JP4537240B2 - Program, information storage medium and wheel wear estimation device - Google Patents

Description

  The present invention relates to a wheel wear estimation device and the like for estimating wear of a railway wheel due to traveling.

  The wheel of a railway vehicle wears its tread and changes its shape as the travel distance increases. Since wear on the wheel tread greatly affects the safe traveling of the railway vehicle, rolling is performed to adjust the tread shape of the worn wheel at a predetermined cycle. Further, although the wheel diameter decreases due to wear or rolling accompanying an increase in travel distance, it is necessary to replace the wheel at an appropriate time so that the wheel diameter does not fall below a predetermined use limit diameter.

  Currently, the determination of the wheel turning time, the amount of correction, and the replacement time (ie, life) is made by humans. In other words, the railway vehicle inspection (vehicle inspection) is performed mainly at a predetermined cycle according to the travel distance. At the time of this vehicle inspection, the inspector in the field determines the next vehicle from the tread shape of the wheel at the present time. Predict the tread shape at the time of inspection, and based on this prediction, determine whether or not to perform turning at the time of inspection, whether or not the amount of correction when performing rolling, and whether to replace the wheel. It was. That is, there was no method for quantitatively estimating wheel wear, turning time, replacement time, and the like. For this reason, the prior art document which approximates this application was not discovered.

  Further, at the time of vehicle inspection, a wheel dimension inspection is performed to measure various inspection item values such as wheel diameter, flange thickness, flange height, and flange angle. Among these inspection item values, the wheel diameter, flange thickness, and flange height can be predicted to some extent at the next vehicle inspection by primary interpolation or secondary interpolation based on measured values. However, it was impossible to formulate the relationship with the travel distance, and quantitative estimation was impossible.

  In this way, the judgment of the wheel turning time, the amount of correction, the replacement time, etc. was made by the inspector, so the judgment result may vary depending on the experience and skill level of the inspector. As a result, there is a possibility that unnecessary rolling or replacement of the wheels occurred, resulting in an increase in cost.

In view of the above circumstances, the present invention makes it possible to quantitatively estimate the worn tread shape of a railway wheel and quantitatively estimate the rolling time and life (replacement time) of the wheel using this estimation. The purpose is to .

The first invention for solving the above-described problems is
Computer
A plurality of tread shape measurement data (for example, tread shape measurement data 332 in FIG. 5) of railway wheels measured at different mileage points are converted into discrete data at predetermined intervals in the wheel thickness direction to obtain tread shape. Data conversion means (for example, the data conversion unit 210 in FIG. 5; step S1 in FIG. 14) for obtaining data (for example, tread shape data 334 in FIG. 5),
Estimated desired distance setting means for setting a plurality of estimated desired travel distances, which are desired travel distances when estimating the tread surface shape, at predetermined travel distance intervals (for example, the rolling time estimation unit 220 in FIG. 5; step S13 in FIG. 15) ),
Based on each of the plurality of tread shape data obtained by the data conversion means and each travel distance corresponding to each of the plurality of tread shape data, at each predetermined distance in the wheel thickness direction, By executing a regression calculation process on the tread shape data, tread shape estimation means for estimating tread shape data at each of the set plurality of estimated desired travel distances (for example,
Tread surface shape estimation unit 222 in FIG. 5; step S15 in FIG.
Based on the tread surface shape data of each of the plurality of estimated desired travel distances estimated by the tread shape estimation means, the inspection item value of the railway wheel at each of the plurality of estimated desired travel distances is calculated and calculated. A rolling time estimation means (for example, estimating a time at which the railway wheel is to be rolled by determining whether the inspection item value satisfies a specified wheel shape condition for determining whether or not the rolling is necessary) , The cutting time estimation unit 220 in FIG. 5; Steps S17 to S23 in FIG.
For example, a wheel wear estimation program 310 of FIG.

In addition, the seventh invention,
Data conversion means for obtaining tread shape data by converting each of a plurality of tread shape measurement data of railway wheels measured at different mileage points into discrete data at predetermined intervals in the wheel thickness direction;
Estimated desired distance setting means for setting a plurality of estimated desired travel distances that are desired travel distances when estimating the tread shape at predetermined travel distance intervals ;
Based on each of the plurality of tread shape data obtained by the data conversion means and each travel distance corresponding to each of the plurality of tread shape data, at each predetermined distance in the wheel thickness direction, A tread shape estimating means for estimating tread shape data at each of the set plurality of estimated desired travel distances by executing a regression calculation process on the tread shape data;
Based on the tread surface shape data of each of the plurality of estimated desired travel distances estimated by the tread shape estimation means, the inspection item value of the railway wheel at each of the plurality of estimated desired travel distances is calculated and calculated. A rolling time estimation means for estimating a time at which the railway wheel should be rolled by determining whether or not the inspection item value satisfies a specified wheel shape condition for determining whether or not the rolling is necessary,
Is a wheel wear estimation device (for example, the wheel wear estimation device 20 of FIGS. 1 and 5).

According to the first or seventh aspect of the present invention, each of the plurality of tread shape measurement data of railway wheels measured at different travel distances is converted into discrete data at predetermined intervals in the wheel thickness direction. On the basis of each tread shape data and each travel distance corresponding to each tread shape data, a regression calculation process is performed on the tread shape data at each travel distance at predetermined intervals in the wheel thickness direction. The tread surface shape data at the set estimated desired travel distance is estimated. That is, tread shape data at an arbitrary estimated desired travel distance is obtained from a plurality of tread shape measurement data. Therefore, it is possible to quantitatively estimate the worn tread shape of the railway wheel according to the travel distance.
Also, based on the estimated tread shape data, the inspection item value of the railway wheel is calculated, and whether or not the calculated inspection item value satisfies a prescribed wheel shape condition for determining whether or not the rolling is necessary Is determined, the time when the railway wheel should be rolled is estimated. Accordingly, it is possible to quantitatively estimate an appropriate turning time of the wheel from a plurality of tread shape data.

