JP2021025813A - Structure degradation diagnostic system - Google Patents

Abstract

To provide a structure degradation diagnostic system that can precisely diagnose degradation in a structure on the basis of an active load displacement measured during a monitoring time without being required to generate a reference value in advance.SOLUTION: The present invention includes: at least two sensors (10) set in a structure for measuring an active load displacement of the structure caused by an active load; and a diagnosis unit (20) for diagnosing degradation in the structure by generating time-series data of the active load displacement by sequentially acquiring active load displacements measured by the at least two sensors, generating a histogram related to the active load displacement from the time-series data, and comparing a reference histogram, which is a histogram generated from the result of measurement by one of the sensors, and a diagnosis histogram, which is a histogram generated from the result of measurement by the sensors other than the one sensor, the reference histogram and the diagnosis histogram being generated in the same time zone.SELECTED DRAWING: Figure 6

Description

The present invention relates to a structure deterioration diagnosis system for diagnosing deterioration of structures such as bridges.

For example, a structure corresponding to a bridge through which a vehicle passes gradually deteriorates due to aging due to the passage of the vehicle. For structures such as bridges, it is important to detect deterioration before they break.

As a conventional technique for diagnosing deterioration of a bridge, there is a bearing abnormality inspection device for detecting an abnormality of a bearing, which is a member installed between an upper structure and a lower structure (see, for example, Patent Document 1). The device according to Patent Document 1 detects bearing abnormalities by the following procedure.
(1) The reference value, which is a characteristic value related to the shaking of the bridge and is a reference characteristic value, is stored in advance.
(2) The acquired value, which is a characteristic value related to the shaking of the bridge, is acquired by using a sensor.
(3) Bearing abnormality detection is performed based on the difference between the reference value and the acquired value.

JP-A-2019-31830 International Publication No. 2017/064854

However, the prior art has the following problems.
In Patent Document 1, it is necessary to generate a reference value in advance. In order to generate an accurate reference value, for example, it is necessary to prepare a vehicle of a known weight and collect data. Therefore, it takes time and effort to generate a reference value.

In addition, if the bridge has already begun to deteriorate when the reference value is generated, the reference value itself may be unreliable and accurate deterioration diagnosis may not be possible.

The present invention has been made to solve the above-mentioned problems, and the structure is highly accurate based on the live load displacement measured during the monitoring period without the need to generate a reference value in advance. The purpose is to obtain a structural deterioration diagnosis system capable of performing deterioration diagnosis.

The structure deterioration diagnosis system according to the present invention is installed in a structure and measures the live load displacement of the structure due to the live load by two or more sensors and the live load displacement measured by each of the two or more sensors for a time. Time-series data of live load displacement is generated by sequentially acquiring with the passage of time, a histogram regarding live load displacement is generated from the time-series data, and the histogram generated from the measurement result by any one sensor is used as a reference histogram. A histogram generated from measurement results by sensors other than one sensor is used as a diagnostic histogram, and a diagnostic unit is provided for diagnosing deterioration of a structure by comparing a reference histogram generated at the same time with a diagnostic histogram. ..

According to the present invention, there is a structure deterioration diagnosis system capable of performing a structure deterioration diagnosis with high accuracy based on the live load displacement measured during the monitoring period without the need to generate a reference value in advance. Obtainable.

It is a block diagram of the structure deterioration diagnosis system which concerns on Embodiment 1 of this invention. It is explanatory drawing which showed the state which the sensor was installed in the structure which is the diagnosis target of the structure deterioration diagnosis system which concerns on Embodiment 1 of this invention. It is explanatory drawing which showed the time transition of the live load displacement in each of the steady state and the deterioration progressing state in Embodiment 1 of this invention. It is explanatory drawing which showed the histogram of the live load displacement in each of the steady state and the deterioration progressing state in Embodiment 1 of this invention. It is explanatory drawing which showed the time transition of the mode value obtained from the histogram of the live load displacement in Embodiment 1 of this invention. It is a block diagram of the structure deterioration diagnosis system which concerns on Embodiment 2 of this invention. It is explanatory drawing which showed the state which the sensor was installed in the structure which is the diagnosis target of the structure deterioration diagnosis system which concerns on Embodiment 2 of this invention. It is explanatory drawing which showed the steady state and the deterioration progress state in comparison in the deterioration diagnosis using two sensors in Embodiment 2 of this invention. It is explanatory drawing which showed the time transition of the live load displacement based on the measurement result of two sensors in each of the steady state and the deterioration progress state in Embodiment 2 of this invention. It is explanatory drawing which showed the histogram of the live load displacement based on the measurement result of two sensors in each of the steady state and the deterioration progress state in Embodiment 2 of this invention. It is explanatory drawing which showed the time transition of the natural frequency based on the measurement result of two sensors in each of the steady state and the deterioration progress state in the conventional structure abnormality detection apparatus.

