Metal body monitoring device and metal body monitoring method

Abstract

To allow discrimination of specific sites on a metal body in a metal body monitoring environment where a non-contact magnetic sensor part relatively moves on the metal body.SOLUTION: A metal body monitoring device comprises a magnetic detector, a distance detector, and a processor. The magnetic detector includes a magnetic sensor part which is provided on a moving body relatively moving on the metal body and detects a generated leakage magnetic field in a non-contact manner. The distance detector is provided on the moving body and detects a travelling distance of the moving body relative to the metal body. The processor converts, on the basis of travelling distances at time points detected by the distance detector, first data indicative of time sequence of detection signal intensity from the magnetic detector into second data indicative of relations between the travelling distance and the detection signal intensity. The processor extracts a spectral response in a wave number space identified from the second data and outputs monitoring information which is information based on the extracted spectral response.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates generally to monitoring metallic objects. [Background technology]

[0002] An example of a metal body is a wire rope. As an example of a wire rope monitoring device, a wire rope deterioration determination device is described in Patent Document 1. Patent Document 1 states that "the wire rope deterioration determination device includes a detector 30 that detects wire rope deterioration by a leakage magnetic flux method, a data input unit 31 that obtains measurement data from the detector 30, a noise component removal means that removes noise components from the data input unit 31, and a waveform processing means that extracts data that is determined to have a high correlation with the deterioration factors of the wire rope." [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent Publication No. 2022-52864 Summary of the Invention [Problem to be solved by the invention]

[0004] Patent Document 1 describes a wire rope deterioration determination device that detects deterioration of the wire rope using a leakage magnetic flux method.

[0005] In this device, the signal waveform of the detection signal can change depending on the speed at which the wire rope passes through the detector. Also, in this device, noise occurs due to the environment or condition in monitoring the wire rope (for example, offset drift due to positional fluctuations of the detector, external noise, etc.), and this noise affects the signal waveform of the detection signal. For this reason, it is difficult to distinguish, from the detection signal, a peculiar portion that is different from the healthy portion of the wire rope (specifically, whether or not the peculiar portion is a damaged portion).

[0006] Patent Document 1 does not describe how to identify peculiar points on a wire rope or the means for doing so.

[0007] Such a problem may occur when the metal object is a metal object other than a wire rope, and may occur in any metal object monitoring environment in which a non-contact magnetic sensor unit (e.g., a detector) moves relatively on the metal object.

[0008] An object of the present invention is to enable discrimination of specific locations on a metal object being monitored in such a metal object monitoring environment. [Means for solving the problem]

[0009] In order to solve the above problem, one representative metal object monitoring device of the present invention includes a magnetic detection device, a distance detection device, and a processing device connected to the magnetic detection device and the distance detection device. The magnetic detection device includes a magnetic sensor unit, which is provided on a moving object that moves relatively over the metal object and detects the generated leakage magnetic field in a non-contact manner. The distance detection device is provided on the moving object and detects the moving distance of the moving object relative to the metal object. The processing device converts first data representing a time series of the detection signal strength from the magnetic detection device into second data representing the relationship between the moving distance and the detection signal strength based on the moving distance at each time point detected by the distance detection device. The processing device extracts a spectral response in wave number space specified from the second data, and outputs monitoring information that is information based on the extracted spectral response. Effect of the Invention

[0010] According to the present invention, it is possible to distinguish a singular portion of a metal body in a metal body monitoring environment in which a magnetic sensor unit that does not come into contact with the metal body moves relatively on the metal body. Problems, configurations and effects other than those described above will become apparent from the following description of the embodiments. [Brief description of the drawings]

[0011] [Figure 1] FIG. 1 is a schematic diagram of a metal object monitoring device according to a first embodiment of the present invention. [Diagram 2] 1 is a perspective view of a magnetic detection device according to a first embodiment. [Diagram 3] FIG. 2 is a bottom view of the magnetic detection device according to the first embodiment. [Figure 4] FIG. 1 is a partially cutaway plan view of a magnetic detection device according to a first embodiment. [Diagram 5] 5A to 5C are schematic diagrams illustrating an operating state of the magnetic sensor unit of the first embodiment. [Figure 6] 5A to 5C are schematic diagrams showing other operating states of the magnetic sensor unit of the first embodiment. [Figure 7A] FIG. 2 is an explanatory diagram of processes 1 to 3 relating to the monitoring information extraction and analysis process to which continuous wavelet analysis is applied in the metal object monitoring device according to the first embodiment of the present invention. [Figure 7B] FIG. 11 is an explanatory diagram of processes 4 to 6 relating to the monitoring information extraction and analysis process to which continuous wavelet analysis is applied in the metal object monitoring device according to the first embodiment of the present invention. [Figure 7C] FIG. 11 is an explanatory diagram of process 5 relating to the monitoring information extraction and analysis process when a short-time Fourier transform is used in the metal object monitoring device according to the first embodiment of the present invention. [Figure 8A] FIG. 7B is an explanatory diagram relating to the interpolation process of the distance information conversion data in FIG. 7A in the metal object monitoring device according to the first embodiment of the present invention. [Figure 8B] FIG. 7B is an explanatory diagram relating to the interpolation process of the distance information conversion data in FIG. 7A in the metal object monitoring device according to the first embodiment of the present invention. [Figure 9] FIG. 7C is an explanatory diagram of hierarchical approximation by performing discrete wavelet processing in process 5 in FIG. 7B in the metal object monitoring device according to the first embodiment of the present invention. [Figure 10] FIG. 7C is an explanatory diagram of hierarchical decomposition by performing discrete wavelet processing in process 5 in FIG. 7B in the metal object monitoring device according to the first embodiment of the present invention. [Figure 11] FIG. 1 is a block diagram of a metal object monitoring device according to a first embodiment. [Figure 12] FIG. 2 is a block diagram of a detection unit in the processing device. [Figure 13] 10 is a flowchart of a metal object monitoring processing program executed by the evaluation device. [Figure 14] FIG. 11 is a bottom view of the magnetic detection device according to the second embodiment. [Figure 15] FIG. 11 is a partially cutaway plan view of a magnetic detection device according to a second embodiment. [Figure 16] FIG. 11 is a block diagram of a metal object monitoring device according to a second embodiment. [Figure 17] 1A and 1B are diagrams showing examples of positions of singular points present on a metal body and contour lines representing signal intensity distribution at those positions; DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0012] Hereinafter, some embodiments will be described with reference to the drawings. [First embodiment] <External Configuration of First Embodiment>

[0013] FIG. 1 is a schematic diagram of a metal object monitoring device according to a first embodiment of the present invention.

[0014] 1, the metal object monitoring device 1 includes a magnetic detection device 2, a distance detection device 3, a processing device 4, a power supply 88, and a connection cable 60. The metal object monitoring device 1 is mounted on a moving object 100. There is a metal object 200 as an inspection object (monitoring object), and the moving object 100 includes wheels 300 for traveling on the metal object 200, and the wheels 300 rotate while contacting a traveling surface 200a.

[0015] The magnetic detection device 2 is installed at a position facing the traveling surface 200a of the metal body 200, and the distance detection device 3, the processing device 4, and the power supply 88 are installed inside the moving body 100. The power supply 88 supplies driving current to the magnetic detection device 2, the distance detection device 3, and the processing device 4, and operates the magnetic detection device 2, the distance detection device 3, and the processing device 4.

[0016] When the moving body 100 travels on the metal body 200, the magnetic detection device 2 detects the state of the metal body 200, and a signal representing the detection result is sent to the processing device 4 via the connection cable 60. In addition, the axle 400 of the wheel 300 of the moving body 100 is connected to the distance detection device 3 via the rotation drive mechanism 500, and the operation of the rotation drive mechanism 500 is detected by the distance detection device. Then, the processing device 4 collects each signal from the magnetic detection device 2 and the distance detection device 3, and performs processing such as analysis and display using each signal. In other words, the processing device 4 monitors the state of the metal body 200. Note that, if the moving body 100 is equipped with an AC power supply, the power supply 88 may be a stabilized power supply circuit driven by the AC power supply. If the AC power supply is not available, the power supply 88 may be an uninterruptible power supply device with a built-in battery.

[0017] The structure of the magnetic detection device 2 will be described with reference to FIG.

