The present invention relates to an abnormality detection device, an abnormality detection method, and a program.
Priority is claimed on Japanese Patent Application No. 2017-210884, filed Oct. 31, 2017, the content of which is incorporated herein by reference.
A technology for detecting abnormality occurring in a vehicle traveling along a track or in the track is known. For example, Japanese Patent Publication No. 5691319 discloses a technology for determining the presence or absence of abnormality based on an acceleration of a vehicle. Furthermore. Japanese Unexamined Patent Application, First Publication No. 2006-160153 and Japanese Unexamined Patent Application, First Publication No. 2008-108250 disclose technologies for filter-processing an acceleration of a vehicle and determining abnormality in the vehicle by a Mahalanobis-Taguchi (MT) method.
However, in the aforementioned technologies, it is not possible to determine a vehicle or a track in which abnormality has occurred.
In light of the foregoing, an object of the present invention is to provide an abnormality detection device, an abnormality detection method, and a program that solve the aforementioned problem.
According to a first aspect of the present invention, an abnormality detection device includes: a measurement value acquiring unit configured to acquire input accelerations of n vehicles traveling along a track, wherein n represents a number of two or more; and an abnormality determination unit configured to determine abnormality in the track at a track position at which the input accelerations are equal to or more than a threshold value in a case where the abnormality determination unit has detected that the input accelerations for all of the n vehicles are equal to or more than a threshold value, the abnormality determination unit being configured to determine abnormality in any one or a plurality of vehicles out of n−1 or less vehicles in the n vehicles at which the input accelerations are equal to or more than the threshold value in a case where the abnormality determination unit has detected that the input accelerations for the any one or a plurality of vehicles out of the n−1 or less vehicles in the n vehicles are equal to or more than the threshold value.
In the above abnormality detection device, the measurement value acquiring unit may be configured to acquire a correspondence relation between the input accelerations and a position of the track, and the abnormality determination unit may be configured to inversely estimate a vertical displacement amount of the track based on the input accelerations and a model formula of the vehicle and specify a vertical displacement amount equal to or more than a predetermined threshold value and a position of the track at which the specified vertical displacement amount has been generated in a case where the abnormality determination unit has detected that the input accelerations for all of the n vehicles are equal to or more than the threshold value, the model formula including a relation between at least a vertical displacement amount of the track and a slate amount of the constituent member of the vehicle and an acceleration of the vehicle.
In the above abnormality detection device, the measurement value acquiring unit may be configured to acquire a correspondence relation between the input accelerations and a position of the track, and the abnormality determination unit may be configured to inversely estimate a state amount of a constituent member of the vehicle based on the input accelerations and a model formula of the vehicle and specify, as an abnormal place, the constituent member which indicates the state amount equal to or more than a predetermined threshold value in a case where the abnormality determination unit has detected that the input accelerations for the any one or a plurality of vehicles out of the n−1 or less vehicles in the n vehicles are equal to or more than the threshold value, the model formula including a relation between at least a vertical displacement amount of the track and the state amount of the constituent member of the vehicle and an acceleration of the vehicle.
In the above abnormality detection device, the abnormality determination unit may be configured to inversely estimate a state amount of a constituent member of the vehicle based on the input accelerations and a model formula of the vehicle and specify, as an abnormal place, the constituent member which indicates the state amount equal to or more than a predetermined threshold value in a case where the abnormality determination unit has not detected that the input accelerations for one or more vehicles are equal to or more than the threshold value, the model formula including a relation between at least a vertical displacement amount of the track and the state amount of the constituent member of the vehicle and an acceleration of the vehicle.
According to a second aspect of the present invention, an abnormality detection method includes: acquiring input accelerations of n vehicles traveling along a track, wherein n represents a number of two or more; determining abnormality in the track at a track position at which the input accelerations are equal to or more than a threshold value in a case where it has been detected that the input accelerations for all of the n vehicles are equal to or more than a threshold value; and determining abnormality in any one or a plurality of vehicles out of n−1 or less vehicles in the n vehicles at which the input accelerations are equal to or more than the threshold value in a case where it has been detected that the input accelerations for the any one or a plurality of vehicles out of the n−1 or less vehicles in the n vehicles.
