JP2019052441A - Grout filling state discrimination system and program - Google Patents

Abstract

To accurately discriminate the filling state of grout by analyzing nondestructive inspection data by artificial intelligence.SOLUTION: In discriminating the filling state of grout in a cable sheath 71 of a PC structure by a nondestructive inspection: three or more stages of an association degree between inspection data of the past nondestructive inspection on the cable sheath 71 and a discrimination result of the filling state of grout for the inspection data are acquired in advance; the inspection data obtained by performing the nondestructive inspection on the cable sheath 71 for newly discriminating the filling state of grout is inputted; the filling state of grout into the cable sheath is discriminated based on the input information with reference to the acquired association degree.SELECTED DRAWING: Figure 3

Description

  The present invention relates to a grout filling status discrimination system and a program for discriminating a grout filling status in a cable sheath of a PC structure by nondestructive inspection.

  Conventionally, when grout is injected into a cable sheath of a PC structure such as a post-tension type bridge, viaduct or building, a pump is connected to the grout injection side of the cable sheath and a vacuum pump is connected to the discharge side. . After the pressure inside the cable sheath is reduced by the vacuum pump, the pressure pump is operated while the vacuum pump is operated to fill the cable sheath with grout.

  By the way, in recent years, corrosion and breakage accidents of tendons due to poor filling of the grout into the cable sheath in the PC structure have come to be seen. For this reason, conventionally, the grout filling state in the cable sheath is determined by nondestructive inspection. As this nondestructive inspection method, for example, an X-ray transmission method, a shock elastic wave method, an impact echo method, a broadband ultrasonic method, or the like is used.

JP 2000-206098 A

  However, even if inspection data can be obtained by these nondestructive inspection methods, it is not easy to accurately determine the grout filling state in the cable sheath based on the inspection data. In fact, it takes considerable skill to predict the grout filling status from the inspection data only to a certain degree of accuracy. There was also.

  For this reason, there has been a demand for a technique that can automatically perform accurate determination without accumulating skill in determining the grout filling state. A technical idea for improving accuracy by automatically determining the grout filling state by artificial intelligence is also conceivable.

  In particular, Patent Document 1 receives an ultrasonic reflection echo from a building structure, acquires shape information of a flaw in a pillar, etc., and information on the shape of the flaw and an inspection reference database obtained by artificial intelligence or the like. A technique for performing comparison and evaluating the degree of maintenance of a building is disclosed.

  However, the technique disclosed in Patent Document 1 does not specifically disclose a technique for discriminating the state of grout filling in the cable sheath of the PC structure by analyzing nondestructive inspection data using artificial intelligence.

  Therefore, the present invention has been devised in view of the above-mentioned problems, and the object of the present invention is to grout for determining the grout filling state in the cable sheath of the PC structure by nondestructive inspection. To provide a grout filling state discriminating system and program capable of determining the grout filling state with high accuracy by analyzing nondestructive inspection data by artificial intelligence, in particular, in the filling state discriminating system and program. is there.

  The grout filling status determination system according to the present invention is a grout filling status determination system for determining the grout filling status of a PC structure in a cable sheath by nondestructive inspection. The above-described nondestructive inspection is performed on a database in which three or more levels of association between the data and the grout filling state determination result for the inspection data are stored in advance, and a cable sheath for newly determining the grout filling state. The status of grout filling in the cable sheath based on the information input through the input means by referring to the input means for inputting the inspection data obtained by performing and the association degree stored in the database And a discriminating means for discriminating between.

  A grout filling status determination program according to the present invention is a grout filling status determination program for determining the grout filling status of a PC structure in a cable sheath by nondestructive inspection. A non-destructive inspection for the cable sheath for newly determining the degree of filling of the grout, and an association degree obtaining step for obtaining in advance three or more levels of relevance between the data and the result of determining the filling state of the grout for the inspection data Referring to the input step in which the inspection data obtained by performing the input is input and the association degree acquired in the association degree acquisition step, the grout filling state in the cable sheath based on the information input in the input step Characterized by having a computer execute a determination step for determining .

  According to the present invention having the above-described configuration, it is possible to easily grasp the grout filling state without requiring special skill. According to the present invention, it is possible to grasp the grout filling state with higher accuracy. Furthermore, by configuring the above-mentioned association degree with artificial intelligence, it is possible to further improve the discrimination accuracy by learning this.

It is a block diagram which shows the whole structure of the grout filling condition discrimination system to which this invention is applied. It is a figure which shows the specific structural example of a discrimination device. It is a figure for demonstrating the search concept of the output solution by the grout filling condition discrimination system to which this invention is applied. It is a flowchart which shows the processing operation of a search program. It is a figure which shows the example of the relevance in the case of utilizing an X-ray transmission method as a nondestructive inspection method. It is a figure which shows the relevance of the combination in the case of utilizing an X-ray transmission method as a nondestructive inspection method. It is a figure which shows the example of the relevance in the case of using the impact elastic wave method as a nondestructive inspection method. It is a figure which shows the example of the relevance of the combination in the case of using the impact elastic wave method as a nondestructive inspection method. It is a figure which shows the other example of the relevance of the combination in the case of using the impact elastic wave method as a nondestructive inspection method. It is a figure which shows the example of an association degree in the case of using an impact echo method as a nondestructive inspection method. It is a figure which shows the example of the relevance of the combination in the case of using an impact echo method as a nondestructive inspection method. It is a figure which shows the example of the association degree in the case of utilizing a wide-range ultrasonic method as a nondestructive inspection method. It is a figure which shows the example of the relevance of the combination in the case of utilizing a wide-range ultrasonic method as a nondestructive inspection method.

  Hereinafter, a grout filling situation determination system to which the present invention is applied will be described in detail with reference to the drawings.

  FIG. 1 is a block diagram showing the overall configuration of a grout filling status determination system 1 to which the present invention is applied. The grout filling status discrimination system 1 discriminates the grout filling status of the PC structure 7 into the cable sheath 71 by nondestructive inspection. The grout filling status determination system 1 includes a non-destructive inspection unit 8, an evaluation device 9 connected to the non-destructive inspection unit 8, a determination device 2 connected to the evaluation device 9, and a database 3 connected to the determination device 2. And.

  The PC structure 7 is a bridge, a viaduct, a building or the like in which a PC steel material and a cable sheath 71 are disposed.

  The cable sheath 71 is arranged such that a PC steel rod (not shown) such as a PC steel rod or a number of PC steel wires is in a tension state and is separated from the inner wall surface of the cable sheath 71. Incidentally, since the present embodiment is intended for the post-tension type PC structure 7, in this case, the cable sheath 71 is placed in the PC structure 7 and then concrete is filled and cured, and thereafter A PC steel material (not shown) is inserted into the cable sheath 71 to apply a tensile stress. Thereafter, the cable sheath 71 is filled with grout and cured.

