation in as many vehicles 6 as possible with as few detection sensors 5 as possible, it is preferable to install the detection sensor 5 on the track where the vehicle 6 travels more frequently compared to other tracks.

[0165] For example, a depression formed by mineral mining is called a "pit," and a track is provided in the pit that extends from the bottom to the top of the pit in order to transport the mined minerals. Because the minerals mined in the pit are being transported, vehicles 6 tend to concentrate on the track in the pit compared to other tracks. Therefore, a detection sensor 5 may be installed on the track in the pit.

[0166] Intersections where multiple roads meet are also places where vehicles 6 tend to concentrate compared to other roads. Therefore, detection sensors 5 may be installed at road intersections.

[0167] Furthermore, since a power source such as gasoline or electricity is required for vehicle 6 to run, supply facilities that provide power to vehicle 6 tend to have a higher concentration of vehicles 6 compared to other locations. Therefore, detection sensors 5 may be installed on the roads at the entrances and exits of the supply facilities that provide power. Vehicle 6 may run on electricity, but in the example of this disclosure, vehicle 6 is assumed to run on gasoline. Therefore, in this case, the supply facility that provides power to vehicle 6 is a refueling facility.

[0168] Since the vehicles 6 that transport minerals unload them at the unloading area set up in the mine, the unloading area tends to have a higher concentration of vehicles 6 compared to other locations. Therefore, detection sensors 5 may be installed on the roads at the entrance and exit of the unloading area.

[0169] Furthermore, in order to transport the accumulated minerals to processing plants and other facilities, the loading area where the minerals are loaded onto the vehicles 6 tends to have a higher concentration of vehicles 6 compared to other locations. Therefore, detection sensors 5 may be installed on the roads at the entrances and exits of the mineral loading area.

[0170] Furthermore, since drivers take breaks at set times, rest areas designated for drivers tend to have a higher concentration of vehicles 6 compared to other locations. Therefore, detection sensors 5 may be installed on the roads at the entrances and exits of rest areas.

[0171] Furthermore, the location of the detection sensor 5 is not limited to the track; it may also be installed on equipment operating in the mine other than the vehicle 6. Equipment operating in the mine other than the vehicle 6 includes, for example, belt conveyors.

[0172] In order to detect the presence or absence of tire separation in a large number of vehicles 6 using as few detection sensors 5 as possible, it is preferable to install the detection sensors 5 in equipment in locations where vehicles 6 tend to be concentrated compared to other equipment. Therefore, for example, the detection sensors 5 should be installed in unloading equipment operating in a loading area or in loading equipment operating in a mineral loading area.

[0173] Figure 12 is a flowchart showing an example of the flow of detection processing executed by the CPU 1A of a detection device 10B that uses a microphone installed in a location different from the vehicle 6 as a detection sensor 5 when it receives a start command from the user to start separation detection. The CPU 1A of the detection device 10B reads the detection program stored in the non-volatile memory 1C and executes the detection processing. It is assumed that the time-series location information of each vehicle 6 is sequentially stored in, for example, RAM 1B by the processing of the information acquisition unit 15.

[0174] In step S200 of Figure 12, CPU 1A starts collecting audio data in chronological order through each microphone, similar to step S10 of Figure 4, and stores the collected audio data in, for example, RAM 1B.

[0175] In step S210, CPU 1A measures the volume of each sound in chronological order from the audio data collected in step S200, similar to step S20 in Figure 4.

[0176] In step S220, CPU 1A, similar to step S30 in Figure 4, determines whether the sound level of each tire measured in step S210 is above the first threshold. If the sound level is above the first threshold, the process proceeds to step S230. At this point, it has been detected that there is a vehicle 6 with tire separation, but it has not been determined which vehicle 6 has tire separation.

[0177] Therefore, in step S230, CPU 1A obtains time-series position information for each vehicle 6 from RAM 1B, similar to step S34 in Figure 10.

[0178] In step S240, CPU1A acquires the sound intensity along the time series measured in step S210, similar to step S35 in Figure 10.

[0179] In step S250, the CPU 1A uses the changes in the position of each vehicle 6 acquired in step S230 and the changes in the volume of the sound acquired in step S240 to individually identify the vehicle 6 in which tire separation has occurred.

[0180] As vehicle 6 approaches the microphone, the sound gets louder, and as vehicle 6 moves away from the microphone, the sound gets quieter. In this case, the sound is loudest when vehicle 6 is closest to the microphone. Therefore, CPU 1A identifies the vehicle 6 among the multiple vehicles 6 that is closest to the microphone at the moment of maximum sound volume, and whose position changes are consistent with the changes in sound volume (approaching the microphone when the sound gets louder and moving away from the microphone when the sound gets quieter), as the vehicle 6 in which tire separation is occurring.

[0181] In step S260, CPU 1A processes the output of a warning and additional information from the warning output device. The additional information in step S260 is identification information that uniquely identifies the vehicle 6 that was identified in step S250 as having tire separation. After outputting the warning and additional information from the warning output device, the process proceeds to step S270.

[0182] On the other hand, if the judgment process in step S220 determines that the measured sound level is below the first threshold, it is highly likely that no separation has occurred in the tires of any of the vehicles 6. Therefore, the process proceeds to step S270 without executing steps S230 to S260.

[0183] In step S270, CPU 1A determines whether or not it has received a termination command from the user. If it has not received a termination command, it proceeds to step S200 and continues the detection process. On the other hand, if it has received a termination command, it terminates the detection process shown in Figure 12.

[0184] In this way, the detection device 10B, which performs the detection process shown in Figure 12, individually identifies vehicles 6 in which tire separation has occurred by using the changes in the position of the vehicle 6 and the changes in the volume of sound obtained from audio data from a microphone installed in a different location from the vehicle 6.

[0185] In some cases, it is possible that in step S250, there may be multiple vehicles 6 that exhibit positional changes that correspond to the changes in sound intensity. In this case, the detection device 10B individually identifies the vehicle 6 in which tire separation has occurred from among the multiple vehicles 6 that exhibit positional changes that correspond to the changes in sound intensity, based on the changes in the center frequency of the audio data.

[0186] Figure 13 is a flowchart illustrating an example of a detection process that can individually identify a vehicle 6 in which tire separation has occurred, even when there are multiple vehicles 6 that show positional changes corresponding to changes in sound intensity.

