JP7249145B2 - Conduit health diagnostic method - Google Patents

Description

TECHNICAL FIELD The present invention relates to a conduit health diagnosis method for diagnosing the health of a conduit by non-destructive inspection.

Various conduits such as ducts, various plant piping, water pipes, gas pipes, air supply pipes, sewage pipes, oil pipelines, gas pipelines, etc. are installed in building structures. These conduits are susceptible to corrosion, general corrosion, partial corrosion, thinning, pitting, erosion, erosion-corrosion, wear, cracking, pinholes, leakage, fatigue cracking, stress corrosion cracking, high cycle fatigue cracking, and internal protection. Soundness deteriorates due to exfoliation, clogging, adhesion of sediments, poor construction of joints, deterioration over time, etc. For this reason, soundness diagnosis of conduits has been conventionally performed by non-destructive inspection.

Specifically, corrosion, cracking, and the like are diagnosed by visual inspection, and the wall thickness, thinning, and cracking of conduits are diagnosed by ultrasonic measurement.

However, visual diagnosis is suitable for checking the condition of the outer surface of the conduit, but when trying to diagnose the inner surface of the conduit, the conduit must be opened. It hangs.

Ultrasonic measurement can only inspect and diagnose thinning and cracks in a small area where sensors are placed, so when inspecting a long conduit, sensors are placed in many places. It is necessary to carry out the measurement by

Under such circumstances, a ventilation inspection technique for a quench duct (for example, Patent Document 1) and a duct inspection technique using compressed gas pulses (for example, Patent Document 2) have been proposed.

However, the inspection techniques disclosed in Patent Literatures 1 and 2 cannot be said to be a simple method, and their application is limited to ducts, so they are not inspection methods that can be applied to conduits in general. In addition, from among the various inspection items described above, only holes, gaps, and surface components are inspected. Item testing is not disclosed.

JP 2007-252576 A JP-A-8-254477

In view of the above-described problems of the prior art, the present invention is directed to a pipeline health system that makes it possible to appropriately diagnose, by non-destructive inspection, all of the items that are thought to lead to poor soundness, regardless of the type of pipeline. An object of the present invention is to provide a sex diagnosis technique.

The present inventors conducted intensive studies and found that the above problems can be solved by the inventions described below, and completed the present invention.

The invention according to claim 1,
A conduit health diagnosis method for diagnosing the health of a conduit by non-destructive inspection,
Acquiring a feature value that serves as a reference index for diagnosing the soundness of the conduit based on the vibration waveform of the conduit or the frequency distribution obtained by numerically analyzing the vibration waveform;
A conduit health diagnosis method for diagnosing the health of the conduit based on the acquired change in the feature quantity,
Using a conduit of the same type as the conduit to be diagnosed and having been confirmed to be sound in advance, the vibration waveform of the conduit in operation is directly acquired by the AE sensor, and the feature amount is used as the reference feature amount. while getting as
Acquiring the feature quantity as a diagnostic feature quantity by directly acquiring the vibration waveform of the conduit in the operating state with an AE sensor using the conduit to be diagnosed,
A method for diagnosing the health of a conduit, comprising diagnosing whether or not the health of a conduit to be diagnosed is degraded based on the amount of change in the diagnostic feature amount from the reference feature amount.

The invention according to claim 2,
2. The conduit soundness diagnosis according to claim 1, wherein either the shape of the vibration waveform or the frequency of the evaluation peak selected from the natural vibration peaks obtained from the frequency distribution is used as the feature quantity. The method.

The invention according to claim 3,
As the reference feature amount,
3. The conduit according to claim 1 or 2, characterized in that, when a conduit to be diagnosed is newly installed, a feature value obtained based on a vibration waveform directly obtained from the conduit in an operating state by an AE sensor is used. is a health diagnostic method for

The invention according to claim 4 ,
4. The conduit soundness diagnosis method according to claim 1 , wherein the vibration waveform of the conduit to be diagnosed is measured at a fixed point over time.

According to the present invention, regardless of the type of conduit, it is possible to provide a conduit health diagnosis technique that enables appropriate diagnosis of all items that may lead to poor soundness by non-destructive inspection. can.

