KR102580358B1 - Apparatus and method for structural health monitoring using distributed sensing technique based on random-accessibility and multi-spatial Resolution - Google Patents

Abstract

A structure health monitoring device and method utilizing a distributed sensing technique capable of random position measurement and multi-spatial resolution measurement are disclosed. The structure health monitoring method includes the steps of obtaining measured values of the initial state of the monitoring target structure measured with a preset low-fidelity reference and a preset high-fidelity reference, and generating a reference value; Obtaining measurement values for each first measurement point measured at low spatial resolution, and performing monitoring on the structure to be monitored at low spatial resolution using the obtained measurement values and reference values for each first measurement point, monitoring results, acquisition If an outlier is found among the measured values for each first measurement point, obtaining the measured value for each second measurement point measured with high spatial resolution in the section where the outlier was found, and the step of obtaining the measured value for each second measurement point obtained, It includes the step of detecting the damage and calculating the damage location.

Description

Structural health monitoring device and method using distributed sensing technique capable of random location measurement and multi-spatial resolution measurement {Apparatus and method for structural health monitoring using distributed sensing technique based on random-accessibility and multi-spatial resolution}

The present invention relates to a structural health monitoring device and method using a distributed sensing technique capable of random position measurement and multi-spatial resolution measurement.

The deterioration of public infrastructure is an increasingly important issue worldwide, and much research is in progress. Like the cases of the United States and Japan, Korea also recognizes that the rapid aging of SOC facilities will become a problem in the future, and is conducting research and development on efficient and reliable maintenance technology for this purpose. Structural health monitoring is a system that measures facilities using sensors installed in social infrastructure, detects damage early on based on this, and quickly alerts managers to support decision-making such as future maintenance.

In general, measurement systems that utilize damage-sensitive strain rates are widely used, and much research has been conducted using optical fiber sensors that are highly durable and unaffected by electromagnetic interference and can be used permanently. A representative optical fiber sensor includes a fiber Bragg grating sensor.

Figure 1 is a diagram showing the sensing concept of a point sensor and a distributed sensor.

Referring to Figure 1, an optical fiber grid sensor is a system that measures strain and temperature using light reflected from a grid engraved at a specific position of an optical fiber, similar to the sensing concept of the point sensor shown in Figure 1. In other words, an optical fiber grid sensor is a point sensor that measures the response of a specific location of an optical fiber.

In large infrastructure facilities, the limitations of structural health monitoring using point sensors are as follows.

First, there is the possibility of missing fault (corruption) detection. Since only the response where the point sensor is located is measured, only damage occurring near the point sensor can be detected. Therefore, if damage occurs in a location other than near the point sensor, it is difficult to detect it. Furthermore, undetected damage can significantly affect the performance and durability of a structure and, in the worst case, cause an accident.

Second, there are economic and technical challenges when building and operating a maintenance system. When applied to large-scale infrastructure such as dams, installing numerous point sensors in a vast area excessively increases the initial system construction cost. Additionally, since defect (damage) information cannot be known in advance, there is no choice but to design and build the sensor system within the available budget. This means that there is still a chance of missing corruption detection.

Referring again to Figure 1, as a method of overcoming the limitations of point sensors, like the distributed sensor shown in Figure 1, a distributed sensor capable of continuous measurement in the longitudinal direction of the optical fiber cable due to the scattering phenomenon within the optical fiber. Research utilizing . The advantages and disadvantages of such a distributed sensor are as follows.

The first advantage is that a common optical fiber cable can be used as a sensing unit. Distributed fiber optic sensing techniques can be performed using common telecommunication fiber optic cables. Therefore, optical fiber cables for general communication can be attached to large infrastructure and used to measure strain and temperature. In general, optical fiber grid sensors incur costs for generating the grid, but general communication optical fiber cables do not incur separate production and purchase costs.

The second advantage is that continuous sensing is possible along the length of the optical fiber. When optical fiber cables are attached throughout the structure, strain can be measured throughout the structure, making it easy to determine whether damage has occurred.

Next, the first disadvantage is that repeated measurements are required due to the low signal to noise ratio (SNR) in the scattered waves. Because measurement is performed through scattering within the optical fiber, it has a low signal-to-noise ratio. Therefore, multiple sensing must be performed for the same location and averaged to reduce noise. Therefore, when measurement of multiple measurement points (thousands to tens of thousands of points) is required for large infrastructure facilities (1 km long sensing section), it takes a lot of time to measure, making it difficult to quickly detect damage.