[0018] FIG. 2 is a perspective view of the magnetic detection device 2. As shown in FIG. 2, the magnetic detection device 2 has an integral structure in which an upper housing 26 (an example of a second housing) and a lower housing 20 (an example of a first housing) are fixed to each other, and a flange 25 is provided on the upper side of the upper housing 26. The upper housing 26 and the lower housing 20 are formed in a rectangular parallelepiped shape, and the lower surface of the upper housing 26 and the upper surface of the lower housing 20 are joined together. The flange 25, which is formed in a rectangular shape, is joined and fixed to the upper surface of the upper housing 26. A connector 28 is provided on one side of the upper housing 26, and a connector 62 is also provided on one end of a connection cable 60. The connector 28 and the connector 62 can be connected by fitting them together, and after the connection, the magnetic detection device 2 and the processing device 4 can communicate with each other through the connection cable 60. The connector 28 and the connector 62 have a dustproof and waterproof structure, and prevent foreign matter such as dust and water from entering through the gap when the connectors 28 and 62 are connected to each other, which can cause a breakdown of the magnetic detection device 2 or a connection failure of the connection cable 60. Connector 28 is preferably a through-type connector that can be inserted into one side of the magnetic detection device 2 to be installed and tightened to prevent it from falling off or loosening due to vibration and that can prevent dust and water from entering, but a connector other than a through-type may be used as long as it has sufficient dustproof and waterproof functions in the installation environment of the magnetic detection device 2.

[0019] Through holes 25a are formed at the four corners of the flange. The moving body 100 (see FIG. 1) also has a screw hole (not shown) at a position facing the through hole 25a at the installation location of the magnetic detection device 2. A bolt (not shown) is inserted into the through hole 25a via a washer (not shown), and the bolt is fastened to a screw hole provided in the moving body 100, thereby fixing the magnetic detection device 2 at a predetermined position of the moving body 100. The lower housing 20 incorporates a magnetic sensor unit 21 for detecting the state of the metal body 200. The upper housing 26 incorporates a preamplifier unit 210 for amplifying a magnetic signal detected by the magnetic sensor unit 21. The magnetic sensor unit 21 and the preamplifier unit 210 will be described in detail later.

[0020] When the magnetic detection device 2 is installed at a predetermined position on the moving body 100 and used, measures against vibration and impact caused by the rocking motion of the moving body 100 when it moves on the metal body 200 are necessary. Therefore, the internal space of the upper housing 26 and the lower housing 20 is filled with a filler (not shown) having insulating and non-magnetic properties, and is molded with resin. With this structure, the magnetic sensor unit 21 and the preamplifier unit 210 are firmly held inside the lower housing 20 and the upper housing 26, and damage to the magnetic sensor unit 21 and the preamplifier unit 210 caused by rocking motion accompanying the movement of the moving body 100 and deviation of the detection position of the magnetic sensor unit 21 can be prevented. In the example shown in FIG. 2, the upper housing 26 and the lower housing 20 are rectangular parallelepiped in shape, but these shapes can also be other shapes such as a cube, a cylinder, or a prism, depending on conditions such as the installation space with respect to the moving body 100 to be used.

[0021] The configurations of the magnetic sensor unit 21 and the preamplifier unit 210 in the magnetic detection device 2 will be described with reference to FIG.

[0022] As shown in Fig. 3, the magnetic sensor unit 21 is composed of an oscillator coil 5A, an oscillator coil 5B, and a receiver coil 6, each of which is manufactured by winding a coated copper wire. The receiver coil 6 is located between the oscillator coils 5A and 5B, and the coils are arranged in a parallel relationship to the direction of movement of the moving body 100 moving on the metal body 200. An AC current with a predetermined oscillation frequency f (predetermined frequency) is supplied to the oscillator coils 5A and 5B from the processing device 4 (see Fig. 1) via a connection cable 60. As a result, an AC magnetic field is generated from each of the oscillator coils 5A and 5B, which excites the metal body 200. An induced voltage is generated in the receiver coil 6 by the magnetic flux generated from the excited metal body 200.

[0023] FIG. 4 is a partially cutaway plan view of the magnetic detection device 2, showing the layout of the preamplifier section 210 inside the upper housing .

[0024] In Fig. 4, the center of the flange 25 is cut away to expose the inside of the upper housing. The preamplifier section 210 is made up of a printed circuit board 210a on which the amplification filter circuit 22 is mounted. The amplification filter circuit 22 amplifies and filters the induced voltage generated in the receiving coil 6, and transmits the result to the processing device 4 via the connection cable 60 (see Fig. 1). The processing device 4 analyzes the received signal and detects the magnetic signal generated from the metal body 200.

[0025] The upper housing 26 incorporating the preamplifier section 210 is made of a metal such as aluminum that functions as an electromagnetic shield. By making the upper housing 26 out of a metal housing, it is possible to shield the electromagnetic field generated by the preamplifier section 210 and suppress electromagnetic waves from entering the preamplifier section 210 from the outside of the usage environment. In addition, if the flange 25 is provided on the upper housing 26 by metal cutting during the manufacturing of the upper housing 26, the flange 25 and the upper housing 26 become the same, so the number of components of the magnetic detection device 2 is reduced and the strength is improved. Furthermore, when aluminum is used for the upper housing 26, it is more preferable to use aluminum that has been anodized to form an oxide film on the aluminum surface, since this can improve the surface hardness and corrosion resistance and provide insulation.

[0026] The lower housing 20 is made of a non-magnetic material. This is because the lower housing 20 contains the oscillator coil 5A and oscillator coil 5B that generate an AC magnetic field, and the receiver coil 6 that detects changes in the magnetic field generated by the metal body. In addition, since the magnetic detection device 2 is installed outside the moving body 100 and is used while the moving body 100 is moving, it is preferable to use a material with excellent toughness and corrosion resistance, such as fiber reinforced resin, for the lower housing 20. For example, when using glass fiber reinforced plastic such as GFRP, it is better to apply a coating film treatment to the surface of the lower housing using a paint made by combining glass fiber with a mixture of liquid unsaturated polyester resin and a hardener. This coating film treatment forms a coating waterproof layer, which further improves the weather resistance of the lower housing.

[0027] The lower housing 20 is provided with a screw-in insert nut (not shown) on the side of the contact surface with the upper housing 26, and is fixed to the upper housing 26 by screwing. The upper housing 26 and the lower housing 20 are bonded at their contact surfaces with a silicone contact agent that has excellent weather resistance, and the gaps are sealed to form an integrated unit.

[0028] The connection cable 60 connecting the magnetic detection device 2 and the processing device 4 includes a power line of the preamplifier unit 210, an output signal line of the receiving coil via the amplification filter circuit 22, and an input signal line of the excitation signal to the oscillation coil 5A and the oscillation coil 5B. If the connection cable 60 is subjected to noise due to electromagnetic waves flying through space, the detection of the magnetic signal from the metal body 200 is affected. For this reason, it is preferable to use a multi-pair shielded cable with excellent noise resistance such as a twisted pair shielded wire for the connection cable 60. In addition, as a countermeasure against crosstalk in the connection cable 60, the connection cable 60 may be divided into two cables. Specifically, one cable may be a multi-pair shielded cable including a power line of the preamplifier unit 210 and an output signal line of the receiving coil from the amplification filter circuit. In addition, the other cable may be another multi-pair shielded cable including an input signal line of the excitation signal to the oscillation coil 5A and the oscillation coil 5B.

[0029] The connection cable 60 is fixed to the underside of the moving body 100 facing the metal body 200, and is connected to the processing device 4 through an inlet provided in the moving body 100. The connection cable 60 is firmly fixed and held using a fastener such as a cable tie so that the cable does not become loose around the underside of the moving body 100, in order to prevent interference with the movement of the moving body 100 and noise generation due to the vibration of the connection cable. In addition, when the connection cable 60 is fixed and held, it is preferable to design the wiring path so that the length of the connection cable is as short as possible. The shorter the wiring path, the more effectively the risk of noise being mixed into the detection signal from the magnetic detection device 2 via the connection cable 60 can be avoided.

