JP2018021402A - Shield excavator operation analysis system, shield excavator operation analysis method and program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a shield excavator operation analysis system which can perform an operation support, and can homogenize an operation by modeling the operation of a shield excavator of a skilled operator on the basis of a relationship with monitoring data of a corresponding construction environment.SOLUTION: A shield excavator operation analysis system for analyzing a correspondence relationship of monitoring item data for monitoring an excavation status of a shield excavator, and operation data corresponding to the monitoring item data comprises; an operation data change detection part for detecting a change of the operation data; a monitoring item data detection part for extracting the monitoring item data at operation data change timing being timing at which a change of the operation data occurs; and a data relevancy analysis part for extracting the monitoring item data having relevancy with the operation data from the monitoring item data detection part.SELECTED DRAWING: Figure 1

Description

  The present invention relates to a shield excavator operation analysis system, a shield excavator operation analysis method, and a program.

Conventionally, when constructing a tunnel or the like by a shield construction method, the construction environment of the site where the shield excavator excavates (the state of the ground such as soil and water pressure) changes every moment depending on the position of the site. Therefore, it is necessary for an operator to perform operations such as a traveling speed and a traveling direction in excavation of the shield excavator in accordance with changes in the construction environment.
In other words, if the operator does not appropriately operate the shield excavator corresponding to each of the sites having different construction environments, the accuracy and safety of the excavated tunnel design are reduced.

In addition, the operator builds the experience of operating the shield excavator in response to changes in the construction environment and improves the skill level by performing tunnel construction at various sites.
Skilled operators operate the shield machine at the site during excavation, and perform operations corresponding to the current construction environment at the site, applying knowledge of operation in similar past construction environments. . However, in the case of an operator with a small number of construction sites, in a construction environment that has never been experienced, it is not possible to operate an appropriate shield excavator in that construction environment with insufficient experience and basic operational knowledge.

For this reason, the accuracy and safety with respect to the design of the tunnel to be excavated vary depending on the skill level of the operator of each shield excavator. Also, highly skilled operators tend to decrease.
In order to solve this problem, there is a configuration in which the shield excavator is automatically operated based on measurement data indicating the rotation state of the cutter of the shield excavator and the propulsion state of the propulsion jack during excavation (see, for example, Patent Document 1).

Japanese Patent Laid-Open No. 07-71189

However, in the shield excavator described above, excavation is controlled depending on whether or not each of the measurement data exceeds a preset value for each of the measurement data.
For this reason, although the operation by the operator is made uniform, the relevance of the operation of the shield excavator performed corresponding to the measurement data to the construction environment at the site is unknown. That is, the skill level of the operator cannot be improved only by acquiring the measurement data as in the cited document 1 and performing control corresponding to the measurement data.

  In addition, since control is performed by comparing measured measurement data with set values, unlike operations based on the experience of skilled operators, control corresponding to the construction environment of the site that changes from moment to moment is performed appropriately. However, the accuracy and safety of the excavated tunnel design cannot be improved. For this reason, unlike the case where a skilled operator's experience in operating a shield excavator is provided to all operators, the operation of the shield excavator cannot be made uniform at the level of the skilled operator.

  The present invention has been made in consideration of the above circumstances, and by modeling the operation of a shield excavator by a skilled operator based on the relationship with the monitoring data of the corresponding construction environment, operation support and It is an object of the present invention to provide a shield excavator operation analysis system, a shield excavator operation analysis method, and a program that enable uniform operation.

  In order to solve the above problems, the shield excavator operation analysis system according to the present invention relates to the operation on the shield excavator, the monitoring item data for monitoring the excavation status of the shield excavator and the operation corresponding to each of the monitoring item data. A shield excavator operation analysis system that analyzes a correspondence relationship with operation data, an operation data change detection unit that detects a change in the operation data, and an operation data change timing that is a timing at which the change in the operation data occurs. A monitoring item data detection unit that extracts monitoring item data, and a data relevance analysis unit that extracts monitoring item data related to the operation data from each of the monitoring item data detection units. .