[0187] The detection process shown in Figure 13 differs from the detection process shown in Figure 12 in that steps S251 and S252 have been added; the other processes are the same. Therefore, the detection process shown in Figure 13 will be explained focusing on the differences between the detection process shown in Figure 12 and the detection process shown in Figure 13.

[0188] After identifying vehicle 6 in which tire separation has occurred in step S250 of Figure 13, the process proceeds to step S251.

[0189] In step S251, CPU 1A determines whether multiple vehicles 6 have been identified as vehicles 6 with tire separation. If multiple vehicles 6 have been identified, the process proceeds to step S252. Note that the multiple vehicles 6 identified in step S250 as having tire separation may include vehicles 6 that do not actually have tire separation. Therefore, the vehicles 6 identified in step S250 as having tire separation are referred to as "candidate vehicles 6".

[0190] In step S252, CPU1A applies a known frequency analysis method to the obtained audio data and performs a time-series frequency analysis. Through the frequency analysis of the audio data, CPU1A obtains the changes in the center frequency of the sound over time.

[0191] CPU1A identifies candidate vehicle 6 from among the candidate vehicles 6 that exhibits driving conditions that match the approach of vehicle 6 to the microphone, as determined from the changes in the center frequency of the sound, as vehicle 6 in which tire separation is occurring. For example, CPU1A identifies candidate vehicle 6 from among the candidate vehicles 6 that exhibits movement that brings it closest to the microphone at the inflection point time of the center frequency as vehicle 6 in which tire separation is occurring.

[0192] After identifying vehicle 6, which has tire separation, proceed to step S260.

[0193] On the other hand, if the determination process in step S251 determines that there is only one candidate vehicle 6 with tire separation, then the vehicle 6 with tire separation has already been identified. Therefore, the process proceeds to step S260 without executing step S252.

[0194] Thus, when there are multiple candidate vehicles 6 identified based on the changes in the position of the vehicle 6 and the changes in the volume of the sound obtained from the audio data, the detection device 10B that performs the detection process shown in Figure 13 identifies the vehicle 6 in which tire separation is actually occurring from among the candidate vehicles 6, based on the changes in the position of the candidate vehicles 6 and the changes in the center frequency of the sound represented by the audio data.

[0195] In the detection process shown in Figure 12, if a vehicle 6 with tire separation is detected by comparing the sound intensity obtained from the microphone audio data with a first threshold, the vehicle 6 with tire separation is identified based on the changes in the vehicle 6's position and the changes in the sound intensity. However, the identification of a vehicle 6 with tire separation can also be done based on the changes in the vehicle 6's position and the changes in the center frequency of the sound represented by the audio data.

[0196] Figure 14 is a flowchart showing an example of the flow of detection processing executed by the CPU 1A of a detection device 10B that uses a microphone installed in a location different from the vehicle 6 as a detection sensor 5 when it receives a start command from the user to start separation detection. The CPU 1A of the detection device 10B reads the detection program stored in the non-volatile memory 1C and executes the detection processing. It is assumed that the time-series location information of each vehicle 6 is sequentially stored in, for example, RAM 1B by the processing of the information acquisition unit 15.

[0197] In step S300 of Figure 14, CPU 1A starts collecting audio data in chronological order through each microphone, similar to step S10 of Figure 4, and stores the collected audio data in, for example, RAM 1B.

[0198] In step S310, CPU 1A measures the volume of each sound collected in step S300 in a time-series manner, similar to step S20 in Figure 4.

[0199] In step S320, CPU 1A, similar to step S30 in Figure 4, determines whether the sound level of each tire measured in step S310 is above the first threshold. If the sound level is above the first threshold, the process proceeds to step S330.

[0200] In step S330, CPU 1A obtains time-series position information for each vehicle 6 from RAM 1B, similar to step S34 in Figure 11.

[0201] In step S340, CPU 1A applies a known frequency analysis method to the obtained audio data, similar to step S37 in Figure 11, and performs a time-series frequency analysis. Through the frequency analysis of the audio data, CPU 1A obtains the changes in the center frequency of the sound over time.

[0202] In step S350, the CPU 1A, similar to step S38 in Figure 11, uses the positional changes of each vehicle 6 acquired in step S330 and the change in the center frequency of the sound acquired in step S340 to identify, from among the vehicles 6, the vehicle 6 whose positional changes match the approach of the vehicle 6 to the microphone obtained from the change in the sound frequency, as the vehicle 6 in which tire separation is occurring. For example, the CPU 1A identifies, from among the vehicles 6, the vehicle 6 that moves closest to the microphone at the inflection point time of the center frequency as the vehicle 6 in which tire separation is occurring.

[0203] In step S360, CPU 1A performs the process of outputting a warning and additional information from the warning output device. The additional information in step S360 is identification information that uniquely identifies the vehicle 6 that was identified in step S350 as having tire separation. After outputting the warning and additional information from the warning output device, the process proceeds to step S370.

[0204] On the other hand, if the judgment process in step S320 determines that the measured sound level is below the first threshold, it is highly likely that no separation has occurred in the tires of any of the vehicles 6. Therefore, the process proceeds to step S370 without executing steps S330 to S360.

[0205] In step S370, CPU 1A determines whether or not it has received a termination command from the user. If it has not received a termination command, it proceeds to step S300 and continues the detection process. On the other hand, if it has received a termination command, it terminates the detection process shown in Figure 14.

[0206] In this way, the detection device 10B, which performs the detection process shown in Figure 14, individually identifies vehicles 6 in which tire separation has occurred by using the changes in the position of the vehicle 6 and the changes in the center frequency of the sound obtained from audio data from a microphone installed in a different location from the vehicle 6.

[0207] In some cases, it is possible that in step S350, there may be multiple vehicles 6 that exhibit positional changes that match the changes in the center frequency of the sound. In this case, the detection device 10B uses the changes in the loudness of the sound to individually identify the vehicle 6 in which tire separation has occurred from among the multiple vehicles 6 that exhibit positional changes that match the changes in the center frequency of the sound.

[0208] Figure 15 is a flowchart illustrating an example of a detection process that can individually identify a vehicle 6 in which tire separation has occurred, even when there are multiple vehicles 6 that show positional changes that match the changes in the center frequency of the sound.

[0209] The detection process shown in Figure 15 differs from the detection process shown in Figure 14 in that steps S351 to S353 have been added; the other processes are the same. Therefore, the detection process shown in Figure 15 will be explained focusing on the differences between the detection process shown in Figure 14 and the detection process shown in Figure 15.

