CROSS-REFERENCE TO RELATED APPLICATION(S)

[0001] This application claims priority to U.S. Provisional Patent Application No. 62/613,877, filed on January 5, 2018, the entire contents of which are fully incorporated herein by reference.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH

[0002] This invention was made with government support under grant 69A3551747132 awarded by the U.S. Department of Transportation. The U.S. government has certain rights in the invention.

BACKGROUND

[0003] The present disclosure is directed to the detection of defects in rails. More specifically, the present disclosure is directed to systems, methods, and devices for passively detecting traverse defects in rails at a high speed.

[0004] Since the railway was first introduced centuries ago, it has become an essential component in the global transportation system. In recent years, rail has comprised more than 30% of United States (U.S.) exports, hauling five million tons of freight and approximately 85,000 passengers per day. The private freight rail industry comprises the majority of the rail infrastructure in the U.S. In 2015, more than $27 billion in railway infrastructure construction was invested. After a prolonged service-life, steel rails can generate defects, such as cracks or corrugations due to surface fatigue. Rail deterioration presents obvious safety concerns. To promote continued safe and reliable rail operation, numerous inspection and detection technologies have been proposed to monitor the condition of rail health. However, current detection technologies still contain disadvantages limiting their application.

[0005] Among these disadvantages are a slow rate of inspection (for example, 25 mph for ultrasonic inspection); a high rate of false recognition for imaging technology, most of which are related to the issue of defect classification; and/or an inability to distinguish between defect signals and regular noises for acoustic technology.

[0006] Therefore, there exists a need for a system and method for the detection of rail defects, such as transverse defects, which are capable of reliably detecting defects at high speeds.

BRIEF SUMMARY OF THE DISCLOSURE

[0007] Various aspects of the present disclosure related to devices, vehicles, and methods for detecting a rail defect.

[0008] In one exemplary aspect of the present disclosure, there is provided a rail defect detection device, comprising: a first sensor configured to receive a first acoustic signal representing contact between a train and a rail, and to generate a first output signal; a second sensor configured to receive a second acoustic signal representing contact between the train and the rail, and to generate a second output signal; a location sensor configured to generate a location data; a processor configured to compare the first output signal and the second output signal with a reference signal, and to generate a detection data; and a memory configured to store at least one selected from the first output signal, the second output signal, the location data, the reference signal, or the detection data.

[0009] In another exemplary aspect of the present disclosure, there is provided a vehicle configured to operate on a rail, comprising: an engine; a plurality of wheels; and a rail defect detection device, including: a first sensor configured to receive a first acoustic signal representing contact between the vehicle and the rail, and to generate a first output signal, a second sensor configured to receive a second acoustic signal representing contact between the vehicle and the rail, and to generate a second output signal, a location sensor configured to generate a location data, a processor configured to compare the first output signal and the second output signal with a reference signal, and to generate a detection data, and a memory configured to store at least one selected from the first output signal, the second output signal, the location data, the reference signal, or the detection data.

[0010] In another exemplary aspect of the present disclosure, there is provided a method of detecting a defect in a rail, comprising: receiving a first acoustic signal via a first sensor, the first acoustic signal representing contact between a train and a rail, and generating a first output signal; receiving a second acoustic signal via a second sensor, the second acoustic signal representing contact between the train and the rail, and generating a second output signal;

generating a location data; comparing the first output signal and the second output signal with a reference signal, and generating a detection data; and storing at least one selected from the first output signal, the second output signal, the location data, the reference signal, or the detection data.

[0011] In this manner, various aspects of the present disclosure provide for improvements in at least the technical fields of rail transportation and rail inspection.

[0012] This disclosure can be embodied in various forms, including hardware or circuits controlled by computer-implemented methods, computer program products, computer systems and networks, user interfaces, and application programming interfaces; as well as hardware- implemented methods, signal processing circuits, memory arrays, application specific integrated circuits, field programmable gate arrays, and the like. The foregoing summary is intended solely to provide a general idea of various aspects of the present disclosure, and does not limit the scope of the disclosure in any way.