According to a third aspect of the present invention, a non-transitory computer-readable recording medium stores a program for causing a computer of an abnormality detection device to function as: a measurement value acquiring unit configured to acquire input accelerations of n vehicles traveling along a track, wherein n represents a number of two or more; and an abnormality determination unit configured to determine abnormality in the track at a track position at which the input accelerations are equal to or more than a threshold value in a case where the abnormality determination unit has detected that the input accelerations for all of the n vehicles are equal to or more than a threshold value, the abnormality determination unit being configured to determine abnormality in any one or a plurality of vehicles out of n−1 or less vehicles in the n vehicles at which the input accelerations are equal to or more than the threshold value in a case where the abnormality determination unit has detected that the input accelerations for the any one or a plurality of vehicles out of the n−1 or less vehicles in the n vehicles are equal to or more than the threshold value.
Hereinafter, an abnormality detection device according to an embodiment of the present invention will be described with reference to the drawings.
As shown in
As shown in
The CPU 101 of the abnormality detection device 1 executes a stored abnormality sensing program on the basis of a user operation. Accordingly, the abnormality detection device 1 has each function of a control unit 31, a measurement value acquiring unit 32, an abnormality determination unit 33, and a position sensing unit 34.
The control unit 31 controls other functions.
The measurement value acquiring unit 32 acquires input accelerations of a plurality of (n) vehicles 3 traveling along a track. In the present embodiment, the measurement value acquiring unit 32 acquires accelerations from the acceleration sensors 2a and 2b of each of the three vehicles 3 constituting the train.
When input accelerations equal to or more than a threshold value are detected for all of the plurality of (n) vehicles 3, the abnormality determination unit 33 determines abnormality in a track position at which the input accelerations are equal to or more than the threshold value. Furthermore, when the input accelerations equal to or more than the threshold value are detected for any one or a plurality of vehicles 3 equal to or less than (n−1) of the plurality of (n) vehicles 3, the abnormality determination unit 33 determines abnormality in a vehicle 3 at which the input acceleration is equal to or more than the threshold value.
The position sensing unit 34 acquires a signal transmitted from an on-ground unit or a GPS satellite, and senses the position of the train on the basis of information included in the signal.
While the train is travelling, the measurement value acquiring unit 32 of the abnormality detection device 1 acquires acceleration information, which includes IDs of the acceleration sensors 2, IDs of the vehicles 3 provided with the acceleration sensors 2, and an ID of the train configured by the vehicles 3, from the acceleration sensors 2 (step S101). Furthermore, the measurement value acquiring unit 32 acquires position information (coordinates) from the position sensing unit 34 (step S102). The measurement value acquiring unit 32 correlates the IDs of the acceleration sensors 2, the acquired acceleration information, the position information, and a time with one another, and records the correlated results in an acceleration table of the database device 107 (step S103).
Accordingly, the time, the acceleration of the acceleration sensor 2a, the acceleration of the acceleration sensor 2b, and positions, each sensor ID, the vehicle IDs, and the train ID, which have been acquired from the position sensing unit 34 at the acquisition timings of these accelerations, are recorded in the acceleration table of the database device 107 in association with one another. The abnormality determination unit 33 reads information recorded in the database device 107 at a predetermined timing and starts an abnormality determination process (step S104). The predetermined timing, at which the abnormality determination process is started, for example, may be immediately after the train have traveled a start point to an end point of the track L or a timing provided for each predetermined period such as one week and one month. In the abnormality detection device 1, train information obtained by associating the train ID with the vehicle IDs constituting the train is recorded in a train management table of the database device 107.
