JP7287858B2 - Structural deterioration diagnosis system - Google Patents

Description

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

For example, a structure corresponding to a bridge over which vehicles pass gradually deteriorates due to secular change associated with the passage of vehicles. For structures such as bridges, it is important to detect the state of deterioration before they collapse.

As a conventional technique for diagnosing deterioration of a bridge, there is a bearing abnormality inspection device that detects abnormality in 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 performs bearing abnormality detection in the following procedure.
(1) A reference value, which is a characteristic value relating to the shaking of the bridge and serves as a reference, is stored in advance.
(2) A sensor is used to acquire an acquired value, which is a characteristic value relating to the shaking of the bridge.
(3) Bearing abnormality detection is performed based on the difference between the reference value and the acquired value.

Japanese Patent Application Laid-Open No. 2019-31830 WO2017/064854

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 known weight and collect data. Therefore, it takes time and effort to generate the reference value.

Moreover, if the bridge has already begun to deteriorate when the reference value is generated, the reference value itself lacks reliability, and there is a risk that accurate diagnosis of deterioration cannot be performed.

SUMMARY OF THE INVENTION The present invention has been made to solve the above-mentioned problems. It is an object of the present invention to obtain a structural deterioration diagnosis system capable of diagnosing the deterioration of a building.

A structural deterioration diagnosis system according to the present invention includes two or more sensors installed in a structure for measuring the live load displacement of the structure due to the live load, and measuring the live load displacement measured by each of the two or more sensors over time. Generate time-series data of live load displacement by acquiring sequentially over time, generate a histogram on live load displacement from the time-series data, and use the histogram generated from the measurement results of any one sensor as a reference histogram, A diagnostic unit for diagnosing deterioration of a structure by comparing a histogram generated from the measurement results of sensors other than one sensor as a diagnostic histogram and comparing the reference histogram generated in the same time period with the diagnostic histogram. .

According to the present invention, there is provided a structural deterioration diagnosis system capable of highly accurately diagnosing structural deterioration based on live load displacement measured during a monitoring period without the need to generate reference values in advance. Obtainable.

1 is a configuration diagram of a structural deterioration diagnosis system according to Embodiment 1 of the present invention; FIG. FIG. 2 is an explanatory diagram showing a state in which sensors are installed in a structure to be diagnosed by the structural deterioration diagnosis system according to Embodiment 1 of the present invention; FIG. 4 is an explanatory diagram showing time transition of live load displacement in each of a steady state and a state of progress of deterioration in Embodiment 1 of the present invention. FIG. 4 is an explanatory diagram showing histograms of live load displacement in each of a steady state and a deterioration advancing state in Embodiment 1 of the present invention; FIG. 4 is an explanatory diagram showing temporal transition of a mode value obtained from a live load displacement histogram according to Embodiment 1 of the present invention; FIG. 2 is a configuration diagram of a structural deterioration diagnosis system according to Embodiment 2 of the present invention; FIG. 9 is an explanatory diagram showing a state in which a sensor is installed on a structure to be diagnosed by the structural deterioration diagnostic system according to Embodiment 2 of the present invention; FIG. 9 is an explanatory diagram showing a comparison between a steady state and a deterioration progression state in deterioration diagnosis using two sensors according to Embodiment 2 of the present invention; FIG. 9 is an explanatory diagram showing temporal transition of live load displacement based on measurement results of two sensors in each of a steady state and a deterioration progress state in Embodiment 2 of the present invention; FIG. 9 is an explanatory diagram showing histograms of live load displacement based on the measurement results of two sensors in each of the steady state and the progressing state of deterioration in the second embodiment of the present invention; FIG. 10 is an explanatory diagram showing temporal transition of the natural frequency based on measurement results of two sensors in each of the steady state and the progressing state of deterioration in the conventional structural abnormality detection device.

