JP2005017215A - Device and method for diagnosing crack of concrete, computer program, and computer-readable recording medium - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To make exactly estimable and presentable a cause of generating a crack only by inputting a data of a crack condition of concrete or the like. <P>SOLUTION: A diagnostic server 12 narrows the causes of generating the crack based on a diagnostic object data (S106-S112), when receiving the diagnostic object data for expressing information as to a crack diagnostic object a prescribed item by a prescribed item from a terminal computer 16 (S104). A degree of conviction in the every crack generation cause narrowed as to the each item of the diagnostic object data is read out (S114) from a conviction degree table database 22 stored with the degrees of conviction of the respective crack generation causes the prescribed item by the prescribed item about the crack diagnostic object, and an integrated degree of conviction is calculated based on the read-out degrees of conviction read out the item by the item (S116). A diagnostic result screen is transmitted to the computer 16 to display a calculated degree of conviction (S122). <P>COPYRIGHT: (C)2005,JPO&NCIPI

Description

この場合、確信度ＣＦの正の値は、０．２， ０．３， ０．２， ０．３， ０．１であるから、ひび割れ原因「アルカリ骨材反応」についての正の確信度ＨＢ（Ｈ）は
０．２ ＋ ０．３・（１−０．２） ＝ ０．４４
０．４４ ＋ ０．２・（１−０．４４） ＝ ０．５５２
０．５５２ ＋ ０．３・（１−０．５５２） ＝ ０．６８６４
０．６８６４ ＋ ０．１・（１−０．６８６４） ＝ ０．７１７７６
により、ＨＢ（Ｈ）＝０．７１７７６と算出される。
【００２８】
また、確信度ＣＦの負の値は、−０．２， −０．１であるから、負の確信度ＭＤ（Ｈ）は、
０．２ ＋ ０．１・（１−０．２） ＝ ０．２８
により、ＭＤ（Ｈ）＝０．２８と計算される。
【００２９】
したがって、ひび割れ原因「アルカリ骨材反応」に対する総合的な確信度ＣＦｃｏｍｂ（Ｈ）は、

となる。
【００３０】
このような総合的な確信度ＣＦｃｏｍｂがひび割れ原因毎に計算され、ひび割れ原因が確信度ＣＦｃｏｍｂの大きい順にソートされる（Ｓ１１８）。そして、確信度ＣＦｃｏｍｂの大きい方から上位所定数のひび割れ原因とそれらの確信度ＣＦｃｏｍｂの値を表示する診断結果画面が生成されて（Ｓ１２０）、端末コンピュータ１６へ送信される（Ｓ１２２）。図６に診断結果画面の一例を示す。
【００３１】
診断結果画面において、何れかのひび割れ原因の名称がクリックされると（Ｓ１２４）、それに応じて、診断サーバー１２は、原因対策データベース２４から、該当するひび割れ原因についての対策内容等のデータを読み出して（Ｓ１２６）、そのデータを表示する詳細説明画面を端末コンピュータ１６へ送信する（Ｓ１２８）。図７に、詳細説明画面の一例を示す。現場担当者は、このような詳細説明画面を参照することで、ひび割れについての知識を得て、ひび割れに対する適切な対応策をとることができる。
【００３２】
また、診断サーバー１２は、端末コンピュータ１６から送られてきた診断対象データと、それに対して得られた各原因の信頼度とを、ひび割れ事例データベース２６に蓄積していく。こうして、ひび割れ事例データベース２６に蓄積されたデータを用いて、確信度テーブルの内容を修正していくことで、ひび割れ原因の診断精度を向上させることが可能となる。
【００３３】
以上説明したように、本実施形態によれば、工事現場等に設置された端末コンピュータ１６から診断対象データを入力すると、診断サーバー１２が確信度テーブルに基づき、ひび割れ発生原因を推論して各発生原因の確信度を算出し、その結果や各原因についての対策等が端末コンピュータ１６に表示される。このため、現場担当者は、ひび割れに関する専門的な知識がなくても、ひび割れ原因を正確に判定し、その原因に対する適切な対応策をとることができる。
【００３４】
また、診断対象データのひび割れ形状やひび割れ発見時期等に基づいて、ひび割れ発生原因を絞り込んだうえで、確信度を計算しているので、診断サーバー１２の処理負荷が軽減できるうえ、診断対象の状態・条件等からひび割れ発生原因としてあり得ないことが明らかな発生原因が提示されるのを防止することができる。
【００３５】
なお、上記実施形態では、本発明が、診断サーバー１２と端末コンピュータ１６とからなるサーバークライアントシステムとして実施される場合を説明したが、本発明はこれに限らず、スタンドアローンのコンピュータシステムとして実施することも可能である。
【００３６】
【発明の効果】
本発明によれば、コンクリートのひび割れ状況等のデータを入力するだけで、ひび割れ発生原因を推定して提示することができる。
【図面の簡単な説明】
【図１】本発明の一実施形態であるコンクリートのひび割れ診断システムの全体構成図である。
【図２】本実施形態の診断システムにおける処理の流れを示す図である。
【図３】データ入力画面の一例を示す図である。
【図４】ひび割れ形状とひび割れ発生原因の組合せにより絞り込まれたひび割れ発生原因を示す図である。
【図５】確信度テーブルの一部を一例として示す図である。
【図６】診断結果画面の一例を示す図である。
【図７】詳細説明画面の一例を示す図である。
【符号の説明】
１０ ひび割れ診断システム
１２ 診断サーバー
１４ ネットワーク
１６ 端末コンピュータ
２０ 診断対象データベース
２２ 確信度テーブルデータベース
２４ 原因対策データベース
２６ 事例データベース[0001]
BACKGROUND OF THE INVENTION
