JP7359378B2 - Information board anomaly detection system - Google Patents

Description

The present invention relates to an information board abnormality detection system for diagnosing abnormalities in the mounting state of information boards installed on pillars.

The mainstream method for detecting the mounting status of information boards installed on pillars has been to conduct periodic inspections by inspectors, either visually or using some type of instrument. Furthermore, a conventional technique has been disclosed that easily and quickly performs a quantitative test for cracks that occur over time in information boards that are subject to abnormality diagnosis of the installation state (see, for example, Patent Document 1).

In Patent Document 1, a fluorescent dye that emits light when excited by excitation light such as ultraviolet rays or blue-based visible light is mixed in advance into an information board that is an object of abnormality diagnosis. Then, the information board is irradiated with a light source that emits ultraviolet rays or blue-based visible light, and the occurrence of cracks is determined quantitatively by visual inspection or by analyzing images captured by a CCD camera or the like.

Japanese Patent Application Publication No. 2013-83493

However, the conventional technology has the following problems.
Although Patent Document 1 enables quantitative abnormality diagnosis of the installation state, it is basically based on periodic inspections by inspectors. Furthermore, in Patent Document 1, it is necessary to mix a fluorescent dye in advance into the information board to be diagnosed as an abnormality.

On the other hand, in recent years, there has been a demand for an abnormality diagnosis system that can diagnose abnormalities in the mounting state of information boards in a shorter cycle than regular inspections and can be performed unattended without the intervention of an inspector. Additionally, there is an increasing need to quantitatively diagnose the deterioration of the mounting condition of information boards installed on pillars over a long period of time. Furthermore, it is desired that the system can be easily applied not only to new information boards but also to existing information boards.

In detecting accumulated fatigue of information boards, we accurately measure and count the repeated stress applied to the pillars to which the information boards are attached, and from the results of a history analysis of repeated stress applied to the pillars, we can determine past accumulated fatigue and future stress. Accumulated fatigue can be predicted.

A strain gauge or the like is used to measure the stress applied to the strut. However, due to their nature, strain gauges have poor durability and are unsuitable for long-term measurements.

The present invention was made in order to solve the above-mentioned problems, and it is possible to prevent accumulated fatigue of information boards over a long period of time without requiring periodic inspections by inspectors, based on the stress applied to the pillars. Another purpose of the present invention is to obtain a system for diagnosing abnormalities in information boards that can be quantitatively diagnosed.

An abnormality diagnosis system for an information board according to the present invention includes an acceleration sensor that is installed on a support that is a target of abnormality diagnosis or an information board attached to the support, and that measures acceleration information, and from the acceleration information measured by the acceleration sensor. This information board abnormality detection system includes a diagnosis section that detects accumulated fatigue of information boards by estimating the stress applied to the pillars. The diagnosis unit further includes a strain measurement sensor that temporarily measures strain information at the installation location by temporarily installing it at or near the concentrated area so that it can be held by the frictional force caused by compression, and the diagnosis unit includes: With the strain measurement sensor temporarily installed in the preliminary preparation stage , acceleration information measured by the acceleration sensor and strain information measured by the strain measurement sensor are acquired at the same time for a predetermined period, and multiple pieces of acceleration information are obtained. Calculate the correlation between acceleration information and strain information from multiple pieces of distortion information for each of After estimation, strain information is generated from the acceleration information measured by the acceleration sensor using the estimated conversion formula or conversion coefficient, so that it can be applied to the pillar without using a strain measurement sensor during actual operation. This method estimates the stress caused by

According to the present invention, a strain measurement sensor that is not suitable for long-term measurement is temporarily installed, a conversion coefficient for converting acceleration to strain is calculated, and during actual operation, acceleration information obtained from the acceleration sensor is The system is equipped with a configuration that can convert into distortion using conversion coefficients calculated in advance. As a result, we developed an abnormality diagnosis system for information boards that can quantitatively diagnose the accumulated fatigue of information boards over a long period of time based on the stress applied to the struts, without the need for periodic inspections by inspectors. Obtainable.

