JP2010091396A - Device and method for detecting decrease in tire air pressure, and program for detecting decrease in tire air pressure - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a device for detecting decrease in air pressure of tire for stably determining the decrease in pressure, even under an environment of small pressure decrease sensitivity. <P>SOLUTION: The device for detecting decrease in tire air pressure includes: a means for detecting information on the rotational speed of each wheel tire of a vehicle; a means for estimating the frequency characteristics of the information on the rotational speed from the information on rotary speed; and a means for determining the decrease in tire air pressure, based on the estimated frequency characteristics. The frequency characteristic estimation means includes a means for estimating parameters of a linear model to a time series signal, including the information on rotary speed. The determination means includes: a means for matching the scale of a gain by minimizing the gain at the first frequency selected appropriately and normalizing the entire frequency characteristics, in a band including a resonance peak; a means for calculating the area of a region created between the first frequency of the band and a reference frequency by reference frequency characteristics, obtained at the time of initialization and those estimated at current time; and a means for scaling the calculated area between -1 and 1. <P>COPYRIGHT: (C)2010,JPO&INPIT

Description

  The present invention relates to a tire pressure drop detection apparatus and method for detecting a tire pressure drop based on a resonance frequency of a tire of a running vehicle, and a tire pressure drop detection program.

  One of the factors that enable a car to travel safely is the tire air pressure. If the air pressure falls below an appropriate value, the steering stability and fuel consumption are deteriorated, which may cause tire bursts. For this reason, a tire pressure monitoring system (TPMS) that detects a decrease in tire pressure and issues an alarm to the driver to prompt appropriate measures is important from the standpoint of environmental conservation and ensuring driver safety. Technology.

  Conventional alarm devices can be classified into two types, a direct detection type and an indirect detection type. The direct detection type directly measures tire air pressure by incorporating a pressure sensor inside the tire wheel. While it is possible to detect a decrease in air pressure with high accuracy, there are technical and cost issues such as the need for a dedicated wheel and the problem of fault-tolerant performance in the actual environment.

  On the other hand, the indirect detection type is a method of estimating air pressure from tire rotation information, and is a dynamic load radius (DLR) method and a resonance frequency (RFM) method (for example, see Patent Document 1). Can be subdivided. The DLR method uses a phenomenon in which the dynamic load radius becomes smaller due to the crushed tire being crushed during driving, and as a result, it rotates faster than a normal pressure tire, and the pressure drop is reduced by comparing the rotation speeds of the four tires. This is a detection method. Since calculation processing can be performed relatively easily using only the wheel rotation speed signal obtained from the wheel speed sensor, research has been extensively conducted mainly for the purpose of detecting puncture of one wheel. However, since the rotational speeds of the wheels are merely compared, it is impossible to detect the case where the four wheels are depressurized simultaneously (natural leakage). In addition, since wheel speed differences also occur depending on traveling conditions such as turning of the vehicle, acceleration / deceleration, and load bias, there is a problem that pressure reduction cannot be detected accurately through all traveling states.

  On the other hand, the RFM method is a method for detecting a difference from the normal pressure by utilizing the change in the frequency characteristics of the wheel speed signal due to the reduced pressure. Unlike the DLR method, since it is an absolute comparison with the normal value of each wheel that has been held in advance, it can be used for simultaneous depressurization of four wheels, and is attracting attention as a better indirect detection method. However, depending on the driving conditions, there is a problem that the estimated value of the frequency in the target region is not robust to the vehicle speed and the road surface condition due to strong noise or the like. The present invention relates to a tire state detection device based on an RFM system. Hereinafter, the basic principle of the RFM method will be described in more detail.

  When the vehicle travels, the torsional motion in the front-rear direction that appears when the tire receives a force from the road surface and the motion in the front-rear direction of the suspension cause a coupled resonance. Since this resonance phenomenon also affects the rotational movement of the wheel, information on the resonance phenomenon is also present in the wheel speed signal acquired from the wheel sensor mounted on the anti-lock braking system (ABS). included. In addition, since coupled resonance is an inherent vibration mode due to the torsional rigidity of the tire, its excited state changes only depending on changes in the air pressure that constitutes the physical characteristics of the tire, and changes in vehicle speed and road surface There is almost no dependence. That is, since the dynamics of the torsional motion of the tire changes as the air pressure decreases, when the wheel speed signal is analyzed by frequency, the peak created by the coupled resonance (resonance peak) appears on the lower frequency side during normal pressure than during normal pressure.

