Deterioration diagnosis system

Abstract

To visualize a deterioration range of a deterioration diagnosis object on the basis of detection results by a plurality of sensors.SOLUTION: A deterioration diagnosis device includes a sensor controller configured to generate the display information in which a deterioration state of a deterioration diagnosis target is visualized on the basis of detection results obtained by a plurality of sensors installed in the deterioration diagnosis target. The sensor controller includes the steps of: calculating a correlation value between the two sensors as a deterioration determination index which indicates a deterioration state based on feature amounts calculated for each of the plurality of sensors; and performing the layout display reflecting installation places of the plurality of sensors and generating the display information so that the deterioration determination index can be visually recognized in association with the layout display.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present disclosure relates to a degradation diagnosis system that can visualize the positional relationship of sensors in association with an abnormality detection state when performing degradation diagnosis of an object to be diagnosed with degradation using acceleration information detected by each of a plurality of sensors. [Background technology]

[0002] For example, structures such as bridges over which vehicles pass will gradually deteriorate due to the passage of vehicles. It is important to detect the deterioration of structures such as bridges before they break.

[0003] There is a conventional technique for more efficiently and accurately grasping changes in the state of a structure (for example, see Patent Document 1). The conventional technique related to Patent Document 1 discloses a technique for calculating correlations between multiple physical quantities between sensors and detecting anomalies based on changes in the correlations. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Patent No. 5832814 Summary of the Invention [Problem to be solved by the invention]

[0005] However, the conventional techniques have the following problems. In Patent Document 1, when detecting an abnormality in a structure, a combination of sensors that output a measurement value exceeding a threshold is detected from a change in the correlation between physical quantities between the sensors.

[0006] Here, when performing deterioration diagnosis of a structure such as a bridge, it is considered to place many sensors at various locations of the structure. In the conventional technology of Patent Document 1, although it is possible to identify a combination of sensors that output a measurement value exceeding a threshold, such identification alone makes it difficult to link the placement of each sensor on the structure with the deterioration state. In other words, the conventional technology has a problem in that it is difficult to identify the extent of deterioration. In addition, it is important to identify the extent of deterioration for deterioration diagnosis targets other than structures.

[0007] The present disclosure has been made to solve the above-mentioned problems, and aims to provide a deterioration diagnosis system that can visualize the range of deterioration of a target for deterioration diagnosis based on detection results from multiple sensors. [Means for solving the problem]

[0008] The deterioration diagnosis system according to the present disclosure is A structure that is Based on the detection results from multiple sensors installed at different locations structure The deterioration diagnosis system includes a sensor controller that generates display information that visualizes the deterioration state of a plurality of sensors, and the sensor controller generates display information based on the detection results of the plurality of sensors. structure A physical quantity relating to the deterioration state is calculated as a feature quantity, and a correlation value between two sensors is calculated as a deterioration judgment index indicating a deterioration state based on the feature quantities calculated for each of the plurality of sensors. A layout display reflecting the installation locations of the plurality of sensors is performed, and display information is generated so that the deterioration judgment index is linked to the layout display and can be visually confirmed. The feature quantity, which is a physical quantity related to the structure, is a feature quantity in which the correlation value, which is a deterioration judgment index, decreases as the structure deteriorates compared to before the deterioration. It is something. Further, a deterioration diagnosis system according to the present disclosure includes a plurality of sensors that are installed at different locations of a structure that is a deterioration diagnosis target and that output acceleration information of the structure, and a sensor controller that generates display information that visualizes a deterioration state of the structure based on the acceleration information output from the sensors, and the sensor controller calculates a physical quantity related to the structure as a feature value based on the acceleration information for each of the plurality of sensors, calculates a correlation value between two sensors as a deterioration determination index that indicates a deterioration state based on the feature value calculated for each of the plurality of sensors, performs a layout display that reflects the installation locations of the plurality of sensors, and generates display information so that the deterioration determination index is linked to the layout display and can be visually confirmed. The feature quantity, which is a physical quantity related to the structure, is a feature quantity in which the correlation value, which is a deterioration judgment index, decreases as the structure deteriorates compared to before the deterioration. It is something. Effect of the Invention