  The shield excavator operation analysis system according to the present invention includes a monitoring item data input unit that acquires the monitoring item data every predetermined time, an operation data input unit that acquires the operation data every predetermined time, and the predetermined data A data table storage unit storing the monitoring item data and the operation data every time, and an operation data change detection unit detects a change in the operation data in the data table storage unit, The monitoring item data detection unit extracts monitoring item data before and after the operation data change timing in the data table storage unit.

  The shield excavator operation analysis system according to the present invention provides an operation from the operation data change timing at which the operation data has changed to a monitoring item data change timing at which the monitoring item data has changed before the operation data change timing. An operation timing extraction unit for obtaining a timing time, and a data relevance storage unit for accumulating a combination of the operation data and the monitoring item data related to the operation data are further provided.

  The shield excavator operation analysis method of the present invention relates to the operation on the shield excavator, and shows the correspondence between each of the monitoring item data for monitoring the excavation status of the shield excavator and the operation data of the operation corresponding to each of the monitoring item data. A shield excavator operation analysis method to analyze, wherein an operation data change detection unit detects an operation data change detection process, and a monitoring item data detection unit detects when the operation data change occurs The monitoring item data detection process for extracting the monitoring item data at the operation data change timing, and the data relevance analysis unit extracts the monitoring item data related to the operation data from each of the monitoring item data detection units Data relevance analysis process.

  The program of the present invention relates to an operation on a shield excavator, and the shield excavator analyzes the correspondence between each of the monitoring item data for monitoring the excavation status of the shield excavator and the operation data of the operation corresponding to each of the monitoring item data. This is a program for causing a computer to function as an operation analysis system, and the operation data change detection means for detecting a change in the operation data, monitoring the operation data change timing that is the timing at which the change in the operation data occurs. A monitoring item data detecting means for extracting item data and a program for functioning as a data relevance analyzing means for extracting monitoring item data related to the operation data from each of the monitoring item data detecting sections.

  ADVANTAGE OF THE INVENTION According to this invention, the database for construction of the operation model of a skilled operator can be formed by accumulating the operation data of a skilled operator corresponding to the measurement data which shows construction environment. The operation model based on this database can be utilized for assistance of an operator with little experience, uniform operation, and the like.

It is a figure explaining the shield excavator of the object which performs operation analysis of the shield excavator operation analysis system of this embodiment. It is a figure which shows the structural example of the shield excavator operation analysis system by this embodiment. It is a figure which shows the structural example of the data table in the data table memory | storage part 17 of FIG. It is a figure which shows the structural example of the data relationship table in the data relationship storage part. It is a flowchart which shows the operation | movement which analyzes each relevance of the operation data by the shield excavator operation analysis system of this embodiment, and monitoring item data.

Hereinafter, an embodiment of a shield excavator operation analysis system according to the present invention will be described with reference to FIG.
FIG. 1 is a diagram for explaining a shield excavator to be subjected to operation analysis of the shield excavator operation analysis system of the present embodiment.
Fig.1 (a) has shown the conceptual diagram of the shield excavator of the object which performs the operation analysis of the shield excavator operation analysis system of this embodiment.
The excavation mechanism 50 is a mechanism for excavating the shield excavator 20 while constructing the primary lining S by assembling the segments with an erector (not shown) at the rear of the cylindrical skin plate 2 in the direction of arrow D1. . In the excavation mechanism 50, the mud clay chamber 7 is provided behind the annular and face plate type cutter 10 having the face 23 in the direction of arrow D <b> 1. The mud clay chamber 7 is filled with a mud clay material injection pipe 8 from a mud clay material injection pipe 8 and converts the excavated soil into mud by powerful mixing with a mixing blade (not shown). The face 23 is stabilized by balancing with and excavation is performed. Here, the excavation residual soil accumulated in the mud clay chamber 7 of the excavation mechanism 50 is introduced into the screw conveyor 60 and is discharged to the outside of the excavating tunnel via the conveyors 62 and 63. The gantry M supports the screw conveyor 60 and the conveyors 62 and 63, respectively. Although not shown, the excavation mechanism 50 is provided with a propulsion jack (described later), and the excavation direction and the propulsion speed are operated by the propulsion jack.

