Method and system for monitoring abnormalities in bridge girder bearings

Abstract

To realize an abnormality monitoring method of a bridge girder bearing portion and an abnormality monitoring system of a bridge girder bearing portion that monitor an abnormality of a bridge bearing portion by a quartz vibration type acceleration sensor.SOLUTION: A quartz vibration type acceleration sensor 13 installed on a bearing portion of a steel bridge 3 is used to measure an acceleration of vibration of the steel bridge 3 at the time of train passage to estimate an amount of fluttering of the steel bridge 3 based on a predetermined correlation and values associated with the acceleration data acquired by the measurement (for example, a value of total amplitude, a maximum value, and a minimum value of the acceleration data, a value of total amplitude, a maximum value, and a minimum value of velocity data, and value of total amplitude, a maximum value, and a minimum value of deviation data), and a presence or absence of an abnormality in the bridge girder bearing portion can be monitored by determining that the steel bridge 3 has an abnormality when the estimated amount of fluttering is larger than a threshold value.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to a method and system for monitoring an abnormality in a bridge girder support portion. [Background technology]

[0002] Conventionally, there is known technology for detecting abnormalities in the bearings of railway bridges (e.g., steel bridges) by using an acceleration sensor attached to the bridge to measure changes in the acceleration of the bridge girder vibration when a train passes (see, for example, Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2016-50404 A Summary of the Invention [Problem to be solved by the invention]

[0004] However, the technology of Patent Document 1 mentioned above does not detect the up and down flapping of the girder, known as "tilt," based on the acceleration measured by an acceleration sensor. If a tilt occurs in the support of a railway bridge, it can damage components near the support, so it is desirable to detect the tilt before damage or other problems occur. Therefore, the inventors conducted intensive research and developed a technology to detect abnormalities related to tilt using an acceleration sensor attached to a bridge girder (steel bridge).

[0005] An object of the present invention is to provide a method and system for monitoring an abnormality in a bridge girder support portion by using an acceleration sensor to monitor an abnormality in the bridge girder support portion. [Means for solving the problem]

[0006] In order to achieve the above object, one aspect of the present invention is to A method for monitoring an abnormality in a bridge girder support portion, comprising: an acceleration measurement step of measuring the acceleration of vibration of the bridge girder when a train passes by the quartz crystal vibration acceleration sensor to obtain acceleration data; a filtering process for extracting acceleration data of a low frequency band including a train passing frequency from the acceleration data; a determination step of determining whether or not there is an abnormality in the support portion based on a value associated with the acceleration data extracted by the filter processing and a predetermined correlation between a tilt amount in the support portion and a value associated with the acceleration data; having The correlation is performed in advance by using a quartz crystal oscillator acceleration Degree The acceleration data is a value associated with the acceleration data of the vibration of the bridge girder measured multiple times by a displacement sensor, and the amount of up and down movement of the bridge girder measured multiple times by a displacement sensor.

[0007] With this type of abnormality monitoring method for bridge girder support parts, a quartz vibration acceleration sensor is used to measure the acceleration of the bridge girder vibration when a train passes, and the amount of bridge girder deflection can be estimated based on a value linked to the acceleration data obtained by measurement and a predetermined correlation.If the estimated deflection amount is greater than a threshold value (reference value), it is determined that there is an abnormality in the bridge girder, making it possible to monitor for the presence or absence of abnormalities in the bridge girder support parts. In the judgment process, for example, if the estimated amount of swing exceeds a predetermined threshold, it is determined that the flapping of the bridge girder has become greater than normal, and that an abnormality has occurred in the support section.

[0008] Also preferably, The determination step includes: an acceleration waveform acquiring step of acquiring a waveform of acceleration data extracted by the filter processing; a determination step of determining whether or not an abnormality has occurred in the support portion based on a value relating to a waveform of the acquired acceleration data and a predetermined correlation between a tilt amount in the support portion and a value relating to a waveform of the acceleration data; Including, The value relating to the waveform of the acceleration data is any one of the total amplitude value of the waveform of the acceleration data, the maximum value of the acceleration data, and the minimum value of the acceleration data.

[0009] By obtaining the acceleration data waveform from the acceleration measured using a quartz vibration acceleration sensor and determining either the total amplitude value of the acceleration data waveform, the maximum value of the acceleration data, or the minimum value of the acceleration data, it is possible to accurately estimate the amount of tilt of the bridge girder based on a predetermined correlation, allowing for appropriate judgment regarding any abnormalities in the bridge girder.

[0010] Also preferably, The determination step includes: a velocity waveform acquisition step of integrating the acceleration data extracted by the filter processing to convert it into velocity data and acquiring a waveform of the velocity data; a determination step of determining whether or not an abnormality has occurred in the support portion based on a value relating to a waveform of the acquired speed data and a predetermined correlation between a tilt amount in the support portion and a value relating to a waveform of the speed data; Including, The value relating to the waveform of the speed data is any one of the total amplitude value of the waveform of the speed data, the maximum value of the speed data, and the minimum value of the speed data.

[0011] By obtaining a velocity data waveform from acceleration data measured using a quartz vibration acceleration sensor and determining either the total amplitude value of the velocity data waveform, the maximum value of the velocity data, or the minimum value of the velocity data, it is possible to accurately estimate the amount of bridge girder deflection based on a predetermined correlation, allowing for appropriate judgment regarding any abnormalities in the bridge girder.

[0012] Also preferably, The determination step includes: a data conversion step of integrating the acceleration data extracted by the filter processing to convert it into velocity data; a displacement waveform acquisition step of integrating the obtained velocity data to convert it into displacement data and acquiring a waveform of the displacement data; a determination step of determining whether or not an abnormality has occurred in the support portion based on a value relating to a waveform of the acquired displacement data and a predetermined correlation between a tilt amount in the support portion and a value relating to a waveform of the displacement data; Including, The value relating to the waveform of the displacement data is any one of the total amplitude value of the waveform of the displacement data, the maximum value of the displacement data, and the minimum value of the displacement data.

[0013] By obtaining the waveform of displacement data from acceleration data measured using a quartz vibration acceleration sensor and determining either the total amplitude value of the waveform of the displacement data, the maximum value of the displacement data, or the minimum value of the displacement data, it is possible to accurately estimate the amount of deflection of the bridge girder based on a predetermined correlation, allowing for appropriate judgment regarding any abnormalities in the bridge girder.

[0014] Also preferably, The quartz crystal vibration acceleration sensor is installed on the upper surface of the planar portion of the steel material constituting the bridge girder at a bridge girder support portion where the bridge girder is installed on the abutment via a support.

[0015] This makes it possible to suitably measure the acceleration of the bridge girder vibration when a train passes.

[0016] Also preferably, The correlation regarding the amount of tilt is classified into cases where the span length of the bridge girder is less than the distance between the front and rear wheels of the train cars and cases where the span length of the bridge girder is greater than or equal to the distance between the front and rear wheels of the train cars, and the judgment process is performed according to the span length of the bridge girder on which the quartz vibration acceleration sensor is installed.