[0009] According to the present disclosure, it is possible to obtain a degradation diagnosis system capable of visualizing the degradation range of an object to be diagnosed with degradation, based on the detection results from a plurality of sensors. [Brief description of the drawings]

[0010] [Figure 1] 1 is a configuration diagram of a degradation diagnosis system according to a first embodiment of the present disclosure. [Diagram 2] 1 is an explanatory diagram showing a state in which a plurality of sensors are installed at different locations of a structure that is a target for deterioration diagnosis by a deterioration diagnosis system according to a first embodiment of the present disclosure. FIG. [Diagram 3] FIG. 2 shows a scatter plot of a sensor layout and the inclination of each sensor when the inclination is used as a feature amount in the first embodiment of the present disclosure. [Figure 4] FIG. 13 is an explanatory diagram of display information according to a conventional technique when tilt is used as a feature amount. [Diagram 5] 4 is an explanatory diagram related to display information generated by the determination processing unit according to the first embodiment of the present disclosure when the tilt is used as a feature amount. FIG. [Figure 6] FIG. 2 is an explanatory diagram relating to deterioration diagnosis when live load displacement is used as a feature amount in the first embodiment of the present disclosure. [Figure 7] FIG. 2 shows a scatter diagram of maximum displacement amounts of sensors when live load displacement is used as a feature amount in the first embodiment of the present disclosure. [Figure 8] FIG. 13 is an explanatory diagram of display information according to the prior art when the maximum displacement amount is calculated using the live load displacement as a feature amount. [Figure 9] 10 is an explanatory diagram related to display information generated by the determination processing unit according to the first embodiment of the present disclosure when a maximum displacement amount is obtained using a live load displacement as a feature amount. FIG. [Figure 10] FIG. 13 is an explanatory diagram regarding display information according to the prior art when two feature quantities, namely, tilt and live load displacement, are taken into consideration. [Figure 11] FIG. 2 is an explanatory diagram regarding display information according to the present disclosure. [Figure 12] FIG. 12 is a diagram showing display information different from the display information shown in FIGS. 5, 9, and 11, which is generated by a determination processing unit according to the first embodiment of the present disclosure in order to make the deteriorated area of ​​a structure visible. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0011] 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 of having a function of visualizing the range of deterioration of a deterioration diagnosis target by determining the correlation between sensors from the detection results of multiple sensors as a deterioration judgment index, and further generating display information that associates the arrangement of each sensor with the correlation between the sensors. Note that, although the following description will be given using an example in which the deterioration diagnosis target is a structure, the deterioration diagnosis target is not limited to structures, and the present disclosure has a remarkable effect on visualizing the range of deterioration.

[0012] Embodiment 1 In this embodiment 1, a specific configuration is described for generating and displaying display information that associates the placement of each sensor with the correlation between the sensors when the deterioration diagnosis target is a structure and deterioration diagnosis of the structure is performed based on measurement results from multiple sensors.

[0013] 1 is a configuration diagram of a degradation diagnosis system according to a first embodiment of the present disclosure. The degradation diagnosis system in the first embodiment is configured to include a plurality of N sensors 10(1)-10(N) and a sensor controller 20.

[0014] 2 is an explanatory diagram showing a state in which a plurality of sensors 10 are installed at different locations of a structure that is a degradation diagnosis target of the degradation diagnosis system according to the first embodiment of the present disclosure. In Fig. 2, a bridge 30 is shown as a specific example of the structure, with Fig. 2(A) being a side view of the bridge 30 and Fig. 2(B) being a rear view of the bridge 30.

[0015] The bridge 30 gradually deteriorates due to aging caused by the passage of the vehicle 1. Therefore, the deterioration diagnosis system according to the first embodiment diagnoses the ever-changing deterioration state of the bridge 30 by analyzing, with the sensor controller 20, acceleration information output by each of the multiple sensors 10(1) to 10(N) installed at positions suitable for deterioration diagnosis.

[0016] Furthermore, the sensor controller 20 according to the first embodiment has a function of displaying a layout that reflects the installation locations of multiple sensors, and generating display information for linking the correlation state between the sensors, which is an index for determining deterioration, to the layout display so that it can be visually confirmed.