1 is a perspective view showing the configuration of a conduit to be diagnosed in an experimental example of the present invention; FIG. FIG. 5 is a diagram showing the relationship between the installation position of a sensor that detects a vibration signal and the hitting position in an experimental example of the present invention. FIG. 2 shows the estimated peak frequency at each corrosion stage of the conduit to be diagnosed shown in FIG. 1; It is the frequency distribution obtained by FFT-analyzing the vibration waveform measured near the hole. It is the frequency distribution obtained by FFT-analyzing the vibration waveform measured at the position 7m away from the hole. FIG. 6 is a diagram in which evaluation peak frequencies are extracted from the frequency distributions of FIGS. 4 and 5 and compared for each condition; FIG. 4 is an image diagram of the duct with the lining peeled off as viewed from the side; This is a vibration waveform measured in a duct with a lining attached. Vibration waveforms measured in a duct with peeled lining.

BEST MODE FOR CARRYING OUT THE INVENTION Hereinafter, the present invention will be described based on embodiments with reference to the drawings.

[1] Basic concept of the present invention First, the basic concept of the method for diagnosing the integrity of a conduit according to the present invention will be described.

The inventor of the present invention conducted various experiments and studies to solve the above-described problems of the present invention, and found that a decrease in the soundness of the duct causes a change in the vibration waveform, and a change in the frequency distribution obtained from the vibration waveform. Since these lead to changes, it was found that deterioration in the soundness of the conduit can be diagnosed by adopting these as feature quantities that serve as indicators for the criteria for diagnosing the soundness of the conduit.

That is, the method for diagnosing the soundness of a conduit according to the present invention acquires a feature quantity that serves as an index for diagnosing the soundness of a conduit based on the vibration waveform of the conduit and the frequency distribution obtained by numerically analyzing the vibration waveform. and diagnosing the soundness of the conduit based on the change in the acquired feature amount.

Specifically, as the soundness of the conduit declines, the shape of the vibration waveform and the frequency of the evaluation peak selected from the natural vibration peaks obtained from the frequency distribution change. It is possible to qualitatively diagnose the soundness of the conduit by adopting it as a feature quantity that serves as an index for diagnosing the quality of the conduit and by knowing the change in this feature quantity.

At this time, if the change in the characteristic amount and the degree of deterioration in soundness are associated in advance, the deterioration in the soundness of the conduit can be quantitatively diagnosed by knowing the change in the characteristic amount. can also

[2] Specific Embodiment Next, a specific embodiment will be described.

1. Acquisition of Feature Amount In the present embodiment, acquisition of a feature amount (reference feature amount) that serves as a criterion (diagnostic criterion) for diagnosing deterioration of soundness is performed using one of the following two methods. The soundness of the conduit can be diagnosed by comparing it with the feature quantity (diagnostic feature quantity) obtained from the conduit to be diagnosed.

(1) First soundness diagnosis method (obtaining reference feature values at the time of diagnosis)
A first method is to acquire a reference feature amount at the time of diagnosis. Specifically, a conduit that is of the same type as the conduit to be diagnosed and that has been confirmed to be sound in advance is used to acquire the feature quantity, which is used as the reference feature quantity.

On the other hand, using the conduit to be diagnosed, the feature quantity is similarly acquired. At this time, as described above, the feature amount changes as the soundness of the conduit deteriorates. , the health of the conduit to be diagnosed can be diagnosed.

(2) Second soundness diagnosis method (acquisition of reference feature values at the time of new installation)
A second method is to acquire a reference feature amount when a new pipeline is installed, considering that a pipeline whose soundness is known is used when the pipeline is newly installed.

As a result, it is possible to know the amount of change from the reference feature amount only by acquiring the feature amount using the diagnostic target conduit, and to efficiently diagnose the soundness of the diagnostic target conduit. In addition, even if the pipe to be diagnosed is no longer installed due to discontinuation of production, etc., the soundness can be diagnosed.

