JP7319911B2 - Train information management device - Google Patents

Description

An embodiment according to the present invention relates to a train information management device.

Visualization of data collected from rolling stock that constitutes a train and its processed data (hereinafter also referred to as rolling stock data) is utilized in monitoring train conditions, factor analysis of equipment failures, and the like. In train status monitoring, representative vehicle data that meets the purpose of monitoring is limited in advance from the data that can be collected. By monitoring this limited data, we are able to respond smoothly when service disruptions occur. In equipment failure factor analysis, etc., vehicle data is not limited according to purposes such as train status monitoring. For example, the user of the analysis tool refers to the vehicle data of the target train according to the purpose, and the factor analysis of the equipment failure is performed by investigating the relationship between the data.

On the other hand, with the recent Internet of Things (IoT), the amount of vehicle data to be analyzed is increasing. It is larger than the item. Generally, in factor analysis of equipment failure, etc., the relationship of vehicle data is investigated using an analysis tool. Users of analysis tools can investigate abnormal behavior in output values and operations by visualizing device outputs and device operating states that are relevant to their objectives. At this time, when the range of data to be analyzed is large and the number of vehicle data items ranges from 100 to 10,000 or more, finding and identifying data items may become a burden on the user.

Japanese Patent No. 6290777

An object of the present invention is to provide a train information management device capable of indicating more appropriate data items.

A train information management device according to the present embodiment acquires vehicle data from a vehicle data storage unit that stores vehicle data including vehicle operation information, and controls a train information display device to display the vehicle data. and includes a user input data receiving section, a user identification data receiving section, a user data processing section, and a recommendation information processing section. The user input data receiving unit receives user input data to be input to the train information display device for displaying vehicle data. The user identification data receiving unit receives user identification data identifying a user who uses the train information display device. The user data processing unit creates user data in which user input data and user identification data are associated. The recommendation information processing unit acquires structural data from a structural data storage unit that stores structural information about train components and structural data including correspondence relationships between vehicle data and structural information, and stores user data, structural data, and , based on the user input data being input, items of recommended vehicle data to be displayed on the train information display device next to the display vehicle data corresponding to the user input data being input are calculated.

The block diagram which shows the structure of the train information management apparatus by 1st Embodiment, and a train information display apparatus. The figure which shows an example of the display screen of a train information display apparatus. 4 is a block diagram showing the configuration of a recommendation information processing unit according to the first embodiment; FIG. 4 is a flow chart showing the operation of the user data processing unit according to the first embodiment; FIG. The figure which shows an example of user data. 4 is a flow chart showing the operation of the user display information calculation unit according to the first embodiment; FIG. The figure which shows an example of user display information. 4 is a flow chart showing the operation of a user recommendation information calculation unit according to the first embodiment; FIG. FIG. 4 is a flowchart showing the operation of updating user recommendation information of a user recommendation information calculation unit according to the first embodiment; The figure which shows an example of a user display ratio. The figure which shows an example of train structure data. The figure which shows an example of the hierarchical relationship of the train structure data shown in FIG. The figure which shows an example of structure name data. FIG. 4 is a flowchart of calculation of similar structure information using train structure data and structure name data in the user recommendation information calculation unit according to the first embodiment; FIG. 4 is a flowchart showing the operation of a user recommended item calculation unit according to the first embodiment; The block diagram which shows the structure of the train information management apparatus by 2nd Embodiment, and a train information display apparatus. The block diagram which shows the structure of the recommendation information processing part by 2nd Embodiment. FIG. 7 is a diagram showing an example of group recommendation information calculated for each group; The block diagram which shows the structure of the train information management apparatus by 3rd Embodiment, and a train information display apparatus. FIG. 11 is a block diagram showing the configuration of a recommendation information processing unit according to the third embodiment; The figure which shows an example of the screen which displayed the recommendation pattern of the recommendation pattern model.

Hereinafter, embodiments according to the present invention will be described with reference to the drawings. This embodiment does not limit the present invention. The drawings are schematic or conceptual, and the ratio of each part is not necessarily the same as the actual one. In the specification and drawings, the same reference numerals are given to the same elements as those described above with respect to the previous drawings, and detailed description thereof will be omitted as appropriate.

(First embodiment)
FIG. 1 is a block diagram showing configurations of a train information management device 100 and a train information display device 200 according to the first embodiment. The train information management device 100 acquires vehicle data from a vehicle data storage unit that stores vehicle data including vehicle operation information, and controls the train information display device 200 to display the vehicle data. The train information display device 200 displays, for example, vehicle data required to perform factor analysis of vehicle failure in response to user's operation (see FIG. 2).

The train information management device 100 includes a user data storage unit 101, a vehicle data storage unit 102, a structure data storage unit 103, a user recommendation information storage unit 104, a user input data reception unit 105, and a user identification data reception unit 106. , a user data processing unit 107 , a display data acquisition unit 108 , a display data transmission unit 109 , a recommendation information processing unit 110 , and a recommendation item transmission unit 111 .

The user data storage unit 101 stores user data. The user data includes the ID (Identification) of the user who uses the train information display device 200, the user's group, the user's affiliation, parameters relating to train information display, and the like. Parameters related to train information display are also called user input data, and include, for example, the data name of the X-axis, the data name of the Y-axis, and extraction conditions for target data. User data is updated by the user data processing unit 107 . Details of the user data will be described later with reference to FIG.

The vehicle data storage unit 102 stores vehicle data including vehicle operation information. Vehicle data is data obtained through a data collection device or the like mounted on a railroad vehicle, and includes, for example, notch information, travel speed data, and the like. Vehicle data is accumulated in the vehicle data storage unit 102 . The vehicle data storage unit 102 may be provided outside the train information management device 100, for example.

