Deterioration diagnosis system

Abstract

To obtain a degradation diagnosis system with which it is possible to suppress a rise of manufacturing cost and detect the degradation of a point with high accuracy at which a change of natural vibration hardly shows up.SOLUTION: The degradation diagnosis system comprises a sensor head that detects the physical quantity for conducting degradation diagnosis and is installed to a structure, and a diagnosis unit for performing the degradation diagnosis of the structure on the basis of the physical quantity. The structure is supported by a bearing that is provided outside of a quartile point, and the sensor head is installed between the quartile point and the bearing. The diagnosis unit calculates, from the physical quantity detected by the sensor head, the inclination information of the structure as a feature quantity that constitutes a first index to the degradation diagnosis of the structure, causes a storage unit to store the inclination information as time-series data successively with the passage of time, extracts a past feature quantity from among the time-series data stored in the storage unit, and determines that there is occurrence of degradation in the structure when there exists a preset significant difference between the past feature quantity and the present feature quantity.SELECTED DRAWING: Figure 3

Description

[Technical field]

[0001] The present disclosure relates to a deterioration diagnosis system that diagnoses deterioration of a structure such as a bridge. [Background technology]

[0002] As a conventional technique for detecting abnormalities in a structure, there is a structural abnormality detection system that uses a natural frequency as a feature for detecting an abnormality (see, for example, Patent Document 1). The system according to Patent Document 1 detects an abnormality by evaluating the relationship between multiple positions regarding the vibration intensity of the natural frequency. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] International Publication No. 2017 / 064855 Summary of the Invention [Problem to be solved by the invention]

[0004] However, the conventional techniques have the following problems. In Patent Document 1, deterioration of a structure can be detected based on a change in the natural frequency. However, when deterioration occurs near a node of the vibration form, the effect on the natural frequency is small, and the change in the natural frequency is difficult to detect.

[0005] In such a case, therefore, there is a problem that the deterioration cannot be detected with high accuracy based on the change in the natural vibration. Moreover, in order to avoid such a problem, a large number of sensors are required, which leads to an increase in manufacturing costs.

[0006] The present disclosure has been made to solve the above-mentioned problems, and aims to provide a deterioration diagnosis system that can suppress increases in manufacturing costs and detect deterioration in areas where changes in natural vibration are less likely to occur with high accuracy. [Means for solving the problem]

[0007] The deterioration diagnosis system according to the present disclosure comprises a sensor head that is installed in a structure and detects a physical quantity for performing deterioration diagnosis of the structure, and a diagnosis unit that performs deterioration diagnosis of the structure based on the physical quantity detected by the sensor head, the structure being supported by a support provided outside a quartile in a structural member of the structure, the sensor head being installed between the quartile and the support, the diagnosis unit calculating tilt information of the structure as a feature amount from the physical quantity detected by the sensor head, which is a first indicator for deterioration diagnosis of the structure, storing the calculated tilt information as time-series data in a memory unit sequentially over time, extracting past feature amounts from the time-series data sequentially stored in the memory unit, and if a predetermined significant difference exists between the past feature amount and the current feature amount, From the time change of the tilt information calculated from the detection result of one sensor head Determining that deterioration has occurred in a structure can It is something. Effect of the Invention

[0008] According to the present disclosure, it is possible to obtain a degradation diagnosis system that can suppress increases in manufacturing costs and can detect degradation in areas where changes in natural vibration are unlikely to occur with high accuracy. [Brief description of the drawings]