Hereinafter, preferred embodiments of the structure deterioration diagnosis system of the present invention will be described with reference to the drawings.
The present invention is a technique capable of monitoring the deterioration state of the structure to be diagnosed with high accuracy based on the time series data of live load displacement measured during the deterioration diagnosis without the need to generate a reference value in advance. It is a characteristic feature.

Embodiment 1.
In the first embodiment, a case where the deterioration diagnosis of the structure is performed based on the measurement result by one sensor will be described.

FIG. 1 is a block diagram of a structure deterioration diagnosis system according to a first embodiment of the present invention. The structure deterioration diagnosis system according to the first embodiment is configured to include one sensor 10 and a diagnosis unit 20.

Further, FIG. 2 is an explanatory diagram showing a state in which the sensor 10 is installed in the structure to be diagnosed by the structure deterioration diagnosis system according to the first embodiment of the present invention. In FIG. 2, a bridge 30 is shown as a specific example of the structure, FIG. 2A is a side view of the bridge 30, and FIG. 2B is a back view of the bridge 30.

The bridge 30 gradually deteriorates due to aging due to the passage of the vehicle 1. Therefore, in the structure deterioration diagnosis system according to the first embodiment, the diagnosis unit 20 analyzes the detection result by the sensor 10 installed at a position suitable for the deterioration diagnosis, so that the deterioration of the bridge 30 changes from moment to moment. Diagnose the condition.

Specifically, the sensor 10 is installed on the main girder 31, which is a component of the bridge 30. Here, the main girder 31 corresponds to the structure of the structure to be diagnosed. As shown in FIG. 2B, the main girder 31 is configured as three main girders 31a, 31b, 31c as an example. Then, in the example of FIG. 2B, the case where the sensor 10 is installed in the central portion of the main girder 31b (that is, the central portion between the spans corresponding to the distance between the left and right bearings 2) is illustrated. This installation position corresponds to an example of a position suitable for deterioration diagnosis.

In the following description, a case where deterioration diagnosis is performed based on the detection result by one sensor 10 will be described. However, as for the sensor 10, one sensor may be installed at a position different from that of the first embodiment, or a plurality of sensors may be installed at a plurality of locations on the bridge 30. When a plurality of sensors 10 are installed, the diagnosis unit 20 can obtain a plurality of deterioration diagnosis results based on the detection results at the installation positions of the individual sensors 10.

The sensor 10 measures the live load displacement of the bridge 30 due to the live load generated on the bridge 30. Here, the live load means that the magnitude of the load is not constant and the acting position changes. Factors that cause such live load displacement include the weight of the vehicle 1 passing through the bridge 30, the weight of the bridge 30 itself, and the inertial force acting on the bridge 30 due to an earthquake.

The sensor 10 includes a sensor 10 that directly measures live load displacement (for example, a displacement sensor) and a sensor 10 that converts a physical quantity detection result into live load displacement and outputs the measurement result (for example, an acceleration sensor). included.

On the other hand, the diagnostic unit 20 sequentially acquires the live load displacement measured by the sensor 10 with the passage of time, thereby generating time-series data of the live load displacement. Further, the diagnosis unit 20 performs a deterioration diagnosis of the bridge 30 which is a structure from the generated time series data.

As described above, the structure deterioration diagnosis system according to the first embodiment is based on the time series data showing the live load displacement that changes from moment to moment during the monitoring period without the need to generate the reference value in advance. , It has a technical feature in that deterioration diagnosis of the bridge 30 is performed. Therefore, a specific deterioration diagnosis method executed by the diagnosis unit 20 will be described in detail next.