The structural data storage unit 103 stores structural information regarding train components, and structural data including correspondence between vehicle data and structural information. The structure data includes train structure data (structure information) and structure name data. The train structure data includes, for example, structure information such as the organization number of a train consisting of one car or two or more cars, the type of car, the car number, and on-board equipment. Also, the train structure data has a hierarchical structure. The structure name data is data indicating a correspondence relationship between vehicle data and structure information. The structure data storage unit 103 may be provided outside the train information management device 100, for example. Details of the structure data will be described later with reference to FIGS. 11 to 13. FIG.

The user recommendation information storage unit 104 stores user recommendation information. The user recommendation information is information indicating relationships between vehicle data items, as will be described later. Further, the user recommendation information includes, for example, user display ratio based on display frequency for each user and similar structure information based on train structure. User recommendation information is updated by the recommendation information processing unit 110 . Details of the user recommendation information (user display ratio) will be described later with reference to FIG.

The user input data receiving unit 105 receives user input data input to the train information display device 200 for displaying vehicle data. The user input data receiving unit 105 acquires, for example, parameters (user input data) used when using the train information display device 200 . The parameters include, for example, the data item name of the X-axis, the data item name of the Y-axis, the period of the target data, and the like.

The user identification data receiving unit 106 receives user identification data identifying the user who uses the train information display device 200 . The user identification data receiving unit 106 acquires information (user identification data) for identifying the user who used the train information display device 200, for example. User identification data includes, for example, user IDs and user groups.

The user data processing unit 107 creates user data in which user input data and user identification data are associated. The user data processing unit 107 receives user input data and user identification data from, for example, the user input data receiving unit 105 and the user identification data receiving unit 106, respectively, and adds date information and the like at the time of input to create user data. The user data processing unit 107 controls the user data storage unit 101 to accumulate and update user data. The user data processing unit 107 also sends user input data to the recommendation information processing unit 110 and the display data acquisition unit 108 . Hereinafter, the user input data sent from the user data processing unit 107 to the recommendation information processing unit 110 and the display data acquisition unit 108 is also referred to as "user input data being input" to distinguish it from user input data accumulated as user data. Called. The user input data being input is also user input data being selected on the screen of the train information display device 200, for example.

The display data acquisition unit 108 receives user input data (user input data being input) acquired by the user data processing unit 107 and acquires vehicle data corresponding to the user input data being input from the vehicle data storage unit 102 . In the following, vehicle data corresponding to user input data being entered is also referred to as "display vehicle data".

The display data transmission unit 109 transmits the display vehicle data acquired from the vehicle data storage unit 102 by the display data acquisition unit 108 to the train information display device 200 .

The recommendation information processing unit 110 acquires structure data from the structure data storage unit 103 . Also, the recommendation information processing unit 110 displays on the train information display device 200 next to the display vehicle data corresponding to the user input data being input, based on the user data, the structure data, and the user input data being input. Calculate items of recommended vehicle data. In addition, hereinafter, the “recommended vehicle data items” may also be referred to as “recommended items”. The recommendation information processing unit 110 creates, for example, user recommendation information indicating the degree of similarity between data items to be displayed from the user data acquired from the user data storage unit 101 and the structure data acquired from the structure data storage unit 103. and update the user recommendation information storage unit 104 . The recommendation information processing unit 110 also calculates the item name of the train information to be displayed next (hereinafter also referred to as a recommended item) from the user input data being input and the user recommendation information. This makes it possible to present more appropriate data items to the user. Details of the configuration of the recommendation information processing unit 110 will be described later with reference to FIG.

The recommended item transmission unit 111 transmits items of recommended vehicle data to the train information display device 200 . The recommended item transmission unit 111 receives, for example, the recommended items calculated by the recommendation information processing unit 110 and transmits them to the train information display device 200 . The recommended items are displayed on one screen of the train information display device 200 together with the displayed vehicle data, for example.

The train information display device 200 receives data from the train information management device 100 and displays it. The train information display device 200 is, for example, a personal computer, and may be installed so as to receive user operations related to maintenance and inspection. Note that the train information display device 200 may be a tablet terminal, a smartphone, or the like.

FIG. 2 is a diagram showing an example of a display screen of the train information display device 200. As shown in FIG. The upper left side shows an example of a screen for accepting input of user input data UD. The upper right side shows a display example of display vehicle data. The lower left side shows a display example of buttons for outputting the visualized result (display of vehicle data) and for downloading the visualized data. The lower right side shows a display example of recommended items R on the X-axis and the Y-axis. The recommended items include a recommended item R1 based on the user's display and a recommended item R2 based on the train structure.

As shown in FIG. 1, the train information display device 200 includes a display data receiving unit 201, a recommended item receiving unit 202, a data display unit 203, a user input data transmitting unit 204, a user identification data transmitting unit 205, It has

The display data reception unit 201 acquires the display vehicle data transmitted by the display data transmission unit 109 and inputs the data to the data display unit 203 .

The recommended item receiving unit 202 acquires the recommended items transmitted by the recommended item transmitting unit 111 and inputs them to the data display unit 203 .

The data display unit 203 receives the display vehicle data acquired from the display data reception unit 201 and the recommendation items acquired from the recommendation item reception unit 202, and displays the data on the screen (the upper right side and the lower side of FIG. 2, respectively). (see right).

The user input data transmission unit 204 transmits user input data input to the train information display device 200 by the user to the train information management device 100 . For example, when the user input data graph or data condition on the upper left side of FIG. 2 is selected, the user input data transmitting unit 204 transmits the user input data.

The user identification data transmission unit 205 transmits the user identification data of the user input to the train information display device 200 to the train information management device 100 . The user identification data transmission section 205 may transmit the user identification data almost simultaneously with the transmission of the user input data transmission section 204, for example.

FIG. 3 is a block diagram showing the configuration of the recommendation information processing section 110 according to the first embodiment. The recommendation information processing unit 110 has a user display information calculation unit 300 , a user display information storage unit 301 , a user recommendation information calculation unit 302 , and a user recommendation item calculation unit 303 .

