JP6984682B2 - RBI estimation device - Google Patents

Description

The present invention relates to a hitting point estimation device, a method and a program for estimating hitting points on the face surface of a golf club head when a golf club is swung to hit a golf ball.

Conventionally, a technique for estimating a hitting point on the face surface of a golf club head during a golf swing has been proposed. For example, Patent Document 1 discloses a device in which a plurality of sensors for detecting vibration at the time of impact are attached to the back surface of a face surface, and a hitting point is estimated from the output signals of these sensors.

International Publication No. 2009/06698 Pamphlet

However, in the method of Patent Document 1, since the sensor is attached to the head, more specifically, to the back surface side of the face surface, it may be difficult to attach the sensor. Also, if the sensor is attached to the head, the presence of the sensor can interfere with the golfer's natural golf swing.

It is an object of the present invention to provide a hitting point estimation device, a method and a program capable of estimating a hitting point on the face surface of a golf club head at the time of a golf swing easily and with high accuracy.

The hitting point estimation device according to the first aspect of the present invention is a hitting point estimation device that estimates the hitting point on the face surface of the head when a golf club having a grip, a shaft and a head is swung to hit a golf ball. , An acquisition unit and an estimation unit are provided. The acquisition unit acquires time-series sensor data output from at least one of the angular velocity sensor and the acceleration sensor attached to at least one of the grip and the shaft. The estimation unit estimates the hitting point according to the shaft characteristic, which is the characteristic of the shaft, based on the sensor data.

The hitting point estimation device according to the second aspect of the present invention is a hitting point estimation device according to the first aspect, and the estimation unit derives an index depending on the hitting point from the sensor data according to the shaft characteristic. , The hitting point is estimated according to the index.

The hitting point estimation device according to the third aspect of the present invention is the hitting point estimation device according to the second aspect, and the estimation unit determines a specific frequency according to the shaft characteristics, and uses the toe as the index. To the specific frequency of the phase angle corresponding to the specific frequency in the spectrum of angular velocity around the axis in the heel direction or in a direction substantially parallel to the heel direction, or to the specific frequency in the spectrum of acceleration in the face-back direction or in a direction substantially parallel to the phase angle. The corresponding phase angle is derived, and the vertical position of the hitting point is estimated according to the phase angle.

The hitting point estimation device according to the fourth aspect of the present invention is a hitting point estimation device according to any one of the first to third viewpoints, and the shaft characteristic is flex.

The hitting point estimation device according to the fifth aspect of the present invention is a hitting point estimation device according to the first aspect, and the estimation unit derives an index depending on the hitting point from the sensor data, and the index and the shaft characteristic. The hitting point is estimated according to the above.

The dot estimation device according to the sixth aspect of the present invention is the dot estimation device according to the fifth aspect, and the estimation unit is among a plurality of regression equations using the index as an explanatory variable and the dot as an objective variable. Therefore, the hitting point is estimated by selecting a specific regression equation according to the shaft characteristics and substituting the index derived from the sensor data into the specific regression equation.

The hitting point estimation device according to the seventh aspect of the present invention is the hitting point estimation device according to the fifth or sixth aspect, and the shaft characteristic is at least one of flex, torque, tone and weight.

The hitting point estimation device according to the eighth aspect of the present invention is a hitting point estimation device that estimates the hitting point on the face surface of the head when a golf club having a grip, a shaft and a head is swung to hit a golf ball. , An acquisition unit and an estimation unit are provided. The acquisition unit acquires time-series sensor data output from at least one of the angular velocity sensor and the acceleration sensor attached to at least one of the grip and the shaft. The estimation unit estimates the hitting point based on the sensor data. Based on the sensor data, the estimation unit determines whether or not the hitting point exists in the vicinity of the inertial spindle on the face surface.

The hitting point estimation device according to the ninth aspect of the present invention is a hitting point estimation device according to the eighth aspect, and the estimation unit derives an index depending on the hitting point from the sensor data, and according to the index, It is determined whether or not the hitting point exists in the vicinity of the inertial spindle on the face surface.

The hitting point estimation device according to the tenth aspect of the present invention is the hitting point estimation device according to the ninth aspect, and the estimation unit uses the angular velocity around the axis in the toe-heel direction or a direction substantially parallel to the toe-heel direction as the index. Derived from the size of the spectrum corresponding to a predetermined mode or a predetermined frequency, or the size of the spectrum corresponding to a predetermined mode or a predetermined frequency of acceleration in the face-back direction or a direction substantially parallel to the face-back direction. Depending on the size of the spectrum, it is determined whether or not the hitting point exists in the vicinity of the inertial spindle on the face surface.

The hitting point estimation device according to the eleventh aspect of the present invention is a hitting point estimation device that estimates the hitting point on the face surface of the head when a golf club having a grip, a shaft and a head is swung to hit a golf ball. , An acquisition unit and an estimation unit are provided. The acquisition unit acquires time-series sensor data output from at least one of the angular velocity sensor and the acceleration sensor attached to at least one of the grip and the shaft. The estimation unit estimates the hitting point based on the sensor data. The estimation unit classifies the hitting point into one of a plurality of regions defined on the face surface according to the first index derived from the sensor data, and the second is derived from the sensor data. When the index of is exceeded the threshold value, the hit points are reclassified into another region included in the plurality of regions.

The hitting point estimation program according to the twelfth aspect of the present invention is a hitting point estimation program that estimates the hitting point on the face surface of the head when a golf club having a grip, a shaft and a head is swung to hit a golf ball. , Have the computer perform the following steps.
(1) A step of acquiring time-series sensor data output from at least one of the angular velocity sensor and the acceleration sensor attached to at least one of the grip and the shaft.
(2) A step of estimating the hitting point according to the shaft characteristic, which is the characteristic of the shaft, based on the sensor data.

The hitting point estimation program according to the thirteenth aspect of the present invention is a hitting point estimation program that estimates the hitting point on the face surface of the head when a golf club having a grip, a shaft and a head is swung to hit a golf ball. , Have the computer perform the following steps.
(1) A step of acquiring time-series sensor data output from at least one of the angular velocity sensor and the acceleration sensor attached to at least one of the grip and the shaft.
(2) A step of estimating the hitting point based on the sensor data.
Further, the step (2) includes a step of determining whether or not the hitting point exists in the vicinity of the inertial spindle on the face surface based on the sensor data.

The hitting point estimation program according to the fourteenth aspect of the present invention is a hitting point estimation program that estimates the hitting point on the face surface of the head when a golf club having a grip, a shaft and a head is swung to hit a golf ball. , Have the computer perform the following steps.
(1) A step of acquiring time-series sensor data output from at least one of the angular velocity sensor and the acceleration sensor attached to at least one of the grip and the shaft.
(2) A step of estimating the hitting point based on the sensor data.
Further, in the step (2), the hitting point is classified into any of a plurality of regions defined on the face surface according to the first index derived from the sensor data, and is derived from the sensor data. A step of reclassifying the hitting point into another region included in the plurality of regions when the second index to be performed exceeds a threshold value is included.

