METHOD FOR MONITORING TIRE CONDITION

Abstract

A method for monitoring a tire condition includes the following steps: sense a rotational speed of a tire of a moving vehicle; when the sensed rotational speed reaches a predetermined rotational speed range, obtain a condition of the rotating tire through at least one sensor to generate a piece of first condition data; compare the first condition data with a plurality of pieces of pavement feature data to obtain the corresponding one; process with the obtained piece of pavement feature data and the first condition data to filter a pavement feature out of the first condition data, generating a piece of second condition data; determine whether the condition of the tire is abnormal based on the second condition data; and send out a warning message when the condition of the tire is determined as abnormal Whereby, the road security is improved.

Description

BACKGROUND OF THE INVENTION

1. Technical Field

The present invention generally relates to tire monitoring, and more particularly to a method for monitoring the condition of a tire during the running of a motor vehicle.

2. Description of Related Art

Typically, a conventional wireless monitoring system including a plurality of sensors and a receiver is adapted to sense tire pressure or tire temperature, wherein the sensors are provided respectively at each tire of the vehicle. The sensors are adapted to sense tire pressure or tire temperature, and send the sensed tire pressure or tire temperature to the receiver. By receiving the information sent by the sensors, the receiver is adapted to monitor tire pressure or tire temperature. Whereby, the receiver could raise an alarm to prevent an accident once tire pressure or tire temperature is found to be abnormal.

However, the conventional wireless monitoring system can only monitor tire pressure or tire temperature. In all aspects, adding in additional functions and providing higher security has become a trend for manufacturers.

BRIEF SUMMARY OF THE INVENTION

In view of the reasons mentioned above, the primary objective of the present invention is to provide a method for monitoring tire condition, which could determine whether the tire is abnormal by detecting the condition of a tire while it is running.

The present invention provides a method for monitoring a condition of each of at least one tire of a moving vehicle. The method includes the following steps: A. sense a rotational speed of each of the at least one tire of the moving vehicle; B. generate a piece of first condition data for each of the at least one tire by sensing the condition of each of the at least one tire through at least one sensor once the sensed rotational speed reaches a predetermined rotational speed range, wherein the first condition data contains a pavement feature; C. compare the first condition data of one of the at least one tire with a plurality of pieces of pavement feature data stored in a database to obtain the one piece of the pavement feature data which corresponds to said first condition data, wherein each piece of the pavement feature data respectively corresponds to one of a plurality types of pavements; D. filter the pavement feature out of each piece of the first condition data based on the obtained pavement feature data to generate a piece of second condition data for each of the at least one tire; and E. determine whether the condition of each of the at least one tire is abnormal based on the generated second condition data, and send out a warning message once the condition of one of the at least one tire is determined as abnormal.

With the aforementioned design, by filtering out the pavement features, the condition of the rotating tire sensed by the monitoring device could be used to accurately determine whether the condition of the rotating tire is abnormal to provide higher security.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

The present invention will be best understood by referring to the following detailed description of some illustrative embodiments in conjunction with the accompanying drawings, in which

FIG. 1 is a schematic diagram of the wireless monitoring system applied with a first embodiment of the present invention;

FIG. 2 is a block diagram of the sensors of the first embodiment of the present invention;

FIG. 3 is a block diagram of the receiver and the vibration sensor of the first embodiment of the present invention;

FIG. 4 is a flowchart of the method of the first embodiment;

FIG. 5 is a schematic diagram, showing the vibration generated by the unbalanced right front tire;

FIG. 6 is a schematic diagram, showing the right front tire has a positive camber angle; and

FIG. 7 is a schematic diagram, showing the toe angle of the right front tire has a negative toe angle.

DETAILED DESCRIPTION OF THE INVENTION

As shown in FIG. 1, a wireless monitoring system 100 applied with a method for monitoring tire condition of the first embodiment of the present invention includes a plurality of monitoring devices 10 and a receiver 20, wherein the wireless monitoring system 100 is provided in a vehicle 200.