The user display information calculation unit 300 acquires user data from the user data storage unit 101 and calculates user display information based on the user data. The user display information is information related to input by each user. Since the user data includes user identification data, the user display information calculation unit 300 calculates user display information for each user. Details of the user display information will be described later with reference to FIG.

The user display information storage unit 301 stores user display information. User display information is updated by the user display information calculation unit 300 .

A user recommendation information calculation unit 302 as a recommendation information calculation unit acquires structure data from the structure data storage unit 103 . Also, the user recommendation information calculation unit 302 calculates user recommendation information indicating relationships between items of vehicle data based on the structure data and the user data. The user recommendation information includes similar structure information and user display ratio. For example, the user recommendation information calculation unit 302 calculates similar structure information based on structure data and user input data. The similar structure information indicates similarity between vehicle data items based on the structure information. More specifically, the structural similarity information indicates similarity between items of vehicle data based on similarity of at least one character string of the component and the item of vehicle data. More specifically, the similar structure information includes at least one character string of the component and vehicle data items corresponding to the user input data, and at least one character string of the component and vehicle data items in the structure data. , similarity between vehicle data items. Also, for example, the user recommendation information calculation unit 302 calculates a user display ratio based on user data. The user display ratio indicates the strength of the relationship between vehicle data items based on display frequency or display time for each user. In the following, unless otherwise specified, the user display ratio is based on the display frequency. More specifically, the user recommended information calculation unit 302 acquires the user display information from the user display information calculation unit 300 or the user display information storage unit 301, and calculates the user display ratio based on the user display information.

A user recommendation item calculation unit 303 as a recommendation item calculation unit calculates items of recommended vehicle data based on user recommendation information and user input data being input. More specifically, the user recommended item calculation unit 303 calculates items of recommended vehicle data based on similar structure information and user input data being input. Also, the user recommended item calculation unit 303 calculates items of recommended vehicle data based on the user display ratio and the user input data being input.

Next, a procedure for creating user recommendation information will be described.

FIG. 4 is a flowchart showing operations of the user data processing unit 107 according to the first embodiment.

In step S<b>100 , the user data processing unit 107 acquires user input data input from the user input data receiving unit 105 . In step S<b>101 , the user data processing unit 107 acquires user identification data input from the user identification data receiving unit 106 . In step S102, the user data processing unit 107 combines the user input data and the user identification data to create user data. In step S103, the user data processing unit 107 writes the user data created in step S102 to the user data storage unit 101 to update the user data.

FIG. 5 is a diagram showing an example of user data. The first line in the figure shows examples of types of user data, and the second and subsequent lines show examples of user data. In the example shown in FIG. 5, time, user identification information, user input data, and display time are associated. The user ID and user group shown in the second and third columns are the user identification data obtained in step S102. However, the user identification data is not limited to this, and may be other user identification information (for example, department to which the user belongs, type of work, etc.) input in the system.

FIG. 6 is a flowchart showing the operation of the user display information calculator 300 according to the first embodiment.

In step S200, the user display information calculation unit 300 acquires user input data (user input data being input). In step S201, the user display information calculation unit 300 acquires user identification data. In step S202, the user display information calculation unit 300 acquires user data. In step S<b>203 , the user display information calculation unit 300 uses the user identification data to check whether the user display information of the corresponding user already exists in the user display information storage unit 301 . If user display information exists (Yes in S203), step S204 is executed. On the other hand, if the user display information does not exist (No in S203), step S205 is executed. In step S204, the user display information calculation unit 300 acquires the corresponding user display information, and then step S206 is executed. In step S205, the user display information calculation unit 300 newly creates user display information, and then step S206 is executed. In step S206, the user display information calculation unit 300 updates the user display information.

FIG. 7 is a diagram showing an example of user display information. The user display information is matrix information in which data item names of vehicle data are arranged in the row direction and the column direction, and each component is the display count of the data item name corresponding to the row and column. When the user displays the data item name in the i-th row (for example, "date") and displays the data item name in the j-th column (for example, "knitting speed"), the number of times of display is j The number of times of display of the column (583, which is the “date” row and the “knitting speed” column) is shown. The display count is counted by one when, for example, the X-axis item and the Y-axis item of the user input data are determined. User display information is stored as individual information for each user. Here, the user display information is not limited to the number of times the data item name is displayed, but may be display time (stay time on the system) or the like.

Also, the example shown in FIG. 7 is user display information on the X-axis. Therefore, the row direction indicates the items of the vehicle data on the X axis, and the column direction indicates the items of the vehicle data on the Y axis. Similarly, Y-axis user display information is also created. In this case, the row direction indicates the items of vehicle data on the Y axis, and the column direction indicates the items of vehicle data on the X axis. Note that the diagonal elements of the matrix are zero because the same items are not expected to be displayed.

The display count becomes a larger value as the relationship between the items is higher. For example, formation speed has a strong relationship with train power. Therefore, the number of times of display in the "knitting speed" row and the "1st car tensile force" column is a large value of 431 times. That is, the number of times that the Y-axis "car No. 1 tensile force" is input after the "knitting speed" of the X-axis is input is large. On the other hand, the knitting speed has a weak relationship with the temperature inside the car. Therefore, the number of times of display in the "set speed" row and the "temperature inside car No. 1" column is a small value of 0 times.

FIG. 8 is a flowchart showing the operation of the user recommendation information calculation unit 302 according to the first embodiment.

In step S300, the user recommendation information calculation unit 302 acquires the data item names of the X-axis and Y-axis based on the user input data. In step S301, the user recommendation information calculation unit 302 acquires structure data. In step S<b>302 , the user recommendation information calculation unit 302 confirms whether or not the user recommendation information of the corresponding user exists in the user recommendation information storage unit 104 . If the user recommendation information does not exist (No in S302), step S303 is executed. On the other hand, if user recommended information exists (Yes in S302), step S304 is executed. In step S303, the user recommendation information calculation unit 302 creates user recommendation information for the corresponding user. In step S304, the user recommendation information calculation unit 302 calculates and updates the user recommendation information of the corresponding user.