[0210] After identifying candidate vehicle 6 in step S350 of Figure 15, where tire separation is suspected, the process proceeds to step S351.

[0211] In step S351, CPU 1A determines whether multiple candidate vehicles 6 have been identified as vehicles 6 in which tire separation has occurred. If multiple candidate vehicles 6 have been identified, the process proceeds to step S352.

[0212] In step S352, CPU1A acquires the sound intensity along the time series measured in step S310, similar to step S35 in Figure 10.

[0213] In step S353, CPU 1A uses the positional changes of each vehicle 6 acquired in step S330 and the sound intensity changes acquired in step S352 to individually identify the vehicle 6 in which tire separation has occurred from among the candidate vehicles 6. Specifically, CPU 1A identifies the candidate vehicle 6 in which tire separation has occurred as the vehicle 6 whose positional changes match the sound intensity changes, such as being closest to the microphone at the moment of maximum sound, moving closer to the microphone when the sound gets louder, and moving away from the microphone when the sound gets quieter.

[0214] After identifying vehicle 6, which has tire separation, proceed to step S360.

[0215] On the other hand, if the determination process in step S351 determines that there is only one candidate vehicle 6 with tire separation, then the vehicle 6 with tire separation has already been identified. Therefore, the process proceeds to step S360 without executing steps S352 and S353.

[0216] Thus, when there are multiple candidate vehicles 6 identified based on the changes in the position of the candidate vehicle 6 and the changes in the center frequency of the sound represented by the audio data, the detection device 10B that performs the detection process shown in Figure 15 identifies the vehicle 6 in which tire separation is actually occurring from among the candidate vehicles 6, based on the changes in the position of the vehicle 6 and the changes in the loudness of the sound obtained from the audio data.

[0217] In the fourth embodiment described above, microphones installed on equipment operating in the mine other than the track and vehicle 6 were used as detection sensors 5, but odor sensors may be installed instead of microphones.

[0218] Next, the detection process when an odor sensor is used as the detection sensor 5 will be described. Figure 16 is a flowchart showing an example of the flow of the detection process executed by the CPU 1A of the detection device 10B, which uses an odor sensor installed in a different location from the vehicle 6 as the detection sensor 5, when the detection device 10B receives a start command from the user to start separation detection. The CPU 1A of the detection device 10B reads the detection program stored in the non-volatile memory 1C and executes the detection process. It is assumed that the position information of each vehicle 6 in chronological order is sequentially stored in, for example, RAM 1B by the processing of the information acquisition unit 15.

[0219] In step S400 of Figure 16, the CPU 1A starts collecting odor data in a time-series manner through the odor sensor and stores the collected odor data in, for example, RAM 1B.

[0220] In step S410, CPU1A measures the odor intensity from the time-series odor data collected in step S400.

[0221] In step S420, CPU 1A determines whether the odor intensity emitted from the tire, as measured in step S410, is above the second threshold. If the odor intensity is above the second threshold, the process proceeds to step S430. At this point, it has been detected that there is a vehicle 6 with tire separation, but it has not been determined which vehicle 6 has tire separation.

[0222] Therefore, in step S430, CPU 1A obtains time-series position information for each vehicle 6 from RAM 1B, similar to step S34 in Figure 10.

[0223] In step S440, the CPU 1A uses the changes in the position of each vehicle 6 acquired in step S430 and the changes in the intensity of the odor acquired in step S410 to individually identify the vehicle 6 in which tire separation has occurred.

[0224] As vehicle 6 approaches the odor sensor, the odor intensifies, and as vehicle 6 moves away from the odor sensor, the odor weakens. In this case, the odor intensity is at its maximum when vehicle 6 is closest to the odor sensor. Therefore, CPU 1A identifies the vehicle 6 that is experiencing tire separation as the vehicle 6 whose position changes match the changes in odor intensity, such as approaching the odor sensor when the odor intensity is at its maximum, and moving away from the odor sensor when the odor weakens as time progresses.

[0225] In step S450, CPU 1A processes the output of a warning and additional information from the warning output device. The additional information in step S450 is identification information that uniquely identifies the vehicle 6 that was identified in step S440 as having tire separation. After outputting the warning and additional information from the warning output device, the process proceeds to step S460.

[0226] On the other hand, if the determination process in step S420 determines that the measured odor intensity is below the second threshold, it is highly likely that separation has not occurred in the tires of any of the vehicles 6. Therefore, the process proceeds to step S460 without executing steps S430 to S450.

[0227] In step S460, CPU 1A determines whether or not it has received a termination command from the user. If it has not received a termination command, it proceeds to step S400 and continues the detection process. On the other hand, if it has received a termination command, it terminates the detection process shown in Figure 16.

[0228] In this way, the detection device 10B, which performs the detection process shown in Figure 16, individually identifies vehicles 6 in which tire separation has occurred by using the changes in the position of the vehicle 6 and the changes in the intensity of the odor obtained from an odor sensor installed in a different location from the vehicle 6.

[0229] <Fifth Embodiment> In the first to fourth embodiments, an example was described in which a vehicle 6 in which tire separation has occurred is identified using a detection sensor 5. When tire separation occurs, in addition to information on which vehicle 6 has experienced separation, information on the degree of separation is also important to the user. The degree of separation refers to the extent of the separation, such as whether it is a minor separation that allows the vehicle 6 to continue driving, or a severe separation that requires the vehicle 6 to be stopped immediately.

[0230] In the fifth embodiment, a detection device 10C will be described that, when it detects that separation has occurred in the tires of the vehicle 6, outputs an alarm notifying the occurrence of separation and the level at which separation has occurred.

[0231] In the fifth embodiment, an example will be described in which an alarm notifying the occurrence of separation and the separation occurrence level are output based on the detection device 10 shown in the first embodiment.Therefore, the detection sensor 5 is installed on the vehicle 6, and the detection device 10C detects whether or not separation has occurred in the tire of the vehicle 6 on which the detection sensor 5 is installed, and if separation has occurred, it outputs the separation occurrence level.

[0232] It goes without saying that the separation occurrence level estimation function described in the fifth embodiment can be applied to the detection device 10A in the second embodiment, and to the detection device 10B in the third and fourth embodiments.

[0233] Figure 17 shows an example of the functional configuration of the detection device 10C. The difference between the example of the functional configuration of the detection device 10C shown in Figure 17 and the example of the functional configuration of the detection device 10 shown in Figure 2 is the addition of an estimation unit 16. Therefore, the example of the functional configuration of the detection device 10C will be explained focusing on the function of the estimation unit 16.