  FIG. 8 shows a case where tires with normal air pressure and tires with a pressure reduced by 25% from normal pressure are mounted on a vehicle, and the respective wheel acceleration signals (time difference of wheel speed signals) obtained during a certain period of time are calculated. It represents a power spectrum obtained by applying a Fast Fourier Transform (FFT) to (obtained).

  The component in the vicinity of 40 to 50 Hz is the vibration that occurs when the vibration in the longitudinal direction of the tire and the suspension of the vehicle resonate, and the frequency having the peak value (resonance frequency) moves to the lower frequency side due to the change in internal pressure. I understand that. Because this phenomenon appears independently from the above-mentioned characteristics, such as the type of tire or vehicle, traveling speed, road surface condition, etc., the RFM method focuses on this resonance frequency and is relatively in comparison to the reference frequency estimated at initialization. An alarm is issued when it is judged to be low. Here, it is necessary to estimate the resonance frequency from the wheel speed signal acquired from the ABS, but it is difficult to store the necessary time series data in an in-vehicle computer with limited calculation resources, so frequency analysis by FFT Is difficult to do. For this reason, in the conventional method, the resonance frequency is estimated using an online method described below.

Since vibration can be described by a quadratic model, a time series analysis is performed on the wheel speed signal based on a quadratic autoregressive (AR) model. Specifically, parameters θ = {a ₁ ,..., A _K } in the model represented by the following equation (1) are estimated by a Kalman filter (sequential least square method).

Here, y (t) represents the wheel speed at time t, ε represents white noise, and K represents the order of the model (here, since a quadratic model is assumed, K = 2). . Since the frequency corresponding to the pole of the transfer function representing the AR model is estimated as the resonance frequency, the resonance frequency can be accurately obtained if the resonance peak is correctly extracted by the model.

Japanese Patent Laid-Open No. 5-133831

However, depending on the type of tire or vehicle, the difference in resonance frequency between normal pressure and reduced pressure (hereinafter referred to as “decompression sensitivity”) may be small. When the influence of noise mixed independently of the target signal becomes relatively large, such as when driving on a smooth road, it is difficult to stably estimate the resonance frequency. When the resonance frequency is smaller than the estimated variance, it is difficult to accurately determine the pressure reduction. In such a case, in addition to the resonance frequency, another index that changes depending on the tire pressure may be used as an auxiliary.
The present invention has been made in view of such circumstances, and in addition to the resonance frequency, the area of the region created by the two frequency characteristics at normal pressure and at the time of pressure reduction is used as an auxiliary index, thereby reducing the pressure reduction sensitivity. It is an object of the present invention to provide a tire air pressure drop detection device and method capable of performing stable decompression determination even in a small environment, and a tire air pressure drop detection program.

A tire pressure drop detecting device according to a first aspect of the present invention (hereinafter also simply referred to as “detecting device”) includes a rotational speed information detecting means for periodically detecting rotational speed information of tires of each wheel of a vehicle,
From the rotational speed information obtained by the rotational speed information detecting means, a frequency characteristic estimating means for estimating the frequency characteristics of the rotational speed information,
Determining means for determining a decrease in the tire air pressure based on the estimated frequency characteristics,
The frequency characteristic estimation means includes parameter estimation means for estimating a linear model parameter for a time-series signal including the rotation speed information, and
The determination means includes
As a first step, a scaling unit that adjusts a gain scale by minimizing a gain at an appropriately selected first frequency and normalizing an entire frequency characteristic in a band including a resonance peak;
As a second step, an area calculating means for calculating an area of a region created between the first frequency of the band and the reference frequency based on the reference frequency characteristic obtained at the time of initialization and the currently estimated frequency characteristic; The third step is characterized by including scaling means for scaling the area calculated by the area calculating means between −1 and 1.

  In the detection apparatus according to the first aspect of the present invention, in addition to the resonance frequency, the area of the predetermined region created by the frequency characteristic at the normal pressure and the frequency characteristic at the time of pressure reduction is used as an auxiliary indicator for pressure reduction determination. Even if only the resonance frequency is used, even if it is buried in the estimated variance, it is possible to make a more robust and accurate decompression determination by adding the auxiliary index and performing the decompression determination in two dimensions.