FIG. 9 is a flowchart showing the operation of updating the user recommendation information of the user recommendation information calculation unit 302 according to the first embodiment. FIG. 9 shows details of the operation of step S304 shown in FIG. Note that steps S400 and S403 indicate operations related to user recommended information based on user display. Steps S401, S402, S404, and S405 represent operations related to user recommendation information based on train structure. Also, the order is not limited to this, and for example, each update operation may be executed in parallel.

In step S400, the user recommendation information calculation unit 302 calculates the user display ratios of the X-axis and the Y-axis. Here, the user display ratio is an index representing the strength of the relationship between data items calculated based on the user display information.

ここで、式１のＮｄａｔａは、式２で表され、該当するユーザの全表示回数を示す。

式１で計算されるユーザ表示割合Ｐｄａｔａ_ｉｊは、該当するユーザに応じた車両データの項目間の関係性を表す。尚、式１の計算では、ユーザの項目の全表示回数に対する各項目の割合が計算されているが、全表示回数が大きくなった場合、全体に対する割合が極めて小さくなる可能性がある。その場合、例えば、対数関数を用いることでユーザ表示割合の計算を行うことが可能であり、式１に限られない。 FIG. 10 is a diagram showing an example of user display ratios. The table shown in FIG. 10 shows user display ratios calculated from the user display information of user 1 shown in FIG. Here, if Pdata _ij is the display information ratio of i row j column, data _ij is the display count of i row j column in the user display information, and Ndata is the number of vehicle data items, the user display ratio Pdata _ij is given by Equation 1 can be calculated with

Here, Ndata in Equation 1 is represented by Equation 2 and indicates the total number of times of display for the corresponding user.

The user display ratio Pdata _ij calculated by Equation 1 represents the relationship between items of vehicle data according to the corresponding user. In addition, in the calculation of Equation 1, the ratio of each item to the total display count of the user's items is calculated, but if the total display count increases, the ratio to the whole may become extremely small. In that case, for example, the user display ratio can be calculated by using a logarithmic function, and is not limited to Equation 1.

In step S401, the user-recommended information calculation unit 302 calculates X-axis similar structure information regarding the items on the X-axis input by the user. In step S402, the user recommendation information calculation unit 302 calculates Y-axis similar structure information regarding the Y-axis item input by the user. In steps S401 and S402, the user recommendation information calculation unit 302 calculates similar structure information using, for example, structure data and user input data in the user data. Note that user input data being input may be used to calculate similar structure information. Here, the structure data includes train structure data and structure name data as described above. In steps S403 to S405, the user recommendation information calculation unit 302 updates the user display ratio, the X-axis similar structure information, and the Y-axis similar structure information, which are recommended information. Details of calculation of similar structure information in steps S401 and S402 will be described later with reference to FIG.

FIG. 11 is a diagram showing an example of train structure data. Train structure data includes, for example, structure ID, structure name, structure depth and parent structure. The structure ID is, for example, information for identifying each structure name. The structure name is, for example, a structure name corresponding to each structure ID. Hierarchical depth is, for example, the depth of the structure corresponding to each structure ID. A parent structure is, for example, one shallow structure ID with each structure ID.

FIG. 12 is a diagram showing an example of the hierarchical relationship of the train structure data shown in FIG. 11. As shown in FIG. The train structure data shown in FIG. 11 has a hierarchical structure with five levels of depths 1-5. FIG. 11 shows that the structure name A40000 is identified by the parenthesized structure ID 10001 in the car system, which is the highest hierarchy. For example, in a device with a hierarchy of depth 5, there are two structure names VVVF (Variable Voltage Variable Frequency) 1 . However, the structure IDs of VVVF1 for car 1 and VVVF1 for car 3 are 50001 and 50052 respectively. By referring to this structure ID, each VVVF1 can be identified. "M car" indicates a motor car. "SIV1" indicates the power source of the accessory. "BCU1" indicates equipment related to the brake.

FIG. 13 is a diagram showing an example of structure name data. A data ID, a data name, a parent structure ID, a parent structure name, and the like are recorded in the structure name data. The structure name data is data that associates the train structure data and the vehicle data, as described above. For example, in VVVF1 of car No. 1 whose parent structure ID is 50001, a plurality of data are detected, such as car No. 1 tensile force command value, car No. 1 motor current value, and car No. 1 motor voltage value. That is, the structure name data specifies the vehicle data measured by each device using the data ID.

FIG. 14 shows a flowchart of calculation of similar structure information using train structure data and structure name data in the user recommendation information calculation unit 302 according to the first embodiment. The X-axis similar structure information and Y-axis similar structure information shown in steps 401 and S402 of FIG. 9 are similarly calculated. Steps S500 to S507 indicate calculation of the degree of similarity at the first stage using train structure data. Steps S508 to S513 show the calculation of the second stage similarity using the structure name data for the structure name with high similarity calculated in the first stage.

In step S500, the user recommendation information calculation unit 302 acquires the parent structure name of the user input item. For example, when the data name corresponding to the user input data being input is "No. 1 car tensile force command value" shown in FIG. 13, the user recommendation information calculation unit 302 acquires the parent structure name "VVVF1". In step S501, the user recommendation information calculation unit 302 initializes a similar structure name list that stores similar structure names. In step S502, the user recommendation information calculation unit 302 initializes a similar structure information list that stores the calculated similar structure information.

In step S503, the user recommendation information calculation unit 302 acquires the head structure name of the train structure data. In the example shown in FIG. 11, the head structure name "vehicle system" is acquired. In step S504, the user recommendation information calculation unit 302 calculates the degree of similarity between the parent structure name of the user input item and the acquired structure name. For example, the user recommendation information calculation unit 302 calculates the degree of similarity between "VVVF1" and "vehicle system". Here, the degree of similarity is a value indicating the distance between character strings. For this value, for example, an edit distance or the like is used. Note that other similarity calculation techniques may be used. In step S505, the user recommendation information calculation unit 302 adds the calculated similarity to the similarity structure name list.