[0017] If the span length of a bridge girder (steel bridge) is less than the distance between the front and rear wheels of a train car, when a train passes over the girder, the wheels on both the front and rear of the car will not be able to rest on the girder. On the other hand, if the span length of a bridge girder (steel bridge) is greater than or equal to the distance between the front and rear wheels of a train car, when a train passes over the bridge girder, at least one of the wheels on either the front or rear of the car will necessarily rest on the bridge girder. In other words, if the span length of the bridge girder is less than the distance between the front and rear wheels of the train's cars, there will be times when wheel vibration does not act on the bridge girder as the train passes over it, but if the span length of the bridge girder is greater than or equal to the distance between the front and rear wheels of the train's cars, wheel vibration will always act on the bridge girder as the train passes over it. As the wheel vibration acting on the bridge girder differs depending on the span length of the bridge girder, if the correlation between the amount of swing is classified according to the span length of the bridge girder, a stronger correlation will be obtained, allowing for more accurate judgment of any abnormalities in the bridge girder.

[0018] Another invention of the present application is a bridge girder support part abnormality monitoring system for implementing the above-mentioned bridge girder support part abnormality monitoring method. An acceleration measuring device including the quartz crystal vibration acceleration sensor for measuring the acceleration of vibration of the bridge girder when a train passes; an information management device capable of communicating with the acceleration measuring device, The bridge girder support abnormality monitoring system includes a control means for issuing an alarm regarding an abnormality in the support based on the acceleration data measured and acquired by the quartz crystal vibration acceleration sensor.

[0019] With such a configuration of an abnormality monitoring system for bridge girder support parts, the acceleration measuring device is equipped with a quartz vibration acceleration sensor that measures the acceleration of the bridge girder vibration when a train passes, and the amount of swing of the bridge girder can be estimated based on a value linked to the acceleration data obtained by measurement and a predetermined correlation.If the estimated swing amount is greater than a reference value, it is determined that there is an abnormality in the bridge girder, thereby making it possible to monitor for the presence or absence of abnormalities in the bridge girder support parts. In particular, this abnormality monitoring system can notify bridge managers and others of the presence or absence of abnormalities in bridge girder supports.

[0020] Also preferably, The control means a measuring device side control unit included in the acceleration measuring device, which executes a process of transmitting the acceleration data measured and acquired by the quartz vibration type acceleration sensor to the information management device; a control unit included in the information management device, which executes a filtering process to extract acceleration data of a low frequency band including a train passing frequency from the acceleration data transmitted from the acceleration measuring device, and executes a process to determine the presence or absence of an abnormality in the support unit based on a value associated with the acceleration data extracted by the filtering process and a predetermined correlation between a tilt amount in the support unit and a value associated with the acceleration data, and executes a notification regarding the abnormality; To have the following.

[0021] In this bridge girder support abnormality monitoring system, acceleration data measured by the quartz vibration acceleration sensor equipped in the acceleration measuring device is transmitted to an information management device, and the information management device calculates the amount of bridge girder deflection when a train passes from the acceleration data, and performs a process to determine whether or not there is an abnormality in the support based on the calculated amount of deflection, and then alerts the user of the abnormality.

[0022] Also preferably, The control means a measuring device side control unit included in the acceleration measuring device, which executes a filtering process to extract acceleration data of a low frequency band including a train passing frequency from the acceleration data measured and acquired by the quartz vibration acceleration sensor, and executes a process to transmit to the information management device data relating to the amount of deflection of the bridge girder when a train passes, based on a value associated with the acceleration data extracted by the filtering process and a predetermined correlation between the amount of deflection at the support and the value associated with the acceleration data; a control unit included in the information management device, which executes a process of determining whether or not there is an abnormality in the support unit based on the data on the amount of tilt transmitted from the acceleration measuring device, and executes a notification of the abnormality; To have the following.

[0023] With this bridge girder support abnormality monitoring system, the acceleration measuring device determines the amount of swing of the bridge girder when a train passes from acceleration data measured by a quartz vibration acceleration sensor, and data related to the determined amount of swing is sent to an information management device. The information management device then executes a process to determine whether or not there is an abnormality in the support based on the data related to the amount of swing, and can alert the user of the abnormality.

[0024] Also preferably, The control means a measuring device side control unit included in the acceleration measuring device, which executes a filtering process to extract acceleration data of a low frequency band including a train passing frequency from the acceleration data measured and acquired by the quartz crystal vibration acceleration sensor, and executes a process to determine the presence or absence of an abnormality in the support part based on a value associated with the acceleration data extracted by the filtering process and a predetermined correlation between the tilt amount in the support part and the value associated with the acceleration data, and executes a process to transmit the determination result to the information management device; a control unit included in the information management device, the control unit executing a notification regarding an abnormality in the support unit based on the determination result transmitted from the acceleration measuring device; To have the following.

[0025] In this bridge girder support abnormality monitoring system, the acceleration measuring device estimates the amount of swing of the bridge girder when a train passes from acceleration data measured by a quartz vibration acceleration sensor, and then performs a process to determine whether or not there is an abnormality in the support based on the estimated amount of swing, and the result of this determination is sent to an information management device. The information management device can then notify the user of any abnormality in the support portion based on the result of the determination. Effect of the Invention

[0026] According to the present invention, a quartz crystal vibration acceleration sensor is used as an acceleration sensor, and the quartz crystal vibration acceleration sensor is used to measure the acceleration of the vibration of the bridge girder when a train passes. Based on the acceleration data obtained, it is possible to properly estimate the amount of deflection of the bridge girder, and to appropriately monitor abnormalities in the bridge girder support parts. [Brief description of the drawings]