The present invention relates to an apparatus and method for diagnosing the cause of occurrence of cracks in concrete, a program for causing a computer to execute the method, and a recording medium on which the program is recorded.
[0002]
[Prior art]
Cracks generated in various concrete structures such as buildings and bridges adversely affect the durability of the structure. For this reason, the person in charge of these constructions and structures must regularly check for cracks in the concrete structure, and if any cracks are found, they must take immediate measures such as repairs. It is necessary to determine the appropriate countermeasures after determining the cause of cracking.
[0003]
[Problems to be solved by the invention]
Therefore, in the past, the person in charge of the spot who found the crack himself / herself consulted the literature such as a specialized book to investigate the countermeasures, and sent materials to the expert indicating the crack status, construction conditions, structure conditions, etc. , I received instructions on how to deal with them by telephone or in writing, or I received an instruction on how to deal with them directly from an expert. However, the countermeasures obtained by referring to the literature by field personnel who do not have specialized knowledge about cracks are not very reliable, and there is a possibility that appropriate measures against cracks cannot be taken. In addition, although it is possible to take appropriate measures by sending materials to specialists or by directly receiving them and receiving instructions from specialists, it takes time, and transportation costs are required for specialists to come. There was also a problem that it was necessary.
[0004]
The present invention has been made in view of the above points, and it is an object of the present invention to accurately estimate and present the cause of cracking by simply inputting data relating to a diagnosis target such as a cracking condition of concrete. .
[0005]
[Means for Solving the Problems]
In order to achieve the above object, the present invention is an apparatus for diagnosing the cause of cracking in concrete,
Diagnostic target data acquisition means for acquiring diagnostic target data representing information on a crack diagnostic target for each predetermined item;
Based on the acquired diagnostic object data, narrowing means for narrowing down the cause of crack occurrence;
A certainty factor representing the certainty of each crack occurrence cause, a certainty factor table corresponding to the data content for each of the predetermined items,
A certainty factor acquisition unit that reads the certainty factor corresponding to the data content of each of the predetermined items of the diagnosis target data of the narrowed-down crack causes from the certainty factor table;
A certainty factor calculating means for calculating a certainty factor representing a total likelihood of the cause of occurrence of each of the narrowed cracks based on the certainty factor for each of the predetermined items read out;
Output means for outputting the calculated certainty factor.
