Method and system for identifying water-wet conditions

Abstract

To provide a method and system for identifying water-wet conditions that can easily identify the water-wet conditions inside an exterior wall of a building.SOLUTION: A calculation device 4 of an identification system 10 includes an amplitude ratio and phase difference calculation unit 4A that calculates the amplitude ratio and phase difference of a reflected wave received for each partitioned area, a cluster analysis unit 4B that performs cluster analysis to classify each partitioned area into clusters of whether or not it is water-wetted using the amplitude ratio and phase difference at each frequency, and a water-wet identification unit 4C that identifies whether or not each partitioned area is a partitioned area corresponding to water-wet based on classification results. Seven different frequencies are (1) 9.5 to 9.7 GHz, (2) 9.9 to 10.1 GHz, (3) 10.3 to 10.5 GHz, (4) 10.7 to 10.9 GHz, (5) 11.1 to 11.3 GHz, (6) 11.5 to 11.7 GHz, and (7) 11.9 to 12.1 GHz.SELECTED DRAWING: Figure 2

Description

[Technical field]

[0001] The present invention relates to a method and system for identifying a water-wet condition inside an exterior wall of a building. [Background technology]

[0002] The increase in second-hand and vacant houses has become a social problem, but concerns about quality are one of the reasons why reuse and re-distribution are slow. Meanwhile, while the legal framework for inspections etc. has been developed, most methods rely on visual inspections, which require knowledge and experience, and training takes time, so there are concerns that quality will continue to vary in the future. The proportion of second-hand and vacant houses is high among wooden houses, but the durability and speed of deterioration are largely determined by whether or not rainwater has infiltrated, which causes a decrease in strength and decay. In other words, the most important thing is to detect abnormal moisture in important structural parts early. The bearing walls (plywood) necessary for pillars and earthquake-resistant structures are installed inside the walls (between the interior and exterior materials), and their condition cannot be seen with the naked eye.

[0003] For example, Patent Document 1 discloses a method for inspecting the inside of the exterior wall of a building. In this inspection method, first, an X-ray generator is disposed on one side of the exterior wall so that it can irradiate X-rays toward the part to be inspected inside the exterior wall. Next, an X-ray detector is disposed on the other side of the exterior wall so that it can detect the X-rays irradiated from the X-ray generator toward the part to be inspected. Finally, X-rays are irradiated from the X-ray generator toward the part to be inspected. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2020-159890 A Summary of the Invention [Problem to be solved by the invention]

[0005] However, the X-ray inspection method requires special qualifications because it uses a radioactive source, and strict on-site protection is required, making the work difficult. In addition, it is difficult to accurately identify the water-wet state inside the exterior wall of a building using X-rays.

[0006] The present invention has been made in consideration of such problems, and its object is to provide a method and system for identifying water wetness that can easily identify the water wetness state inside the exterior wall of a building. [Means for solving the problem]

[0007] In view of the above-mentioned problems, the method for identifying a water-wet state of the inside of an exterior wall of a building is a method for identifying a water-wet state of the inside of the exterior wall from a reflected wave of an electromagnetic wave irradiated to the exterior wall, the method including at least an irradiation and receiving step of irradiating electromagnetic waves of seven different frequencies having a certain amplitude from a wall surface of the exterior wall toward the inside of the exterior wall, and receiving the reflected waves reflected inside the exterior wall at each of the frequencies, for each partitioned region of the wall surface of the exterior wall; an amplitude ratio and phase difference calculation step of calculating an amplitude ratio of the reflected wave to the amplitude of the electromagnetic wave at each of the frequencies and a phase difference of the reflected wave to the electromagnetic wave at each of the frequencies, received for each partitioned region; a cluster analysis step of performing a cluster analysis for each of the partitioned regions using at least one of the amplitude ratio and the phase difference at each of the frequencies, to classify each of the partitioned regions into clusters of at least the presence or absence of water-wetness; and a water-wetness identification step of identifying whether each of the partitioned regions is a water-wet region based on the classification results, wherein the seven different frequencies are frequencies within each of the ranges (1) to (7) below. (1) 9.5~9.7GHz (2) 9.9~10.1GHz (3) 10.3~10.5GHz (4) 10.7~10.9GHz (5) 11.1~11.3GHz (6) 11.5~11.7GHz (7) 11.9~12.1GHz

[0008] According to the present invention, in the irradiation and reception step, seven electromagnetic waves of different frequencies with a certain amplitude are irradiated from the wall surface of the exterior wall of the building toward the inside of the exterior wall, and the reflected waves reflected inside the exterior wall at each frequency are received. Such an operation is performed for each partitioned area of ​​the exterior wall. Here, as the seven different frequencies, frequencies in the ranges (1) to (7) described above are used. According to experiments by the inventors, each of these frequencies in the ranges (1) to (7) are effective frequencies for identifying the water-wet state. As a result, it is possible to obtain information on the reflected waves that contribute to identifying the water-wet state inside the exterior wall for each partitioned area of ​​the exterior wall of the building.

[0009] In the present invention, the amplitude ratio and phase difference calculation step calculates the amplitude ratio of the reflected wave to the amplitude of the electromagnetic wave at each frequency received for each partitioned area, and the phase difference of the reflected wave to the electromagnetic wave at each frequency. The calculated amplitude ratio and phase difference of the reflected wave are data that contribute to water wettability.