[0027] [Figure 1] FIG. 2 is an explanatory diagram of an abnormality monitoring system for steel bridge bearings. [Diagram 2] FIG. 2(b) is a cross-sectional view taken along line bb in FIG. 2(a) and FIG. 2(b) is an explanatory diagram of the location of an acceleration measuring device (quartz vibration acceleration sensor) installed in a steel bridge support. [Diagram 3] 1 is a schematic block diagram of an abnormality monitoring system for steel bridge bearings. [Figure 4] This table shows the results of a verification based on the coefficient of determination regarding the correlation between the acceleration index of the vibration of a steel bridge measured by various acceleration sensors and the amount of tilt on the steel bridge. The results are for a servo acceleration sensor (a), a piezoelectric acceleration sensor (b), a quartz vibration acceleration sensor (c), and a capacitance acceleration sensor (d). The acceleration index and [Diagram 5] FIG. 1 is an explanatory diagram of the dominant frequency of a displacement waveform caused by tilt at a steel bridge support. [Figure 6] This is an explanatory diagram of the predominant frequency caused by vibration due to the vehicle / wheel gap of a train on a steel bridge, and shows a schematic diagram of the train (a) and the calculated predominant frequency (b). [Figure 7] FIG. 2 is an explanatory diagram of the waveform of the low frequency band of acceleration data, showing (a) a case where there is no tilt and (b) a case where there is tilt. [Figure 8] FIG. 11 is an explanatory diagram regarding conversion of acceleration data. [Figure 9] This is an explanatory diagram of the maximum, minimum, and total amplitude values ​​read from the waveforms of acceleration data, velocity data, and displacement data. [Figure 10] 1A is a diagram illustrating the correlation between the tilt amount and acceleration data, and FIG. 1C is a diagram illustrating the correlation between the total amplitude of acceleration (a), the correlation between the maximum value of acceleration (b), and the correlation between the minimum value of acceleration (c). [Figure 11] 1A is a diagram illustrating the correlation between the tilt amount and the velocity data, and FIG. 1C is a diagram illustrating the correlation between the total amplitude of the velocity (a), the correlation between the maximum value of the velocity (b), and the correlation between the minimum value of the velocity (c). [Figure 12] 1A is a diagram for explaining the correlation between the tilt amount and the displacement data, and FIG. 1C is a diagram for explaining the correlation between the total amplitude of the displacement (a), the correlation between the maximum value of the displacement (b), and the correlation between the minimum value of the displacement (c). [Figure 13] Regarding the correlation of deflection amount, the coefficient of determination when classified by the span length of steel bridges of 11.7 m is shown in Table (a) and Graph (b). [Figure 14] 2 is a flowchart illustrating an abnormality monitoring method for a steel bridge support part according to the present embodiment. [Figure 15] FIG. 13 is an explanatory diagram relating to a modified example of the abnormality monitoring system for steel bridge bearings. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0028] Hereinafter, the embodiment of the method and system for monitoring abnormalities in bridge girder bearings according to the present invention will be described in detail with reference to the drawings. However, the embodiment described below is subject to various technically preferable limitations for carrying out the present invention, but the scope of the present invention is not limited to the following embodiment and illustrated examples. In this embodiment, the subject of monitoring is a steel bridge bearing, which is a bearing part of a railway bridge (steel bridge) and corresponds to a bridge girder bearing part of a steel bridge, and a method and system for monitoring abnormalities in a steel bridge bearing part will be described. The method for monitoring abnormalities in steel bridge bearings of this embodiment is, for example, a technology for monitoring abnormalities in steel bridge bearings (bridge girder bearings) using an abnormality monitoring system for steel bridge bearings, and in particular, monitors abnormalities in the bearings using a quartz vibration acceleration sensor installed in the bearings of the steel bridge girders. In this embodiment, as an abnormality in the support, the vertical fluttering of the steel bridge support, known as "flutter", is monitored by monitoring the amount of displacement of the flutter (amount of flutter).

[0029] [Abnormality monitoring system for steel bridge bearings] The abnormality monitoring system 100 for steel bridge bearings of this embodiment includes, for example, an acceleration measuring device 10 installed in a steel bridge bearing where a steel bridge 3 is installed on an abutment 1 via a bearing 2, as shown in Figure 1, and an information management device 20 capable of communicating with the acceleration measuring device 10.

[0030] The acceleration measuring device 10 is equipped with a quartz crystal vibration type acceleration sensor 13, which will be described later, and is installed on the upper surface of the planar portion of the steel material 3a that constitutes the bridge girder of the steel bridge 3 at the steel bridge support portion, as shown in Figures 2(a) and (b). Here, the steel material 3a of a steel bridge 3 (bridge girder) is installed on the abutment 1 via a bearing 2 and a sole plate 4, and an acceleration measuring device 10 (quartz crystal vibration acceleration sensor 13) is installed on the upper surface of the lower flange of the steel material 3a. This acceleration measuring device 10 (quartz crystal vibration acceleration sensor 13 ) measures the acceleration of vibration when the train T passes over the steel bridge 3 . Among various types of acceleration sensors, the quartz vibration type acceleration sensor 13 is classified as a frequency change type acceleration sensor, and is known to have low noise and high stability among frequency change type acceleration sensors. The reason why we chose a quartz vibration type acceleration sensor from the various types of acceleration sensors available will be explained later.

[0031] As shown in FIG. 3, the acceleration measuring device 10 includes, for example, a control unit (CPU; control means) 11, a communication unit 12, a quartz vibration type acceleration sensor 13, a storage unit 14, and the like.

[0032] The control unit 11, which is a measuring device side control unit, is, for example, a CPU, and executes various processes according to a control program stored in the storage unit . The communication unit 12 has, for example, an antenna and a communication circuit, and communicates with the information management device 20 under the control of the control unit 11, and transmits to the information management device 20 data regarding the acceleration at the steel bridge support portion measured by the quartz vibration type acceleration sensor 13. The quartz crystal vibration acceleration sensor 13, as part of the acceleration measuring device 10, is installed on the upper surface of a planar portion of the steel material 3a constituting the steel bridge 3 at the steel bridge support portion. This quartz crystal vibration acceleration sensor 13 measures the acceleration of the vibration of the steel bridge 3 when a train passes through. The storage unit 14 is configured with, for example, a RAM, a ROM, a non-volatile memory, and a hard disk drive, and stores various control programs executed by the CPU, various fixed data, and the like.

[0033] The information management device 20 is configured by a computer having a control unit (CPU; control means) 21, a communication unit 22, a storage unit 23, a display unit 24, an operation unit 25, and the like, as shown in FIG.

[0034] The communication unit 22 has, for example, an antenna and a communication circuit, and communicates with the acceleration measuring device 10 under the control of the control unit 21, and receives data relating to the acceleration at the steel bridge bearings from the acceleration measuring device 10. The storage unit 23 is composed of, for example, a RAM, a ROM, a non-volatile memory, and a hard disk drive, and stores various control programs executed by the CPU, various fixed data, etc. The storage unit 23 also stores data related to acceleration at the steel bridge bearings measured by the acceleration measuring device 10 (quartz vibration type acceleration sensor 13), data obtained by analyzing and processing the acceleration data, etc. The display unit 24 is, for example, a liquid crystal display or an EL display, and displays data relating to acceleration measured at the steel bridge bearings, data obtained by analyzing and processing the acceleration data, various processing results, and the like. The operation unit 25 is, for example, a keyboard, a mouse, or a touch panel, and operation input for executing various analysis processes can be performed using this operation unit 25.

[0035] The control unit 21 , which is a management device side control unit, is, for example, a CPU, and executes various processes according to a control program stored in the storage unit 23 . For example, the control unit 21 acquires data regarding acceleration at the steel bridge support parts received by the communication unit 22, performs filtering to extract acceleration data in a low frequency band including the train passing frequency from the acceleration data, and calculates the amount of tilt of the steel bridge when a train passes based on a value associated with the acceleration data extracted by filtering and a predetermined correlation between the amount of tilt at the support parts and the value associated with the acceleration data, and performs processing to determine the presence or absence of an abnormality in the support parts based on the calculated amount of tilt. This determination process will be described later.