The monitoring devices 10 are respectively provided at different tires 202 of the vehicle 200. Each of the monitoring devices 10 has the same structure, and therefore, one of the monitoring devices 10 is used for illustration.

As shown in FIG. 2, the monitoring device 10 includes a tire pressure sensor 122, a sensor which is a vibration sensor 124 as an example, a sensor which is a pickup 126 as an example, a sensor which is a first accelerometer (G-sensor) 128 as an example, a first processor 14, and a wireless signal transmission circuit 16. The tire pressure sensor 122 is adapted to sense the tire pressure of the corresponding tire 202. The vibration sensor 124 is adapted to sense the rotation frequency of the corresponding tire 202, and to output an electrical signal corresponding to the sensed rotation frequency. Since the vibration sensor 124 is rotated along with the corresponding tire 202, the frequency of the outputted electrical signal from the vibration sensor 124 equals the rotation frequency of the corresponding tire 202. In addition, the vibration sensor 124 is also adapted to sense the vibration generated by the rotating tire 202. The pickup 126 is adapted to sense the sound of vibration generated by the rotating tire 202. The first G-sensor 128 is adapted to sense the acceleration generated by the rotating tire 202. The first G-sensor 128 is a triaxial accelerometer of the first embodiment, wherein a y-axis is adapted to sense the acceleration of the corresponding tire 202 in an axial direction of a tangent on a circumference thereof, an x-axis is adapted to sense the acceleration of the corresponding tire 202 in a horizontal axial direction thereof, while a z-axis is adapted to sense the acceleration of the corresponding tire 202 in an axial direction thereof perpendicular to the x-axis and the y-axis (i.e., perpendicular to a ground). The first processor 14 wirelessly sends out the tire pressure data through the wireless signal transmission circuit 16.

As shown in FIG. 3, the receiver 20 is provided in a vehicle body 204 of the vehicle 200, wherein the receiver 20 includes a wireless signal receiving circuit 22, a second processor 24, a second accelerometer 26, and a gyroscope 28. The wireless signal receiving circuit 22 is adapted to receive wireless signals transmitted from each of the monitoring devices 10 to obtain the tire pressure data. The receiver 20 is electrically connected to an in-vehicle computer 206 of the vehicle 200, wherein the receiver 20 transmits the received tire pressure data to the in-vehicle computer 206, and the received tire pressure data is displayed on a monitor 208. The in-vehicle computer 206 also receives the information of the moving vehicle 200, such as a speed of the vehicle 200, a rotational speed of an engine thereof, or a rotating direction of a steering wheel thereof. The second accelerometer 26 is adapted to sense the acceleration generated by the vibration of the vehicle body 204. The gyroscope 28 is adapted to sense a moving direction of the vehicle body 204.

With the aforementioned structures, the method shown in FIG. 4 could be executed.

First, a database is created and stored in a memory 242 of the second processor 24, wherein the database contains a plurality of pieces of pavement feature data, each of which represents the features related to one specific type of pavement (such as asphalt pavement, concrete pavement, brick pavement, and so on). More specifically, the pieces of pavement feature data could be obtained by driving the vehicle 200 on different types of pavements to get the practical condition of the tire 202 through the monitoring device 10 (the vibration sensor 124, the pickup 126, the first G-sensor 128), wherein the vehicle 200 should use new tires, and should be balance corrected and wheel aligned. Each piece of the pavement feature data contains tire condition data sensed by the monitoring device 10, such as vibration data sensed by the vibration sensor 124, sound data sensed by the pickup 126, acceleration data sensed by the first G-sensor 128. The pavement feature data obtained from different pavements are different from each other. Whereby, the pavement feature data could be used as a basis for comparison.