In step S506, the user recommendation information calculation unit 302 determines whether all similarities have been calculated. If all calculations have not been completed (No in S506), step S507 is executed. On the other hand, if all calculations have been completed (Yes in S506), step S508 is executed. In step S507, the user recommendation information calculation unit 302 acquires the structure name next to the current structure name from the train structure data. In the example shown in FIG. 11, the user recommendation information calculation unit 302 acquires the structure name "A4000" next to the structure name "vehicle system". After that, step S504 is executed. Therefore, the similarity calculations in steps S504 and S505 are repeated for all structure names shown in FIG.

In step S508, the user-recommended information calculation unit 302 acquires the structure names with the top five similarities from the similar structure name list. For example, the user recommendation information calculation unit 302 acquires "VVVF1", which has the same structure name as the user input item, as the structure name with the highest degree of similarity. Here, the number of upper structure names to be acquired is not limited to five, and the number can be changed arbitrarily. In step S509, the user recommendation information calculation unit 302 acquires all data names having the acquired structure name as a parent structure. For example, as shown in FIG. 13, for VVVF1, the user recommendation information calculation unit 302 calculates "motor current value for car No. 1" and "motor voltage value for car No. 1" other than the user input items ("pulling force command value for car No. 1"). and "No. 3 car tensile force command value". In step S510, the user recommendation information calculation unit 302 calculates the degree of similarity between the user input item and the data name (“motor current value of car No. 1”). In step S511, the user recommendation information calculation unit 302 adds the calculated similarity to the similar structure information list.

In step S512, the user recommendation information calculation unit 302 determines whether all similarities have been calculated. If all calculations have not been completed (No in S512), step S513 is executed. On the other hand, if all calculations have been completed (Yes in S512), step S514 is executed. In step S513, the user recommendation information calculation unit 302 acquires the data name next to the current data name (“motor voltage value of car No. 1”) from the train structure data. Then step S510 is executed. Therefore, the similarity calculation in steps S510 and S511 is repeated for the data names in the top five structure names such as "VVVF1". In the example shown in FIG. 13, the data name with the highest degree of similarity to the user input item ("Tension force command value for car No. 1") is "Train force command value for car No. 3". "No. 3 car tensile force command value" is, for example, vehicle data that is highly likely to be displayed next by a user who performs failure factor analysis such as confirmation of differences between cars.

In step S514, the user recommendation information calculation unit 302 outputs a similar structure information list. The similar structure information list includes, for example, the degree of similarity between vehicle data. Since the structure names are narrowed down in the first stage extraction (S508) using the train structure data, the degree of similarity between vehicle data with relatively high similarity is calculated. That is, since the number of similarity calculations can be reduced, there is no need to perform calculations for all vehicle data.

Similar structure information is matrix information in which data item names of vehicle data are arranged in the row direction and the column direction, similar to the user display ratio shown in FIG. For example, the similarity between the item name of the user input data in the row direction and the item name of the vehicle data in the column direction extracted from the train structure data and the structure name data based on the user input data is calculated and updated. be.

Next, a procedure for creating recommended items will be described.

FIG. 15 is a flowchart showing the operation of the user recommended item calculation unit 303 according to the first embodiment. Note that steps S600, S601, S605, S606, S610, S611, S614, and S615 indicate calculation of recommended items based on user display. Steps S602, S603, S607, S608, S612, S613, S616, and S617 indicate calculation of recommended items based on train structure. Also, the order is not limited to this, and for example, each calculation may be executed in parallel.

In step S600, the user recommended item calculation unit 303 initializes the X-axis recommended display item list. In step S601, the user recommended item calculation unit 303 initializes the Y-axis recommended display item list. In step S602, the user recommended item calculation unit 303 initializes the X-axis recommended structure item list. In step S603, the user recommended item calculation unit 303 initializes the Y-axis recommended item structure list.

In step S604, the user-recommended item calculation unit 303 determines whether or not there is user-input data being input regarding the X-axis. If there is user input data being input (Yes in S604), steps S605 to S608 are executed. On the other hand, if there is no user input data being input (No in S604), step S609 is executed. In step S605, the user-recommended item calculation unit 303 acquires the top five items of the user display ratio of the X-axis to the user input data being input regarding the X-axis. Here, the number of top items to be acquired is not limited to five items, and the number can be changed arbitrarily. In step S606, the user-recommended item calculation unit 303 adds the top five items of the acquired user display ratio to the Y-axis recommended item display list. In step S607, the user-recommended item calculation unit 303 acquires the top five items of the X-axis similar structure information for the user input data being input regarding the X-axis. Here, the number of top items to be acquired is not limited to five items, and the number can be changed arbitrarily. In step S608, the user-recommended item calculation unit 303 adds the top five items of the X-axis similar structure information to the X-axis recommended structure item list.

In step S609, the user recommended item calculation unit 303 determines whether or not there is user input data being input regarding the Y axis. If there is user input data being input (Yes in S609), steps S610 to S613 are executed. On the other hand, if there is no user input data being input (No in S609), step S614 is executed. In step S610, the user-recommended item calculation unit 303 acquires the top five items of the user display ratio of the Y-axis to the user input data being input regarding the Y-axis. Here, the number of upper items is not limited to five items, and the number can be changed arbitrarily. In step S<b>611 , the user-recommended item calculation unit 303 adds the top five items of the acquired user display ratio to the X-axis recommended item display list. In step S612, the user-recommended item calculation unit 303 acquires the top five items of the Y-axis similar structure information for the user input data being input regarding the Y-axis. Here, the number of top items to be acquired is not limited to five items, and the number can be changed arbitrarily. In step S612, the user-recommended item calculation unit 303 adds the top five items of the Y-axis similar structure information to the Y-axis recommended structure item list.