[0010] In the cluster analysis step, a cluster analysis is performed for each divided region, using at least one of the amplitude ratio and the phase difference at each frequency, to classify each divided region into clusters of at least whether it is wet or not. In the water-wetness identification step, it is possible to identify whether each divided region corresponds to a wet or not wet state from the classification results.

[0011] In this way, seven different frequencies that have a high contribution rate to identifying the water wetness state of the exterior wall of a building are used, making it possible to accurately identify the water wetness state of the exterior wall of a building.

[0012] In a more preferred embodiment, in the cluster analysis step, for each divided region, the amplitude ratio and the phase difference at each frequency are complex transformed to a real part and an imaginary part, and each divided region is classified into a cluster at least according to whether or not it is wet.

[0013] According to this aspect, in the cluster analysis step, data obtained by complex-transforming the amplitude ratio and phase difference of the reflected waves at each frequency into real and imaginary parts for each partition area is generated as data based on the amplitude ratio and phase difference. The complex-transformed real and imaginary part data are data on the same complex plane. Therefore, by using a combination of the real and imaginary part data, the water-wet state inside the exterior wall can be identified with higher accuracy.

[0014] In a further preferred embodiment, in the cluster analysis step, the following real parts and imaginary parts of the complex transformed real parts and imaginary parts are used to classify the data into clusters: (1) Imaginary part at frequencies in the range of 9.5 to 9.7 GHz (2) Real and imaginary parts at frequencies in the range of 9.9 to 10.1 GHz (3) Real and imaginary parts at frequencies in the range of 10.3 to 10.5 GHz (4) Imaginary part at frequencies in the range of 10.7 to 10.9 GHz (5) Real part at frequencies in the range of 11.1 to 11.3 GHz (6) Real and imaginary parts at frequencies in the range of 11.5 to 11.7 GHz (7) Real part at frequencies in the range of 11.9 to 12.1 GHz

[0015] In particular, according to the inventors' experiments, the wetness state of the inside of an exterior wall can be determined with greater accuracy by using the real and imaginary parts of the complex transformation of the amplitude ratio and phase difference of the reflected waves measured at these frequencies.

[0016] In a more preferred embodiment, in the irradiating and receiving step, the electromagnetic waves are irradiated from a wall surface on an indoor side of the exterior wall toward the inside of the exterior wall.

[0017] According to this embodiment, the electromagnetic waves emitted from the interior side of the exterior wall of the building are more likely to penetrate into the interior of the wall than from the exterior side of the exterior wall of the building. This makes it possible to more accurately identify the water-wet state of the exterior wall of the building. Furthermore, since the inspection can be performed from the interior side, there is no need to set up scaffolding outside the building for the inspection, and the inspection can be performed regardless of the weather.

[0018] The water-wet condition determining system of the present invention is a determining system that determines the water-wet condition of the inside of an exterior wall of a building from the reflected waves of electromagnetic waves irradiated to the exterior wall, and the determining system includes an irradiation and receiving device that irradiates electromagnetic waves of seven different frequencies having a certain amplitude from a wall surface of the exterior wall toward the inside of the exterior wall and receives the reflected waves reflected inside the exterior wall at each of the frequencies for each of the partitioned areas of the wall surface of the exterior wall, and a calculation device that performs calculations to determine the water-wet condition, and the calculation device receives the electromagnetic waves at each of the frequencies received for each of the partitioned areas. The present invention is characterized in that it includes at least an amplitude ratio and phase difference calculation unit that calculates an amplitude ratio of the reflected wave to the amplitude of an electromagnetic wave and a phase difference of the reflected wave to the electromagnetic wave at each of the frequencies; a cluster analysis unit that performs a cluster analysis for each of the divided areas using at least one of the amplitude ratio and the phase difference at each of the frequencies to classify each of the divided areas into clusters of whether or not the divided areas are wet; and a water wetting identification unit that identifies, from the classification results, whether or not each of the divided areas is wet, and the seven different frequencies are frequencies within each of the ranges (1) to (7) below. (1) 9.5~9.7GHz (2) 9.9~10.1GHz (3) 10.3~10.5GHz (4) 10.7~10.9GHz (5) 11.1~11.3GHz (6) 11.5~11.7GHz (7) 11.9~12.1GHz

[0019] According to the present invention, an irradiating and receiving device irradiates electromagnetic waves of seven different frequencies with a certain amplitude from the wall surface of an exterior wall of a building toward the inside of the exterior wall, and receives reflected waves reflected inside the exterior wall at each frequency. The irradiating and receiving device can perform such an operation for each partitioned area of ​​the exterior wall. Here, as the seven different frequencies, frequencies in the ranges (1) to (7) described above are used. According to experiments by the inventors, each of the frequencies in the ranges (1) to (7) is effective for identifying the water-wet state. This makes it possible to obtain information on reflected waves that contribute to identifying the water-wet state inside the exterior wall for each partitioned area of ​​the exterior wall of the building.

[0020] Here, the calculation device performs the following calculation. Specifically, the amplitude ratio and phase difference calculation unit calculates the amplitude ratio of the reflected wave to the amplitude of the electromagnetic wave at each frequency received for each divided area, and the phase difference of the reflected wave to the electromagnetic wave at each frequency. The calculated amplitude ratio and phase difference of the reflected wave are data that contribute to water wettability. The cluster analysis unit performs cluster analysis for each divided area using at least one of the amplitude ratio and phase difference at each frequency to classify each divided area into at least clusters of water wetness or non-wetness. The water wetness identification unit can identify whether each divided area corresponds to a divided area that is wet or not wet from the classification results. In this way, seven different frequencies that contribute highly to identifying the water wetness state of the exterior wall of a building are used, so that the water wetness state of the exterior wall of a building can be identified with high accuracy.