The second drawback is that there is no precise damage location detection depending on spatial resolution. Distributed sensing techniques have the concept of spatial resolution. Spatial resolution is expressed in units of length, and the measured value according to spatial resolution may mean the average value of strain or temperature measured for each unit length. High spatial resolution of several centimeters (cm) can produce measurement points densely in units of several centimeters along the length of the optical fiber. On the other hand, a low spatial resolution of several meters (m) can generate measurement points in units of several meters along the length of the optical fiber.

For example, in order to precisely detect damage, if 1 km of optical fiber is measured in the longitudinal direction with high spatial resolution of 2 cm, 50,000 points are generated. When repeating measurements N times to improve SNR in an actual field, the measurement time can linearly increase by the number of repetitions (50,000 points * N times). On the other hand, when measuring 1 km of optical fiber with a low spatial resolution of 10 m, 100 points are generated. When repeating measurements N times to improve SNR, the measurement time can linearly increase by the number of repetitions (100 points * N times).

Scattered waves measured for each unit length along the longitudinal direction of the optical fiber can be converted into a physical quantity (for example, Brillouin frequency) related to strain or temperature through signal processing. For example, if the number of points that can be processed per second is 10, the time required to process 50,000 points generated at high spatial resolution is 5,000 seconds (50,000/10). On the other hand, the time required to process 100 points generated at low spatial resolution is 10 seconds (100/10), which greatly reduces the time required.

Therefore, when distributed sensors are used to monitor the health of large structures such as dams and long-span bridges, the following trade-off occurs. In other words, when high spatial resolution is used, the measurement points become denser and the damage location can be accurately detected, but the measurement time may increase excessively, reducing effectiveness. On the other hand, when using low spatial resolution, measurement points may become rare, making it difficult to accurately detect damage location, although measurement time is usable.

Republic of Korea Patent Publication No. 10-0879601 (2009.01.13)

The present invention monitors a structure using a distributed optical fiber sensor system capable of random position measurement and multi-spatial resolution measurement, and provides a structure health monitoring device and method that accurately detects damage to the structure by adaptively adjusting the spatial resolution. It is for.

According to one aspect of the present invention, structural health monitoring is performed by a structural health monitoring device that obtains the measured value from a distributed optical fiber sensor device that calculates the measured value through a measurement optical fiber cable installed along the monitoring section of the monitoring target structure. A method is disclosed.

The structure health monitoring method according to an embodiment of the present invention includes the measured value of the initial state of the monitoring target structure measured with a preset low-fidelity reference and a preset high-fidelity reference. Obtaining and generating a reference value, obtaining measured values for each first measurement point measured at the low spatial resolution, and using the obtained measured value for each first measurement point and the reference value to monitor the target at the low spatial resolution. Performing monitoring on a structure, when an outlier is found among the obtained measurement values for each first measurement point as a result of the monitoring, measurement for each second measurement point measured with the high spatial resolution in the section where the outlier was found. It includes a step of acquiring a value, and a step of detecting an anomaly among the obtained measured values for each second measurement point and calculating a damage location.

The step of generating the reference value generates a low spatial resolution reference value and a high spatial resolution reference value measured for each of the low spatial resolution and the high spatial resolution.

The step of performing the monitoring includes controlling the distributed optical fiber sensor device to measure at the low spatial resolution, periodically acquiring measured values for each first measurement point from the distributed optical fiber sensor device, and obtaining the measured value for each first measurement point from the distributed optical fiber sensor device. A difference value between the measured value for each first measurement point and the low spatial resolution reference value is calculated, and an anomaly is detected by checking whether the calculated difference value exceeds a preset threshold.

The step of acquiring the measured value for each second measurement point includes controlling the distributed optical fiber sensor device to measure the section where the outlier is found with the high spatial resolution, and then measuring the second measurement value from the distributed optical fiber sensor device. Obtain measured values for each point.

The step of calculating the damage location includes calculating a difference value between the measured value for each second measurement point and the high spatial resolution reference value, and detecting an outlier by checking whether the calculated difference value exceeds a preset threshold. And, the measurement point determined as the outlier is calculated as the damage location.

According to another aspect of the present invention, a structure health monitoring device that obtains the measured value from a distributed optical fiber sensor device that calculates the measured value through an optical fiber cable for measurement installed along the monitoring section of the monitored structure is disclosed.

A structural health monitoring device according to an embodiment of the present invention includes a memory for storing a command and a processor for executing the command, wherein the command has a preset low-fidelity reference and a preset high spatial resolution. Obtaining a measured value of the initial state of the monitoring target structure measured with a (high-fidelity reference) and generating a reference value, acquiring measured values for each first measurement point measured with the low spatial resolution, and 1. Monitoring the monitoring target structure at the low spatial resolution using measured values for each measurement point and the reference value, when an outlier is found among the obtained measurement values for each first measurement point as a result of the monitoring, Obtaining measured values for each second measurement point measured at the high spatial resolution in the section where the outlier was found, and calculating a damage location by detecting an outlier among the obtained measured values for each second measurement point. Implement structural health monitoring methods.