[0036] [About the use of quartz vibration type acceleration sensors] Next, the reason for selecting the quartz crystal vibration acceleration sensor 13 as the acceleration sensor for measuring the acceleration of the vibration of the steel bridge 3 when a train passes, in monitoring the presence or absence of abnormalities in the steel bridge bearings, will be explained.

[0037] In order to verify what type of acceleration sensor is suitable for monitoring abnormalities in the steel bridge support parts, the inventors installed various acceleration sensors and displacement sensors on the upper surface of the lower flange of the steel material 3a that constitutes the steel bridge 3 at the steel bridge support part, and measured the acceleration of the vibration of the steel bridge 3 when a train passes over multiple times using the acceleration sensor, and measured the amount of up and down movement of the steel bridge 3 when a train passes over multiple times using the displacement sensor. Various acceleration sensors include: Servo type acceleration sensor (model: Rion LS-10C) Piezoelectric acceleration sensor (model: Rion PV-87) - Quartz vibration acceleration sensor (model: Epson M-A352AD10) Capacitive acceleration sensor (type: Analog Devices ADXL355) was used. We then examined the degree of correlation between the values ​​associated with the acceleration of the vibration of the steel bridge measured by each acceleration sensor and the amount of tilt on the steel bridge. Here, we calculated the values ​​of 12 types of indices, namely maximum acceleration, minimum acceleration, total acceleration amplitude, maximum velocity, minimum velocity, total velocity amplitude, maximum displacement, minimum displacement, total displacement amplitude, RMS, equivalent peak, and FFT area, which are values ​​related to the vibration acceleration of the steel bridge, and calculated the coefficient of determination (R 2 The results of the comparison are shown in Figure 4.

[0038] As shown in Figure 4, the coefficient of determination (R 2 ) is 0.6 or higher, the results showed that the correlation was strong for all 12 types of indices for the quartz vibration type acceleration sensor. In addition, the results showed that there was a strong correlation between servo acceleration sensors and piezoelectric acceleration sensors for five indicators: minimum acceleration, total acceleration amplitude, RMS, equivalent peak, and FFT area. On the other hand, the results showed that the capacitance-type acceleration sensor showed a weak correlation for all 12 indicators. In particular, the coefficient of determination (R 2 ) was 0.8 or higher. Based on these results, the inventors concluded that by using a quartz vibration acceleration sensor to measure the acceleration of the vibration of the steel bridge, it would be possible to infer the amount of tilt of the steel bridge based on the correlation between the value associated with that acceleration and the amount of tilt of the steel bridge, and therefore decided to adopt a quartz vibration acceleration sensor.

[0039] [About the need for filtering] Next, the reason for performing a filtering process to extract acceleration data in a low frequency band including the train passing frequency from the acceleration data measured by the acceleration sensor (quartz vibration type acceleration sensor 13) when monitoring for abnormalities in the steel bridge bearings will be explained.

[0040] (The dominant frequency of the displacement waveform caused by tilt at the bearing of a steel bridge) A displacement sensor installed on the upper surface of the lower flange of the steel material 3a constituting the steel bridge 3 at the steel bridge support measures the displacement related to the tilt at the steel bridge support, and when the obtained displacement waveform is Fourier transformed, it is possible to confirm dominant frequencies such as 1.3 Hz, 2.5 Hz, and 3.8 Hz as the displacement power spectrum, as shown in Figure 5, for example. When the displacement waveforms obtained by measuring the displacement of the tilt angle in the same way on various steel bridges 3 were subjected to a Fourier transform, a similar displacement power spectrum was obtained, and it was possible to confirm the predominant frequency of an approximate value. From such verification, the inventors have concluded that the predominant frequency is in the low frequency band of 0.01 Hz to 4.0 Hz, which includes the train passing frequency. This is the first consideration regarding the predominant frequency.

[0041] (Primitive frequency caused by train car / wheel spacing on steel bridge) As shown in Figure 6(a), when the vehicle length is 20 m, the wheel spacing within the vehicle is 13.8 m, and the wheel spacing between coupled vehicles is 6.2 m, the predominant frequency caused by vibration when this train is traveling at 80 km / h was calculated, and it was confirmed to be 1.1 Hz to 3.6 Hz, as shown in Figure 6(b). In addition, assuming that the maximum train speed is 130 km / h, the predominant frequency caused by vibration when the train is traveling at 130 km / h was calculated and confirmed to be 1.8 Hz to 5.8 Hz. From such verification, the inventors have concluded that the predominant frequency is in the low frequency band of 0.01 Hz to 6.0 Hz, which includes the train passing frequency. This is the second consideration regarding the predominant frequency.

[0042] In this way, based on the consideration (first consideration, second consideration) that the displacement and vibration of the steel bridge 3 have predominant frequencies in the low frequency band, the inventors have discovered that by extracting acceleration data in the low frequency band of 6.0 Hz or less, which includes the train passing frequency, from the measured acceleration data through filtering, it is possible to suitably obtain data regarding the "tilt" at the steel bridge supports. The filtering process here is performed using a low-pass filter or a band-pass filter.

[0043] (The presence or absence of "tilts" in the waveform of low-frequency acceleration data) As described above, the inventors have found that it is effective to extract acceleration data in the low frequency band, including the train passing frequency, by filtering from the acceleration data of the vibration of the steel bridge 3 obtained by measurement using the quartz vibration acceleration sensor 13. The evidence that this filtering process is effective will now be described. As shown in Figure 7(a), in the case of a steel bridge 3 where no "tilt" occurs, when acceleration data in the low frequency band including the train passing frequency is extracted by filtering from the acceleration data of the vibration of the steel bridge 3 measured by the quartz vibration acceleration sensor 13, it can be seen that the amplitude of the waveform of the extracted acceleration data is small. In contrast, as shown in Figure 7(b), when acceleration data in the low frequency band including the train passing frequency is extracted by filtering from the acceleration data of the vibration of the steel bridge 3 measured by the quartz vibration acceleration sensor 13 in the case of a steel bridge 3 where a tilt is occurring, the amplitude of the waveform of the extracted acceleration data is large. In this way, it is seen that information regarding "tailgating" can be obtained from the acceleration data of the vibration of the steel bridge 3, and that information regarding "tailgating" can be suitably obtained from acceleration data in the low frequency band including the train passing frequency extracted by filtering the acceleration data of the vibration of the steel bridge 3 measured by the quartz vibration type acceleration sensor 13.