As a second invention, the program of the first invention is
The plurality of tread shape data used in the estimation calculation processing by the tread shape estimating means has a travel distance interval of less than 50,000 km of tread shape data with a travel distance of less than 50,000 km, and a travel distance of 50,000 km. The tread surface shape data may be data that satisfies the condition that the travel distance interval is 50,000 km or less.

  According to the second aspect, as the tread shape data, the tread shape data with a running distance of less than 50,000 km is less than 10,000 km, and the tread shape data with a running distance of more than 50,000 km is traveled. Data that satisfies the condition that the distance interval is 50,000 km or less is used for the estimation calculation. The flange angle may be estimated as the inspection item value from the estimated tread shape data. However, if the mileage is less than 50,000 km between the flange angle and the mileage, the flange against the change in mileage When the angle changes greatly and the travel distance is 50,000 km or more, there is a characteristic that the flange angle hardly changes with the change of the travel distance. For this reason, it is possible to estimate the tread shape data at a more accurate estimated desired travel distance by performing the estimation calculation using a plurality of tread shape data satisfying the above conditions.

As a third invention, the program of the first or second invention is
The estimated desired distance setting means sets the plurality of estimated desired distances so that the estimated desired distance is a distance at a future vehicle inspection time based on a distance at a predetermined vehicle inspection. Make the computer work,
The rolling time estimation means may be a program for causing the computer to function so as to estimate the time of vehicle inspection for rolling the railway wheels.

According to the third aspect of the invention, a plurality of estimated desired travel distances are set based on the travel distance at a predetermined vehicle inspection time, and the vehicle inspection time to be cut is estimated. Therefore, since the vehicle inspection time is estimated as the turning time, it is possible to estimate the turning time according to the actual operation.

As a fourth invention, the program of any one of the first to third inventions,
Based on the shape data at the time of entry of the railway wheel and the tread shape data calculated by the tread shape estimation means corresponding to the travel distance at the time when the rolling time estimation means is estimated to roll. A correction amount calculating means for calculating a correction amount at the time of cutting (for example, wheel life estimation unit 230 in FIG. 5; steps S37 to S41 in FIG. 16),
Based on the correction amount calculated by the correction amount calculation means, the time estimated by the cutting time estimation means, the diameter at the time of entry of the railway wheel, and the use limit diameter of the railway wheel, Life estimation means for estimating the life of the railway wheel (for example, wheel life estimation unit 230 in FIG. 5; steps S43 to S55 in FIG. 16),
As a program for causing the computer to function.

According to the fourth aspect of the invention, the correction amount at the time of rolling is calculated and calculated based on the shape data at the time of participation and the tread shape data calculated at the time when it is estimated that the rolling should be performed. The service life of the wheel is estimated on the basis of the amount of correction, the time when it is estimated that the milling should be performed, the diameter at the time of entry, and the use limit diameter. That is, the life of the wheel can be quantitatively estimated from a plurality of tread shape measurement data. Here, “when entering” means when the vehicle is not traveling, which is a new wheel, or immediately after rolling.

The fifth invention provides a program according to any one of the first to fourth inventions,
The rolling time estimation means calculates the wheel diameter, flange thickness, flange height and flange angle as the inspection item values, and all of the calculated wheel diameter, flange thickness, flange height and flange angle are calculated. Determining whether or not the prescribed wheel shape condition is satisfied, thereby causing the computer to function to estimate the time when the railway wheel should be rolled.
It is good also as a program for.

According to the fifth invention, the wheel diameter, flange thickness, flange height and flange angle are calculated as the inspection item values, and all of the calculated wheel diameter, flange thickness, flange height and flange angle are calculated. Determines whether the rolling wheels should be milled by determining whether or not the prescribed wheel shape condition is satisfied. For this reason, it is possible to quantitatively estimate an appropriate turning time of the wheel.

A sixth invention is a computer-readable information storage medium (for example, the storage unit 300 in FIG. 5 and the storage unit 700 in FIG. 20) that stores the program of any one of the first to fifth inventions.

Here, the “information storage medium” is a storage medium such as a hard disk, an MO, a CD-ROM, a DVD, a memory card, and an IC memory, which can read stored information. Therefore, according to the seventh invention, the same effect as any of the first to fifth inventions can be obtained by causing the computer to read the information stored in the information storage medium and executing the arithmetic processing. be able to.

According to the present invention, tread shape data at any desired estimated travel distance is estimated from a plurality of tread shape measurement data of railway wheels measured at different travel distances. In other words, it is possible to quantitatively estimate the worn tread shape of the railway wheel according to the travel distance. In addition, it is possible to quantitatively estimate the appropriate turning time of the wheel from a plurality of tread shape measurement data and quantitatively estimate the life of the wheel .

  Hereinafter, preferred embodiments of the present invention will be described with reference to the drawings.

[First Embodiment]
First, the first embodiment will be described. 1st Embodiment is embodiment about the wheel wear estimation apparatus which estimates the wear of the wheel by driving | running | working from the tread shape data of the measured railway wheel.

[overall structure]
FIG. 1 is an overall configuration diagram of the present embodiment. As shown in the figure, the present embodiment includes a shape measuring device 10 and a wheel wear estimating device 20, and both devices are connected by a predetermined cable K. Here, the cable K is a communication path through which data can be exchanged, such as a cable for parallel connection or a cable for USB (Universal Serial Bus) connection.

  The shape measuring device 10 measures the tread shape (cross-sectional shape in the thickness direction) of the wheel W for a railway vehicle that is a target object. The measured data is output as two-dimensional analog data.

  The wheel wear estimation device 20 is configured by a PC (Personal Computer) or the like, and estimates (calculates) wear of the wheel W based on the tread surface shape measurement data of the wheel W measured by the shape measurement device 10. Specifically, tread shape data of the wheel W at an arbitrary travel distance is calculated based on a plurality of tread shape measurement data having different travel distances at the time of measurement, and the wheel W is rotated using the calculated tread shape data. Calculate (estimate) the time to cut (turning time) and the life (replacement time).