FIG. 1 is an explanatory diagram showing a structure that is a target for abnormality diagnosis in Embodiment 1 of the present invention, in which (A) is a front view and (B) is an enlarged view of a base portion of a support. FIG. 1 is a configuration diagram of an information board abnormality detection system according to Embodiment 1 of the present invention. 2 is a flowchart showing a series of processing for measuring the correlation between distortion and acceleration, which is executed in the information board abnormality detection system according to Embodiment 1 of the present invention. FIG. 3 is a diagram showing an example of the correlation between acceleration information and distortion information in Embodiment 1 of the present invention. 2 is a flowchart showing a series of abnormality detection processes executed in the information board abnormality detection system according to Embodiment 1 of the present invention. 12 is a flowchart showing a series of processes of a first method for determining a conversion coefficient based on the results of simultaneous measurement of acceleration and strain in Embodiment 2 of the present invention. FIG. 7 is an explanatory diagram showing processing at each stage in the first method according to Embodiment 2 of the present invention, and is shown divided into (A) to (G). 12 is a flowchart showing a series of processes of a second method for determining a conversion coefficient based on the results of simultaneous measurement of acceleration and strain in Embodiment 2 of the present invention. FIG. 7 is an explanatory diagram showing processing at each stage in a second method according to Embodiment 2 of the present invention, and is shown divided into (A) to (E).

Hereinafter, preferred embodiments of the information board abnormality detection system of the present invention will be described using the drawings.
The present invention relates to a system for diagnosing an abnormality in the mounting condition of an information board by determining the accumulated fatigue of the information board based on the stress applied to the support column, and the present invention relates to a system for diagnosing an abnormality in the installation state of an information board by determining the accumulated fatigue of the information board based on the stress applied to the support column. The correlation between the measured value and the measured value of acceleration information is analyzed accurately, and during actual operation, the measured value of acceleration information and the correlation analyzed in advance can be used to calculate the The technical feature is that the applied stress is estimated with high accuracy to determine the cumulative fatigue of the information board.

In a fatigue prediction system for an information board using such an acceleration sensor, the performance depends on how accurately the acceleration-stress conversion coefficient can be calculated. In the present invention, since the relationship between acceleration information and strain (stress) information is calculated after error factors are removed, extremely accurate conversion coefficients can be calculated.

Embodiment 1.
FIG. 1 is an explanatory diagram showing a structure that is an object of abnormality diagnosis in Embodiment 1 of the present invention, in which (A) is a front view and (B) is an enlarged view of the base of a support column. In FIG. 1, the structure whose installation state is to be diagnosed is constructed by having an information board 1 attached to the upper part of a support column 2. An example of the information board 1 is a road information board installed on a road, and pedestrians or drivers can obtain necessary information by visually recognizing the road information board.

A structure in which the information board 1 is installed on the top of the support column 2 will have an upper load. Therefore, fatigue of the support column 2 progresses due to repeated stress vibrations caused by external force, which may lead to damage. In order to prevent catastrophic damage to the struts 2, it is important to observe the accumulated fatigue of the struts 2 and know the lifespan of the struts 2.

As mentioned above, strain gauges may be used to measure the stress applied to the struts. However, strain gauges have poor durability due to their nature and are not suitable for long-term measurements. Considering durability, it is conceivable to use an acceleration sensor instead.

Here, in order to accurately measure accumulated fatigue from acceleration, it is necessary to accurately calculate the stress applied to the stress concentration part of the support column from the acceleration information measured by the acceleration sensor. However, even for similar structures including the information board 1 and the support columns 2, the relationship between acceleration and stress will differ due to individual differences and slight differences in design.

Accordingly, in the present invention, by adopting the following configuration, an abnormality detection system for information boards is realized that combines improved accuracy in measuring accumulated fatigue and improved durability of the sensor.
(Configuration 1) A configuration is provided in which accumulated fatigue is estimated using the acceleration sensor 20 during normal operation. This configuration aims to improve the durability of the sensor.

(Configuration 2) In the preliminary preparation stage before actual operation, the strain measurement sensor 40 can be installed at or near the stress concentration part of the support column where accumulated fatigue is to be measured, and the acceleration sensor 20 and strain measurement sensor 40 can be installed. It is equipped with a configuration that accurately determines the correlation between the two by performing simultaneous measurements. With this configuration, the stress applied to the stress concentration portion of the support column can be accurately calculated from the measurement results of the acceleration sensor 20 without using the strain measurement sensor 40 during actual operation.