[0030] The distance detection device 3 that detects the moving distance of the moving body 100 will be described. The distance detection device 3 is a rotary encoder, and a pulse signal is generated by the rotation of the rotary encoder's rotating shaft. The amount of movement associated with the rotation of the rotating shaft can be calculated by counting this pulse signal. Using the function of this rotary encoder, the rotation of the axle 400 of the wheel 300 of the moving body 100 is transmitted to the rotating shaft of the rotary encoder via the rotary drive mechanism 500. This rotary drive mechanism 500 is composed of pulleys and a timing belt attached to the axle 400 and the rotating shaft of the rotary encoder. In other words, when the moving body 100 moves, the axle 400 rotates in response to the operation of the wheel, and the movement is transmitted to the rotary drive mechanism 500, causing the rotating shaft of the rotary encoder to rotate at the same time.

[0031] The pulse signal output from the rotary encoder is input to the processing device 4 via the connection cable 61. The processing device 4 inputs this pulse signal in a state synchronized with the output signal from the magnetic detection device 2. The connection cable 61 may be a multi-pair shielded cable with excellent noise resistance, such as a twisted pair shielded wire, like the connection cable 60. The above-mentioned rotary encoder is of an incremental type that performs counting measurement by accumulating pulses generated corresponding to rotations from the measurement start point, but it is also possible to use an absolute type rotary encoder that measures the absolute angular position of the rotary encoder's rotation shaft. Furthermore, there are various types of rotary encoders, including an optical type that shines light onto an internal slit disk to obtain rotational position information as an optical pulse signal that passes through the slit disk; a magnetic type that obtains rotational position information from a rotating disk with a magnetic pattern formed on it and outputs a pulse signal from periodic changes in a magnetic field; an electrostatic type that is composed of a transmitter, receiver, and rotor fixed inside the encoder and outputs distance information based on changes in capacitance associated with the rotation of the rotor; and a contact type in which electrical contacts inside the encoder come into contact as the rotating shaft rotates, generating an electrical signal that is converted into the amount of rotation. Any of these types may be used. <Principle of detecting specific points on metal objects>

[0032] 5 is a schematic diagram showing the operating state of this embodiment. When current is supplied from the processing device 4 (see FIG. 1), the oscillator coil 5A and the oscillator coil 5B generate a synchronized, phase-inverted AC magnetic field. Specifically, the oscillator coil 5A and the oscillator coil 5B are connected in series (or in parallel) at the start or end of the insulated copper wire, and when an AC voltage is applied from the processing device 4, an AC magnetic field is generated.

[0033] When the magnetic fluxes ΦA and ΦB generated from the oscillator coils 5A and 5B propagate to the travel surface 200a (see FIG. 1) of the metal body 200, a magnetic flux flow occurs on the travel surface 200a. Here, the moving direction of the moving body 100, which is the moving direction of the magnetic detection device and the distance moving device, is defined as the "x direction". Moreover, the direction in which the magnetic flux is detected by the receiving coil 6, i.e., the direction of separation between the metal body 200 and the magnetic detection device 2, is defined as the "y direction".

[0034] FIG. 5 shows an example of a case where there is no change in the state of the metal body 200 near the oscillator coil 5A, the oscillator coil 5B, and the receiver coil 6. Here, the case where there is no change in the state of the metal body means a case where there is no damage due to defects such as cracks, or a case where there is no structural change such as a connection between metal bodies (for example, a structure that is not damaged such as a joint, welding, or bolt installation). The components of the magnetic flux linking the receiver coil 6 are offset because the magnetic fluxes ΦA and ΦB are in opposite directions, and depend on the strength balance of the magnetic fluxes ΦA and ΦB. Therefore, when there is no change in the state of the metal body, the magnetic flux linking the receiver coil 6 becomes almost zero, and the induced voltage of the receiver coil 6 also becomes almost zero.

[0035] FIG. 6 is a schematic diagram showing another operation of this embodiment.

[0036] 6 shows an example in which a singular point 202 is present in the vicinity of the oscillator coil 5A, the oscillator coil 5B, and the receiver coil 6. Here, the singular point 202 refers to a point having magnetic properties different from those of a normal metal body 200. Specifically, the singular point 202 can be broadly classified into a "damaged point" and a "structural point." In other words, the singular point 202 is a damaged point or a structural point.

[0037] The meanings of "x direction" and "y direction" in Fig. 6 are the same as those in Fig. 5. In the illustrated example, the flow of magnetic flux generated on the running surface 200a of the metal body 200 by the oscillator coils 5A and 5B is disturbed, causing leakage of magnetic flux from the running surface 200a. Therefore, when the receiving coil 6 passes over the singular point 202, the change in induced voltage of the receiving coil 6 is significantly larger than the change in induced voltage in the case shown in Fig. 5.

[0038] The metal body monitoring device 1 in this embodiment detects the generated leakage magnetic field based on the fact that the flow of magnetic flux generated in the metal body 200, which is the inspection target, changes in the vicinity of the singular point 202. As an analytical model of this leakage magnetic field, the leakage magnetic field generated in space can be expressed based on a dipole model. Here, as an example, let us assume that, in this model, the singular point 202 is a structure that is a joint with a gap in the metal body 200. In the leakage magnetic field component generated from the y direction of the metal body 200, a bipolar magnetic flux change appears having extreme values ​​(maximum and minimum values) in the x direction, with the center position of the joint as an inflection point when the mobile body 100 moves.

[0039] In the above example, the case where the singular location is a structure that is a joint with a gap in the metal body 200 has been described, but the singular location 202 can also be detected in the same way when it is damaged. When a crack that is damage is present on the running surface 200a of the metal body 200, the gap at the damaged location differs significantly from the magnetic permeability of the metal body 200, so that magnetic resistance occurs and the flow of magnetic flux is disturbed. Due to this disturbance in the flow of magnetic flux, the magnetic flux flowing on the running surface 200a bypasses the crack, and leakage magnetic flux is generated from the running surface 200a. Therefore, when the magnetic detection device 2 passes above the damaged location, the strength balance of the magnetic fluxes ΦA and ΦB (see FIG. 6) in the metal body 200 is disturbed, as in the case of detecting the above-mentioned structure, and the magnetic detection device 2 can detect the presence of the damaged location. <Metal object monitoring>

[0040] Monitoring of metal object 200 by metal object monitoring device 1 will be described with reference to Figs. 7A, 7B, and 7C.

[0041] The detection signal acquired by the magnetic detection device 2 is time series data 111 that represents the time series of the detection signal intensity (Process 1 in FIG. 7A). Therefore, the response waveform of the detection signal changes depending on the moving speed of the moving body 100, and is moving speed dependent. Therefore, a singular point where damage or a structure exists does not always have the same signal response, and even if the signal is from a similar singular point, it is difficult to intuitively grasp the response from the signal waveform. In addition, when noise is mixed into the detection signal, the setting of the filter applied to remove noise needs to be changed according to the moving speed, which makes the application complicated. For example, the waveform 971 indicates that the response time is relatively long when the moving speed is relatively low, and the waveform 972 indicates that the response time is relatively short when the moving speed is relatively high.

[0042] Therefore, the detection signal from the magnetic detection device 2 is captured by the processing device 4 in synchronization with the output signal from the distance detection device 3, and the processing device 4 converts the time series data 111 of the detection signal into data 222 indicating the change in detection signal strength with respect to the moving distance (processing 2 in FIG. 7A). The sampling of this converted data 222 is at equal intervals if the moving speed of the moving body 100 is constant, but in reality, the movement of the moving body 100 is accelerated and decelerated, so the moving speed is not always constant, and therefore the sampling is not at equal intervals.

[0043] Therefore, the processing device 4 converts the data 222 into data 333 with equal intervals of sampling by interpolating the sampling of the converted data 222 obtained in process 2 in Fig. 7A (process 3 in Fig. 7A). The sampling interval in the data 333 may be a set value interval such as equal intervals of 1 mm, and the set value may be a value that matches the resolution required for monitoring the metal object to be inspected.

[0044] An example of sampling conversion accompanying the interpolation of the detection signal with respect to the moving distance will be described with reference to FIG.

[0045] In process 2, the processing device 4 assigns an ID to each moving distance from the signals acquired from the magnetic detection device 2 and the distance detection device 3, and stores data including the ID, the moving distance, and the detection signal strength for the moving distance. As shown in Fig. 8A, in this stored data, the distance intervals are not equal because they depend on the moving speed of the moving object 100.