[0009] [Figure 1] 2 is an explanatory diagram showing an installation position of a sensor head used in the degradation diagnosis system according to the first embodiment of the present disclosure. FIG. [Diagram 2] FIG. 2 is an explanatory diagram showing a change in inclination when damage due to a crack occurs near the center of a bridge in the first embodiment of the present disclosure. [Diagram 3] 1 is a configuration diagram of a degradation diagnosis system according to a first embodiment of the present disclosure. [Figure 4A] FIG. 2 is an explanatory diagram showing a change in tilt information over time when damage due to a crack occurs near the center of a bridge in the first embodiment of the present disclosure. [Figure 4B]FIG. 11 is an explanatory diagram showing a change in gradient information over time when damage due to a crack occurs near a quartile of a bridge in the first embodiment of the present disclosure. [Figure 4C] FIG. 2 is an explanatory diagram showing a change in tilt information over time when damage due to a crack occurs near a bridge support in the first embodiment of the present disclosure. [Figure 5A] FIG. 11 is an explanatory diagram showing a time change in natural vibration information when damage due to a crack occurs near the center of a bridge in the second embodiment of the present disclosure. [Figure 5B] FIG. 11 is an explanatory diagram showing a time change in natural vibration information when damage due to a crack occurs near a quartile of a bridge in the second embodiment of the present disclosure. [Figure 5C] FIG. 11 is an explanatory diagram showing a time change in natural vibration information when damage due to a crack occurs near a bridge support in the second embodiment of the present disclosure. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] Hereinafter, preferred embodiments of the degradation diagnosis system of the present disclosure will be described with reference to the drawings. The present disclosure has a technical feature in which a structure supported by a support located outside a quartile in the structure of the structure is targeted for deterioration diagnosis, a sensor head is installed between the quartile and the support, tilt information of the structure which serves as an index for deterioration diagnosis of the structure is calculated as a feature value from physical quantities detected by the sensor head, and deterioration diagnosis of the structure is performed from changes in the tilt information over time.

[0011] Embodiment 1 In this embodiment 1, as a specific example of installing a sensor head on the structural components of a structure, a deterioration diagnosis of the structure is described based on a comparison of measurement results from two sensor heads installed on the main girders of a bridge that corresponds to the structure.

[0012] Although details will be described later, the number of sensor heads may be other than 2. By providing one sensor head, it is possible to determine whether or not deterioration has occurred, and by providing two or more sensor heads, it is possible to further identify the location where deterioration has occurred.

[0013] 1 is an explanatory diagram showing the installation positions of sensor heads used in a deterioration diagnosis system according to a first embodiment of the present disclosure. A bridge 10, which corresponds to a structure, is supported by a bearing 12(1) provided outside a quartile 11(1) in the structural body of the bridge 10, and a bearing 12(2) provided outside a quartile 11(2).

[0014] Each of sensor heads 20(1) and 20(2) is installed on bridge 10 and detects physical quantities for diagnosing deterioration of bridge 10. Here, sensor head 20(1) is installed between quartile point 11(1) and bearing 12(1), and sensor head 20(2) is installed between quartile point 11(2) and bearing 12(2).

[0015] That is, the sensor head 20(1) and the sensor head 20(2) are installed on the side of the support 12(1) and the support 12(2), which are on the outer side beyond the quarter point when viewed from the center of the bridge 10 structure.

[0016] Since structures have elasticity, they deflect under their own weight. When deterioration or damage occurs between the supports, the deflection becomes larger. However, in a structure such as bridge 10, the change in the inclination of the structure that occurs when the deflection becomes larger due to damage is not constant between the supports due to the elasticity of the structure, but varies depending on the position of the structure.

[0017] 2 is an explanatory diagram showing a change in inclination when damage due to a crack 1 occurs near the center of a bridge 10 in the first embodiment of the present disclosure. Fig. 2(a) shows a state in which damage has occurred near the center such that the bridge 10 is completely divided. Such a state occurs due to the continued progression of deterioration or the occurrence of a major earthquake or disaster.

[0018] In this case, the repair cost of the structure is high. On the other hand, Fig. 2(b) shows the initial state of damage before the bridge 10 is completely severed. This state occurs when deterioration progresses gradually due to corrosion, etc. If the structure is repaired at this stage, the repair cost is much smaller than the repair cost after the structure is severed, so there is a great advantage in detecting deterioration at an early stage.

[0019] In a state where a structure is separated between supports as shown in Figure 2(a), the change in inclination tends to be greater the closer to the damaged part. On the other hand, in a damaged state as shown in Figure 2(b) before the structure is completely separated, the change in inclination at the center of bridge 10 is small, while the change in inclination near supports 12(1) and 12(2) is large. Therefore, even if a sensor head is installed in the center, it is difficult to detect the gradual deterioration from the change in inclination.