Then, the monitoring devices 10 sense the rotational speed of at least one of the tires 202 during the running of the vehicle 200. In the first embodiment, the first processor 14 of each of the monitoring devices 10 determines the rotational speed according to the frequency of the electrical signals outputted from the vibration sensor 124, wherein the electrical signals could be digital or analog. Once the rotational speed reaches a predetermined rotational speed range, the monitoring device 10 (the vibration sensor 124, the pickup 126, the first G-sensor 128) senses the condition of rotating tires 202 as a piece of first condition data. The first condition data contains a piece of first vibration data, a piece of first sound data, and a piece of first acceleration data, wherein the first vibration data, the first sound data, and the first acceleration data respectively have the pavement features of the pavement the moving vehicle 200 is currently on. Furthermore, each of the first processors 14 sends out the corresponding first condition data through the wireless signal transmission circuit 16. In practice, the condition of the rotating tire 202 could be sensed and the first condition data could be sent out only in a predetermined period after the rotational speed reaches and stays in the predetermined rotational speed range, wherein the predetermined period could be 10 minutes, for instance. After the predetermined period, the sensing would be stopped to reduce the power consumption of the monitoring device 10.

The wireless signal receiving circuit 22 of the receiver 20 is adapted to receive the first condition data and transmit it to the second processor 24, wherein the second processor 24 compares the received first condition data with the pavement feature data stored in the database. For instance, by analyzing how similar the first vibration data, the first sound data, and the first acceleration data of the first condition data to the vibration data, the sound data, and the acceleration data of each piece of the pavement feature data, the one piece of the pavement feature data which is the most similar to the first condition data could be identified and obtained, and the obtained piece of pavement feature data would be the one corresponding to the first condition data. Said analysis could find the most similar one through a frequency domain or/and a time domain. Preferably, the vibration data, the sound data and the acceleration data should be all analyzed, and the one piece of pavement feature data which is the most similar to the first condition data in all three aspects would be considered the one corresponding to the pavement that the vehicle 200 is currently on. In other embodiments, there could be only one or two pieces of data among the vibration data, the sound data, and the acceleration data to be compared.

After that, the second processor 24 processes with the obtained pavement feature data and the first condition data to filter out the pavement features of the first condition data, which generates a second condition data containing a second vibration data, a second sound data, and a second acceleration data. In other words, the second vibration data, the second sound data, and the second acceleration data have no relation to the pavement features of the pavement which the moving vehicle 200 is currently on, but merely represent the condition of the tire 202. Whereby, the second condition data could be used to accurately determine whether the tire 202 is abnormal or not.

Through the second condition data, the second processor 24 could determine what abnormal condition the tire 202 is encountering, such as problems about tire balance, wheel alignment, or tire aging. The detailed method for realizing abnormal conditions in these three aspects will be described below.

1. Tire Balance.

With inappropriate counterweight, the tire 202 would vibrate while rotating at high speed, which leads the tire 202 to deflect away at a deflection angle θ1 from a reference plane P (a right front tire is illustrated in FIG. 5 as an example), wherein the reference plane P is the plane parallel to a tread of the tire 202 which has been adjusted and balanced.

The second processor 24 determines the acceleration along the x-axis of the rotating tire 202 (i.e., the acceleration of the tire 202 in the horizontal direction) according to the second acceleration data of the second condition data, and derives the deflection angle θ1 corresponding to the tire 202 from the acceleration along the x-axis in the second condition data. Once the deflection angle θ1 is greater than a predetermined angle, the condition of the tire 202 would be determined as abnormal. For instance, when the tire 202 is balanced and parallel to the reference plane P in the horizontal direction, the deflection angle θ1 corresponding the reference plane P in the horizontal direction could be derived from the comparison between a piece of reference acceleration data of the balanced tire 202, which is stored in memory 242 in advance, and the second acceleration data. The acceleration data along the x-axis used for deriving the deflection angle θ1 could be obtained from the second acceleration data, or derived from the acceleration data along the y-axis and the z-axis. For instance, in normal condition, the acceleration in the horizontal direction would vary periodically between +/−1 G, while the deflection angle θ1 is abnormal, the variation of the acceleration in the horizontal direction would be greater than +/−3 G. In other words, if the variation of the acceleration in the horizontal direction of the rotating tire 202 is greater than +/−3 G, the condition of the tire 202 would be determined abnormal.