  The nondestructive inspection unit 8 uses, for example, inspection data for determining the grout filling state in the cable sheath 71 by a nondestructive inspection method such as an X-ray transmission method, a shock elastic wave method, an impact echo method, and a broadband ultrasonic method. To detect. The nondestructive inspection unit 8 transmits the detected inspection data to the evaluation device 9.

  The evaluation device 9 is composed of electronic devices such as a PC (personal computer), a smartphone, a tablet terminal, and a wearable terminal. The evaluation device 9 is optimal for evaluating the degree of filling of the grout in the cable sheath 71 by analyzing the inspection data acquired by the nondestructive inspection unit 8 if it has a waveform. Process as appropriate. For example, the evaluation device 9 may perform FFT (Fast Fourier Transform) conversion on the obtained frequency axis data to convert time axis waveform data into frequency axis spectrum data. The evaluation device 9 transmits the inspection data appropriately processed in this way to the determination device 2.

  Incidentally, the evaluation device 9 can display each inspection data via a display unit including a display (not shown), for example. Further, the evaluation device 9 can record each data in the storage, display the data on the display unit based on a command from the user, or write the data to the portable memory. The user can remove the portable memory from the evaluation device 9 and carry it freely. Furthermore, the evaluation device 9 can transfer these data to other electronic devices via the public communication network.

  In the present invention, the configuration of the evaluation device 9 is not essential and may be omitted. In such a case, the inspection data output from the nondestructive inspection unit 8 is directly transmitted to the determination device 2.

  The database 3 is constructed with respect to the condition for determining the grout filling status to be provided. The database 3 stores information sent via a public communication network or information input by a user of this system. Further, the database 3 transmits the accumulated information to the determination device 2 based on a request from the determination device 2.

  The discriminating device 2 is composed of electronic devices such as a personal computer (PC), for example. In addition to the PC, the discriminating device 2 can be embodied in any other electronic device such as a mobile phone, a smartphone, a tablet terminal, and a wearable terminal. It may be made. The user can determine whether or not the grout filling in the cable sheath 71 is sufficient by obtaining the determination result of the grout filling state as a search solution by the determination device 2. When the grout is not sufficiently filled in the cable sheath 71, an operation of filling the grout into the cable sheath 71 by operating a pressure feed pump (not shown) is performed.

  FIG. 2 shows a specific configuration example of the discrimination device 2. The discrimination device 2 performs wired communication or wireless communication with a control unit 24 for controlling the discrimination device 2 as a whole, and an operation unit 25 for inputting various control commands via operation buttons, a keyboard, and the like. A communication unit 26 for searching, a search unit 27 for searching for an optimum design condition, and a storage unit 28 for storing a program for performing a search to be executed, represented by a hard disk or the like, are connected to the internal bus 21, respectively. Has been. Further, the internal bus 21 is connected to a display unit 23 as a monitor for actually displaying information.

  The control unit 24 is a so-called central control unit for controlling each component mounted in the determination device 2 by transmitting a control signal via the internal bus 21. Further, the control unit 24 transmits various control commands via the internal bus 21 in accordance with an operation via the operation unit 25.

  The operation unit 25 is embodied by a keyboard or a touch panel, and an execution command for executing a program is input from the user. When the execution command is input from the user, the operation unit 25 notifies the control unit 24 of this. Upon receiving this notification, the control unit 24 executes a desired processing operation in cooperation with each component including the search unit 27.

  The search unit 27 searches for the determination result of the grout filling status. The search unit 27 reads various information stored in the storage unit 28 as necessary information and various information stored in the database 3 when executing the search operation. The search unit 27 may be controlled by artificial intelligence. This artificial intelligence may be based on any known artificial intelligence technology.

  The display unit 23 includes a graphic controller that creates a display image based on control by the control unit 24. The display unit 23 is realized by, for example, a liquid crystal display (LCD).

  When the storage unit 28 is composed of a hard disk, based on the control by the control unit 24, predetermined information is written to each address and is read out as necessary. The storage unit 28 stores a program for executing the present invention. This program is read by the control unit 24 and executed.

  The operation in the grout filling situation determination system 1 having the above-described configuration will be described.

  In the grout filling status discrimination system 1, for example, as shown in FIG. 3, an output solution related to the discrimination result of the grout filling status in the cable sheath 71 is searched based on input parameters including inspection data A, B,. To do. The determination result of the grout filling state may be shown as information determined as a filling rate such as a filling rate of 0%, 50%, 100%, etc. It may be indicated by a discrimination result such as a filling distribution P indicating what distribution the grout is filled with.

  The input parameters are inspection data detected by the nondestructive inspection unit 8, processed by the evaluation device 9 as necessary, and analyzed. Inspection data A, B,... Are input as input parameters.

  Thus, after the inspection data is detected by the nondestructive inspection unit 8, the processing operation by the search program is actually executed. The processing operation flow of this search program is shown in FIG.

  The evaluation device 9 performs various analyzes on the inspection data detected by the nondestructive inspection unit 8 in step S11, and processes the various data in order to facilitate the search by the subsequent search device (step S12).

  Next, the process proceeds to step S13, and an output solution of the inspection data analyzed and processed in step S12 and the association degree is searched. Prior to performing this search, the database 3 acquires in advance three or more levels of association between reference parameters for input (hereinafter referred to as reference input parameters) and results of determining the grout filling status as an output solution. Keep it.

  FIG. 5 shows an example of the association degree acquired in advance in the database 3. In the example of FIG. 5, an X-ray transmission method is used as a nondestructive inspection method in the nondestructive inspection unit 8. The inspection data detected by the nondestructive inspection unit 8 based on this X-ray transmission method is composed of, for example, an image taken based on the X-ray transmission method. For this reason, in the reference input parameters, images r1, r2, r3,... Captured based on these X-ray transmission methods are learned in advance.

  The database 3 includes images r1, r2, r3,... Taken based on the X-ray transmission method as reference input parameters, and a determination result of the grout filling state in the cable sheath 71 as an output solution. The degree of association of three or more levels is stored in advance. According to the example of FIG. 5, when the reference input parameter is the image r1, “filling rate 50%” is set with an association degree of 80%, and “filling rate 0%” with an association degree of 60%. Further, when the reference input parameter is the image r2, “filling rate 100%” is set with an association degree of 90%, and “filling state P” is set with an association degree of 40%.