  In the present embodiment, the operation of determining the propulsion direction and propulsion speed of the skin plate 2 is performed by the hydraulic operation of the propulsion jack, and the operation of determining the rotational speed (screw speed described later) of the screw conveyor 60 is performed. This will determine the mud pressure. A shield excavator operation analysis system, which will be described later, acquires each of these operation data and monitoring item data (described later), and analyzes the relationship between the operation data and the monitoring item data.

  In the present embodiment, the operation of determining the propulsion direction and the propulsion speed of the skin plate 2 is performed by the hydraulic operation of the propulsion jack, and the operation of determining the screw rotation speed (screw rotation speed) of the screw conveyor 60 is performed. Thus, it is assumed that the operation data for determining the mud pressure is acquired. In the present embodiment, the monitoring item data includes, for example, cutter torque, cutter speed, propulsion pressure, propulsion speed, propulsion speed instruction sheet as data for monitoring the construction environment being excavated and the operating state of the shield excavator. Deviation value, control earth pressure, face earth pressure average value instruction range dummy, agitator torque, screw speed, primary screw pressure, secondary screw pressure, NO. 1 copy stroke, NO. 1 Copy stroke command value difference, NO. 1 copy position, NO. 1 copy position instruction deviation value, pitching, pitching instruction value difference, rolling, rolling instruction value difference, vertical folding angle, vertical folding angle instruction value difference, left and right folding angle, left and right folding angle instruction value difference, S / M front trunk direction, S / M front trunk direction instruction value difference, S / M rear trunk direction instruction value, S / M rear trunk direction instruction value difference, planned route horizontal deviation (control point), planned route vertical deviation (control point), There are azimuth (management point), azimuth indication value difference (management point), planned route azimuth (management point), pitch (management point), planned route pitch (management point), and the like.

  FIG. 1B shows a conceptual diagram illustrating a propulsion jack that propels the excavation mechanism 50. As shown in FIG. 1B, a force point for propelling the surface of the skin plate 2 is set depending on which position of the propulsion jack is driven. In FIG. 1 (b), 22 propulsion jacks are shown, but this number is not limited. By distributing the jack pressure of each propulsion jack, the propulsion jack force point position Fx on the x axis and the propulsion jack force point position Fy on the y axis are set, and the mark P becomes the position of the force point. When the propulsion pressure is applied to a position corresponding to the force point on the surface of the skin plate 2, the direction in which the excavation mechanism 50 propels is set. Setting (operation) of this direction is performed by a propulsion jack pattern indicating which of the propulsion jacks is driven. The propulsion speed is set by the amount of oil (oil amount) supplied per unit time to increase the jack pressure.

  FIG. 2 is a diagram illustrating a configuration example of the shield excavator operation analysis system according to the present embodiment. 2, the shield excavator operation analysis system includes a monitoring item data input unit 11, an operation data input unit 12, an operation data detection unit 13, an operation timing extraction unit 14, a monitoring item data detection unit 15, a data relation analysis unit 16, Each of the data table storage unit 17 and the data relationship storage unit 18 is provided.

  The monitoring item data input unit 11 receives the data of each of the monitoring items described above at a timing when a timing signal indicating the passage of a predetermined period of time (for example, 1 second) is supplied from a timing unit (not shown). Is used as a measurement value, and the monitoring item data is acquired from each of the detection means (sensor, measuring instrument, etc.) provided in each part. In addition, the monitoring item data input unit 11 sequentially writes and stores monitoring item data in the monitoring item data table in the data table storage unit 17 together with the acquisition time in time series.