According to the present invention, the hitting point on the face surface of the golf club head is based on the time-series sensor data output from at least one of the angular velocity sensor and the acceleration sensor attached to at least one of the grip and the shaft of the golf club. Presumed. Therefore, not only is it relatively easy to attach the sensor, but the presence of the sensor is less likely to interfere with the golf swing. As a result, the hitting point at the time of golf swing can be estimated easily and with high accuracy.

Further, the influence of the impact of the golf ball on the face surface is transmitted from the head via the shaft to the sensor attached to at least one of the grip or the shaft. Therefore, the waveform of the sensor data output from the sensor is easily affected by the characteristics of the shaft. In this respect, according to the first viewpoint and the twelfth viewpoint, since the hitting point is estimated according to the characteristics of the shaft, the hitting point can be estimated with higher accuracy.

Further, when the golf ball is hit on the face surface near the inertial spindle of the head, the rotation of the head is unlikely to occur, and the waveform of the sensor data at this time is hit at another place on the face surface. A different tendency may appear. For example, high frequency components are unlikely to occur in the sensor data when the head is hit near the inertial spindle. From this point, the eighth viewpoint and the thirteenth viewpoint, it is determined whether or not the hitting point exists in the vicinity of the inertial spindle of the head on the face surface based on the sensor data. Therefore, the hitting point can be estimated with higher accuracy.

Further, according to the eleventh viewpoint and the fourteenth viewpoint, the hitting point is classified into one of a plurality of regions defined on the face surface according to the first index derived from the sensor data. Further, when the second index derived from the sensor data exceeds the threshold value, the hit points are reclassified into another region included in the plurality of regions. Therefore, it is possible to estimate the hitting point with high accuracy from various viewpoints.

The figure which shows the swing analysis system which includes the hitting point estimation apparatus which concerns on one Embodiment of this invention. The functional block diagram of the swing analysis system of FIG. The figure explaining the xyz local coordinate system with respect to the grip of a golf club. (A) The figure which shows the address state. (B) The figure which shows the top state. (C) The figure which shows the impact state. (D) The figure which shows the finish state. A flowchart showing the flow of the dot estimation process. The figure which shows the face surface of a head. A flowchart showing the flow of the classification process of the area to which the dot belongs, which is included in the dot estimation process. The figure explaining the behavior of a head when it hits at the lower part, the upper part, and the vicinity of the inertial spindle of a face surface. The graph which shows the phase spectrum at the time of hitting at the lower part and the upper part of a face surface. The figure explaining the 1st index. The figure explaining the second index. The figure explaining the third index. The figure explaining the 4th index. The figure explaining the 5th index. A graph showing the percentage of correct answers in the RBI estimation process (reference example). Another graph (Example) showing the correct answer rate of the dot estimation process. The graph which shows the occurrence frequency of the peak frequency of the 4th order mode of the spectrum of the angular velocity ω _{x for each flex of a shaft.}

Hereinafter, a dot estimation device, a method, and a program according to an embodiment of the present invention will be described with reference to the drawings.

<1. Outline configuration of swing analysis system>
1 and 2 show the overall configuration of the swing analysis system 100 including the hitting point estimation device 2 according to the present embodiment. The swing analysis system 100 is a system for analyzing a golf swing by a golfer 7 using a golf club 4. The hit point estimation device 2 has a function of estimating the hit point (collision position) of the golf ball on the face surface 41a (see FIG. 6) of the head 41 when the golfer 7 swings the golf club 4 and hits the golf ball. Is installed. The information on the hit points estimated by the hit point estimation device 2 can be used, for example, to grasp how much the golfer 7 is catching the ball in the sweet area during golf practice. Alternatively, it can also be used to support the fitting of the golf club 4. The data to be analyzed is collected by the sensor unit 1 attached to the grip 42 of the golf club 4, and the hitting point estimation device 2 constitutes the swing analysis system 100 together with the sensor unit 1.

Hereinafter, the configuration of the sensor unit 1 and the hitting point estimation device 2 will be described, and then the flow of the hitting point estimation process will be described.

<1-1. Sensor unit configuration>
As shown in FIGS. 1 and 3, the sensor unit 1 is attached to an end portion of the grip 42 of the golf club 4 opposite to the head 41, and measures the behavior of the grip 42. The golf club 4 is a general golf club, and is composed of a shaft 40, a head 41 provided at one end of the shaft 40, and a grip 42 provided at the other end of the shaft 40. The sensor unit 1 is compact and lightweight so as not to interfere with the swing operation. The sensor unit 1 can be attached to the outside of the golf club 4 and can be detachably configured with respect to the golf club 4.

As shown in FIG. 2, the sensor unit 1 is equipped with an acceleration sensor 11 and an angular velocity sensor 12. Further, the sensor unit 1 is also equipped with a communication device 10 for transmitting sensor data output from these sensors 11 and 12 to an external dot estimation device 2. In the present embodiment, the communication device 10 is wireless so as not to interfere with the swing operation, but it may be connected to the dot estimation device 2 by wire via a cable.

The acceleration sensor 11 and the angular velocity sensor 12 measure the acceleration and the angular velocity in the xyz local coordinate system, respectively. More specifically, the acceleration sensor 11 measures _{the accelerations a x} , a _y , a _z of the grip 42 in the x-axis, y-axis, and z-axis directions. The angular velocity sensor 12 measures _{the angular velocities ω x} , ω _y , ω _z of the grip 42 around the x-axis, y-axis, and z-axis. These sensor data are acquired as time-series data having a predetermined sampling period Δt. The xyz local coordinate system is a 3-axis Cartesian coordinate system defined as shown in FIG. That is, the z-axis coincides with the extending direction of the shaft 40, and the direction from the head 41 to the grip 42 is the z-axis positive direction. The y-axis is oriented so as to be as close as possible to the flying ball direction at the time of addressing the golf club 4, that is, substantially along the face-back direction, and the direction from the back side to the face side is the positive y-axis direction. .. The x-axis is oriented so as to be orthogonal to the y-axis and the z-axis, that is, substantially along the toe-heel direction, and the direction from the heel side to the toe side is the x-axis positive direction. Therefore, the x-axis and the z-axis are included in a plane substantially parallel to the face surface 41a.