As shown in FIG. 1, in the information board abnormality detection system according to the first embodiment, an acceleration sensor 20 is installed at the top of the support column 2, and acceleration information measured by the acceleration sensor 20 is processed by a relay device 30. By doing so, configuration 1 is realized.

In addition, as shown in FIG. 1, the information board abnormality detection system according to the first embodiment temporarily installs a strain measurement sensor 40 at or near the stress concentration part of the support column 2 in the preparatory stage before actual operation. to be installed. Here, the strain measurement sensor 40 can be installed at or near the stress concentration part of the support column 2 so that it can be held by the frictional force caused by compression. Then, in the preliminary preparation stage, the acceleration information measured by the acceleration sensor 20 and the strain information of the stress concentration part measured by the strain measurement sensor 40 are read into the relay device 30 for a predetermined period at the same timing, and the Configuration 2 is realized by accurately determining the correlation.

Next, the configuration of the information board abnormality detection system according to the first embodiment will be described using FIG. 2. FIG. 2 is a configuration diagram of an information board abnormality detection system according to Embodiment 1 of the present invention. The information board abnormality detection system according to the first embodiment includes a data processing device 10, an acceleration sensor 20, a relay device 30, and N (N is an integer) strain measurement sensors 40(1) to 40(N). It is composed of

In the information board abnormality detection system according to the first embodiment, if at least one strain measurement sensor 40 is temporarily installed, it is possible to determine the correlation between acceleration information and strain information. Furthermore, when a plurality of N strain measurement sensors are used, each function is common. Therefore, in the following description, if there is no need to distinguish between the respective strain measurement sensors, they will be simply referred to as strain measurement sensors 40 without using the subscripts (1) to (N).

The acceleration sensor 20 has a sensor section 21 and an acceleration information output section 22, and is installed at the top of the support column 2. Note that the installation position of the acceleration sensor 20 is not limited to the top of the support column 2, and may be installed at a position other than the top of the support support 2, or on the information board 1 attached to the support support 2.

Generally, the acceleration sensor 20 has a longer lifespan than the strain measurement sensor 40, and abnormality determination during actual operation is performed using only acceleration information measured by the acceleration sensor 20.

The sensor unit 21 is, for example, a three-axis acceleration sensor using a thin film crystal resonator. Further, the acceleration information output unit 22 converts the analog signal regarding the three-axis acceleration at the top of the support column 2 into a digital signal at a predetermined sampling rate (for example, a sampling rate of 50 Hz), and sends it to the relay device 30 as acceleration information. Send.

On the other hand, the strain measurement sensor 40 is installed so that it can be temporarily held at or near the stress concentration part of the support column 2 before starting the operation of the abnormality detection device. Note that the stress concentration part is a general term for a position including a part where stress is concentrated or its vicinity. Furthermore, the strain measurement sensor 40 can be connected to the relay device 30.

The sensor section 41 enables stress measurement using, for example, a friction type strain gauge. Further, the distortion information output unit 42 converts the analog signal detected by the sensor unit 41 into a digital signal at a predetermined sampling rate (for example, a sampling rate of 50 Hz), and transmits the digital signal to the relay device 30 as distortion information.

The relay device 30 is attached to the support column 2, as shown in FIG. The relay device 30 then converts the acceleration information and strain information based on the acceleration information received from the acceleration information output section 22 in the acceleration sensor 20 and the strain information received from the distortion information output section 42 in the strain measurement sensor 40. Find the correlation.

More specifically, the relay device 30 transmits the acceleration information measured by the acceleration sensor 20 and the strain information measured by the strain measurement sensor 40 at the same time in a state where the strain measurement sensor 40 is temporarily installed. The correlation between acceleration information and distortion information is calculated. The correlation here refers to a conversion formula or conversion coefficient for converting acceleration information to distortion information.

Note that, as shown in FIG. 1, when a plurality of strain measurement sensors 40 are installed in a stress concentration area, an appropriate correlation can be obtained depending on each installation location.