  These relevance levels are stored in the database 3 with the images r1, r2, r3,..., And the filling rate and the filling status as the result of the non-destructive inspection based on the X-ray transmission method. It may be accumulated in advance and set based on them. This association degree may be configured by a so-called neural network. This degree of association indicates the accuracy with which the grout filling state in the actual cable sheath 71 is determined based on the image when the nondestructive inspection is performed based on the X-ray transmission method. For example, for the image r3 based on the X-ray transmission method, the “filling state Q” with a relevance of 70% is close to the most accurate determination, and the “filling rate of 50%” with a relevance of 50% is the subsequent accurate determination. It turns out that. Similarly, for the image r2 based on the X-ray transmission method, the relevance 90% “filling rate 100%” is close to the most accurate judgment, and the “filling status P” with the relevance 40% is subsequent accurate judgment. It turns out that.

  After shifting to step S13, the search program performs an operation of determining the grout filling state in the cable sheath 71 based on the input parameter analyzed in step S12. Reference is made to the association shown in FIG. 5 acquired in advance to determine the grout filling status. For example, when the image of the input parameter analyzed in step S12 is the image r1 as the reference input parameter or an approximation thereof, when referring to the association degree described above, the highest association degree “ “Filling rate 50%” is selected as the optimal solution. However, it is not essential to select a solution with the highest degree of association as the optimum solution, and “filling rate 0%” that allows the association itself with a low degree of association may be selected as the optimum solution. Of course, an output solution that is not connected with an arrow may be selected. That is, the selection of the grout filling status in the cable sheath 71 is not limited to the case where the degree of association is selected in order from the highest degree of association, but the order of selection from the order of the lowest association degree according to the case. Or any other priority order.

  In addition, the image of the input parameter analyzed in step S12 is partially similar to the image r2 as the reference input parameter, but is also partially similar to the image r3, and it is not possible to assign to which one. For example, the determination may be made by paying attention to features between images. In such a case, for example, the luminance of the pixels constituting the air gap in the cable sheath 71 may be regarded as a feature region in the image and may be determined. When determining which reference input parameter is similar to the input parameter image, for example, deep learning or the like may be used. Based on the feature quantity on the image through deep learning, it is determined which reference input parameter is assigned. In this way, after assigning the input parameter analyzed in step S12 to the reference input parameter, the grout filling state in the cable sheath 71 as the output solution is determined based on the association degree set in the reference input parameter. Will choose.

  Note that the method of selecting an output solution for the input parameter analyzed in step S12 is not limited to the above-described method, and may be executed based on any method as long as it refers to the degree of association. Further, the search operation in step S13 may be performed using artificial intelligence.

  Next, the process proceeds to step S14, and the determination result of the grout filling state in the cable sheath 71 as the selected optimum solution is displayed via the display unit 23. Thus, the user can immediately grasp the determination result of the grout filling state in the cable sheath 71 by visually recognizing the display unit 23.

  FIG. 6 shows a combination of images r1, r2,... As inspection data of past nondestructive inspection by the X-ray transmission method, and one or more of the configuration information of the cable sheath 71 and the arrangement information of the cable sheath. An example is shown in which three or more levels of association are set with the result of determining the grout filling status for the combination.

  As the form information of the cable sheath 71, for example, in addition to the member thickness, length, and size of the cable sheath 71, all kinds of information including the material and the surface state are included. Further, the arrangement information of the cable sheath 71 includes all information related to the arrangement form of the cable sheath 71 in the PC structure 7. Examples of the arrangement information of the cable sheath 71 include, for example, information on whether or not the cable sheaths are arranged in parallel when viewed from the front, and the interval between the cable sheaths 71.

  In such a case, as shown in FIG. 6, the relevance is one or more of images r1, r2,... As non-destructive inspection data, and configuration information of the cable sheath 71 and cable sheath arrangement information. A set of combinations is expressed as so-called hidden layer nodes 61a to 61e. In each of the nodes 61a to 61e, a weight for the reference input parameter and a weight for the output solution are set. This weighting is an association degree of three or more levels. For example, in the node 61a, the image r1 is associated with an association degree of 80%, and “parallel arrangement” as arrangement information is associated with an association degree of 80%. The node 61c is associated with an image r2 having an association degree of 60%, a “member thickness of 500 mm to 1500 mm” as form information is associated with an association degree of 60%, and “non-parallel arrangement” as arrangement information is associated with an association degree of 40%. .

  Similarly, when such association is set, when the process proceeds to step S13, the images r1, r2, and the cable sheath as inspection data of nondestructive inspection as input parameters extracted in step S12. An output solution is searched according to the degree of association between the form information 71 and the cable sheath arrangement information. The search program performs an operation of selecting one or more optimal solutions from the output solutions based on the input parameters analyzed in step S12. In selecting this optimum solution, the association degree shown in FIG. 6 acquired in advance is referred to. For example, when the input parameter analyzed in step S12 is the image r1 and the member information is “member thickness 150 to 500 mm”, the node 61b is associated through the association degree. "Filling rate 50%" is associated with an association degree of 60%, and "Filling state Q" is associated with an association degree of 40%.

  The search program similarly outputs a solution in step S14 based on the search result.

  In the example of FIG. 7, a shock elastic wave method is used as a nondestructive inspection method in the nondestructive inspection unit 8. The inspection data detected by the nondestructive inspection unit 8 based on the shock elastic wave method is composed of data such as an input / output ratio and propagation velocity detected based on the shock elastic wave method, for example. For this reason, in the reference input parameter, data such as the input / output ratio and the propagation velocity detected based on the shock elastic wave method is learned in advance.

In the database 3, there are three or more levels of relevance between data such as input / output ratios and propagation speeds as reference input parameters and the result of determination of the grout filling state in the cable sheath 71 as an output solution. Store in advance. According to the example of FIG. 7, the input parameters for reference are “input / output ratio: 0.001 to 0.1 (× 10 ⁻³ ), propagation speed: 3.0 to 4.0 (m / s)”. In this case, “filling rate 50%” is set with an association degree of 80%, and “filling rate 0%” is set with an association degree of 60%. When the input parameters for reference are “input / output ratio: 0.1 to 1 (× 10 ⁻³ ), propagation speed: 4.0 to 5.0 (m / s)”, “filling rate 100%” Is set with a relevance of 90% and “filling status P” with a relevance of 40%.

These relevance levels are preliminarily stored in the database 3 such as the input / output ratio and propagation speed data obtained when the non-destructive inspection was performed based on the shock elastic wave method previously, and the filling rate and filling state as the determination results. They may be stored and set based on them. This association degree may be configured by a so-called neural network. This association degree indicates the accuracy in determining the grout filling state in the actual cable sheath 71 based on the image when the nondestructive inspection is performed based on the shock elastic wave method. For example, for “input / output ratio: 1 to 10 (× 10 ⁻³ ), propagation velocity: 5.0 to 6.0 (m / s)” based on the shock elastic wave method, “Situation Q” is close to the most accurate determination, and “filling rate 50%” with an association degree of 50% is the subsequent accurate determination. Similarly, for “input / output ratio: 0.1 to 1 (× 10 ⁻³ ), propagation velocity: 4.0 to 5.0 (m / s)” based on the shock elastic wave method, the degree of association is 90%. The “filling rate of 100%” is close to the most accurate determination, and the “filling state P” having an association degree of 40% is the subsequent accurate determination.