[0046] Therefore, as shown in FIG. 8B, in process 3, the processing device 4 calculates the detection signal strength of the distance by interpolation (for example, linear interpolation) in accordance with the desired sampling interval (for example, the sampling interval represented by a set value). After calculation, the processing device 4 stores data on the detection signal strength for the uniform sampling movement distance with the interpolation process ID. FIG. 8B shows an example where sampling is performed at equal intervals of a distance of 1 mm. In this case, in order to calculate the detection signal strength for the distance of 1 mm shown in FIG. 8B from the stored data shown in FIG. 8A, it is obtained by linearly interpolating data on the detection signal strength between two points at distances of 0.5 mm and 1.3 mm which sandwich the distance of 1 mm. This linear interpolation is performed by linearly interpolating data on the detection signal strength between two points (X i ,Y i ) and (X i+1 ,Y i+1 ) to express the approximation of function Y for any point X as a linear function of X, which is a line connecting two points, a =Y i +(Y i+1 -Y i )*(X a -X i ) / (X i+1 -X i ) where X i ≦X a ≦X i+1 For example, the data when the distance is 1 mm shown in FIG. 8B (X a (=1), Y a ), the data at a distance of 0.5 mm shown in FIG. 8A (X i (=0.5), Y i (=1.1)) and the data when the distance is 1.3 mm (X i+1 (=1.3),Y i+1(=1.2)) and from the above formula, Y becomes 1.1625. Similarly, data at other distances (for example, a distance of 2 mm) is continuously calculated and processed within the processing device 4, and data on the detection signal intensity at equal sampling intervals of 1 mm of moving distance is stored. Note that, although an example of intervals of 1 mm has been given in the explanation, the distance interval in the interpolation process can be set to any value by the processing device 4.

[0047] Since the data 333 obtained in the process 3 in FIG. 7A is uniformly sampled data, a spatial filter can be applied to the detection signal (process 4 in FIG. 7B). By using this spatial filter, it is possible to extract only the signal components necessary for extracting the singular part. For example, a signal change for a distance larger than the size of the magnetic detection device 2 that detects the signal, or a signal change for a distance smaller than the size of the receiving coil 6 built in the magnetic detection device 2, can be regarded as electrical noise caused by the oscillation of the moving body 100 or disturbance during measurement. Therefore, the processing device 4 performs spatial filtering using a desired band pass filter 444 consisting of a high pass filter and a low pass filter. This process 4 can remove offset fluctuations and the like from the detection signal, resulting in cleansed data 555. The band pass filter 444 used in the process 4 in FIG. 7B is shown as an example in which the detection signal components for a distance range of 20 mm to 1 m from the cutoff spatial frequency are extracted. The cutoff spatial frequency can be freely set according to the metal object to be inspected. In the spatial filtering process in process 4, the data 333 represents the change in detection signal strength relative to the moving distance, so that the detection signal can be handled without being affected at all by the moving speed of the moving object 100.

[0048] The detection signal data 555 cleansed by the process 4 is subjected to extraction and analysis of the spectral response of the detection signal in the selected inspection section 666 by the processing device 4 (process 5 in FIG. 7B). The processing device 4 performs continuous wavelet analysis on the spectral response of the inspection section 666 selected in the process 5. Since the singular portion of the metal body 200 does not occur continuously with periodicity, the detection signal does not occur as a periodic change, but is observed as a sudden change. Since the area when cutting out the detection signal on the moving distance area is variable in this continuous wavelet analysis, it is possible to process a long analysis area for the gradual fluctuation component of the detection signal and a short analysis area for the fine fluctuation component of the detection signal. Therefore, it is possible to effectively grasp the non-stationary or transient fluctuation characteristics of the detection signal generated at the singular portion. In the continuous wavelet analysis according to the process 5 in FIG. 7B shown as an example for explanation, Ω represents the spatial frequency resolution defined by the wavelet function used, and Δ represents the distance resolution defined by the wavelet function used.

[0049] In the continuous wavelet analysis, the processing device 4 converts the detection signal (for the sake of explanation, g(t)) that has been data cleansed in the processing device 4 into a wavelet function (ψ a,b (t)), a continuous wavelet transform T(a,b) is performed using convolution integral. This continuous wavelet transform T(a,b) is expressed by the following [Equation 1].

number

[0050] The continuous wavelet function is expressed by the following [Equation 2].

number

[0051] Note that the following part of [Equation 1] of the continuous wavelet transform, [Equation 3], is the complex conjugate of the continuous wavelet function, and ψ represents the base of the wavelet function called the mother wavelet.

number

[0052] From T(a,b), a scale parameter a having information related to spatial frequency and a shift parameter b having information related to moving distance can be obtained, and the magnitude of the signal component at each spatial frequency for each position of the moving distance can be known in the data-cleansed detection signal data 555. Representative continuous wavelet functions include the Mexican hat function, the Meyer function, the Morlet function, and the Symlet function, and any of these functions can be used depending on the response of the metal object to be inspected. For example, when the Mexican hat function is used as the continuous wavelet function, the Mexican hat function has a shape obtained by second-order differentiation of a Gaussian function, and the mother wavelet ψ is expressed by the following [Equation 4].

number

[0053] In combination, the wavelet function is expressed as follows [Equation 5].

number

[0054] In addition to the above functions, the continuous wavelet function can have any waveform shape. If the shape of the response waveform to be obtained from the metal body 200 is known in advance, a wavelet function with a shape similar to that waveform may be created and wavelet transformation may be performed by the processing device 4. In the continuous wavelet analysis, two parameters, a and b, are defined and processing is performed. a is a coefficient for the expansion / contraction operation of the wavelet function, and when the value is increased, the wavelet function is expanded in the distance axis direction, and when the value is decreased, the wavelet function is contracted in the distance axis direction. In addition, b is a coefficient for shifting the wavelet function in the distance axis direction. In the continuous wavelet analysis (processing 5 in FIG. 7B) shown as an example for explanation, an image of the expansion / contraction operation of the wavelet function is described using an example in which the parameter a is changed to large, medium, and small (a1, a2, a3).

[0055] Based on the information obtained by the wavelet analysis in process 5, the processing device 4 performs a process of displaying a color contour showing a signal intensity bar of the detection signal with the vertical axis being the spatial frequency and the horizontal axis being the moving distance of the moving body 100 (process 6 in FIG. 7B). Since the spatial frequency components of the detection signal differ depending on the type of the peculiar place, it is possible to monitor including the peculiar place information from the spectral response (pattern, spatial frequency range in which the signal occurs, etc.) at the peculiar place extracted by the color contour display. This color contour display makes it possible to visualize the peculiar place by using the spectral response in wave number space of the detection signal data 555 cleansed by the spatial filter (band pass filter 444), which is also effective in terms of usability. For example, since a structure exists in a relatively wide area, it shows a spectral response in which the signal intensity increases in the low spatial frequency range (see reference numeral 89). On the other hand, since damage such as a crack exists locally, it shows a spectral response in the high spatial frequency range (see reference numeral 88). Furthermore, when the metal object being inspected is infrastructure equipment, while joints such as welds and structures for maintaining the equipment are present at specific intervals, abnormal parts of the metal object due to damage are likely to occur irregularly. Therefore, it is possible to identify (discriminate) structures and damage from differences in spectral response in wavenumber space and the regularity of response patterns occurring in the inspection section.

[0056] Part of the processing of the metal object monitoring described with reference to Figures 7A and 7B may be a different processing. The detection signal from the magnetic detection device 2 acquired by the metal object monitoring device 1 is data cleansed by spatial filter processing in processing 4, but there are cases where observation noise originating from the device or the usage environment cannot be efficiently removed. In this case, it is necessary to take appropriate measures against the noise contained in the detection signal after processing 4. As a measure for this, before performing the continuous wavelet analysis performed in processing 5 in Figure 7B, the processing device 4 separates the detection signal in the form of a linear combination of different resolution components by discrete wavelet transform (Figure 9).