[0020] On the other hand, by installing the sensor head 20(1) and the sensor head 20(2) at the above positions, it is possible to detect damage to a structure such as the bridge 10 at an early stage of the damage. In other words, it is possible to detect damage to the structure with higher sensitivity.

[0021] Furthermore, even if the deterioration does not occur in the center but in the quartiles where cracks between the supports are more likely to occur, the change in slope will be larger at sensor head 20(1) and sensor head 20(2), or at positions closer to the supports than at the center.

[0022] Note that Figures 2(a) and 2(b) show a schematic diagram of a state in which a crack 1 has occurred near the center of bridge 10, while Figure 1 shows a schematic diagram of a state in which damage caused by crack 1 has occurred and deterioration is progressing between quartile 11(1) and support 12(1).

[0023] Next, a specific configuration of the degradation diagnosis system according to the first embodiment will be described with reference to Fig. 3, which corresponds to the explanatory diagram of Fig. 1. Fig. 3 is a configuration diagram of the degradation diagnosis system according to the first embodiment of the present disclosure. The degradation diagnosis system in the first embodiment is configured to include two sensor heads 20(1) and 20(2), a diagnosis unit 30, and a storage unit 40.

[0024] The diagnosis unit 30 corresponds to a controller that performs deterioration diagnosis of the bridge 10, which is a structure, based on the physical quantities detected by the sensor heads 20(1) and 20(2). The diagnosis unit 30 calculates, from the physical quantities detected by one or more sensor heads 20, tilt information of the structure, which is a first index for bridge deterioration diagnosis, as a feature quantity.

[0025] Next, the diagnosis unit 30 sequentially stores the calculated tilt information as time passes in the storage unit 40 as time-series data. Furthermore, the diagnosis unit 30 extracts past feature amounts from the time-series data sequentially stored in the storage unit 40, and determines whether or not a significant difference set in advance exists between the past feature amounts and the current feature amounts. If the diagnosis unit 30 determines that a significant difference exists, it determines that deterioration has occurred in the bridge 10.

[0026] Particularly, in this embodiment 1, tilt information of a structure is used as the feature amount. Therefore, a degradation diagnosis method based on tilt information will be described in detail using a specific example shown in Fig. 4A to Fig. 4C.

[0027] 4A is an explanatory diagram showing a time change in tilt information when damage due to crack 1 occurs near the center of bridge 10 in embodiment 1 of the present disclosure. The line graph in Fig. 4A shows the time change in tilt associated with the progression of damage as time-series data, with the horizontal axis representing the time course showing the progress of damage and the vertical axis representing the tilt.

[0028] The diagnosis unit 30 calculates first tilt information, which is one of the feature quantities, from the physical quantity detected by the sensor head 20(1), and stores the first tilt information sequentially over time as first time-series data in the storage unit 40. In the line graph of Fig. 4A, each data indicated by a ▲ plot on the dotted line corresponds to the first time-series data.

[0029] Similarly, the diagnosis unit 30 calculates second tilt information, which is one of the feature quantities, from the physical quantity detected by the sensor head 20(2), and stores the second tilt information sequentially over time as second time-series data in the storage unit 40. In the line graph of Fig. 4A, each data indicated by a ● plot on the solid line corresponds to the second time-series data.

[0030] When damage due to crack 1 occurs near the center of bridge 10, as shown in Figure 4A, the time change in the slope based on the first time series data and the time change in the slope based on the second time series data are opposite in positive and negative, and the absolute value of the slope changes at approximately the same rate over time.

[0031] Therefore, the diagnosis unit 30 can determine that deterioration has occurred when a predetermined significant difference exists between the slope, which is a past characteristic amount, and the slope, which is a current characteristic amount, based on either the first time series data calculated based on the physical amount detected by the sensor head 20(1) or the second time series data calculated based on the physical amount detected by the sensor head 20(2).

[0032] For example, in Figure 4A, if the past time is taken as time 0 on the horizontal axis and the current time is taken as time 6 on the horizontal axis, the diagnosis unit 30 can determine that crack 1 has occurred if the difference in slope at each time is greater than or equal to a predetermined significant difference.