The swing motion of a golf club generally proceeds in the order of address, top, impact, and finish. The address means an initial state in which the head 41 of the golf club 4 is arranged near the ball as shown in FIG. 4 (A), and the top means the golf club 4 from the address as shown in FIG. 4 (B). This means the state in which the head 41 is swung up most. The impact means the state at the moment when the golf club 4 is swung down from the top and the head 41 collides with the ball as shown in FIG. 4 (C), and the finish means the state at the moment when the head 41 collides with the ball, and the finish means as shown in FIG. 4 (D). It means a state in which the golf club 4 is swung forward after the impact.

Further, the toe-heel direction, the face-back direction and the top-sole direction are defined with reference to the reference state. The reference state is a state in which the extending direction of the shaft 40 is included in a plane perpendicular to the horizontal plane (hereinafter referred to as a reference vertical plane), and the head 41 is placed on the horizontal plane at a predetermined lie angle and loft angle. be. Predetermined lie and loft angles are described, for example, in product catalogs. The direction of the line of intersection between the reference vertical plane and the horizontal plane is the toe-heel direction, and the direction perpendicular to the toe-heel direction and parallel to the horizontal plane is the face-back direction. Further, the direction perpendicular to the horizontal plane is referred to as a top-sole direction. In the description of the present embodiment, unless otherwise specified, "left and right" means the toe-heel direction, and the toe side is the left and the heel side is the right. Unless otherwise specified, "up and down" means the top-sole direction, with the top side being the top and the sole side being the bottom.

In the present embodiment, the sensor data from the acceleration sensor 11 and the angular velocity sensor 12 are transmitted to the dot estimation device 2 in real time via the communication device 10. However, for example, the sensor data may be stored in the storage device in the sensor unit 1, and the sensor data may be taken out from the storage device after the swing operation is completed and passed to the hit point estimation device 2.

<1-2. Configuration of RBI estimation device>
The configuration of the hitting point estimation device 2 will be described with reference to FIG. 2. The dot estimation device 2 is a general-purpose personal computer as hardware, and is realized as, for example, a desktop computer, a notebook computer, a tablet computer, or a smartphone. The dot estimation device 2 is manufactured by installing the dot estimation program 3 on a general-purpose computer from a recording medium 20 such as a CD-ROM or a USB memory that can be read by a computer, or via a network such as the Internet. The hit point estimation program 3 is software for analyzing the golf swing based on the sensor data sent from the sensor unit 1 and estimating the hit points on the face surface 41a. The dot estimation program 3 causes the dot estimation device 2 to execute an operation described later.

The hitting point estimation device 2 includes a display unit 21, an input unit 22, a storage unit 23, a control unit 24, and a communication unit 25. These units 21 to 25 are connected to each other via the bus line 26 and can communicate with each other. In the present embodiment, the display unit 21 is composed of a liquid crystal display or the like, and displays information described later to the user. The user here is a general term for a person who needs an analysis result, such as the golfer 7 himself or his instructor. Further, the input unit 22 can be configured by a mouse, a keyboard, a touch panel, or the like, and receives an operation from the user on the dot estimation device 2.

The storage unit 23 is composed of a non-volatile storage device such as a hard disk and a flash memory. In addition to storing the dot estimation program 3 in the storage unit 23, the sensor data sent from the sensor unit 1 is stored. Further, in the storage unit 23, data (hereinafter, coefficient data) 28 indicating the coefficient of the regression equation used for estimating the hitting point is stored. The details of the coefficient data 28 will be described later. The communication unit 25 is a communication interface that enables communication between the dot estimation device 2 and the external device, and receives data from the sensor unit 1.

The control unit 24 can be composed of a CPU, a ROM, a RAM, and the like. The control unit 24 virtually operates as a data acquisition unit 24A, a dot estimation unit 24B, a miss shot determination unit 24C, and a result output unit 24D by reading and executing the dot estimation program 3 in the storage unit 23. Details of the operation of each unit 24A to 24D will be described later.

<2. RBI estimation process>
Subsequently, with reference to FIG. 5, the hitting point estimation process executed by the swing analysis system 100 will be described. FIG. 5 is a flowchart showing the flow of the dot estimation process. The dot estimation process starts when the user commands the execution of the dot estimation process. _{In the present embodiment, the coordinates (D th} ,, D _{ts ) of the hitting points in the D th} −D _ts plane (see FIG. 6) defined on the face surface 41a are specified. The D _th −D _ts plane has the face center Fc as the origin, and the direction from the toe side to the heel side is the D _th axis positive direction, and the direction from the sole side to the top side is the D _ts axis positive direction.

First, in step S1, the data acquisition unit 24A acquires time-series sensor data output from the sensor unit 1. More specifically, the golfer 7 swings the golf club 4 with the sensor unit 1 described above. At this time, the sensor unit 1 detects sensor data including time-series data _{of accelerations a x} , a _y , a _z and angular velocities ω _x , ω _y , ω _{z during the golf swing.} These sensor data are transmitted to the dot estimation device 2 via the communication device 10 of the sensor unit 1. On the other hand, on the dot estimation device 2 side, the data acquisition unit 24A receives the data acquisition unit 24A via the communication unit 25 and stores it in the storage unit 23. In this embodiment, at least time-series sensor data from the address to the finish is collected.

Next, in step S2, the data acquisition unit 24A acquires information indicating the flex of the shaft 40 of the golf club 4 used for the golf swing in step S1. Flex is one of the characteristics of the shaft 40 and is an index showing the hardness (flexural rigidity) of the shaft 40. In the present embodiment, the data acquisition unit 24A displays a predetermined screen on the display unit 21, asks the user the type of flex of the shaft 40 on the screen, and causes the user to input the type of flex. The question format is preferably a selection format in which a list of types of flex to be selected is presented to the user and an answer is selected from the list. The information indicating the flex is referred to in step S7 when calculating the index φ2 described later.

In step S3, RBI estimation unit 24B is, on the basis of the sensor data stored in the storage unit 23, derives the impact time t _i of the top and address, t _t, the t _a. Since the impact based on the time-series data such as an angular velocity, acceleration, time t _i of the top and address, t _t, as an algorithm for calculation of t _a, are known various ones, omitting detailed description here do.

_{In the following step S4, the hitting point estimation unit 24B obtains accelerations a x} , a _y , a _z and angular velocities ω _x , ω _y , ω _z in the analysis period near the impact from the sensor data stored in the storage unit 23. Extract time series data (analysis data). The analysis period here, in the present embodiment, a period from the time t _i of the impact to the (time of the impact t _i + T _1). For example, T ₁ = 500 ms. Incidentally, the analysis period, may include a previous period than the time t _i of the impact.

In the following step S5, the hitting point estimation unit 24B spectrally analyzes the analysis data acquired in step S4. _{Specifically, the time series data of acceleration a x} , a _y , a _z and angular velocity ω _x , ω _y , ω _z included in the analysis data are fast Fourier transformed, and acceleration a _x , a _y , a _z and angular velocity are performed. Derivation of spectra (including amplitude and phase spectra) for each of ω _x , ω _y , and ω _z.