2. Establishment of Diagnosis Items and Diagnosis Criteria for Soundness Specific diagnosis items for diagnosing deterioration of pipe integrity include corrosion, general corrosion, partial corrosion, thinning, pitting, erosion, and erosion and corrosion, as described above. Corrosion, wear, cracking, pinholes, leakage, fatigue cracking, stress corrosion cracking, high-cycle fatigue cracking, peeling of internal protective material, clogging, adhesion of deposits, poor joint construction, joint deterioration over time. By selecting one or more diagnostic items from among them and diagnosing the degree of soundness for each diagnostic item, the soundness of the conduit can be diagnosed with high accuracy.

Specifically, a vibration simulation simulating a selected diagnostic item is performed in advance, a feature value is acquired, and a diagnostic criterion adapted to each diagnostic item is set, thereby diagnosing the soundness of the conduit.

3. Acquisition Method of Feature Amount Next, a specific method of acquiring a feature amount necessary for diagnosing deterioration of soundness will be described. As described above, the shape of the vibration waveform or the evaluation peak frequency arbitrarily selected from the peak frequency obtained from the frequency distribution obtained by numerically analyzing the vibration waveform is used as the feature quantity.

(1) Acquisition of vibration waveform The vibration waveform can be acquired by measuring the vibration signal generated by striking the duct to be measured with a hammer or the like to vibrate it. may be obtained.

In addition, when measuring the vibration signal due to excitation, an accelerometer that can acquire vibration, a microphone, etc. may be used, but it is possible to directly contact the measurement target and measure it, and the vibration signal can be acquired with high sensitivity. Preferably, an acoustic emission sensor (AE sensor) is used.

The hammer used for vibration excitation is not particularly limited to plastic hammers, rubber hammers, wooden hammers, test hammers, iron hammers, etc., but they are generally used for hammering inspection, are light in weight, and are easy to carry. A convenient test hammer is preferred.

(2) Acquisition of evaluation peak frequency A frequency distribution including natural frequencies can be obtained by performing numerical analysis on the vibration waveform acquired above and performing frequency analysis. An arbitrarily selected evaluation peak frequency can be obtained from the obtained frequency distribution.

In numerical analysis, known analysis methods such as fast Fourier transform (FFT), autoregressive maximum entropy method (MEM), autoregressive model (AR), and autoregressive-moving average model (ARMA) can be used. Among them, the FFT conversion is preferable because it can be processed in a short time.

In the above description, the vibration waveform is obtained by actual measurement when obtaining the feature quantity, but the vibration waveform may be obtained by using a vibration simulation based on a theoretical analysis. For the simulation by theoretical analysis, a known analysis method such as a method of performing eigenvalue analysis on each analysis model using the finite element method can be used.

4. Building a database When simulating the above vibrations, the type of conduit, the diagnostic item, and the amount of change from the reference feature value of the feature value (diagnosis criteria), which is the result of the simulation, are associated with each other and stored in advance in a personal computer or the like. can build a database of diagnostic criteria.

Then, by collating the feature values obtained from the diagnostic object corresponding to the diagnostic item with this database, it is possible to specifically diagnose how much the soundness is degraded in this diagnostic item. It is possible to know the appropriate timing for repair or replacement.

5. Utilization of Contour Diagrams When diagnosing the health of a conduit to be diagnosed as described above, feature values are acquired at multiple locations, and based on the acquired multiple feature values, a contour map of the feature values is created. It is possible to relatively evaluate the soundness in the region, and detect the difference between the sound portion and the non-sound portion of the conduit to be diagnosed.

By detecting the difference between the sound portion and the non-sound portion of the conduit in this way, it is possible to specifically know to what extent in the region the unsoundness of the conduit has progressed.

In addition, when the vibration waveform of the pipeline to be diagnosed is measured at a fixed point over time, it is possible to grasp the progress of deterioration due to aging and to predict the future progress. It is possible to accurately predict and prepare for the repair time and replacement time of the conduit.

[3] Effect of the Present Embodiment By applying the above-described present embodiment, the following effects can be obtained.

(1) The thinning of the inner surface, which cannot be visually confirmed unless the conduit is opened, can be diagnosed without opening the conduit, enabling efficient diagnosis.

(2) Corrosion, thinning, and cracks, which are difficult to detect visually, can also be detected.

(3) Ultrasonic measurement can only diagnose the location where the sensor is installed, but it can also detect leaks caused by cracks that occur far away from the sensor.