[0057] In this discrete wavelet transform, the scale parameter a in the continuous wavelet transform is 2 j and the shift parameter b is 2 j The process of binary division is performed with k as the input. In this binary division process, the discrete wavelet function is expressed by the following [Equation 6].

number

[0058] The j shown in the discrete wavelet function is called the level, and represents a doubling of the expansion or contraction. Note that j and k are integers. The detection signal (which for the sake of explanation is assumed to be g(t)) from the magnetic detection device 2, which has been data cleansed by spatial filtering in process 4, can be expanded in a series based on the discrete wavelet function, and can be separated as the value of j increases. Series expansion refers to the process of separating signals, and the detection signal is expressed by the following [Equation 7].

number

[0059] The following [Equation 8] in the series expansion ([Equation 7]) is the discrete wavelet coefficient.

number

[0060] The discrete wavelet transform S(j,k), which has a similar format to the continuous wavelet processing, is expressed by the following [Equation 9].

number

[0061] This series expansion corresponds to approximation processing using a linear combination of wavelet functions, and the approximation accuracy of the detection signal g(t) using this approximation processing depends on the level, and the larger the level value, the coarser the approximation becomes. In other words, the approximation function of the level j of the signal g(t) is expressed as a series as shown in [Equation 10] below. A level of 0 indicates the most accurate detection signal g(t).

number

[0062] The detection signal g(t) is a continuous signal, and N values ​​(a1...a) are obtained at regular intervals (e.g., 1 mm intervals). N ) where the number of data N is a power of 2 when performing discrete wavelet processing, and N=2 n The approximation of the detection signal g(t) is performed hierarchically, and the flow is explained in FIG. 9. For the sake of explanation, FIG. 9 assumes that the number of data N when the detection signal g(t) is level 0 is 8 (=2 3 ) is used as an example of hierarchical approximation. This hierarchical approximation is a process in which eight pieces of data (a1...a8) are replaced with the average value of every two consecutive pieces of data. In the first approximation, the eight pieces of data (a1...a8) are replaced with four pieces of data ((a1+a2) / 2, (a3+a4) / 2, (a5+a6) / 2, (a7+a8) / 2). This means that a similar process is then performed in which the replaced four pieces of data are replaced with the average value of every two consecutive pieces of data.

[0063] When performing this hierarchical approximation, the detection signal g(t) is decomposed hierarchically by calculating data h(t) obtained by subtracting data before and after the approximation. Based on the example shown in FIG. 9, hierarchical decomposition is explained in FIG. 10. Data g0(t) at level 0 is obtained from approximate data g1(t) to obtain h1(t). Next, data g1(t) at level 1 can be decomposed to h2(t). Similarly, at level 2, g0(t) is decomposed to g3(t) and h3(t). Here, the original data g0(t) can be reproduced by the sum of g3(t), h1(t), h2(t), and h3(t). Therefore, the discrete wavelet coefficients of the detection signal g(t) are calculated under the conditions for each level value within the desired range, and the calculated discrete wavelet coefficients are smoothed by a certain threshold T to perform noise removal. There are hard threshold processing and soft threshold processing for the threshold processing performed in this noise removal. Hard thresholding is performed on the wavelet coefficients (see Equation 11 below).

number

[0064] When hard thresholding is performed, a decision is made as to whether the discrete wavelet coefficients should be left as they are or removed. On the other hand, soft thresholding considers that the discrete wavelet coefficients contain both signal and noise, and removes the noise from all discrete wavelet coefficients to separate the signal. This soft thresholding takes the form of wavelet coefficients (see below [Equation 12]).

number

[0065] Here, all discrete wavelet coefficients less than the threshold T are set to zero, and all discrete wavelet coefficients with magnitudes equal to or greater than the threshold are reduced toward zero by T. Note that the thresholding process is carried out on the detection signal g j You can choose the preferred one according to (t). A universal threshold T is used for threshold processing, and the threshold at level j is as shown in the following [Equation 13].

number

[0066] where n j is the length (number) of discrete wavelet coefficients at level j, and σ j is the target detection signal g j is the standard deviation of the noise contained in (t). In reality, σ j Since the value of is unknown, the median value of the absolute deviation of the discrete wavelet coefficients at the minimum scale is divided by 0.6745 to estimate the standard deviation, and a value adjusted to the standard deviation of the Gaussian distribution is used. Note that in addition to the above-mentioned method using a universal threshold, threshold processing can also be performed using the mini-max method, the SURE method, the HYBRID method, the cross-validation method, the Lorenz method, the Bayesian approach, and other methods, and any of these may be used. As described above, the discrete wavelet coefficients obtained by the discrete wavelet transform are thresholded at each level j according to the threshold, and the detection signal g is obtained by the inverse discrete wavelet transform. j (t) is reconstructed. The reconstructed detection signal g j (t) is subjected to a continuous wavelet transform in process 5 shown in FIG. 7B, and a spectral response in wavenumber space is output from the continuous wavelet transformed data by a color contour display shown in process 6.

[0067] In addition, in metal object monitoring, process 5 may be process 5 shown in FIG. 7C. This can be applied when the detection signal constantly shows periodic fluctuations and a specific location in the fluctuation is detected. In this process, instead of the continuous wavelet analysis performed in process 5 in FIG. 7B, the processing device 4 performs short-time Fourier transform analysis of a predetermined section 1111 set, for example, 1 m, in the area where the detection signal of the section to be inspected exists, shifting the section by 1 mm, and performs color contour display processing of the spectrum response similar to process 6 in FIG. 7B from the obtained results. Continuous wavelet analysis is an excellent analysis means that achieves both a moving distance and spatial frequency resolution better than short-time Fourier transform, but when monitoring a metal object having a surface shape in which strands called strands, such as a wire rope, are twisted together, periodic fluctuations reflecting the strands occur in the detection signal, and in the case of analysis involving periodic fluctuations, short-time Fourier transform may be more suitable than wavelet analysis. <Circuit configuration of the first embodiment>

[0068] FIG. 11 is a block diagram showing the overall configuration of a metal object monitoring device 1 according to this embodiment.

[0069] As described above, the metal object monitoring device 1 has the magnetic detection device 2, the distance detection device 3, the processing device 4, and the power supply 88. The magnetic detection device 2 has a magnetic sensor unit 21 and a preamplifier unit 210, and the magnetic sensor unit 21 has an oscillator coil 5A, an oscillator coil 5B, and a receiving coil 6. The preamplifier unit 210 has an amplifier filter circuit 22, and the amplifier filter circuit 22 is connected to the magnetic sensor unit 21.

[0070] The processing device 4 also includes an amplifier 31, a digital-to-analog converter 32, an oscillator 33, a detector 34, an analog-to-digital converter 35, a memory 36, and an evaluation device 7. The oscillator 33 outputs a sinusoidal digital oscillator signal with a predetermined oscillatory frequency f. The oscillatory frequency f is selected to a value that can output a sufficient excitation magnetic field and ensure sufficient sensitivity of the receiving coil 6, taking into consideration the impedance of the oscillatory coil 5A and the oscillatory coil 5B. When selecting the oscillatory frequency f, it is preferable to fully consider the influence on the inspection of the metal object monitoring. Specifically, it is preferable to select the selected frequency range from 10 kHz to 100 kHz in order to be away from 1 / f noise, to be sufficiently separated from line noise (50 Hz or 60 Hz) and its harmonics, and to obtain a sufficient magnetic flux flow even if there is an influence of the skin effect of the metal object to be inspected.

[0071] 11, the digital-to-analog conversion unit 32 converts the digital oscillation signal output by the oscillation unit 33 into an analog AC voltage. The amplification unit 31 amplifies this AC voltage and applies it to the oscillation coil 5A and the oscillation coil 5B in the magnetic sensor unit 21. As a result, an AC magnetic field with an inverted phase is generated from the oscillation coil 5A and the oscillation coil 5B. The magnetic detection device 2 mounted on the moving body 100 is separated from the running surface 200a (see FIG. 1) so as not to interfere with the movement of the moving body 100, and therefore outputs an AC magnetic field of sufficient strength to sufficiently excite the running surface 200a from the oscillation coil.

[0072] The amplifier filter circuit 22 in the magnetic detection device 2 amplifies and filters the signal from the receiving coil 6, and transmits the result to the detection unit 34 of the processing device 4. This "filtering" is low-pass filtering to remove frequency components higher than the upper limit frequency of the oscillation frequency f in the set variable range, or high-pass filtering to remove frequency components lower than the lower limit frequency of the oscillation frequency f in the set variable range, taking into consideration the case where the oscillation frequency f is set with a degree of freedom. When the oscillation frequency f to be used is fixed, band-pass filtering may be used to pass only a bandwidth including a frequency range that satisfies the response speed at the maximum moving speed of the moving body 100, centered on the oscillation frequency f. The detection unit 34 also uses the reference signal SR1 supplied from the oscillator 33 to generate signals X, Y, R, and θ (these signals will be described in detail later) based on the signal supplied from the amplifier filter circuit 22, and supplies them to the analog-to-digital conversion unit 35. The analog-to-digital conversion unit 35 converts each analog signal received from the detection unit 34 into a digital signal.