[0044] [Conversion of acceleration data] Next, the conversion of acceleration data, which is data related to the "tilt" at the steel bridge support portion and is performed to obtain a value associated with the acceleration of the vibration of the steel bridge 3, will be described. As shown in Fig. 8, the above-mentioned filtering process is applied to the acceleration data (original) of the vibration of the steel bridge 3 measured by the quartz crystal vibration type acceleration sensor 13 to extract acceleration data in the low frequency band of 6.0 Hz or less, which includes the train passing frequency (filtering process step). The waveform of the acceleration data extracted by the conversion using this filtering process (the waveform in the upper right corner in the figure) is obtained (acceleration waveform acquisition process). As shown in FIG. 8, the acquired acceleration data is integrated and converted into velocity data (data conversion step), and the waveform of the velocity data (the waveform at the lower left in the figure) is acquired (velocity waveform acquisition step). Moreover, as shown in FIG. 8, the acquired velocity data is integrated and converted into displacement data, and the waveform of the displacement data (the waveform at the lower right in the figure) is acquired (displacement waveform acquisition step). From the waveform thus obtained, the maximum value, minimum value, and total amplitude value can be obtained, as shown in FIG. For example, the total amplitude value of the acceleration data, the maximum value of the acceleration data, and the minimum value of the acceleration data can be obtained from the waveform of the acceleration data. Moreover, the total amplitude value of the velocity data, the maximum value of the velocity data, and the minimum value of the velocity data can be obtained from the waveform of the velocity data. Moreover, the total amplitude value of the displacement data, the maximum value of the displacement data, and the minimum value of the displacement data can be obtained from the waveform of the displacement data.

[0045] [Correlation between tilt amount and values ​​linked to acceleration data] Next, the correlation between the amount of tilt at the steel bridge support and the value associated with the acceleration data will be described. As explained in the "Use of Quartz Vibration Acceleration Sensors" section above, a correlation is determined between the amount of tilt at the steel bridge support and a value linked to the acceleration data. Specifically, a quartz crystal vibration acceleration sensor 13 and a displacement sensor are installed on the upper surface of the lower flange of the steel material 3a that constitutes the steel bridge 3 at the steel bridge support section, and the acceleration of the vibration of the steel bridge 3 when a train passes is measured multiple times using the quartz crystal vibration acceleration sensor 13, and the amount of up and down movement of the steel bridge 3 when a train passes is measured multiple times using the displacement sensor. Then, as explained in the above "Conversion of acceleration data", the acceleration data measured by the quartz vibration type acceleration sensor 13 is converted to obtain "Total amplitude value of acceleration data", "Maximum value of acceleration data", "Minimum value of acceleration data", "Total amplitude value of speed data", "Maximum value of speed data", "Minimum value of speed data", Nine values ​​were calculated: "total amplitude value of displacement data," "maximum value of displacement data," and "minimum value of displacement data." Each of the nine values ​​was associated with the "amount of tilt" measured by the displacement sensor, and the correlation between each value and the "amount of tilt" was calculated. Here, the coefficient of determination (R 2 ) The above value was correlated with the amount of tilt. In order to obtain a correlation, it is of course preferable to measure the acceleration of the vibration of the steel bridge 3 when a train passes and the amount of tilt of the steel bridge 3 as many times as possible. FIG. 10 shows the correlation between the tilt amount and acceleration data obtained by carrying out numerous measurements in this manner, FIG. 11 shows the correlation between the tilt amount and velocity data, and FIG. 12 shows the correlation between the tilt amount and displacement data. By determining such a correlation (for example, see Figures 10, 11, and 12) in advance, it becomes possible to estimate the amount of tilt of the steel bridge 3 based on the acceleration of the vibration of the steel bridge 3 measured by the quartz vibration acceleration sensor 13 when a train passes. In this embodiment, such predetermined correlations (correlation between tilt amount and acceleration data, correlation between tilt amount and velocity data, correlation between tilt amount and displacement data) are stored in the storage unit 23 of the information management device 20, for example.

[0046] [Steel bridge span length] Next, regarding the correlation between the amount of tilt and the value associated with the acceleration data, classification based on the span length of the steel bridge 3, 11.7 m, will be explained. In this embodiment, it is assumed that a train such as the one shown in FIG. 6(a) runs with the distance between the inner wheels of the front and rear bogies of the vehicle being 11.7 m. Therefore, if the span length of the steel bridge 3 is less than 11.7 m, when a train passes over the steel bridge 3, the wheels on both the front and rear of the train will not be able to rest on the steel bridge 3. On the other hand, if the span length of the steel bridge 3 is 11.7 m or more, when a train passes over the steel bridge 3, at least one of the wheels on either the front or rear of the vehicle will necessarily rest on the steel bridge 3. In other words, if the span length of the steel bridge 3 is less than 11.7 m, there will be times when wheel vibration does not act on the steel bridge 3 as a train passes over it, and if the span length of the steel bridge 3 is 11.7 m or more, wheel vibration will always act on the steel bridge 3 as a train passes over it. Since the wheel vibration acting on the steel bridge 3 differs depending on the span length of the steel bridge 3, the inventors discovered that a stronger correlation can be obtained with respect to the correlation of the amount of swing by classifying the steel bridge 3 according to its span length. Specifically, as shown in Figure 13(a)(b), when the steel bridge was classified by the span length of 11.7 m, the coefficient of determination was generally higher than when it was not classified (all bridges), indicating a stronger correlation. In this way, correlations related to the amount of tailwind are defined by classifying cases into cases where the span length of the steel bridge 3 is less than the distance between the front and rear wheels of the train cars, and cases where the span length of the steel bridge 3 is equal to or greater than the distance between the front and rear wheels of the train cars, and it is preferable to determine the presence or absence of an abnormality in the steel bridge support parts based on one of the correlations depending on the span length of the steel bridge 3 on which the quartz vibration acceleration sensor 13 (acceleration measuring device 10) is installed.

[0047] [Method of monitoring abnormalities in steel bridge bearings] Next, a method for monitoring an abnormality in a steel bridge bearing using the abnormality monitoring system 100 of this embodiment will be described. As described above, the abnormality monitoring system 100 for steel bridge bearings comprises an acceleration measuring device 10 equipped with a quartz vibration type acceleration sensor 13 that measures the acceleration of the vibration of the steel bridge 3 when a train passes, and an information management device 20 capable of communicating with the acceleration measuring device 10. This abnormality monitoring system 100 is equipped with control means (measurement device side control unit 11, management device side control unit 21) that issues an alert regarding abnormalities in the steel bridge bearings based on the acceleration data measured and acquired by the quartz vibration acceleration sensor 13.

[0048] Here, the determination process performed by the control unit 21 serving as the management device side control unit in the information management device 20 described above will be described. The management device side control unit 21 executes a filtering process to extract acceleration data in a low frequency band including the train passing frequency from the acceleration data measured and acquired by the quartz vibration type acceleration sensor 13 (filtering process step). Furthermore, the control unit 21 on the management device side estimates and determines the amount of tilt of the steel bridge 3 when a train passes, based on a value associated with the acceleration data extracted by the filter processing and a predetermined correlation between the amount of tilt at the support part and the value associated with the acceleration data.