The structure health monitoring device and method according to an embodiment of the present invention monitors the structure using a distributed optical fiber sensor system capable of random position measurement and multi-spatial resolution measurement, and adaptively adjusts the spatial resolution to prevent damage to the structure. It can be detected accurately.

Figure 1 is a diagram showing the sensing concept of a point sensor and a distributed sensor.
Figure 2 is a flowchart showing a structural health monitoring method performed by a structural health monitoring device according to an embodiment of the present invention.
Figures 3 to 8 are diagrams for explaining the structural health monitoring method according to the embodiment of the present invention of Figure 2.
Figure 9 is a diagram schematically illustrating the configuration of a structural health monitoring device according to an embodiment of the present invention.

As used herein, singular expressions include plural expressions unless the context clearly dictates otherwise. In this specification, terms such as “consists of” or “comprises” should not be construed as necessarily including all of the various components or steps described in the specification, and some of the components or steps may be included in the specification. It may not be included, or it should be interpreted as including additional components or steps. In addition, terms such as "... unit" and "module" used in the specification refer to a unit that processes at least one function or operation, which may be implemented as hardware or software, or as a combination of hardware and software. .

Hereinafter, various embodiments of the present invention will be described in detail with reference to the attached drawings.

Figure 2 is a flowchart showing a structural health monitoring method performed by a structural health monitoring device according to an embodiment of the present invention, and Figures 3 to 8 are for explaining the structural health monitoring method according to an embodiment of the present invention in Figure 2. It is a drawing. Hereinafter, a structural health monitoring method according to an embodiment of the present invention will be described, focusing on FIG. 2, with reference to FIGS. 3 to 8.

In step S210, the structure health monitoring device 100 measures the initial state of the monitoring target structure 10 measured with a preset low spatial resolution (low-fidelity reference) and a preset high spatial resolution (high-fidelity reference). Obtain a value and create a reference value.

Figure 3 is a diagram schematically illustrating a structural health monitoring system according to an embodiment of the present invention.

Referring to FIG. 3, the structural health monitoring system according to an embodiment of the present invention may be configured to include a structural health monitoring device 100, a distributed optical fiber sensor device 200, and an optical fiber cable 210 for measurement.

The structure health monitoring device 100 according to an embodiment of the present invention can obtain continuous measured values of the monitoring section of the monitoring target structure 10 from the distributed optical fiber sensor device 200. Here, the distributed optical fiber sensor device 200 can calculate measured values through the optical fiber cable 210 for measurement installed along the monitoring section of the monitoring target structure 10.

For example, the distributed optical fiber sensor device 200 may be a BOCDA (Brillouin Optical Correlation Domain Analysis) device, and receives scattered waves at each measurement point of the optical fiber cable 210 for measurement according to a preset spatial resolution and receives the received scattered waves. Through signal processing, scattered waves can be converted into physical quantities related to strain or temperature to calculate measured values. Additionally, the measurement optical fiber cable 210 may be a general communication optical fiber cable to which a single-mode optical fiber core is applied.

The distributed optical fiber sensor device 200 may be implemented to operate with multiple spatial resolutions that vary depending on measurement variable settings. Here, multiple spatial resolutions may include low spatial resolution and high spatial resolution.

For example, low spatial resolution may be set to a unit length of several centimeters (cm), and high spatial resolution may be set to a unit length of several meters (m). At this time, the measurement point interval (Readout) can be set to several centimeters (cm) to several meters (m). The distributed optical fiber sensor device 200 can perform measurement through distributed sensing up to several kilometers (km).

In addition, the distributed optical fiber sensor device 200 can perform measurement at an arbitrary measurement point rather than sequentially measuring the measurement optical fiber cable 210 in the longitudinal direction.

For example, the measurement performance of the distributed optical fiber sensor device 200 required for large-scale social infrastructure may be defined as shown in FIG. 4.

That is, as shown in FIG. 5, the structure health monitoring device 100 uses the distributed optical fiber sensor device 200 to monitor the initial state of the monitoring target structure 10 for each preset high spatial resolution and preset low spatial resolution. By measuring , low spatial resolution reference values and high spatial resolution reference values can be generated.

For example, if damage occurs in the monitoring target structure 10 near the measurement optical fiber cable 210, the measured value at the point where the damage occurred may show a large difference from the measured value before damage (i.e., reference value). .