By using the correlation calculated in advance, the relay device 30 can convert the acceleration information measured by the acceleration sensor into distortion information after the distortion measurement sensor 40 is removed. Then, the relay device 30 sequentially stores the converted and generated distortion information in the storage unit together with the time information at which the acceleration information was acquired. Further, the relay device 30 transmits distortion information and time information to the data processing device 10 every time distortion information is generated.

The diagnosis unit 11 in the data processing device 10 estimates the accumulated fatigue of the support column 2 to be diagnosed based on the strain information and time information received from the relay device 30, and determines whether it is normal or abnormal. . Furthermore, if it is necessary to store strain information and measurement time information for a long period of time, the data processing device 10 can also store them in a large-capacity storage unit.

In this way, before starting the operation of the abnormality detection device, the relay device 30 simultaneously measures acceleration information and strain information for a certain period of time, analyzes the correspondence between the two, and converts acceleration into stress. A conversion formula or conversion coefficient can be calculated as an appropriate value depending on the installation environment. As a result, it is possible to realize an abnormality detection system for information boards that can absorb the relationship between acceleration and stress due to individual differences in structures and exhibit stable diagnostic performance.

A series of abnormality diagnosis methods based on such accumulated fatigue will be described below with reference to FIGS. 3 to 5. FIG. 3 is a flowchart showing a series of processing for measuring the correlation between distortion and acceleration, which is executed in the information board abnormality detection system according to Embodiment 1 of the present invention. Moreover, FIG. 4 is a diagram showing an example of the correlation between acceleration information and distortion information in Embodiment 1 of the present invention. Further, FIG. 5 is a flowchart showing a series of abnormality detection processes executed in the information board abnormality detection system according to Embodiment 1 of the present invention.

Note that steps S301 to S308 shown in FIG. 3 are all steps performed in advance preparation stage before actual operation, and include both processing by the operator and processing executed by the abnormality detection system. .

In step S301, the operator installs the strain measurement sensor 40 at or near the stress concentration area. Furthermore, in step S302, the operator connects the strain measurement sensor to the relay device 30. As a result, in step S303, a connection is established, and the relay device 30 can now read the strain information output from the temporarily installed strain measurement sensor 40.

Next, in step S304, the relay device 30 simultaneously measures acceleration information and strain information, and sequentially stores the measurement results in the storage unit. Note that the operator may intentionally vibrate the support column 2 during the simultaneous measurement in step S304. Then, in step S305, the relay device 30 ends the simultaneous measurement after a predetermined period of time has elapsed.

Next, in step S306, the relay device 30 calculates a conversion coefficient indicating the correlation between acceleration information and distortion information by analyzing the measurement results in step S304. Note that when the measurement results obtained in step S304 are plotted on a plane with acceleration on the horizontal axis and distortion on the vertical axis, a relationship as shown in FIG. 4 is obtained as an example. Therefore, the relay device 30 can calculate a conversion coefficient for converting acceleration into distortion from the measurement result obtained in step S304.

Next, in step S307, the operator disconnects the temporarily connected relay device 30 and strain measurement sensor 40. Furthermore, in step S308, the operator removes the strain measurement sensor 40 that was temporarily installed to calculate the conversion coefficient from the support 2, and ends the series of processing.

In addition, in the explanation of the flowchart of FIG. 3 mentioned above, the relay device 30 which acquired distortion information was the structure which calculates a conversion coefficient. However, the present invention is not limited to such a configuration. A calculation processing unit is provided on the temporarily installed strain measurement sensor 40 side, and by acquiring acceleration information via the relay device 30, a conversion coefficient is calculated within the calculation processing unit, and the calculated conversion coefficient is sent to the relay device 30. It is also possible to have a configuration in which it is sent back.

Furthermore, when calculating the conversion formula or conversion coefficient, the relay device 30 can also perform the following filtering process. That is, the relay device 30 performs a filtering process on the acquired acceleration information and distortion information to remove unnecessary high-frequency components and low-frequency components that cause errors, and then uses the calculation result of the correlation between the two. It is possible to estimate the conversion formula or conversion coefficient. By performing such filtering processing, it becomes possible to calculate correlations with higher accuracy.