[0017] The sensor 10 is installed on a main girder 31, which is a component of a bridge 30. Here, the main girder 31 corresponds to the structural body of the structure that is the subject of deterioration diagnosis. As shown in Fig. 2(B), the main girder 31 is configured as three main girders 31a, 31b, and 31c, for example.

[0018] 2(B) illustrates an example in which two sensors 10(1), 10(2) are installed at the quartiles of the respective main girders 31a, 31b, 31c (i.e., portions corresponding to one-quarter and three-quarters of the spans corresponding to the distance between the left and right supports 2). The quartiles, which are the installation positions, correspond to an example of a position suitable for deterioration diagnosis.

[0019] In the following description, three sensors 10 are installed on each of the main girders 31a, 31b, and 31c, and deterioration diagnosis is performed based on the detection results of each sensor 10. However, the number and arrangement of the sensors 10 are not limited to this example.

[0020] Each sensor 10 detects acceleration information occurring on the bridge 30, and outputs the acceleration information to the sensor controller 20. One example of the sensor 10 is a three-axis acceleration sensor that uses a thin-film quartz crystal oscillator, has excellent responsiveness, and has a measurement range of about DC to several tens of Hz that can measure acceleration.

[0021] In this way, by using a three-axis acceleration sensor as the sensor 10, it is not necessary to perform leveling, and the sensor output can be obtained regardless of the direction of tilt or vibration. Therefore, if the direction of tilt can be specified by performing leveling, a two-axis or one-axis acceleration sensor may be used.

[0022] Furthermore, the sensor 10 can convert analog signals relating to the three-axis acceleration of the structure at the installation location into digital signals at a predetermined sampling rate (for example, a sampling rate of 50 Hz) and transmit the digital signals to the sensor controller 20 as acceleration information.

[0023] The sensor controller 20 that receives the acceleration information output from each sensor 10 is configured to include a feature conversion section 21, a correlation value calculation section 22, and a determination processing section 23, as shown in FIG.

[0024] The feature conversion unit 21 converts the acceleration information received from each sensor 10 into the inclination and live load displacement of the structure at the installation location of the sensor 10. Here, the inclination and live load displacement, which are physical quantities, each correspond to a feature for diagnosing deterioration of the structure.

[0025] A live load is a load whose magnitude is not constant and whose acting position changes. Factors that cause the displacement of such a live load include the weight of the vehicle 1 passing over the bridge 30, the weight of the bridge 30 itself, and the inertial force acting on the bridge 30 due to an earthquake. In the following explanation, "displacement" and "live load displacement" are treated as synonyms.

[0026] The correlation value calculation unit 22 calculates a correlation value between the sensors for each of the multiple feature amounts, ie, the inclination and the live load displacement, generated by the conversion process by the feature amount conversion unit 21.

[0027] Furthermore, the determination processing unit 23 generates display information for displaying the correlation value between the sensors, which is the deterioration determination index, in association with a layout display that reflects the placement locations of the sensors.

[0028] In the following, a method for generating display information in each of the cases where the inclination is used as the feature amount, the live load displacement is used, and both the inclination and the live load displacement are used will be described in detail.

[0029] <Case 1: Details of display information when tilt is used as a feature> FIG. 3 is a diagram illustrating a scatter diagram of a sensor layout and the inclination of each sensor when the inclination is used as a feature amount in the first embodiment of the present disclosure.

[0030] Fig. 3(A) is a sensor layout showing a state in which a total of nine sensors are installed on main girders 31a to 31c of a structure that is the target of deterioration diagnosis. That is, Fig. 3(A) corresponds to a layout display that reflects the installation locations of the nine sensors. Specifically, the example shows a case in which three sensors 10(1) to 10(3) are installed on main girder 31a, three sensors 10(4) to 10(6) are installed on main girder 31b, and three sensors 10(7) to 10(9) are installed on main girder 31c.

[0031] Fig. 3(B) shows a scatter diagram of the inclination calculated as a feature by feature conversion unit 21 based on the acceleration information output from each of sensors 10(1) to 10(9). The scatter diagram shown in Fig. 3(B) was created by collecting hourly average inclinations for about one and a half years, as an example.