[0073] In this embodiment, a signal from the distance detection device 3 is supplied to the processing device 4. This distance detection device 3 (see FIG. 1) detects the rotation angle of the wheel 300 of the moving body 100 via a rotation drive mechanism 500 connected to an axle 400, and the distance detection device 3 outputs a pulse signal SP in response to rotation with a predetermined accuracy. Then, the analog-to-digital conversion unit 35 converts the pulse signal SP into a digital signal and stores it in the memory unit 36. The digital signal output from the analog-to-digital conversion unit 35 is stored as data in the memory unit 36, and information on the moving distance of the moving body 100 is supplied to the evaluation device 7. The evaluation device 7 counts the pulse signals SP to calculate the moving distance of the moving body 100.

[0074] Next, the evaluation device 7 will be described. The evaluation device 7 is a hardware that includes a CPU (Central Processing Unit), a RAM (Random Access Memory), a ROM (Read Only Memory), and a HDD (Hard Disk Drive) as a general computer, and the HDD stores an OS (Operating System), application programs, various data, etc. The OS and application programs are expanded in the RAM and executed by the CPU.

[0075] The evaluation device 7 includes a control unit 42, a data processing unit 43, an output processing unit 44, an operation input unit 45, a display unit 46, and a storage unit 47. The evaluation device 7 executes an inspection processing program for identifying a singular point 202 (see FIG. 6) of the metal body 200 based on the metal body monitoring data received from the magnetic detection device 2, the detection unit 34, the analog-to-digital conversion unit 35, and the memory unit 36. Note that in this embodiment, the "metal body monitoring data" refers to data at all stages from the receiving coil 6 of the magnetic detection device 2 to the evaluation device 7.

[0076] The control unit 42 is, for example, a CPU (an example of a processor), and controls reading of the inspection data from the memory unit 36, arithmetic processing, and the like. The data processing unit 43 performs inspection processing based on the inspection data (details will be described later). The display unit 46 is an LCD (Liquid Crystal Display), a CRT (Cathode Ray Tube) display, or the like that displays the inspection results, and the like. The output processing unit 44 causes the display unit 46 to display the results of the metal body monitoring, and the like. At that time, the output processing unit 44 performs processing for displaying the results in a visually easy-to-understand display format by appropriately using the format of a graph or table. The operation input unit 45 is an information input means such as a keyboard, a mouse, or a touch panel. The storage unit 47 saves data such as the inspection results processed by the data processing unit 43. The data stored in the memory unit 36 ​​is also transferred to the storage unit 47. The data processing unit 43 and the output processing unit 44 are realized by loading the programs and data stored in the storage unit 47 into the control unit 42 and executing arithmetic processing.

[0077] 12 is a block diagram of the detection unit 34. The received signal SS from the amplification filter circuit 22 is supplied to phase comparators 74 and 76. The reference signal SR1 supplied from the oscillation unit 33 (see FIG. 8) is delayed by a delay circuit 72 by a time corresponding to a phase of 90° of the oscillation frequency f. The delayed reference signal SR1 is called a reference signal SR2. The reference signal SR1 is supplied to a phase comparator 76, and the reference signal SR2 is supplied to the phase comparator 74. The phase comparator 76 extracts a component of the received signal SS that is synchronized with the reference signal SR1. The extracted signal is filtered by an LPF (low pass filter) 80, which outputs the processing result as a cosine signal X.

[0078] Furthermore, the phase comparator 74 extracts a component of the received signal SS that is synchronized with the reference signal SR2. The extracted signal is filtered by the LPF 78, which outputs the result as a sine signal Y. The calculator 84 calculates the sine signal Y by √(X 2 +Y 2) and outputs the result as an amplitude signal R. Furthermore, calculator 82 calculates the arc tangent of (Y / X), that is, atan(Y / X), and outputs the result as a phase difference signal θ.

[0079] Then, the detection unit 34 supplies the above-mentioned signals X, Y, R and θ to the memory unit 36 ​​via the analog-to-digital conversion unit 35 (see FIG. 11). In the illustrated example, the detection unit 34 outputs all of the signals X, Y, R and θ, but the amplitude signal R and the phase difference signal θ may not be calculated by the detection unit 34, but may be calculated by the data processing unit 43 (see FIG. 11) based on the cosine signal X and the sine signal Y.

[0080] Here, the reason why the detection unit 34 detects the sine signal Y in addition to the cosine signal X will be explained. Information related to metal object monitoring (change in amplitude in the detection signal) can be obtained from either the cosine signal X or the sine signal Y. On the other hand, when only the cosine signal X is used, adjustment is required to set the phase of the reference signal so that the amplitude of the cosine signal X is maximized during inspection. This phase setting needs to be adjusted each time when, for example, the target metal object changes, the distance between the metal object and the magnetic detection device changes, or the excitation frequency of the oscillation coil in the magnetic detection device is changed as an inspection condition. Therefore, by simultaneously detecting the cosine signal X and the sine signal Y, the phase difference can be calculated, so that inspection can be performed without phase adjustment. In addition, not only the change in amplitude in the detection signal but also the change in phase difference can be obtained at the same time, and more detailed metal object monitoring information can be obtained. Furthermore, the value of the amplitude signal R that can be calculated by the calculator 84 (or the evaluation device 7) is constant in principle even if the phase difference signal θ fluctuates, so there is also the advantage of omitting the process of optimizing the phase of the reference signal. <Operation in the first embodiment>

[0081] FIG. 13 is a flowchart of metal object monitoring data processing executed by the data processing unit 43 of the evaluation device 7.

[0082] This process is executed at every predetermined control period. In FIG. 10, the processes of steps S2 and S14 are executed in parallel. First, the evaluation device 7 acquires metal object monitoring data from the storage unit 47 in step S2, and acquires the distance pulse signal SP from the storage unit 47 in step S14. After completing step S14, the evaluation device 7 converts the distance pulse signal SP into distance data SK in step S16. That is, the evaluation device 7 calculates the distance data SK based on the number of detections of the distance pulse signal SP detected by the distance detection device until the movement of the moving object stops. Here, the distance data SK indicates the distance from a predetermined reference position (the movement start position of the moving object), and the distance data SK may be an example of position data.

[0083] After completing step S2, in step S4, the evaluation device 7 acquires spectral response data in wavenumber space using the distance data SK. After completing step S4, it is determined whether or not the spectral response data falls outside a predetermined reference range, that is, a signal strength range for which a lower limit value is set. Here, the "spectral response data" used for the determination is, for example, the amplitude signal R shown in FIG. 12. If there is a singular point 202 (see FIG. 6), the amplitude signal R will clearly be large. Therefore, in step S6, the evaluation device 7 calculates a spectral response data in wavenumber space by comparing the amplitude signal R with a predetermined threshold value R. th1 Compare with "R ≠ R th1 ", it may be determined that there is a possibility that there is a singularity. th1 ” (which may include the case where the difference is equal to or smaller than a predetermined difference), it may be determined as “No”, that is, that there is no singular portion.

[0084] If the determination here is "No," the process proceeds to step S18. The details of this process will be described later. On the other hand, if the determination in step S6 is "Yes," the process proceeds to step S8. In step S8, the structure and damage are discriminated based on the spatial frequency region in which an increase in the signal intensity of the signals X, Y, R, θ, etc. shown in FIG. 12 occurs.

[0085] When the above-mentioned steps S2 to S16 are completed, the process proceeds to step S18, where a metal object monitoring result is generated. Here, the "metal object monitoring result" may include a correlation between peculiar points (structure and damage) and distance data SK if step S8 has been performed (if step S8 has not been performed, the "metal object monitoring result" may include a result indicating that no peculiar points are found). Next, when the process proceeds to step S20, the data processing unit 43 outputs the metal object monitoring result to the display unit 46 or the like, and the process of this routine ends. <Advantages of the First Embodiment>

[0086] As described above, according to the metal object monitoring device 1 of this embodiment, the magnetic detection device 2 includes the lower housing 20 and the upper housing 26. The lower housing 20 houses the magnetic sensor unit 21 and is made of a non-magnetic material. The upper housing 26 houses the preamplifier unit 210 and is fixed to the upper surface of the lower housing 20. A connector 28 connected to a connection cable 64 is attached to one side of the upper housing 26. The upper housing 26 is made of metal. This allows the state of the metal object 200 to be detected stably.