[0234] If the detection unit 12 detects that separation has occurred in the tires of the vehicle 6, the estimation unit 16 estimates the level of separation in the tires based on the data collected by the data collection unit 11.

[0235] If the separation is minor, the amount of detached rubber and steel cords is relatively small, and therefore the contact between the rubber and steel cords inside the tire during vehicle operation is also relatively small. Consequently, the noise emitted from the tire is quieter, and the odor caused by friction between the rubber and steel cords inside the tire is also weaker.

[0236] On the other hand, as the separation becomes more severe, the amount of detached rubber and steel cords increases compared to when the separation is minor. Consequently, the contact between the rubber and steel cords inside the tire during vehicle 6 operation also increases compared to when the separation is minor. Therefore, compared to when the separation is minor, the noise emitted from the tire becomes louder, and the odor produced by the friction of the rubber and steel cords inside the tire also becomes stronger.

[0237] In other words, the louder the sound obtained from the audio data, and the stronger the odor obtained from the odor data, the higher the separation occurrence level. Therefore, the estimation unit 16 sets a predetermined range for sound loudness and associates the range representing sound loudness with the separation occurrence level so that the range with a louder sound loudness corresponds to a higher separation occurrence level. Similarly, the estimation unit 16 sets a predetermined range for odor intensity and associates the range representing odor intensity with the separation occurrence level so that the range with a stronger odor intensity corresponds to a higher separation occurrence level. In other words, the higher the separation occurrence level, the more severe the separation occurring. Hereafter, the range set for sound loudness or the range set for odor intensity will be referred to as the "set range".

[0238] The estimation unit 16 determines which set range the loudness of the sound or the intensity of the odor measured from the data collected by the detection unit 12 falls into. The estimation unit 16 estimates the occurrence level associated with the set range that includes the loudness of the sound or the intensity of the odor as the separation occurrence level in the tire.

[0239] The estimation unit 16 notifies the output unit 13 of the detection result regarding whether or not separation has occurred in the tire, as detected by the detection unit 12, and, if separation has occurred in the tire, the level of separation in the tire.

[0240] When the output unit 13 receives a detection result from the estimation unit 16 indicating that separation has occurred in the tire, it outputs an alarm along with the separation level from the alarm output device.

[0241] The system including the detection sensor 5 and the detection device 10C is called the detection system 100C.

[0242] The detection device 10C is configured using computer 1, just like the detection device 10. The example of the main components of the electrical system of the detection device 10C configured using computer 1 is the same as the example of the main components of the electrical system of the detection device 10 shown in Figure 3.

[0243] Figure 18 is a flowchart showing an example of the flow of detection processing executed by the CPU 1A of the detection device 10C, which uses a microphone as the detection sensor 5, when the CPU 1A of the detection device 10C receives a start command from the user to begin separation detection. The CPU 1A of the detection device 10C reads the detection program stored in the non-volatile memory 1C and executes the detection processing.

[0244] The detection process shown in Figure 18 differs from the detection process shown in Figure 4 in that step S35A is added and the process in step S40 is replaced by the process in step S40B; all other processes are the same. Therefore, the detection process shown in Figure 18 will be explained focusing on the differences between the detection process shown in Figure 4 and the detection process shown in Figure 18.

[0245] If the determination process in step S30 determines that at least one of the measured sound levels is equal to or greater than the first threshold, the process proceeds to step S35A.

[0246] In step S35A, CPU1A determines which setting range the sound level determined to be above the first threshold by the judgment process in step S30 falls into. CPU1A estimates the generation level associated with the setting range that includes the sound level determined to be above the first threshold as the separation generation level in the tire.

[0247] CPU1A may also estimate the remaining time of the tire that has separated based on the changes in sound intensity over time. The remaining time of the separated tire is the remaining time that vehicle 6 can safely travel at the current speed. For example, CPU1A can input the changes in sound intensity over time of the separated tire into an estimation model that has been trained using machine learning to associate the changes in sound intensity over time with the remaining time of the tire, and obtain the remaining time of that tire.

[0248] Alternatively, CPU1A may estimate the remaining distance of the tire that has separated, either in addition to or in conjunction with the remaining tire time. The remaining distance of the tire that has separated is the remaining distance that vehicle 6 can safely travel if it is driven at the current speed. If the remaining tire time can be estimated, the remaining distance of the tire can be estimated by multiplying the average speed of vehicle 6 over a certain period of time up to the point in time when the remaining tire time was estimated by the remaining tire time.

[0249] In step S40B of Figure 18, the CPU 1A outputs an alarm notifying the occurrence of separation and the separation level in the tire estimated in step S35A from the alarm output device. In this case, the CPU 1A may output additional information from the alarm output device along with the alarm and the separation level. The additional information according to the fifth embodiment includes at least one of the following: the mounting position of the tire where separation may be occurring, the remaining time on the tire, and the remaining distance on the tire. After outputting the alarm and the separation level from the alarm output device, the process proceeds to step S50.

[0250] The above describes an example in which a microphone is used as the detection sensor 5, but an odor sensor may also be used as the detection sensor 5. In this case, after the determination process in step S120 of the detection process shown in Figure 5 determines that the odor intensity is equal to or greater than the second threshold, the process corresponding to step S35A in Figure 18 is executed, and the process corresponding to step S40A in Figure 18 is executed instead of step S130 in Figure 5.

[0251] As described above, the detection device 10C, which performs the detection process shown in Figure 18, estimates the level of separation in the tire based on the collected data when it detects that separation has occurred in the tire, and outputs the estimated level of separation from the alarm output device.

[0252] <How to deal with vehicle 6 where separation has occurred> Depending on the estimated level of separation, CPU1A may output, via an alarm output device, a method of action that vehicle 6 can take to at least one of the driver of vehicle 6 equipped with the separated tire and the operator in the control room 7.

[0253] The countermeasures that vehicle 6 can take are predetermined for each level of separation occurrence, and are associated with each occurrence level and stored, for example, in non-volatile memory 1C.

[0254] For example, the higher the estimated incidence level, the shorter the interval between tire inspections can be.

[0255] Let's assume that the occurrence levels are in the order of increasing severity: Occurrence Level A < Occurrence Level B < Occurrence Level C < Occurrence Level D. Occurrence Level A represents the least severe occurrence of separation, and Occurrence Level D represents the most severe occurrence of separation.