[0033] Furthermore, the diagnostic unit 30 compares the time changes of the first time series data calculated based on the physical quantities detected by the sensor head 20(1) and the second time series data calculated based on the physical quantities detected by the sensor head 20(2), and if it determines that the positive and negative values ​​are opposite and that the absolute values ​​of the slopes change at the same rate over time, it can determine that damage due to crack 1 has occurred near the center of the bridge 10, and identify the location of the deterioration.

[0034] Fig. 4B is an explanatory diagram showing a time change in slope information when damage due to crack 1 occurs near quartile 11(1) of bridge 10 in embodiment 1 of the present disclosure. Similar to Fig. 4A, the line graph in Fig. 4B shows the time change in slope accompanying the progression of damage as time-series data, with the horizontal axis representing the progress of damage and the vertical axis representing the slope.

[0035] The diagnosis unit 30 calculates first tilt information, which is one of the feature quantities, from the physical quantity detected by the sensor head 20(1), and stores the first tilt information sequentially over time as first time-series data in the storage unit 40. In the line graph of FIG. 4B, each data indicated by a ▲ plot on the dotted line corresponds to the first time-series data.

[0036] Similarly, the diagnosis unit 30 calculates second tilt information, which is one of the feature quantities, from the physical quantity detected by the sensor head 20(2), and stores the first tilt information sequentially over time as second time-series data in the storage unit 40. In the line graph of Fig. 4B, each data indicated by a ● plot on the solid line corresponds to the second time-series data.

[0037] When damage due to crack 1 occurs near quartile 11(1) of bridge 10, as shown in Figure 4B, it can be seen that the time change in the slope based on the first time series data and the time change in the slope based on the second time series data are opposite in positive and negative, and the absolute value of the slope changes over time to different degrees.

[0038] More specifically, in FIG. 4B, crack 1 occurs near quartile 11(1), and therefore the change over time in the slope as the first time series data from sensor head 20(1) is greater than the change over time in the slope as the second time series data from sensor head 20(2).

[0039] Therefore, the diagnosis unit 30 can determine that deterioration has occurred when a predetermined significant difference exists between the slope, which is a past characteristic amount, and the slope, which is a current characteristic amount, based on either the first time series data calculated based on the physical amount detected by the sensor head 20(1) or the second time series data calculated based on the physical amount detected by the sensor head 20(2).

[0040] For example, in Figure 4B, if the past time is represented as time 0 on the horizontal axis and the current time is represented as time 6 on the horizontal axis, the diagnosis unit 30 can determine that crack 1 has occurred if the difference in slope at each time is greater than or equal to a predetermined significant difference.

[0041] Furthermore, the diagnostic unit 30 compares the time changes of the first time series data calculated based on the physical quantities detected by the sensor head 20(1) and the second time series data calculated based on the physical quantities detected by the sensor head 20(2), and if it determines that the positive and negative values ​​are opposite and that the absolute values ​​of the slopes change at different degrees over time, it can determine that damage due to crack 1 has occurred near the quartile where the sensor head showing the greater time change is installed, and can identify the location where the deterioration has occurred.

[0042] Fig. 4C is an explanatory diagram showing a time change in tilt information when damage due to crack 1 occurs near a support of bridge 10 in embodiment 1 of the present disclosure. Similar to Figs. 4A and 4B, the line graph in Fig. 4C shows the time change in tilt associated with the progression of damage as time-series data, with the horizontal axis representing the progress of damage and the vertical axis representing the tilt.

[0043] The diagnosis unit 30 calculates first tilt information, which is one of the feature quantities, from the physical quantity detected by the sensor head 20(1), and stores the first tilt information sequentially over time as first time-series data in the storage unit 40. In the line graph of FIG. 4C, each data indicated by a ▲ plot on the dotted line corresponds to the first time-series data.

[0044] Similarly, the diagnosis unit 30 calculates second tilt information, which is one of the feature quantities, from the physical quantity detected by the sensor head 20(2), and stores the second tilt information sequentially over time as second time-series data in the storage unit 40. In the line graph of Fig. 4C, each data indicated by a ● plot on the solid line corresponds to the second time-series data.

[0045] When damage due to crack 1 occurs near support 12(1) of bridge 10, as shown in Figure 4C, it can be seen that the time change in the slope based on the first time series data and the time change in the slope based on the second time series data change in the same direction, both positive and negative.