[0087] Moreover, the magnetic detection device 2 excites the traveling surface 200a of the metal body 200 with an AC magnetic field, and detects a singular point 202 on the traveling surface based on disturbances in the flow of magnetic flux generated on the traveling surface. This makes it possible to accurately detect the state of the metal body.

[0088] The metal object monitoring device 1 further has an output processing unit 44. The output processing unit 44 displays the type and location of the detected unique portion 202 as an image on the display unit 46. This allows the user to visually grasp the state of the metal object 200.

[0089] Moreover, the evaluation device 7 identifies the singular point 202 based on the discrimination result for the singular point 202, and can manage the structure and damage as information on the singular point that existed in the metal body 200. Furthermore, the processing device 4 detects the position of the singular point based on the distance pulse signal SP from the distance detection device 3, and displays the result on the display unit 46. [Second embodiment]

[0090] Next, a second embodiment of the present invention will be described. In the following description, parts corresponding to those in Fig. 1 to Fig. 12 are given the same reference numerals, and their description may be omitted. In addition, the following description will mainly focus on the differences from the first embodiment, and descriptions of the commonalities with the first embodiment will be omitted or simplified. <Configuration of the second embodiment>

[0091] The configuration of this embodiment is based on the configuration of FIG. 3 described in the above-mentioned first embodiment, and uses a plurality of magnetic sensor units as shown in FIG. 14. FIG. 14 is a bottom view of a magnetic detection device 2 incorporating a plurality of magnetic sensor units. As shown in FIG. 14, the magnetic sensor unit group 77 has N magnetic sensor units 21-1 to 21-N (N is an integer of 2 or more as described above in this embodiment) arranged in a row along the width direction of the lower housing 20, i.e., the width direction of the metal body 200 (see FIG. 1).

[0092] The magnetic sensor unit 21-k (k is an arbitrary integer from 1 to N) includes an oscillator coil 5A-k, an oscillator coil 5B-k, and a receiver coil 6-k. Each of these coils is formed by winding a coated copper wire.

[0093] The oscillator coil 5A-k, the receiver coil 6-k, and the oscillator coil 5B-k are arranged along the width direction (direction perpendicular to the moving direction) of the metal body 200 (see FIG. 1), and the receiver coil 6-k is arranged so as to be equidistant between the oscillator coil 5A-k and the oscillator coil 5B-k. AC currents with different frequency values ​​are supplied to each of the oscillator coils 5A-k and 5B-k from the processing device 4 (see FIG. 1) via the connection cable 60. As a result, AC magnetic fields with different frequency values ​​are generated from the oscillator coils 5A-k and 5B-k, which excite the metal body 200, and an induced voltage is generated in each of the receiver coils 6-k due to the magnetic flux generated from the excited metal body 200.

[0094] Fig. 15 is a partially cutaway plan view of the magnetic detection device 2 in the second embodiment. As in Fig. 3, Fig. 14 is an explanatory diagram in which the center of the flange 25 is cut away to expose the inside of the upper housing 26. Note that the configuration related to the housing structure and materials used for the magnetic sensor unit is the same as in the first embodiment.

[0095] 15, the preamplifier unit 210 includes a printed circuit board 210a on which an amplifying filter circuit group 79 is mounted. The amplifying filter circuit group 79 includes the same number (N) of amplifying filter circuits 22-1 to 22-N as the above-mentioned magnetic sensor unit 21. The magnetic sensor unit 21 and the amplifying filter circuit 22 may have a 1:1 correspondence.

[0096] The amplification filter unit 22-k (k is any integer from 1 to N) amplifies and filters the induced voltage generated in the receiving coil 6-k, and transmits the result to the processing device 4 via the connection cable 60 (see FIG. 1). The processing device 4 performs an analysis process on the received signal, and detects the magnetic signal generated from the metal body 200. <Circuit configuration of the second embodiment>

[0097] FIG. 16 is a block diagram showing the overall configuration of a metal object monitoring device 1 according to this embodiment.

[0098] In the metal object monitoring device 1 of this embodiment, the magnetic detection device 2 has magnetic sensor units 21-1 to 21-N and a preamplifier unit 210, and the magnetic sensor unit 21-k has oscillator coils 5A-k and 5B-k and a receiving coil 6-k. The preamplifier unit 210 has amplifying filter units 22-1 to 22-N, and the amplifying filter unit 22-k is connected to the magnetic sensor unit 21-k.

[0099] The processing device 4 also includes amplifiers 31-1 to 31-N, N digital-to-analog converters 32, an oscillator 33, detectors 34-1 to 34-N, an analog-to-digital converter 35, a memory unit 36, and an evaluation device 7 (N is an integer of 2 or more in this embodiment, but may be 1). In FIG. 16, the digital-to-analog converter 32 converts the digital oscillation signal output by the oscillator 33 into an analog AC voltage. The amplifier 31-k (k is an arbitrary integer of 1 to N) amplifies this AC voltage and applies it to the oscillator coils 5A-k and 5B-k in the magnetic sensor unit 21-k via the resonant filter unit 60-k. As a result, an AC magnetic field with an inverted phase is generated from the oscillator coils 5A-k and 5B-k.

[0100] In this embodiment, the signal of the magnetic detection device 2 and the signal of the distance detection device are used to obtain the spectral response in wave number space derived by the processing described in FIG. 7A, FIG. 7B, FIG. 7C, FIG. 8A, FIG. 8B, FIG. 9, and FIG. 10 over the entire area of ​​the metal body 200 occupied by the multiple magnetic sensor units 21 used. Therefore, when extracting the peculiar place, the response change of the signal intensity at a specific spatial frequency in the measurement area of ​​the metal body 200 can be known, so that more detailed metal body monitoring can be performed, for example, by grasping the distribution of damage occurrence. According to this embodiment, the position of the peculiar place existing in the metal body and the signal intensity distribution at that position can be expressed by contour lines as shown in FIG. 17, using the signal component at a specific spatial frequency obtained by the multiple magnetic sensor units 21 used. In FIG. 17, the vertical axis is the position information of the magnetic sensor unit 21 used, the horizontal axis is the moving distance of the moving body 100, and a color contour display with a signal intensity bar of the detection signal component at a specific spatial frequency is shown. Among the singular points, the structure is artificial, and therefore exists throughout the area measured by each magnetic sensor unit at its location. Therefore, as shown by reference numeral 1000 in FIG. 17, the signal intensity is uniform at each measurement position of the magnetic sensor unit 21 at the location of the structure. On the other hand, unlike the structure, damage is not uniform because its location occurs naturally. That is, the signal intensity obtained at each measurement position of the magnetic sensor unit 21 reflects the area where the damage has occurred and shows a non-uniform distribution showing a bias, as shown by reference numeral 2000 in FIG. 17. Note that the specific spatial frequency can be set and inputted at any value, and the position of the singular point present on the metal body and a contour representation of the signal intensity distribution at that position are output and displayed on the display unit 46 by the evaluation device 7. Such an output display of the contour representation may be an example of a display of monitoring information. [Variations]

[0101] The present invention is not limited to the above-mentioned embodiment, and various modifications are possible. The above-mentioned embodiment is exemplified to explain the present invention in an easy-to-understand manner, and is not necessarily limited to those having all the configurations described. In addition, it is possible to replace a part of the configuration of a certain embodiment with the configuration of another embodiment, and it is also possible to add the configuration of another embodiment to the configuration of a certain embodiment. In addition, it is possible to delete a part of the configuration of each embodiment, or to add and / or replace other configurations. In addition, the control lines and information lines shown in the figures show those that are considered necessary for explanation, and do not necessarily show all control lines and information lines necessary on the product. In reality, it may be considered that almost all configurations are connected to each other. Possible modifications of the above-mentioned embodiment are, for example, as follows. (1) The hardware of the evaluation device 7 in each of the above embodiments can be realized by a general-purpose computer, and therefore a program for executing the signal processing shown in Figures 7A, 7B, 7C, 8A, 8B, 9, and 10 and the processing related to the flowchart shown in Figure 13 may be installed in a computer from a program source such as a portable storage medium or a server. (2) In the above embodiments, the functions shown in Figures 11, 12, and 16 and the processes explained based on Figures 7A, 7B, 7C, 8A, 8B, 9, 10, and 13 have been explained as functions and processes realized by a processor executing a program, but some or all of them may be replaced with hardware functions and processes using an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array), etc. (3) In each of the above embodiments, the metal object monitoring device 1 may be mounted on any type of moving object, including manually operated objects such as a handcart, and self-propelled objects such as those powered by a motor or diesel engine. (4) The distance detection device 3 can be a self-propelled moving body equipped with a speed generator other than the distance pulse signal SP using the encoder described in the embodiment. Also, alternative means such as estimating the traveled distance based on acceleration information obtained from an acceleration sensor or measuring the traveled distance using a laser Doppler may be applied.