The abnormality determination unit 33 specifies a vehicle ID and a train ID associated with an acceleration equal to or more than a threshold value. The threshold value of the acceleration is a lower limit threshold value of an acceleration for determining that there is abnormality in the track L or one or a plurality of constituent members of the vehicles 3. The abnormality determination unit 33 acquires IDs of all vehicles constituting the train from the train management table by using the train ID from the specified vehicle ID and train ID. The abnormality determination unit 33 determines whether the acceleration equal to or more than the threshold value has been detected for all the vehicle IDs acquired from the train management table (step S105). When the acceleration equal to or more than the threshold value is detected for all the vehicle IDs, the abnormality determination unit 33 determining that there is abnormality in the track L (step S106). Furthermore, when the acceleration equal to or more than the threshold value has been detected for vehicle IDs of one or a plurality of vehicles 3 equal to or less than (n−1) vehicles among vehicle IDs corresponding to n vehicles constituting the train, the abnormality determination unit 33 determines that there is an abnormality in the one or plurality of vehicles 3 (step S107).
When it is determined that there is abnormality in the track L, the abnormality determination unit 33 puts the acceleration equal to or more than the threshold value into a model formula of the vehicle 3 including a relation between at least a displacement amount in an up and down direction due to unevenness of the track L and state amounts and accelerations of one or a plurality of constituent members of the vehicle 3, thereby inversely estimating the displacement amount in the up and down direction due to the unevenness of the track L (step S108). Furthermore, the abnormality determination unit 33 specifies position information of the track L for which the acceleration equal to or more than the threshold value has been detected (step S109). The abnormality determination unit 33 outputs the calculated displacement amount in the up and down direction due to the unevenness of the track L and the position information (step S110). Accordingly, on the basis of the displacement amount in the up and down direction and the position information, a manager specifies the state and the position of the track L and performs inspection, repair and the like.
When it is determined that there is abnormality in the vehicle 3, the abnormality determination unit 33 puts the acceleration equal to or more than the threshold value, which has been obtained from the acceleration sensors 2 of the vehicle 3, into the model formula, thereby inversely estimating the state amounts of the one or plurality of constituent members of the vehicle 3 (step S111). The abnormality determination unit 33 specifies a constituent member in which the state amount is equal to or more than the threshold value (step S112). The abnormality determination unit 33 outputs an ID of a vehicle 3 in which the state amount of the constituent member is equal to or more than the threshold value, an ID of the train to which the vehicle 3 is connected, an ID of a vehicle to be specified, and an ID of the constituent member in which the state amount is equal to or more than the threshold value (step S113). Accordingly, on the basis of the train ID, the vehicle ID, and the constituent member ID, a manager specifies a constituent member of a vehicle 3 of a train in which abnormality has occurred, and performs inspection, repair and the like.
As shown in
In the model formula (1), a right side indicates a force applied to the tire. A dash and a double dash added onto signs of the model formula (1) indicate a differentiation and a second-order differentiation, respectively. In the model formula (1), a value indicated by a second-order differentiation of the displacement amount X1 is an acceleration measured by the acceleration sensor 2a. Furthermore, in the model formula (1), a value (an acceleration) indicated by a second-order differentiation of the displacement amount X2 is an acceleration measured by the acceleration sensor 2b. In addition, differential values (speeds) of the displacement amounts X1 and X2 can be calculated by integration of the accelerations, and the displacement amounts X1 and X2 can be calculated by integrating the differential values (speeds) of the displacement amounts X1 and X2.