BEST MODE FOR CARRYING OUT THE INVENTION Preferred embodiments of the structural deterioration diagnosis system of the present invention will be described below with reference to the drawings.
The present invention enables highly accurate monitoring of the deterioration state of a structure to be diagnosed based on time-series data of live load displacement measured during deterioration diagnosis without the need to generate reference values in advance. It is a characteristic feature.

Embodiment 1.
In the first embodiment, a case of diagnosing the deterioration of a structure based on the measurement result of one sensor will be described.

FIG. 1 is a configuration diagram of a structural deterioration diagnosis system according to Embodiment 1 of the present invention. The structural deterioration diagnostic system according to Embodiment 1 is configured with one sensor 10 and a diagnostic unit 20 .

Moreover, FIG. 2 is an explanatory diagram showing a state in which the sensor 10 is installed on a structure to be diagnosed by the structural deterioration diagnosis system according to Embodiment 1 of the present invention. 2 shows a bridge 30 as a concrete example of the structure, FIG. 2(a) is a side view of the bridge 30, and FIG. 2(b) is a rear view of the bridge 30.

The bridge 30 gradually deteriorates due to secular change associated with 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 of the sensor 10 installed at a position suitable for deterioration diagnosis, so that the deterioration of the bridge 30 that changes from moment to moment Diagnose the condition.

Specifically, the sensor 10 is installed on a main girder 31 that 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. 2(b), the main girder 31 is configured as three main girders 31a, 31b, and 31c, for example. The example of FIG. 2(b) illustrates the case where the sensor 10 is installed at the central portion of the main girder 31b (that is, the central portion of the span corresponding to the distance between the left and right bearings 2). This installation position corresponds to an example of a position suitable for deterioration diagnosis.

In the following description, a case of diagnosing deterioration based on the detection result of one sensor 10 will be described. However, as for the sensor 10 itself, one sensor may be installed at a position different from that in 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 a load whose magnitude is not constant but whose acting position changes. In addition to the weight of the vehicle 1 passing through the bridge 30, factors that cause such a live load to be displaced include the dead weight of the bridge 30 itself and the inertial force acting on the bridge 30 due to an earthquake.

The sensors 10 include those that directly measure live load displacement (for example, displacement sensors) and those that convert the detection results of physical quantities into live load displacements and output them as measurement results (for example, acceleration sensors). included.

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

As described above, the structural deterioration diagnostic system according to the first embodiment can perform the following operations based on the time-series data indicating the live load displacement that changes from moment to moment during the monitoring period without the need to generate the reference value in advance. , the bridge 30 has a technical feature of diagnosing deterioration. Therefore, a concrete deterioration diagnosis method executed by the diagnosis unit 20 will be described in detail below.

FIG. 3 is an explanatory diagram showing time transition of live load displacement in each of the steady state and the progressing state of deterioration in Embodiment 1 of the present invention. FIG. 3(a) shows the time transition of the live load displacement in a steady state where deterioration does not progress, and FIG. 3(b) shows the time transition of the live load displacement in the advanced deterioration state. In FIGS. 3A and 3B, the vertical axis represents live load displacement [mm] and the horizontal axis represents time [H].

The monitoring period shall be set according to the traffic volume to be monitored. For example, the period can be changed as appropriate, such as a period of integral multiples of a calendar unit such as one week or one month. ing.

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

The amount of displacement of the live load in the steady state shown in FIG. 3(a) is within a relatively small value range. On the other hand, the amount of displacement of the live load in the state of progress of deterioration shown in FIG.

FIG. 4 is an explanatory diagram showing histograms of live load displacement in each of the steady state and the progressing deterioration state in Embodiment 1 of the present invention. FIG. 4(a) shows a histogram of live load displacement generated based on the time-series data of live load displacement in a steady state where deterioration does not progress, and FIG. FIG. 4 shows a live load displacement histogram generated based on live load displacement time series data; FIG. In FIGS. 4A and 4B, the vertical axis represents frequency, and the horizontal axis represents live load displacement [mm].