In step S220, the structure health monitoring device 100 acquires measured values for each measurement point measured at low spatial resolution and performs monitoring on the monitoring target structure 10 at low spatial resolution.

That is, referring to FIG. 6, the structure health monitoring device 100 controls the distributed optical fiber sensor device 200 to measure at low spatial resolution, and then measures the data at low spatial resolution from the distributed optical fiber sensor device 200. Measured values for each measurement point can be periodically acquired, and the difference between the obtained measurement value for each measurement point and the low spatial resolution standard value can be calculated. Additionally, the structural health monitoring device 100 may detect an outlier by checking whether the calculated difference value exceeds a preset threshold.

For example, the structural health monitoring device 100 may perform anomaly detection using the Median Absolute Deviation (MAD) algorithm on the calculated difference values for each measurement point. Here, the MAD algorithm is a method of detecting outliers using the median absolute deviation.

In step S230, the structural health monitoring device 100 determines whether an outlier is found in the measurement values for each measurement point measured at low spatial resolution.

The structural health monitoring device 100 may determine an outlier discovery section including a measurement point where the calculated difference value exceeds a preset threshold as a rough damage section.

In step S240, when an outlier is found, the structural health monitoring device 100 acquires measured values for each measurement point measured with high spatial resolution in the section where the outlier was found among the monitoring sections.

That is, the structure health monitoring device 100 controls the distributed optical fiber sensor device 200 to measure the outlier detection section with high spatial resolution, and then discovers the outliers measured with high spatial resolution from the distributed optical fiber sensor device 200. Measured values for each measurement point in the section can be obtained.

For example, as shown in FIG. 7, the distributed optical fiber sensor device 200 can perform measurement with high spatial resolution using a random-accessibility function that measures at a random measurement point. .

In step S250, the structural health monitoring device 100 detects outliers among the measured values for each measurement point measured with high spatial resolution and calculates the damage location.

That is, referring to FIG. 8, the structural health monitoring device 100 calculates the difference value between the measured value for each measurement point in the acquired outlier detection section and the high spatial resolution standard value, and the calculated difference value exceeds the preset threshold value. Outliers can be detected by checking whether the difference value is an outlier, and the measurement point where the difference value is determined to be an outlier can be calculated as the final damage location.

For example, the structural health monitoring device 100 may perform anomaly detection using the Median Absolute Deviation (MAD) algorithm on the calculated difference values for each measurement point.

In addition, the structure health monitoring device 100 may notify the manager of the monitoring target structure 10 of the calculated damage location.

For example, the structural health monitoring device 100 may be equipped with wired or wireless communication means, and may transmit a monitoring message including the calculated damage location to the manager's terminal through the provided communication means.

In this way, the structure health monitoring device 100 measures the entire monitoring section of the monitoring target structure 10 at low spatial resolution, thereby minimizing the time required for measurement and the resources required for computation, and the data discovered through measurement at low spatial resolution can be minimized. The exact location of damage can be calculated by randomly measuring the expected damage section with high spatial resolution. Through this, the structure health monitoring device 100 performs efficient and highly accurate monitoring within limited resources and can be effectively applied to objective and various unknown damage types. In addition to detecting damage to structures, it can also detect leakage of pipelines or dams. It can also be expanded to capture changes in temperature, etc., and it can be possible to make decisions about efficient maintenance plans, repair and reinforcement timing and methods, etc. during the life cycle of social infrastructure.

Figure 9 is a diagram schematically illustrating the configuration of a structural health monitoring device according to an embodiment of the present invention.

Referring to FIG. 9, the structural health monitoring device 100 according to an embodiment of the present invention includes a processor 110, a memory 120, a communication unit 130, and an interface unit 140.

The processor 110 may be a CPU or a semiconductor device that executes processing instructions stored in the memory 120.

Memory 120 may include various types of volatile or non-volatile storage media. For example, memory 120 may include ROM, RAM, etc.

For example, the memory 120 may store instructions for performing a structure health monitoring method according to an embodiment of the present invention.

The communication unit 130 is a means for transmitting and receiving data with other devices through a communication network.

The interface unit 140 may include a network interface and a user interface for accessing a network.

Meanwhile, the components of the above-described embodiment can be easily understood from a process perspective. In other words, each component can be understood as a separate process. Additionally, the processes of the above-described embodiments can be easily understood from the perspective of the components of the device.