In addition, if the tire 202 is unbalanced and causes the rotating tire 202 to bounce up and down, the amplitude of the acceleration along the z-axis could be determined based on the acceleration along the z-axis (i.e., perpendicular to the ground) in the second acceleration data of the second condition data, and the condition of tire 202 would be defined abnormal if the amplitude exceeds a predetermined range. For instance, while in normal condition, the amplitude of the acceleration along the z-axis would vary periodically between +/−1 G. On the contrary, if the tire 202 is unbalanced, it would bounce up and down, and the amplitude of the acceleration along the z-axis would exceed the predetermined range (e.g. +/−3 G), whereby the condition of the tire 202 could be determined as abnormal.

During the running of the vehicle 200, the tire 202 would vibrate. Thus, the second processor 24 could determine whether the sound generated by the rotating tire 202 is abnormal based on the second sound data of the second condition data. In the first embodiment, the second processor 24 could determine whether the condition of the tire 202 is abnormal based on the comparison between the second sound data of the second condition data and a reference sound data which is stored in the memory 242 in advance, wherein the reference sound data is obtained by moving the balanced tire 202 on a flat pavement and filtering out the pavement features of the flat pavement. Whereby, if the second sound data has a noise which is not contained in the reference sound data, the tire 202 would be determined as unbalanced. In practice, the sound of the second sound data which is out of an audio frequency range could also be filtered out through bandpass filtering to eliminate unnecessary audio frequencies.

Furthermore, the second processor 24 could also determine whether the vibration caused by the tire 202 is abnormal based on the second vibration data of the second condition data. In the first embodiment, the second processor 24 could determine whether the condition of the tire 202 is abnormal based on the comparison between the second vibration data of the second condition data and a piece of reference vibration data which is stored in the memory 242 in advance, wherein the reference vibration data is obtained by moving the balanced tire 202 on a flat pavement and filtering out the pavement features of the flat pavement. Whereby, if the second vibration data has an abnormal vibration which is not contained in the reference vibration data, the tire 202 would be determined as unbalanced. In practice, the vibration frequency of the second vibration data, which is out of a particular frequency range could also be filtered out through bandpass filtering to eliminate unnecessary vibration frequencies.

In practice, to further eliminate the factor of the pavement for ensuring the accuracy of determining whether the tire 202 is unbalanced, the second processor 24 could determine whether the vibration of the vehicle body 204 is abnormal based on the comparison between the vibration frequency of the vehicle body 204 sensed through the second accelerometer 26 and a reference vibration frequency stored in the memory 242 in advance. In the first embodiment, if the vibration frequency matches with the reference vibration frequency, the vibration of the vehicle body 204 would be determined as normal. If any one of the following conditions takes place when the vibration of the vehicle body 204 is determined normal, the condition of the tire 202 would still be deemed abnormal, including:

The deflection angle θ1 is greater than the predetermined angle; the amplitude of the acceleration along the z-axis of the second acceleration data in the vertical direction exceeds the predetermined range; the second sound data has a noise not contained in the reference sound data; and the second vibration data has an abnormal vibration not contained in the reference vibration data. As mentioned, with any one of the above conditions taking place, even when the vibration of the vehicle body 204 is determined normal, the condition of the tire 202 would still be deemed abnormal.

2. Wheel Alignment.

A camber angle θ2 and a toe angle θ3 of the tire 202 are sensed to determine whether the wheel alignment is abnormal. As shown in FIG. 6, the camber angle θ2 is defined as an angle between a center line I of the tire 202 and a vertical line L perpendicular to the ground, wherein the tire illustrated in FIG. 6, which is a right front tire, has a positive camber angle. As shown in FIG. 7, the toe angle θ3 is defined as an angle between the center line I of the tire 202 and a moving direction D of the moving vehicle body 204, wherein the tire illustrated in FIG. 7, which is the right front tire again, has a negative toe angle.