[0032] The numbers 1 to 9 on the vertical and horizontal axes in the scatter plot correspond to the sensor numbers 1 to 9 in Fig. 3(A). A histogram of the inclination calculated based on the acceleration information from each sensor is displayed on the diagonal line. In addition, the portion other than the diagonal line plots the correspondence between the inclination calculated based on the detection result of one sensor and the inclination calculated based on the detection result of the other sensor.

[0033] For example, where the horizontal axis is sensor 1 and the vertical axis is sensor 2, a plot of one and a half years of data is shown, with the horizontal axis showing the hourly average slope calculated based on the detection results of sensor 1 and the vertical axis showing the hourly average slope calculated based on the detection results of sensor 2.

[0034] Therefore, the correlation value calculation section 22 can calculate the correlation value relating to the inclination between the two sensors based on the scatter diagram shown in FIG. 3(B).

[0035] Fig. 4 is an explanatory diagram of display information as a conventional technique when the tilt is used as a feature amount. Specifically, (A) and (B) in Fig. 4 respectively show the following diagrams. Figure 4(A): Heatmap display of correlation matrix for slope before degradation Figure 4(B): Heat map display of correlation matrix for slope as deterioration progresses

[0036] The correlation matrix is ​​a matrix display of the correlation values ​​calculated based on the scatter plot in Figure 3(B) that have been quantified. The elements on the diagonal are the autocorrelation values, which are 1, and the other elements correspond to the correlation values ​​between the two sensors.

[0037] A heat map display is a display in which the correlation values ​​of the elements of the correlation matrix are displayed in gradations of color to indicate the magnitude relationship. In the prior art, such a heat map display of the correlation matrix was possible. However, it was difficult to grasp the deterioration state of the structure from such a display in association with the actual arrangement of each sensor.

[0038] In other words, although an operator who visually checks the display contents shown in Figure 4 can compare the gradation display of the state before deterioration and the state as deterioration progresses, it is difficult for the operator to grasp the extent of deterioration in the structure that is the subject of deterioration diagnosis in relation to the actual arrangement of each sensor.

[0039] Therefore, the judgment processing unit 23 according to the first embodiment has a function of generating display information for displaying the correlation value between sensors, which is a deterioration judgment index, in association with a layout display showing the arrangement state of the sensors. An operator who visually checks the display information generated in this way can easily grasp the extent to which deterioration has progressed in the structure that is the deterioration diagnosis target. Therefore, the function of generating display information using the inclination as a feature will be described in detail with reference to FIG. 5.

[0040] 5 is an explanatory diagram regarding display information generated by the determination processing unit 23 according to the first embodiment of the present disclosure when the tilt is used as a feature amount. Specifically, (A) and (B) in FIG. 5 respectively show the following diagrams. Figure 5(A): Display information that visualizes the correlation between the slopes of the sensors before deterioration, superimposed on the sensor layout shown in Figure 3(A). Figure 5(B): Information displayed on the sensor layout shown in Figure 3(A) to visualize the correlation between the slopes of sensors as deterioration progresses.

[0041] As shown in FIGS. 5(A) and 5(B), the determination processing unit 23 generates display information that is superimposed on the sensor layout and that performs distinguishable display such that the width of the line connecting the sensors becomes thinner as the correlation value becomes smaller.

[0042] For example, the correlation value between sensors for inclination will be high unless there is an abnormality in the structure. As long as there is no abnormality in the structure and no change in the traffic volume of passing vehicles, the only factor that will affect the average value of inclination for one hour, for example, will be temperature. As for the effect of temperature, if the sensors are installed on the same structure, the temperature difference between the sensors is not large, so the degree of change in inclination of each sensor will be roughly the same.

[0043] In this case, the correlation value of the inclination between the sensors will be high (if the inclination changes in the opposite direction, the correlation will be high in the direction of the anti-correlation). On the other hand, if an abnormality occurs in the structure, factors other than temperature will affect the inclination, and the degree of influence is thought to differ for each sensor, so the correlation between the sensors will be low and approach no correlation.