In the following step S6, the hitting point estimation unit 24B uses the analysis data acquired in steps S4 and S5 and their spectra to estimate the hitting points C _th1 , C _th2 , ..., C _thN and C _ts1 , C. Derivation of _ts2 , ..., C _tsM. The indexes C _th1 , C _th2 , ..., C _{thN are indexes for estimating the hitting point D th} of the ball in the toe-heel direction, and the indexes C _ts1 , C _ts2 , ..., C _tsM are the top. _-This is an index for estimating the hitting point D ts of the ball in the sole direction. Indicators C _th1 , C _th2 , ..., C _thN and C _ts1 , C _ts2 , ..., C _tsM are indexes whose values change depending on where the ball collides on the face surface 41a. It is an index that depends on the hitting point. In addition, most of the indicators C _th1 , C _th2 , ..., C _thN and C _ts1 , C _ts2 , ..., C _{tsM quantify} the waveform characteristics (including the spectral characteristics of the analysis data) of the analysis data. It is a feature quantity expressed as a target. The details of the indicators C _th1 , C _th2 , ..., C _thN and C _ts1 , C _ts2 , ..., C _{tsM according to} this embodiment will be described later.

In the following step S7, the hitting point estimation unit 24B sets the hitting point on the face surface 41a into any of the plurality of regions A1 to A8 (see FIG. 6) based on the analysis data acquired in steps S4 and S5 and the spectrum thereof. Classify. In FIG. 6, the boundary line of the regions A1 to A8 is shown by a dotted line. Of these, the regions A3 and A4 are regions on the face surface 41a that extend toward the center in the toe-heel direction (near the face center Fc in the toe-heel direction and also near the sweet spot), and the upper region is The area A3, and the lower area is the area A4. Further, the regions A7 and A8 are regions extending along a line (hereinafter, simply referred to as an inertial spindle) in which the axis closest to the toe-heel direction among the three inertial spindles of the head 41 is projected onto the face surface 41a. .. The inertial spindle is tilted on the face surface 41a at an angle smaller than 45 ° with respect to the toe-heel direction, and extends from above the toe to below the heel. The regions A7 and A8 are regions extending near the inertial spindle, the region above the toe is the region A7, and the region below the toe is the region A8. Further, the regions A1, A2, A5, and A6 are regions located above the toe, below the toe, above the heel, and below the heel, respectively, among the remaining regions on the face surface 41a.

In step S7, four indexes f1, φ1, φ2, and H are derived as indexes for classifying the hit points into the regions A1 to A8. First, the indexes f1 and φ1 are indexes for determining the position of the hitting point in the toe-heel direction on the face surface 41a. φ2 is an index for determining the vertical position of the hitting point on the face surface 41a. H is an index for determining whether or not the hitting point exists in the vicinity of the inertial spindle, in other words, whether or not it belongs to the regions A7 and A8. Then, in step S7, the hitting points are classified into any of the regions A1 to A8 according to the calculated indexes f1, φ1, φ2, H (steps S71 to S78), and then whether or not the classification is correct. A review is performed (step S79). More specifically, in step S79, when the exception condition is satisfied, an exception process for reclassifying the hit points into another area included in the areas A1 to A8 is executed.

More specifically, the process of classifying the hit points in step S7 proceeds according to the sub-steps S71 to S79 shown in FIG. 7. First, as step S71, the hitting point estimation unit 24B derives the peak frequency f1 of the primary mode, that is, the primary natural frequency f1 based on the spectrum of the _{angular velocity ω z (see FIG. 10).} Then, when f1 is equal to or more than a predetermined value and f1 ≧ 40 Hz in the present embodiment, it is determined that the hitting point of the ball is included in any of the regions A3 and A4 near the center in the toe-heel direction, and the process is performed. Proceed to step S78. In other cases, the process proceeds to step S72. When a ball collides near the center in the toe-heel direction, the twist mode is unlikely to occur in the head 41 and the shaft 40. Further, although there is a difference depending on the type of golf club, the primary peak frequency of the twisting mode is usually about 25 Hz. Therefore, when the first-order peak frequency f1 is far from the applied value, it can be estimated that the ball has collided near the center in the toe-heel direction. Step S71 utilizes this principle.

In step S72, the hitting point estimation unit 24B derives a phase angle φ1 corresponding to the peak frequency f1 in the primary mode based on the spectrum of the _{angular velocity ω z (see FIG. 10).} Then, in the present embodiment in which φ1 is within a predetermined range, when −50 ° ≦ φ1 ≦ 5 °, the hitting point of the ball is in any of the regions A3 and A4 near the center in the toe-heel direction. It is determined that it is included, and the process proceeds to step S78. In other cases, the process proceeds to step S73. It should be noted that, in the case where the ball collides with the face center Fc deviated from the face center Fc in the toe-heel direction to the toe side and the case where the ball collides with the heel side deviated from each other, the analysis data is associated with the twisting period in which the phase angle φ1 is deviated by 90 ° from each other. It is considered that the waveform of is generated. On the other hand, when the collision occurs near the face center Fc in the toe-heel direction, the phase angle φ1 becomes near 0 °. Therefore, when the phase angle φ1 is near 0 °, in this case −50 ° ≦ φ1 ≦ 5 °, it can be estimated that the ball has collided near the center in the toe-heel direction.

In step S73, RBI estimation unit 24B includes, omega based on the amplitude spectrum of _x, an index indicating the magnitude of the amplitude spectrum of the omega _x in higher order modes (e.g. cubic or quartic mode) or the corresponding frequency to H Is derived. In the present embodiment, as the index H, the integrated value of the amplitude spectrum _{of ω x} in the frequency band from 150 Hz to 350 Hz where the fourth-order mode is considered to appear is calculated. Then, it is determined whether H is equal to or less than a predetermined threshold value, and if it is equal to or less than the threshold value, it is determined that the hitting point of the ball is included in any of the regions A7 and A8 near the inertial spindle, and the process is performed in step S75. Proceed to. In other cases, it is determined that the hitting point of the ball is included in any of the remaining areas A1, A2, A5, and A6, and the process proceeds to step S74. When the ball collides on the face surface 41a near the inertial spindle, the head 41 does not rotate much, when the ball collides at the upper part, the face surface 41a falls further backward, and when the ball collides at the lower part, the face The surface 41a stands up more (see FIG. 8). As a result, when the ball collides with the face surface 41a near the inertial spindle, it tends to be difficult for a high frequency component to be generated in the time series data of _{ω x.} Step S73 uses this principle to determine whether or not the hitting point exists near the inertial spindle on the face surface 41a according to the magnitude of the index H indicating the magnitude of the amplitude spectrum in the high frequency mode. ing.