FIG. 3 is an explanatory diagram showing the time transition of the live load displacement in each of the steady state and the deterioration progressing state in the first embodiment of the present invention. FIG. 3 (a) shows the time transition of the live load displacement in the steady state where the deterioration has not progressed, and FIG. 3 (b) shows the time transition of the live load displacement in the deterioration progress state. Further, in FIGS. 3A and 3B, the vertical axis represents the live load displacement [mm] and the horizontal axis represents the time [H].

The monitoring period is set according to the traffic volume to be monitored, and can be changed as appropriate, for example, a period that is an integral multiple of the calendar unit such as one week or one month. ing.

The diagnostic unit 20 sequentially acquires the live load displacement measured by the sensor 10 at a predetermined sampling cycle, which corresponds to the time transition of the live load displacement shown in FIGS. 3 (a) and 3 (b). As the data to be generated, time-series data of live load displacement is generated.

The displacement amount of the live load in the steady state shown in FIG. 3A is within a relatively small value range. On the other hand, the displacement amount of the live load in the deterioration progressing state shown in FIG. 3B is larger than that in the steady state, and the variation of the live load displacement with the passage of time becomes remarkable.

FIG. 4 is an explanatory diagram showing histograms of live load displacements in each of the steady state and the deterioration progressing state in the first embodiment of the present invention. FIG. 4 (a) shows a histogram of the live load displacement generated based on the time series data of the live load displacement in the steady state where the deterioration has not progressed, and FIG. 4 (b) shows the histogram in the deteriorate progress state. The histogram of the live load displacement generated based on the time series data of the live load displacement is shown. Further, in FIGS. 4A and 4B, the vertical axis represents the frequency and the horizontal axis represents the live load displacement [mm].

The diagnostic unit 20 generates a histogram as shown in FIGS. 4 (a) and 4 (b) by totaling the frequency of each displacement amount based on the generated time-series data of the live load displacement. be able to. The histogram in the steady state shown in FIG. 4A is a histogram generated corresponding to the time transition of the live load displacement in the steady state shown in FIG. 3A. Further, the histogram in the deterioration progress state shown in FIG. 4 (b) is a histogram generated corresponding to the time transition of the live load displacement in the deterioration progress state shown in FIG. 3 (b).

As is clear from FIG. 4A, the frequency of live load displacement in the steady state is concentrated in the range of 0.02 to 0.03 [mm]. On the other hand, as is clear from FIG. 4B, the live load displacement in the deterioration progressing state is the most frequent, which corresponds to the value of the live load displacement showing the peak frequency when compared with the live load displacement in the steady state. As the value shifts to the right, the frequency at the most frequent value becomes smaller, and the live load displacement varies. Therefore, the diagnosis unit 20 monitors the time transition of the mode value, and when the mode value deviates from the preset allowable range, it can determine that the deterioration progress state.

FIG. 5 is an explanatory diagram showing the time transition of the mode value obtained from the histogram of the live load displacement in the first embodiment of the present invention. In FIG. 5, when the mode value of live load displacement is in the range of 0.020 [mm] to 0.028 [mm], it is set in advance as an allowable range in which deterioration has not progressed. Is illustrated. The diagnosis unit 20 can specify the mode with respect to the histogram of the live load displacement with time, and can diagnose the deterioration of the bridge 30 based on the comparison between the mode and the allowable threshold.

In the example shown in FIG. 5, deterioration is detected when the mode at the present time deviates from the permissible range. However, the deterioration detection method by the diagnostic unit 20 is not limited to this. For example, it is possible to set the mode value obtained in a certain time zone during the monitoring period as a reference value and detect deterioration from the difference between the mode value and the reference value at the present time. Such deterioration detection will be specifically described.

The diagnosis unit 20 generates a first histogram as a histogram based on the time-series data of the live load displacement generated in the first time zone, and the first mode showing the mode in the first histogram. To identify. This first time zone corresponds to the time zone included in the steady state.