  That is, first, as shown in FIG. 2, each of a plurality of tread shape measurement data 332 having different travel distances during measurement, which is analog data, is converted into tread shape data 334 that is digital data (discrete data). In the figure, tread surface shape measurement data 332A, 332B,..., Whose travel distances during measurement are A1, A2,... Are converted into tread shape data 334A, 334B,.

  Details of the data conversion will be described. FIG. 3A is an example of tread surface shape data measured by the shape measuring apparatus 10. However, the X direction is the wheel thickness direction, and the Y direction is the height direction. The wheel wear estimation device 20 uses the tread shape measurement data as the data interval in the X direction for the data portion in the range of X = 4.1 to 120.0 [mm] as shown in FIG. Are converted into digital data at predetermined equal intervals. FIG. 5B shows a case where the data interval in the X direction is converted into data with an equal interval of 0.1 [mm] for a part of the tread shape measurement data shown in FIG.

  Here, the measurement data by the shape measuring apparatus 10 is analog data, but the same applies to the case where it is given as digital data. That is, a predetermined interpolation process is performed on the digital data, and the digital data may be converted into digital data having an equal interval of 0.1 [mm].

  Then, the wheel wear estimation device 20 estimates (calculates) tread shape data at an arbitrary travel distance using tread shape data which is digital data after conversion. FIG. 4 is a diagram illustrating estimation of tread shape data. The wheel wear estimation device 20 performs regression calculation as an estimation calculation based on the travel distance for a plurality of tread shape data having different travel distances, thereby obtaining tread shape data at an arbitrary travel distance (estimated desired travel distance). presume.

  That is, for each X value 22a, the Y value at the estimated desired travel distance 22c is calculated by performing a regression calculation on the Y value at each travel distance 22b. In the figure, the regression calculation is performed on the tread surface shape data 334 when the travel distance 22a is “0”, “143,000 km”..., And the estimated desired travel distance 22c is “180,000 km”. The case where tread shape data is estimated is shown. Here, the tread shape data with a travel distance of “0” is tread shape data of the wheel at the time of participation. “At the time of participation” means the time of non-travel immediately after replacement with the wheel or immediately after the rolling.

  Here, it is desirable that the plurality of tread shape data used for estimating the tread shape satisfy the following conditions. That is, for the tread shape data with a measured travel distance of less than 50,000 km, the measured travel distance interval was less than 10,000 km, and for the tread shape data with a travel distance of more than 50,000 km The travel distance is less than 50,000 km.

  This is based on the relationship between the flange angle and the travel distance. That is, between the flange angle and the travel distance, when the travel distance is less than 50,000 km, the flange angle changes greatly with respect to the change of the travel distance, and when the travel distance is more than 50,000 km, The flange angle hardly changes with the travel distance. Therefore, by estimating the tread shape using the tread shape data that satisfies the above conditions, the inspection item values such as wheel diameter, flange thickness, flange height, and flange angle are accurately estimated from the estimated tread shape data. It becomes possible to do.

[Wheel wear estimation device]
FIG. 5 is a block diagram of the wheel wear estimation device 20. As shown in the figure, the wheel wear estimation apparatus 20 includes a communication unit 120, an input unit 140, a processing unit 200, a storage unit 300, and an output unit 160.

  The communication unit 120 performs data communication with an external device such as the shape measuring device 10 via the cable K. In particular, in this embodiment, the measured shape data of the wheel W is taken from the shape measuring device 10. The captured shape data is stored in the storage unit 300 as tread surface shape measurement data 332 in association with the travel distance at the time of measurement of the data. The communication unit 120 is realized by an interface board for external connection.

  The input unit 140 receives a user (user) operation input to the wheel wear estimation device 20 and outputs operation data to the processing unit 200. The input unit 140 is realized by, for example, a keyboard, a mouse, a button switch, a touch panel, various sensors, a microphone, and the like.

  The processing unit 200 performs overall control of the wheel wear estimation device 20. The processing unit 200 is realized by an arithmetic device such as a CPU or a storage device such as an IC memory. The processing unit 200 includes a data conversion unit 210, a rolling time estimation unit 220, and a wheel life estimation unit 230, and estimates wheel wear according to programs and data read from the storage unit 300. Execute the process.

  The data converter 210 converts the tread shape measurement data 332 into digital data whose data interval in the X direction is a predetermined interval (for example, 0.1 [mm]). The converted data is stored in the storage unit 300 as tread surface shape data 334. Specifically, as described with reference to FIG. 4, for example, the data portion in the range where the X value is x = 4.0 to 120.0 [mm] in the tread shape measurement data 332 is the X direction. Is converted into digital data having a data interval of 0.1 [mm], and the tread surface shape data 334 at the travel distance is obtained.

  The rolling time estimation unit 220 includes a tread shape estimation unit 222 and an inspection item value estimation unit 224, and estimates (calculates) a time (rolling time) when the wheel should be rolled based on the tread shape data 334. .

  FIG. 6 is a diagram for explaining the estimation of the milling time by the milling time estimation unit 220. The measurement of the tread shape of the wheel is performed, for example, at a predetermined vehicle inspection such as an alternating inspection. Therefore, in this embodiment, the milling time estimation unit 220 calculates (estimates) the tread shape data at the time of each vehicle inspection, and the calculated tread shape data of the wheels satisfying the predetermined inspection regulations. By determining whether or not the shape condition (specified wheel shape condition) is satisfied, the rolling time of the wheel is estimated. That is, for each vehicle inspection, the satisfaction / non-satisfaction of the condition is determined based on the calculated tread shape data, and the vehicle inspection time immediately before the vehicle inspection first determined as “unsatisfied” is the “turning time”. And

  In the figure, the tread shape is measured at the first and second vehicle inspections counted from the time of entry, and the tread shape data is estimated for each subsequent vehicle inspection. In the third to n-th vehicle inspections, all are determined to be “satisfied”, and in the next (n + 1) th vehicle inspection, it is determined to be “unsatisfied”. Therefore, the n-th vehicle inspection time is estimated as the “turning time”.