In step S73, as an index H for determining whether or not the hitting point exists near the inertial spindle, the magnitude of the amplitude spectrum of _{the acceleration a y} corresponding to the higher-order mode is used instead _{of the angular velocity ω x.} An index to represent can also be used.

In step S74, the hitting point estimation unit 24B determines whether the above-mentioned phase angle φ1 is larger than a predetermined value or, in the present embodiment, larger than −5 °. If it is larger than −5 °, it is determined that the hitting point of the ball is included in the toe-side regions A1 and A2, and the process proceeds to step S77. In other cases, it is determined that the hitting point of the ball is included in the areas A5 and A6 on the heel side, and the process proceeds to step S76. When the ball deviates from the face center Fc to the toe side and collides, a waveform of analysis data such that the phase angle φ1 becomes positive is generated, and when the ball deviates to the heel side and collides, the phase angle φ1 It is considered that the waveform of the analysis data in which is negative is generated. Therefore, it is possible to estimate whether the ball collides on the face surface 41a on the toe side or the heel side depending on whether the phase angle φ1 is positive or negative.

In step S75, the same determination as in step S74 is performed. Specifically, in step S75, the hitting point estimation unit 24B determines whether or not the above-mentioned phase angle φ1 is larger than a predetermined value, and if it is large, the hitting point of the ball is included in the toe side region A7. In other cases, it is determined that the area A8 on the heel side is included. After step S75, the process proceeds to step S79.

In step S76, the hitting point estimation unit 24B sets the _{specific frequency f m} included in the frequency band in which the higher-order mode (typically the third-order or fourth-order) appears based on the spectrum of the _{angular velocity ω x.} The corresponding phase angle φ2 is derived. In the present embodiment, the phase angle φ2 is a phase angle near 200 Hz in which the fourth-order mode is considered to appear. Then, the hitting point estimation unit 24B determines that the hitting point of the ball is included in the upper region A5 in the case of 0 ° ≦ φ2 in the present embodiment in which φ2 is equal to or larger than a predetermined value. On the other hand, in the present embodiment in which φ2 is smaller than a predetermined value, it is determined that the hitting point of the ball is included in the lower region A6 when 0 °> φ2. The graph of the phase angle of _{the angular velocity ω x} when the hitting point is shifted upward from the face center Fc and when it is shifted downward is as shown in FIG. Therefore, when paying attention to the phase angle φ2 at a specific frequency f _m, it is possible to estimate whether the phase angle φ2 is a predetermined value or more, and whether it is an upper hitting point or a lower hitting point.

In the step S76, as an index φ2 for determining the vertical position of RBI, instead of the angular velocity omega _x, it may be used a phase angle corresponding to a specific frequency f _m of the spectrum of the acceleration a _y ..

Further, in the present embodiment, the specific frequency f _m is determined according to the flex which is one of the characteristics of the shaft 40. Specifically, the hitting point estimation unit 24B determines the _{frequency f m} by collating the flex specified in step S2 with the following table 1 stored in advance in the storage unit 23. Since Table 1 is a table _{for determining the frequency f m} in a certain head type, a table for determining the _{frequency f m may be stored in the head according to the type.} In this case, the data acquisition unit 24A causes the user to input the head type, and the frequency f _m is selected from a plurality of tables such as Table 1 corresponding to the plurality of heads according to the input head type. Select a specific table to determine.

The influence of the impact of the ball on the face surface 41a is transmitted to the sensor unit 1 attached to the head 41 or the grip 42 via the shaft 40. Therefore, the waveform of the sensor data output from the sensor unit 1 is easily affected by the characteristics of the shaft 40. In this regard, in step S76 according to the present embodiment, since the index φ2 for determining the vertical position of the hitting point is determined in consideration of the flex, the accuracy of estimating the hitting point by the index φ2 is improved. The information in Table 1 can be used, for example, by performing a large number of trial hits in advance, and based on the data at this time, the optimum frequency for determining the index φ2 can be calculated by a parameter study.

In step S77, the same determination as in step S76 is performed. Specifically, in step S77, the hitting point estimation unit 24B determines whether or not the above-mentioned phase angle φ2 is equal to or greater than a predetermined value, and if it is equal to or greater than a predetermined value, the hitting point of the ball is in the upper region A1. If it is smaller than a predetermined value, it is determined that it is contained in the lower region A2. After step S77, the process proceeds to step S79.

Further, in step S78, the same determination as in steps S76 and S77 is performed. Specifically, in step S78, the hitting point estimation unit 24B determines whether or not the above-mentioned phase angle φ2 is equal to or greater than a predetermined value, and if it is equal to or greater than a predetermined value, the hitting point of the ball is in the upper region A3. If it is smaller than a predetermined value, it is determined that it is contained in the lower region A4. If it is determined in step S78 that the hitting point is included in the area A3, the process proceeds to step S79. In other cases, step S7 ends.

The exception handling in step S79 is a step in which the validity of the area classification in steps S71 to S78 is checked from another index, and if it is determined to be incorrect, appropriate correction is made. Specifically, the hitting point estimation unit 24B determines whether or not the area classified in steps S71 to S78 is included in the left column according to the information in Table 2 stored in advance in the storage unit 23, and includes the area. If so, it is determined whether at least one of the exception conditions on the right side of Table 2 is satisfied, and if it is satisfied, a dot is made to the area shown on the right side of Table 2. Reclassify.

In the present embodiment, as shown in Table 2, the vertical position of the hitting point is corrected by the exception handling in step S79. Therefore, the index referred to here is an index having a high correlation with the position of the hitting point in the vertical direction (at least at the position of the hitting point in the toe-heel direction specified by steps S71 to S78), and is an index having a high correlation with the position of the hitting point in the vertical direction. _{Then, the indexes C ts2 to} C _ts5 , C _ts8 , and C _ts10 described later, which are a part of the indexes calculated in step S6. Further, the exception condition is determined by whether or not the index exceeds the threshold value. When the above processing is completed, step S7 ends.