[0049] The value associated with the acceleration data here may be a value related to the waveform of the acceleration data, and may be any one of the total amplitude value of the waveform of the acceleration data, the maximum value of the acceleration data, or the minimum value of the acceleration data, or a value related to the waveform of the velocity data, and may be any one of the total amplitude value of the waveform of the velocity data, the maximum value of the velocity data, or the minimum value of the velocity data, or a value related to the waveform of the displacement data, and may be any one of the total amplitude value of the waveform of the displacement data, the maximum value of the displacement data, or the minimum value of the displacement data. These nine values ​​associated with the acceleration data can be obtained as described in the above "Conversion of acceleration data". (For example, the values ​​associated with the acceleration data can be obtained by processes such as an acceleration waveform acquisition step, a velocity waveform acquisition step, a data conversion step, and a displacement waveform acquisition step. See Figs. 8 and 9.) In addition, predetermined correlations (the correlation between the tilt amount and the acceleration data (FIG. 10), the correlation between the tilt amount and the velocity data (FIG. 11), and the correlation between the tilt amount and the displacement data (FIG. 12)) are stored in the memory unit 23 of the information management device 20.

[0050] Then, based on any one of the values ​​associated with the nine acceleration data and a predetermined correlation, the amount of swing of the steel bridge 3 when a train passes is estimated. With respect to the total amplitude value of the acceleration data waveform, the amount of tilt can be estimated based on the correlation shown in FIG. 10(a). With respect to the maximum value of the acceleration data, the amount of tilt can be estimated based on the correlation shown in FIG. 10(b). With respect to the minimum value of the acceleration data, the amount of tilt can be estimated based on the correlation shown in FIG. 10(c). In addition, for the total amplitude value of the velocity data waveform, the tilt amount can be estimated based on the correlation shown in FIG. 11(a). For the maximum value of the velocity data, the tilt amount can be estimated based on the correlation shown in FIG. 11(b). For the minimum value of the velocity data, the tilt amount can be estimated based on the correlation shown in FIG. 11(c). Furthermore, for the total amplitude value of the waveform of the displacement data, the amount of tilt can be estimated based on the correlation shown in FIG. 12(a). For the maximum value of the displacement data, the amount of tilt can be estimated based on the correlation shown in FIG. 12(b). For the minimum value of the displacement data, the amount of tilt can be estimated based on the correlation shown in FIG. 12(c). As explained above in the section "Span Length of Steel Bridges," if the amount of deflection is estimated based on the correlation according to the span length, it becomes possible to estimate the amount of deflection more appropriately.

[0051] Then, the management device side control section 21 executes a process of determining the presence or absence of an abnormality in the support section based on the tilt amount estimated based on a predetermined correlation (determination step (judgment step)). For example, the control unit 21 on the management device side determines that there is an abnormality in the support section when the estimated tilt amount exceeds a predetermined threshold value (when the tilt amount is larger than a reference value), and determines that there is no abnormality in the support section when the estimated tilt amount is equal to or less than the predetermined threshold value (when the tilt amount is small). The result of this determination is notified to the manager of the steel bridge 3, for example, by displaying it on the display unit 24 of the information management device 20.

[0052] [First abnormality monitoring method] Next, an abnormality monitoring method using the abnormality monitoring system 100 for steel bridge bearings will be described with reference to the flowchart shown in FIG.

[0053] First, the quartz crystal vibration type acceleration sensor 13 of the acceleration measuring device 10 installed on the steel bridge 3 measures the acceleration of the vibration of the steel bridge 3 when a train passes (step S1; acceleration measuring step). The acceleration data measured and acquired by the quartz vibration type acceleration sensor 13 is transmitted to the information management device 20 by a transmission process performed by the measurement device side control unit 11 .

[0054] Next, the management device side control unit 21 of the information management device 20 executes a filtering process to extract low-frequency band acceleration data including the train passing frequency from the acceleration data transmitted from the acceleration measuring device 10 (filtering process step), and calculates the amount of deflection of the steel bridge 3 when a train passes based on a value associated with the acceleration data extracted by the filtering process and a predetermined correlation between the amount of deflection at the support section and the value associated with the acceleration data (step S2). In this embodiment, the total amplitude value of the velocity data waveform is obtained as the value associated with the acceleration data, and the tilt amount is estimated based on the correlation shown in Fig. 11(a). In order to obtain the value associated with the acceleration data used in the processing of step S2, the processing of the acceleration waveform acquisition step, the velocity waveform acquisition step, the data conversion step, and the displacement waveform acquisition step are appropriately executed.

[0055] Next, the management apparatus side control section 21 judges whether or not the obtained tilt amount is equal to or less than a predetermined threshold value (step S3; judging step (judging step)). When the management device side control section 21 judges that the amount of tilt is equal to or less than the predetermined threshold value (step S3; Yes), it judges that there is no abnormality in the steel bridge support section, and returns to step S1. On the other hand, if it is determined that the tilt amount is not below the predetermined threshold value (is a value exceeding the threshold value) (step S3; No), it is determined that an abnormality has occurred in the steel bridge support, and the occurrence of the abnormality is notified to the manager of the steel bridge 3, etc., by displaying a message on the display unit 24 of the information management device 20 (step S4), and the process returns to step S1.

[0056] In this way, with the abnormality monitoring system 100 for steel bridge bearings (abnormality monitoring method for steel bridge bearings) of this embodiment, the amount of tilt in the steel bridge 3 can be estimated by measuring the acceleration of the vibration of the steel bridge 3 using the quartz vibration acceleration sensor 13, and the presence or absence of an abnormality in the steel bridge bearings can be determined and reported based on the estimated amount of tilt. In other words, the abnormality monitoring system 100 for steel bridge bearings (method for monitoring abnormalities in steel bridge bearings) of this embodiment can measure the acceleration of the vibration of the steel bridge 3 using a quartz vibration acceleration sensor 13, and monitor the presence or absence of abnormalities in the bearings of the steel bridge 3.

[0057] [Second abnormality monitoring method] The abnormality monitoring method by the abnormality monitoring system 100 of the present invention is not limited to the above embodiment. For example, the method may be a method for monitoring abnormalities in steel bridge bearings in which part of the processing by the management device control unit 21 described above is performed by the measurement device control unit 11 . Specifically, first, the quartz crystal vibration type acceleration sensor 13 of the acceleration measuring device 10 installed on the steel bridge 3 measures the acceleration of the vibration of the steel bridge 3 when a train passes (step S1; acceleration measuring step).