[0021] In a more preferred embodiment, the cluster analysis unit classifies each of the divided regions into clusters of at least whether or not the region is wet using real and imaginary parts obtained by complex transforming the amplitude ratio and the phase difference at each frequency.

[0022] The cluster analysis unit generates data for each partition area, which is obtained by complex-transforming the amplitude ratio and phase difference of the reflected waves at each frequency into real and imaginary parts, as data based on the amplitude ratio and phase difference. The complex-transformed real and imaginary part data are data on the same complex plane. Therefore, by using a combination of these real and imaginary part data, the water-wet state inside the exterior wall can be identified with higher accuracy.

[0023] In a further preferred embodiment, the cluster analysis unit classifies the complex transformed real and imaginary parts into clusters using the following real and imaginary parts: (1) Imaginary part at frequencies in the range of 9.5 to 9.7 GHz (2) Real and imaginary parts at frequencies in the range of 9.9 to 10.1 GHz (3) Real and imaginary parts at frequencies in the range of 10.3 to 10.5 GHz (4) Imaginary part at frequencies in the range of 10.7 to 10.9 GHz (5) Real part at frequencies in the range of 11.1 to 11.3 GHz (6) Real and imaginary parts at frequencies in the range of 11.5 to 11.7 GHz (7) Real part at frequencies in the range of 11.9 to 12.1 GHz

[0024] In particular, according to the inventors' experiments, the wetness state of the inside of an exterior wall can be determined with greater accuracy by using the real and imaginary parts of the complex transformation of the amplitude ratio and phase difference of the reflected waves measured at these frequencies. Effect of the Invention

[0025] According to the present invention, the water wetness state of the inside of the exterior wall of a building can be identified with high accuracy by using electromagnetic waves. [Brief description of the drawings]

[0026] [Figure 1] 1 is a schematic diagram of a water-wet state specifying system according to an embodiment of the present invention; [Diagram 2]2 is a block diagram of a computing device of the wet condition identifying system shown in FIG. 1. [Diagram 3] FIG. 2 is a diagram for explaining a partitioned region. [Figure 4] 13 is a table showing the amplitude ratio and phase difference calculated in an amplitude ratio and phase difference calculation step, and a table showing the real part and the imaginary part after complex transformation. FIG. [Diagram 5] FIG. 1 is a diagram for explaining a complex transformation. [Figure 6] 2 is a flow chart showing a determination flow using the water-wet state determining system shown in FIG. 1. [Figure 7] FIG. 13 shows a test specimen modeled after an exterior wall and the results of identifying the water-wet state of the test specimen. [Figure 8] 6(a) to 6(c) are diagrams showing the results of identifying the water-wet state of another test structure. [Figure 9] FIG. 1A is a diagram showing the results of the water-wet state determined under different conditions according to an embodiment, and FIG. 1B is a diagram showing the results of the water-wet state determined under different conditions according to a comparative example. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0027] Hereinafter, a method for identifying a water wetness state of an exterior wall of a building according to an embodiment of the present invention will be described with reference to Figs.

[0028] 1. Regarding exterior wall 20 As shown in Fig. 1, in this embodiment, the identification system 10 identifies the wetness state of the inside of an exterior wall 20 of a building from the reflected waves of electromagnetic waves irradiated to the exterior wall 20. In addition to the wetness state of the inside of the exterior wall of the building, the identification system 10 may also identify, for example, the presence or absence of pillars, fireproofing materials, heat insulating materials, wooden boards, braces (metal or wooden), piping, and wiring, and their arrangement states. In this case, in addition to the cluster of the presence or absence of wetness of the wooden board 24, a separate cluster corresponding to these is set.

[0029] In this embodiment, the exterior wall 20 is a member corresponding to the exterior wall of a building to be inspected. In this embodiment, the building is a wooden house, and the exterior wall 20 has a structure in which an exterior wall board 21 is provided on the exterior side and a plaster board 22 is provided on the interior side. The thickness of the plaster board 22 is preferably in the range of 9.5 mm to 25 mm.

[0030] Between the exterior wall board 21 and the gypsum board 22, for example, a wooden board 24 is provided as a structural plywood. The wooden board 24 is, for example, plywood, and the thickness of the wooden board 24 is preferably in the range of 6 to 12 mm. The thickness of the exterior wall board 21 is preferably in the range of 10 to 20 mm. A fireproof material (fiber-based fireproof material) 23 such as glass wool is provided between the gypsum board 22 and the wooden board 24. The thickness of the fireproof material 23 may be in the range of 0 to 125 mm, and a pillar may be provided between the gypsum board 22 and the wooden board 24. The pillar is a square pillar in the range of 105 to 125 mm. Furthermore, a ventilation layer 25 is formed between the exterior wall board 21 and the wooden board 24. The thickness of the ventilation layer 25 is in the range of 0 to 30 mm. The above-mentioned thickness of the fireproof material 23 of 0 mm corresponds to a state in which the fireproof material 23 is not provided, and the thickness of the ventilation layer 25 of 0 mm corresponds to a state in which the exterior wall board 21 and the wooden board 24 are in contact with each other.