A detection device according to a second aspect of the present invention includes a rotation speed information detection unit that periodically detects rotation speed information of a tire of each wheel of a vehicle,
From the rotational speed information obtained by this rotational speed information detecting means, rotational acceleration information calculating means for calculating tire rotational acceleration information;
From this rotational acceleration information, frequency characteristic estimation means for estimating the frequency characteristic of the rotational acceleration information,
Determining means for determining a decrease in the tire air pressure based on the estimated frequency characteristics,
The frequency characteristic estimation unit includes a parameter estimation unit that estimates a parameter of a linear model with respect to a time-series signal including the rotational acceleration information, and
The determination means includes
As a first step, a scaling unit that adjusts a gain scale by minimizing a gain at an appropriately selected first frequency and normalizing an entire frequency characteristic in a band including a resonance peak;
As a second step, an area calculating means for calculating an area of a region created between the first frequency of the band and the reference frequency based on the reference frequency characteristic obtained at the time of initialization and the currently estimated frequency characteristic; The third step is characterized by including scaling means for scaling the area calculated by the area calculating means between −1 and 1.

  Also in the detection device according to the second aspect of the present invention, it is possible to make a robust and accurate pressure reduction determination as in the detection device according to the first aspect. Moreover, in the detection apparatus which concerns on a 2nd viewpoint, although wheel acceleration data are used, since this wheel acceleration data changes less than wheel speed data, it can raise calculation precision.

The parameter estimation means can be configured to estimate the parameters of the linear model by the least square method. Since the parameter is estimated by the method of least squares, an optimum solution for given data can be obtained.

A tire air pressure drop detection method (hereinafter also simply referred to as “detection method”) according to a third aspect of the present invention includes a detection step of periodically detecting tire rotation speed information of each wheel of a vehicle,
From the rotation speed information obtained in this detection step, an estimation process for estimating the frequency characteristics of the rotation speed information;
A determination step of determining a decrease in air pressure of the tire based on the estimated frequency characteristic,
The estimating step is configured to estimate a parameter of a linear model with respect to a time-series signal including the rotation speed information; and
The determination step includes
A first step of adjusting a gain scale by minimizing a gain at an appropriately selected first frequency and normalizing an entire frequency characteristic in a band including a resonance peak;
A second step of calculating an area of a region formed between the first frequency of the band and the reference frequency by the reference frequency characteristic obtained at the time of initialization and the currently estimated frequency characteristic; and a second step And a third step of scaling the area calculated in step −1 to −1.

In the detection method according to the third aspect of the present invention, in addition to the resonance frequency, the area of the predetermined region created by the frequency characteristic at normal pressure and the frequency characteristic at the time of pressure reduction is used as an auxiliary indicator for pressure reduction determination. Even if only the resonance frequency is used, even if it is buried in the estimated variance, it is possible to make a more robust and accurate decompression determination by adding the auxiliary index and performing the decompression determination in two dimensions.

A detection method according to a fourth aspect of the present invention includes a detection step of periodically detecting rotation speed information of a tire of each wheel of a vehicle;
From the rotation speed information obtained in this detection step, a calculation step of calculating the rotational acceleration information of the tire,
From the rotational acceleration information obtained in this calculation step, an estimation step for estimating the frequency characteristics of the rotational acceleration information,
A determination step of determining a decrease in the tire air pressure based on the estimated frequency characteristics, and
The estimation step is configured to estimate a parameter of a linear model for a time series signal including the rotational acceleration information, and
The determination step includes
A first step of adjusting a gain scale by minimizing a gain at an appropriately selected first frequency and normalizing an entire frequency characteristic in a band including a resonance peak;
A second step of calculating an area of a region formed between the first frequency of the band and the reference frequency by the reference frequency characteristic obtained at the time of initialization and the currently estimated frequency characteristic; and a second step And a third step of scaling the area calculated in step −1 to −1.

Also in the detection method according to the fourth aspect of the present invention, as in the detection method according to the third aspect, robust and accurate pressure reduction determination can be performed. In the detection method according to the fourth aspect, the wheel acceleration data is used. However, since the wheel acceleration data is less changed than the wheel speed data, the calculation accuracy can be improved.

In the step of estimating the parameter, the linear model parameter can be estimated by a least square method. Since the parameter is estimated by the method of least squares, an optimum solution for given data can be obtained.