(4) By using the contour diagram, it is possible to diagnose the state of deterioration of soundness over the entire surface.

(5) By taking measurements at fixed points over time, it is possible to formulate an appropriate repair plan.

1. Experimental example 1
In this experimental example, it was confirmed that the frequency of the evaluation peak can be used as a feature quantity for diagnosing deterioration of soundness.

(1) Experimental method After machining the inner surface of a square tube simulating a duct to add scratches corresponding to thinning due to corrosion, the square tube was vibrated by hitting with a test hammer and the vibration signal was measured. . An AE sensor was used to measure the vibration signal.

FIG. 1 shows the square tube 1 used. In addition, in FIG. 1, 2 is a scratch added portion. Seven types of square tubes A to G below were prepared as diagnostic objects. Note that E, F, and G have micro holes that simulate cracks.
A: healthy,
B: thickness reduction 0.8 mm, range 20 mm square,
C: thickness reduction 0.8 mm, range 50 mm square,
D: thickness reduction 0.8 mm, range 100 mm square,
E: thickness reduction 1.6 mm, range 20 mm square,
F: thickness reduction 1.6 mm, range 50 mm square,
G: thickness reduction 1.6 mm, area 100 mm square.

FIG. 2 shows the hitting position and the sensor installation position. As shown in FIG. 2, the sensors were placed at the center of the scratched area and on the left and right sides thereof at intervals of 50 mm.

FFT analysis was performed based on the measured vibration waveform to acquire the frequency distribution. An evaluation peak was determined from the obtained frequency distribution, and its frequency (evaluation peak frequency) was obtained.

(2) Experimental Results Experimental results are shown in FIG. FIG. 3 is a diagram collectively showing the evaluation peak frequency of each diagnosis target.

From FIG. 3, it can be seen that at the measurement point (sensor installation position) 2 in the center of the flaw, the evaluation peak frequency tends to decrease as the size of the flaw increases, that is, as the range of thinning increases. . It is also found that at measurement points 1 and 3, which are 50 mm away from the center of the flaw, the evaluation peak frequency tends to decrease due to the expansion of the corrosion range in the center.

The above results also agree with theory. That is, the theoretical formula of bending vibration of a plate is as shown in the following formula, and generally, the vibration frequency f decreases as the plate thickness h decreases.

In the above formula,
f: natural frequency (Hz), a: side length (mm), h: plate thickness (mm)
λ: Constant due to boundary conditions and vibration mode, ρ: Density (kg/m ³ )
D=Eh ³ /12(1−ν ² ): flexural rigidity of the plate, E: Young's modulus (N/m ² ), ν: Poisson's ratio.

From the above experimental results, even for corrosion of the inner surface that cannot be visually confirmed, vibration measurement is performed by vibration with a hammer using an AE sensor, and evaluation peak frequency is obtained from the frequency distribution and evaluated. It was found that cracks (microholes) can be detected, and it was confirmed that the frequency of the evaluation peak can be used as a feature quantity for diagnosing deterioration in soundness.

2. Experimental example 2
In this experimental example, it was confirmed that, in the case of vibration measurement using an AE sensor, the presence of cracks can be detected even at a distant point, unlike ultrasonic inspection.

(1) Experimental method A soundness diagnosis experiment was conducted on a diagnosis target simulating cracks in a duct. In addition, a method of directly measuring without vibrating the object to be measured was used to acquire the vibration waveform.

Five types of ducts H to L below with different hole sizes were prepared for diagnosis. Note that the holes I to L have larger sizes in later stages.
H: no hole,
I: Microhole 01,
J: micro holes 02,
K: Crack 01,
L: crack 02;

An AE sensor was used to measure the vibration signal, and two measurement positions were set, one near the hole and the other 7 m away from the hole. The obtained signal waveform was numerically analyzed using FFT to obtain the frequency distribution.

(2) Experimental Results Experimental results are shown in FIGS. FIG. 4 shows the frequency distribution when the measurement position is set near the hole, and FIG. 5 shows the frequency distribution when the measurement position is set 7 m away from the hole. 4 and 5, the horizontal axis is frequency, and the vertical axis is vibration intensity. Also, the peaks marked with a circle are evaluation peaks. FIG. 6 is a diagram collectively showing the evaluation peak frequencies for each diagnostic object obtained from FIGS.