The tread shape estimation unit 222 calculates the tread shape data of the wheels at the time of each wheel inspection based on the tread shape data 334. When the travel distance interval of time each vehicle inspection and constant distance l, the travel distance L _i at the vehicle inspection time of i-th is "i × l". Therefore, tread shape data at the travel distance L _i is calculated based on the tread shape data 334 as tread shape data at the i-th vehicle inspection. The calculated tread shape data is stored in the storage unit 300 as tread shape estimation data (A) 336.

  The inspection item value estimation unit 224 calculates a wheel diameter, a flange thickness, a flange height, and a flange angle as inspection item values based on the tread shape estimation data (A) 336 calculated by the tread shape estimation unit 222.

FIG. 7 is an explanatory diagram of a method of calculating each inspection item value, and shows tread shape data in which the X direction is the wheel thickness direction and the Y direction is the height direction. Further, the position of the back surface of the wheel is x = 0, and the position in the Y direction of x = 65 [mm] is y = 0. The wheel diameter is a value obtained by subtracting a value twice as much as the tread wear amount from the wheel diameter (design value) at the time of participation, as shown in the equation (1).
Wheel diameter = Wheel diameter at entry-2 x Tread wear amount. (1)
Here, the amount of tread wear is the difference between the y value at x = 65 [mm] and the y value at x = 65 [mm] in the tread shape data at the time of participation indicated by a one-dot chain line in the figure. Incidentally, the tread shape data at the time of participation is stored in design wheel data 322 described later.

The flange thickness is an x value at y = −10 [mm]. The flange height is the absolute value of the difference between the y value at x = 65 [mm] and the y value at the flange top, that is, the minimum value of the y value. The flange angle is converted into equidistant data in which the data interval in the Y direction is 0.1 [mm] by performing an interpolation process in the range of y = −18 to −12 [mm]. The average value of the flange angle at the position. The flange height may be calculated according to the calculation formula shown in the following formula (2).
Flange height = Flange height at entry + Tread wear amount (2)

  Each inspection item value calculated by the inspection item value estimation unit 224 is stored in the estimated inspection item value data 338. FIG. 8 shows an example of the data configuration of the estimated inspection item value data 338. According to the figure, the estimated inspection item value data 338 stores an estimated value 338b and a determination result 338c in association with each inspection item 338a. As the inspection item 338a, a wheel diameter, a flange thickness, a flange height, and a flange angle are set.

  The estimated value 338b stores a value calculated by the inspection item value estimating unit 224. The determination result 338c is a determination result of whether or not the corresponding estimated value 338b satisfies a specified value that is a wheel shape condition. If it satisfies, “◯” is stored, and if not satisfied, “×” is stored.

  Here, the tread surface shape estimation unit 222 determines whether or not each inspection item value satisfies a specified value. Also, the prescribed values for each inspection item value are stored in the wheel inspection prescribed data 324. FIG. 9 shows an example of the data configuration of the wheel inspection regulation data 324. According to the figure, the wheel inspection regulation data 324 stores a regulation value 324b in association with each inspection item 324a. As the inspection item 324a, a wheel diameter, a flange thickness, a flange height, and a flange angle are set.

  The rolling time estimation unit 220 sets the rolling candidate times in order from the time of the next vehicle inspection at the time of the vehicle inspection in which the measurement of the tread surface shape of the wheel is finally performed. Whether or not the inspection item value calculated by the inspection item value estimation unit 224 satisfies the specified value based on the tread shape estimation data (A) 336 calculated by the tread shape estimation unit 222 for the milling candidate time. And whether the wheel shape condition is satisfied or not is determined. That is, if all the inspection item values satisfy the specified value, it is determined as “satisfactory”, and if any one of the inspection item values is not satisfied, it is determined as “unsatisfied”. As a result, the time of vehicle inspection immediately before the turning candidate time determined as “unsatisfied” first is set as the turning time.

  The wheel life estimation unit 230 calculates the life of the wheel (time to be replaced. Wheel replacement time) based on the cutting time calculated by the cutting time estimation unit 220.

  FIG. 10 is a diagram for explaining a wheel life estimation method by the wheel life estimation unit 230. It is assumed that the wheel life estimation unit 230 sets the travel distance from the time of entry to the turning time estimated by the rolling time estimation unit 220 as the rolling travel distance, and has performed rolling at this rolling travel distance interval from the time of participation. In this case, the service life of the wheel is estimated (calculated).

  Specifically, first, tread shape data at the time of initial rotational cutting is calculated. That is, the tread shape data at the rolling travel distance is calculated based on the tread shape data 334. Then, a correction amount at the initial rotational cutting time is calculated from the calculated tread shape data. Here, the calculated tread shape data at the time of the first rotational cutting is stored in the storage unit 300 as tread shape estimation data (B) 342.

  The correction amount is calculated as follows. That is, first, as shown in FIG. 7, the tread wear amount is calculated from the tread shape estimation data (B) 342 and the tread shape data at the time of participation. Here, the tread shape data at the time of participation is tread shape data at the time of design, and is stored in the design wheel data 322 as tread shape design data. In FIG. 11, an example of a data structure of the design wheel data 322 is shown. According to the figure, the design wheel data 322 includes a tread shape design data 322a and a design value table 322b.

  The tread shape design data 322a is data in which at least a value in the X direction (x value) that is the thickness direction of the wheel is in a range of, for example, x = 4.1 to 120.0 [mm]. The data interval in the direction is stored in the form of digital data having an equal interval of, for example, 0.1 [mm]. The design value table 322b stores a design value 322b-2 in association with each inspection item 322b-1. As the inspection item 322b-1, a wheel diameter, a flange thickness, a flange height, and a flange angle are set.