Additionally, the technical contents described above may be implemented in the form of program instructions that can be executed through various computer means and recorded on a computer-readable medium. The computer-readable medium may include program instructions, data files, data structures, etc., singly or in combination. Program instructions recorded on the medium may be specially designed and configured for the embodiments or may be known and available to those skilled in the art of computer software. Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks, and magnetic tapes, optical media such as CD-ROMs and DVDs, and magnetic media such as floptical disks. -Includes optical media (magneto-optical media) and hardware devices specifically configured to store and execute program instructions, such as ROM, RAM, flash memory, etc. Examples of program instructions include machine language code, such as that produced by a compiler, as well as high-level language code that can be executed by a computer using an interpreter, etc. A hardware device may be configured to operate as one or more software modules to perform the operations of the embodiments, and vice versa.

The above-described embodiments of the present invention have been disclosed for illustrative purposes, and those skilled in the art will be able to make various modifications, changes, and additions within the spirit and scope of the present invention, and such modifications, changes, and additions will be possible. should be regarded as falling within the scope of the patent claims below.

10: Structure to be monitored
100: Structure health monitoring device
110: processor
120: memory
130: Department of Communications
140: Interface unit
200: Distributed optical fiber sensor device
210: Optical fiber cable for measurement

Claims (6)

In the structure health monitoring method performed by a structure health monitoring device that obtains the measured value from a BOCDA (Brillouin Optical Correlation Domain Analysis) device that calculates the measured value through a measurement optical fiber cable installed along the monitoring section of the monitored structure,
Obtain measured values of the initial state of the monitored structure measured with a preset low-fidelity reference and a preset high-fidelity reference to generate low-fidelity reference values and high-fidelity reference values. steps;
Obtain measured values for each first measurement point measured at the low spatial resolution, and monitor the monitoring target structure at the low spatial resolution using the obtained measured value for each first measurement point and the low spatial resolution reference value. Steps to perform;
As a result of the monitoring, when an outlier is found among the obtained measured values for each first measurement point, acquiring a measured value for each second measurement point measured with the high spatial resolution in the section where the outlier is found; and
Detecting outliers among the obtained measurement values for each second measurement point and calculating the location of damage,
The steps for performing the monitoring are:
After controlling the BOCDA device to measure at the low spatial resolution, the measured value for each first measurement point is periodically obtained from the BOCDA device, and the obtained measured value for each first measurement point and the low spatial resolution reference value are combined. Detect outliers by calculating a difference value and checking whether the calculated difference value exceeds a preset threshold,
The step of acquiring measured values for each second measurement point is,
After controlling the BOCDA device to measure the section where the outlier was found with the high spatial resolution, obtaining measured values for each second measurement point from the BOCDA device,
The step of calculating the damage location is,
Calculate a difference between the measured value for each second measurement point and the high spatial resolution reference value, detect an outlier by checking whether the calculated difference exceeds a preset threshold, and detect the measurement point determined as an outlier. A structural health monitoring method, characterized in that calculating to the damage location.
delete delete delete delete In a structure health monitoring device that obtains the measured value from a BOCDA (Brillouin Optical Correlation Domain Analysis) device that calculates the measured value through an optical fiber cable for measurement installed along the monitoring section of the monitored structure,
Memory for storing instructions; and
Including a processor that executes the instructions,
The command is:
Obtain measured values of the initial state of the monitored structure measured with a preset low-fidelity reference and a preset high-fidelity reference to generate low-fidelity reference values and high-fidelity reference values. steps;
Obtain measured values for each first measurement point measured at the low spatial resolution, and monitor the monitoring target structure at the low spatial resolution using the obtained measured value for each first measurement point and the low spatial resolution reference value. Steps to perform;
As a result of the monitoring, when an outlier is found among the obtained measured values for each first measurement point, acquiring a measured value for each second measurement point measured with the high spatial resolution in the section where the outlier is found; and
Performing a structure health monitoring method including the step of detecting outliers among the obtained measurement values for each second measurement point and calculating the damage location,
The steps for performing the monitoring are:
After controlling the BOCDA device to measure at the low spatial resolution, the measured value for each first measurement point is periodically obtained from the BOCDA device, and the obtained measured value for each first measurement point and the low spatial resolution reference value are combined. Detect outliers by calculating a difference value and checking whether the calculated difference value exceeds a preset threshold,
The step of acquiring measured values for each second measurement point is,
After controlling the BOCDA device to measure the section where the outlier was found with the high spatial resolution, obtaining measured values for each second measurement point from the BOCDA device,
The step of calculating the damage location is,
Calculate a difference between the measured value for each second measurement point and the high spatial resolution reference value, detect an outlier by checking whether the calculated difference exceeds a preset threshold, and detect the measurement point determined as an outlier. A structural health monitoring device, characterized in that for calculating the damage location.

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