The abnormality determination unit 33 puts the masses M1 and M2, the measured accelerations X1″ and X2″, the calculated speeds X1′ and X2′, the calculated displacement amounts X1 and X2, the spring constants K1 and K2 in a normal case, the attenuation coefficients C1 and C2 in the normal case, and the like into the model formula (1), thereby performing inverse estimation for calculating a displacement amount in an up and down direction of the tire 12, a spring constant, and an attenuation coefficient by an optimization calculation when simultaneous equations are satisfied. When it is determined that there is abnormality in the track L, the abnormality determination unit 33 specifies and outputs the displacement amount X in the up and down direction of the tire 12 in the up and down direction as a result of the inverse estimation. Furthermore, when it is determined that there is abnormality in a vehicle, the abnormality determination unit 33 specifies a tire corresponding to a spring constant and an attenuation coefficient which are values deviating from the spring constants K1 and K2 or the attenuation coefficients C1 and C2 in the normal case, and a constituent member such as a buffer device as abnormal places as a result of the inverse estimation.
The abnormality determination unit 33 may use a model formula (2) below instead of the model formula (1). The explanation of a model formula shown in
Similarly to the inverse estimation using the model formula (1), the abnormality determination unit 33 puts the mass M, the inertia moment I, the measured acceleration X1″, the calculated speed X′, the calculated displacement amount X, the spring constants k11, k12, k21, and k22 in a normal case, the attenuation coefficients c11, c12, c21, and c22 in the normal case, and the like into the model formula (2), thereby performing inverse estimation for calculating a displacement amount in an up and down direction of the tire 12, a spring constant, and an attenuation coefficient by an optimization calculation when simultaneous equations are satisfied. When it is determined that there is abnormality in the track L, the abnormality determination unit 33 specifies and outputs the displacement amount x11 and x21 in the up and down direction of the tire 12 as a result of the inverse estimation. Furthermore, when it is determined that there is abnormality in a vehicle, the abnormality determination unit 33 specifies a tire corresponding to a spring constant and an attenuation coefficient which are values deviating from the spring constants or the attenuation coefficients in the normal case, and a constituent member such as a buffer device as abnormal places as a result of the inverse estimation.
The abnormality determination unit 33 may use a model formula (3) below instead of the model formula (1) or the model formula (2). The explanations of model formulas shown in
As shown in
Furthermore, as shown in
Furthermore, it is assumed that the inertia moment of the bogie 11 is I2x.
Similarly to the inverse estimation using the model formula (1) or (2), the abnormality determination unit 33 puts the masses M1 and M2, a measured acceleration, a calculated speed, the displacement amounts Z1 to Z3 calculated on the basis of a measurement value of the acceleration sensor 2a, the displacement amounts ZRf. ZRr, ZRf, and ZRr in a normal case, the inertial moments I1x, I1y, and I2x, the measured inclinations θx, θy, θf, and θr, the spring constants K1 and K2 in the normal case, the attenuation coefficients C1 and C2 in the normal case, and the like into the model formula (3), thereby performing inverse estimation for calculating a displacement amount in an up and down direction of the tire 12, a spring constant, and an attenuation coefficient by an optimization calculation when simultaneous equations are satisfied. When it is determined that there is abnormality in the track L, the abnormality determination unit 33 specifies and outputs the displacement amounts ZRf, ZRr, ZRf, and ZRr in the up and down direction of the tire 12 as a result of the inverse estimation. Furthermore, when it is determined that there is abnormality in the vehicle 3, the abnormality determination unit 33 specifies a tire corresponding to a spring constant and an attenuation coefficient which are values deviating from the spring constants or the attenuation coefficients in the normal case, and a constituent member such as a buffer device as abnormal places.
Since the aforementioned model formulas (1) to (3) are examples, the abnormality in a constituent member may be specified by performing inverse estimation using other model formulas. It is assumed that an object to be specified as being abnormal is the vehicle body 10, an air spring or a damper constituting the buffer device of the bogie 11, the tire 12 and the like in the aforementioned model formulas (1) to (3); however, other constituent members may be employed as the object to be specified as being abnormal.
Furthermore, in the aforementioned examples, a case where the acceleration of a train including a plurality of connected vehicles 3 is measured to perform processing has been described. However, the vehicles 3 may not be connected to one another, the plural of each individual vehicle 3 may be employed as a unit, and then the abnormality detection device 1 may determine whether the accelerations of one set of all vehicles 3 are equal to or more than a threshold value in step S105.