DESCRIPTION OF THE DRAWINGS

[0013] These and other more detailed and specific features of various aspects are more fully disclosed in the following description, reference being had to the accompanying drawings, in which:

[0014] FIG. 1 illustrates a cross-sectional view of an exemplary rail for use with various aspects of the present disclosure;

[0015] FIG. 2 illustrates a partial cross-sectional view of the exemplary rail of FIG. 1;

[0016] FIG. 3 illustrates another partial cross-sectional view of the exemplary rail of FIG. 1;

[0017] FIG. 4 illustrates another partial cross-sectional view of the exemplary rail of FIG. 1;

[0018] FIG. 5 illustrates another partial cross-sectional view of the exemplary rail of FIG. 1;

[0019] FIG. 6 illustrates an exemplary detection system according to various aspects of the present disclosure;

[0020] FIG. 7 illustrates an exemplary detection device according to various aspects of the present disclosure;

[0021] FIG. 8 illustrates another exemplary detection device according to various aspects of the present disclosure; and

[0022] FIG. 9 illustrates an exemplary detection method according to various aspects of the present disclosure. DETAILED DESCRIPTION

[0023] In the following description, numerous details are set forth, such as circuit configurations, circuit operations, and the like, in order to provide an understanding of one or more aspects of the present disclosure. It will be readily apparent to one skilled in the art that these specific details are merely exemplary and not intended to limit the scope of this application.

[0024] The present disclosure provides for an acoustic emission sensor capable of detecting transverse rail defects at a high speed; for example, at 220 mi/hr (350 km/hr) or higher.

Moreover, while the present disclosure focuses mainly on examples in which the various aspects are used in the detection of rail defects, it will be understood that this is merely one example of an implementation. It will be further understood that the disclosed aspects can be used in any setting in which there is a need to detect particular acoustic signatures, including high-speed settings.

[0025] Rails and Rail Defects

[0026] A railway typically consists of a plurality of rails (for example, two rails) which extend parallel to one another, rail ties which support the rails and extend perpendicular to the rails, and fasteners which connect the rails to the rail ties. FIG. 1 illustrates an exemplary rail 100 from a cross-sectional perspective. The rail 100 includes a head 101, a web 102, and a base (or foot)

103. The base 103 is attached to a support, such as a rail tie, by a fastener (not shown). In use, the head 101 contacts the wheel or wheels of rolling stock which travels along the rail.

[0027] Modem rails are generally formed from steel, for example by a hot-rolling process. Rails are placed in service for a period of several years, up to several decades or more. Given the long service life and high-stress service conditions, even modern rails may be subject to failure. Failure of modern steel rails can be divided into three groups: manufacturing defects, inappropriate installation and maintenance, and in-service wear or rolling contact fatigue.

[0028] As for the first type of failure: modern steel rails still contain some defects from the manufacturing process. Hydrogen imperfections during the cooling process can cause transverse defects in high-chrome rails known as transverse fissures. FIG. 2 illustrates an expanded view of a rail, such as the rail 100 of FIG. 1, focusing on the head 101. FIG. 2 further illustrates a transverse fissure 201. A transverse fissure is a defect which begins as a fracture and

progressively develops in a direction transverse to the running surface of the head 101.

Transverse fissure defects are not easy to detect. Cyclic loading from passing trains may cause the hydrogen imperfection to grow into a fatigue crack. The crack will grow faster the longer it becomes; thereby, accelerating the failure progress. Upon reaching the critical size, the rail can fracture in half.