Next, the diagnostic unit 20 generates a second histogram as a histogram based on the time series data of the active load displacement generated in the second time zone after the first time zone, and the second histogram. The second mode indicating the mode in is specified. This second time zone corresponds to the current time zone during monitoring.

Next, the diagnosis unit 20 determines that the bridge 30 is in a deteriorated state when the difference value between the first mode value and the second mode value deviates from the preset difference tolerance range. Diagnose.

In order to specify the first mode value as a reference value, it is premised that the first mode value is within the above-mentioned allowable range. Further, the first mode value, which is the reference value, may be calculated only once or updated periodically, and it is not necessary to calculate it repeatedly every time the second mode value is calculated.

In this way, even when the reference value is specified from the mode value of the histogram during the monitoring period, it is possible to perform the deterioration diagnosis of the structure with high accuracy without having to generate the reference value in advance. The effect can be realized.

Further, the live load displacement used as an index for deterioration diagnosis in the first embodiment may fluctuate depending on the season and climate. In particular, live load displacement is affected by air temperature. Therefore, a supplementary explanation will be given on measures against this seasonal fluctuation.

The rigidity of the material of the bridge 30, which is the object of deterioration diagnosis, generally changes due to fluctuations in temperature. Specifically, it is less rigid in the hot summers and more rigid in the colder winters. Therefore, depending on the season and climate, the live load displacement may differ even when the live load of the same weight is applied.

To give a specific numerical example, the live load displacement when a vehicle of the same weight traveled on a certain bridge 30 was measured in different seasons, and the following results were obtained.
August: Live load displacement at a running temperature of 26.0 ° C (cloudy) 1.55 [mm]
January: Live load displacement at a running temperature of 0.2 ° C (snow) 1.29 [mm]

Therefore, in order to deal with such fluctuations in live load displacement due to air temperature, the diagnostic unit 20 corrects the permissible threshold value or the difference permissible range with a preset correction coefficient according to the temperature when the histogram is generated. , The deterioration diagnosis can be performed using the corrected tolerance threshold value or the difference tolerance range. As a result, stable and highly accurate deterioration diagnosis can be realized without being affected by seasonal fluctuations.

The effect of using the mode value as an index for diagnosing deterioration of the structure will be supplementarily described. When an average value or the like is used as an index for diagnosing deterioration of a structure, it may be difficult to compare because the result fluctuates only by changing the size distribution of vehicles such as small vehicles or large vehicles depending on traffic conditions. .. Generally, the traffic volume of small vehicles is larger than that of large vehicles.

Further, even if the ratio of the small vehicle to the large vehicle fluctuates to some extent, the hierarchical relationship of the traffic volume of the large vehicle and the small vehicle cannot change in the long term. Therefore, by using the mode value as an index for diagnosing deterioration of the structure, it is possible to identify the distribution of small vehicles with the largest traffic volume. Therefore, by using the mode value of displacement as a reference, the structure can be identified with high accuracy. Deterioration diagnosis can be performed.

As described above, according to the first embodiment, the time transition of the most frequent value of the live load displacement generated based on the measurement result of the live load displacement by one sensor installed in the structure is used. It has a configuration for diagnosing the presence or absence of deterioration progress of the structure.

Specific examples of the deterioration diagnosis method include the following, as described in detail in the first embodiment.
-Using the time transition of the most frequent value of live load displacement generated sequentially during the monitoring period, deterioration diagnosis of the structure is performed based on the comparison between the most frequent value and the preset allowable threshold value.
-The mode of the active load displacement generated for the past data during the monitoring period is set as the first mode, and the mode of the live load displacement generated for the current data during the subsequent monitoring period. The mode is set as the second mode, and it is determined whether or not there is a significant difference between the first mode and the second mode that deviates from the permissible threshold. Perform deterioration diagnosis.

As a result, it is possible to realize a structure deterioration diagnosis system capable of performing a structure deterioration diagnosis with high accuracy based on the live load displacement measured during the monitoring period without having to generate a reference value in advance.

Embodiment 2.
In the second embodiment, it is assumed that two or more sensors are provided in the structure of the structure, and the deterioration diagnosis of the structure is performed based on the comparison of the measurement results by the two sensors installed in each main girder of the bridge. Will be described.