[0031] In addition, as shown in FIG. 8(b), a metal plate 26 such as an aluminum plate or a stainless steel plate may be attached to the outside of the exterior wall board 21. Furthermore, as shown in FIG. 8(c), in a state where the ventilation layer 25 is formed, a heat insulating board 27 made of a foamed resin board such as polystyrene foam may be provided along the surface of the wood board 24 facing the ventilation layer 25, and the thickness of the heat insulating board 27 is preferably in the range of, for example, 20 to 90 mm. The materials and dimensions of each component that constitutes the exterior wall 20 described above are general, and it has been found through experiments by the inventor that, at least in a general exterior wall 20 including such components, the water wetness state inside the exterior wall 20 can be identified by a later-described identification system.

[0032] 2. Regarding the hardware of specific system 10 The identification system 10 identifies the water-wet state of the inside of the exterior wall of a building from the reflected waves of electromagnetic waves irradiated to the exterior wall. The identification system 10 includes an irradiation receiving device 3 that performs non-destructive testing using electromagnetic waves B. The irradiation receiving device 3 irradiates electromagnetic waves B of seven different frequencies with a certain amplitude from the wall surface 22a of the exterior wall 20 toward the inside of the exterior wall 20, and receives reflected waves C reflected inside the exterior wall 20 at each frequency, for each partitioned area A of the wall surface 22a of the exterior wall 20.

[0033] The irradiation receiving device 3 includes a housing 15. A handle 17 that an operator holds is provided on the upper part of the housing 15. Wheels 13 are provided on the lower part of the housing 15 at a position facing an outer wall 20, which is an object to be inspected. A transmitter 11 and a receiver 12 are disposed inside the housing 15.

[0034] The transmitter 11 is a device that irradiates the exterior wall 20 with electromagnetic waves B having a constant amplitude and a constant frequency while changing the frequency of the electromagnetic waves B in stages. The housing 15 is provided with a control device (not shown) that changes the frequency of the electromagnetic waves B of the transmitter 11 in stages, which will be described later. The transmitter 11 irradiates the electromagnetic waves B while changing the frequency of the electromagnetic waves B in stages by the control device in accordance with the rotation speed of the wheels 13. This allows the irradiation receiving device 3 (transmitter 11) to irradiate the electromagnetic waves B with the frequency changed in stages for each partitioned area A partitioned on the wall surface of the exterior wall 20, which will be described later.

[0035] In this embodiment, the transmitter 11 radiates electromagnetic waves B having frequencies in the following seven different ranges, specifically, (1) 9.5 to 9.7 GHz, (2) 9.9 to 10.1 GHz, (3) 10.3 to 10.5 GHz, (4) 10.7 to 10.9 GHz, (5) 11.1 to 11.3 GHz, (6) 11.5 to 11.7 GHz, and (7) 11.9 to 12.1 GHz, stepwise for each divided area A of the exterior wall 20. The transmitter 11 may further radiate electromagnetic waves B having frequencies other than these seven different frequencies, but the frequencies used to determine the presence or absence of a water-wet state are the seven frequencies in the ranges (1) to (7) described above. For this reason, the receiver 12 described later may not receive the reflected waves C when radiated with frequencies other than the seven frequencies in the ranges (1) to (7). In addition, the calculation device 4 described later may extract only the data of the reflected wave C when frequencies within each range of (1) to (7) are applied in a stepwise manner, and the water wetness state of the inside of the exterior wall 20 may be identified based on the extracted data.

[0036] The receiver 12 is a device that receives a reflected wave C that is the result of the electromagnetic wave B transmitted from the transmitter 11 being reflected by the exterior wall 20. Here, the electromagnetic wave transmitted (irradiated) by the transmitter 11 includes one that is reflected by the surface of the object to be inspected and one that is reflected after being refracted, attenuated, and transmitted inside the object to be inspected. The receiver 12 receives a wave that is the result of these reflected waves physically interfering with each other as the reflected wave C. The reflected wave C that is reflected inside the object to be inspected has a changed amplitude and frequency with respect to the electromagnetic wave B. The received reflected wave C is recorded in a storage device (not shown) provided in the housing 15 or a storage device (not shown) provided together with the calculation device 4.

[0037] The identification system 10 includes a calculation device 4 that performs calculations for identifying a water-wet state, and a display device 5 that displays the results of the calculations performed by the calculation device 4. In this embodiment, the calculation device 4 and the display device 5 are provided separately from the irradiation receiving device 3, but may be provided integrally with the irradiation receiving device 3.

[0038] 3. Software for Calculation Unit 4 The arithmetic unit 4 includes at least an amplitude ratio phase difference calculation unit 4A, a cluster analysis unit 4B, and a water wetting identification unit 4C. The amplitude ratio phase difference calculation unit 4A calculates the amplitude ratio of the reflected wave to the amplitude of the electromagnetic wave B at each frequency received for each divided area A, and the phase difference of the reflected wave C to the electromagnetic wave B at each frequency.