[0029] During the manufacturing process, rails may also generate internal seams and/or segregations. The seams may cause a split head to form. Split heads can be either horizontal, longitudinal to the rail, or vertical, transverse to the rail. FIG. 3 illustrates an expanded view of a rail, such as the rail 100 of FIG. 1, focusing on the head 101. FIG. 3 further illustrates a horizontal split head defect 301 and a vertical split head 302. Generally, a horizontal split head such as the horizontal split defect 301 will originate approximately ¼ inch under the rail surface, while a vertical split head such as the vertical split head defect 302 will usually generate through, or near, the center of the head 101 and progress to the surface. The split will grow quickly once the seam or separation begins to spread, ultimately leading to failure of the rails.

[0030] Inappropriate cooling can also cause a longitudinal seam or shrinkage cavity in the middle of web, which may lead to a defect known as piped rail. Once development initiates, the defect will grow vertically towards the two sides of the rail. Axle loading will then cause the defect to develop in a horizontal direction, resulting in a cavity inside the web. FIG. 4 illustrates an expanded view of a rail, such as the rail 100 of FIG. 1, focusing on the web 102. FIG. 4 further illustrates a piped rail defect 401.

[0031] As for the second type of failure: during the installation process, improper handling methods can lead to rail damage. Seams and segregations can be formed due to poor installation. During service, such flaws can cause severe defects in joints and bases, ultimately leading to failure.

[0032] Rail bases at grade crossings are vulnerable to corrosion from asphalt-based acidic filled materials. Most of the corrosion fatigue originates at the web-to-head connection, which causes rail separating at the head-to-web joint. Further, gravel in crossings, excessive speed on curves, or improper canting of the rail can cause the accelerated development of defects. Similar cracking can also be found in the head fillet area at the jointed rail end, which is usually caused by an extreme stress condition.

[0033] During the installation process of base and rail, a base break can be generated. A base break can be divided into two different failure types: broken base and base fracture. FIG. 5 illustrates an expanded view of a rail, such as the rail 100 of FIG. 1, focusing on the base 103. FIG. 4 further illustrates a broken base defect 501 and a base fracture defect 502. The failure is typically due to a seam, segregation, or improper bearing on the rail tie. Development in the transverse direction can be relatively slow before the defect extends some distance into the rail surface. However, a complete and sudden failure may still occur with little transverse defect development. [0034] During the rail welding process, insufficient combination and fusion of the welding materials between joints, shrinkage, or fatigue cracks can cause discontinuities or cavities in the welded connection. Such welding issues are possible in both field and plant welds. Defective welds may generate in joints at the head-to-web or base-to-web connections. In some cases, defects may develop longitudinally through welded joints which may be classified as a split web. Porosity is a typical type of welding defect, usually caused by gas released from the weld pool as it solidifies.

[0035] Plant welds generally result from excessive weld material removal during the shearing process. Such removal will make the web surface flusher. Unlike field welds, excessive weld material will be present at the surface of the web-to-base joint. Both types of welds can also lead to failure at an inclined direction.

[0036] As for the third type of failure: rolling contact fatigue (RCF) is a crack-like defect which is caused by recurring loads at the wheel-rail contact area. Defect initiation is due to repeated loading of the material. Over a prolonged period RCF defects can develop into larger flaws and lead to fracture. RCF defects are the primary reason for maintenance and replacement on heavy haul railways.

[0037] Head checks, shells, flaking, and burning rails are all part of surface-initiated RCF defects. Such defects are caused by wheel-rail friction, high contact stress, or concentrated loading. However, the mechanics involving how a single crack causes the rail to break are still not clear. RCF defects are not as common as other defects, but are extremely dangerous since RCF cracks are very easily formed at the rail surface. Fracture due to a single crack can increase stress in the nearby rail, thereby increasing the risk of further breaks and disintegration of the rail. [0038] Detection of Defects

[0039] The above defects are detectable using an acoustic detection technique. Through signal processing, for example, common noise associated with an undamaged rail may be filtered out, leaving behind the sound markers correlating to rail defects. The acoustic detection technique operates on the principle of acoustic emission (AE). AE is defined as an elastic wave generated by changes in the internal structure of a material which is caused by a sudden change of internal stress or external impact. Microstructure changes are responsible for such phenomena. Changes can include crack growth in the body, sectional displacement in material, phase change, fiber breakage, and decomposition. AE technology operates differently compared to other detection techniques. First, instead of providing energy to the object during examination, AE technology receives the energy released by the material. Second, AE technology only responds to dynamic processes, or changes, in a material. The dynamic response is particularly relevant because it can be used to trace the continuous changes of the material.