FIG. 6 is a block diagram of the structure deterioration diagnosis system according to the second embodiment of the present invention. The structure deterioration diagnosis system according to the second embodiment is configured to include two sensors 10 (1) and 10 (2) and a diagnosis unit 20.

Further, FIG. 7 is an explanatory diagram showing a state in which the sensor 10 is installed in the structure to be diagnosed by the structure deterioration diagnosis system according to the second embodiment of the present invention. In FIG. 7, a bridge 30 is shown as a specific example of the structure, FIG. 7A is a side view of the bridge 30, and FIG. 7B is a back view of the bridge 30.

In the second embodiment, the sensors 10 (1) and 10 (2) are installed on the main girder 31 which is a component of the bridge 30. Here, the main girder 31 corresponds to the structure of the structure to be diagnosed. As shown in FIG. 7B, the main girder 31 is configured as three main girders 31a, 31b, 31c as an example. Then, in the example of FIG. 7B, the two sensors 10 (1) and 10 (2) correspond to the quartile points of the main girders 31a, 31b, and 31c (that is, the distance between the left and right bearings 2). The case where it is installed in the part corresponding to one-fourth and three-quarters of the bearings) is illustrated. The quartile, which is the installation position, corresponds to an example of a position suitable for deterioration diagnosis.

In the following description, a case where deterioration diagnosis is performed based on the detection results by the two sensors 10 (1) and 10 (2) installed on the main girder 31b will be described. However, the sensor 10 itself may be installed at three or more locations on the bridge 30. When three or more sensors 10 are installed, a plurality of deterioration diagnosis results can be obtained by comparing the detection results at the installation positions of the individual sensors 10 with the detection results with other sensors. .. Further, the sensor 10 itself may be installed on the main girders 31a, 31b, and 31c, respectively.

The structure deterioration diagnosis system according to the second embodiment is generated from the measurement results by the two sensors 10 (1) and 10 (2) during the monitoring period without the need to generate the reference value in advance. In addition, it has a technical feature in that deterioration diagnosis of the bridge 30 is performed based on two time-series data showing live load displacements that change from moment to moment. Therefore, a specific deterioration diagnosis method executed by the diagnosis unit 20 will be described in detail next.

FIG. 8 is an explanatory diagram showing a steady state and a deterioration progress state in comparison with each other in the deterioration diagnosis using the two sensors in the second embodiment of the present invention. 8 (a) shows a steady state, and FIGS. 8 (b) and 8 (c) show a state of progress in deterioration. 8 (b) and 8 (c) show a state in which a crack A or a crack B is generated in the main girder 31 of the bridge 30 in the vicinity of the sensor 10 (1) and deterioration is progressing. Therefore, FIGS. 9 to 12 show specific methods for detecting the deterioration progress state shown in FIGS. 8 (b) or 8 (c) using the two sensors 10 (1) and 10 (2). It will be described below in use.

FIG. 9 shows the time transition of live load displacement based on the measurement results of the two sensors 10 (1) and 10 (2) in each of the steady state and the deterioration progress state in the second embodiment of the present invention. It is explanatory drawing. FIG. 9 (a) shows the time transition of the live load displacement based on the measurement results of the two sensors 10 (1) and 10 (2) in the steady state where the deterioration has not progressed, and FIG. 9 (b). ) Indicates the time transition of the live load displacement based on the measurement results of the two sensors 10 (1) and 10 (2) in the deterioration progress state.

In FIGS. 9A and 9B, the waveform based on the measurement result of the sensor 10 (1) is shown as a dotted line, and the waveform based on the measurement result of the sensor 10 (2) is shown as a solid line. Further, in FIGS. 9 (a) and 9 (b), the vertical axis represents the live load displacement [mm] and the horizontal axis represents the time [min].

The diagnostic unit 20 sequentially acquires the live load displacements measured by the sensors 10 (1) and the sensors 10 (2) at predetermined sampling cycles, whereby FIGS. 9 (a) and 9 (b) Time-series data of live load displacement is generated as data corresponding to the time transition of live load displacement shown in.