[0102] The above description can be summarized, for example, as follows. The following summary may include supplementary and modified examples of the above description.

[0103] The metal body monitoring device (1) includes a magnetic detection device (2), a distance detection device (3), and a processing device (4) connected to the magnetic detection device and the distance detection device. The magnetic detection device includes a magnetic sensor unit (21), which is provided on a moving body (100) that moves relatively over a metal body (200) and detects the leakage magnetic field generated by AC excitation of the metal body in a non-contact manner. The distance detection device is provided on the moving body and detects the moving distance of the moving body relative to the metal body. The processing device converts first data (111) representing a time series of the detection signal strength from the magnetic detection device into second data (222) representing the relationship between the moving distance and the detection signal strength based on the moving distance at each time point detected by the distance detection device. The processing device extracts a spectral response in wave number space specified from the second data, and outputs monitoring information that is information based on the extracted spectral response. From the monitoring information, a singular location of the metal body can be identified. In addition, since the offset drift caused by the oscillation of the moving body, which is a noise factor, has a different distance range, it is easy to remove the offset drift regardless of the speed. The monitoring information may include information indicating the result of discrimination of the peculiar part of the metal body (for example, information indicating the moving distance and what the peculiar part is). The peculiar part may be broadly classified into a damaged part and a structural part, and the structural part may be identified (estimated) to be one of the multiple types of parts classified as structural parts.

[0104] The monitoring information may be output by displaying the monitoring information (for example, displaying it on a display unit). The monitoring information may be information that indicates the correspondence between the spatial frequency and the moving distance of the moving object. Since the spatial frequency components of the detection signal differ depending on the type of peculiar location, it is possible to distinguish the peculiar location from such monitoring information. The correspondence between the spatial frequency and the moving distance of the moving object may be a color contour of an orthogonal coordinate system with a first axis corresponding to the spatial frequency and a second axis corresponding to the moving distance of the moving object, and a color indicator according to the detection signal intensity may be arranged in the orthogonal coordinate system. This is expected to provide high visibility.

[0105] The processing device may perform spatial filtering on the second data according to a size required for monitoring the metal object, and extract a spectral response in wave number space for each section (666) corresponding to the monitoring of the metal object from the data (555) that has been subjected to the spatial filtering. The spectral response in wave number space obtained after data cleansing using the spatial filter can provide visualization of extraction and separation of singular points (discrimination between structural points and damaged points).

[0106] The processing device may perform an interpolation process on the movement distance samples so that the movement distance samples in the second data are equally spaced. The spatial filtering process may be performed on the interpolated second data. Since the movement distance samples are thus interpolated so as to be equally spaced, the spatial filtering process is possible.

[0107] For each section of the second data, the processing device may perform continuous wavelet analysis to extract a spectral response in wavenumber space. This allows for identifying which spatial frequency components have changed at which moving distance for each section. For each section of the second data, the processing device may perform signal separation using discrete wavelet analysis to extract a spectral response in wavenumber space, and may use continuous wavelet analysis on the separated signals.

[0108] For each second data block, the processing device may perform a short-time Fourier transform to extract a spectral response in wavenumber space, where the metal object may have features that are periodically arranged along the direction of relative movement of the moving object, allowing periodic changes in the structure of the metal object to be detected.

[0109] The magnetic detection device may have a plurality of magnetic sensor units arranged in a direction perpendicular to the direction of relative movement of the moving body. [Explanation of symbols]

[0110] 1 Metal monitoring device 2. Magnetic detection device 3 Distance detection device 4 Processing Equipment 5, 5A-1 to 5A-N, 5B-1 to 5B-N Oscillating coil 6,6-1~6-N Receiving coil 21 Magnetic sensor section 100 Mobile 200 Metal objects 202 Unique locations (structural and damaged locations on metal bodies)

Claims

1. a magnetic detection device having a magnetic sensor unit provided on a moving body that moves relatively on a metal body and that detects a leakage magnetic field generated from the metal body in a non-contact manner; a distance detection device provided on the moving body and detecting a relative moving distance of the moving body with respect to the metal body; a processing device connected to the magnetic detection device and the distance detection device; Equipped with The processing device includes: converting first data representing a time series of detection signal strength from the magnetic detection device into second data representing a relationship between a moving distance and a detection signal strength based on a moving distance at each time point detected by the distance detection device; Extracting a spectral response in a specified wavenumber space from the second data; outputting monitoring information, the monitoring information being information based on the extracted spectral response; Metal body monitoring device.

2. The output of the monitoring information is a display of the monitoring information; The monitoring information is information representing a correspondence relationship between a spatial frequency and a moving distance of the moving object. The metallic object monitoring device according to claim 1 .

3. the correspondence relationship is a color contour in an orthogonal coordinate system having a first axis corresponding to a spatial frequency and a second axis corresponding to a moving distance of the moving object; In the orthogonal coordinate system, a color indicator is arranged according to the detected signal strength. The metallic object monitoring device according to claim 2 .

4. The processing device includes: performing a spatial filter process on the second data according to a size required for monitoring the metal object; extracting a spectral response in wavenumber space for each section corresponding to the monitor of the metal object from the spatially filtered data; The metallic object monitoring device according to claim 1 .

5. the processing device performs a sample interpolation process so that samples of the movement distance in the second data are spaced equally apart; the spatial filtering process is performed on the second data that has been subjected to the interpolation process; The metallic object monitoring device according to claim 4.

6. For each partition, the processing unit performs a continuous wavelet analysis to extract a spectral response in wavenumber space. The metallic object monitoring device according to claim 4.

7. For each partition, the processing device performs signal separation with discrete wavelet analysis and uses continuous wavelet analysis on the separated signals to extract the spectral response in wavenumber space. The metallic object monitoring device according to claim 4.

8. For each section, the processor performs a short-time Fourier transform to extract the spectral response in wavenumber space. The metallic object monitoring device according to claim 4.

9. The metal body has a shape that is periodically arranged along the relative movement direction of the moving body. The metallic object monitoring device according to claim 8.

10. The magnetic detection device has a plurality of magnetic sensor units arranged in a direction perpendicular to a relative movement direction of the moving body. The metallic object monitoring device according to claim 1 .

11. converting first data representing a time series of detection signal strength from the magnetic detection device into second data representing a relationship between a moving distance and a detection signal strength based on a moving distance at each time point detected by the distance detection device; Extracting a spectral response in a specified wavenumber space from the second data; outputting monitoring information, the monitoring information being information based on the extracted spectral response; This is done by a computer, The magnetic detection device is a device having a magnetic sensor unit provided on a moving body that moves relatively on a metal body and detects a leakage magnetic field generated from the metal body in a non-contact manner, The distance detection device is a device provided on the moving body and detects a relative moving distance of the moving body with respect to the metal body. Metal object monitoring method.

12. converting first data representing a time series of detection signal strength from the magnetic detection device into second data representing a relationship between a moving distance and a detection signal strength based on a moving distance at each time point detected by the distance detection device; Extracting a spectral response in a specified wavenumber space from the second data; outputting monitoring information, the monitoring information being information based on the extracted spectral response; Have the computer do this, The magnetic detection device is a device having a magnetic sensor unit provided on a moving body that moves relatively on a metal body and detects a leakage magnetic field generated from the metal body in a non-contact manner, The distance detection device is a device provided on the moving body and detects a relative moving distance of the moving body with respect to the metal body. Computer program.

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