[0044] In addition, the judgment processing unit 23 can set a threshold value based on the correlation value between each sensor before deterioration, and when the correlation value calculated during deterioration diagnosis becomes equal to or lower than the threshold value, display information can be generated by, for example, changing the line color of that part to red.

[0045] As a result, an operator viewing the display information shown in Figure 5(A) or Figure 5(B) can easily visually identify the extent to which deterioration is progressing in the structure that is the subject of deterioration diagnosis by focusing on the thickness or color of the lines.

[0046] <Case 2: Details of display information when live load displacement is used as a feature quantity> Fig. 6 is an explanatory diagram relating to deterioration diagnosis in a case where live load displacement is used as a feature amount in the first embodiment of the present disclosure. Specifically, (A1) to (A3) and (B1) to (B3) in Fig. 6 respectively show the following diagrams. Figure 6(A1): An explanatory diagram showing the state of the structure before deterioration and the relative positions of the two sensors Figure 6 (A2): Time series data of live load displacement calculated based on the detection results of two sensors before deterioration Figure 6 (A3): A diagram showing the correlation between the maximum displacements for the two sensors, obtained by calculating the maximum displacements in the time series data of the live load displacements for each fixed period before deterioration, and plotting the maximum displacements for sensor 1 on the horizontal axis and the maximum displacements for sensor 2 on the vertical axis.

[0047] Figure 6(B1): An explanatory diagram showing the state of a structure as deterioration progresses and the relative positions of the two sensors Figure 6 (B2): Time series data of live load displacement calculated based on the detection results of two sensors during deterioration Figure 6 (B3): The maximum displacement in the time series data of live load displacement at certain intervals during deterioration progression was calculated, and the horizontal axis was plotted as the maximum displacement for sensor 1, and the vertical axis was plotted as the maximum displacement for sensor 2, showing the correlation between the maximum displacement for the two sensors.

[0048] Figure 6 shows an example in which the correlation value in Figure 6 (A3) before deterioration was 0.94, but in Figure 6 (B3) as deterioration progresses, the correlation value decreases to 0.69. Therefore, when live load displacement is used as a feature quantity, a scatter diagram can be obtained by finding the correlation regarding the maximum displacement amount for each fixed period.

[0049] Fig. 7 is a diagram showing a scatter diagram of the maximum displacement amount of each sensor when the live load displacement is used as a feature amount in the first embodiment of the present disclosure. The scatter diagram shown in Fig. 7 is, as an example, a summary of the correlation of the maximum displacement amount for each fixed period over about one and a half years, using the nine sensors shown in Fig. 3(A) above, on a bridge where the number of passing vehicles is about 30 per hour during the daytime.

[0050] The meaning of the scatter diagram has been explained above using Fig. 3(B), and will not be explained here. However, in the scatter diagram shown in Fig. 7, a regression line relating to the maximum displacement between the two sensors is added.

[0051] The correlation value calculation section 22 can calculate the correlation value between the two sensors with respect to the maximum displacement amount based on the scatter diagram shown in FIG.

[0052] The meaning of this correlation value is that if sensors are installed on the same structure, the maximum displacement of each sensor is constant according to the weight of passing vehicles. Therefore, a high correlation between the maximum displacements of sensors indicates that the structure is not deteriorating during the measurement period and is maintaining a stable state.

[0053] On the other hand, if some damage occurs to the structure, the balance of the maximum displacement of each sensor will change compared to before the damage. Therefore, if the values ​​of each sensor before the damage are also included, the correlation will decrease over the entire measurement period.

[0054] Fig. 8 is an explanatory diagram of display information as a conventional technique when the maximum displacement amount is calculated using the live load displacement as a feature amount. Specifically, (A) and (B) in Fig. 8 show the following figures, respectively. Fig. 8(A): Heat map display of correlation matrix for maximum displacement before deterioration Figure 8(B): Heat map display of correlation matrix for maximum displacement during deterioration

[0055] The meaning of the correlation matrix and heat map display has been explained above using Figures 4(A) and 4(B), and will not be explained here. In the conventional technology, it was possible to display the correlation matrix as a heat map in this way. However, it was difficult to grasp the deterioration state of the structure from such a display in association with the actual arrangement of each sensor.