After shifting to step S13, the search program performs an operation of determining the grout filling state in the cable sheath 71 based on the input parameter analyzed in step S12. Reference is made to the association shown in FIG. 7 acquired in advance to determine the grout filling status. For example, the input parameter image analyzed in step S12 is “input / output ratio: 0.001 to 0.1 (× 10 ⁻³ ), propagation speed: 3.0 to 4.0 (m / S) ”, when the above-mentioned association degree is referred to,“ filling rate 50% ”having the highest association degree is selected as the optimum solution. However, it is not essential to select a solution with the highest degree of association as the optimum solution, and “filling rate 0%” that allows the association itself with a low degree of association may be selected as the optimum solution. In addition to this, it is of course possible to select an output solution that is not connected to an arrow, and any other solution may be selected as long as it is based on the degree of association.

  Next, the process proceeds to step S14, and the determination result of the grout filling state in the cable sheath 71 as the selected optimum solution is displayed via the display unit 23. Thus, the user can immediately grasp the determination result of the grout filling state in the cable sheath 71 by visually recognizing the display unit 23.

  FIGS. 8 and 9 show data such as input / output ratio and propagation velocity detected based on the shock elastic wave method, configuration information of the cable sheath 71, arrangement information of the cable sheath 71, and the PC structure 7. A combination of any one or more of the tendon information on the tendon (PC steel), the grout information on the grout, and the concrete information placed in the PC structure 7, and the determination result of the grout filling status for the combination This shows an example in which three or more levels of association are set.

  The form information of the cable sheath 71 includes the length of the cable sheath 71, the diameter of the cable sheath 71, and the like. The arrangement information of the cable sheath 71 includes all information related to the arrangement form of the cable sheath 71 in the PC structure 7. Examples of the arrangement information of the cable sheath 71 include, for example, information on whether or not the cable sheaths are arranged in parallel when viewed from the front, and the interval between the cable sheaths 71. The grout information is the Young's modulus of the grout. The tension material information includes the length of the PC steel material, the type of the PC steel material, and the tension force. The concrete information includes the Young's modulus of concrete placed on the PC structure 7 and the presence / absence of cover concrete.

  In such a case, as shown in FIGS. 8 and 9, the relevance is obtained by comparing the input / output ratio and propagation speed based on the shock elastic wave method as the inspection data of the nondestructive inspection, the form information of the cable sheath 71, the cable sheath 71 Combination of one or more of arrangement information, tendon information on tendon (PC steel) provided in the PC structure 7, grout information on the grout, and concrete information placed in the PC structure 7 The set is expressed as hidden layer nodes 61a to 61e in the same manner as described above. Incidentally, in the example of FIG. 8, a case in which a set of combinations of tendon information and concrete information is configured.

For example, in FIG. 8, the node 61 a is “input / output ratio: 0.001 to 0.1 (× 10 ⁻³ ), propagation speed: 3.0 to 4.0 (m / s)”, and concrete information. “Young's modulus of concrete: 26 to 30 GPa” is associated with an association degree of 80%. In addition, the node 61c has an input / output ratio of 0.1 to 1 (× 10 ⁻³ ) and a propagation speed of 4.0 to 5.0 (m / s) of 60% associative information. “Steel length: 10 to 14 m” is associated with 60% association, and “Young's modulus of concrete: 30 to 35 GPa” as concrete information is associated with 40% association.

Similarly, when such association is set, when the process proceeds to step S13, the input / output ratio, propagation speed, tension material as inspection data of the nondestructive inspection as the input parameter extracted in step S12. Search for output solutions according to the degree of association between information and concrete information. The search program performs an operation of selecting one or more optimal solutions from the output solutions based on the input parameters analyzed in step S12. In selecting this optimum solution, the association degree shown in FIG. 8 acquired in advance is referred to. For example, in the input parameters analyzed in step S12, “input / output ratio: 0.001 to 0.1 (× 10 ⁻³ ), propagation velocity: 3.0 to 4.0 (m / s)”, and steel material information As “steel length: 8 to 10 m”, the node 61b is associated with the degree of association, and the node 61b has a degree of filling of 60% and a degree of filling of Q of 60%. The association is 40%.

  The search program similarly outputs a solution in step S14 based on the search result.

  FIG. 9 shows an example in which the degree of association is configured for a combination of form information and arrangement information in addition to the input / output ratio and propagation speed based on the shock elastic wave method as inspection data for nondestructive inspection. An example of this form information is the sheath diameter, and an example of the arrangement information is whether or not the arrangement is parallel arrangement. Similarly, when such association is set, when the process proceeds to step S13, the input / output ratio, propagation speed, and form information as nondestructive inspection data as input parameters extracted in step S12. Therefore, an output solution corresponding to the association degree of the arrangement information is searched.

  In the example of FIG. 10, the impact echo method is used as a nondestructive inspection method in the nondestructive inspection unit 8. The inspection data detected by the nondestructive inspection unit 8 based on the impact echo method is composed of data such as a frequency response detected based on the impact echo method, for example. For this reason, in the reference input parameter, data such as a frequency response detected based on the impact echo method is learned in advance.

  The database 3 stores in advance three or more levels of relevance between the frequency response data as the reference input parameter and the determination result of the grout filling status in the cable sheath 71 as the output solution. . According to the example of FIG. 10, when the reference input parameter is the frequency response f1, “filling rate 50%” is set with an association degree of 80% and “filling rate 0%” with an association degree of 60%. When the reference input parameter is the frequency response f2, the “filling rate 100%” is set with an association degree of 90%, and the “filling state P” is set with an association degree of 40%.

  These relevance levels are the frequency responses f1, f2, f3,... When the nondestructive inspection was previously performed based on the impact echo method, and the filling rate and the filling situation as the determination results in the database 3. It may be accumulated in advance and set based on them. This association degree may be configured by a so-called neural network. This degree of association indicates the accuracy with which the grout filling state in the actual cable sheath 71 is discriminated based on the image when the nondestructive inspection is performed based on the impact echo method. For example, with respect to the frequency response f3 based on the impact echo method, the “filling state Q” with an association degree of 70% is close to the most accurate judgment, and the “filling rate of 50%” with an association degree of 50% is the subsequent accurate judgment. It turns out that. Similarly, for the frequency response f2 based on the impact echo method, the relevance 90% “filling rate 100%” is close to the most accurate judgment, and the “filling status P” with the relevance 40% is subsequent accurate judgment. It turns out that.