[0006]
In this crack diagnosis apparatus, the predetermined items may be classified into items relating to the occurrence of cracks, items relating to concrete construction conditions, items relating to structural conditions, items relating to concrete mixing, and items relating to environmental conditions. Good.
[0007]
Further, the output means may output the calculated certainty factor for a predetermined number of crack occurrence causes from among the narrowed cause of crack occurrences, from the larger calculated certainty factor.
[0008]
In addition, the crack diagnosis apparatus of the present invention, for each cause of the occurrence of cracks, a cause countermeasure database storing a countermeasure method for cracks caused by the cause,
Means for reading out a countermeasure for the cause of occurrence of the specified crack from the cause countermeasure database;
The output means may include means for outputting the read countermeasure method.
[0009]
Moreover, it is good also as providing the case database for accumulating the data regarding a diagnostic object and data, such as a crack cause diagnosed with respect to the diagnostic object.
[0010]
Further, the crack diagnosis apparatus of the present invention is constituted by a server computer connected to a computer network,
The diagnostic target data acquisition means receives the diagnostic target data from a terminal that has accessed the server computer via the computer network;
The output means may output to the terminal through the computer network.
[0011]
DETAILED DESCRIPTION OF THE INVENTION
FIG. 1 is an overall configuration diagram of a concrete crack diagnosis system (hereinafter simply referred to as a diagnosis system) 10 according to an embodiment of the present invention. As shown in the figure, the diagnostic system 10 includes a diagnostic server 12 and a terminal computer 16 connected to the diagnostic server 12 via a network 14. For example, the terminal computer 16 is installed at a construction site of a concrete structure and can be operated by a person in charge of the site.
[0012]
The diagnosis server 12 is constituted by a server computer connected to the network 14, and is provided with databases such as a diagnosis target database 20, a certainty factor database 22, a cause countermeasure database 24, and a case database 26. As will be described later, the diagnosis object database 20 stores data related to the diagnosis object input by the terminal computer 16. The certainty table database 22 stores a table (confidence table) for determining the certainty of the cause of crack occurrence. This certainty factor table will be described later. The cause countermeasure database 24 stores information on the characteristics of cracks caused by the cause, detailed contents of the cause, contents of countermeasures for preventing cracks, repair methods, and the like for each cause of the crack. Further, the case database 26 stores data related to the diagnosis target and data such as the cause of cracks diagnosed for the diagnosis target.
[0013]
FIG. 2 is a diagram showing a flow of processing in the diagnostic system 10. When there is an access from the terminal computer 16 to the diagnostic server 12 (S100), user authentication is performed using a user ID and password, and a data input screen is transmitted from the diagnostic server 12 to the terminal computer 16 (S102).
[0014]
FIG. 3 shows an example of the data input screen. As shown in the figure, on the condition input screen, the data related to the crack diagnosis target (hereinafter referred to as diagnosis target data) is classified into input data, structure data, crack data, concrete data, construction data, environmental condition data, etc. Input every time. The data items included in each classification are as follows, for example.
[0015]
(1) Input user data Bibliographic data such as the input date, construction name, and input user name.
(2) Structure data Data on structure conditions such as structure type, structure type, and foundation.
(3) Crack data Data related to the occurrence of cracks, such as crack discovery time, crack shape, crack depth and crack width. Of these, cracks were detected i) several hours to one day after placement, ii) several hours to several days after placement, iii) several days to one year after placement, iv) one year to several years after placement. It is possible to select and input within 10 years and before / after mold removal / support dismantling. In addition, the crack shape can be selected and input either linear or turtle shell shape.
(4) Concrete data Data on concrete mix (concrete maximum dimensions, slump, flow, air volume, etc.), cement type, fine aggregate, admixture, etc.
(5) Construction data Data on concrete construction conditions such as placement date, amount of concrete placement, weather at the time of placement, and temperature.
(6) Environmental condition data Data on environmental conditions such as whether the cracked surface is in contact with the outside air, the environment of the structure (in the sea, at sea, on the coast, in the soil, in the atmosphere, etc.), whether there is solar radiation, and whether there is a fire. .