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

As is clear from FIG. 4(a), the frequency of occurrence of the 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. 4(b), the live load displacement in the progressing state of deterioration corresponds to the value of the live load displacement showing the peak of frequency when compared with the live load displacement in the steady state. As the value shifts to the right side, the frequency of the mode value becomes smaller, and the live load displacement becomes uneven. Therefore, the diagnosis unit 20 can monitor the temporal transition of the mode value, and determine that the deterioration is progressing when the mode value deviates from a preset allowable range.

FIG. 5 is an explanatory diagram showing the temporal transition of the mode obtained from the live load displacement histogram according to the first embodiment of the present invention. In FIG. 5, when the mode of the live load displacement is within the range of 0.020 [mm] to 0.028 [mm], it is preset as an allowable range where deterioration does not progress. is exemplified. The diagnosing unit 20 can specify the mode value of the histogram of live load displacement along with the time transition, and diagnose the deterioration of the bridge 30 based on the comparison between the mode value and the allowable threshold value.

In the example shown in FIG. 5, deterioration detection is performed when the current mode value deviates from the allowable 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 period during the monitoring period as the reference value, and detect deterioration from the difference between the current mode value and the reference value. 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 live load displacement generated in the first time period, and generates a first mode value indicating a mode value in the first histogram. identify. This first time period corresponds to the time period included in the steady state.

Next, the diagnosis unit 20 generates a second histogram as a histogram based on the time-series data of the live load displacement generated in the second time period after the first time period. Identify a second mode that indicates the mode in . This second time period corresponds to the current time period during which monitoring is being performed.

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 a preset difference allowable range. Diagnose.

In addition, in order to specify the first mode value as the reference value, it is a prerequisite that the first mode value is within the allowable range described above. Moreover, the first mode value, which is the reference value, may be calculated only once or may be updated periodically, and it is not necessary to repeatedly calculate each time the second mode value is calculated.

In this way, even if the reference value is specified from the histogram mode value during the monitoring period, it is possible to diagnose the deterioration of the structure with high accuracy without the need to generate the reference value in advance. effect can be achieved.

Further, it is conceivable that the live load displacement used as an index for deterioration diagnosis in the first embodiment varies depending on the season and climate. In particular, live load displacement is affected by air temperature. Therefore, a supplementary explanation will be given on countermeasures against this seasonal variation.

The stiffness of the material of the bridge 30, which is the target of deterioration diagnosis, generally changes due to changes in temperature. Specifically, the stiffness is lower in summer when the temperature is high, and the stiffness is higher in the winter when the temperature is low. Therefore, depending on the season and climate, the live load displacement may differ even if the live load with the same weight is applied.

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

Therefore, in order to cope with such fluctuations in live load displacement due to air temperature, the diagnostic unit 20 corrects the allowable threshold value or the allowable difference range using a preset correction coefficient according to the air temperature when the histogram was generated. , the corrected allowable threshold value or the difference allowable range can be used to perform degradation diagnosis. This makes it possible to realize stable and highly accurate deterioration diagnosis without being affected by seasonal fluctuations.

The effect of using the mode value as an index for diagnosing structural deterioration will be supplemented. If the average value is used as an index for diagnosing the deterioration of structures, the result will fluctuate simply by changing the distribution of vehicle sizes, such as small or large vehicles, depending on traffic conditions, making it difficult to make comparisons. . Generally, the traffic volume of small vehicles is larger than that of large vehicles.

Moreover, even if the ratio of small vehicles to large vehicles changes somewhat, it is unlikely that the vertical relationship between the traffic volume of large vehicles and small vehicles will change in the long term. Therefore, by using the mode as an index for diagnosing structural deterioration, it is possible to identify the distribution of small vehicles with the highest traffic volume. It becomes possible to diagnose deterioration.

As described above, according to Embodiment 1, the time transition of the mode value of live load displacement generated based on the measurement result of live load displacement by one sensor installed in the structure is used. , and a configuration for diagnosing the presence or absence of a progressing state of deterioration of the structure.