[0256] In the case of occurrence level A, the vehicle 6 is often still able to drive. Therefore, CPU1A outputs a warning from the alarm output device prompting the driver to inspect the tires during the next scheduled maintenance.

[0257] In the case of occurrence level B, vehicle 6 is still able to be driven, but it is preferable to have the tires inspected as soon as possible. Therefore, if vehicle 6 is refueled every time after the completion of daily work, CPU1A will output a warning from the alarm output device prompting the vehicle 6 to have its tires inspected the next time it stops at a refueling facility.

[0258] In the case of occurrence level C, it is best to avoid driving vehicle 6 as much as possible until the tire inspection is complete. Therefore, CPU1A outputs a warning from the alarm output device instructing the driver to interrupt the scheduled work and drive vehicle 6 to the tire inspection facility.

[0259] In the case of occurrence level D, immediate action is required regarding the tires. Therefore, CPU1A outputs a warning message from the alarm output device prompting the driver to immediately suspend the scheduled work and drive vehicle 6 to a cooling facility where the tires will be cooled by water or air. After the tires have cooled, CPU1A outputs a warning message from the alarm output device prompting the driver to drive vehicle 6 to a tire inspection facility.

[0260] If vehicle 6 is being driven by a driver, the driver can take appropriate action according to the degree of separation that has occurred by driving in accordance with the instructions of the detection device 10C. Furthermore, if the driving status of vehicle 6 is being managed by an operator in the control room 7, the operator can provide advice to the driver of vehicle 6 experiencing separation, in accordance with the instructions of the detection device 10C.

[0261] Furthermore, if separation occurs in a tire, CPU1A may record, for example, the identification information of the vehicle 6 in which separation has occurred, the level of separation, and the mounting position of the tire in which separation has occurred in the inspection list. In addition, CPU1A may record at least one of the remaining time and remaining distance of the tire in the inspection list. The information about the tire in which separation has occurred that is recorded in the inspection list is called "separation information".

[0262] The inspection list is, for example, a list that can be read from multiple predetermined terminals and is stored on a cloud server or the like. Terminals that can read the inspection list are installed not only in the control room 7, but also in inspection facilities that inspect and replace the tires of vehicle 6, refueling facilities that supply gasoline to vehicle 6, and cooling facilities that cool the tires of vehicle 6. Therefore, operators in the control room 7, workers at the tire inspection facilities, workers at the refueling facilities, and workers at the tire cooling facilities can share separation information. Facilities such as inspection facilities, refueling facilities, and cooling facilities that check the condition of tires that have separated are collectively referred to as "related facilities."

[0263] Furthermore, CPU1A outputs an alarm and the separation occurrence level to the alarm output device, and also sends a request for action to the relevant facilities according to the separation occurrence level via communication unit 2, informing them that separation has occurred in the tires of vehicle 6. For example, email and SNS (Social Networking Service) may be used for the request for action.

[0264] In the above example, if separation of level A is suspected in the tire, vehicle 6 will continue with its scheduled work, so CPU1A will not send a response request to any of the relevant facilities. If separation of level B is suspected in the tire, vehicle 6 will stop at a refueling facility, so CPU1A will send a response request to the refueling facility. If separation of level C is suspected in the tire, vehicle 6 will head to an inspection facility, so CPU1A will send a response request to the inspection facility. If separation of level D is suspected in the tire, vehicle 6 will head to a cooling facility, so CPU1A will send a response request to the cooling facility.

[0265] By sending a request for assistance, workers at the relevant facility can check the inspection list before vehicle 6 arrives at the facility and understand the status of any separation that may have occurred in advance. Furthermore, workers at the relevant facility can prepare by coordinating the schedules of the workers responsible for the response and checking the inventory of replacement tires before vehicle 6 arrives.

[0266] The inspection facility worker refers to the inspection list and, if a record of separation at level A is found on the tire, checks the tire's condition in addition to the usual periodic inspection items, for example, with the tire mounted on vehicle 6. The inspection facility worker decides whether or not to replace the tire based on the inspection results and replaces the tire if necessary. If tire replacement is not necessary, vehicle 6 can continue with its scheduled work. Once the tire inspection is complete, the inspection facility worker records that the tire inspection is finished by adding, for example, the inspection result and inspection completion information indicating that the inspection has been completed to the separation information recorded on the inspection list of the inspected vehicle 6.

[0267] Furthermore, the refueling facility staff will refer to the inspection list and, if a record of separation at level B is found on the tires, will thoroughly check the condition of the tires in addition to refueling vehicle 6. Based on the tire inspection results, the refueling facility staff will decide whether or not to replace the tires. If tire replacement is necessary, the refueling facility staff will send a request for action to the inspection facility via the refueling facility terminal and inform the driver of vehicle 6 to have the tires replaced at the inspection facility. If tire replacement is not necessary, vehicle 6 can continue with its scheduled operations. Once the tire inspection is complete, the refueling facility staff will record that the tire inspection is complete by adding, for example, the inspection result and inspection completion information to the separation information recorded on the inspection list of the inspected vehicle 6.

[0268] Furthermore, the inspection facility workers refer to the inspection list and, if a history of separation at level C is recorded for the tire, they will thoroughly check the tire's condition. Based on the tire inspection results, the inspection facility workers will decide whether or not to replace the tire and replace it if necessary. If tire replacement is not necessary, vehicle 6 can continue with its scheduled work. Once the tire inspection is complete, the inspection facility workers will record that the tire inspection is finished by adding, for example, the inspection results and inspection completion information to the separation information recorded in the inspection list of the inspected vehicle 6.

[0269] Furthermore, the cooling facility workers refer to the inspection list and, if a record of separation occurrence at level D is found on the tire, they check the tire's condition and determine whether or not cooling is necessary. If cooling is necessary, the cooling facility workers perform the cooling. In addition, the cooling facility workers replace the tire regardless of whether or not cooling is necessary. Once the tire replacement is complete, the cooling facility workers record that the tire replacement is complete by adding, for example, the condition of the tire before replacement and inspection completion information to the separation information recorded on the inspection list of the vehicle 6 whose tire has been replaced.

[0270] In this manner, the CPU 1A of the detection device 10C outputs possible countermeasures that the vehicle 6 can take through the alarm output device, according to the estimated level of separation occurrence. The CPU 1A of the detection device 10C also records the separation information in the inspection list and sends a request for action to the relevant facilities according to the level of separation occurrence.