[0040] FIG. 6 illustrates an example of a rail defect detection system 600 utilizing the acoustic detection technique. As illustrated in FIG. 6, the rail defect detection system 600 includes a vehicle 610 configured to operate on a rail 620, such as a train or other rolling stock. The vehicle 610 includes an engine 611, a plurality of wheels 612, subsets of which are connected to one another by an axle 613, and a rail defect detection device 614. The rail defect detection device 614 may be installed on the vehicle 610 near the rail 614, such as on the wheel 612 or the axle 613. As the vehicle 610 passes over a section of track, the rail 620 releases acoustic emissions 630 that are dependent on the structure and condition of the rail 620, the weight of the vehicle 610, etc. Because properties of the vehicle 610 do not change from track section to track section, differences in the acoustic emissions 630 provide information relating to condition of the rail 620 itself. Thus, a track section with a defect will have an acoustic signature that is appreciably different from a track section with no defect.

[0041] The rail defect detection system 600 can detect, record, and store information relating to the acoustic emissions 630 for processing in real-time or later processing off-line (for example, at a rail depot). Additionally, information relating to the acoustic emissions 630 may be fused with location data from an onboard location sensor, such as a Global Positioning Sensor (GPS), to provide defect location information.

[0042] FIG. 7 illustrates a first example of a rail defect detection device 700, such as the rail defect detection device 614 illustrated in FIG. 6. As illustrated in FIG. 7, the rail defect detection device 700 includes a processor 701, a memory 702, input/output (I/O) circuitry 703 which provides a wired connection to external elements, and wireless communication circuitry 704 which provides a wireless connection to external elements. The I/O circuitry 703 is connected to an air conduction sensor 710 (an example of a“first sensor”), a bone conduction sensor 720 (an example of a“second sensor”), and a location sensor 730, each of which may be provided separate from the rail defect detection device 700. The wireless communication circuitry 704 is connected to a remote device 740, such as a server, a database, and the like. While FIG.

illustrates various elements connected via a wire to the I/O circuitry 703 and various elements connected wirelessly to the wireless communication circuitry 704, this is illustrative and not restrictive. In some aspects of the present disclosure, a different subset of the external elements (or all of the external elements) may be connected via a wire, or a different subset of the external elements (or all of the external elements) may be connected wirelessly.

[0043] The air conduction sensor 710 may be any sensor capable of detecting acoustic signals from a rail, representative of contact between a vehicle and the rail, that have been transmitted through the air (for example, a microphone). The bone conduction sensor 720 may be any sensor capable of detecting acoustic signals from the rail that have been transmitted through a solid such as the wheels and chassis of the vehicle itself (for example, a vibration detector). The air conduction and bone conduction sensors 710 and 720 may generate respective output signals corresponding to the received acoustic signals. The location sensor 730 may operate using a satellite-based technology (such as GPS, GLONASS, Galileo, or BeiDou). As illustrated in FIG. 7, the air conduction sensor 710, the bone conduction sensor 720, and the location sensor 730 are separate from the rail defect detection device 700. In this manner, individual sensors may be located at different locations within or on the vehicle so as to maximize flexibility. For example, the air conduction sensor 710 may be located on the exterior of the vehicle whereas the bone conduction sensor 720 may be mounted on or inside the vehicle.

[0044] The rail defect detection device 700 constitutes a high-speed data acquisition system capable of up to 500,000 samples per second at 18 or 24 bits. The rail defect detection device 700 includes a signal processing algorithm (for example, in the memory 702) or signal processing circuitry (for example, in the processor 701 or in a separate processor) capable of distinguishing ambient and/or typical noise from rail defects.