In step S614, the user recommended item calculation unit 303 outputs an X-axis recommended display item list. In step S615, the user recommended item calculation unit 303 outputs a Y-axis recommended display item list. In step S616, the user recommended item calculation unit 303 outputs an X-axis recommended structure item list. In step S617, the user recommended item calculation unit 303 outputs a Y-axis recommended structure item list.

The calculated recommended items are displayed on the train information display device 200, as shown in the lower right part of FIG. In the example shown in FIG. 2, the recommended items include X-axis user display information, Y-axis user display information, X-axis recommended structure information, and Y-axis recommended structure information. As described above, the upper left side of FIG. 2 shows user input items (user input data UD), the upper right side shows the display result of the input items, and the lower right side shows recommended items R to the user. By referring to this recommended item R, the user can refer to items related to the displayed item without directly inputting the item name to the train information display device 200 . In the example shown in FIG. 2, a recommended item based on user display (Y-axis) and a recommended item based on train structure (X-axis) are shown for user input data "time" being input on the X-axis. Similarly, a recommended item (X-axis) based on the user display and a recommended item (Y-axis) based on the train structure are shown for the user input data "motor current value of car No. 1" being input for the Y-axis.

As described above, according to the first embodiment, the recommendation information processing unit 110 calculates recommended vehicle data based on user data, structure data, and user input data being input. This makes it possible to present more appropriate data items to the user.

Also, the user recommendation information calculation unit 302 calculates user recommendation information indicating relationships between items of vehicle data based on the structure data and the user data. For example, train condition monitoring requires certain predefined input parameters. On the other hand, when analysis does not require specific input parameters, for example, factor analysis of equipment failure, the user needs to select vehicle data to be displayed from a large amount of vehicle data such as 10,000 items or more. In the first embodiment, the user does not need to select target data from all vehicle data by considering the relationship between data. This makes it possible to reduce the burden on the user. For example, it is possible to refer to items related to each user for displayed items, or similar items in terms of train structure. Therefore, the user does not need to refer to all vehicle data, and can reduce the time required to find and identify the required data.

Also, when the recommendation item shown in FIG. 2 is selected, the corresponding vehicle data is visualized. In this case, the train information management device 100 calculates the recommended items again and causes the train information display device 200 to display them.

Note that updating of various data such as user data, user display ratio, and user recommendation information and display of recommended items are performed at the time when data items of user input data are selected. However, it is not limited to this, and may be performed at the timing of visualization of the graph.

(Second embodiment)
FIG. 16 is a block diagram showing configurations of a train information management device 100 and a train information display device 200 according to the second embodiment. FIG. 17 is a block diagram showing the configuration of the recommendation information processing section 110 according to the second embodiment.

In the second embodiment, the train information management device 100 further includes a group recommendation information storage section 112 (see FIG. 16). In the second embodiment, the recommendation information processing section 110 further has a group display information storage section 304 (see FIG. 17). Therefore, the second embodiment differs from the first embodiment in that recommendation information is displayed not only for each user but also for each group.

As shown in FIG. 16, the user data processing unit 107 identifies groups including at least one user based on the user identification data. The user data processing unit 107 classifies groups using, for example, user IDs, user groups, and the like. The user data processing unit 107 can define groups based on user ID patterns, multiple pieces of information, and the like. The user data processing unit 107 also creates group data in which user input data and groups are associated with each other. Group data may be stored in the user data storage unit 101, for example.

As shown in FIG. 17, the user display information calculator 300 calculates group display information based on group data. The group display information is the user display information in the first embodiment, which is created not for each user but for each group including a plurality of users. Accordingly, the user display information calculator 300 calculates group display information in the same manner as user display information.

A user recommendation information calculation unit 302 calculates group recommendation information (hereinafter also referred to as group display ratio) based on group data. The group display ratio indicates the strength of the relationship between vehicle data items based on the display frequency or display time for each group. More specifically, the user recommended information calculation unit 302 acquires group display information from the user display information calculation unit 300 or the user display information storage unit 301, and calculates the group display ratio based on the group display information. The group display ratio is created not for each user, but for each group including a plurality of users, unlike the user display ratio in the first embodiment. Therefore, the user recommendation information calculation unit 302 calculates the group display ratio in the same manner as the user display ratio.

FIG. 18 is a diagram showing an example of group recommendation information calculated for each group. In the example shown in FIG. 18 , different recommendation information (group display ratio) is shown for group 1 and group 2 .

As shown in FIG. 17, the user recommended item calculation unit 303 calculates items of recommended vehicle data based on the group display ratio and user input data being input. The user-recommended item calculation unit 303 may calculate recommended items using the group display ratio as in the case of using the user display ratio.

The group recommendation information storage unit 112 stores group recommendation information. The user recommendation information calculation unit 302 updates the group recommendation information.

The group display information storage unit 304 stores group display information. The group display information is updated by the user display information calculation unit 300. FIG.

Other configurations of the train information management device 100 according to the second embodiment are the same as the corresponding configurations of the train information management device 100 according to the first embodiment, so detailed description thereof will be omitted.

The user recommendation item calculation unit 303 calculates recommendation items for each group of users who perform inspections, groups of users who perform maintenance, and the like. As a result, the user-recommended item calculation unit 303 can show, for example, vehicle data displayed by a senior employee in the same group as a recommended item to a new employee. As a result, it is possible to reduce the burden of data selection for inexperienced users such as new employees.

In addition, by adding database information of vehicle maintenance records, inspection records, and repair records to the user identification information, it is possible to create a group for each purpose that the user has performed or intends to perform.

The train information management device 100 according to the second embodiment can obtain effects similar to those of the first embodiment.