[0046] 4C, because crack 1 has occurred near support 12(1) outside quartile 11(1), both the time change in the slope as the first time series data from sensor head 20(1) and the time change in the slope as the second time series data from sensor head 20(2) tend to increase in the positive direction. Furthermore, the time change in the first time series data from sensor head 20(1) closer to crack 1 tends to be smaller than the time change in the second time series data from sensor head 20(2).

[0047] Therefore, the diagnosis unit 30 can determine that deterioration has occurred when a predetermined significant difference exists between the slope, which is a past characteristic amount, and the slope, which is a current characteristic amount, based on either the first time series data calculated based on the physical amount detected by the sensor head 20(1) or the second time series data calculated based on the physical amount detected by the sensor head 20(2).

[0048] For example, in Figure 4C, if the past time is taken as time 0 on the horizontal axis and the current time is taken as time 6 on the horizontal axis, the diagnosis unit 30 can determine that crack 1 has occurred if the difference in slope at each time is greater than or equal to a predetermined significant difference.

[0049] Furthermore, the diagnostic unit 30 compares the time changes of the first time series data calculated based on the physical quantities detected by the sensor head 20(1) and the second time series data calculated based on the physical quantities detected by the sensor head 20(2), and if it determines that both have the same positive and negative directions and that the absolute values ​​of the slopes change to different degrees over time, it can determine that damage due to crack 1 has occurred near the support where the sensor head showing the smaller time change is installed, and can identify the location where the deterioration has occurred.

[0050] It is desirable that the sensor head 20(1) and the sensor head 20(2) are placed at equal distances on the left and right from the center of the pier 10. However, if the sensor head 20(1) is placed between the quartile point 11(1) and the bearing 12(1) and the sensor head 20(2) is placed between the quartile point 11(2) and the bearing 12(2), the effect of being able to identify the location where the deterioration has occurred can be obtained even if the sensor heads are not placed at equal distances on the left and right.

[0051] As described above, according to the first embodiment, a sensor head is installed between the quartile point and the support, and the inclination information of the structure, which is an index for diagnosing deterioration of the structure, is calculated as a feature value from the physical quantity detected by the sensor head, and deterioration of the structure is diagnosed from the time change of the inclination information. As a result, a deterioration diagnosis system that can detect deterioration occurring particularly near the support with high accuracy can be realized.

[0052] In particular, when the amplitude, phase, natural vibration, etc. of a structure are used as index values ​​for deterioration diagnosis, it is difficult to detect deterioration with high accuracy because the index values ​​do not change over time. In contrast, by placing a sensor head between the quartile and the support and using information on the inclination of the structure as an index value for deterioration diagnosis, it is possible to detect deterioration that occurs near the support with high accuracy.

[0053] Embodiment 2 In the above-described embodiment 1, a case where tilt information is used as a feature amount has been described. In contrast to this, in embodiment 2, a case where natural vibration information of a structure, which is a second index for degradation diagnosis, is further calculated in addition to tilt information of a structure, which is a first index for degradation diagnosis, and degradation diagnosis is performed using both the tilt information and natural vibration information will be described.

[0054] First, a degradation diagnosis method based on natural vibration information will be described in detail using a specific example shown in Fig. 5A to Fig. 5C. Each of the sensor heads 20(1) and 20(2) used in the second embodiment is capable of detecting acceleration as a physical quantity. In the following, a case where the detection result of the sensor head 20(1) is used will be described.

[0055] Fig. 5A is an explanatory diagram showing a time change in natural vibration information when damage due to a crack 1 occurs near the center of a bridge 10 in embodiment 2 of the present disclosure. The line graph in Fig. 5A shows the time change in natural frequency accompanying the progression of damage as time-series data, with the horizontal axis representing the progress of damage over time and the vertical axis representing the rate of decrease in natural frequency relative to when there is no damage.

[0056] The diagnosis unit 30 calculates the first-order natural frequency, which is one of the characteristic quantities, as natural vibration information from the acceleration, which is a physical quantity detected by the sensor head 20(1), and stores the first-order natural frequency sequentially over time as third time-series data in the storage unit 40. In the line graph of Fig. 5A, each data indicated by a ● plot on the solid line corresponds to the third time-series data.