[0016]
The diagnosis target data input on the data input screen is transmitted from the terminal computer 16 to the diagnosis server 12 (S104).
[0017]
The diagnosis server 12 stores the diagnosis target data transmitted from the terminal computer 16 in the diagnosis target database. Then, processing for diagnosing the cause of the occurrence of cracks is performed based on the diagnosis target data (S106 to S116).
[0018]
First, the generation cause of a crack is narrowed down based on the data which shows a crack shape and a crack discovery time among crack data (S108-S112). That is, it is determined whether the shape of the crack is a straight line or a turtle shell shape (S106). Further, in each case of the straight line shape and the turtle shell shape, the discovery time of the crack is as follows. Before the frame support is removed, it is determined whether (2) the form support is removed to less than one year after placing the concrete, or (3) one to several decades after placing the concrete (S108). Then, the possible causes of occurrence of cracks are removed for each combination of crack shape and crack discovery time, and the cause of occurrence of cracks is narrowed for each combination as shown in FIG. 4, for example (S110).
[0019]
Next, the cause of occurrence of cracking is further narrowed down based on data of items other than the crack shape and crack discovery time in the diagnosis target data (S112). For example, if there is no influence of a fire in the environmental condition data, the cause is narrowed down by removing the cause of the occurrence of a crack that is not possible, such as removing the cause of the occurrence of a crack related to the fire.
[0020]
Next, for each of the crack occurrence causes narrowed down as described above, a certainty factor representing the possibility of the occurrence of a crack is calculated with reference to the certainty factor table stored in the certainty factor table database 22 ( S114 to S116).
[0021]
FIG. 5 shows a part of the certainty factor table as an example. Note that the certainty factor table is provided, for example, for each crack shape or for each combination of a crack shape and a crack discovery time.
[0022]
As shown in FIG. 5, the certainty factor table shows the cause of each crack occurrence (in the example shown in the figure, bleeding subsidence (bottom plate, floor slab, beam), bleeding subsidence (wall, column), formwork interference, etc.) For each item (in the example of the figure, crack width, presence / absence of rust juice, presence / absence of discoloration, etc.), a certainty factor corresponding to the data of each item is stored. For example, in FIG. 5, when the crack width is 0.1 mm or less, the certainty factor that the cause of the occurrence of cracking is “formation of the mold” is 0.2. Here, the certainty factor is a value indicating the possibility of actually causing the crack (that is, the probability as the cause of the crack) and takes a value of [−1, 1], and −1 is an absolute negation. (Never causes cracking) 1 indicates absolute affirmation (absolutely causes cracking). For each factor, the overall certainty factor of each factor is calculated from the certainty factor set for each item of diagnosis target data.
[0023]
Specifically, first, the certainty factor for each item of the diagnosis target data is read for each narrowed cause with reference to the certainty factor table (S114). Based on the read certainty factor for each item, the overall certainty factor of each crack occurrence cause is calculated as follows (S116).
[0024]
It is assumed that the certainty factor CF is assigned to a plurality of crack diagnosis target items for a certain crack cause H. The certainty factor CF is divided into positive and negative values, the positive certainty factor CF is expressed as MB, and the negative certainty factor CF is expressed as MD. These MB and MD are recursively calculated as in the following equations, respectively. However, MB (H, Rj) and MD (H, Rj) are the certainty factors for each item about the crack cause H obtained from the certainty factor table for the jth item, and MB (H, [R1.Rj]. ), MD (H, [R1.Rj]) is a certainty factor calculated from the certainty factors of the first to jth items for the crack cause H, and N is the number of items giving positive and negative certainty factors.