The displacement amounts of the live loads corresponding to the sensors 10 (1) and 10 (2) in the steady state shown in FIG. 9 (a) all show the same behavior and are within a relatively small value range. .. On the other hand, the displacement amounts of the live loads corresponding to 10 (1) and 10 (2) in the deterioration progress state shown in FIG. 9B show different behaviors.

Specifically, in FIG. 9B, the displacement amount of the live load corresponding to the sensor 10 (1) installed in the vicinity of the generated crack A becomes larger than that in the steady state, and over time. The variation in live load displacement that accompanies it is remarkable. On the other hand, the displacement amount of the live load corresponding to the sensor 10 (2) installed at a place away from the generated crack A shows the same behavior as the steady state.

That is, the time series data of the live load displacement based on the measurement result by the sensor 10 (1) is affected by the crack A shown in FIG. 8 (b) or the crack B shown in FIG. 8 (c), and is in a steady state. It has changed compared to the time series data in. On the other hand, the time series data of the live load displacement based on the measurement result by the sensor 10 (2) is not easily affected by the crack A shown in FIG. 8 (b) or the crack B shown in FIG. 8 (c), and is in a steady state. The degree of change is suppressed to be small compared to the time series data in.

FIG. 10 shows a histogram of live load displacement based on the measurement results of the two sensors 10 (1) and 10 (2) in each of the steady state and the deterioration progress state in the second embodiment of the present invention. It is a figure. FIG. 10A shows a histogram of live load displacement generated based on time series data of live load displacement in a steady state where deterioration has not progressed. On the other hand, FIG. 10B shows a histogram of the live load displacement generated based on the time series data of the live load displacement in the deterioration progress state.

In FIGS. 10A and 10B, the waveform based on the measurement result of the sensor 10 (1) is shown as a solid line, and the waveform based on the measurement result of the sensor 10 (2) is shown as a dotted line. Further, in FIGS. 10A and 10B, the vertical axis represents the frequency and the horizontal axis represents the live load displacement [mm].

The diagnostic unit 20 aggregates the frequency of each displacement amount based on the time series data of the respective live load displacements generated from the measurement results of the two sensors 10 (1) and 10 (2), and FIG. A histogram as shown in (a) and 10 (b) can be generated.

Here, the diagnostic unit 20 uses a histogram generated from the measurement results of any one of the two sensors 10 (1) and 10 (2) as a reference histogram, and generates the histogram from the measurement results of sensors other than one sensor. The histogram can be a diagnostic histogram. Then, the diagnosis unit 20 diagnoses the deterioration of the bridge 30 which is a structure by comparing the reference histogram generated in this time zone with the diagnostic histogram.

In FIG. 8 (b) or FIG. 8 (c) shown above, a case where a crack A or a crack B occurs in the vicinity of the sensor 10 (1) is illustrated. Therefore, in order to make the explanation easy to understand, the histogram generated from the measurement result by the sensor 10 (1) is used as a diagnostic histogram, and the histogram generated from the measurement result by the sensor 10 (2) is used as a reference histogram. However, even if the histogram generated from the measurement result by the sensor 10 (2) is used as the diagnostic histogram and the histogram generated from the measurement result by the sensor 10 (1) is used as the reference histogram, the same deterioration diagnosis can be performed.

The reference histogram and the diagnostic histogram in the steady state shown in FIG. 10A are histograms generated corresponding to the time transition of the live load displacement in the steady state shown in FIG. 9A. The reference histogram and the diagnostic histogram in the deterioration progress state shown in FIG. 10B are histograms generated corresponding to the time transition of the live load displacement in the deterioration progress state shown in FIG. 9B. ..

As is clear from FIG. 10A, the frequency of live load displacement in the steady state is concentrated in the range of 0.02 to 0.03 [mm] in both the reference histogram and the diagnostic histogram. On the other hand, as is clear from FIG. 10 (b), the live load displacement in the deterioration progress state is compared with the live load displacement in the steady state, and the reference histograms are shown in FIGS. 10 (a) and 10 (b). There is no big difference between. On the other hand, with regard to the diagnostic histogram, the mode corresponding to the live load displacement value indicating the peak frequency shifts to the right, and the frequency at the most frequent value becomes smaller, resulting in variations in live load displacement. ..