[0045] In real-time processing, the rail defect detection device 700 continually samples the acoustic emissions and compares them to a reference signal that is representative of a rail with no defects. The reference signal may be stored in the memory 702 or may be stored in the remote device 740. Where there is a difference between the sampled signal and the reference signal, the rail defect detection device 700 may note the location data from the location sensor 730 and generate a marker that indicates the location of the defect and/or potential defect category.

Alternatively, the rail defect detection device 700 may compare the acoustic emissions to a reference signal that is representative of a rail with a particular type of defect, and generate the marker when the sampled signal matches the reference signal. The rail defect detection device 700 may accumulate and store data for an entire operating period of the vehicle, may store only data relating to defects such as the markers, or may store both the entire data and the marker data.

[0046] In off-line processing, the rail defect detection device 700 continually samples and stores the acoustic emissions as well as the location data from the location sensor. Thus, when the vehicle is no longer in operation, it is possible to compare the sampled data to a reference signal (for example, in a manner described above) and determine the presence and location of defects at such time.

[0047] Moreover, it is possible to select a desired level of granularity in the detector operation. For example, the rail defect detection device 700 may be configured to determine that a defect is present within a particular length of track, such as one mile, while the vehicle is operating at full speed. Thus, a lower data throughput may be utilized on high-speed runs. If a defect is detected, it is possible to conduct a comparatively low-speed run within the particular length of track to further narrow down the location of the defect.

[0048] FIG. 8 illustrates a second example of a rail defect detection device 800, such as the rail defect detection device 614 illustrated in FIG. 6. As illustrated in FIG. 8, the rail defect detection device 800 includes a processor 801, a memory 802, an air conduction sensor 803 (an example of a“first sensor”), a bone conduction sensor 804 (an example of a“second sensor”), and a location sensor 805. Various elements of the rail defect detection device 800 are connected to one another via a bus 806. [0049] The air conduction sensor 810 may be any sensor capable of detecting acoustic signals from a rail, representative of contact between a vehicle and the rail, that have been transmitted through the air (for example, a microphone). The bone conduction sensor 820 may be any sensor capable of detecting acoustic signals from the rail that have been transmitted through a solid such as the wheels and chassis of the vehicle itself (for example, a vibration detector). The air conduction and bone conduction sensors 810 and 820 may generate respective output signals corresponding to the received acoustic signals. The location sensor 830 may operate using a satellite-based technology such as GPS, Global Navigation Satellite System (GLONASS), Galileo, Quasi-Zenith Satellite System (QZSS), or BeiDou Navigation Satellite System (BDS). As illustrated in FIG. 8, the air conduction sensor 810, the bone conduction sensor 820, and the location sensor 830 are integrated with the rail defect detection device 800.

[0050] The rail defect detection device 800 constitutes a high-speed data acquisition system capable of up to 500,000 samples per second at 18 or 24 bits. The rail defect detection device 800 includes a signal processing algorithm (for example, in the memory 802) or signal processing circuitry (for example, in the processor 801 or in a separate processor) capable of distinguishing ambient and/or typical noise from rail defects. The rail defect detection device 800 may be configured to perform real-time or off-line processing in a manner similar to that described above with regard to the rail defect detection device 700.

[0051] While FIG. 7 illustrates a fully modular rail defect detection device 700 and FIG. 8 illustrates a fully integrated rail defect detection device 800, a rail defect detection device in accordance with the present disclosure may be partly modular and partly integrated. For example, the rail defect detection device 800 may connect to a remote device and include wireless communication circuitry; some of the sensors may be provided separately; and the like. [0052] FIG. 9 illustrates an exemplary rail defect detection method in accordance with various aspects of the present disclosure. This rail defect detection method may be implemented as a signal processing algorithm in the memory 702, the memory 802, or the remote device 740 described above. The rail defect detection method may also be implemented in dedicated signal processing circuitry in the processor 701, the processor 801, or the remote device 740, described above, or in another processor. In some aspects of the present disclosure, the rail defect detection method may be implemented using a combination of algorithms and circuitry.