  After shifting to step S13, the search program performs an operation of determining the grout filling state in the cable sheath 71 based on the input parameter analyzed in step S12. Reference is made to the association shown in FIG. 10 acquired in advance to determine the grout filling status. For example, when the frequency response of the input parameter analyzed in step S12 is the frequency response f1 as the reference input parameter or approximates it, when the above-mentioned relevance is referred, A high “filling rate of 50%” is selected as the optimal solution. However, it is not essential to select a solution with the highest degree of association as the optimum solution, and “filling rate 0%” that allows the association itself with a low degree of association may be selected as the optimum solution. Of course, an output solution that is not connected with an arrow may be selected. That is, the selection of the grout filling status in the cable sheath 71 is not limited to the case where the degree of association is selected in order from the highest degree of association, but the order of selection from the order of the lowest association degree according to the case. Or any other priority order.

  Further, although the frequency response of the input parameter analyzed in step S12 is partially similar to the frequency response f2 as the reference input parameter, it is also partially similar to the frequency response f3, and it can be assigned to which one. For example, the determination may be made by paying attention to characteristics between frequency responses. In such a case, for example, a predetermined peak of the frequency response may be determined as the feature region. When determining which reference input parameter the frequency response of the input parameter is similar to, for example, deep learning or the like may be used. Based on the feature quantity on the image through deep learning, it is determined which reference input parameter is assigned. In this way, after assigning the input parameter analyzed in step S12 to the reference input parameter, the grout filling state in the cable sheath 71 as the output solution is determined based on the association degree set in the reference input parameter. Will choose.

  Note that the method of selecting an output solution for the input parameter analyzed in step S12 is not limited to the above-described method, and may be executed based on any method as long as it refers to the degree of association. Further, the search operation in step S13 may be performed using artificial intelligence.

  FIG. 11 shows frequency responses f1, f2,... As the inspection data of the past nondestructive inspection by the impact echo method, the shape information of the cable sheath 71, the arrangement information of the cable sheath 71, and the test condition information of the impact echo method. 3 shows an example in which three or more levels of association between a combination with one or more of the surface state information of the PC structure 7 and a determination result of the grout filling state for the combination are set.

  As the form information of the cable sheath 71, for example, in addition to the member thickness, length, and size of the cable sheath 71, all kinds of information including the material and the surface state are included. Further, the arrangement information of the cable sheath 71 includes all information related to the arrangement form of the cable sheath 71 in the PC structure 7. Examples of the arrangement information of the cable sheath 71 include, for example, information on whether the cable sheaths 71 are arranged in parallel in the front view, the interval between the cable sheaths 71, the cover depth of the cable sheath 71, and the like. It is. The test condition information of the impact echo method indicates all test conditions such as a ball diameter for striking for hitting a test object in the impact echo method. Further, the surface state information of the PC structure 7 indicates an uneven state of the surface of the PC structure 7 or the like.

  In such a case, as shown in FIG. 11, the relevance is the frequency response f1, f2,... As non-destructive inspection data, the striking steel ball diameter as test condition information, and the shape information of the cable sheath. A set of one or more combinations of the sheath diameters is expressed as so-called hidden layer nodes 61a to 61e. In each of the nodes 61a to 61e, a weight for the reference input parameter and a weight for the output solution are set. This weighting is an association degree of three or more levels. For example, the node 61a is associated with the frequency response f1 having an association degree of 80% and “sheath diameter: 26 to 50 mm” as form information with an association degree of 80%. Further, in the node 61c, the frequency response f2 has an association degree of 60%, “steel ball diameter: 100 to 200 mm” as form information has an association degree of 60%, and “sheath diameter: 50 to 75 mm” as form information has an association degree of 40. % Are related.

  Similarly, when such association is set, when the process proceeds to step S13, frequency responses f1, f2,... As inspection data of nondestructive inspection as input parameters extracted in step S12. An output solution corresponding to the degree of association between the test condition information and the form information of the cable sheath 71 is searched. The search program performs an operation of selecting one or more optimal solutions from the output solutions based on the input parameters analyzed in step S12. In selecting this optimum solution, the association degree shown in FIG. 13 acquired in advance is referred to. For example, in the input parameter analyzed in step S12, when the frequency response is f1 and the test condition information is “steel ball diameter: 30 to 100 mm”, the node 61b is associated via the association degree. 61b is associated with a "filling rate of 50%" with an association degree of 60% and a "filling status Q" with an association degree of 40%.

  The search program similarly outputs a solution in step S14 based on the search result.

  In the example of FIG. 11, the example of referring to the association degree of the combination of the test condition information and the configuration information of the cable sheath 71 has been described, but other than this, the configuration information of the cable sheath and the surface structure of the PC structure A solution search may be performed based on the relevance of any one or more combinations including objects.

  In the example of FIG. 12, a wide-area ultrasonic method is used as a nondestructive inspection method in the nondestructive inspection unit 8. The inspection data detected by the nondestructive inspection unit 8 based on the wide-area ultrasonic method is composed of data such as an ultrasonic analysis image detected based on the wide-area ultrasonic method, for example. For this reason, in the reference input parameter, data such as an ultrasonic analysis image detected based on these wide-area ultrasonic methods is learned in advance.

  The database 3 stores in advance three or more levels of relevance between the data of the ultrasonic analysis image as the reference input parameter and the determination result of the grout filling state in the cable sheath 71 as the output solution. Keep it. According to the example of FIG. 12, when the reference input parameter is the ultrasonic analysis image G1, the “filling rate 50%” is set with the association degree 80%, and the “filling rate 0%” is set with the association degree 60%. Yes. Further, when the reference input parameter is the ultrasonic analysis image G2, “filling rate 100%” is set with an association degree of 90%, and “filling state P” is set with an association degree of 40%.

  These associations are the database of the ultrasonic analysis images G1, G2, G3,..., And the filling rate and the filling status as the discrimination results when the nondestructive inspection was previously performed based on the wide-range ultrasonic method. 3 may be stored in advance and set based on them. This association degree may be configured by a so-called neural network. This degree of association indicates the accuracy with which the grout filling state in the actual cable sheath 71 is discriminated based on the image when the nondestructive inspection is performed based on the wide-area ultrasonic method. For example, with respect to the ultrasonic analysis image G3 based on the wide-area ultrasonic method, the “filling status Q” with the association degree of 70% is closest to the most accurate determination, and the “filling rate of 50%” with the association degree of 50% follows. It will be an accurate judgment. Similarly, with respect to the ultrasonic analysis image G2 based on the wide-area ultrasonic method, an association degree of 90% “filling rate 100%” is close to the most accurate determination, followed by “filling state P” with an association degree of 40%. It will be an accurate judgment.