[0056] In other words, although an operator who visually checks the display contents shown in Fig. 8 can compare the gradation display of the state before deterioration and the state as deterioration progresses, it is difficult for the operator to grasp the extent of deterioration in the structure that is the subject of deterioration diagnosis in relation to the actual arrangement of each sensor.

[0057] Therefore, the determination processing unit 23 according to the first embodiment has a function of generating display information for displaying the correlation value between sensors, which is a deterioration determination index, in association with a layout display showing the arrangement state of the sensors. An operator who visually checks the display information generated in this way can easily grasp the extent to which deterioration has progressed in the structure that is the target of deterioration diagnosis.

[0058] Therefore, display information generated when the maximum displacement amount is obtained using the live load displacement as a feature is shown in Fig. 9. Fig. 9 is an explanatory diagram related to display information generated when the maximum displacement amount is obtained using the live load displacement as a feature by the determination processing unit 23 according to the first embodiment of the present disclosure. Specifically, (A) and (B) in Fig. 9 respectively show the following figures. Fig. 9(A): Display information visualizing the correlation between the maximum displacements between sensors before deterioration, superimposed on the sensor layout shown in Fig. 3(A). Fig. 9(B): Information displayed on the sensor layout shown in Fig. 3(A) to visualize the correlation between the maximum displacements between sensors as deterioration progresses.

[0059] As shown in FIGS. 9(A) and 9(B), the determination processing unit 23 generates display information that is superimposed on the sensor layout and that performs distinguishable display such that the line width connecting the sensors becomes thinner as the correlation value becomes smaller.

[0060] In addition, the judgment processing unit 23 sets a threshold value based on the correlation value between each sensor before deterioration, and when the correlation value calculated during deterioration diagnosis becomes equal to or lower than the threshold value, it can generate display information by, for example, changing the color of the line in that part to red.

[0061] As a result, an operator viewing the display information shown in Figure 9(A) or 9(B) can easily visually identify the extent to which deterioration is progressing in the structure that is the subject of deterioration diagnosis by paying attention to the thickness or color of the lines.

[0062] <Case 3: Details of display information when slope and live load displacement are used as feature quantities> Fig. 10 is an explanatory diagram of display information as a conventional technique when considering two feature quantities, tilt and live load displacement. Specifically, (A) and (B) in Fig. 10 show the following figures, respectively. Fig. 10(A): Heat map display of the correlation matrix calculated by multiplying or adding the corresponding elements of the correlation matrix for the inclination before deterioration and the correlation matrix for the maximum displacement. Figure 10(B): Heat map display of the correlation matrix calculated by multiplying or adding the corresponding elements of the correlation matrix for the slope during deterioration and the correlation matrix for the maximum displacement.

[0063] The meaning of the correlation matrix and heat map display has been explained above using Figures 4(A) and 4(B), and will not be explained here. In the prior art, it was possible to display a heat map of a correlation matrix related to one feature. However, it was not possible to obtain one correlation matrix by taking into account two feature amounts and calculating the product / sum of each correlation matrix element.

[0064] Therefore, it is not possible to view a correlation matrix that reflects multiple feature quantities, making it difficult to grasp the deterioration state of a structure based on multiple feature quantities in association with the actual placement of each sensor.

[0065] Furthermore, as shown in Fig. 10, an operator who visually checked the heat map display taking into account two feature quantities could compare the gradation display of the state before deterioration and the state as deterioration progressed, but it was difficult for him to grasp the extent of deterioration in the structure that was the subject of deterioration diagnosis in relation to the actual arrangement of each sensor.

[0066] Therefore, the determination processing unit 23 according to the first embodiment has a function of calculating a correlation value between sensors, which is a deterioration determination index, taking into consideration two feature amounts, and generating display information for displaying the correlation value in association with a layout display showing the arrangement state of the sensors. An operator who visually checks the display information generated in this way can easily grasp the extent to which deterioration has progressed for the structure that is the target of deterioration diagnosis, based on changes in multiple feature amounts.