[0271] The driver of vehicle 6 and the operator in control room 7 can ensure the safety of vehicle 6 and proceed with the work using vehicle 6 as scheduled as possible by following the procedures outlined. In addition, the relevant facilities can make the necessary preparations for tire inspection and replacement before vehicle 6 arrives at the facility.

[0272] <Sixth Embodiment> In the sixth embodiment, a detection device 10D that estimates the level of tire separation when the vehicle 6, which detects whether or not tire separation occurs, is in autonomous driving mode will be described.

[0273] Figure 19 shows an example of the functional configuration of the detection device 10D. The difference between the example of the functional configuration of the detection device 10D shown in Figure 19 and the example of the functional configuration of the detection device 10C shown in Figure 17 is the addition of a control unit 17. Therefore, the example of the functional configuration of the detection device 10D will be explained focusing on the functions of the control unit 17.

[0274] Since vehicle 6 operates autonomously, there is no driver in vehicle 6. Therefore, the control unit 17 controls vehicle 6 on behalf of the driver. Specifically, the control unit 17 uses information obtained from sensors such as acceleration sensors, gyro sensors, LiDAR (Light Detection And Ranging), millimeter-wave radar, and cameras attached to vehicle 6 to understand the state of vehicle 6 and the state of the road, and performs autonomous control to drive vehicle 6 to its destination without colliding with other vehicles 6 by controlling the amount of accelerator operation, brake operation, and steering operation.

[0275] The system including the detection sensor 5 and the detection device 10D is called the detection system 100D.

[0276] The detection device 10D is also configured using the computer 1 in the same manner as the detection device 10. An example of the main configuration of the electrical system of the detection device 10D configured using the computer 1 is the same as the example of the main configuration of the electrical system of the detection device 10 shown in FIG. 3.

[0277] FIG. 20 is a flowchart showing an example of the flow of detection processing executed by the CPU 1A of the detection device 10D that uses a microphone as the detection sensor 5 when a start instruction to start detection of separation is received from the user. The CPU 1A of the detection device 10D reads a detection program stored in the non-volatile memory 1C and executes the detection processing.

[0278] The difference between the detection processing shown in FIG. 20 and the detection processing shown in FIG. 18 is that step S45 is added and the processing of step S50 is replaced with the processing of step S50A. Also, with the addition of step S45, when it is determined by the determination processing in step S30 that the magnitude of any of the measured sounds is less than the first threshold value, the destination of the transition is changed to step S50A, but the other processing is the same. Therefore, the description of the detection processing shown in FIG. 20 will be made focusing on the parts where the processing is different from the detection processing shown in FIG. 18.

[0279] After performing the process of outputting an alarm notifying the occurrence of separation and the occurrence level of separation from the alarm output device in step S40B, the process proceeds to step S45.

[0280] In step S45, the CPU 1A acquires, for example, from the non-volatile memory 1C, the coping methods that the vehicle 6 can take for each occurrence level of separation determined in advance. The CPU 1A executes control according to the acquired coping method on the vehicle 6 having the identification information included in the separation information.

[0281] For example, if the separation occurrence level is level B, CPU1A will continue the scheduled work assigned to vehicle 6 and, after the end of the day's work, will control the vehicle to stop at a refueling facility.

[0282] In this way, control is performed on the vehicle 6 according to the countermeasures corresponding to the level of separation occurrence, and the process proceeds to step S50A.

[0283] On the other hand, if the judgment process in step S30 determines that the loudness of any of the measured sounds is below the first threshold, that is, if it is determined that no separation has occurred in the tires, the process proceeds to step S50A.

[0284] In step S50A, CPU1A determines whether the termination conditions for terminating separation detection are met. These conditions may include, for example, whether all scheduled tasks have been completed, or whether a termination instruction to terminate separation detection has been received from the operator in control room 7. If the termination conditions are not met, the process proceeds to step S10 and continues. If the termination conditions are met, the detection process shown in Figure 20 is terminated.

[0285] The detection device 10D shown in Figure 19 executed a corresponding countermeasure on the vehicle 6 based on the separation occurrence level estimated by the detection device 10D. However, the detection device 10D may also execute control on the vehicle 6 based on instructions from the control device 7A in the control room 7, which notified the separation occurrence level.

[0286] Figure 21 shows an example of a functional configuration of a detection device 10D that controls the vehicle 6 based on instructions from the management device 7A according to the response method.

[0287] Unlike the detection device 10D shown in Figure 19, the control unit 17 of the detection device 10D shown in Figure 21 is not connected to the estimation unit 16 but is connected to the management device 7A. In this case, the predetermined countermeasures that the vehicle 6 can take for each separation occurrence level are stored not in the non-volatile memory 1C, but, for example, in the storage device of the management device 7A.

[0288] Upon receiving the separation occurrence level from the detection device 10D, the management device 7A refers to the corresponding countermeasures stored in the management device 7A's memory device and transmits a control instruction to the detection device 10D according to the countermeasures.

[0289] The control unit 17 of the detection device 10D, upon receiving a control instruction from the management device 7A, executes control in accordance with the control instruction from the management device 7A for the vehicle 6 that has identification information included in the separation information.

[0290] The control unit 17 does not necessarily have to be included in the detection device 10D; an ECU (Electronic Control Unit) pre-installed in the vehicle 6 may be used as the control unit 17. In this case, the management device 7A only needs to send control instructions according to the handling method to the ECU of the vehicle 6 that has the identification information included in the separation information.

[0291] Although one form of the detection device 10, 10A to 10D (hereinafter referred to as "detection device 10, etc.") has been described above using embodiments, the disclosed form is merely an example, and the form of the detection device 10, etc. is not limited to the scope described in the embodiments. Various modifications or improvements can be made to the embodiments without departing from the gist of this disclosure, and such modified or improved forms of the detection device 10, etc. are also included within the technical scope of the disclosure.

[0292] In the above embodiment, as an example, a configuration in which each detection process is implemented in software was described. However, it is also possible to have the equivalent processes of each detection process executed in hardware. In this case, the processing speed can be increased compared to the case in which each detection process is implemented in software.

[0293] Furthermore, the above embodiment described an example in which the detection program is stored in the non-volatile memory 1C. However, the storage location of the detection program is not limited to the non-volatile memory 1C. The detection program can also be provided in a form recorded on a storage medium that can be read by a computer.

[0294] For example, the detection program may be provided in the form of a portable semiconductor memory such as a USB (Universal Serial Bus) memory or memory card. Non-volatile memory 1C, USB, and memory cards are examples of non-transitory storage media.