In the following step S8, the hitting point estimation unit 24B determines _{the hitting point D th} of the ball in the toe-heel direction on the face surface 41a according to _{the indexes C th1} , C _th2 , ..., C _{thN derived in step S6.} presume. More specifically, the _{dot D th} is calculated according to the following equation with the _{dot D th} as the objective variable and the indices C _th1 , C _th2 , ..., C thN as the explanatory variables. However, the values of the coefficients k _th0 , k _th1 , k _th2 , ..., K _thN used here are determined for each of the regions A1 to A8. Therefore, in step S8, a set of coefficients corresponding to the region finally classified in step S7 is selected from the set of these plurality of coefficients and used for estimating the hitting point.
D _th = k _th0 + k _th1・ C _th1 ＋ k _th2・ C _th2 ＋ ・ ・ ・ ＋ k _thN・ C _thN (1)

The values of the coefficients k _th0 , k _th1 , k _th2 , ..., K _thN are calculated by experiments and stored in advance in the storage unit 23 as coefficient data 28. Specifically, a large number of trial hits are performed, the hit points D _th and the indexes C _th1 , C _th2 , ..., C _thN at each trial hit are calculated, and the coefficients k _th0 , k are calculated by multiple regression analysis. _th1 , k _th2 , ..., k _thN are specified. The hitting point used for the multiple regression analysis can be determined with high accuracy by, for example, taking a picture of the golf swing using a plurality of cameras and performing image processing on the obtained image. Further, in this experiment, the hitting points at the time of each test hit are classified into any of the regions A1 to A8 according to the same algorithm as in step S7. Then, by executing the multiple regression analysis for each of these regions A1 to A8, the coefficients k _th0 , k _th1 , k _th2 , ...・, Calculate _{k thN.}

Similarly, the hitting point estimation unit 24B estimates _{the hitting point D ts} of the ball in the top-sole direction on the face surface 41a according to _{the indexes C ts1} , C _ts2 , ..., C _{tsM derived in step S6.} .. More specifically _{, the hitting point D ts} is calculated according to the following equation with the hitting _{point D ts} as the objective variable and the indices C _ts1 , C _ts2 , ..., C _{tsM as the explanatory variables.} However, the values of the coefficients k _ts0 , k _ts1 , k _ts2 , ..., K _tsM used here are also defined for each of the regions A1 to A8. Therefore, in step S8, a set of coefficients corresponding to the region finally classified in step S7 is selected from the set of these plurality of coefficients and used for estimating the hitting point. The values of the coefficients k _ts0 , k _ts1 , k _ts2 , ..., K _tsM are also calculated in advance by the same experiment as for the values of the coefficients k _th0 , k _th1 , k _th2 , ..., K _thN. , The coefficient data 28 is stored in advance in the storage unit 23.
D _ts = k _ts0 ＋ k _ts1・ C _ts1 ＋ k _ts2・ C _ts2 ＋ ・ ・ ・ ＋ k _tsM・ C _tsM (2)

Incidentally, necessarily RBI D _th estimate all indicators C _th1, C _th2 used in the, ..., is C _thN, need not have a RBI D _th high correlation. Even if some indicators with low correlation exist, in that case, the coefficient k _thi of the multiple regression equation corresponding to such indicators is set small. Therefore, the accuracy of the estimated value of the _dot D th is maintained as long as at least a part of the index has a high correlation. Of course, the index C _thi having a low correlation may be omitted from the multiple regression equation. _{The same applies} to the indexes C ts1, C _ts2 , ..., C _tsM for estimating the hitting point D _ts .

In the following step S9, the miss shot determination unit 24C makes a miss shot determination. Specifically, missed shot determining unit 24C is an index C _th1 -C _th5 calculated in step _S6, C _th8 ~C th10 and _{C ts1 ~C ts5, C ts8 ~C} ts10 are each within a predetermined range Determine if it exists. When the indicator _{C th1 ~C th5, C th8 ~C} th10 and _{C ts1 ~C ts5, C ts8 ~C} ts10 is outside a predetermined range, it determines that missed shot. In the present embodiment, the threshold value used for the miss shot determination (the boundary value that defines the above-mentioned predetermined range) is set for each of the areas A1 to A8, and in step S9, it is finally classified in step S7. A miss shot determination is made based on the threshold value corresponding to the determined area. Further, in the present embodiment, when at least one of the indices _{C th1 ~C th5, C th8 ~C} th10 and _{C ts1 ~C ts5, C ts8 ~C} ts10 but that is outside the predetermined range, is missed shot Is determined.

Further, in step S9, the miss shot determination unit 24C makes a miss shot determination from another viewpoint. That is, when the hitting points (D _th , D _ts ) derived in step S8 are outside the predetermined range, for example, when -40 _{mm ≤ D th} ≤ 40 mm and -30 _{mm ≤ D ts} ≤ 30 mm are not satisfied. It is determined to be a miss shot.

If it is determined that the shot is a miss shot by the above processing, the processing proceeds to step S11. If not, the process proceeds to step S10.

In step S10, the result output unit 24D _{displays the information of the hit points (D th} , D _ts ) derived in step S8 on the display unit 21. At this time, the coordinates of the hitting point may be displayed numerically, or in place of or in addition to this, an image in which the figure showing the position of the hitting point is superimposed on the figure showing the face surface 41a is generated, and the hitting point is represented by the figure. It may be displayed as a target. On the other hand, in step S11, the result output unit 24D displays a message such as "The hitting point cannot be estimated because it hits the end of the face" on the display unit 21. After steps S10 and S11, the hitting point estimation process ends.

<2-1. Indicator>
Hereinafter, the indicators C _th1 , C _th2 , ..., C _thN and C _ts1 , C _ts2 , ..., C _{tsM according} to the present embodiment will be described. In this embodiment, N = M = 11 and the index C _thi = C _tsi (i = 1, 2, ..., 11).

<2-1-1. First-order peak amplitude of the spectrum of angular velocity ω _z>
The first index C _th1 = C _{ts1 according} to the present embodiment is the angular velocity around the axis in the shaft 40 direction, that is, the peak amplitude of the primary mode of the spectrum of _{ω z (see FIG. 10).} This index represents the torsional component of the shaft 40. In addition, according to the experiment conducted by the present inventor, it was confirmed that _{this index has a high correlation with the hitting point D th in the left-right direction.} In this experiment, a golf club having an acceleration sensor and an angular speed sensor attached to the grip end, similar to the golf club 4 according to the present embodiment, is used to play golf many times (a total of about 30 balls) for one golfer. A swing was performed and sensor data of acceleration and angular velocity were acquired. In this case, the sampling period Delta] t = 1 ms, between t _i -2s~t _i + 0.5s, measurements were taken. The sensor data was acquired so that the hit points were totally dispersed on the face surface 41a. Then, based on the measured data, the indexes C _th1 , C _th2 , ..., C _thN and C _ts1 , C _ts2 , ..., C _tsM were calculated. In addition, the state of the golf swing was photographed using a plurality of cameras at the same time, and the hitting point specified by this was taken as the true value. Then, the correlation between the true value of this RBI and the index C _th1 = C _ts1 was investigated. The verification results regarding the correlation of the second to fifth and eighth to tenth indicators described below are also obtained through this experiment.

<2-1-2. Second-order peak amplitude of the spectrum of acceleration a _y>
The second index C _th2 = C _{ts2 according} to the present embodiment is the acceleration in the direction of the fly ball, that is, the peak amplitude of the secondary mode of the spectrum of _{a y (see FIG. 11).} This index represents the bending component of the shaft 40. Further, according to the experiment conducted by the present inventor, it was confirmed that this index has a high correlation with both _{the vertical hitting point D ts} and the horizontal hitting point D _th.