[0039] 3-1. Amplitude ratio phase difference calculation unit 4A Here, since the reflected wave C is a waveform composed of multiple frequencies, the frequency that is the main component of the reflected wave C (i.e., the frequency with the highest spectrum (largest amplitude)) is identified by frequency analysis using FFT or the like, and the amplitude ratio L and phase difference P are calculated from the amplitude and phase of the reflected wave C at the identified frequency. Note that the reflected wave C may be received directly, and the peak of the received waveform may be used as the amplitude, the phase of the peak period may be found, and the amplitude ratio L and phase difference P may be calculated from these amplitudes and phases. Figure 4 shows the calculated amplitude ratios L1, L2, ..., L7 and phase differences P1, P2, ..., P7 for seven frequencies (measurement frequencies) F1, F2, ..., F7.

[0040] In this embodiment, the frequencies F1 to F7 are in the ranges of the frequencies (1) to (7) described above, namely, [1] 9.6 GHz, [2] 10.0 GHz, [3] 10.4 GHz, [4] 10.8 GHz, [5] 11.2 GHz, [6] 11.6 GHz, and [7] 12.0 GHz. The values ​​of the frequencies (1) to (7) described above are the medians of the respective frequency ranges of (1) to (7), but it has been found that by selecting seven different frequencies within a range of ±0.1 GHz based on these medians, it is possible to identify the water wetness state inside the exterior wall 20, as described below.

[0041] 3-2. About Cluster Analysis Section 4B The cluster analysis unit 4B performs cluster analysis for each divided area A, classifying each divided area A into clusters of at least whether it is wet or not, using at least one of the amplitude ratio L and the phase difference P at each frequency F1 to F7. The cluster analysis may be performed using only the amplitude ratio L at each frequency F1 to F7, or may be performed using only the phase difference P at each frequency F1 to F7. However, in this embodiment, the cluster analysis is performed as follows. Specifically, the cluster analysis unit 4B includes a complex conversion unit 41, an identification data allocation unit 42, and a cluster classification unit 43.

[0042] 3-2-1. About the complex transform unit 41 The complex transformation unit 41 performs complex transformation on the amplitude ratios L1, L2, ..., L7 and phase differences P1, P2, ..., P7 at the frequencies F1, F2, ..., F7 for each divided region A. Specifically, as shown in Fig. 5, a point T corresponding to the amplitude ratio L and phase difference P is plotted on a complex plane, and the values ​​of the real part R and the imaginary part K on the real axis and the imaginary axis are calculated.

[0043] As a result, it is possible to obtain the calculated real parts R1, R2, ..., R7 and imaginary parts K1, K2, ..., K7 for each of the seven frequencies (measurement frequencies) F1, F2, ..., F7, as shown in Fig. 4. These results are identification data for identifying the water wet state.

[0044] Since the identification data of the complex-transformed real and imaginary parts are identification data on the same complex plane, by using a combination of these identification data, it is possible to identify a combination of identification data elements that can more accurately identify the internal condition of the exterior wall.

[0045] 3-2-2. Identification data allocation unit 42 The identification data allocation unit 42 allocates, for each divided area A, the following real parts and imaginary parts from among the complex-converted real parts and imaginary parts. (1) Imaginary part at frequencies in the range of 9.5 to 9.7 GHz (2) Real and imaginary parts at frequencies in the range of 9.9 to 10.1 GHz (3) Real and imaginary parts at frequencies in the range of 10.3 to 10.5 GHz (4) Imaginary part at frequencies in the range of 10.7 to 10.9 GHz (5) Real part at frequencies in the range of 11.1 to 11.3 GHz (6) Real and imaginary parts at frequencies in the range of 11.5 to 11.7 GHz (7) Real part at frequencies in the range of 11.9 to 12.1 GHz

[0046] Next, for each divided area A, as identification data based on the amplitude ratios L1, L2, ..., L7 and phase differences P1, P2, ..., P7 at each frequency F1, F2, ..., F7, of the calculated real parts R1, R2, ..., R7 and imaginary parts K1, K2, ..., K7, the real parts R2, R3, R5 to R7 and imaginary parts K1 to K4, K6 surrounded by ellipses in Figure 4 are assigned to each divided area A.

[0047] 3-2-3. Cluster Classification Unit 43 Here, among the complex-transformed real and imaginary parts, the above-mentioned real parts R2, R3, R5 to R7 and imaginary parts K1 to K4, K6 are used to classify into two clusters, one for wetness and the other for wetness. When performing cluster analysis, the number of types of the specified wetness and other internal states is set, and each divided area A is classified into which type it corresponds. As shown in FIG. 3, each divided area A of the wall surface 22a is a rectangular area divided into 12 vertically and 8 horizontally, divided into 10 rows and 8 columns. In this example, it is assumed that the upper reverse surface of the wooden board 24 of the exterior wall 20 is wetted with water in advance. In this case, two clusters are set: cluster "1" for the wooden board 24 not wetted with water, and cluster "2" for the wooden board 24 not wetted with water (dry).

[0048] Further, in the case of FIG. 7, each partitioned area A of the wall surface 22a is a rectangular area partitioned into 10 vertically and 8 horizontally, with 27 rows and 24 columns. Three clusters are set: a cluster "1" of pillars, a cluster "2" of the wooden board 24 not wet with water, and a cluster "3" of the wooden board 24 not wet with water. In this case, since there are three types of internal states, three types of clusters are set, and each partitioned area A is classified into one of the three types of clusters. The number of clusters may be set according to the types of members constituting the internal structure of the exterior wall 20 (pillars, fireproofing material, heat insulation material, wooden board, braces (metal or wood), piping and wiring, exterior wall board, gypsum board, air layer) and the position in the thickness direction of the exterior wall 20. However, if at least two clusters are set using the data of the amplitude ratio and phase difference obtained under the electromagnetic wave frequency conditions shown in (1) to (7) above, the wet area can be roughly specified.