(Third embodiment)
FIG. 19 is a block diagram showing configurations of a train information management device 100 and a train information display device 200 according to the third embodiment. Also, FIG. 20 is a block diagram showing the configuration of the recommendation information processing unit 110 according to the third embodiment.

In the third embodiment, the train information management device 100 includes a user purpose data reception unit 113, a user action data reception unit 114, a recommended pattern transmission unit 115, a recommended pattern model storage unit 116, and a display count reception unit 117. (See FIG. 19. In the third embodiment, the train information display device 200 includes a recommended pattern receiving unit 206, a user purpose data transmitting unit 207, a user action data transmitting unit 208, and a display count (See FIG. 19.) Further, in the third embodiment, the recommendation information processing unit 110 further includes a recommendation pattern model creation unit 305 and a recommendation pattern calculation unit 306 (see FIG. 19). 20.) Accordingly, the third embodiment differs from the first embodiment in that a recommended pattern is displayed as a method of displaying data for each purpose of the user.

As shown in FIG. 19 , the user input data receiving unit 105 receives graph patterns of vehicle data displayed on the train information display device 200 . A graph pattern is, for example, a part of information of user-input data relating to “graph (type of graph)” and “data conditions” such as item names of X-axis and Y-axis. That is, the user input data according to the third embodiment includes graph patterns of vehicle data displayed on the train information display device 200 in addition to data items on the X-axis and Y-axis. Also, the graph pattern is processed by the user data processing unit 107 so as to be included in the user data. Note that the graph pattern sent to the recommendation information processing unit 110 and the display data acquisition unit 108 is hereinafter also referred to as a “displayed graph pattern” to distinguish it from the graph pattern accumulated as user data.

The user purpose data receiving unit 113 receives user purpose data indicating the purpose of the user. The user purpose data is, for example, "failure factor analysis". The user purpose data is input by the user, for example, on the screen before graph visualization on the train information display device 200 . Also, the user object data is processed by the user data processing unit 107 so as to be included in the user data. The purpose of the user is not limited to "failure factor analysis", but may be, for example, equipment output confirmation, equipment operation trend confirmation, or data aggregation.

The user action data receiving unit 114 receives user action information for the vehicle data displayed on the train information display device 200 . Action information is, for example, "graph output". Graph output indicates that graph data is output on a computer and left as a file. For example, vehicle data useful for failure factor analysis may be verified in more detail not only by simple visualization but also by graph output and the like. In addition, after graph output, there is a possibility that other vehicle data will be visualized as failure factor analysis. Therefore, vehicle data for which graph output is performed is highly likely to be useful for failure factor analysis. Also, vehicle data for which graph output is performed is highly likely to be a segment of visualization. This is because the items that the user wants to see may change after the action information, such as analysis of brakes, etc., after visualization of the motor current. Also, the action information is processed by the user data processing unit 107 so as to be included in the user data. Note that the action information is not limited to "graph output", and may be, for example, saving a graph template, outputting a graph report, or downloading data. Also, the action information is processed by the user data processing unit 107 so as to be included in the user data.

As shown in FIG. 20, the recommended pattern model creation unit 305 creates, for each user purpose data, a first graph pattern without action information, a second graph pattern displayed after the first graph pattern and having action information, are associated as input data and output data, respectively, to create a recommendation pattern model. For example, the recommendation pattern model creation unit 305 creates a recommendation pattern model using user purpose data, action information, and graph patterns included in user data. The first graph pattern is a graph pattern visualized in the process up to the visualization of the second graph pattern useful for "failure factor analysis". The recommendation pattern model creation unit 305 creates a recommendation pattern model from, for example, user data including user purpose data and action information, and structure data.

The number-of-displays receiving unit 117 receives the number of continuous displays counted each time a graph pattern is displayed on the train information display device 200 . The number of consecutive displays is, for example, the number of times the user transitions the graph from the start of the analysis tool to the end of the analysis tool. Also, the number of consecutive displays is processed by the user data processing unit 107 so as to be included in the user data. In this case, the recommended pattern model creation unit 305 creates the recommended pattern model so that the difference obtained by subtracting the number of consecutive displays of the first graph pattern from the number of consecutive displays of the second graph pattern becomes one. For example, the recommended pattern model creation unit 305 creates the recommended pattern model so that the number of consecutive displays of the second graph pattern is equal to the number of consecutive displays of the first graph pattern by one. As a result, it is possible to recommend to the user a graph pattern that is highly likely to be useful for failure factor analysis next to the currently displayed graph pattern. That is, it is possible to improve the accuracy of the recommended pattern model.

The recommended pattern calculation unit 306 applies the graph pattern being displayed to the recommended pattern model, and calculates a recommended pattern to be displayed on the train information display device 200 after the graph pattern being displayed.

The recommended pattern model storage unit 116 stores recommended pattern models. The recommended pattern model is updated by the recommended pattern model creating unit 305 .

As shown in FIG. 19 , the recommended pattern transmission unit 115 transmits recommended patterns to the train information display device 200 .

The recommended pattern reception unit 206 acquires the recommended pattern transmitted by the recommended pattern transmission unit 115 and inputs it to the data display unit 203 .

The user purpose data transmission unit 207 transmits the inputted user purpose data to the train information management device 100 .

User action data transmission unit 208 transmits the input action information to train information management device 100 .

The number-of-displays transmission unit 209 transmits the number of consecutive displays to the train information management device 100 .

Other configurations of the train information management device 100 according to the third embodiment are the same as corresponding configurations of the train information management device 100 according to the first embodiment, so detailed description thereof will be omitted.

FIG. 21 is a diagram showing an example of a screen displaying recommended patterns of a recommended pattern model. The right side of FIG. 21 shows a plurality of recommended patterns for recommended actions (user's purpose). A indicates action information. OD indicates user object data. RP indicates a recommendation pattern.