<2-1-3. Second-order peak amplitude of the spectrum of angular velocity ω _x>
The third index C _th3 = C _{ts3 according} to the present embodiment is the angular velocity around the axis in the toe-heel direction, that is, the peak amplitude in the secondary mode of the spectrum of _{ω x (see FIG. 12).} This index represents the bending component of the shaft 40. Further, according to the experiment conducted by the present inventor, it was confirmed that this index has a high correlation with both _{the vertical hitting point D ts} and the horizontal hitting point D _th. In particular, the correlation with the _{hitting points D ts in the vertical direction was high.}

<2-1-4. Maximum amplitude of the spectrum of acceleration _{az in a given frequency band>}
The fourth index C _th4 = C _{ts4 according} to the present embodiment is the acceleration in the shaft 40 direction, that is, the maximum amplitude in a predetermined frequency band (around 50 to 100 Hz) of the spectrum of _{az (see FIG. 13).} .. This index represents the vertical vibration component of the shaft 40. In addition, according to the experiment conducted by the present inventor, it was confirmed that _{this index has a high correlation with the hitting point D ts in the vertical direction.}

<2-1-5. Maximum value of angular velocity ω _{y immediately after impact>}
Index C _th5 = C _ts5 fifth according to the present embodiment, the angular velocity about the flight trajectory direction axis, i.e., the maximum value immediately after the impact of the omega _y (e.g., 0.1 seconds after the time t _i) There is (see FIG. 14). This index represents the shear component of the head 41. Further, according to the experiment conducted by the present inventor, it was confirmed that this index has a certain degree of correlation with both _{the vertical hitting point D ts} and the horizontal hitting point D _th.

<2-1-6. Angular velocity at impact ω _x ＞
The sixth index C _th6 = C _{ts6 according} to the present embodiment is the angular velocity around the axis in the toe-heel direction at the time of impact, that is, ω _x at the time of impact. This index is an index for evaluating the type and ability of golfers.

<2-1-7. Angular velocity at impact ω _z ＞
The seventh index C _th7 = C _{ts7 according} to the present embodiment is the angular velocity around the axis in the shaft 40 direction at the time of impact, that is, ω _z at the time of impact. This index is an index for evaluating the type and ability of golfers.

<2-1-8. Amplitude of angular velocity ω _x>
The eighth index C _th8 = C _{ts8 according} to the present embodiment is the angular velocity around the axis in the toe-heel direction, that is, the amplitude of _{ω x.} In the present embodiment, it is the difference between the maximum value and the minimum value in a predetermined period (from impact to 0.1 seconds later). When the same verification as the first to fifth indexes was performed, it was confirmed that this index had a high correlation with the _{hitting points D ts in the vertical direction.}

<2-1-9. Amplitude of angular velocity ω _y>
The ninth index C _th9 = C _{ts9 according} to the present embodiment is the angular velocity around the axis in the face-back direction, that is, the amplitude of _{ω y.} In the present embodiment, it is the difference between the maximum value and the minimum value in a predetermined period (from impact to 0.1 seconds later). When the same verification as the first to fifth indexes was performed, it was confirmed that this index had a high correlation with the _{hitting point D th in the left-right direction.}

<2-1-10. Amplitude of angular velocity ω _z>
The tenth index C _th10 = C _{ts10 according} to the present embodiment is the angular velocity around the z-axis, that is, the amplitude of _{ω z.} In the present embodiment, it is the difference between the maximum value and the minimum value in a predetermined period (from impact to 0.1 seconds later). When the same verification as the first to fifth indexes was performed, it was confirmed that this index had a high correlation with the _{hitting point D th in the left-right direction.}

<2-1-11. Head speed at impact v _h ＞
The eleventh index C _th11 = C _{ts11 according} to the present embodiment is the head speed v _h at the time of impact. The head velocity v _h can be calculated if there is data of acceleration a _x , a _y , a _z and angular velocity ω _x , ω _y , ω _{z, and various calculation methods are known.} Explanation is omitted.

<2-2. Verification ＞
Hereinafter, the verification result of the accuracy of the above-mentioned dot estimation process will be described. The present inventors made five golfers perform a test swing using a golf club having an acceleration sensor and an angular velocity sensor attached to the grip end, similar to the golf club 4 described above. As a result, sensor data of acceleration and angular velocity for a total of 441 balls were acquired. The sensor data here was acquired so that the hitting points were totally dispersed on the face surface. _{In addition to the above sensor data, the data of the dots D th} and D _ts (true values) specified with high accuracy by the system using the above-mentioned multiple cameras were also acquired.

Then, the sensor data is set according to the flowchart shown in FIG. 5 except that the phase angle φ2 used in step S7 is set to a uniform (200 Hz) value without changing according to the flex and the exception handling in step S79 is omitted. The hit points D _th and D _ts (experimental values) were estimated from. Furthermore, the experimental values of the hit points D _th and D _ts were compared with the true values, and the error was calculated. FIG. 15 shows the percentage of correct answers when the error is within the range of ± 10 mm and the case where the error is within the range of ± 5 mm for each of the hit _{points D th in the} left-right direction and the hit _{points D ts in the vertical direction.} It is a graph.

_{Further, the hit points D th} and D _ts (experimental values) were estimated according to the same algorithm as the flowchart shown in FIG. FIG. 16 is a graph showing the results of calculating the correct answer rate similar to that in FIG. 15 using the experimental values at this time. From the results of FIGS. 15 and 16, it was confirmed that the index φ2 was changed according to the characteristics of the shaft and that the exception handling was superior.

Further, FIG. 17 is a graph showing the frequency of occurrence of the peak frequency in the fourth-order mode of the spectrum of the _{angular velocity ω x} for the sensor data for the above total of 441 balls. In FIG. 17, a graph for each flex of the shaft is drawn. And, as is clear from the figure, it can be seen that the value of the peak frequency of the fourth-order mode of the spectrum of the _{angular velocity ω x is different when the flex is different.} Therefore, from FIG. 17, it is possible to understand the significance of changing the frequency for determining the index φ2 for classifying the upper and lower parts of the hitting point.

<3. Modification example>
Although one embodiment of the present invention has been described above, the present invention is not limited to the above embodiment, and various modifications can be made without departing from the spirit of the present invention. For example, the following changes are possible. In addition, the gist of the following modifications can be combined as appropriate.