  Further, as shown in FIG. 7, the wheel life estimation unit 230 calculates the maximum vertical wear amount (maximum vertical wear amount) from the tread shape estimation data (B) 342 and the tread shape design data 322a. That is, the difference between the y value of the tread shape data 334 and the y value of the tread shape design data 322a is calculated as the vertical wear amount for every x value set as data points, for example, at intervals of 0.1 [mm]. FIG. 12 is a graph showing an example of the calculated vertical wear amount. The maximum value of the vertical wear amount is defined as the maximum vertical wear amount.

Next, the correction amount at the time of the first rotational cutting is calculated according to the calculation formula shown in the following formula (3). However, the amount of correction calculated here is equivalent to the wheel radius.
Correction amount = Maximum vertical wear amount-Tread wear amount (3)

Subsequently, the wheel life estimation unit 230 calculates the wheel diameter before turning at the time of initial turning according to the calculation formula shown in the following formula (4). However, the wheel diameter at the time of entry shall be the wheel diameter when not traveling, which is a new wheel, or immediately after rolling.
Wheel diameter before rolling = Wheel diameter at entry-2 x Tread wear amount (4)

  Then, whether or not the wheel can be used is determined based on whether or not the calculated pre-rolling wheel diameter satisfies a predetermined value that is a predetermined use limit diameter. Here, the specified value of the wheel diameter is stored in the wheel inspection specification data 324. That is, in the wheel inspection regulation data 324, the regulation value 324b corresponds to the inspection item 324a “wheel diameter”.

If the wheel diameter before rolling satisfies the specified value, the wheel diameter after rolling (wheel diameter immediately after rolling) at the time of initial rotary cutting is calculated according to the calculation formula shown in the following formula (5).
Wheel diameter immediately after rolling = wheel diameter before rolling-2 x grinding amount (5)

  And the wheel life estimation part 230 is the said wheel according to whether the calculated wheel diameter immediately after rolling satisfy | fills the regulation value which is a predetermined use limit diameter similarly to the case of the wheel diameter before rolling mentioned above. Judge whether or not to use.

  If the wheel diameter immediately after the rolling satisfies the specified value, then the rolling time is set in order at the rolling travel distance interval from the first rotational cutting. Then, for each rolling time, the wheel diameter before rolling is calculated according to the equation (4), it is determined whether or not the calculated wheel diameter before rolling satisfies the specified value, and the rolling diameter is calculated according to the equation (5). By calculating the wheel diameter immediately after cutting and determining whether or not the calculated wheel diameter immediately after rolling satisfies a specified value, it is determined whether or not the wheel can be used during the rolling time. As a result, the rolling time immediately before the rolling time determined to be “unusable” first is defined as the life of the wheel.

  In FIG. 10, “usable” is determined at the m-th rolling time counted from the time of entry, and “unusable” is determined for the first time at the next (m + 1) th rolling time. Therefore, the m-th cutting time is estimated as “life”. Further, if the rolling travel distance is k, the cumulative travel distance until the end of life is “k × m”.

  Here, each value calculated by the wheel life estimation unit 230 is stored in the life estimation data 344. In FIG. 13, an example of a data structure of the lifetime estimation data 344 is shown. According to the figure, the life estimation data 344 includes each rolling time data 345 and life estimation result data 346.

  Each rolling data 345 includes a rolling timing 345a, a rolling travel distance 345b, a tread wear amount 345c, a maximum vertical wear amount 345d, a cutting amount 345e, a wheel diameter 345f at the time of entry, a rolling The front wheel diameter 345g and the wheel diameter 345h immediately after rolling are stored. Among these, the rolling time 345a, the rolling travel distance 345b, the tread wear amount 345c, the maximum vertical wear amount 345d and the correction amount 345e are updated at the time of estimation at the first rotational cutting, and the wheel diameter 345f at the time of entry The wheel diameter before rolling 345 g and the wheel diameter 345 h immediately after rolling are updated for each estimation at the time of each rolling.

  The life estimation result data 346 stores a wheel diameter 346b immediately after rolling, a determination result 346c, and an accumulated travel distance 346d in association with each rolling frequency 346a.

  The storage unit 300 stores various programs and data for causing the processing unit 200 to control the wheel wear estimation device 20 in an integrated manner. Specifically, a wheel wear estimation program 310 is stored as a program, and tread shape measurement data 332, tread shape data 334, tread shape estimation data (A) 336, estimated inspection item value data 338, as data, Tread surface shape estimation data (B) 342, life estimation data 344, design wheel data 322, and wheel inspection regulation data 324 are stored. The storage unit 300 is realized by, for example, a hard disk, ROM, RAM, MO, or the like.

  The output unit 160 outputs the processing result of the processing unit 200, and is realized by a display device such as a CRT, LCD, or ELD, a sound output device such as a speaker, a printing device such as a printer, or the like.

[Process flow]
FIG. 14 is a flowchart for explaining the flow of the wheel wear estimation process in the present embodiment. This process is realized by the processing unit 200 executing a process according to the wheel wear estimation program 310. According to the figure, first, the data conversion unit 210 converts the tread shape measurement data 332 into tread shape data 334 which is digital data whose data interval in the X direction is a predetermined interval (for example, 0.1 [mm]). (Step S1). Next, the milling time estimation unit 220 performs a milling period estimation process to estimate the milling time (step S3).

  FIG. 15 is a flowchart for explaining the flow of the milling time estimation process. According to the figure, the rolling time estimation unit 220 first sets the next vehicle inspection time at the time of the vehicle inspection in which the wheel tread shape was measured last as the cutting candidate time (step S11). Next, the travel distance from the entry time to the milling candidate time is set as the estimated travel distance (step S13), and the tread shape estimation unit 222 performs a regression operation on the tread shape data 334 to estimate the tread shape at the estimated travel distance. Data (A) 336 is calculated (step S15).