Next, the flow of a series of abnormality detection processing will be explained using the flowchart of FIG. In step S501, the relay device 30 acquires acceleration information from the acceleration sensor 20. Next, in step S502, the relay device 30 converts the acceleration information obtained in step S501 into distortion using a conversion coefficient determined in advance.

Then, in step S503, the relay device 30 diagnoses the information board for abnormality by calculating the accumulated fatigue of the structure made up of the information board 1 and the pillars 2 based on the converted distortion.

As described above, according to the first embodiment, a strain measurement sensor that is not suitable for long-term measurement is temporarily installed, a conversion coefficient for converting acceleration to strain is calculated, and during actual operation, It has a configuration that can convert acceleration information acquired from an acceleration sensor into distortion using a conversion coefficient calculated in advance. As a result, the accumulated fatigue of the structure to be diagnosed can be accurately calculated using an acceleration sensor suitable for long-term measurement. In other words, we have created an abnormality diagnosis system for information boards that can quantitatively diagnose the accumulated fatigue of information boards over a long period of time based on the stress applied to the struts, without requiring periodic inspections by inspectors. realizable.

Embodiment 2.
In the second embodiment, two specific methods for determining conversion coefficients based on simultaneous measurement results of acceleration and strain will be described. Note that, as preprocessing common to each method, only components near the resonant frequency of the object to be measured are extracted using a digital filter.

<First method>
The first method will be explained using FIGS. 6 and 7. FIG. 6 is a flowchart showing a series of processes of the first method for determining conversion coefficients based on the results of simultaneous measurement of acceleration and strain in Embodiment 2 of the present invention. Further, FIG. 7 is an explanatory diagram showing the processing at each stage in the first method according to the second embodiment of the present invention, and is shown divided into (A) to (G).

In step S601, the relay device 30 simultaneously measures acceleration and strain for a predetermined period of time. This processing corresponds to the processing in step S304 and step S305 in FIG. 3 above. An example of raw waveforms acquired simultaneously is shown in FIG. 7(A).

Next, in step S602, the relay device 30 acquires resonance frequencies related to acceleration and distortion by performing FFT processing. An example of the waveform from which the resonance frequency was determined is shown in FIG. 7(B).

Next, in step S603, if the resonant frequencies obtained in step S602 are clearly different, the relay device 30 determines that the measurement has failed, and redoes the processing in steps S601 and S602.

Next, in step S604, the relay device 30 performs bandpass filter processing using a digital filter on each of the acceleration time series data and the distortion time series data, and extracts only components around the resonance frequency. Here, the band-pass filter processing performed on each of the acceleration time-series data and the strain time-series data corresponds to narrow-band band-pass filter processing with the same characteristics that includes the primary resonance frequency of the pillar 2. An example of a waveform in which only components around the resonance frequency are extracted is shown in FIG. 7(C).

Next, in step S605, the relay device 30 converts the distortion time-series data after the band-pass filter processing to the acceleration time-series data after the band-pass filter processing in a predetermined time direction. The cross-correlation coefficient is calculated by shifting one sampling at a time within the period range. An example of a state in which the time direction is shifted is shown in FIG. 7(D), and an example of a state in which the cross-correlation coefficient is the highest is shown in FIG. 7(E).

Next, in step S606, the relay device 30 obtains a cross-correlation function by plotting the cross-correlation coefficient over the entire range shifted by one sampling within a predetermined range. An example of the obtained cross-correlation function is shown in FIG. 7(F).

Next, in step S607, the relay device 30 obtains the time shift at which the cross-correlation function shown in FIG. 7(F) takes the maximum value.

Next, in step S608, the relay device 30 plots the acceleration data (X) and strain data (Y) at the same time on the XY plane, taking into account the time difference relationship obtained in step S607. , create a scatter plot. An example of the created scatter diagram is shown in FIG. 7(G).

Next, in step S609, the relay device 30 removes unique outliers from the data forming the scatter diagram.

Next, in step S610, relay device 30 calculates a regression line based on the scatter diagram and obtains the slope value of the regression line.