[0067] Therefore, display information generated when one correlation matrix is ​​calculated using two feature quantities, inclination and live load displacement, is shown in Fig. 11. Fig. 11 is an explanatory diagram related to display information generated when two feature quantities, inclination and live load displacement, are taken into consideration by the determination processing unit 23 according to the first embodiment of the present disclosure. Specifically, (A) and (B) in Fig. 11 respectively show the following diagrams. Fig. 11(A): Display information that visualizes one correlation calculated by multiplying and adding elements of the correlation matrix for the inclination between sensors before deterioration and the correlation matrix for the maximum displacement amount, overlaid on the sensor layout shown in Fig. 3(A). Fig. 11(B): Display information that visualizes one correlation calculated by multiplying and adding elements of the correlation matrix for the slope between sensors as deterioration progresses and the correlation matrix for the maximum displacement amount, overlaid on the sensor layout shown in Fig. 3(A).

[0068] As shown in Figures 11(A) and 11(B), the judgment processing unit 23 generates display information that is overlaid on the sensor layout and displays one correlation matrix taking into account two feature amounts in such a way that the line width connecting the sensors becomes thinner as the correlation value becomes smaller.

[0069] In addition, the judgment processing unit 23 sets a threshold value based on the correlation value between each sensor before deterioration, and when the correlation value calculated during deterioration diagnosis becomes equal to or lower than the threshold value, it can generate display information by, for example, changing the color of the line in that part to red.

[0070] As a result, an operator viewing the display information shown in Figure 11(A) or Figure 11(B) can easily visually identify the extent to which deterioration is progressing in the structure that is the subject of deterioration diagnosis by focusing on the thickness or color of the lines, while taking into account the effects of the two feature quantities.

[0071] In the display information shown in Figures 5, 9, and 11, the deterioration range is visually recognizable by the thickness and color of the line connecting the sensors. However, the display information in the present disclosure is not limited to identification by the thickness and color of the line.

[0072] Fig. 12 is a diagram showing display information different from the display information shown in Fig. 5, Fig. 9, and Fig. 11, which is generated by the determination processing unit 23 according to the first embodiment of the present disclosure to make the deteriorated range of a structure visible. (A) and (B) in Fig. 12 respectively show the following diagrams. Fig. 12(A): Visualization of the normal state of the structure, which is judged to be free of deterioration from the detection results of each sensor before deterioration. Fig. 12(B): Visualization of abnormal conditions that are judged to be progressing in a part of a structure based on the detection results of each sensor when deterioration progresses.

[0073] Instead of creating display information that changes the thickness and color of the lines connecting the sensors, the judgment processing unit 23 can create display information that changes the area of ​​the shape displayed at the corresponding sensor position to be smaller in accordance with a decrease in the correlation value, as shown in Figure 12.

[0074] In addition, in Figures 5, 9 and 11, display information can be created in which the line width of the line connecting the sensors in the pre-deterioration state is set to 0 and not displayed, and the line width is increased when the correlation value becomes small, or conversely, the line width of the line connecting the sensors in the pre-deterioration state is set to the maximum width and the line width is changed to be smaller when the correlation value becomes small.

[0075] In addition, in Figures 5, 9 and 11, display information can be created that changes the line connecting the sensors as deterioration progresses to a different color or type, parallel to the line connecting the sensors before deterioration, so that the line width becomes smaller when the correlation value becomes smaller.

[0076] When creating display information, it is also possible to use a coefficient of determination calculated by squaring the correlation value instead of the correlation value.

[0077] As described above, according to the first embodiment, the system is provided with a function for visualizing the extent of deterioration of a structure by obtaining the correlation between sensors as a deterioration judgment index from the detection results of multiple sensors and generating display information that associates the arrangement of each sensor with the correlation between the sensors. In addition, the system can visualize the deterioration diagnosis based on two feature quantities as necessary.

[0078] In other words, the sensor controller according to the first embodiment has a function of generating display information such that the lines connecting each two sensors in the layout display are identifiable by a line width or line color corresponding to the magnitude of the correlation value, or the sizes of each sensor in the layout display are identifiable by a size corresponding to the magnitude of the correlation value.

[0079] As a result, it is possible to realize a deterioration diagnosis system that can provide display information for visually determining the deterioration state and extent of deterioration of a structure more reliably than conventional techniques.