  Subsequently, the inspection item value estimation unit 224 calculates each inspection item value such as a wheel diameter, a flange thickness, a flange height, and a flange angle based on the calculated tread shape estimation data (A) 336 (step S17). ). Then, the milling time estimation unit 220 refers to the wheel prescribed inspection data 324 to determine whether or not each calculated inspection item value satisfies the prescribed value. If all the inspection item values satisfy the specified values (step S19: YES), the wheel shape condition at the current turning candidate time is determined to be “satisfactory”, and the turning candidate time is changed at the next vehicle inspection. (Step S21), the process returns to Step S13, and the same process is executed again.

  On the other hand, if even one item does not satisfy the specified value among the calculated inspection item values (step S19: NO), the wheel shape condition at the cutting candidate time is determined to be “unsatisfied”, and this cutting candidate time is determined. The vehicle inspection time immediately before is set as the cutting time (step S23). Then, the milling time estimation process ends, and the process returns to step S5 in FIG.

  In FIG. 14, when the milling time estimation process ends, the wheel life estimation unit 230 performs the wheel life estimation process to estimate the wheel life (step S5).

  FIG. 16 is a flowchart for explaining the flow of the wheel life estimation process. According to the figure, the wheel life estimation unit 230 first sets the number of rolling j as “1” and the cumulative travel distance as “0” as an initial setting (step S31). Next, the wheel diameter at the time of participation is set (step S32). Subsequently, the travel distance from the time of entry to the time of the first rotational cutting calculated by the rolling time calculation process is set as the rolling travel distance (step S33), and regression operation is performed on the tread shape data 334, and this rolling travel distance is calculated. Tread surface shape estimation data (B) 342 is calculated (step S35).

  Subsequently, the wheel life estimation unit 230 refers to the tread shape design data 322a and calculates the tread wear amount from the calculated tread shape estimation data (B) 342 (step S37) and the maximum vertical wear amount (step S37). The maximum vertical wear amount is calculated (step S39). Then, the correction amount is calculated by subtracting the tread wear amount from the calculated maximum vertical wear amount (step S41).

  Thereafter, the wheel life estimation unit 230 calculates a wheel diameter before turning by subtracting a value twice the tread wear amount from a preset wheel diameter at the time of participation (step S43). Then, with reference to the wheel inspection regulation data 324, it is determined whether or not the calculated wheel diameter before rolling satisfies a prescribed value. If not satisfied (step S44: NO), the (j-1) th rolling operation is regarded as the life of the wheel (step 55), and the life estimation process is terminated.

If the wheel diameter before milling satisfies the specified value (step S44: YES), the wheel life estimation unit 230 subtracts a value twice the grinding amount from the wheel diameter before milling to obtain the wheel diameter just after milling. Calculate (step S45). Then, with reference to the wheel inspection regulation data 324, it is determined whether or not the calculated wheel diameter immediately after rolling satisfies a prescribed value. If satisfied (step S49: YES), the rolling travel distance is added to the cumulative travel distance (step S47), the number of times of rolling is updated to “1” (step S51), and the wheel diameter immediately after the rolling Is reset to the wheel diameter at the time of participation (step S53), the process returns to step S43, and the same processing is repeated. On the other hand, if the wheel diameter does not satisfy the specified value immediately after the rolling (step S49: NO), the (j-1) th rolling is defined as the life of the wheel. And this lifetime estimation process is complete | finished.
Then, in FIG. 14, when the wheel life estimation process ends, the wheel wear estimation process ends.

[Action / Effect]
As described above, according to the first embodiment, the wheel wear estimation apparatus 20 uses a predetermined data interval in the X direction, which is the wheel thickness direction, for each of the plurality of tread surface shape measurement data 332 of the wheels W having different travel distances at the time of measurement. Are converted into tread surface shape data 334 having an equal interval (for example, 0.1 [mm]), and wear of the wheel W is estimated using a plurality of tread surface shape data 334 after conversion.

  That is, the milling time estimation unit 220 calculates the tread shape estimation data (A) 336 at the time of each vehicle inspection such as an alternating inspection performed at a predetermined travel distance interval based on the tread shape data 334, The rolling time of the wheel is estimated (calculated) based on whether or not each inspection item value calculated from the tread surface shape estimation data (A) 336 satisfies a specified value specified by the wheel inspection specified data 324. Further, the wheel life estimation unit 230 calculates a correction amount at the cutting time calculated by the cutting time estimation unit 220, and based on this correction amount, at a travel distance interval to the cutting time. Calculate the wheel diameter before rolling and the wheel diameter immediately after rolling at the time of each rolling when the rolling is performed, and the calculated wheel diameter before rolling and the wheel diameter immediately after rolling are defined in the wheel inspection regulation data 324. The life of the wheel W is calculated by determining whether or not the specified value is satisfied. As described above, the worn tread shape of the railway wheel can be quantitatively estimated, and the rolling time and life (replacement time) of the wheel can be quantitatively estimated.

[ Reference example ]
Next, a reference example will be described. This reference example is a form example of the flange angle estimation device that estimates the relationship between the flange angle and the travel distance from the measured value of the flange angle.

[Relationship between mileage and flange angle]
FIG. 17 is a diagram in which measured values of the flange angle at a certain travel distance are plotted. However, the horizontal axis is the travel distance, and the vertical axis is the measured value of the flange angle. Also, since the manner of wear of the wheels used in the vehicle differs depending on the type of vehicle, here, the flange angle measured for a wheel used in a specific railway vehicle (but not necessarily the same wheel) Only the value of is targeted.

  As shown in the figure, between the travel distance and the flange angle, the flange angle greatly changes (increases) with respect to the change of the travel distance until the travel distance is up to 50,000 km. If it exceeds 50,000 km, the flange angle hardly changes with changes in travel distance. Furthermore, since the way of wear differs depending on the type of vehicle, the change in the flange angle after the mileage of 50,000 km or more is (a) almost constant, (b) slightly increased, (c) slightly decreased. It turns out that there are three patterns. In the figure, (c) corresponds to the case of a slight decrease.

Then, by analyzing the accumulated measurement values of many flange angles, it was found that the following expression (6) is appropriate as a relational expression between the travel distance X and the flange angle Y.
Y = A × tanh (B × X) + C × X + D (6)
However, A, B, C, and D are constants.