[0049] As an ideal result of the cluster analysis, as shown in Fig. 3, the delimited area A in the upper half is classified into cluster "1" which identifies the type of dryness, and the delimited area A in the lower half is classified into cluster "2" which identifies the type of wetness. As shown in Fig. 3, the classification result of the cluster analysis is assigned to each delimited area A. When performing the cluster analysis, a non-hierarchical cluster analysis may be performed using the k-means method, or the delimited area A may be classified into which of the set types of clusters it belongs using another cluster analysis such as the EM algorithm.

[0050] 3-3. Water damage specific section 4C The water exposure identifying unit 4C identifies, based on the classification result, whether each divided area A is a divided area that is wet. The water exposure identifying unit 4C includes a classification result allocating unit 44 and a water exposure estimating unit 45.

[0051] The classification result allocation unit 44 assigns clusters "1" and "2" to each divided area A based on the classification results of the cluster classification unit 43. The water exposure estimation unit 45 identifies divided areas that are wet from the assignment results, and outputs the identification results to the display device 5. Here, the assignment results themselves may be output to the display device 5. For example, if one divided area A is cluster "1" and the surrounding eight divided areas A are cluster "2," the cluster "1" of the corresponding one divided area A may be replaced with cluster "2."

[0052] In this way, seven different frequencies that contribute highly to identifying the wet state of the building exterior wall 20 are used, so it is possible to accurately identify the wet state of the building exterior wall 20. By using the real parts R2, R3, R5 to R7 and imaginary parts K1 to K4, K6 obtained by complex transforming the amplitude ratio L and phase difference P of the reflected wave C measured at the above-mentioned seven frequencies, it is possible to identify the wet state of the inside of the exterior wall 20 with higher accuracy.

[0053] A method for identifying the water wet state will be described below with reference to the flow chart of FIG. First, in step S11, an irradiation and reception process is performed. Specifically, electromagnetic waves are irradiated to the exterior wall 20 and the reflected waves are received. Specifically, as shown in Fig. 1, electromagnetic waves B having a certain amplitude and a certain frequency are irradiated from the wall surface 22a (of the gypsum board 22) on the indoor side of the exterior wall 20 toward the inside of the exterior wall 20, and while the frequency of the electromagnetic waves B is changed stepwise, reflected waves C reflected inside the exterior wall 20 are received at each frequency (for each of the seven different frequencies mentioned above). This operation is performed for each partitioned area A of the wall surface 22a of the exterior wall 20.

[0054] The irradiation of the electromagnetic waves B and the reception of the reflected waves C for each divided area A are performed by holding the handle 17 of the irradiation receiving device 3 shown in FIG. 1, pressing the wheels 13 of the irradiation receiving device 3 against the wall surface 22a, and moving the irradiation receiving device 3 in the vertical direction (or horizontal direction) while rotating the wheels 13 against the wall surface 22a. This allows the irradiation receiving device 3 to irradiate the electromagnetic waves B with a stepwise changed frequency for each divided area A and receive the reflected waves C for each frequency. The same operation is repeated by shifting in the horizontal direction (or vertical direction). The frequency of the electromagnetic waves B is one of seven different frequencies within the ranges shown in (1) to (7) above, and the measurement frequency is changed stepwise for each divided area A.

[0055] In step S12, an amplitude ratio phase difference calculation step is performed. In this step, the amplitude ratio L of the reflected wave C at each frequency and the phase difference P of the reflected wave C relative to the electromagnetic wave B at each frequency received for each divided area A are calculated. As a result, the calculated amplitude ratios L1, L2, ..., L7 and phase differences P1, P2, ..., P7 are calculated for each of the seven frequencies (measurement frequencies) F1, F2, ..., F7.

[0056] Next, in steps S13 to S15, a cluster analysis process is performed. First, in step S13, the complex conversion unit 41 of the cluster analysis unit 4B performs complex conversion on the amplitude ratios L1, L2, ..., LN and phase differences P1, P2, ..., PN at the frequencies F1, F2, ..., FN for each divided area A.

[0057] Next, the process proceeds to step S14, where the identification data allocation unit 42 of the cluster analysis unit 4B allocates the complex-converted real parts R2, R3, R5-R7 and imaginary parts K1-K4, K6 to each partitioned region as identification data.The process proceeds to step S15, where the cluster classification unit 43 of the cluster analysis unit 4B classifies the multiple partitioned regions A into two clusters, one with and one without water-wet conditions, using the above-mentioned real parts R2, R3, R5-R7 and imaginary parts K1-K4, K6.

[0058] Next, in steps S16 and S17, a water-wetness identification process is performed. In this process, it is determined from the classification results whether each divided area A is a divided area that is wet. First, in step S16, the classification result allocation unit 44 of the water-wet identification unit 4C assigns a cluster, which is the classification result, to each divided area A. Next, the water-wetness estimation unit 45 of the water-wet identification unit 4C identifies divided areas that are wet from the assigned results, and outputs the identified results to a display device.