[0057] Similarly, the diagnosis unit 30 calculates the second-order natural frequency, which is one of the characteristic quantities, as natural vibration information from the acceleration, which is a physical quantity detected by the sensor head 20(1), and stores the second-order natural frequency sequentially over time as fourth time-series data in the storage unit 40. In the line graph of Fig. 5A, each data indicated by a plot of x on the dotted line corresponds to the fourth time-series data.

[0058] When damage due to crack 1 occurs near the center of bridge 10, as shown in Figure 5A, it can be seen that the time change of the first-order natural frequency based on the third time series data is larger than the time change of the second-order natural frequency based on the fourth time series data.

[0059] Therefore, the diagnostic unit 30 can determine that deterioration is occurring when a predetermined significant difference exists between the past feature amount and the current feature amount based on the third time series data and the fourth time series data calculated based on the physical quantity detected by the sensor head 20(1).

[0060] For example, in FIG. 5A, if the past time is taken as time 0 on the horizontal axis and the current time is taken as time 6 on the horizontal axis, the diagnosis unit 30 can determine that crack 1 has occurred if the rate of decline in the first-order natural frequency is equal to or greater than a preset threshold value.

[0061] Furthermore, the diagnosis unit 30 compares the time changes of both the third time series data and the fourth time series data calculated based on the physical quantities detected by the sensor head 20(1), and if the rate of decline in the first-order natural frequency is greater than the rate of decline in the second-order natural frequency, it determines that damage due to crack 1 has occurred near the center of the bridge 10, and can identify the location where the deterioration has occurred.

[0062] Fig. 5B is an explanatory diagram showing a time change in natural vibration information when damage due to a crack 1 occurs near the quartile 11(1) of the bridge 10 in the second embodiment of the present disclosure. The line graph in Fig. 5B, like Fig. 5A, shows the time change in the natural frequency with the progression of damage as time series data, with the horizontal axis representing the progress of damage and the vertical axis representing the rate of decrease in the natural frequency relative to when there is no damage.

[0063] The diagnosis unit 30 calculates the first-order natural frequency, which is one of the characteristic quantities, as natural vibration information from the acceleration, which is a physical quantity detected by the sensor head 20(1), and stores the first-order natural frequency sequentially over time as third time-series data in the storage unit 40. In the line graph of Fig. 5B, each data indicated by a ● plot on the solid line corresponds to the third time-series data.

[0064] Similarly, the diagnosis unit 30 calculates the second-order natural frequency, which is one of the characteristic quantities, as natural vibration information from the acceleration, which is a physical quantity detected by the sensor head 20(1), and stores the second-order natural frequency sequentially over time as fourth time-series data in the storage unit 40. In the line graph of Fig. 5B, each data indicated by a plot of x on the dotted line corresponds to the fourth time-series data.

[0065] When damage due to crack 1 occurs near quartile 11(1) of bridge 10, as shown in FIG. 5B, it can be seen that the change over time of the second-order natural frequency based on the fourth time series data is larger than the change over time of the first-order natural frequency based on the third time series data.

[0066] Therefore, the diagnostic unit 30 can determine that deterioration is occurring when a predetermined significant difference exists between the past feature amount and the current feature amount based on the third time series data and the fourth time series data calculated based on the physical quantity detected by the sensor head 20(1).

[0067] For example, in Figure 5B, if the past time is taken as time 0 on the horizontal axis and the current time is taken as time 6 on the horizontal axis, the diagnosis unit 30 can determine that crack 1 has occurred when the rate of decrease in the second-order natural frequency is equal to or greater than a predetermined threshold value.

[0068] Furthermore, the diagnosis unit 30 compares the time changes of both the third time series data and the fourth time series data calculated based on the physical quantities detected by the sensor head 20(1), and if the rate of decline in the second-order natural frequency is greater than the rate of decline in the first-order natural frequency, it can determine that damage due to crack 1 has occurred near quartile 11(1), and identify the location where deterioration has occurred.

[0069] Fig. 5C is an explanatory diagram showing a time change in natural vibration information when damage due to a crack 1 occurs near a support 12(1) of a bridge 10 in the second embodiment of the present disclosure. The line graph in Fig. 5C, like Figs. 5A and 5B, shows the time change in the natural frequency with the progression of damage as time-series data, with the horizontal axis representing the progress of damage and the vertical axis representing the rate of decrease in the natural frequency relative to when there is no damage.