  FIG. 18 is a diagram illustrating an example of the curve of Expression (6). However, the horizontal axis is X and the vertical axis is Y. As shown in the figure, in the left part of the figure where the X value is less than the predetermined value, the Y value changes greatly with respect to the change of the X value, and the curve of the equation (6) shows that the X value is greater than or equal to the predetermined value. The middle right part has a characteristic that the change in the Y value is small with respect to the change in the X value. That is, the characteristic is the same as the relationship between the travel distance and the flange angle described above. The slope of the left part of the curve is mainly determined by the values of constants A and B, and the slope of the right part is mainly determined by the value of constant C. Then, depending on the value of the constant C, the slope of the right part is any one of (a) 0, (b) positive, and (c) negative.

  Accordingly, by appropriately setting the constants A, B, C, and D according to the relationship between the accumulated measured value of the flange angle and the travel distance, the relationship between the travel distance and the flange angle can be expressed by Equation (6). It can be formulated. The constant D is a Y value when X = 0, that is, a design value of the flange angle. In the equation (5), the first term mainly represents the characteristics of the portion where the travel distance X is 50,000 km or less, and the second term represents the characteristics of the portion where the travel distance X is 50,000 km or more. The third term (constant term) is a design value of the flange angle.

  FIG. 19 is a diagram showing a comparison result between the relational expression between the travel distance X and the flange angle Y given by the equation (6) and the measured value of the accumulated flange angle. However, the horizontal axis is the travel distance X, and the vertical axis is the flange angle Y. Further, in the equation (6), a curve of a relational expression in which A = 5.3, B = 1.8, C = 60, and D = 65 is shown. As shown in the figure, the curve of the relational expression expressed by the equation (6) and the measured value of the flange angle are almost the same, and it can be seen that this relational expression is appropriate.

[Flange angle estimation device]
FIG. 20 is a block configuration diagram of the flange angle estimation device 30 in the present reference example . According to the figure, the flange angle estimation device 30 includes an input unit 520, a processing unit 600, a storage unit 700, and an output unit 540.

  The input unit 520 accepts a user (user) operation input to the flange angle estimation device 30 and outputs operation data to the processing unit 600. The input unit 520 is realized by, for example, a keyboard, a mouse, a button switch, a touch panel, various sensors, a microphone, and the like.

  The processing unit 600 performs overall control of the flange angle estimation device 30. The processing unit 600 is realized by an arithmetic device such as a CPU or a storage device such as an IC memory. Further, the processing unit 600 executes flange angle estimation processing for estimating the relationship between the travel distance and the flange angle from the measured value of the flange angle in accordance with the program and data read from the storage unit 700.

  Specifically, based on the measured value accumulation data 722 and the design value data 724, the constants A, B, C, and D of the relational expression represented by the equation (6) are determined, and the travel distance of the wheel that is the object of estimation. And the relationship between the flange angle and the angle. Here, the measured value accumulation data 722 is obtained by associating the measured value of the flange angle with respect to the travel distance at the time of measurement for each wheel used in the past in the railway vehicle in which the wheel to be estimated is used. A large number of accumulated data (history data), for example, the data group shown in FIG.

  Further, the design value data 724 is dimension data at the time of designing the wheel to be estimated. FIG. 21 shows an example of the design value data 724. As shown in the figure, the design value data 724 stores a flange angle 724a as a design value.

  First, the processing unit 600 determines the design value of the flange angle stored in the design value data 724 as the constant D in Expression (6). Next, a plurality of (many) candidate formulas are calculated by varying the constants A, B, and C in formula (6). Then, for each candidate equation, the degree of approximation between the curve and each data value of the measured value accumulation data 722 is calculated by a predetermined approximation degree calculation method, and the candidate equation having the highest degree of approximation (the most approximate) is The relational expression that is most appropriate for the wheel being estimated is determined.

  The determined relational expression is stored in relational expression data 726. FIG. 22 shows an example of the data structure of the relational expression data 726. According to the figure, relational expression data 726 stores relational expression 726a and the value of each constant 726b in relational expression 726a.

  The storage unit 700 stores various programs and data for causing the processing unit 600 to control the flange angle estimation device 30 in an integrated manner. Specifically, a flange angle estimation program 710 for causing the processing unit 600 to perform flange angle estimation processing is stored as a program, and measured value accumulation data 722, design value data 724, and relational expression data 726 are stored as data. And remember.

[Process flow]
FIG. 23 is a flowchart for explaining the flow of the flange angle estimation process in the reference example . This processing is realized by the processing unit 600 executing processing according to the flange angle estimation program 710.

  According to the figure, the processing unit 600 first sets the design value of the flange angle set in the design value data 724 as the constant D in the relational expression shown in Expression (6) (Step T1). Next, a plurality (large number) of candidate expressions are generated by changing the constants A, B, and C in this relational expression (step T3). For each generated candidate formula, the degree of approximation between the curve and each data value stored in the measured value storage data 722 is calculated, and the most approximate candidate formula is the most appropriate for the estimation target wheel. It is determined that the relational expression is satisfied (step T5). When the above processing is performed, the processing unit 600 ends the flange angle estimation formula.

[Action / Effect]
According to the above reference example , the flange angle estimation device 30 uses a constant in the expression “Y = A × tanh (B × X) + C × X + D” as a relational expression between the travel distance X and the flange angle Y for a certain wheel. Estimate (calculate) by determining A, B, C, and D. That is, the constant D is set as the design value of the flange angle of the wheel set in the design value data 724. Then, among the plurality of candidate formulas that are changed variously as constants A, B, and C, the measured value of the flange angle for each wheel that has been used in the past in the railway vehicle in which the wheel is used is measured at the time of the measurement. A candidate formula that most closely approximates each piece of measured value accumulation data 722 accumulated in association with the travel distance is estimated (calculated) as a relational expression for the wheel. In this way, it is possible to formulate the relationship between the flange angle of the railway wheel and the travel distance from the measured value of the flange angle.