[0053] The rail defect detection method may begin with data acquisition. As illustrated in FIG.

9, the method begins with step S901 in which a first acoustic signal is acquired and a first output signal is generated. Step 901 may be performed by the air conduction sensor 710 of FIG. 7 or the air conduction sensor 803 of FIG. 8, for example. The method further includes step S902 in which a second acoustic signal is acquired and a second output signal is generated. Step S902 may be performed by the bone conduction sensor 720 of FIG. 7 or the bone conduction sensor 804 of FIG. 8, for example. The method further includes step S903 in which a location data is acquired. Step S903 may be performed by the location sensor 730 of FIG. 7 or the location sensor 805 of FIG. 8, for example. Once the first and second output signals have been generated, at step S904 the first and second output signals are compared with a reference signal to generate a detection data.

[0054] While FIG. 9 illustrates steps S901-S904 being performed in one particular order in series, steps S901-S904 may be performed in another order in series, may be performed in parallel, or may be performed in any combination of series and parallel. For example, steps S901 and S902 may be performed initially (in series and parallel), and the location data acquisition of step S903 may not be performed until after the comparing of step S904. In any event, after the detection data has been generated, at step S905 the method correlates the detection data with the location data. For example, the detection data may indicate that a defect exists in the rail, and the method may append the detection data with the location data corresponding to the particular location at which the defect exists.

[0055] At step S906, data is stored in a memory, such as the memory 702 of FIG. 7 or the memory 802 of FIG. 8. For example, the first output signal, the second output signal, the location data, the reference signal, the detection data, or combinations or subsets thereof may be stored in the memory. The data may be stored for the entirety of the defect detection period or may be stored only when a defect or defect candidate has been detected.

[0056] The present disclosure may be implemented using hardware (such as dedicated and/or application-specific circuitry such as a Field-Programmable Gate Array or FPGA), using software, or using a combination of hardware and software. As an example of implementing the present disclosure using software, the requisite processing can be executed by installing a program in which the processing sequence is recorded in the memory of a specialized computer embedded in dedicated hardware, or can be executed by installing the program in a computer that can execute various processing.

[0057] For example, the program can be recorded on a hard disk, a solid-state drive (SSD), or a read only memory (ROM) in advance. Alternatively, the program can be temporarily or permanently stored on a removable recording medium such as a flash drive, a CD-ROM, a magnetic disk, a DVD, a Blu-Ray Disc (BD), or a semiconductor memory card.

[0058] Additionally, the program may be transferred wirelessly or by wire to the computer from a remote site or server via a network such as a Local Area Network (LAN) or the Internet. [0059] A rail defect detection device, system, or method in accordance with the present disclosure may be embodied in any one or more of the following configurations:

[0060] (1) A rail defect detection device, comprising: a first sensor configured to receive a first acoustic signal representing contact between a train and a rail, and to generate a first output signal; a second sensor configured to receive a second acoustic signal representing contact between the train and the rail, and to generate a second output signal; a location sensor configured to generate a location data; a processor configured to compare the first output signal and the second output signal with a reference signal, and to generate a detection data; and a memory configured to store at least one selected from the first output signal, the second output signal, the location data, the reference signal, or the detection data.

[0061] (2) The rail defect detection device according to (1), wherein the first sensor is an air conduction sensor.

[0062] (3) The rail defect detection device according to (1) or (2), wherein the second sensor is a bone conduction sensor.

[0063] (4) The rail defect detection device according to any one of (1) to (3), wherein the memory is configured to store the location data and at least one selected from the first output signal, the second output signal, the location data, the reference signal, or the detection data.