[0058] Next, the measuring device side control unit 11 of the acceleration measuring device 10 performs a filtering process to extract low-frequency band acceleration data including the train passing frequency from the acceleration data measured and acquired by the quartz vibration acceleration sensor 13 (filtering process step), and calculates the amount of deflection of the steel bridge 3 when a train passes based on a value associated with the acceleration data extracted by the filtering process and a predetermined correlation between the amount of deflection at the support section and the value associated with the acceleration data (step S2). In this embodiment, the total amplitude value of the velocity data waveform is obtained as the value associated with the acceleration data, and the tilt amount is estimated based on the correlation shown in Fig. 11(a). In order to obtain the value associated with the acceleration data used in the processing of step S2, the processing of the acceleration waveform acquisition step, the velocity waveform acquisition step, the data conversion step, and the displacement waveform acquisition step are appropriately executed. The data relating to the tilt amount obtained here is transmitted to the information management device 20 by a transmission process performed by the measurement device side control unit 11.

[0059] Next, the management device side control unit 21 of the information management device 20 judges whether or not the tilt amount is equal to or less than a predetermined threshold based on the data on the tilt amount transmitted from the acceleration measuring device 10 (step S3; judgment step (judgment step)). When the management device side control section 21 judges that the amount of tilt is equal to or less than the predetermined threshold value (step S3; Yes), it judges that there is no abnormality in the steel bridge support section, and returns to step S1. On the other hand, if it is determined that the tilt amount is not below the predetermined threshold value (is a value exceeding the threshold value) (step S3; No), it is determined that an abnormality has occurred in the steel bridge support, and the occurrence of the abnormality is notified to the manager of the steel bridge 3, etc., by displaying a message on the display unit 24 of the information management device 20 (step S4), and the process returns to step S1.

[0060] Even with this type of abnormality monitoring system 100 for steel bridge bearings (method for monitoring abnormalities in steel bridge bearings), the acceleration of the vibration of the steel bridge 3 can be measured using a quartz vibration acceleration sensor 13, and the presence or absence of abnormalities in the bearings of the steel bridge 3 can be monitored.

[0061] [Third abnormality monitoring method] Furthermore, the abnormality monitoring method using the abnormality monitoring system 100 of the present invention is not limited to the above embodiment. For example, the method may be a method for monitoring abnormalities in steel bridge bearings in which part of the processing by the management device control unit 21 described above is performed by the measurement device control unit 11 . Specifically, first, the quartz crystal vibration type acceleration sensor 13 of the acceleration measuring device 10 installed on the steel bridge 3 measures the acceleration of the vibration of the steel bridge 3 when a train passes (step S1; acceleration measuring step).

[0062] Next, the measuring device side control unit 11 of the acceleration measuring device 10 performs a filtering process to extract low-frequency band acceleration data including the train passing frequency from the acceleration data measured and acquired by the quartz vibration acceleration sensor 13 (filtering process step), and calculates the amount of deflection of the steel bridge 3 when a train passes based on a value associated with the acceleration data extracted by the filtering process and a predetermined correlation between the amount of deflection at the support section and the value associated with the acceleration data (step S2). In this embodiment, the total amplitude value of the velocity data waveform is obtained as the value associated with the acceleration data, and the tilt amount is estimated based on the correlation shown in Fig. 11(a). In order to obtain the value associated with the acceleration data used in the processing of step S2, the processing of the acceleration waveform acquisition step, the velocity waveform acquisition step, the data conversion step, and the displacement waveform acquisition step are appropriately executed. Furthermore, the measurement device side control unit 11 judges whether or not the obtained tilt amount is equal to or less than a predetermined threshold value (step S3; judgment step (judgment step)). When the measurement device side control unit 11 judges that the amount of tilt is equal to or less than the predetermined threshold value (step S3; Yes), it judges that there is no abnormality in the steel bridge support, and returns to step S1. On the other hand, if the control unit 11 on the measuring device side determines that the tilt amount is not below the predetermined threshold value (is a value exceeding the threshold value) (step S3; No), it determines that an abnormality has occurred in the steel bridge support, and the determination result is transmitted to the information management device 20 by a transmission process by the control unit 11 on the measuring device side.

[0063] Next, the management device side control unit 21 of the information management device 20 notifies the manager of the steel bridge 3, etc., of the occurrence of an abnormality by, for example, displaying the occurrence of an abnormality on the display unit 24 of the information management device 20 based on the judgment result transmitted from the acceleration measuring device 10 (step S4), and the process returns to step S1.

[0064] Even with this type of abnormality monitoring system 100 for steel bridge bearings (method for monitoring abnormalities in steel bridge bearings), the acceleration of the vibration of the steel bridge 3 can be measured using a quartz vibration acceleration sensor 13, and the presence or absence of abnormalities in the bearings of the steel bridge 3 can be monitored.

[0065] As described above, with the abnormality monitoring system 100 for steel bridge bearings (method for monitoring abnormalities in steel bridge bearings) of this embodiment, the amount of tilt of the steel bridge 3 can be estimated by measuring the acceleration of the vibration of the steel bridge 3 using the quartz vibration acceleration sensor 13, and the presence or absence of abnormalities in the steel bridge bearings can be monitored based on the estimated amount of tilt.

[0066] In the above embodiment, the steel bridge bearing abnormality monitoring system 100 is equipped with an acceleration measuring device 10 and an information management device 20 capable of communicating with the acceleration measuring device 10. However, the present invention is not limited to this, and for example, the processing in the information management device 20 may be performed on a server or in the cloud. 15, an abnormality monitoring system 100 for steel bridge bearings may include an acceleration measuring device 10 installed at a steel bridge bearing where a steel bridge 3 is installed on an abutment 1 via a bearing 2, a cloud server 20a capable of communicating with the acceleration measuring device 10, and a terminal device 20b capable of communicating with the cloud server 20a. Of course, the acceleration measuring device 10 includes a quartz vibration type acceleration sensor 13 that measures the acceleration of the vibration of the steel bridge 3 when a train passes over it. Then, the processing (steps S2 and S3) by the management device side control unit 21 of the information management device 20, as explained in the above-mentioned "first abnormality monitoring method", can be performed by the cloud server 20a, and the notification processing (step S4) of the determination result that an abnormality has occurred in the steel bridge support can be performed by a terminal device 20b such as a tablet. That is, the cloud server 20a and the terminal device 20b function as the information management device 20 here. The abnormality monitoring system 100 for steel bridge bearings configured in this manner can also monitor the presence or absence of abnormalities in steel bridge bearings.

[0067] Furthermore, in the explanation of the above-mentioned method for monitoring abnormalities in steel bridge bearings, an example was given in which the value associated with the acceleration data is determined by calculating the total amplitude of the velocity data, and the amount of tilt is estimated and calculated based on the correlation of the velocity and total amplitude. However, the present invention is not limited to this, and the value associated with the acceleration data may be any of the total amplitude of the acceleration data, the maximum value of the acceleration data, the minimum value of the acceleration data, the total amplitude of the velocity data, the maximum value of the velocity data, the minimum value of the velocity data, the total amplitude of the displacement data, the maximum value of the displacement data, and the minimum value of the displacement data, and the amount of tilt can be estimated and calculated based on the correlation corresponding to each value.