Similar to the monitoring item data input unit 11, the operation data input unit 12 acquires each of the operation values of the operation described above as a measured value at the timing when the timing signal is supplied from the timing unit. In addition, the operation data input unit 12 writes operation data in the operation data table in the data table storage unit 17 in order and stores the operation data sequentially in time series.
This operation data input part 12 acquires the operation value for every kind of operation input with respect to the touch panel in the operation panel which operates a shield excavator as operation data, for example. The operation data of the touch panel is output as digital data from the operation panel to the computer. For this reason, since the operation data input unit 12 can directly obtain operation data as digital data, there is no need to convert dial-type analog data into digital data, and an A / D (Analog / Digital) converter or the like. Therefore, the apparatus can be simplified and the processing time for acquiring operation data can be shortened by the time required for conversion.

  FIG. 3 is a diagram illustrating a configuration example of a data table in the data table storage unit 17 of FIG. FIG. 3A is an example of a monitoring item data table in which monitoring item data is stored. As a time stamp, time and monitoring item data (monitoring item data #p to monitoring item data #a) acquired at this time are written and stored in association with each other. These monitoring item data are, for example, data including all or part of the planned route pitch (control point) from the cutter torque already shown.

  FIG. 3B is an example of an operation data table in which operation data is stored. Similar to FIG. 3A, the time and the operation data (operation data # 1, # 2, # 3,...) Acquired at this time are associated with each other and written and stored as a time stamp. ing. These operation data are data including, for example, all or all of the driving pattern of the propulsion jack already shown, the amount of oil supplied per unit time supplied to the propulsion jack driven by the driving pattern, and the screw rotation speed of the screw conveyor. .

Returning to FIG. 2, the operation data detection unit 13 sequentially searches the operation data table in the data table storage unit 17 in time series, and detects operation data whose operation value has changed.
The operation timing extraction unit 14 reads the operation start time, which is the timing when the operation of the operation data detected by the operation data detection unit 13 is started, the time when the operation is stopped, that is, the operation stop time when the operation value is maintained. Here, the operation timing extraction unit 14 subtracts the operation start time from the operation stop time to obtain an operation time width in which the operation data is changed. Further, the operation timing extraction unit 14 subtracts the operation value of the operation data at the operation stop time from the operation value of the operation data before the operation, and obtains a change operation value that is a numerical value of the operation value changed in the operation time width. Ask.

The monitoring item data detection unit 15 monitors the data table storage unit 17 using each numerical value of the monitoring item data in a predetermined time width before the operation start time detected by the operation timing extraction unit 14 as a monitoring item data group before change. Extract from item data table.
In addition, the monitoring item data detection unit 15 sets the numerical value of each of the monitoring item data in the predetermined time width from the operation start time detected by the operation timing extraction unit 14 as a changed monitoring item data group, and the data table storage unit 17. From the monitoring item data table.

The data relevance analysis unit 16 performs the relevance between the operation data and the monitoring item data based on the changed operation value, the pre-change monitoring item data group, and the post-change monitoring item data group of the operation data. For example, the data relevance analysis unit 16 subtracts the average value of the post-change monitoring item data group from the average value of the pre-change monitoring item data group to obtain a monitoring item data difference value.
Then, the data relevance analysis unit 16 calculates a correlation coefficient between the change operation value of the type of operation data to be analyzed and the monitoring item data difference value of each monitoring item data. Here, the data relevance analysis unit 16 extracts monitoring item data whose correlation coefficient with the operation data to be analyzed is equal to or greater than a preset threshold value as monitoring item data having relevance to the operation data.