According to a fifth aspect of the present invention, there is provided a program for detecting a decrease in tire air pressure, a computer for detecting a decrease in tire pressure based on a resonance frequency of a tire in a running vehicle, and a rotation of a tire in each wheel of the vehicle. From the rotational speed information obtained by the rotational speed information detecting means for periodically detecting the speed information, the frequency characteristic estimating means for estimating the frequency characteristics of the rotational speed information, and the air pressure of the tire based on the estimated frequency characteristics Function as a determination means for determining a decrease in
The frequency characteristic estimation means includes parameter estimation means for estimating a linear model parameter for a time-series signal including the rotation speed information, and
The determination means includes
As a first step, a scaling unit that adjusts a gain scale by minimizing a gain at an appropriately selected first frequency and normalizing an entire frequency characteristic in a band including a resonance peak;
As a second step, an area calculating means for calculating an area of a region created between the first frequency of the band and the reference frequency based on the reference frequency characteristic obtained at the time of initialization and the currently estimated frequency characteristic; The third step is characterized by including scaling means for scaling the area calculated by the area calculating means between −1 and 1.

According to a sixth aspect of the present invention, there is provided a program for detecting a decrease in tire air pressure, a computer for detecting a decrease in tire pressure based on a resonance frequency of a tire in a running vehicle, and a rotation of a tire in each wheel of the vehicle. Rotational acceleration information calculating means for calculating tire rotational acceleration information from rotational speed information obtained by rotational speed information detecting means for periodically detecting speed information, and estimating frequency characteristics of the rotational acceleration information from the rotational acceleration information Functioning as frequency characteristic estimating means for determining, and determining means for determining a decrease in air pressure of the tire based on the estimated frequency characteristics;
The frequency characteristic estimation means includes parameter estimation means for estimating a linear model parameter for a time-series signal including the rotation speed information, and
The determination means includes
As a first step, a scaling unit that adjusts a gain scale by minimizing a gain at an appropriately selected first frequency and normalizing an entire frequency characteristic in a band including a resonance peak;
As a second step, an area calculating means for calculating an area of a region created between the first frequency of the band and the reference frequency based on the reference frequency characteristic obtained at the time of initialization and the currently estimated frequency characteristic; The third step is characterized by including scaling means for scaling the area calculated by the area calculating means between −1 and 1.

  According to the detection apparatus and method and the tire pressure drop detection program of the present invention, it is possible to make a pressure reduction determination stably even in an environment with a low pressure reduction sensitivity.

Hereinafter, embodiments of a detection apparatus and method and a tire pressure drop detection program according to the present invention will be described in detail with reference to the accompanying drawings.
As shown in FIG. 1, the detection device according to an embodiment of the present invention includes a left front wheel (FL), a right front wheel (FR), and a left rear wheel (RL) of four tires provided in a four-wheel vehicle. In order to detect the rotational speed information of the right rear wheel (RR), a normal wheel speed detecting means (rotational speed information detecting means) 1 provided in association with each tire is provided.

  The wheel speed detection means 1 generates power using rotation like a wheel speed sensor or dynamo for generating a rotation pulse using an electromagnetic pickup or the like and measuring the rotation angular speed and wheel speed from the number of pulses. It is possible to use an angular velocity sensor including that for measuring the rotational angular velocity and the wheel speed from this voltage. The output of the wheel speed detecting means 1 is given to a control unit 2 which is a computer such as ABS. The control unit 2 includes, for example, a liquid crystal display element for displaying that the tire is depressurized, a display 3 composed of a plasma display element or a CRT, an initialization button 4 that can be operated by a driver, An alarm device 5 is connected to notify the driver of tire decompression.

  As shown in FIG. 2, the control unit 2 stores an I / O interface 2a necessary for passing signals to and from an external device, a CPU 2b that functions as a center of arithmetic processing, and a control operation program for the CPU 2b. The ROM 2c and the RAM 2d from which data is temporarily written or the written data is read when the CPU 2b performs a control operation.

  The wheel speed detection means 1 outputs a pulse signal corresponding to the number of rotations of the tire (hereinafter also referred to as “wheel speed pulse”). Then, by sampling this wheel speed pulse every predetermined sampling period ΔT (seconds), for example, ΔT = 0.005 seconds, time-series data of the wheel speed signal can be obtained. Here, it is necessary to set the sampling period to a period sufficient to observe the band in which the resonance frequency of the tire of interest appears.