[0295] Furthermore, the CPU 1A may download a detection program from an external device via the communication unit 2 and store the downloaded detection program in the non-volatile memory 1C.

[0296] In the embodiment, CPU1A was used as an example of a general-purpose processor for explanation. However, in the embodiment, the term "processor" refers to a processor in a broad sense, and includes not only general-purpose processors like CPU1A, but also dedicated processors (e.g., GPU: Graphics Processing Unit, ASIC: Application Specific Integrated Circuit, FPGA: Field Programmable Gate Array, programmable logic device, etc.).

[0297] Furthermore, the operation of the processor in the above-described embodiment may not be performed by a single processor, but may be performed by multiple processors working together, or by multiple processors located in physically separate locations working together. This disclosure can also be applied to programs and program products.

[0298] All documents, patent applications, and technical standards described in this specification are incorporated herein by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually indicated to be incorporated by reference.

[0299] [Contribution to the United Nations-led Sustainable Development Goals (SDGs)] The SDGs have been proposed towards the realization of a sustainable society. One embodiment of the present invention can be considered as a technology that contributes to "No. 9 - Build the foundation of industry and technological innovation" and the like.

Explanation of Reference Numerals

[0300] 1 Computer 1A CPU 1B RAM 1C Non-volatile Memory 1D I / O 1E Bus 2 Communication Unit 3 Input Unit 4 Output Unit 5 Detection Sensor 6 Vehicle (own vehicle, other vehicle, candidate vehicle, mining vehicle) 6A Notification Device 7 Control Room 7A Management Device 10 (10A, 10B, 10C, 10D) Detection Device 11 Data Collection Unit 12 Detection Unit 13 Output Unit 14 Identification Unit 15 Information Acquisition Unit 16 Estimation Unit 17 Control Unit 100 (100A, 100B, 100C, 100D) Detection System

Claims

1. A data collection unit that uses a microphone as a detection sensor to collect sound generated from the tires of a mining vehicle as data, or uses an odor sensor as the detection sensor to collect odor generated from the tires of a mining vehicle as data, A detection unit that uses the collected data collected by the data collection unit to detect whether or not separation has occurred in the tire, A detection device equipped with this device.

2. The detection unit detects that separation has occurred in the tire when the loudness of the sound or the intensity of the odor, as represented by the collected data, exceeds a predetermined threshold. The detection device according to claim 1.

3. The aforementioned detection sensor is installed on a mining vehicle. The detection device according to claim 2.

4. The aforementioned detection sensors are installed at each of the tire mounting positions, The detection unit detects whether or not separation has occurred in the tire for each mounting position. The detection device according to claim 3.

5. If the detection sensor is the odor sensor, the odor sensor is installed in the air conditioning duct connected to the interior of the mining vehicle. The detection device according to claim 3.

6. If the detection sensor is the microphone, The system further includes an identification unit that identifies a mining vehicle in which tire separation has occurred, using the audio data, which is the collected data, collected by the data collection unit. If the detection unit detects that separation has occurred in the tire, the identification unit identifies that separation has occurred in the tire of the mining vehicle on which the microphone is installed if the loudness of the sound represented by the audio data is above the threshold for a specified period of time, and identifies that separation has occurred in the tire of a different mining vehicle than the mining vehicle on which the microphone is installed if the period during which the loudness of the sound represented by the audio data is above the threshold is less than the specified period. The detection device according to claim 4.

7. If the detection sensor is the microphone, The system further includes an identification unit that identifies a mining vehicle in which tire separation has occurred, using the audio data, which is the collected data, collected by the data collection unit. If the detection unit detects that separation has occurred in the tire, the identification unit identifies that separation has occurred in the tire of the mining vehicle on which the microphone is installed if the frequency of the sound in the time series represented by the audio data falls within a predetermined frequency range, and identifies that separation has occurred in the tire of a different mining vehicle than the one on which the microphone is installed if the frequency of the sound in the time series represented by the audio data exceeds the frequency range. The detection device according to claim 4.

8. The system further includes an output unit that, when the detection unit detects that separation has occurred in the tire, outputs an alarm along with additional information indicating whether the mining vehicle with the tire separation is the mining vehicle on which the microphone is installed, or another mining vehicle. The detection device according to claim 6 or claim 7.

9. It is further equipped with an information acquisition unit that acquires location information for each mining vehicle traveling on the same mine track. When the identifying unit identifies that separation has occurred in the tires of the other mining vehicle, it identifies the other mining vehicle whose position changes in a manner consistent with the changes in sound intensity, based on the changes in sound intensity over time represented by the audio data and the changes in the position of the other mining vehicle over time represented by the position information, as the other mining vehicle in which separation has occurred in its tires. The detection device according to claim 6 or claim 7.

10. The system further includes an output unit that, when the detection unit detects that separation has occurred in the tire, outputs an alarm along with identification information that identifies the other mining vehicle identified by the identification unit. The detection device according to claim 9.

11. It is further equipped with an information acquisition unit that acquires location information for each mining vehicle traveling on the same mine track. When the identifying unit identifies that separation has occurred in the tires of the other mining vehicle, at the inflection point time when an inflection point appears in which the frequency of the sound represented by the audio data changes from rising to falling, the unit identifies the mining vehicle whose position is closest to the mining vehicle on which the microphone is installed, among the mining vehicles whose positions are represented by the position information, as the other mining vehicle on which separation has occurred in the tires. The detection device according to claim 6 or claim 7.

12. The system further includes an output unit that, when the detection unit detects that separation has occurred in the tire, outputs an alarm along with identification information that identifies the other mining vehicle identified by the identification unit. The detection device according to claim 11.

13. The system further includes an identification unit that identifies mining vehicles in which separation has occurred in the tires, using the odor data, which is the collected data, collected by the data collection unit. If the detection unit detects that separation has occurred in the tire, the identification unit identifies that separation has occurred in the tire of the mining vehicle on which the odor sensor is installed if the odor intensity represented by the odor data is above the threshold for a specified period of time, and identifies that separation has occurred in the tire of a different mining vehicle than the one on which the odor sensor is installed if the period during which the odor intensity represented by the odor data is above the threshold is less than the specified period. The detection device according to claim 5.

14. If the detection unit detects that separation has occurred in the tire, it will output an alarm along with additional information indicating whether the mining vehicle with the tire separation is the mining vehicle on which the odor sensor is installed, or another mining vehicle. The detection device according to claim 13.