Finally, in step S611, the relay device 30 multiplies the obtained slope value by a conversion parameter according to material-dependent distortion to obtain a conversion coefficient, and ends the series of processing. By applying such a first method, transform coefficients can be obtained.

<Second method>
The second method will be explained using FIGS. 8 and 9. FIG. 8 is a flowchart showing a series of processes of a second method for determining conversion coefficients based on the results of simultaneous measurement of acceleration and strain in Embodiment 2 of the present invention. Further, FIG. 9 is an explanatory diagram showing the processing at each stage in the second method according to the second embodiment of the present invention, and is shown divided into (A) to (E).

In step S801, the relay device 30 simultaneously measures acceleration and strain for a predetermined period of time. This processing corresponds to the processing in step S304 and step S305 in FIG. 3 above. An example of raw waveforms acquired simultaneously is shown in FIG. 9(A).

Next, in step S802, the relay device 30 acquires resonance frequencies related to acceleration and distortion by performing FFT processing. An example of the waveform from which the resonance frequency was determined is shown in FIG. 9(B).

Next, in step S803, if the resonant frequencies obtained in step S802 are clearly different, the relay device 30 determines that the measurement has failed, and redoes the processing in steps S801 and S802.

Next, in step S804, the relay device 30 performs bandpass filter processing using a digital filter on each of the acceleration time series data and the distortion time series data, and extracts only components around the resonance frequency. Here, the band-pass filter processing performed on each of the acceleration time-series data and the strain time-series data corresponds to narrow-band band-pass filter processing with the same characteristics that includes the primary resonance frequency of the pillar 2. An example of a waveform in which only components around the resonance frequency are extracted is shown in FIG. 9(C).

Note that the processing from step S801 to step S804 is the same as step S601 to step S604 in the first method.

Next, in step S805, the relay device 30 performs cycle counting processing on the acceleration data using the rainflow method, and obtains total amplitude data. Similarly, in step S806, the relay device 30 performs cycle counting processing on the distortion data using the rainflow method, and obtains total amplitude data. The results of cycle counting processing performed on acceleration data and strain data are shown in FIG. 9(D). Note that although the rainflow method is used for cycle counting processing here, the method for cycle counting processing is not limited to this.

Next, in step S807, the relay device 30 sorts the acceleration total amplitude data in descending order. Similarly, in step S808, the relay device 30 sorts the total distortion amplitude data in descending order.

Next, in step S809, the relay device 30 plots the sorted acceleration total amplitude data (X) and the sorted strain total amplitude data (Y) on the XY plane to create a scatter diagram. An example of the created scatter diagram is shown in FIG. 9(E).

Next, in step S810, the relay device 30 removes distortion total amplitude data that is less than or equal to a predetermined value and acceleration total amplitude data corresponding to the distortion total amplitude data from among the data forming the scatter diagram. Remove outliers.

Next, in step S811, the relay device 30 calculates a regression line based on the scatter diagram and obtains the slope value of the regression line.

Finally, in step S812, the relay device 30 multiplies the obtained slope value by a conversion parameter according to the material-dependent distortion to obtain a conversion coefficient, and ends the series of processing. By applying such a second method, transform coefficients can be obtained.

Note that the processing in step S811 and step S812 is the same as step S610 and step S611 in the first method.

As described above, according to the second embodiment, the specific processing configuration is to obtain a regression line between acceleration data and strain data, and to obtain a conversion coefficient for converting the acceleration data into distortion data from the slope of the regression line. It is equipped with Acceleration data and strain data are affected by a time lag due to overhead such as communication processing, and a phase difference occurs between their measured waveforms. Therefore, it is difficult to calculate the conversion coefficient by simply measuring the waveforms of acceleration data and strain data.

Therefore, in the second embodiment, by applying the first method and the second method as described above, it is possible to remove the effects of time lag and phase difference and calculate conversion coefficients with high precision. It is said that As a result, the accumulated fatigue of the structure to be diagnosed can be accurately calculated using an acceleration sensor suitable for long-term measurement. In other words, we have created an abnormality diagnosis system for information boards that can quantitatively diagnose the accumulated fatigue of information boards over a long period of time based on the stress applied to the struts, without requiring periodic inspections by inspectors. realizable.