  The detection apparatus according to the present embodiment includes wheel speed detection means (rotation speed information detection means) 1, frequency characteristic estimation means for estimating frequency characteristics of the information from rotation speed information obtained by the wheel speed detection means, and estimation. And determining means for determining a decrease in the air pressure of the tire based on the frequency characteristics. The tire pressure drop detection program causes the control unit 2 to function as a frequency characteristic estimation unit and a determination unit. The frequency characteristic estimation means includes parameter estimation means for estimating a linear model parameter for a time-series signal including the rotation speed information. Further, as a first step, the determination means adjusts the gain scale by minimizing the gain at an appropriately selected first frequency and normalizing the entire frequency characteristic in a band including the resonance peak. Means, as a second step, an area calculation for calculating an area of a region formed between the first frequency of the band and the reference frequency based on the reference frequency characteristic obtained at the initialization and the currently estimated frequency characteristic. Means and scaling means for scaling the area calculated by the area calculating means between −1 and 1 as a third step.

In the present invention, in order to solve the above-described problem, a value calculated by the following method is used as an auxiliary index for pressure reduction determination together with the resonance frequency.
(1) First, as shown in FIG. 3, the gain scale is adjusted by minimizing the gain at an appropriately selected frequency and normalizing the entire frequency characteristic in an appropriate band including the resonance peak. In the example of FIG. 3, the gain at 25 Hz (first frequency) is set to the minimum value, and the frequency characteristics of 25 to 44 Hz, which is the band including the resonance peak, are normalized on a scale of 0 to 100. The solid line represents the characteristic at normal pressure, and the broken line represents the characteristic at 25% reduced pressure.

In the present invention, the gain in a certain range of frequencies (bHz to cHz) including the resonance frequency is normalized, but the lower limit value of this range, “bHz”, is caused by unsprung resonance present in the vicinity of 20 Hz. Undesirably affected by peaks. On the other hand, if it is too large, the resonance frequency is approached, and the effect of obtaining the area described later is reduced. Therefore, it is desirable to set between approximately 25 to 35 Hz (see the examples).
Further, since the area serving as the auxiliary index is obtained as a range from “bHz” to the reference resonance frequency (dHz) acquired at the time of initialization, as long as the condition of c> d is satisfied, “cHz” is the upper limit value of the range. "May be set in any way.

(2) Next, the area of a region formed between the minimum frequency of the band and the reference frequency is calculated based on the reference frequency characteristic obtained at the initialization and the frequency characteristic estimated at the present time (see FIG. 4). In FIG. 4, the solid line represents the reference frequency characteristic obtained at the time of initialization, and the broken line represents the frequency characteristic estimated at the present time.
(3) Finally, the area calculated in the previous section is scaled between −1 and 1.
At the time of pressure reduction determination, the estimated resonance frequency is similarly scaled and two-dimensional data is used together with the auxiliary index. That is, using the normal pressure and decompression data collected in a prior experiment or the like, an optimal discrimination line is determined in advance on a two-dimensional plane, and the actual decompression judgment was obtained during travel. The decompression judgment is performed by calculating to which side of the discrimination line the two-dimensional data is classified. As shown in the examples described later, since the pressure reduction sensitivity is higher than when each index is used independently, it is possible to perform more robust abnormality detection.

[Example]
In order to confirm the effectiveness of the detection method of the present invention, the discrimination performance using the class variance ratio (CVR) was evaluated. The CVRro, such as handwriting recognition and genetic discrimination is an index for evaluating the goodness of the system to perform certain classification feature quantity as an input, the following using the inter-class variance S _h and within-class variance S _w (2).

From equation (2), as the estimated variance S _w of the resonance frequency is low, also, CVR as decreased pressure sensitivity S _h is large, it is seen to take a large value.
5 to 7 show the evaluation results when the present invention is applied. Optimal one-dimensional feature axis (diagonal line drawn in dotted lines in FIGS. 5 to 7) that maximizes the CVR from a two-dimensional plane composed of two indices using Fisher Discriminant Analysis (FDA). ) And each data is projected onto this feature axis, it can be seen that the CVR is improved as compared to the case where only the resonance frequency is calculated. The auxiliary index in the present invention has a strong correlation with the resonance frequency, but is considered to contain independent information for discrimination, which is considered to improve discrimination performance.