<3-1>
In the above embodiment, in step S8, a multiple regression equation for calculating the _{hit points D th and} D _{ts is prepared for each of the regions A1 to A8.} However, the multiple regression equation used in step S8 may be different depending on the classification according to the characteristics of the shaft 40 in addition to the classification according to the regions A1 to A8. That is, a set of coefficients of the multiple regression equation is prepared, for example, as many as the number of classifications of the region × the number of classifications of the shaft characteristics. In such a case, in an experiment conducted in advance to determine the coefficient data 28, perform multiple regression analysis for each new classification, and store the coefficient data obtained by this in the storage unit 23. Just do it.

This modification can be implemented, for example, as follows. That is, in step S8, the hitting point estimation unit 24B includes the flex input in step S2 and the region finally determined in step S7 from among the many multiple regression equations stored in the storage unit 23. Select a specific multiple regression equation corresponding to. Then, by substituting _{the indices C th1} , C _th2 , ..., C _thN and C _ts1 , C _ts2 , ..., C _tsM derived in step S6 into this specific multiple regression equation, the dot D Estimate _th and D _ts.

Further, the classification according to the regions A1 to A8 can be omitted, and the multiple regression equation used in step S8 can be changed according only to the characteristics of the shaft 40.

As described above, the influence of the impact of the ball on the face surface 41a is transmitted from the head 41 to the sensor unit 1 attached to the grip 42 via the shaft 40. Therefore, the waveform of the sensor data is easily affected by the characteristics of the shaft 40. In this respect, in this modification, the multiple regression equation is determined for each type of the shaft 40, and the multiple regression equation is selected according to the characteristics of the shaft, so that the accuracy of estimating the hitting point is improved.

In addition to the flex described above, the characteristics of the shaft 40 referred to in this modification can be classified according to torque, tone, and the like. Of course, it is possible to classify only by torque and only by tone, and it is also possible to classify by arbitrarily combining flex, torque and tone. Torque is an index showing the ease of twisting (torsional rigidity) of the shaft 40. The tone is an index indicating where the point where the shaft 40 is improved (low rigidity) is located, and the types of the tone include a leading tone, a former tone, and a medium tone. The first tone means that the rigidity of the tip side (head side) of the shaft 40 is relatively low, the original tone means that the rigidity of the butt side (grip side) is relatively low, and the middle tone means that the rigidity is low. , Means that the rigidity near the center is relatively low.

<3-2>
The indexes C _th and C _{ts for obtaining the} hit points D _th and D ts are not limited to the above-mentioned examples, and depend on the _{hit points D th} and D _ts (preferably, have a large correlation with the _{hit points D th} and D _ts). It can be any index. Further, for example, the following indexes (1) to (5) can also be used as indexes for estimating the _{hit points D th} and D _ts.

(1) Peak amplitude in the primary mode of the spectrum of _{ω x} , a _y (especially suitable for estimating the _{dot D ts in the vertical direction)}
(2) Peak amplitude in the secondary mode of the spectrum of _{ω y} (especially suitable for estimating the _{dot D ts in the vertical direction)}
(3) _{Maximum value of ω x} immediately after impact (especially suitable for estimating the hitting point D _{ts in the vertical direction)}
(4) At least one of the peak amplitude and the phase angle of the high frequency mode (for example, 3rd or 4th order mode) of the spectrum of _{ω x} , a _y (especially suitable for estimating the _{dot D ts in the vertical direction).}
(5) At least one of the peak amplitude and the phase angle of the high frequency mode (for example, 3rd or 4th order mode) of the spectrum of _{ω z} (particularly suitable for estimating the _{dot D th in the left-right direction).}

<3-3>
In the above embodiment, the sensor unit 1 having the acceleration sensor 11 and the angular velocity sensor 12 is used, but the sensor unit 1 may have another configuration. For example, the acceleration sensor 11 can be omitted when the hitting point is estimated only from the angular velocity data, and conversely, the angular velocity sensor 12 can be omitted when the hitting point is estimated only from the acceleration data. can.

<3-4>
The mounting location of the sensor unit 1 is not limited to the grip 42, and may be mounted on the shaft 40.

<3-5>
In the above embodiment, the multiple regression equation is used as the regression equation for finding the hitting point, but a simple regression equation can also be used. Further, a non-linear regression equation may be used instead of the linear regression equation. In order to evaluate the non-linearity of the relationship between the hit point and the index, for example, the following method can be used.
(1) The regression equation is provided with an explanatory variable N-th power term, (N ≧ 2), and an interaction term.
(2) Build machine learning (neural network).

<3-6>
In the above embodiment, the local coordinate system of the sensor unit 1 is set as shown in FIG. 3, but it can be set arbitrarily. Further, the axis for defining the coordinates of the hitting point _{is not limited to the D th} axis and the D _ts axis, and can be set arbitrarily. For example, the inertial main axis on the face surface 41a is set as the first axis and is orthogonal to the axis. The axis to be used can be the second axis. Further, the position of the hitting point can be specified not in the coordinates but in the area such as the areas A1 to A8.

1 Sensor unit 11 Accelerometer 12 Angular velocity sensor 2 Dot point estimation device (computer)
24A data acquisition unit (acquisition unit)
24B RBI estimation unit (estimation unit)
3 RBI estimation program 4 Golf club 40 Shaft 41 Head 41a Face surface 42 Grip

Claims (4)

A hitting point estimation device that estimates the hitting point on the face surface of the head when a golf club having a grip, a shaft, and a head is swung to hit a golf ball.
An acquisition unit that acquires time-series sensor data output from at least one of the angular velocity sensor and the acceleration sensor attached to at least one of the grip and the shaft.
It is provided with an estimation unit that estimates the hitting point based on the sensor data.
Based on the sensor data, the estimation unit determines whether or not the hitting point exists in the vicinity of the inertial spindle on the face surface.
RBI estimation device. The estimation unit derives an index depending on the hitting point from the sensor data, and determines whether or not the hitting point exists in the vicinity of the inertial spindle on the face surface according to the index.
The dot estimation device according to claim 1. As the index, the estimation unit indicates the magnitude of the spectrum corresponding to a predetermined mode or a predetermined frequency of the angular velocity around the axis in the toe-heel direction or a direction substantially parallel to the toe-heel direction, or the face-back direction or the like. Whether a predetermined mode of acceleration in a substantially parallel direction or a spectrum size corresponding to a predetermined frequency is derived, and the hitting point is present on the face surface in the vicinity of the inertial spindle according to the spectrum size. Judge whether or not,
The hitting point estimation device according to claim 2. A hit point estimation program that estimates the hit points on the face surface of the head when a golf club having a grip, a shaft, and a head is swung to hit a golf ball.
A step of acquiring time-series sensor data output from at least one of the angular velocity sensor and the acceleration sensor attached to at least one of the grip and the shaft.
A step of estimating the hitting point based on the sensor data, and
Let the computer run
The step of estimating the hitting point includes a step of determining whether or not the hitting point exists in the vicinity of the inertial spindle on the face surface based on the sensor data.
RBI estimation program.

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