[0064] (5) The rail defect detection device according to any one of (1) to (4), wherein the processor is configured to determine whether a defect is present in the rail based on the detection data.

[0065] (6) The rail defect detection device according to (5), wherein, in a case where the processor determines that the defect is present in the rail, the memory stores the at least one selected from the first output signal, the second output signal, the location data, the reference signal, or the detection data.

[0066] (7) A vehicle configured to operate on a rail, comprising: an engine; a plurality of wheels; and a rail defect detection device, including: a first sensor configured to receive a first acoustic signal representing contact between the vehicle and the rail, and to generate a first output signal, a second sensor configured to receive a second acoustic signal representing contact between the vehicle and the rail, and to generate a second output signal, a location sensor configured to generate a location data, a processor configured to compare the first output signal and the second output signal with a reference signal, and to generate a detection data, and a memory configured to store at least one selected from the first output signal, the second output signal, the location data, the reference signal, or the detection data.

[0067] (8) The vehicle according to (7), wherein the first sensor is an air conduction sensor.

[0068] (9) The vehicle according to (7) or (8), wherein the second sensor is a bone conduction sensor.

[0069] (10) The vehicle according to any one of (7) to (9), wherein the rail defect detection device is mounted on or near a respective wheel of the plurality of wheels.

[0070] (11) The vehicle according to any one of (7) to (10), wherein the rail defect detection device is mounted on or near an axle associated with the plurality of wheels.

[0071] (12) The vehicle according to any one of (7) to (11), wherein the memory is configured to store the location data and at least one selected from the first output signal, the second output signal, the location data, the reference signal, or the detection data.

[0072] (13) The vehicle according to any one of (7) to (12), wherein the processor is configured to determine whether a defect is present in the rail based on the detection data. [0073] (14). The vehicle according to (13), wherein, in a case where the processor determines that the defect is present in the rail, the memory stores the at least one selected from the first output signal, the second output signal, the location data, the reference signal, or the detection data.

[0074] (16) A method of detecting a defect in a rail, comprising: receiving a first acoustic signal via a first sensor, the first acoustic signal representing contact between a train and a rail, and generating a first output signal; receiving a second acoustic signal via a second sensor, the second acoustic signal representing contact between the train and the rail, and generating a second output signal; generating a location data; comparing the first output signal and the second output signal with a reference signal, and generating a detection data; and storing at least one selected from the first output signal, the second output signal, the location data, the reference signal, or the detection data.

[0075] (17) The method according to (16), wherein the first sensor is an air conduction sensor.

[0076] (18) The method according to (16) or (17), wherein the second sensor is a bone conduction sensor.

[0077] (19) The method according to any one of (16) to (18), further comprising: determining whether a defect is present in the rail based on the detection data.

[0078] (20) The method according to (19), further comprising: in a case where it is determined that the defect is present in the rail, storing the at least one selected from the first output signal, the second output signal, the location data, the reference signal, or the detection data.

[0079] With regard to the processes, systems, methods, heuristics, etc. described herein, it should be understood that, although the steps of such processes, etc. have been described as occurring according to a certain ordered sequence, such processes could be practiced with the described steps performed in an order other than the order described herein. It further should be understood that certain steps could be performed simultaneously, that other steps could be added, or that certain steps described herein could be omitted. In other words, the descriptions of processes herein are provided for the purpose of illustrating certain aspects of the present disclosure, and should in no way be construed so as to limit the disclosure.

[0080] Accordingly, it is to be understood that the above description is intended to be illustrative and not restrictive. Many embodiments and applications other than the examples provided would be apparent upon reading the above description. The scope should be determined, not with reference to the above description, but should instead be determined with reference to the appended claims, along with the full scope of equivalents to which such claims are entitled. It is anticipated and intended that future developments will occur in the technologies discussed herein, and that the disclosed systems and methods will be incorporated into such future embodiments. In sum, it should be understood that the application is capable of modification and variation.