As described in detail in the first embodiment, specific deterioration diagnosis methods include the following.
・Using the time transition of the mode of live load displacement generated sequentially during the monitoring period, the deterioration diagnosis of the structure is performed based on the comparison between the mode and the preset allowable threshold.
・The mode of live load displacement generated for the past data during the monitoring period is set as the first mode, and the maximum value of live load displacement generated for the current data during the subsequent monitoring period. By determining whether or not a significant difference that deviates from the allowable threshold occurs between the first mode value and the second mode value with the frequent value as the second mode value, Perform deterioration diagnosis.

As a result, it is possible to realize a structure deterioration diagnosis system capable of highly accurately diagnosing the deterioration of a structure based on the live load displacement measured during the monitoring period without the need to generate a reference value in advance.

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

FIG. 6 is a configuration diagram of a structural deterioration diagnosis system according to Embodiment 2 of the present invention. The structural deterioration diagnosis system according to Embodiment 2 is configured with two sensors 10 ( 1 ) and 10 ( 2 ) and a diagnosis section 20 .

Moreover, FIG. 7 is an explanatory diagram showing a state in which the sensor 10 is installed on a structure to be diagnosed by the structural deterioration diagnosis system according to Embodiment 2 of the present invention. 7 shows a bridge 30 as a specific example of the structure, FIG. 7(a) being a side view of the bridge 30, and FIG. 7(b) being a rear view of the bridge 30. As shown in FIG.

In Embodiment 2, sensors 10 ( 1 ) and 10 ( 2 ) are installed on main girders 31 that are components of bridge 30 . Here, the main girder 31 corresponds to the structure of the structure to be diagnosed. As shown in FIG. 7(b), the main girder 31 is configured as three main girder 31a, 31b, and 31c as an example. In the example of FIG. 7(b), 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). 1/4 and 3/4 of the span). The quartile, which is the installation position, corresponds to an example of a position suitable for deterioration diagnosis.

In the following description, a case will be described in which deterioration diagnosis is performed based on detection results from two sensors 10(1) and 10(2) installed on the main girder 31b. However, the sensors 10 themselves 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 position of each sensor 10 with the detection results of other sensors. . Also, the sensors 10 themselves may be installed on the respective main girders 31a, 31b, 31c.

The structural deterioration diagnostic system according to the second embodiment does not need to generate a reference value in advance, and during the monitoring period, the In addition, it is technically characterized in that the deterioration diagnosis of the bridge 30 is performed based on two pieces of time-series data indicating live load displacement that changes from moment to moment. Therefore, a concrete deterioration diagnosis method executed by the diagnosis unit 20 will be described in detail below.

FIG. 8 is an explanatory diagram showing a comparison between a steady state and a progressing state of deterioration in deterioration diagnosis using two sensors according to Embodiment 2 of the present invention. FIG. 8(a) shows the steady state, and FIGS. 8(b) and 8(c) show the progress of deterioration. 8(b) and (c) show a state in which a crack A or a crack B has occurred in the main girder 31 of the bridge 30 in the vicinity of the sensor 10(1) and deterioration is progressing. 9 to 12 for a specific method of detecting the state of progress of deterioration shown in FIG. 8(b) or 8(c) using two sensors 10(1) and 10(2). will be described below.

FIG. 9 shows time transition of live load displacement based on the measurement results of the two sensors 10(1) and 10(2) in the steady state and the progressing deterioration state, respectively, in the second embodiment of the present invention. It is an explanatory diagram. FIG. 9(a) shows the time transition of live load displacement based on the measurement results of the two sensors 10(1) and 10(2) in a steady state where deterioration is not progressing, and FIG. 9(b). ) 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 progressing state of deterioration.

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

The diagnosis unit 20 sequentially acquires the live load displacement measured by each of the sensor 10(1) and the sensor 10(2) at a predetermined sampling period, thereby obtaining the values shown in FIGS. Time-series data of live load displacement is generated as data corresponding to the time transition of live load displacement shown in .