The data relevance analysis unit 16 performs the above-described processing for obtaining the correlation coefficient for each of all types of operation data. Then, the data relevance analysis unit 16 writes the combination of the operation data and the related monitoring item data in the data relevance table of the data relevance storage unit 18 and stores it.
In this embodiment, the correlation coefficient is used as the degree of indicating the relevance between the operation data and the monitoring item data. However, if the relevance can be extracted, a multivariate analysis such as a multiple regression analysis or the like can be performed. Any method such as machine learning that repeatedly learns from data and extracts relevance may be used. By using machine learning, not only relevance but also regularity can be extracted.

  Here, in machine learning, a model is created with monitoring item data as explanatory variables and operation data as explained variables. In other words, a model between input explanatory variables and output explained variables is created by machine learning, and by using this model, highly relevant explained variables corresponding to combinations of explanatory variables. To be obtained. By using this model, it is possible to clearly obtain which of the operation data that is the explained variable needs to be operated in response to the change of the monitoring item data that is the explanatory variable. Here, as a machine learning technique for creating a model, any of commonly used techniques such as decision tree learning, neural network, genetic programming, and support vector machine may be used.

  Further, by using the correlation coefficient already described, it is possible to create a model using only the explanatory variables that are highly relevant to the explained variable. In addition, when the monitoring item data changes as the explained variable, the numerical value of the monitoring item data change is added to the explanatory variable, and the numerical value to which the operation data is manipulated is added to the explained variable. The regularity of how much operation data is given as a numerical value may be extracted as a model. By extracting regularity, when operating related operation data, it can be operated in response to changes in the numerical value of the monitoring item data, so by using machine learning, the operation of the shield excavator can be controlled by the operator. It can be made uniform regardless of experience.

  FIG. 4 is a diagram illustrating a configuration example of the data relationship table in the data relationship storage unit 18. In FIG. 4, the data relevance table relates to operation data types that indicate the types of operation data, time stamps that indicate the time at which the operation data was operated, change operation values that indicate a change in the operation data, and operation data. Then, the determined monitoring item data type is described as a record in association with it. Here, the monitoring item data type indicates the name of the monitoring item data type and the monitoring item data difference value.

By referring to this data relevance table, when the operation data is operated, each of the monitoring item data related to the operation data is known, and the time stamp when the operation data is operated can also be confirmed. Further, it is possible to know how much the operation data has been adjusted in order to operate the numerical value of the monitoring item data from the monitoring item data difference value and the change operation value.
Further, since the time stamp when the operation data is operated can be confirmed, in the monitoring item data table in the data table storage unit 17, when each operation data is operated, how the related monitoring item data changes. Can be confirmed. That is, when each monitoring item data changes, the relationship between the cause and the result of whether the operator operates one or a plurality of operation data corresponding to the changed combination of the monitoring item data is clarified Will be.

As described above, according to the present embodiment, each operation data operated by each operator is known in response to each change in the monitoring item data, and the experience of operating the shield excavator for each operator is visualized. Can be stored as a database (data table storage unit).
Further, according to the present embodiment, implicit knowledge such as empirical know-how or sensory processing of a skilled operator can be used as formal knowledge or organizational knowledge that can be provided in common to all operators. Thereby, when an operator with little experience can operate, it is possible to reflect the operation of the skilled operator, so that the operation of the shield excavator can be made uniform at the level of the skilled operator.

  FIG. 5 is a flowchart showing the operation of analyzing the relationship between the operation data and the monitoring item data of the shield excavator operation analysis system according to the present embodiment. In FIG. 5, FIG. 5 (a) shows a flowchart of an operation for acquiring each of the operation data and the monitoring item data. FIG. 5B shows a flowchart of an operation for analyzing the relevance of each of the operation data and the monitoring item data.

Data acquisition in FIG. 5A will be described.
Step S11: Time measuring means (not shown) measures time and determines whether or not a predetermined period of time has elapsed. Then, the time measuring means advances the process to step S12 when a predetermined period of time has elapsed. The time measuring means outputs a time measuring signal indicating that a predetermined period of time has elapsed to each of the monitoring item data input unit 11 and the operation data input unit 12. On the other hand, the time measuring means repeats the process of step S11 when the predetermined period of time has not elapsed.