The second processor 24 obtains the acceleration of the rotating tire 202 in the z-axis direction based on the second acceleration data of the second condition data, and then estimates the camber angle θ2 of the tire 202 accordingly. The condition of the tire 202 would be determined abnormal if the camber angle θ2 falls out of a first predetermined angle range, wherein the first predetermined angle range is defined as the range of the camber angle θ2 in normal condition after the tire 202 is being wheel-aligned. For instance, the first predetermined angle range could be defined as from 0 degree (i.e., the center line I of the tire 202 perpendicular to the ground) to +10 degrees (i.e., the tire 202 has a positive camber angle of 10 degrees). However, these values are not limitations of the present invention. In practice, the first predetermined angle range could be alternatively defined as negative, or from positive to negative. For instance, after the tire 202 is wheel-aligned, the variation of the acceleration of the tire 202 sensed along the z-axis could be used as a basis and stored in the memory 242. Since the acceleration varies with the camber angle θ2 of the tire 202, the camber angle θ2 of the tire 202 could be derived from the variation of the acceleration. In addition to deriving the camber angle θ2 from the variation of acceleration, the abnormality of the camber angle θ2 could be also realized directly from the sensed acceleration. For instance, the acceleration along the z-axis would vary periodically between +/−1 G in normal condition. On the contrary, if the camber angle θ2 is abnormal, the variation of the acceleration along the z-axis would be greater than +/−3 G. In other words, if the sensed variation of the acceleration along the z-axis exceeds +/−3 G, the condition of the tire 202 could be determined as abnormal.

The asymmetric camber angle θ2 between the right wheels and the left wheels would lead to poor alignment. Thus, the acceleration data of the corresponding pavement feature data could also be derived from the comparison between the acceleration data of each piece of the pavement feature data and one piece of the first acceleration data of the first condition data sensed by the first G-sensor 128 of the monitoring device 10 at each of two corresponding tires 202 (such as the left front tire and the right front tire). By filtering out the pavement features of the first acceleration data, the second acceleration data of two pieces of the second condition data could be obtained. After that, the camber angles θ2 of the left front tire and the right front tire could be estimated according to said two pieces of the second acceleration data. The two tires 202 would be determined abnormal when the camber angles θ2 of the two tires 202 are asymmetric. For instance, the tire 202 would be deemed abnormal when one of the tires 202 has a positive camber angle while the other tire 202 has a negative camber angle.

Also, the acceleration along the y-axis could also be derived from the second acceleration data after the pavement features have been filtered out from the first acceleration data sensed by the first G-sensor 128. At the same time, the toe angle θ3 corresponding to the tire 202 could be derived from the acceleration along the y-axis of the second acceleration data and the moving direction D of the vehicle body 204, wherein the moving direction D could be obtained by reading the data sensed by the gyroscope 28 through the second processor 24. The condition of the tire 202 would be determined abnormal when the toe angle θ3 falls out of a second predetermined angle range, wherein the second predetermined angle range is defined as the range of the toe angle θ3 in a normal condition after the tire 202 being wheel aligned. For instance, the second predetermined angle range could be defined as 0 degree (i.e., the center line I of the tire 202 is parallel to the moving direction D) to +10 degrees (i.e., the center line I of the tire 202 tilts outward relative to the moving direction D by 10 degrees). However, these values are not limitations of the present invention. In practice, the second predetermined angle range could be alternatively defined as positive, or from positive to negative. In addition to deriving the toe angle θ3 from the variation of the acceleration, the abnormality of the toe angle θ3 could be also realized directly from the sensed acceleration. For instance, the acceleration along the y-axis would vary periodically between +/−1 G in normal condition. On the contrary, if the toe angle θ3 is abnormal, the variation of the acceleration along the y-axis would be greater than +/−3 G. In other words, if the sensed variation of the acceleration along the y-axis of the rotating tire 202 exceeds +/−3 G, the condition of the tire 202 would be determined abnormal.