In the example shown in FIG. 21, the recommended pattern calculation unit 306 applies the displayed graph pattern to the recommended pattern model and calculates recommended patterns 1 to 3 for the purpose of “failure factor analysis”. The recommended pattern includes information such as graph type, X-axis item, Y-axis item, and train structure, for example. This makes it possible to recommend and show graph patterns useful for the set purpose to the user. As a result, the time required to find and identify the required data can be reduced. Also, the recommended pattern may include a graph as shown in FIG. This can further reduce the user's data selection load. Note that the number of recommended patterns to be displayed is not limited to three, and may be any value.

Also, when the recommended pattern shown in FIG. 21 is selected, the corresponding graph pattern is visualized. In this case, the train information management device 100 calculates the recommended pattern again and causes the train information display device 200 to display it.

Note that selection of the user object data may be performed on the screen shown in the example of FIG. 21 .

The train information management device 100 according to the third embodiment can obtain effects similar to those of the first embodiment. Moreover, you may combine 2nd Embodiment with the train information management apparatus 100 by 3rd Embodiment.

At least part of the train information management device 100 according to this embodiment may be configured by hardware or may be configured by software. In the case of software configuration, a program that implements at least part of the functions of the train information management device 100 may be stored in a recording medium such as a flexible disk or CD-ROM, and read and executed by a computer. The recording medium is not limited to a detachable one such as a magnetic disk or an optical disk, and may be a fixed recording medium such as a hard disk device or memory. Also, a program that implements at least part of the functions of the train information management device 100 may be distributed via a communication line (including wireless communication) such as the Internet. Furthermore, the program may be encrypted, modulated, or compressed and distributed via a wired line or wireless line such as the Internet, or stored in a recording medium and distributed.

While several embodiments of the invention have been described, these embodiments have been presented by way of example and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, replacements, and modifications can be made without departing from the scope of the invention. These embodiments and their modifications are included in the scope and spirit of the invention, as well as the scope of the invention described in the claims and equivalents thereof.

100 train information management device, 101 user data storage unit, 102 vehicle data storage unit, 103 structure data storage unit, 105 user input data reception unit, 106 user identification data reception unit, 107 user data processing unit, 109 display data transmission unit, 110 recommendation information processing unit 111 recommendation item transmission unit 113 user purpose data reception unit 114 user action data reception unit 117 display count reception unit 200 train information display device 302 user recommendation information calculation unit 303 user recommendation item calculation section 305 recommendation pattern model creation section 306 recommendation pattern calculation section

Claims (9)

A train information management device that acquires the vehicle data from a vehicle data storage unit that stores vehicle data including vehicle operation information and controls a train information display device to display the vehicle data,
a user input data receiving unit that receives user input data to be input to the train information display device to display the vehicle data;
a user identification data receiving unit that receives user identification data that identifies a user who uses the train information display device;
a user data processing unit that creates user data in which the user input data and the user identification data are associated;
obtaining the structural data from a structural data storage unit that stores structural data including structural information about train components and a correspondence relationship between the vehicle data and the structural information, and obtaining the user data, the structural data, and a recommendation information processing unit for calculating items of recommended vehicle data to be displayed on the train information display device next to display vehicle data corresponding to the user input data being input, based on the user input data being input; A train information management device. The recommendation information processing unit
a recommendation information calculation unit that acquires the structure data from the structure data storage unit and calculates user recommendation information indicating relationships between items of the vehicle data based on the structure data and the user data;
2. The train information management device according to claim 1, further comprising a recommended item calculation unit that calculates items of said recommended vehicle data based on said user recommended information and said user input data being input. The recommendation information calculation unit calculates, based on the structure data and the user input data, similar structure information indicating similarity between items of the vehicle data based on the structure information,
3. The train information management device according to claim 2, wherein said recommended item calculation unit calculates items of said recommended vehicle data based on said similar structure information and said user input data being input. 4. The train information management device according to claim 3, wherein said similar structure information indicates similarity between items of said vehicle data based on similarity of at least one character string of said component and said item of said vehicle data. The recommendation information calculation unit calculates, based on the user data, a user display ratio indicating a strength of relationship between items of the vehicle data based on display frequency or display time for each user;
5. The train information according to any one of claims 2 to 4, wherein said recommended item calculation unit calculates items of said recommended vehicle data based on said user display ratio and said user input data being input. management device. The user data processing unit identifies a group including at least one user based on the user identification data, creates group data in which the user input data and the group are associated,
The recommendation information calculation unit calculates, based on the group data, a group display ratio indicating the strength of the relationship between the items of the vehicle data based on the display frequency or display time for each group;
6. The train information according to any one of claims 2 to 5, wherein said recommended item calculation unit calculates items of said recommended vehicle data based on said group display ratio and said user input data being input. management device. a display data transmission unit that transmits the display vehicle data acquired from the vehicle data storage unit to the train information display device;
7. The train information management device according to any one of claims 1 to 6, further comprising: a recommended item transmission unit that transmits the item of the recommended vehicle data to the train information display device. a user purpose data receiving unit that receives user purpose data indicating the purpose of the user;
a user action data receiving unit that receives action information of the user with respect to the vehicle data displayed on the train information display device;
The user input data receiving unit receives a graph pattern of the vehicle data displayed on the train information display device,
The recommendation information processing unit
A recommended pattern in which a first graph pattern without the action information and a second graph pattern displayed after the first graph pattern with the action information are associated as input data and output data, respectively, for each of the user purpose data a recommendation pattern model creation unit that creates a model;
2. A recommended pattern calculation unit that applies the graph pattern being displayed to the recommended pattern model and calculates a recommended pattern to be displayed on the train information display device after the graph pattern being displayed. The train information management device according to any one of claims 7 to 7. Further comprising a display count reception unit that receives the number of continuous displays counted each time the graph pattern is displayed on the train information display device,
3. The recommendation pattern model creation unit creates the recommendation pattern model such that a difference obtained by subtracting the number of continuous displays of the first graph pattern from the number of times of continuous display of the second graph pattern is 1. 9. The train information management device according to 8.