  In the scatter diagram at the center in FIG. 5, “◯” marks indicate normal pressure conditions, and “X” marks indicate pressure reduction conditions. Further, the vertical axis represents the auxiliary index calculated in the above-described three steps (1) to (3) of the present invention, and the horizontal axis represents the reference resonance frequency stored at the time of initialization and the resonance frequency estimated at each time point. Represents an index obtained by normalizing the difference between -1 and 1. In the scatter diagram, an oblique line drawn with a dotted line is an optimal one-dimensional feature axis that maximizes the CVR. The graphs on the left and lower sides of the scatter diagram represent a one-dimensional scatter diagram for each axis and the distribution of estimated resonance frequencies by kernel density estimation using a Gaussian kernel. The numbers in each graph represent the class dispersion ratio evaluated using each index. In the above-described three steps (1) to (3) of the present invention, when the frequency characteristic is normalized in the first step (1), the target region is 25 to 44 Hz, and the gain of 25 Hz is the minimum value. Adopted. By applying the present invention, the CVR was improved from 8.14 to 9.59.

  FIG. 6 shows another example of the evaluation result when the present invention is applied, and the specification of the graph is the same as FIG. In FIG. 6, in the above-described three steps (1) to (3) of the present invention, when normalizing the frequency characteristics in the first step (1), the target region is 30 to 44 Hz, and the gain of 30 Hz is minimized. Adopted as value. By applying the present invention, the CVR was improved from 8.23 to 8.98.

  FIG. 7 shows still another example of the evaluation result when the present invention is applied, and the specification of the graph is the same as FIG. In FIG. 7, in the above-described three steps (1) to (3) of the present invention, when the frequency characteristic is normalized in the first step (1), the target region is 35 to 44 Hz, and the gain of 35 Hz is minimized. Adopted as value. By applying the present invention, the CVR was improved from 8.55 to 9.66.

It is a block diagram which shows one Embodiment of the detection apparatus of this invention. It is a block diagram which shows the electrical structure of the detection apparatus shown by FIG. It is a figure explaining the scale adjustment of the gain in this invention. It is a figure explaining the area of the area | region created between the minimum frequency calculated in this invention and a reference frequency. It is a figure which shows the example of the evaluation result at the time of applying this invention. It is a figure which shows the other example of the evaluation result at the time of applying this invention. It is a figure which shows the further another example of the evaluation result at the time of applying this invention. It is a figure showing distribution of power spectral density when FFT is applied to a 2-minute wheel acceleration signal.

Explanation of symbols

1 Wheel speed detection means 2 Control unit 2a Interface 2b CPU
2c ROM
2d RAM
3 Display 4 Initialization button 5 Alarm

Claims (8)