[0080] In the above-described first embodiment, two physical quantities related to a structure, namely, tilt and live load displacement, are shown as calculated based on acceleration information, and a case has been described in which display information is generated that visualizes one correlation by multiplying / summing each element of a correlation matrix related to tilt and a correlation matrix related to maximum displacement. However, it is also possible to generate display information that visualizes one correlation by multiplying / summing each element of three or more correlation matrices corresponding to three or more physical quantities.

[0081] In other words, as a minimum configuration, by using two correlation matrices, it is possible to generate display information that visualizes one correlation, and in addition, it is also possible to generate display information that visualizes one correlation by further using a third or more correlation matrices, thereby achieving the same effect.

[0082] In the above-mentioned first embodiment, the case where acceleration information is used as the detection result by the sensor has been described. However, as long as the detection result allows a physical quantity indicating the deterioration state to be calculated as a feature quantity, a deterioration diagnosis system capable of visualizing the deterioration range of a structure can be realized by using detection results other than acceleration information.

[0083] In the above-mentioned first embodiment, the degradation diagnosis target is a structure, but the degradation diagnosis target is not limited to a structure. The present disclosure can achieve a remarkable effect of being able to visualize the degradation range even when the degradation diagnosis target is something other than a structure. [Explanation of symbols]

[0084] 10 sensor, 20 sensor controller, 21 feature conversion unit, 22 correlation value calculation unit, 23 determination processing unit.

Claims

1. A deterioration diagnosis system including a sensor controller that generates display information that visualizes a deterioration state of a structure based on detection results from a plurality of sensors installed at different locations of the structure, the deterioration diagnosis system comprising: The sensor controller includes: calculating a physical quantity related to the structure as a feature quantity based on the detection results for each of the plurality of sensors; calculating a correlation value between two sensors as a deterioration determination index indicative of the deterioration state based on the feature amounts calculated for each of the plurality of sensors; generating the display information so as to perform a layout display reflecting installation locations of the plurality of sensors and to visually confirm the deterioration determination index in association with the layout display; The feature value, which is a physical quantity related to the structure, is a feature value in which the correlation value, which is the deterioration determination index, decreases as the structure deteriorates compared to before the deterioration. Deterioration diagnosis system.

2. A plurality of sensors are installed at different locations of a structure that is a deterioration diagnosis target and output acceleration information of the structure; a sensor controller that generates display information that visualizes a deterioration state of the structure based on the acceleration information output from the sensor; Equipped with The sensor controller includes: calculating a physical quantity related to the structure as a feature quantity based on the acceleration information for each of the plurality of sensors; calculating a correlation value between two sensors as a deterioration determination index indicative of the deterioration state based on the feature amounts calculated for each of the plurality of sensors; generating the display information so as to perform a layout display reflecting installation locations of the plurality of sensors and to visually confirm the deterioration determination index in association with the layout display; The feature amount, which is a physical quantity related to the structure, is a feature amount in which the correlation value decreases as the structure deteriorates compared to before the deterioration. Deterioration diagnosis system.

3. A plurality of sensors are installed at different locations of a structure that is a deterioration diagnosis target and output acceleration information of the structure; a sensor controller that generates display information that visualizes a deterioration state of the structure based on the acceleration information output from the sensor; Equipped with The sensor controller includes: calculating a physical quantity related to the structure as a feature quantity based on the acceleration information for each of the plurality of sensors; calculating a correlation value between two sensors as a deterioration determination index indicative of the deterioration state based on the feature amounts calculated for each of the plurality of sensors; A layout display is performed that reflects the installation locations of the plurality of sensors, and the display information is generated so that the deterioration determination index is linked to the layout display and made visible. A deterioration diagnosis system, comprising: The sensor controller includes: calculating, as the feature amount, a plurality of feature amounts which are a first physical amount and a second physical amount as the physical amount related to the structure for each of the plurality of sensors based on the acceleration information; calculating, as the correlation value, a first correlation value based on a feature amount related to a first physical quantity and a second correlation value based on a feature amount related to a second physical quantity; A sum or product of the first correlation value and the second correlation value calculated between the same two sensors is calculated as the deterioration determination index. Deterioration diagnosis system.

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