Therefore, the diagnostic unit 20 monitors the time transition of the mode, and if the difference between the mode in the reference histogram and the mode in the diagnostic histogram deviates from the preset difference tolerance, it deteriorates. It can be determined that it is in progress.

As described in the first embodiment, this difference tolerance is corrected by a preset correction coefficient according to the air temperature when the histogram is generated, and the corrected difference tolerance is used. , Deterioration diagnosis can be carried out. As a result, stable and highly accurate deterioration diagnosis can be realized without being affected by seasonal fluctuations.

As described above, according to the second embodiment, a plurality of time transitions related to the most frequent value of live load displacement generated based on the measurement results of live load displacement by a plurality of sensors installed in the structure are used. Then, it has a configuration for diagnosing the presence or absence of the deterioration progress state of the structure from the mutual comparison result. As a result, as in the first embodiment, the live load displacement can be measured in a shorter monitoring period than in the first embodiment without the need to generate a reference value in advance, and the displacement can be measured during the monitoring period. It is possible to realize a structure deterioration diagnosis system capable of performing a structure deterioration diagnosis with high accuracy based on the live load displacement.

One of the features of the present invention is that live load displacement is used as an index for deterioration diagnosis. On the other hand, as a conventional technique, there is one that uses the natural frequency of a structure as an index for deterioration diagnosis (see, for example, Patent Document 1). Therefore, the merit of diagnosing the deterioration of the structure by using the live load displacement instead of the natural frequency will be supplementarily explained.

FIG. 11 is an explanatory diagram showing the time transition of the natural frequency based on the measurement results of the two sensors in each of the steady state and the deterioration progress state in the conventional structure abnormality detection device. FIG. 11A shows the time transition of the natural frequency based on the measurement results of the two sensors in the steady state where the deterioration has not progressed, and FIG. 11B shows the time transition of the natural frequency in the deteriorated state. The time transition of the natural frequency is shown based on the measurement results of one sensor. The waveforms of FIGS. 11 (a) and 11 (b) correspond to the steady state shown in FIG. 8 (a) and the deterioration progress state shown in FIG. 8 (b) or FIG. 8 (c). It was obtained.

In FIG. 11A, which is a steady state, the natural frequency showing the peak is 11.5 [Hz] for both of the two sensors. On the other hand, in FIG. 11B in the deterioration progress state, the natural frequencies showing peaks are 11.5 [Hz] for both of the two sensors, and the results in the steady state and the deterioration progress state are obtained. There is no significant difference from the results.

That is, as is clear from the results of FIGS. 11 (a) and 11 (b), it is extremely difficult to distinguish the state in which deterioration is progressing from the steady state by the natural frequency. In other words, the effect of deterioration on the natural frequency appears in the final phase of deterioration, and when the natural frequency of the structure is used as an index for deterioration diagnosis, the state in which deterioration is progressing is highly accurate. It was difficult to diagnose with.

On the other hand, in the present invention in which the live load displacement of the structure is used as an index for deterioration diagnosis, as described in the first and second embodiments above, the state in which deterioration is progressing is diagnosed with high accuracy. Is possible.

From the waveforms shown in FIGS. 10 (a) and 10 (b), the statistics corresponding to the steady state and the deterioration progress state are obtained as follows.
<Statistics of live load displacement measured in the steady state of FIG. 10 (a)>
T value: 1.407
P value: 0.160
Mode by sensor 10 (1): 0.025 [mm]
Mode by sensor 10 (2): 0.024 [mm]
Average value by sensor 10 (1): 0.039 [mm]
Average value by sensor 10 (2): 0.039 [mm]

<Statistics of live load displacement measured in the deterioration progress state of FIG. 10B>
T value: -45
P value: 0.0
Mode by sensor 10 (1): 0.025 [mm]
Mode by sensor 10 (2): 0.045 [mm]
Average value by sensor 10 (1): 0.039 [mm]
Average value by sensor 10 (2): 0.076 [mm]

として求められる統計量であり、Ｔ値の絶対値が大きければ「平均値に有意差がありそうだ」と見なすことができる。また、Ｐ値は、Ｔ値を変換して得られる値であり、Ｔ値が大きくなればＰ値は小さくなる関係を有する。そして、一般的には、Ｐ値が０．０５を下回るくらい小さければ、Ｔ値は十分大きいと判断でき、Ｐ値は、Ｔ値の大小判定を定量的に行うために用いられる統計量である。 Here, the T value is

If the absolute value of the T value is large, it can be regarded as "there is a significant difference in the average value". Further, the P value is a value obtained by converting the T value, and the larger the T value, the smaller the P value. In general, if the P value is as small as less than 0.05, it can be determined that the T value is sufficiently large, and the P value is a statistic used to quantitatively determine the magnitude of the T value. ..