[0070] The diagnosis unit 30 calculates the first-order natural frequency, which is one of the characteristic quantities, as natural vibration information from the acceleration, which is a physical quantity detected by the sensor head 20(1), and stores the first-order natural frequency sequentially over time as third time-series data in the storage unit 40. In the line graph of Fig. 5C, each data indicated by a ● plot on the solid line corresponds to the third time-series data.

[0071] Similarly, the diagnosis unit 30 calculates the second-order natural frequency, which is one of the characteristic quantities, as natural vibration information from the acceleration, which is a physical quantity detected by the sensor head 20(1), and stores the second-order natural frequency sequentially over time as fourth time-series data in the storage unit 40. In the line graph of Fig. 5C, each data indicated by a plot of x on the dotted line corresponds to the fourth time-series data.

[0072] When damage due to crack 1 occurs near support 12(1) of bridge 10, as shown in Figure 5C, it can be seen that there is no significant difference as previously set in either the time change of the first-order natural frequency based on the third time series data or the time change of the second-order natural frequency based on the fourth time series data.

[0073] Therefore, the diagnosis unit 30 cannot determine that degradation is occurring from the third time-series data and the fourth time-series data calculated based on the physical quantities detected by the sensor head 20(1).

[0074] In other words, even if the sensor head 20(1) is installed between the quartile 11(1) and the support 12(1), it is difficult to detect deterioration occurring near the support if deterioration diagnosis is performed using only the natural vibration information as a feature amount. However, as described above in the first embodiment, it is possible to detect deterioration occurring near the support by using the inclination information as a feature amount.

[0075] Furthermore, if deterioration occurs at a location other than near the support, the occurrence of deterioration or the location where deterioration has occurred can be identified with greater accuracy by combining deterioration diagnosis using tilt information and deterioration diagnosis using natural vibration information.

[0076] For example, even if a significant difference in tilt cannot be detected between past tilt information and current tilt information by only using tilt information as a feature, if a significant difference in natural frequency can be detected between past natural vibration information and current natural vibration information by further using natural vibration information as a feature, it is possible to identify the occurrence of deterioration or the location where deterioration has occurred.

[0077] As described above, according to the second embodiment, a sensor head is installed between the quartile point and the support, and from the physical quantities detected by the sensor head, natural vibration information is calculated as feature quantities together with inclination information of the structure, which is an index for diagnosing deterioration of the structure, and deterioration diagnosis of the structure is performed using both the inclination information and the natural vibration information.

[0078] As a result, a further effect can be achieved in that a deterioration diagnosis system can be obtained that can detect deterioration that occurs near the support with a high degree of accuracy based on tilt information, and that can detect deterioration that occurs at a position other than near the support with a high degree of accuracy based on a combination of tilt information and natural vibration information.

[0079] In the second embodiment, the sensor head 20(1) has been described, but the sensor head 20(2) may also be used. Moreover, both the sensor head 20(1) and the sensor head 20(2) may also be used.

[0080] Embodiment 3 In this embodiment, a case will be described in which temperature data during detection of a physical quantity is taken into consideration to generate time-series data, thereby improving the accuracy of deterioration detection.

[0081] It is considered that the physical quantities detected by the sensor head 20 are affected by the temperature in the environment in which the structure is installed. For example, if tilt information calculated based on physical quantities detected in midwinter and tilt information calculated based on physical quantities detected in midsummer are directly compared, there is a risk that the deterioration diagnosis accuracy will not be consistent.

[0082] Therefore, the diagnosis unit 30 according to the third embodiment acquires temperature data during detection of a physical quantity by the sensor head 20. As an example, the diagnosis unit 30 can acquire temperature data from a thermometer installed near the structure, or can acquire temperature data as part of weather data for the area where the structure is installed.

[0083] On the other hand, the storage unit 40 in the present embodiment 3 stores correction coefficients that are set in advance in association with temperature data. Therefore, the diagnosis unit 30 can extract the correction coefficient corresponding to the acquired temperature data from the storage unit 40.