Rotational speed information detecting means for periodically detecting rotational speed information of tires of each wheel of the vehicle;
From the rotational speed information obtained by the rotational speed information detecting means, a frequency characteristic estimating means for estimating the frequency characteristics of the rotational speed information,
Determining means for determining a decrease in the tire air pressure based on the estimated frequency characteristics,
The frequency characteristic estimation means includes parameter estimation means for estimating a linear model parameter for a time-series signal including the rotation speed information, and
The determination means includes
As a first step, a scaling unit that adjusts a gain scale by minimizing a gain at an appropriately selected first frequency and normalizing an entire frequency characteristic in a band including a resonance peak;
As a second step, an area calculating means for calculating an area of a region created between the first frequency of the band and the reference frequency based on the reference frequency characteristic obtained at the time of initialization and the currently estimated frequency characteristic; And a third step, a scaling means for scaling the area calculated by the area calculating means to between -1 and 1, including a tire air pressure drop detecting device. Rotational speed information detecting means for periodically detecting rotational speed information of tires of each wheel of the vehicle;
From the rotational speed information obtained by this rotational speed information detecting means, rotational acceleration information calculating means for calculating tire rotational acceleration information;
From this rotational acceleration information, frequency characteristic estimation means for estimating the frequency characteristic of the rotational acceleration information,
Determining means for determining a decrease in the tire air pressure based on the estimated frequency characteristics,
The frequency characteristic estimation unit includes a parameter estimation unit that estimates a parameter of a linear model with respect to a time-series signal including the rotational acceleration information, and
The determination means includes
As a first step, a scaling unit that adjusts a gain scale by minimizing a gain at an appropriately selected first frequency and normalizing an entire frequency characteristic in a band including a resonance peak;
As a second step, an area calculating means for calculating an area of a region created between the first frequency of the band and the reference frequency based on the reference frequency characteristic obtained at the time of initialization and the currently estimated frequency characteristic; And a third step, a scaling means for scaling the area calculated by the area calculating means to between -1 and 1, including a tire air pressure drop detecting device.   The tire pressure drop detecting device according to claim 1 or 2, wherein the parameter estimating means is configured to estimate a parameter of a linear model by a least square method. A detection step of periodically detecting rotation speed information of tires of each wheel of the vehicle;
From the rotation speed information obtained in this detection step, an estimation process for estimating the frequency characteristics of the rotation speed information;
A determination step of determining a decrease in air pressure of the tire based on the estimated frequency characteristic,
The estimating step is configured to estimate a parameter of a linear model with respect to a time-series signal including the rotation speed information; and
The determination step includes
A first step of adjusting a gain scale by minimizing a gain at an appropriately selected first frequency and normalizing an entire frequency characteristic in a band including a resonance peak;
A second step of calculating an area of a region formed between the first frequency of the band and the reference frequency by the reference frequency characteristic obtained at the time of initialization and the currently estimated frequency characteristic; and a second step A method for detecting a decrease in tire air pressure, comprising a third step of scaling the area calculated in step -1 to -1. A detection step of periodically detecting rotation speed information of tires of each wheel of the vehicle;
From the rotation speed information obtained in this detection step, a calculation step of calculating the rotational acceleration information of the tire,
From the rotational acceleration information obtained in this calculation step, an estimation step for estimating the frequency characteristics of the rotational acceleration information,
A determination step of determining a decrease in the tire air pressure based on the estimated frequency characteristics, and
The estimation step is configured to estimate a parameter of a linear model for a time series signal including the rotational acceleration information, and
The determination step includes
A first step of adjusting a gain scale by minimizing a gain at an appropriately selected first frequency and normalizing an entire frequency characteristic in a band including a resonance peak;
A second step of calculating an area of a region formed between the first frequency of the band and the reference frequency by the reference frequency characteristic obtained at the time of initialization and the currently estimated frequency characteristic; and a second step A method for detecting a decrease in tire air pressure, comprising a third step of scaling the area calculated in step -1 to -1.   The tire pressure drop detection method according to claim 4 or 5, wherein in the step of estimating the parameter, the parameter of the linear model is estimated by a least square method. Rotation obtained by rotation speed information detecting means for periodically detecting the rotation speed information of the tires of each wheel of the vehicle based on the resonance frequency of the tires of the running vehicle based on the resonance frequency of the tires. From the speed information, function as frequency characteristic estimation means for estimating the frequency characteristics of the rotational speed information, and determination means for determining a decrease in the tire air pressure based on the estimated frequency characteristics,
The frequency characteristic estimation means includes parameter estimation means for estimating a linear model parameter for a time-series signal including the rotation speed information, and
The determination means includes
As a first step, a scaling unit that adjusts a gain scale by minimizing a gain at an appropriately selected first frequency and normalizing an entire frequency characteristic in a band including a resonance peak;
As a second step, an area calculating means for calculating an area of a region created between the first frequency of the band and the reference frequency based on the reference frequency characteristic obtained at the time of initialization and the currently estimated frequency characteristic; And as a third step, a tire pressure drop detection program characterized by including a scaling means for scaling the area calculated by the area calculating means between -1 and 1. Rotation obtained by rotation speed information detecting means for periodically detecting the rotation speed information of the tires of each wheel of the vehicle based on the resonance frequency of the tires of the running vehicle based on the resonance frequency of the tires. Rotational acceleration information calculating means for calculating the rotational acceleration information of the tire from the speed information, frequency characteristic estimating means for estimating the frequency characteristic of the rotational acceleration information from the rotational acceleration information, and based on the estimated frequency characteristics It functions as a determination means for determining a decrease in tire air pressure,
The frequency characteristic estimation means includes parameter estimation means for estimating a linear model parameter for a time-series signal including the rotation speed information, and
The determination means includes
As a first step, a scaling unit that adjusts a gain scale by minimizing a gain at an appropriately selected first frequency and normalizing an entire frequency characteristic in a band including a resonance peak;
As a second step, an area calculating means for calculating an area of a region created between the first frequency of the band and the reference frequency based on the reference frequency characteristic obtained at the time of initialization and the currently estimated frequency characteristic; And as a third step, a tire pressure drop detection program characterized by including a scaling means for scaling the area calculated by the area calculating means between -1 and 1.

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