[0059] The inventor confirmed the water-wet state of the inside of the exterior wall using the specific system. Specifically, as shown in FIG. 7(a), a test structure 20A of an exterior wall 20 with casters attached to a plaster board assuming the indoor side was prepared. In this test structure 20A, in the inspection area surrounded by a chain line, a wooden pillar 28 exists in front of a wooden board 24 as an internal structure. In this state, a wooden board 24 was prepared in which the upper half was wet and the lower half was dry. Here, the thickness of the exterior wall board 21 is 16 mm, and the thickness of the plaster board 22 is 12.5 mm. The thickness of the pillar 28 and the fireproof material (glass wool) is 105 mm. The thickness of the wooden board (structural plywood) 24 is 9 mm. The thickness of the ventilation layer 25 is 18 mm. Electromagnetic waves of frequencies F1 to F7 shown in FIG. 4 were irradiated from the gypsum board 22 side, which is the indoor side, to each divided area A of the test structure 20A of the exterior wall 20 shown in FIG. 7(a), and reflected waves at each frequency F1 to F7 were received. From the received reflected waves, amplitude ratios L1 to L7 and phase differences P1 to P7 were measured, and by complex transforming these, real parts R1 to R7 and imaginary parts K1 to K7 were calculated for each frequency F1 to F7. Using the real parts R2, R3, R5 to R7 and imaginary parts K1 to K4, K6, three types of clusters consisting of dry pillars 28, parts of the wooden board 24 in a wet state, and parts of the wooden board 24 in a dry state were set for the multiple divided areas A, and cluster analysis was performed by the k-means method. The results are shown in FIG. 7(b). As is clear from FIG. 7(b), it was found that the divided area A in a wet state could be identified.

[0060] In order to reproduce the state in which the exterior wall board 21 is wet due to rainfall, the following test structure 20B was created. Specifically, in Fig. 7(a), a wooden board 24 was prepared in which the upper half was wet and the lower half was dry, while in Fig. 8(a), a test structure 20B was prepared that corresponds to the exterior wall 20 in which the entire wooden board 24 was dry, the upper half of the exterior wall board 21 was wet, and the lower half was not wet.

[0061] The following test structure 20C was created to reproduce a condition in which there was a metal obstacle on the exterior wall board 21. Specifically, in Fig. 8(b), a test structure 20C was prepared by further attaching a 3 mm metal plate (aluminum plate) 26 to the surface of the exterior wall board 21 in addition to the test structure 20A shown in Fig. 7(a).

[0062] The following test structure 20D was fabricated to reproduce the condition where an insulating board is provided on the exterior wall 20. Specifically, in Fig. 8(c), a test structure 20D was prepared in which a 30 mm thick insulating board (polystyrene foam) 27 was attached to the surface of the wooden board 24 on the exterior wall board 21 side of the test structure 20A shown in Fig. 7(a) and the thickness of the ventilation layer 25 was 15 mm.

[0063] The water-wet state of the test structures 20B to 20D in Figures 8(a) to (c) was identified in the same manner as the test structure 20A in Figure 7(a). From the identification results shown in Figures 8(a) to (c), it was found that the water-wet state can be identified regardless of the state, even if the exterior wall board 21 is wet due to rainfall, if there is a metal obstacle on the exterior wall board 21, or if there is a heat-insulating board on the exterior wall 20.

[0064] Furthermore, the wetness state of the test structure 20A was identified by cluster analysis using parameters different from those of the identification method described in Fig. 7(b). An example is shown in Fig. 9(a) and (b). Fig. 9(a) shows the result of identifying the wetness state by cluster analysis using the amplitude ratios L1 to L7 of the reflected wave C at the above-mentioned frequencies F1 to F7 (9.6 GHz, 10.0 GHz, 10.4 GHz, 10.8 GHz, 11.2 GHz, 11.6 GHz, 12.0 GHz).

[0065] FIG. 9(b) shows the result of identifying the water wetness state by performing a cluster analysis using the amplitude ratios L1 to L3 and phase differences P1 to P3 of the reflected wave C at frequencies F1 to F3 (9.6 GHz, 10.0 GHz, 10.4 GHz).

[0066] It is considered that the wetness state of the test structure 20A can be determined more accurately in the determination result of Fig. 9(a) than in Fig. 9(b). This is because a cluster analysis was performed using the amplitude ratios L1 to L7 at all frequencies F1 to F7. In addition, it was confirmed that the wetness state of the test structure 20A can be determined with high accuracy when using the phase differences P1 to P7 of the reflected waves at these frequencies F1 to F7, and even when using at least one of the real part and the imaginary part at each frequency F1 to F7.

[0067] In this way, it is possible to specify whether each divided area A is wet or not from the classification results by cluster analysis, and to specify the extent of water damage in the entire exterior wall 20. This is particularly effective for determining the wettability of large wall structures such as earthquake-resistant walls.

[0068] In addition, since seven different frequencies that have a high contribution rate to identifying the wetness state of the exterior wall 20 of the building are used, the wetness state of the exterior wall of the building can be identified with high accuracy. In addition, since the irradiated electromagnetic waves are in the microwave range, they are safer than radiation such as X-rays.