15. The aforementioned detection sensors are installed on the tracks used by mining vehicles. The detection device according to claim 2.

16. The detection sensors are installed along the track on which mining vehicles travel, from the bottom of the pit (a depression formed by mineral extraction) to the top of the pit. The detection device according to claim 15.

17. The aforementioned detection sensors are installed at intersections where multiple roads intersect. The detection device according to claim 15.

18. The aforementioned detection sensors are installed at the entrances and exits of a supply facility that provides power to mining vehicles. The detection device according to claim 15.

19. The aforementioned detection sensors are installed at the entrance and exit of the unloading area where mining vehicles unload the extracted minerals. The detection device according to claim 15.

20. The aforementioned detection sensors are installed at the entrance and exit of the loading area where minerals are loaded onto mining vehicles. The detection device according to claim 15.

21. The aforementioned detection sensors are installed at the entrance and exit of the rest area where drivers of mining vehicles take breaks. The detection device according to claim 15.

22. The aforementioned detection sensors are installed on equipment operating in mines other than mining vehicles. The detection device according to claim 2.

23. The aforementioned detection sensor is installed in the unloading equipment at the unloading area where mining vehicles unload the extracted minerals. The detection device according to claim 22.

24. The aforementioned detection sensor is installed in the loading equipment of a loading area where minerals are loaded onto mining vehicles. The detection device according to claim 22.

25. If the detection sensor is the microphone, An information acquisition unit that acquires location information for each mining vehicle traveling on the same mine track, The system further includes an identification unit that identifies a mining vehicle in which tire separation has occurred, using location information acquired by the information acquisition unit and audio data which is the collected data acquired by the data collection unit. If the detection unit detects that separation has occurred in the tire, the identification unit identifies a mining vehicle whose position changes in a manner consistent with the changes in sound intensity, based on the changes in sound intensity over time represented by the audio data and the changes in the position of the mining vehicle over time represented by the position information, as the mining vehicle in which separation has occurred in the tire. A detection device according to any one of claims 15 to 24.

26. If there are multiple mining vehicles that exhibit positional changes that correspond to changes in sound intensity, the identification unit identifies, among the multiple mining vehicles whose driving status is represented by the change in position information, the mining vehicle that exhibits a positional change that corresponds to the approach of the mining vehicle to the microphone obtained from the change in sound frequency represented by the audio data, as a mining vehicle in which separation has occurred in the tires. The detection device according to claim 25.

27. If the detection unit detects that separation has occurred in the tire, it will output an alarm along with identification information that identifies the mining vehicle identified by the identification unit. The detection device according to claim 25.

28. If the detection sensor is the microphone, An information acquisition unit that acquires location information for each mining vehicle traveling on the same mine track, The system further includes an identification unit that identifies a mining vehicle in which tire separation has occurred, using location information acquired by the information acquisition unit and audio data which is the collected data acquired by the data collection unit. If the detection unit detects that separation has occurred in the tire, the identification unit identifies the mining vehicle that is moving closest to the microphone among the mining vehicles whose positions are represented by the position information at the inflection point time when the frequency of the sound represented by the audio data changes from rising to falling, as the mining vehicle in which separation has occurred in the tire. A detection device according to any one of claims 15 to 24.

29. If there are multiple mining vehicles passing in front of the microphone, the identification unit identifies, from the changes in sound volume over time represented by the audio data and the changes in the position of the mining vehicles over time represented by the position information, one of the multiple mining vehicles whose position changes match the changes in sound volume, as the mining vehicle in which tire separation has occurred. The detection device according to claim 28.

30. If the detection unit detects that separation has occurred in the tire, it will output an alarm along with identification information that identifies the mining vehicle identified by the identification unit. The detection device according to claim 28.

31. If the detection sensor is the odor sensor, An information acquisition unit that acquires location information for each mining vehicle traveling on the same mine track, The system further includes an identification unit that identifies mining vehicles in which separation has occurred in the tires, using the odor data, which is the collected data, collected by the data collection unit. If the detection unit detects that separation has occurred in the tire, the identification unit identifies the mining vehicle whose driving status is represented by the change in position information and whose change in position is consistent with the approach status of the mining vehicle to the odor sensor obtained from the change in odor intensity represented by the odor data as the mining vehicle in which separation has occurred in the tire. A detection device according to any one of claims 15 to 24.

32. If the detection unit detects that separation has occurred in the tire, it will output an alarm along with identification information that identifies the mining vehicle identified by the identification unit. The detection device according to claim 31.

33. If the detection unit detects that separation has occurred in the tire, the system includes an estimation unit that estimates the level of separation in the tire based on the collected data. The detection device according to claim 1.

34. The system further includes an output unit that, when the detection unit detects that separation has occurred in the tire, outputs an alarm and the level of separation estimated by the estimation unit to at least one of a notification device for the driver of the mining vehicle where the separation has occurred, and a control device in the control room that manages the operation of the mining vehicle. The detection device according to claim 33.

35. The output unit outputs to at least one of the notification device and the management device a method of action that the mining vehicle can take, depending on the level of separation that occurs. The detection device according to claim 34.

36. The aforementioned countermeasures are predetermined for each level of separation occurrence, and the more severe the separation, the shorter the period until the tire is inspected. The detection device according to claim 35.

37. Of the predetermined number of occurrence levels, the countermeasure corresponding to the most severe occurrence level of tire separation is to interrupt scheduled work on the mining vehicle and drive the mining vehicle to the tire cooling facility. The detection device according to claim 36.

38. It also includes a control unit that controls the mining vehicle in place of the driver, The control unit executes control on the mining vehicle in accordance with the countermeasure method. The detection device according to claim 37.

39. The control unit executes control over the mining vehicle in accordance with the aforementioned action method based on instructions from the management device in accordance with the aforementioned action method. The detection device according to claim 38.

40. On the computer, A microphone is used as a detection sensor to collect sound data generated from the tires of a mining vehicle, or an odor sensor is used as the detection sensor to collect odor data generated from the tires of a mining vehicle. A detection program that uses the collected data to perform a process to detect whether or not separation has occurred in the tire.

41. A detection sensor using a microphone that converts the loudness of sound emitted from the tires of a mining vehicle into an electrical signal, or an odor sensor that converts the intensity of odor emitted from the tires into an electrical signal, A detection device comprising a data collection unit for collecting data obtained by the aforementioned detection sensor, and a detection unit for detecting whether or not separation has occurred in the tire using the collected data collected by the data collection unit, A detection system including a detection system.

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