  After shifting to step S13, the search program performs an operation of determining the grout filling state in the cable sheath 71 based on the input parameter analyzed in step S12. Reference is made to the association shown in FIG. 12 acquired in advance to determine the grout filling status. For example, when the frequency response of the input parameter analyzed in step S12 is the ultrasonic analysis image G1 as the reference input parameter or approximates it, when the above-mentioned relevance is referred, The highest “filling rate 50%” is selected as the optimal solution. However, it is not essential to select a solution with the highest degree of association as the optimum solution, and “filling rate 0%” that allows the association itself with a low degree of association may be selected as the optimum solution. Of course, an output solution that is not connected with an arrow may be selected. That is, the selection of the grout filling status in the cable sheath 71 is not limited to the case where the degree of association is selected in order from the highest degree of association, but the order of selection from the order of the lowest association degree according to the case. Or any other priority order.

  Further, the ultrasonic analysis image of the input parameter analyzed in step S12 is partially similar to the ultrasonic analysis image G2 as the reference input parameter, but also partially similar to the ultrasonic analysis image G3. In the case where it is not known whether or not to assign the reference input parameter, for example, it may be determined which reference input parameter is assigned based on the feature amount on the image through deep learning.

  FIG. 13 shows ultrasonic analysis images G1, G2,... As the inspection data of the past nondestructive inspection by the broadband ultrasonic method, the shape information of the cable sheath 71, the arrangement information of the cable sheath 71, and the PC structure 7. 3 shows an example in which three or more levels of association between a combination of one or more of the configuration information and the surface state information of the PC structure 7 and a determination result of the grout filling status for the combination are set. .

  The form information of the cable sheath 71 includes all kinds of information related to the form such as the diameter of the cable sheath 71 and the type of the cable sheath. Further, the arrangement information of the cable sheath 71 includes all information related to the arrangement form of the cable sheath 71 in the PC structure 7. Examples of the arrangement information of the cable sheath 71 include, for example, information on whether the cable sheaths 71 are arranged in parallel in the front view, the interval between the cable sheaths 71, the cover depth of the cable sheath 71, and the like. It is. The configuration information in the PC structure 7 includes, for example, an arrangement interval of reinforcing bars arranged in the PC structure 7, an arrangement interval of PC steel materials, and the like. The surface state information of the PC structure 7 is a surface unevenness state or the like.

  In such a case, as shown in FIG. 13, the relevance is calculated as ultrasonic analysis images G 1, G 2,... As inspection data for nondestructive inspection, as well as arrangement intervals of reinforcing bars as configuration information. A set of combinations of any one or more of the covering depths of the cable sheath 71 is expressed as so-called hidden layer nodes 61a to 61e. In each of the nodes 61a to 61e, a weight for the reference input parameter and a weight for the output solution are set. This weighting is an association degree of three or more levels. For example, in the node 61a, the ultrasonic analysis image G1 is associated with an association degree of 80%, and “sheath covering depth: 0-2m” as arrangement information is associated with an association degree of 80%. In the node 61c, the ultrasonic analysis image G2 has an association degree of 60%, “rebar arrangement interval: 2-3 m” as configuration information has an association degree of 60%, and “sheath covering depth: 2- 4m "is linked with a link degree of 40%.

  Similarly, when such association is set, when the process proceeds to step S13, ultrasonic analysis images G1, G2,... As inspection data for nondestructive inspection as input parameters extracted in step S12. Search for an output solution according to the degree of association between configuration information and arrangement information. The search program performs an operation of selecting one or more optimal solutions from the output solutions based on the input parameters analyzed in step S12. In selecting this optimal solution, the association degree shown in FIG. 11 acquired in advance is referred to. For example, when the input parameter analyzed in step S12 is the ultrasonic analysis image G1 and the configuration information is “rebar arrangement interval: 1-2 m”, the node 61b is associated through the association degree, The node 61b is associated with a “filling rate of 50%” with an association degree of 60% and a “filling state Q” with an association degree of 40%.

  The search program similarly outputs a solution in step S14 based on the search result.

  In the example of FIG. 13, the example of referring to the association degree of the combination of the configuration information and the arrangement information has been described. However, in addition to this, the configuration information of the cable sheath 71 and the surface state information of the PC structure 7 are included. Alternatively, the solution search may be performed based on the association degree of any one or more combinations.

  In the above-described embodiment, the non-destructive inspection method has been described by taking the X-ray transmission method, the impact elastic wave method, the impact echo method, the broadband ultrasonic method as an example, but is not limited thereto. Of course, any other nondestructive inspection method may be substituted.

  In any nondestructive inspection method, the user can grasp the grout filling state in the cable sheath based on the output discrimination result. Based on the grasped state of grout filling, it is possible to inject grout further in the cable sheath 71 if necessary.

  In particular, according to the present invention, it is possible to easily grasp the grout filling state without requiring special skill. According to the present invention, it is possible to grasp the grout filling state with higher accuracy. Furthermore, by configuring the above-mentioned association degree with artificial intelligence, it is possible to further improve the discrimination accuracy by learning this.

  In addition, the present invention is characterized in that an optimum grout filling state determination result is searched for through the association degree set in three or more stages. The association degree can be described by a numerical value of 0 to 100%, for example, but is not limited to this, and may be configured at any stage as long as it can be described by three or more numerical values.

  By searching based on the degree of association represented by numerical values of three or more levels, search and display in descending order of the degree of association in a situation where the determination result of the filling status of a plurality of grouts is selected. Is also possible. In this way, if the user can display to the user in the descending order of the association degree, it is possible to prompt the user to preferentially select the determination result of the more likely grout filling status. On the other hand, even if the result of determining the filling state of the grout with a low association degree can be displayed in the sense of a second opinion, it can be useful when the analysis cannot be performed well with the first opinion.

  In addition to this, according to the present invention, it is possible to make a determination without overlooking the determination result of the grout filling state having an extremely low relevance such as 1%. Even the result of determining the filling status of grout with a very low degree of association is connected as a slight sign and may be useful as a result of determining the filling status of grout once every tens or hundreds of times. This can be alerted to the user.

  Furthermore, according to the present invention, there is an advantage that a search policy can be determined by a method of setting a threshold value by performing a search based on such three or more levels of association. If the threshold is lowered, it is possible to pick up without omission even if the above-mentioned relevance is 1%, but it is unlikely that the discrimination result of the grout filling status can be suitably detected, and a lot of noise is picked up. In some cases. On the other hand, if the threshold value is increased, there is a high possibility that the determination result of the optimum grout filling status can be detected with high probability, but usually the degree of association is low and it is slewed, but it is tens of times and once every hundred times. In some cases, the preferred solution that comes out may be overlooked. It is possible to decide which to place importance on the basis of the idea on the user side and the system side, but it is possible to increase the degree of freedom in selecting points to place such emphasis.