[0068] In addition, other specific details of the structure can of course be modified as appropriate. [Explanation of symbols]

[0069] 1. Abutment 2 Bearing 3 Steel bridge (bridge girder) 3a steel material 4 Soleplate 10 Acceleration measuring device 11 Control section (measurement device side control section, control means) 12 Communications Department 13 Quartz vibration type acceleration sensor 14 Storage section 20 Information management device 21 Control unit (management device side control unit, control means) 22 Communications Department 23 Memory section 24 Display section 25 Control section 20a Cloud Server 20b Terminal equipment 100 Abnormality monitoring system for bridge girder bearings T train

Claims

1. A method for monitoring an abnormality in a bridge girder support portion, comprising: an acceleration measurement step of measuring the acceleration of vibration of the bridge girder when a train passes by the quartz crystal vibration acceleration sensor to obtain acceleration data; a filtering process for extracting acceleration data of a low frequency band including a train passing frequency from the acceleration data; a determination step of determining whether or not there is an abnormality in the support portion based on a value associated with the acceleration data extracted by the filter processing and a predetermined correlation between a tilt amount in the support portion and a value associated with the acceleration data; having This method for monitoring abnormalities in bridge girder supports is characterized in that the correlation corresponds a value linked to the acceleration data of the vibration of the bridge girder measured multiple times in advance by a quartz vibration acceleration sensor when a train passes, and the amount of up and down movement of the bridge girder measured multiple times by a displacement sensor.

2. The determination step includes: an acceleration waveform acquiring step of acquiring a waveform of acceleration data extracted by the filter processing; a determination step of determining whether or not an abnormality has occurred in the support portion based on a value relating to a waveform of the acquired acceleration data and a predetermined correlation between a tilt amount in the support portion and a value relating to a waveform of the acceleration data; Including, The method for monitoring abnormalities in bridge girder supports according to claim 1, characterized in that the value relating to the waveform of the acceleration data is either a value of the total amplitude of the waveform of the acceleration data, a maximum value of the acceleration data, or a minimum value of the acceleration data.

3. The determination step includes: a velocity waveform acquisition step of integrating the acceleration data extracted by the filter processing to convert it into velocity data and acquiring a waveform of the velocity data; a determination step of determining whether or not an abnormality has occurred in the support portion based on a value relating to a waveform of the acquired speed data and a predetermined correlation between a tilt amount in the support portion and a value relating to a waveform of the speed data; Including, The method for monitoring abnormalities in bridge girder supports according to claim 1, characterized in that the value relating to the waveform of the speed data is either a value of the total amplitude of the waveform of the speed data, a maximum value of the speed data, or a minimum value of the speed data.

4. The determination step includes: a data conversion step of integrating the acceleration data extracted by the filter processing to convert it into velocity data; a displacement waveform acquisition step of integrating the obtained velocity data to convert it into displacement data and acquiring a waveform of the displacement data; a determination step of determining whether or not an abnormality has occurred in the support portion based on a value relating to a waveform of the acquired displacement data and a predetermined correlation between a tilt amount in the support portion and a value relating to a waveform of the displacement data; Including, The method for monitoring abnormalities in bridge girder supports according to claim 1, characterized in that the value relating to the waveform of the displacement data is either a value of the total amplitude of the waveform of the displacement data, a maximum value of the displacement data, or a minimum value of the displacement data.

5. The method for monitoring abnormalities in a bridge girder support section according to any one of claims 1 to 4, characterized in that the quartz crystal vibration acceleration sensor is installed on an upper surface of a planar portion of a steel material constituting the bridge girder at a bridge girder support section where the bridge girder is installed on an abutment via a support.

6. The method for monitoring abnormalities in bridge girder supports according to any one of claims 1 to 5, characterized in that the correlation regarding the amount of tilt is classified into cases where the span length of the bridge girder is less than the distance between the front and rear wheels of the train cars and cases where the span length of the bridge girder is equal to or greater than the distance between the front and rear wheels of the train cars, and the judgment process is performed according to the span length of the bridge girder on which the quartz vibration acceleration sensor is installed.

7. A bridge girder support part abnormality monitoring system that implements the bridge girder support part abnormality monitoring method according to claim 1, An acceleration measuring device including the quartz crystal vibration acceleration sensor for measuring the acceleration of vibration of the bridge girder when a train passes; an information management device capable of communicating with the acceleration measuring device, The abnormality monitoring system for bridge girder support parts is characterized in that it is equipped with a control means that executes an alarm regarding abnormalities in the support part based on the acceleration data measured and acquired by the quartz vibration acceleration sensor.

8. The control means a measuring device side control unit included in the acceleration measuring device, which executes a process of transmitting the acceleration data measured and acquired by the quartz vibration type acceleration sensor to the information management device; a control unit included in the information management device, which executes a filtering process to extract acceleration data of a low frequency band including a train passing frequency from the acceleration data transmitted from the acceleration measuring device, and executes a process to determine the presence or absence of an abnormality in the support unit based on a value associated with the acceleration data extracted by the filtering process and a predetermined correlation between a tilt amount in the support unit and a value associated with the acceleration data, and executes a notification regarding the abnormality; 8. The system for monitoring an abnormality in a bridge girder support portion according to claim 7, further comprising:

9. The control means a measuring device side control unit included in the acceleration measuring device, which executes a filtering process to extract acceleration data of a low frequency band including a train passing frequency from the acceleration data measured and acquired by the quartz vibration acceleration sensor, and executes a process to transmit to the information management device data relating to the amount of deflection of the bridge girder when a train passes, based on a value associated with the acceleration data extracted by the filtering process and a predetermined correlation between the amount of deflection at the support and the value associated with the acceleration data; a control unit included in the information management device, which executes a process of determining whether or not there is an abnormality in the support unit based on the data on the amount of tilt transmitted from the acceleration measuring device, and executes a notification of the abnormality; 8. The system for monitoring an abnormality in a bridge girder support portion according to claim 7, further comprising:

10. The control means a measuring device side control unit included in the acceleration measuring device, which executes a filtering process to extract acceleration data of a low frequency band including a train passing frequency from the acceleration data measured and acquired by the quartz crystal vibration acceleration sensor, and executes a process to determine the presence or absence of an abnormality in the support part based on a value associated with the acceleration data extracted by the filtering process and a predetermined correlation between the tilt amount in the support part and the value associated with the acceleration data, and executes a process to transmit the determination result to the information management device; a control unit included in the information management device, the control unit executing a notification regarding an abnormality in the support unit based on the determination result transmitted from the acceleration measuring device; 8. The system for monitoring an abnormality in a bridge girder support portion according to claim 7, further comprising:

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