[Modification]
The application of the present invention is not limited to the above-described embodiments, and can be appropriately changed without departing from the spirit of the present invention.

The whole block diagram in a 1st embodiment. Explanatory drawing of data conversion. Explanatory drawing of data conversion. Explanatory drawing of estimation of tread shape data based on tread shape data. The block diagram of a wheel wear estimation apparatus. Explanatory drawing of cutting time estimation. Calculation example of each inspection item value. The data structural example of estimated inspection item value data. The data structural example of the inspection regulation data of a wheel. Explanatory drawing of lifetime estimation. The example of a data structure of design wheel data. An example of the amount of vertical wear. Data configuration example of life estimation data. The flowchart of a wheel wear estimation process. The flowchart of the rolling time estimation process performed in a wheel wear estimation process. The flowchart of the wheel lifetime estimation process performed in a wheel wear estimation process. An example of the relationship between the measured value of the flange angle and the travel distance. An example of a relational expression between the travel distance X and the flange angle Y. Comparison example between relational expression and measured value of flange angle. The block diagram of the flange angle estimation apparatus in a reference example . Data configuration example of design value data. Data structure example of relational expression data. The flowchart of a flange angle estimation process.

Explanation of symbols

DESCRIPTION OF SYMBOLS 10 Shape measuring apparatus 20 Wheel wear estimation apparatus 120 Communication part 140 Input part 200 Processing part 210 Data conversion part 220 Turning time estimation part 222 Tread surface shape estimation part 224 Inspection item value estimation part 230 Wheel life estimation part 300 Storage part 310 Wheel wear Estimation program 322 Designed wheel data 324 Wheel inspection regulation data 332 Tread surface shape measurement data 334 Tread surface shape data 336 Tread surface shape estimation data (A)
338 Estimated inspection item value data 342 Tread surface shape estimation data (B)
344 Life estimation data 160 Output unit 30 Flange angle estimation device 520 Input unit 600 Processing unit 700 Storage unit 710 Flange angle estimation program 722 Measurement value accumulation data 724 Design value data 726 Relational expression data 540 Output unit

Claims (7)

Computer
Data conversion means for obtaining tread shape data by converting each of a plurality of tread shape measurement data of railway wheels measured at different mileage points into discrete data at predetermined intervals in the wheel thickness direction,
Estimated desired distance setting means for setting a plurality of estimated desired travel distances that are desired travel distances when estimating the tread shape at predetermined travel distance intervals ,
Based on each of the plurality of tread shape data obtained by the data conversion means and each travel distance corresponding to each of the plurality of tread shape data, at each predetermined distance in the wheel thickness direction, Tread surface shape estimation means for estimating tread surface shape data at each of the set plurality of estimated desired travel distances by executing a regression calculation process on the tread shape data;
Based on the tread surface shape data of each of the plurality of estimated desired travel distances estimated by the tread shape estimation means, the inspection item value of the railway wheel at each of the plurality of estimated desired travel distances is calculated and calculated. A rolling time estimation means for estimating a time at which the railway wheel should be rolled by determining whether or not the inspection item value satisfies a specified wheel shape condition for determining whether or not the rolling is necessary,
Program to function as.   The plurality of tread shape data used for the regression calculation processing by the tread shape estimation means has a travel distance interval of less than 10,000 km of tread shape data with a travel distance of less than 50,000 km, and a travel distance of 50,000 km. The program according to claim 1, wherein the program satisfies the condition that the travel distance interval of the tread shape data is 50,000 km or less. The estimated desired distance setting means sets the plurality of estimated desired distances so that the estimated desired distance is a distance at a future vehicle inspection time based on a distance at a predetermined vehicle inspection. Make the computer work,
The program according to claim 1 or 2 , wherein the rolling time estimation means causes the computer to function so as to estimate a time of vehicle inspection for rolling the rail wheels. Based on the shape data at the time of entry of the railway wheel and the tread shape data calculated by the tread shape estimation means corresponding to the travel distance at the time when the rolling time estimation means is estimated to roll. A correction amount calculating means for calculating a correction amount at the time of cutting;
Based on the correction amount calculated by the correction amount calculation means, the time estimated by the rolling time estimation means, the diameter at the time of entry of the railway wheel, and the use limit diameter of the railway wheel, Life estimation means for estimating the life of the railway wheel;
The program as described in any one of Claim 1 to 3 for functioning the said computer as. The rolling time estimation means calculates the wheel diameter, flange thickness, flange height and flange angle as the inspection item values, and all of the calculated wheel diameter, flange thickness, flange height and flange angle are calculated. Determining whether or not the prescribed wheel shape condition is satisfied, thereby causing the computer to function to estimate the time when the railway wheel should be rolled.
A program according to any one of claims 1 to 4 . A computer-readable information storage medium storing the program according to any one of claims 1 to 5 . Data conversion means for obtaining tread shape data by converting each of a plurality of tread shape measurement data of railway wheels measured at different mileage points into discrete data at predetermined intervals in the wheel thickness direction;
Estimated desired distance setting means for setting a plurality of estimated desired travel distances that are desired travel distances when estimating the tread shape at predetermined travel distance intervals ;
Based on each of the plurality of tread shape data obtained by the data conversion means and each travel distance corresponding to each of the plurality of tread shape data, at each predetermined distance in the wheel thickness direction, A tread shape estimating means for estimating tread shape data at each of the set plurality of estimated desired travel distances by executing a regression calculation process on the tread shape data;
Based on the tread surface shape data of each of the plurality of estimated desired travel distances estimated by the tread shape estimation means, the inspection item value of the railway wheel at each of the plurality of estimated desired travel distances is calculated and calculated. A rolling time estimation means for estimating a time at which the railway wheel should be rolled by determining whether or not the inspection item value satisfies a specified wheel shape condition for determining whether or not the rolling is necessary,
A wheel wear estimation device comprising:

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