[0069] Although the embodiments of the present invention have been described in detail above, the present invention is not limited to the above-described embodiments, and various design modifications can be made without departing from the spirit of the present invention as described in the claims. [Explanation of symbols]

[0070] 3: irradiation receiving device, 4: calculation device, 4A: amplitude ratio phase difference calculation unit, 4B: cluster analysis unit, 4C: water wetting identification unit, 10: water wetting state identification system, 20: exterior wall, 24: wooden board, A: partition area, B: electromagnetic wave, C: reflected wave, F: frequency (measurement frequency), L: amplitude ratio, P: phase difference, R: real part, K: imaginary part

Claims

1. A method for determining a water-wet state inside an exterior wall of a building from a reflected wave of an electromagnetic wave irradiated to the exterior wall, comprising: an irradiation and reception process for irradiating seven different frequencies of electromagnetic waves having a certain amplitude from a wall surface of the exterior wall toward the inside of the exterior wall, and receiving the reflected waves reflected inside the exterior wall at each frequency for each partitioned region of the wall surface of the exterior wall; an amplitude ratio and phase difference calculation step of calculating an amplitude ratio of the reflected wave to the amplitude of the electromagnetic wave at each of the frequencies received for each of the divided regions, and a phase difference of the reflected wave to the electromagnetic wave at each of the frequencies; a cluster analysis step of performing a cluster analysis for each of the divided regions using at least one of the amplitude ratio and the phase difference at each of the frequencies to classify each of the divided regions into clusters according to whether or not the divided regions are wet; and a water-wetness determination step of determining whether each of the divided regions corresponds to a water-wet region based on the classification result, The seven different frequencies are frequencies within each of the ranges (1) to (7) below. (1) 9.5-9.7GHz (2) 9.9-10.1GHz (3) 10.3-10.5GHz (4) 10.7-10.9GHz (5) 11.1-11.3GHz (6) 11.5-11.7GHz (7) 11.9-12.1GHz

2. The method for determining a water-wet state according to claim 1, characterized in that in the cluster analysis process, for each divided region, the real and imaginary parts of the complex transformation of the amplitude ratio and the phase difference at each frequency are used to classify each divided region into clusters of at least whether or not it is wet.

3. 3. The method according to claim 2, wherein in the cluster analysis step, of the complex-transformed real part and imaginary part, the following real part and imaginary part are used to classify the images into clusters. (1) Imaginary part at frequencies in the range of 9.5 to 9.7 GHz (2) Real and imaginary parts at frequencies in the range of 9.9 to 10.1 GHz (3) Real and imaginary parts at frequencies in the range of 10.3 to 10.5 GHz (4) Imaginary part at frequencies in the range of 10.7 to 10.9 GHz (5) Real part at frequencies in the range of 11.1 to 11.3 GHz (6) Real and imaginary parts at frequencies in the range of 11.5 to 11.7 GHz (7) Real part at frequencies in the range of 11.9 to 12.1 GHz

4. 2. The method for determining a wet state according to claim 1, wherein, in the irradiating and receiving step, the electromagnetic wave is irradiated from a wall surface on an indoor side of the exterior wall toward an inside of the exterior wall.

5. A system for identifying a water-wet state inside an exterior wall of a building from a reflected wave of an electromagnetic wave irradiated to the exterior wall, comprising: The specific system comprises: an irradiation / reception device that irradiates seven electromagnetic waves of different frequencies having a certain amplitude from a wall surface of the exterior wall toward an interior of the exterior wall and receives the reflected waves reflected inside the exterior wall at each of the frequencies for each partitioned area of ​​the wall surface of the exterior wall; A calculation device that performs a calculation to identify the water wet state, The arithmetic device includes an amplitude ratio and phase difference calculation unit that calculates an amplitude ratio of the reflected wave to the amplitude of the electromagnetic wave at each of the frequencies received for each of the partitioned regions, and a phase difference of the reflected wave to the electromagnetic wave at each of the frequencies; a cluster analysis unit that performs a cluster analysis for each of the divided regions using at least one of the amplitude ratio and the phase difference at each of the frequencies to classify each of the divided regions into clusters of at least whether the divided regions are wet or not; a water-wet identification unit that identifies whether each of the divided areas is a water-wet divided area based on the classification result, A system for identifying a wet state, characterized in that the seven different frequencies are frequencies within each of the ranges (1) to (7) below. (1) 9.5-9.7GHz (2) 9.9-10.1GHz (3) 10.3-10.5GHz (4) 10.7-10.9GHz (5) 11.1-11.3GHz (6) 11.5-11.7GHz (7) 11.9-12.1GHz

6. The system for determining a water wet state as described in claim 5, characterized in that the cluster analysis unit classifies each of the divided regions into clusters of at least whether or not the divided regions are wet using the real and imaginary parts of the complex transformation of the amplitude ratio and the phase difference at each frequency.

7. 7. The system for identifying a wet state according to claim 6, wherein the cluster analysis unit classifies the images into clusters using the following real parts and imaginary parts of the complex-transformed real parts and imaginary parts. (1) Imaginary part at frequencies in the range of 9.5 to 9.7 GHz (2) Real and imaginary parts at frequencies in the range of 9.9 to 10.1 GHz (3) Real and imaginary parts at frequencies in the range of 10.3 to 10.5 GHz (4) Imaginary part at frequencies in the range of 10.7 to 10.9 GHz (5) Real part at frequencies in the range of 11.1 to 11.3 GHz (6) Real and imaginary parts at frequencies in the range of 11.5 to 11.7 GHz (7) Real part at frequencies in the range of 11.9 to 12.1 GHz

Images