The live load displacement amounts corresponding to the sensors 10(1) and 10(2) in the steady state shown in FIG. . On the other hand, the live load displacement amounts corresponding to 10(1) and 10(2) in the state of progress of deterioration shown in FIG. 9(b) 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 in the steady state, and over time The accompanying dispersion of the live load displacement is remarkable. On the other hand, the amount of displacement of the live load corresponding to the sensor 10(2) installed at a location distant from the generated crack A exhibits behavior equivalent to that in the steady state.

That is, the live load displacement time-series data based on the measurement results of the sensor 10(1) is affected by the crack A shown in FIG. 8(b) or the crack B shown in FIG. have changed compared to the time series data in On the other hand, the live load displacement time-series data based on the measurement results of the sensor 10(2) is not easily affected by the crack A shown in FIG. 8(b) or the crack B shown in FIG. 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 the steady state and the progressing state of deterioration, respectively, in the second embodiment of the present invention. It is a diagram. FIG. 10(a) shows a histogram of live load displacement generated based on time-series data of live load displacement in a steady state where deterioration does not progress. On the other hand, FIG. 10(b) shows a histogram of live load displacement generated based on time-series data of live load displacement in the progressing state of deterioration.

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

Based on the time-series data of each live load displacement generated from the measurement results of the two sensors 10(1) and 10(2), the diagnosis unit 20 aggregates the frequency of each displacement amount, thereby A histogram such as that shown in (a) and FIG. 10(b) can be generated.

Here, the diagnostic unit 20 uses a histogram generated from the measurement results of 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 the one sensor. The histogram can be a diagnostic histogram. Then, the diagnosis unit 20 performs deterioration diagnosis of the bridge 30, which is a structure, by comparing the reference histogram generated in the same time period with the diagnostic histogram.

FIG. 8(b) or FIG. 8(c) shown above illustrates the case where crack A or crack B occurs in the vicinity of sensor 10(1). Therefore, in order to make the explanation easier to understand, the histogram generated from the measurement results by the sensor 10(1) will be referred to as a diagnostic histogram, and the histogram generated from the measurement results by the sensor 10(2) will be referred to 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, similar deterioration diagnosis can be performed.

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

As is clear from FIG. 10(a), the frequency of occurrence of the 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 progressing state of deterioration is compared with the live load displacement in the steady state with respect to the reference histogram in FIGS. 10(a) and 10(b). There is no big difference between On the other hand, regarding the histogram for diagnosis, the mode value corresponding to the value of the live load displacement indicating the frequency peak shifts to the right, and the frequency at the mode value becomes smaller, causing variations in the live load displacement. .

Therefore, the diagnosis unit 20 monitors the temporal transition of the mode value, and if the difference between the mode value in the reference histogram and the mode value in the diagnostic histogram deviates from a preset difference allowable range, the deterioration It can be determined that it is in progress.

Note that, as described in the first embodiment, this allowable difference range is corrected by a preset correction coefficient according to the temperature when the histogram is generated, and the allowable difference range after correction is used. , degradation diagnosis can be performed. This makes it possible to realize stable and highly accurate deterioration diagnosis without being affected by seasonal fluctuations.

As described above, according to the second embodiment, a plurality of time transitions of the mode value of live load displacement generated based on the measurement results of live load displacement by a plurality of sensors installed in a structure are used. Then, the presence or absence of the progress of deterioration of the structure is diagnosed from the mutual comparison results. As a result, as in the first embodiment, 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. It is possible to realize a structure deterioration diagnosis system capable of diagnosing the deterioration of a structure with high accuracy based on the live load displacement obtained.

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

FIG. 11 is an explanatory diagram showing the temporal transition of the natural frequency based on the measurement results of the two sensors in each of the steady state and the progressing state of deterioration in the conventional structural abnormality detection device. FIG. 11(a) shows the time transition of the natural frequency based on the measurement results of the two sensors in the steady state where deterioration is not progressing, and FIG. It shows the time transition of the natural frequency based on the measurement results of two sensors. The waveforms of FIGS. 11(a) and 11(b) correspond to the steady state shown in FIG. 8(a) and the deterioration progression state shown in FIG. 8(b) or 8(c). It is obtained.