  Step S12: When the time signal is supplied from the time measuring means, the monitoring item data input unit 11 acquires the measurement value of the monitoring item data corresponding to each detection means from the detection means provided in each part to be measured. To do.

  Step S13: The monitoring item data input unit 11 writes and stores the measured value of the monitoring item data in the monitoring item data table of the data table storage unit 17 in combination with the time (time) indicated by the timing signal.

  Step S13: When the time signal is supplied from the time measuring means, the operation data input unit 12 acquires each operation value of the operation data corresponding to each type of operation from the operation data setting means on the display panel.

Step S14: The operation data input unit 12 samples the operation value of the operation data in combination with the time indicated by the time signal.
Step S15: The operation data input unit 12 writes and stores the operation value obtained by sampling in the operation data table of the data table storage unit 17.
The above-described processing is continuously performed from the start to the end of tunnel excavation or in the excavation range in the section to be analyzed.

Next, the data analysis operation of FIG.
Step S21: The operation data detection unit 13 refers to the operation data table in the data table storage unit 17 in chronological order in the time indicated by the time stamp, and detects a change in the operation data.
Step S22: If the operation value of the operation data changes at the time of the time stamp, the operation data detection unit 13 proceeds to step S23. If the operation value of the operation data does not change, the operation data detection unit 13 Return to S21.

  Step S23: The operation data detection unit 13 detects the time of the operation start time when the change of the operation data is started, that is, the input of the instruction to change the operation data is started. Then, the operation timing extraction unit 14 reads, from the data relevance table, the operation start time that is the timing when the operation of the operation data detected by the operation data detection unit 13 is started and the operation stop time when the operation is stopped. In addition, the operation timing extraction unit 14 obtains an operation time width, and obtains a change operation value that is a numerical value of the operation value changed in the operation time width. Then, the operation timing extraction unit 14 writes the type of operation data, the time stamp indicating the operation start time of the operation data, and the changed operation value in the data relationship table of the data relationship storage unit 18. Remember.

Step S24: The operation data detection unit 13 determines whether or not the process of referring to the operation data table in the data table storage unit 17 in time order is completed.
At this time, when the process of referring to all the operation data in the operation data table is completed, the operation data detection unit 13 notifies the monitoring item data detection unit 15 of the completion and advances the process to step S25. On the other hand, if the process of referring to all the operation data in the operation data table has not been completed, the operation data detection unit 13 advances the process to step S21.

  Step S25: For each type of operation data, the monitoring item data detection unit 15 sets each numerical value of the monitoring item data in a predetermined time width before the detected operation start time as a monitoring item data group before change, From the operation start time, each numerical value of the monitoring item data in the predetermined time width is extracted from the monitoring item data table of the data table storage unit 17 as a changed monitoring item data group.

  Step S26: The data relationship analysis unit 16 determines the relationship between the operation data and the monitoring item data based on the changed operation value, the monitoring item data group before change, and the monitoring item data group after change. Do. Then, the data relevance analysis unit 16 extracts monitoring item data whose degree of relevance with the operation data to be analyzed is equal to or greater than a preset threshold value as monitoring item data that is related to the operation data. .

  Step S27: The data relevance analysis unit 16 uses the combination of the operation data and each of the monitoring item data determined to be related to the operation data as the data relevance of the data relevance storage unit 18. Write to table and store.

  The program for realizing the function of the shield excavator operation analysis system of FIG. 1 in the present invention is recorded on a computer-readable recording medium, and the program recorded on the recording medium is read into the computer system and executed. By doing so, you may perform the production | generation process of the database which shows the relevance of operation data and monitoring item data. Note that the “computer system” herein includes an OS (Operating System) and hardware such as peripheral devices. The “computer system” includes a WWW (World Wide Web) system having a homepage providing environment (or display environment). The “computer-readable recording medium” refers to a portable medium such as a flexible disk, a magneto-optical disk, a ROM (Read Only Memory), a CD-ROM (Compact Disc-Read Only Memory), or a computer system. A storage device such as a hard disk. Further, the “computer-readable recording medium” refers to a volatile memory (RAM (Random Access) in a computer system that becomes a server or a client when a program is transmitted via a network such as the Internet or a communication line such as a telephone line. Memory)) as well as those that hold programs for a certain period of time.