[0025]
For positive confidence MB,
When MB (H, [R1.Rj-1]) = 1 or MB (H, Rj) = 1, MB (H, [R1.Rj]) = 1
-Otherwise, MB (H, [R1.R1]) = MB (H, R1)
When j> 1, MB (H, [R1.Rj]) = MB (H, [R1.Rj-1]) + MB (H, Rj). (1-MB (H, [R1.Rj-1]) )
As
MB (H) = MB (H, [R1.RN])
Similarly, for negative confidence MD,
When MD (H, [R1.Rj-1]) = 1 or MD (H, Rj) = 1, MD (H, [R1.Rj]) = 1
-Otherwise, MB (H, [R1.R1]) = MB (H, R1)
When j> 1, MD (H, [R1.Rj]) = MD (H, [R1.Rj-1]) + MD (H, Rj). (1-MD (H, [R1.Rj-1]) )
As
MD (H) = MD (H, [R1.RN])
And the total reliability CFcomb (H) for the crack cause H is
CFcomb (H) = MB (H) -MD (H)
Calculated by
[0026]
For example, regarding the cause of cracking “alkali aggregate reaction”, the certainty factor CF is as shown in the following table for each item of diagnosis target data.
[0027]
[Table 1]

In this case, since the positive value of the certainty factor CF is 0.2, 0.3, 0.2, 0.3, 0.1, the positive certainty factor HB about the cause of cracking “alkali aggregate reaction” (H) is 0.2 + 0.3 · (1-0.2) = 0.44
0.44 + 0.2. (1-0.44) = 0.552
0.552 + 0.3 · (1-0.552) = 0.6864
0.6864 + 0.1 · (1−0.6864) = 0.71776
Thus, HB (H) = 0.71776 is calculated.
[0028]
Further, since the negative values of the certainty factor CF are −0.2 and −0.1, the negative certainty factor MD (H) is
0.2 + 0.1 · (1-0.2) = 0.28
Therefore, MD (H) = 0.28 is calculated.
[0029]
Therefore, the overall certainty factor CFcomb (H) for the cause of cracking “alkali aggregate reaction” is

It becomes.
[0030]
Such a comprehensive certainty factor CFcomb is calculated for each cause of cracking, and the causes of cracking are sorted in descending order of the certainty factor CFcomb (S118). Then, a diagnosis result screen displaying the top predetermined number of crack causes and values of the certainty factor CFcomb from the one with the highest certainty factor CFcomb is generated (S120) and transmitted to the terminal computer 16 (S122). FIG. 6 shows an example of the diagnosis result screen.
[0031]
When one of the crack cause names is clicked on the diagnosis result screen (S124), the diagnosis server 12 reads data such as the countermeasure contents for the corresponding crack cause from the cause countermeasure database 24 accordingly. (S126), a detailed explanation screen for displaying the data is transmitted to the terminal computer 16 (S128). FIG. 7 shows an example of a detailed explanation screen. By referring to such a detailed explanation screen, the person in charge of the site can acquire knowledge about the crack and take an appropriate countermeasure against the crack.
[0032]
In addition, the diagnosis server 12 accumulates the diagnosis target data sent from the terminal computer 16 and the reliability of each cause obtained for the data in the crack case database 26. Thus, by correcting the contents of the certainty factor table using the data stored in the crack case database 26, it is possible to improve the accuracy of diagnosis of the cause of the crack.
[0033]
As described above, according to the present embodiment, when diagnosis target data is input from the terminal computer 16 installed at a construction site or the like, the diagnosis server 12 infers the cause of occurrence of cracks based on the certainty factor table and generates each occurrence. The certainty factor of the cause is calculated, and the result and countermeasures for each cause are displayed on the terminal computer 16. For this reason, the person in charge of the site can accurately determine the cause of the crack and take an appropriate countermeasure for the cause without having specialized knowledge about the crack.
[0034]
In addition, since the reliability is calculated after narrowing down the cause of cracking based on the crack shape of the diagnosis target data, crack detection time, etc., the processing load on the diagnostic server 12 can be reduced and the state of the diagnosis target -It is possible to prevent presenting a cause of occurrence that is clearly impossible as a cause of occurrence of a crack from conditions.
[0035]
In the above-described embodiment, the case where the present invention is implemented as a server client system including the diagnostic server 12 and the terminal computer 16 has been described. However, the present invention is not limited thereto, and is implemented as a stand-alone computer system. It is also possible.