[0084] Then, the diagnosis unit 30 calculates the current feature by correcting the feature using the extracted correction coefficient, and generates temperature-corrected time series data by sequentially storing the calculated current feature in the memory unit 40 over time.

[0085] The temperature-corrected time-series data thus generated has the influence of the temperature data suppressed by taking into account the temperature data during detection of the physical quantity by the sensor head 20. Therefore, by using the temperature-corrected time-series data, the diagnostic unit 30 can suppress the influence of the temperature data during detection of the physical quantity and achieve uniform deterioration diagnosis accuracy.

[0086] As described above, according to the third embodiment, deterioration diagnosis is performed using temperature-corrected time-series data generated taking into account the air temperature data during detection of the physical quantity, thereby making it possible to standardize the accuracy of deterioration diagnosis that is not affected by air temperature. [Explanation of symbols]

[0087] 10 bridge (structure), 11 (1) quartile (first quartile), 11 (2) quartile (second quartile), 12 (1) support (first support), 12 (2) support (second support), 20 (1) sensor head (first sensor head), 20 (2) sensor head (second sensor head), 30 diagnosis unit, 40 memory unit.

Claims

1. a sensor head that is installed in a structure and detects a physical quantity for diagnosing deterioration of the structure; a diagnosis unit that performs a deterioration diagnosis of the structure based on the physical quantity detected by the sensor head; Equipped with The structure is supported by a support provided outside a quadrant of the structure of the structure, The sensor head is disposed between the quartile and the support; The diagnosis unit includes: calculating, from the physical quantity detected by the sensor head, tilt information of the structure, which is a first index for deterioration diagnosis of the structure, as a feature quantity; The calculated tilt information is stored in a storage unit as time-series data over time. A past feature amount is extracted from the time-series data stored in the storage unit in sequence, and if a significant difference set in advance exists between the past feature amount and the current feature amount, it is possible to determine that deterioration has occurred in the structure based on a time change in the tilt information calculated from the detection result of one sensor head. Deterioration diagnosis system.

2. The sensor head includes: a first sensor head installed between a first quartile located at one position from the center of the structure and a first support; a second sensor head disposed between a second quartile at the other position from the center of the structure and a second support; It is composed of The diagnosis unit includes: calculating first tilt information, which is one of the feature amounts, from the physical amount detected by the first sensor head, and storing the first tilt information in the storage unit as first time-series data over time; calculating second tilt information, which is one of the feature amounts, from the physical amount detected by the second sensor head, and storing the second tilt information in the storage unit as second time-series data over time; When it is determined that deterioration has occurred in the structure based on the first time-series data or the second time-series data, the location where the deterioration has occurred can be identified by comparing the time changes of the tilt information of each of the two sensor heads calculated from the detection results of the first sensor head and the second sensor head. The deterioration diagnosis system according to claim 1 .

3. The sensor head detects acceleration as the physical quantity, The diagnosis unit includes: further calculating, as the feature quantity, natural vibration information of the structure, which is a second index for deterioration diagnosis of the structure, from the acceleration, which is a physical quantity detected by the sensor head; When it is determined that no deterioration has occurred in the structure by the deterioration diagnosis of the structure based on the tilt information, it is determined whether or not deterioration has occurred in the structure by the deterioration diagnosis of the structure based on the natural vibration information. The deterioration diagnosis system according to claim 1 or 2.

4. The sensor head detects acceleration as the physical quantity, The diagnosis unit includes: further calculating, as the feature quantity, natural vibration information of the structure, which is a second index for deterioration diagnosis of the structure, from the acceleration, which is a physical quantity detected by the sensor head; When it is determined that no deterioration has occurred in the structure by the deterioration diagnosis of the structure based on the natural vibration information, it is determined whether or not deterioration has occurred in the structure by the deterioration diagnosis of the structure based on the tilt information. The deterioration diagnosis system according to claim 1 or 2.

5. The diagnosis unit includes: acquiring air temperature data during detection of the physical quantity by the sensor head; The feature amount is corrected using a preset correction coefficient according to the acquired temperature data to calculate the current feature amount, and the calculated current feature amount is sequentially stored in a storage unit over time to generate the time series data. The degradation diagnosis system according to claim 1 .

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