From the above experimental results, comparing the FFT peak frequencies obtained from the vibration waveforms when there is no crack in the duct and when there is no crack, the evaluation peak frequency decreases as the hole becomes larger as compared to when there is no hole. I know there is a tendency.

Moreover, the above tendencies were common both when the measurement position was set near the hole and when it was 7 m away from the hole. From this result, it was confirmed that, in the case of vibration measurement using the AE sensor, the presence of cracks (microholes) can be detected even at a point 7 m away, unlike ultrasonic inspection.

3. Example 3
In this experimental example, it was confirmed that the frequency distribution can be used as a feature quantity for diagnosing deterioration of soundness.

(1) Experimental method A duct whose inner lining was peeled off was used as a diagnosis target, and the vibration signal was measured by vibrating the diagnosis target by hitting it with a test hammer. An AE sensor was used to measure the vibration signal. FIG. 7 is an image diagram of the duct with the lining peeled off as viewed from the side. In FIG. 7, 3 is a duct and 4 is a lining. The lining 4 is applied to the entire inner surface of the duct 3.

Prepare a duct with the lining intact and a duct with the lining peeled off, vibrate each with a test hammer to measure the vibration signal, and perform numerical analysis using FFT on the signal waveform of the measured vibration signal to determine the frequency distribution. Obtained.

(2) Experimental Results Experimental results are shown in FIGS. FIG. 8 shows the frequency distribution (FFT waveform) of a duct whose lining is not peeled off, that is, a sound duct, and FIG. 9 is the FFT waveform of a duct whose lining is peeled off. 8 and 9, the horizontal axis is frequency, and the vertical axis is intensity (magnitude).

As shown in FIG. 8, in the sound duct, the vibration frequency distribution was broad. On the other hand, when the lining was peeled off and the soundness was lowered, there were many peaks in the frequency distribution as shown in FIG. In this way, since there is a large difference in the frequency distribution according to the difference in soundness, peeling of the lining that cannot be detected visually from the outside or by ultrasonic inspection can be detected by vibration measurement using an AE sensor using FFT. It was confirmed that the diagnosis can be made from the shape of the waveform.

Although the present invention has been described above based on the embodiments, the present invention is not limited to the above embodiments. Various modifications can be made to the above embodiment within the same and equivalent scope of the present invention.

1 Square tube 2 Scratches added part 3 Duct 4 Lining

Claims (4)

A conduit health diagnosis method for diagnosing the health of a conduit by non-destructive inspection,
Acquiring a feature value that serves as a reference index for diagnosing the soundness of the conduit based on the vibration waveform of the conduit or the frequency distribution obtained by numerically analyzing the vibration waveform;
A conduit health diagnosis method for diagnosing the health of the conduit based on the acquired change in the feature quantity,
Using a conduit of the same type as the conduit to be diagnosed and having been confirmed to be sound in advance, the vibration waveform of the conduit in operation is directly acquired by the AE sensor, and the feature amount is used as the reference feature amount. while getting as
Acquiring the feature quantity as a diagnostic feature quantity by directly acquiring the vibration waveform of the conduit in the operating state with an AE sensor using the conduit to be diagnosed,
A method for diagnosing the health of a conduit, comprising diagnosing whether or not the health of a conduit to be diagnosed is degraded based on the amount of change in the diagnostic feature amount from the reference feature amount. 2. The conduit soundness diagnosis according to claim 1, wherein either the shape of the vibration waveform or the frequency of the evaluation peak selected from the natural vibration peaks obtained from the frequency distribution is used as the feature quantity. Method. As the reference feature amount,
3. The conduit according to claim 1 or 2, characterized in that, when a conduit to be diagnosed is newly installed, a feature value obtained based on a vibration waveform directly obtained from the conduit in an operating state by an AE sensor is used. health diagnostic method. 4. The conduit soundness diagnosis method according to claim 1, wherein the vibration waveform of the conduit to be diagnosed is measured at a fixed point over time.

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