In FIG. 11A, which is the steady state, the natural frequencies showing the peaks of the two sensors are both 11.5 [Hz]. On the other hand, in FIG. 11(b) showing the state of progress of deterioration, the natural frequencies showing peaks are both 11.5 [Hz] for the two sensors. No significant difference is seen between 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 based on the natural frequency. In other words, the effect of deterioration appears on the natural frequency only in the final stage of deterioration. was difficult to diagnose.

In contrast, in the present invention, which uses the live load displacement of a structure as an index for diagnosing deterioration, as described in the first and second embodiments, it is possible to diagnose with high accuracy the state in which deterioration is progressing. is possible.

From the waveforms shown in FIGS. 10(a) and 10(b), the statistics corresponding to the steady state and the progressing state of deterioration are obtained as follows.
<Statistics of Live Load Displacement Measured in Steady State in FIG. 10(a)>
T value: 1.407
P-value: 0.160
Mode value by sensor 10 (1): 0.025 [mm]
Mode value 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 Progress of Deterioration in FIG. 10(b)>
T value: -45
P-value: 0.0
Mode value by sensor 10 (1): 0.025 [mm]
Mode value 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。 where the T value is

If the absolute value of the T value is large, it can be considered that "the average value is likely to have a significant difference". Also, the P value is a value obtained by converting the T value, and there is a relationship that the larger the T value, the smaller the P value. And, 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 these results, when the live load displacement of a structure is used as an index for diagnosing deterioration, even if statistics other than the mode value are used, the progressing state of deterioration can be diagnosed with high accuracy. It is possible to That is, according to the structural deterioration diagnosis system according to the present invention, by using the live load displacement of the structure as an indicator for deterioration diagnosis, the deterioration state of the structure before it breaks down can be stably and accurately detected. can be diagnosed.

In the second embodiment described above, the live load displacement of the structure is used as an index for diagnosing deterioration. The case of diagnosing the deterioration of the On the other hand, it is also possible to determine the phase characteristics from the amount of shaking acquired by the two sensors, that is, the measurement result of the physical quantity, and to diagnose the deterioration of the structure by comparing the reference phase characteristics and the diagnostic phase characteristics. .

The installation positions of the two sensors are separated by a constant distance in the traveling direction of the vehicle 1, as shown in FIG. 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 positions where the respective sensors are installed is corrected.

By using the phase characteristic of the physical quantity measured in the structure as an index for diagnosing deterioration, it is possible to stably and highly accurately diagnose the state of deterioration of the structure before it breaks down.

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 mounted on a structure to measure the live load displacement of the structure due to the live load;
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 over time, and a histogram of the live load displacement is generated from the time series data. A histogram generated from the measurement results of any one sensor is used as a reference histogram, a histogram generated from measurement results of sensors other than the one sensor is used as a diagnostic histogram, and the reference histogram generated in the same time zone A structure deterioration diagnosis system, comprising: a diagnosis unit that diagnoses deterioration of the structure by comparison with the diagnosis histogram. two or more sensors installed in a structure to measure physical quantities of the structure;
generating the phase characteristic of the physical quantity measured by each of the two or more sensors, using the phase characteristic generated from the measurement result by any one sensor as the reference phase characteristic, and using the measurement result by the sensor other than the one sensor a diagnostic unit that uses the generated phase characteristic as a diagnostic phase characteristic, and performs deterioration diagnosis of the structure by comparing the reference phase characteristic and the diagnostic phase characteristic generated in the same time period. Deterioration diagnosis system. 3. The structural deterioration diagnostic system according to claim 1, wherein at least one of said two or more sensors is installed at a quartile point in the structure of said structure. 4. The method according to any one of claims 1 to 3, wherein the two or more sensors are configured as three or more sensors and installed at two quartile points in the structure of the structure and at the center of the structure. The structural deterioration diagnosis system according to any one of claims 1 to 3. The diagnosis 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, characterized in that:

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