As mentioned above, the moving direction D could be obtained by the gyroscope 28, and it could be also obtained according to a steering direction of the steering wheel, for the steering direction corresponds to the moving direction D of the vehicle body 204, and it could be obtained through the in-vehicle computer 206 or the vehicular communication system.

3. Aging Tire.

The second processor 24 determines whether the condition of the tire 202 is abnormal by comparing the second sound data with the reference sound data stored in the memory 242, wherein the second sound data is generated by filtering the pavement features out of the first sound data sensed by the pickup 126. For instance, a stiffened rubber of the tire 202 would change the sound frequency of the rotating tire 202, and therefore, the condition of the tire 202 could be determined abnormal if the frequency of the second sound data differs from that of the reference sound data by a certain extent.

In addition, the second processor 24 could also determine whether the condition of the tire 202 is abnormal by comparing the second vibration data with the reference vibration data stored in the memory 242, wherein the second vibration data is generated by filtering the pavement features out of the first vibration data sensed by the vibration sensor 124. For instance, the stiffened rubber of the tire 202 would change the vibration frequency, and therefore, the condition of the tire 202 would be determined abnormal if the vibration frequency of the second vibration data differs from that of the reference vibration data by a certain extent.

Once the condition of the tire 202 is determined abnormal by the second processor 24, no matter the abnormality is about tire balancing, wheel alignment, or aging tire, the second processor 24 would send out a warning message to notify the user that the condition of the tire 202 is abnormal. The warning message could be displayed on the monitor 208 through the in-vehicle computer 206 or the vehicular communication system, or could be sent out in a sound form or a light form. Furthermore, the warning message could be different to reflect different abnormal conditions.

In conclusion, the present invention could accurately determine whether the condition of the rotating tire 202 is abnormal through the monitoring devices by filtering the pavement features out of the collected condition data, which would effectively improve the road safety.

It must be pointed out that the embodiments described above are only some embodiments of the present invention. All equivalent methods which employ the concepts disclosed in this specification and the appended claims should fall within the scope of the present invention.

Claims

1. A method for monitoring a condition of each of at least one tire of a moving vehicle; comprising: A. sensing a rotational speed of each of the at least one tire of the moving vehicle;B. generating a piece of first condition data for each of the at least one tire by sensing the condition of each of the at least one tire through at least one sensor for a predetermined period while the sensed rotational speed reaches and stays in a predetermined rotational speed range, and stopping sensing the condition of each of the at least one tire after the predetermined period wherein the first condition data contains a pavement feature;C. comparing the first condition data of one of the at least one tire with a plurality of pieces of pavement feature data stored in a database to obtain the one piece of the pavement feature data which corresponds to said first condition data, wherein each piece of the pavement feature data respectively corresponds to one of a plurality types of pavements;D. filtering the pavement feature out of each piece of the first condition data based on the obtained pavement feature data to generate a piece of second condition data for each of the at least one tire; andE. determining whether the condition of each of the at least one tire is abnormal based on the generated second condition data, and sending out a warning message once the condition of one of the at least one tire is determined as abnormal.

2. The method of claim 1, wherein the at least one sensor comprises an accelerometer, which is adapted to sense an acceleration of each of the at least one tire in a horizontal direction to obtain a piece of first acceleration data, which is contained in the relevant first condition data; each piece of the pavement feature data contains a piece of acceleration data; the second condition data of each of the at least one tire contains a piece of second acceleration data; the condition of each of the at least one tire is determined based on the second acceleration data of the relevant second condition data in step E.

3. The method of claim 2, wherein, in step E, a deflection angle of each of the at least one tire is derived from the second acceleration data of the relevant second condition data, and once the deflection angle of one of the at least one tire is greater than a predetermined angle, the condition of said tire is determined as abnormal.

4. The method of claim 3, wherein step E further comprises sensing a vibration frequency of a vehicle body of the vehicle, and determining whether the vibration frequency of the vehicle body is normal by comparing the sensed vibration frequency with a reference vibration frequency; once the deflection angle of one of the at least one tire is greater than the predetermined angle and the vibration frequency of the vehicle body is determined as normal, the condition of said tire is determined as abnormal.