Reference Signs List 1 Information board, 2 Support column, 10 Data processing device, 11 Diagnosis section, 20 Acceleration sensor, 21 Sensor section, 22 Acceleration information output section, 30 Relay device, 40 Strain measurement sensor, 41 Sensor section, 42 Strain information output section.

Claims (3)

an acceleration sensor that is installed on a column that is a target of abnormality diagnosis or an information board attached to the column and measures acceleration information;
a diagnostic unit that detects accumulated fatigue of the information board by estimating stress applied to the pillar from the acceleration information measured by the acceleration sensor;
An information board abnormality detection system comprising:
In the preparation stage before actual operation, the strut is temporarily installed at or near the stress-concentrated area of the support so that it can be held by the frictional force caused by compression, and the strain information at the installation location is temporarily stored. It is further equipped with a strain measurement sensor that measures
The diagnostic department includes:
In the state in which the strain measurement sensor is temporarily installed in the advance preparation stage , the acceleration information measured by the acceleration sensor and the strain information measured by the strain measurement sensor are transmitted at the same time for a predetermined period of time. a conversion formula that calculates a correlation between the acceleration information and the distortion information from the plurality of distortion information for each of the plurality of acceleration information, and converts the acceleration information to the distortion information based on the calculation result; or estimate the conversion factor,
After estimating the conversion formula or the conversion coefficient, the distortion information is generated from the acceleration information measured by the acceleration sensor using the estimated conversion formula or the conversion coefficient. An abnormality detection system for an information board that estimates stress applied to the pillar without using the strain measurement sensor . an acceleration sensor that is installed on a pillar or an information board attached to the pillar and measures acceleration information;
a diagnostic unit that detects accumulated fatigue of the information board by estimating stress applied to the pillar from the acceleration information measured by the acceleration sensor;
An information board abnormality detection system comprising:
Further comprising a strain measurement sensor that temporarily measures strain information at or near a stress-concentrated portion of the support,
The diagnostic department includes:
In a state where the strain measurement sensor is installed, the acceleration information measured by the acceleration sensor and the strain information measured by the strain measurement sensor are acquired at the same time for a predetermined period, and a plurality of pieces of acceleration information are obtained. Calculating a regression line based on the acceleration information and the distortion information from the plurality of pieces of distortion information for each, estimating a conversion formula or conversion coefficient for converting the acceleration information to the distortion information based on the calculation result,
After estimating the conversion formula or the conversion coefficient, the strain information is generated from the acceleration information measured by the acceleration sensor using the estimated conversion formula or the conversion coefficient, and is applied to the support column. Information board anomaly detection system that estimates the stress caused by an acceleration sensor that is installed on a pillar or an information board attached to the pillar and measures acceleration information;
a diagnostic unit that detects accumulated fatigue of the information board by estimating stress applied to the pillar from the acceleration information measured by the acceleration sensor;
An information board abnormality detection system comprising:
Further comprising a strain measurement sensor that temporarily measures strain information at or near a stress-concentrated portion of the support,
The diagnostic department includes:
In a state where the strain measurement sensor is installed, the acceleration information measured by the acceleration sensor and the strain information measured by the strain measurement sensor are acquired at the same time for a predetermined period, and a time series of the acceleration information is obtained. obtain time-series data of the acceleration information and the strain information, and obtain a narrowband bandpass with the same characteristics that includes the primary resonance frequency of the pillar for both the time-series data of the acceleration information and the time-series data of the strain information. By performing filter processing, time series data of acceleration information after filter processing and time series data of distortion information after filter processing are generated, and time series data of acceleration information after filter processing and time series data of distortion information after filter processing are generated. Based on the time series data of the distortion information, calculate a regression line between the acceleration information and the distortion information , and estimate a conversion formula or conversion coefficient for converting the acceleration information to the distortion information based on the calculation result,
After estimating the conversion formula or the conversion coefficient, the strain information is generated from the acceleration information measured by the acceleration sensor using the estimated conversion formula or the conversion coefficient, and is applied to the support column. Information board anomaly detection system that estimates the stress caused by

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