Furthermore, in the aforementioned processing flow, when the accelerations equal to or more than the threshold value are detected, the abnormal position of the track or the displacement amount of the tire 12 is specified, or an abnormal constituent member is specified by using the model formulas (1) to (3). However, even when the accelerations equal to or more than the threshold value are not detected, the abnormal position of the track or the displacement amount, or the abnormal constituent member may be specified at constant intervals by using these model formulas. Furthermore, this result is recorded in the database device 107, so that a change in a state may be determined, determination regarding whether the constituent member is deteriorating may be performed, or a deterioration period may be calculated on the basis of a change in a spring constant or an attenuation coefficient of the recorded constituent member.
According to such a process, it is possible to estimate the probability of the occurrence of abnormality in the constituent member before the abnormality occurs. Furthermore, since individual measurement of each constituent member is not necessary, it is possible to determine the state of each constituent member by using only a representative acceleration measurement result.
In the aforementioned process, accelerations acquired by the acceleration sensors 2 are used to perform the process; however, a displacement amount, a speed per unit time, and the like may be measured and converted into accelerations. Furthermore, accelerations may be replaced with displacement or speeds and inverse estimation of judgment, track unevenness, and a vehicle model may be performed using a threshold value.
Furthermore, the vehicle 3 may be provided with guide wheels which is in contact with right and left guide rails of the vehicle body 10, and abnormality in the guide rails or the guide wheels may be detected using a model formula of force transferred front the guide wheels to the guide rails. In such a case, a model formula in at least one point of the right and left sides of the vehicle body 10 is required. In addition, the number of measurement points of accelerations and the like increases, so that it is possible to improve the accuracy of abnormality determination. As a threshold value of the acceleration, in addition to a root mean square (rms) value, a maximum value, and a frequency analysis (⅓ octave band analysis) value, data may be accumulated for these parameters from an initial state and a Mahalanobis distance calculated by performing analysis using a MT method may be used as the threshold value.
Furthermore, when the aforementioned process is performed, at the time of construction (beginning) of the track L, unevenness amounts of the track (a road surface and a guide) may be measured and then a displacement amount obtained by adding a predetermined value to unevenness amounts at each position may be used as the threshold value. For installation places of the acceleration sensors 2 in the vehicle body 10, accelerations of other measurement places are estimated from one measurement point by using a Kalman filter and the like, so that measurement points may be reduced. In an optimization calculation using a model formula, for example, it is sufficient if inverse estimation is performed such that values such as each spring constant and attenuation coefficient indicating a state amount of a constituent member, a variation amount in an up and down direction, and the like are minimized using a squared sum of errors of each tick time between measured accelerations and accelerations calculated from an analysis model is employed as an objective function.
The aforementioned abnormality detection device 1 has a computer system therein. Furthermore, the aforementioned each processing step is stored in a computer readable recording medium in the form of a program and the program is read and executed by the computer, so that the process is performed. Examples of the computer readable recording medium include a magnetic disk, a magneto-optical disk, a CD-ROM, a DVD-ROM, a semiconductor memory and the like. Furthermore, the computer program may be distributed to the computer by a communication line and the computer having received the distribution may execute the program.
Furthermore, the aforementioned program may be a program for performing some of the aforementioned functions.
Moreover, the aforementioned program may be a program capable of performing the aforementioned functions through a combination with a program already recorded in the computer system, so-called a differential filter (a differential program).
While preferred embodiments of the invention have been described and shown above, it should be understood that these are exemplary of the invention and are not to be considered as limiting. Additions, omissions, substitutions, and other modifications can be made without departing from the spirit or scope of the present invention. Accordingly, the invention is not to be considered as being limited by the foregoing description, and is only limited by the scope of the appended claims.
Number | Date | Country | Kind |
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2017-210884 | Oct 2017 | JP | national |