  Furthermore, in the present invention, the association degree described above may be updated. This update may reflect information provided via a public communication network such as the Internet. If new knowledge about the relationship between the input parameters and the output solution (the result of determining the grout filling status) is discovered through site information or writing that can be obtained from the public communication network, depending on the knowledge Increase or decrease relevance.

  The update of the first degree of association is performed by the system side or the user side based on the contents of research data, papers, conference presentations, newspaper articles, books, etc. by experts other than based on information obtainable from the public communication network. It may be updated artificially or automatically. Artificial intelligence may be used in these update processes.

DESCRIPTION OF SYMBOLS 1 Grout filling condition discrimination system 2 Discriminator 3 Database 5 Imaging device 7 Structure 8 Nondestructive inspection part 9 Evaluation device 21 Internal bus 23 Display part 24 Control part 25 Operation part 26 Communication part 27 Search part 28 Storage part 61 Node 71 Cable sheath

The grout filling status determination system according to the present invention is a grout filling status determination system for determining the grout filling status of a PC structure in a cable sheath by nondestructive inspection. The above-described nondestructive inspection is performed on a database in which three or more levels of association between the data and the grout filling state determination result for the inspection data are stored in advance, and a cable sheath for newly determining the grout filling state. An input means for inputting inspection data obtained by performing, and assigning the inspection data input via the input means to inspection data associated with the association degree stored in the database, and the assigned inspection grouting status to the cable sheath on the basis of the set associated degree data Characterized in that it comprises a determination means for discriminating for.

A grout filling status determination program according to the present invention is a grout filling status determination program for determining the grout filling status of a PC structure in a cable sheath by nondestructive inspection. A non-destructive inspection for the cable sheath for newly determining the degree of filling of the grout, and an association degree obtaining step for obtaining in advance three or more levels of relevance between the data and the result of determining the filling state of the grout for the inspection data Assigning inspection data input in the association degree acquisition step to inspection data associated with the association degree acquired in advance in the association degree acquisition step It is cable on the basis of the set associated degree test data Characterized in that to execute a determining step of determining the grout filling status into the over scan the computer.

The grout filling status determination system according to the present invention is a grout filling status determination system for determining the grout filling status of a PC structure in a cable sheath by nondestructive inspection. The above-described nondestructive inspection is performed on a database in which three or more levels of association between the data and the grout filling state determination result for the inspection data are stored in advance, and a cable sheath for newly determining the grout filling state. An input means for inputting inspection data obtained by performing, and assigning the inspection data input via the input means to inspection data associated with the association degree stored in the database, and the assigned inspection grouting status to the cable sheath on the basis of the set associated degree data Characterized in that it comprises a determination means for discriminating for.

A grout filling status determination program according to the present invention is a grout filling status determination program for determining the grout filling status of a PC structure in a cable sheath by nondestructive inspection. A non-destructive inspection for the cable sheath for newly determining the degree of filling of the grout, and an association degree obtaining step for obtaining in advance three or more levels of relevance between the data and the result of determining the filling state of the grout for the inspection data An input step in which the inspection data obtained by performing is input, and the inspection data input in the input step is assigned to inspection data associated with the association degree acquired in advance in the association degree acquisition step, and the assigned cable sheath on the basis of the set associated degree test data Characterized in that to execute a determining step of determining the grout filling status to the computer.

The grout filling status determination system according to the present invention is a grout filling status determination system for determining the grout filling status of a PC structure in a cable sheath by nondestructive inspection. The above-described nondestructive inspection is performed on a database in which three or more levels of association between the data and the grout filling state determination result for the inspection data are stored in advance, and a cable sheath for newly determining the grout filling state. An input means for inputting inspection data obtained by performing, and assigning the inspection data input via the input means to inspection data associated with the association degree stored in the database, and the assigned inspection Grout filling status in the cable sheath based on the relevance set in the data And a discrimination means for discriminating for said database, a combination of the test data for the previous non-destructive inspection by any one or more and X-ray transmission method of morphological information, arrangement information of the cable sheath of the cable sheath, the Three or more levels of association with the result of determining the grout filling status for the combination are stored in advance, and the input means newly performs the non-destructive inspection by the X-ray transmission method for the cable sheath that newly determines the grout filling status. One or more of the inspection data obtained by performing the above, the configuration information of the cable sheath constituting the combination, and the arrangement information of the cable sheath are input .

A grout filling status determination program according to the present invention is a grout filling status determination program for determining the grout filling status of a PC structure in a cable sheath by nondestructive inspection. A non-destructive inspection for the cable sheath for newly determining the degree of filling of the grout, and an association degree obtaining step for obtaining in advance three or more levels of relevance between the data and the result of determining the filling state of the grout for the inspection data Assigning inspection data input in the association degree acquisition step to inspection data associated with the association degree acquired in advance in the association degree acquisition step Cable based on the relevance set in the inspection data And a determination step of determining the grout filling status into the over scan, in the association degree obtaining step further embodiment the information of the cable sheath, according to any one or more and X-ray transmission method of the arrangement information of the cable sheath Three or more levels of association between the combination of the inspection data of the past non-destructive inspection and the determination result of the grout filling state with respect to the combination are acquired in advance, and in the input step, the grout filling state is newly determined. One or more of inspection data obtained by performing the non-destructive inspection by the X-ray transmission method on the cable sheath, configuration information of the cable sheath constituting the combination, and arrangement information of the cable sheath are input. It is characterized by having a computer execute what is done .

Claims (18)