  The program may be transmitted from a computer system storing the program in a storage device or the like to another computer system via a transmission medium or by a transmission wave in the transmission medium. Here, the “transmission medium” for transmitting the program refers to a medium having a function of transmitting information, such as a network (communication network) such as the Internet or a communication line (communication line) such as a telephone line. The program may be for realizing a part of the functions described above. Furthermore, what can implement | achieve the function mentioned above in combination with the program already recorded on the computer system, and what is called a difference file (difference program) may be sufficient.

DESCRIPTION OF SYMBOLS 11 ... Monitoring item data input part 12 ... Operation data input part 13 ... Operation data detection part 14 ... Operation timing extraction part 15 ... Monitoring item data detection part 16 ... Data relevance analysis part 17 ... Data table storage part 18 ... Data relevance Memory

Claims (6)

A shield excavator operation analysis system for analyzing a correspondence relationship between each of monitoring item data for monitoring the excavation status of the shield excavator and operation data of an operation corresponding to each of the monitoring item data with respect to the operation on the shield excavator. ,
An operation data change detection unit for detecting a change in the operation data;
A monitoring item data detection unit for extracting monitoring item data of operation data change timing which is a timing at which the change of the operation data occurs;
A shield excavator operation analysis system comprising: a data relevance analysis unit that extracts monitoring item data related to the operation data from each of the monitoring item data detection units. A monitoring item data input unit for acquiring the monitoring item data every predetermined time;
An operation data input unit that acquires the operation data at each predetermined time;
A data table storage unit in which the monitoring item data and the operation data are stored every predetermined time;
An operation data change detection unit detects a change in the operation data in the data table storage unit,
The shield excavator operation analysis system according to claim 1, wherein the monitoring item data detection unit extracts monitoring item data before and after the operation data change timing in the data table storage unit. An operation timing extraction unit that obtains an operation timing time from the operation data change timing at which the operation data has changed to a monitoring item data change timing that is a timing at which the monitoring item data has changed before the operation data change timing;
The shield according to claim 1, further comprising: a data relevance storage unit that accumulates a combination of the operation data and the monitoring item data that is related to the operation data. Excavator operation analysis system. 4. The shield excavator according to claim 1, wherein a data relevance analysis unit extracts relevance between the operation data and the monitoring item data using machine learning. 5. Operation analysis system. Regarding a shield excavator operation, a shield excavator operation analysis method for analyzing a correspondence relationship between each of monitoring item data for monitoring the excavation status of the shield excavator and operation data of an operation corresponding to each of the monitoring item data. ,
An operation data change detection unit, wherein the operation data change detection process detects a change in the operation data,
A monitoring item data detection process, wherein the monitoring item data detection unit extracts monitoring item data at an operation data change timing that is a timing at which the change of the operation data occurs;
A data relevance analysis unit comprising: a data relevance analysis process for extracting monitoring item data related to the operation data from each of the monitoring item data detection units. . As a shield excavator operation analysis system for analyzing the correspondence between each of the monitoring item data for monitoring the excavation status of the shield excavator and the operation data of the operation corresponding to each of the monitoring item data in the operation of the shield excavator Is a program for making
The computer,
Operation data change detecting means for detecting a change in the operation data;
Monitoring item data detecting means for extracting monitoring item data of operation data change timing which is the timing at which the change of operation data occurs;
A program that functions as a data relevance analysis unit that extracts monitoring item data that is related to the operation data from each of the monitoring item data detection units.

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