[0036]
【The invention's effect】
According to the present invention, the cause of occurrence of cracks can be estimated and presented only by inputting data such as the crack status of concrete.
[Brief description of the drawings]
FIG. 1 is an overall configuration diagram of a concrete crack diagnosis system according to an embodiment of the present invention.
FIG. 2 is a diagram showing a flow of processing in the diagnostic system of the present embodiment.
FIG. 3 is a diagram illustrating an example of a data input screen.
FIG. 4 is a diagram showing a cause of occurrence of a crack narrowed down by a combination of a crack shape and a cause of occurrence of a crack.
FIG. 5 is a diagram illustrating a part of the certainty factor table as an example.
FIG. 6 is a diagram illustrating an example of a diagnosis result screen.
FIG. 7 is a diagram illustrating an example of a detailed explanation screen.
[Explanation of symbols]
DESCRIPTION OF SYMBOLS 10 Crack diagnosis system 12 Diagnosis server 14 Network 16 Terminal computer 20 Diagnosis object database 22 Certainty factor table database 24 Cause countermeasure database 26 Case database

Claims (9)

A device for diagnosing the cause of cracks in concrete,
Diagnostic target data acquisition means for acquiring diagnostic target data representing information on a crack diagnostic target for each predetermined item;
Based on the acquired diagnostic object data, narrowing means for narrowing down the cause of crack occurrence;
A certainty factor representing the certainty of each crack occurrence cause, a certainty factor table corresponding to the data content for each of the predetermined items,
A certainty factor acquisition unit that reads the certainty factor corresponding to the data content of each of the predetermined items of the diagnosis target data of the narrowed-down crack causes from the certainty factor table;
A certainty factor calculating means for calculating a certainty factor representing a total likelihood of the cause of occurrence of each of the narrowed cracks based on the certainty factor for each of the predetermined items read out;
And an output means for outputting the calculated certainty factor. 2. The crack diagnosis apparatus according to claim 1, wherein the predetermined items are classified into items relating to the occurrence of cracks, items relating to concrete construction conditions, items relating to structural conditions, items relating to concrete blending, and items relating to environmental conditions. A device characterized by comprising. 3. The crack diagnosis apparatus according to claim 1, wherein the output unit calculates the calculated certainty factor for a predetermined number of cracking causes from the larger one of the calculated certainty factors among the narrowed cracking causes. A device characterized by outputting. In the crack diagnostic apparatus of any one of Claims 1-3,
For each cause of crack occurrence, a cause countermeasure database that stores the countermeasures against the cracks that occurred, and
Means for reading out a countermeasure for the cause of occurrence of the specified crack from the cause countermeasure database;
The output means includes means for outputting the read countermeasure method. The crack diagnostic apparatus according to any one of claims 1 to 4, further comprising a case database for accumulating data relating to a diagnosis target and data such as a crack cause diagnosed for the diagnosis target. Features device. In the crack diagnostic apparatus of any one of Claims 1-5,
Consists of server computers connected to a computer network,
The diagnostic target data acquisition means receives the diagnostic target data from a terminal that has accessed the server computer via the computer network;
The output means outputs to the terminal through the computer network. A method of diagnosing the cause of cracking in concrete, where a computer
Obtaining diagnostic target data representing information on the crack diagnostic target for each predetermined item;
Based on the acquired diagnostic object data, narrowing down the cause of crack occurrence;
The certainty factor of each cause of occurrence of cracks is stored for each predetermined item corresponding to the data content from the certainty factor table, and for each predetermined item of the diagnosis target data, the cause of each narrowed crack A step of reading a certainty factor corresponding to the data content;
Based on the certainty factor for each of the predetermined items read out, calculating a certainty factor representing the possibility that each narrowed cause is actually the cause of cracking;
A step of outputting the calculated certainty factor. A program for causing a computer to execute the method according to claim 7. A recording medium on which the program according to claim 8 is recorded.

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