5. The method of claim 1, wherein the at least one sensor comprises an accelerometer, which is adapted to sense an acceleration of the corresponding tire in a direction perpendicular to a ground to obtain a piece of first acceleration data, which is contained in the relevant first condition data; each piece of the pavement feature data contains a piece of acceleration data; each piece of the second condition data contains a piece of second acceleration data; an amplitude of the acceleration perpendicular to the ground for each of the at least one tire is determined based on the second acceleration data of the relevant second condition data in step E, and once the amplitude of one of the at least one tire falls out of a predetermined range, the condition of said tire is determined as abnormal.

6. The method of claim 5, wherein step E further comprises sensing a vibration frequency of a vehicle body of the vehicle, and determining whether the vibration frequency of the vehicle body is normal by comparing the sensed vibration frequency with a reference vibration frequency; once the amplitude of the acceleration perpendicular to the ground of one of the at least one tire falls out of the predetermined range and the vibration frequency of the vehicle body is determined as normal, the condition of said tire is determined abnormal.

7. The method of claim 1, wherein the at least one sensor comprises an accelerometer, which is adapted to sense an acceleration of the corresponding tire to obtain a piece of first acceleration data, which is contained in the relevant first condition data; each piece of the pavement feature data contains a piece of acceleration data; the second condition data of each of the at least one tire contains a piece of second acceleration data; the condition of each of the at least one tire is determined based on the second acceleration data of the relevant second condition data in step E.

8. The method of claim 7, wherein step E further comprises determining a moving direction of a vehicle body of the vehicle, and deriving a toe angle of each of the at least one tire from the moving direction and the second acceleration data of the relevant second condition data; once the toe angle of one of the at least one tire falls out of a predetermined angle range, the condition of said tire is determined as abnormal.

9. The method of claim 7, wherein step E further comprises deriving a camber angle of each of the at least one tire from the second acceleration data of the relevant second condition data, and once the camber angle of one of the at least one tire falls out of a predetermined angle range, the condition of said tire is determined as abnormal.

10. The method of claim 1, wherein the at least one sensor comprises at least two sensors, which are accelerometers, and the at least one tire comprises at least two tires, which comprise a right tire and a left tire corresponding to the right tire; one of the at least two sensors corresponds to the right tire, and another one of the at least two sensors corresponds to the left tire; the first condition data of each of the at least two tires contain a piece of first acceleration data corresponding to an acceleration sensed by the relevant accelerometer; each piece of the pavement feature data contains a piece of acceleration data, and one of the first condition data of one tire among the right tire and the left tire is compared with the pavement feature data in step C; the pavement feature of the first condition data of each of the at least two tires is filtered out based on the pavement feature data obtained in step C to generate the relevant second condition data, which contain a piece of second acceleration data; step E further comprises deriving a camber angle of each of the right tire and the left tire from the second acceleration data of the relevant second condition data, and once the camber angles of the right tire and the left tire are asymmetric, the conditions of the right tire and the left tire are determined as abnormal.

11. The method of claim 1, wherein the at least one sensor comprises a pickup, which is adapted to sense a sound of the corresponding tire; the first condition data of each of the at least one tire contain a piece of first sound data; each piece of the pavement feature data contain a piece of sound data; the second condition data of each of the at least one tire contain a piece of second sound data; in step E, the condition of each of the at least one tire is determined by comparing the second sound data of the relevant second condition data with a piece of reference sound data stored in the data base.

12. The method of claim 1, wherein the at least one sensor comprises a vibration sensor, which is adapted to sense a vibration generated by the corresponding tire, wherein the first condition data of each of the at least one tire comprises a piece of first vibration data; each piece of the pavement features data contain a piece of vibration data; the second condition data of each of the at least one tire contain a piece of second vibration data; in step E, the condition of each of the at least one tire is determined by comparing the second vibration data of the relevant second condition data and a piece of reference vibration data stored in the database.