As is clear from this result, when the live load displacement of the structure is used as an index for deterioration diagnosis, the state in which deterioration is progressing can be diagnosed with high accuracy even if statistics other than the mode are used. It is possible to do. That is, according to the structure deterioration diagnosis system according to the present invention, by using the live load displacement of the structure as an index of deterioration diagnosis, the deterioration state in the stage before the structure is destroyed is stably and highly accurate. It becomes possible to diagnose with.

Further, in the second embodiment described above, the live load displacement of the structure is used as an index for deterioration diagnosis, and the structure is compared with the reference histogram obtained from the measurement results of the live load displacement by the two sensors and the diagnostic histogram. The case of performing the deterioration diagnosis of is described. On the other hand, it is also possible to obtain the phase characteristics from the measurement results of the amount of shaking acquired by the two sensors, that is, the physical quantity, and perform the deterioration diagnosis of the structure by comparing the reference phase characteristics with the diagnostic phase characteristics. ..

As shown in FIG. 7, the two sensors are installed at regular intervals in the traveling direction of the vehicle 1. Therefore, when comparing the reference phase characteristic generated from the measurement result of the first sensor and the diagnostic phase characteristic generated from the measurement result of the second sensor, one phase characteristic is shifted on the time axis. By doing so, the time difference in which the vehicle 1 passes the position where each sensor is installed is corrected.

By using the phase characteristic of the physical quantity measured in the structure as an index of deterioration diagnosis, it is possible to stably diagnose the deterioration state in the stage before the structure is destroyed with high accuracy.

1 vehicle, 10, 10 (1), 10 (2) sensor, 20 diagnostic unit, 30 bridge (structure), 31, 31a, 31b, 31b main girder (structure).

Claims (5)

Two or more sensors installed on a structure to measure the live load displacement of the structure due to the live load, and
Time-series data of the live-load displacement is generated by sequentially acquiring the live-load displacement measured by each of the two or more sensors with the passage of time, and a histogram regarding the live-load displacement is obtained from the time-series data. The histogram generated from the measurement result of any one sensor is used as a reference histogram, the histogram generated from the measurement result of a sensor other than the one sensor is used as a diagnostic histogram, and the reference histogram generated at the same time is used. A structure deterioration diagnosis system including a diagnostic unit that diagnoses deterioration of the structure by comparison with the histogram for diagnosis. Two or more sensors installed on a structure to measure the physical quantity of the structure,
The phase characteristic of the physical quantity measured by each of the two or more sensors is generated, the phase characteristic generated from the measurement result by any one sensor is used as the reference phase characteristic, and the measurement result by a sensor other than the one sensor is used. A structure characterized in that the generated phase characteristic is used as a diagnostic phase characteristic, and a diagnostic unit that diagnoses deterioration of the structure by comparing the reference phase characteristic generated in the same time zone with the diagnostic phase characteristic is provided. Material deterioration diagnosis system. The structure deterioration diagnosis system according to claim 1 or 2, wherein at least one of the two or more sensors is installed at a quartile in the structure of the structure. Claims 1 to 3, wherein the two or more sensors are configured as three or more sensors and are installed at two quartiles in the structure of the structure and in the center of the structure. The structure deterioration diagnosis system according to any one item. The diagnostic unit corrects the measurement result by a correction coefficient set in advance according to the installation position of each of the two or more sensors, and performs the deterioration diagnosis of the structure by the comparison using the corrected value. The structural deterioration diagnosis system according to any one of claims 1 to 4, wherein the structure deterioration diagnosis system is characterized.

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