In the grout filling status discrimination system for discriminating the grout filling status in the cable sheath of the PC structure by non-destructive inspection,
A database in which the degree of association of three or more stages of inspection data of past non-destructive inspection for the cable sheath and the determination result of the grout filling state for the inspection data is stored in advance;
Input means for inputting inspection data obtained by performing the nondestructive inspection on the cable sheath for newly determining the grout filling state;
A grout filling situation characterized by comprising discrimination means for referring to the degree of association stored in the database and discriminating the grout filling situation in the cable sheath based on information inputted through the input means. Discriminating system. The database stores in advance three or more degrees of association between inspection data of past nondestructive inspection by X-ray transmission method and determination result of grout filling status with respect to the inspection data,
2. The inspection means obtained by performing the non-destructive inspection by the X-ray transmission method on a cable sheath for newly determining a grout filling state is input to the input means. Grout filling status discrimination system. The database further includes a combination of any one or more of the cable sheath configuration information and the cable sheath arrangement information and the inspection data of the past non-destructive inspection by the X-ray transmission method, and a grout filling state for the combination. The degree of association of three or more levels with the discrimination result is stored in advance,
The grout filling situation determination system according to claim 2, wherein the input means further receives at least one of configuration information of the cable sheaths and arrangement information of the cable sheaths constituting the combination. The database stores in advance three or more degrees of association between inspection data of past nondestructive inspection by the shock elastic wave method and a determination result of a grout filling state with respect to the inspection data,
2. The inspection means obtained by performing the non-destructive inspection by the shock elastic wave method on a cable sheath for newly determining a grout filling state is input to the input means. Grout filling status discrimination system. The database further includes configuration information of the cable sheath, arrangement information of the cable sheath, tension material information regarding the tension material provided in the PC structure, grout information regarding the grout, and placement in the PC structure. Three or more levels of association between a combination of any one or more of the concrete information and the inspection data of the past nondestructive inspection by the shock elastic wave method and a determination result of the filling state of the grout for the combination is stored in advance.
The input means includes configuration information of the cable sheath constituting the combination, grout information regarding the grout, arrangement information of the cable sheath, tension material information regarding a tension material provided in the PC structure, and inside the PC structure. 5. The grout filling status determination system according to claim 4, wherein any one or more pieces of concrete information placed on the grind is further input. The database stores in advance three or more degrees of association between inspection data of past nondestructive inspection by impact echo method and determination result of grout filling status with respect to the inspection data,
2. The inspection data obtained by performing the non-destructive inspection by the impact echo method on a cable sheath that newly determines a grout filling state is input to the input means. Grout filling status discrimination system. The database further includes one or more of the configuration information of the cable sheath, the layout information of the cable sheath, the test condition information of the impact echo method, the surface condition information of the PC structure, and the past non-existence by the impact echo method. Three or more levels of association between the combination of the inspection data of the destructive inspection and the determination result of the grout filling state for the combination are stored in advance,
The input means further receives at least one of configuration information of the cable sheaths constituting the combination, layout information of the cable sheaths, test condition information of the impact echo method, and surface state information of the PC structure. The grout filling status determination system according to claim 6. The database stores in advance three or more degrees of association between inspection data of past nondestructive inspection by the broadband ultrasonic method and determination result of grout filling status with respect to the inspection data,
2. The inspection means obtained by performing the non-destructive inspection by a broadband ultrasonic method on a cable sheath for newly determining a grout filling state is input to the input means. Grout filling status discrimination system. The database further includes one or more of the configuration information of the cable sheath, the layout information of the cable sheath, the configuration information in the PC structure, the surface state information of the PC structure, and the past information by the broadband ultrasonic method. Three or more degrees of association between the combination with the inspection data of the non-destructive inspection and the determination result of the filling state of the grout for the combination is stored in advance,
The input means further receives at least one of configuration information of the cable sheaths constituting the combination, arrangement information of the cable sheaths, configuration information in the PC structure, and surface state information of the PC structure. The grout filling status determination system according to claim 8, wherein: In the grout filling status determination program for determining the grout filling status in the cable sheath of the PC structure by non-destructive inspection,
A degree-of-association acquisition step of acquiring in advance three or more degrees of association between the inspection data of the past non-destructive inspection for the cable sheath and the determination result of the grout filling state for the inspection data;
An input step in which inspection data obtained by performing the nondestructive inspection on the cable sheath for newly determining the grout filling state is input,
A grout that refers to the association degree acquired in the association degree acquisition step and causes a computer to execute a determination step for determining a grout filling state in the cable sheath based on the information input in the input step. Filling status determination program. In the above-mentioned association degree acquisition step, three or more degrees of association degree between the inspection data of the past nondestructive inspection by the X-ray transmission method and the determination result of the grout filling state with respect to the inspection data are acquired in advance,
The inspection data obtained by performing the non-destructive inspection by the X-ray transmission method on a cable sheath for newly determining a grout filling state is input in the input step. Grout filling status discrimination program. In the association degree acquisition step, a combination of any one or more of the cable sheath configuration information and the cable sheath arrangement information and inspection data of the past non-destructive inspection by the X-ray transmission method, and a grout for the combination Acquire in advance three or more levels of association with the determination result of the filling status of
12. The grout filling status determination program according to claim 11, wherein in the input step, at least one of configuration information of the cable sheaths and arrangement information of the cable sheaths constituting the combination is further input. In the above-mentioned association degree acquisition step, three or more degrees of association degree between the inspection data of the past nondestructive inspection by the shock elastic wave method and the determination result of the grout filling state with respect to the inspection data are stored in advance.
The inspection data obtained by performing the nondestructive inspection by the shock elastic wave method on a cable sheath for newly determining the grout filling state is input in the input step. Grout filling status discrimination program. In the association degree acquisition step, the cable sheath configuration information, the cable sheath arrangement information, the tension material information on the tension material provided in the PC structure, the grout information on the grout, and the inside of the PC structure. The degree of relevance of three or more levels of a combination of any one or more of the concrete information to be established and the inspection data of the past nondestructive inspection by the shock elastic wave method and the determination result of the grout filling state with respect to the combination is previously determined. Acquired,
In the input step, the configuration information of the cable sheaths constituting the combination, the arrangement information of the cable sheaths, the tension material information on the tension material provided in the PC structure, the concrete placed in the PC structure 14. The grout filling status determination program according to claim 13, wherein any one or more of the information is further input. In the above-described association degree acquisition step, three or more degrees of association degree between the inspection data of the past nondestructive inspection by the impact echo method and the determination result of the filling state of the grout with respect to the inspection data are acquired in advance,
The inspection data obtained by performing the non-destructive inspection by the impact echo method on a cable sheath for newly determining a grout filling state is input in the input step. Grout filling status discrimination program. In the association degree acquisition step, at least one of the shape information of the cable sheath, the arrangement information of the cable sheath, the test condition information of the impact echo method, the surface condition information of the PC structure and the impact echo method is used. Acquire in advance three or more levels of association between the combination with past non-destructive inspection data and the result of determining the grout filling status for the combination,
In the input step, one or more of the configuration information of the cable sheaths constituting the combination, the arrangement information of the cable sheaths, the test condition information of the impact echo method, and the surface state information of the PC structure is further input. The grout filling status determination program according to claim 15, wherein: In the above-mentioned association degree acquisition step, three or more degrees of association degree between the inspection data of the past nondestructive inspection by the broadband ultrasonic method and the determination result of the grout filling state with respect to the inspection data are acquired in advance,
The inspection data obtained by performing the nondestructive inspection by a broadband ultrasonic method on a cable sheath for newly determining a grout filling state is input in the input step. Grout filling status discrimination program. In the association degree acquisition step, one or more of the configuration information of the cable sheath, the arrangement information of the cable sheath, the configuration information in the PC structure, and the surface state information of the PC structure and the broadband ultrasonic method Obtaining in advance three or more levels of relevance between the combination of the past non-destructive inspection data and the determination result of the grout filling status for the combination,
In the input step, one or more of the configuration information of the cable sheaths constituting the combination, the layout information of the cable sheaths, the configuration information in the PC structure, and the surface state information of the PC structure are further input. The grout filling status determination program according to claim 17, wherein:

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