CN214226119U - Pavement monitoring system - Google Patents

Abstract

The present disclosure relates to a road surface monitoring system. The road surface monitoring system includes: a first sensor unit arranged in a monitoring area of a road surface; a second sensor unit arranged in the same monitoring area as the first sensor unit; and a data processing unit connected with the first sensor unit and the second sensor unit and configured to periodically analyze and process the weighing signal acquired by the first sensor unit and the sound signal acquired by the second sensor unit so as to generate a monitoring result. The road surface monitoring system can utilize the two sensor units comprising different sensors to respectively acquire the weighing signal and the sound signal when the vehicle passes through, and analyze the signals to automatically determine the road surface condition, thereby effectively increasing the accuracy of road surface monitoring and improving the monitoring efficiency.

Description

Pavement monitoring system

Technical Field

The present disclosure relates generally to the field of monitoring. In particular, the present disclosure relates to a pavement monitoring system.

Background

With the vigorous rise of economic construction in China, the highway construction is rapidly developed. However, due to the increasing traffic volume, the actual service life of the road surface is lower than the designed service life, and the road in many areas is damaged early soon after being put into use, and needs to be repaired slightly or even greatly, which seriously affects the normal operation of the traffic and causes great economic loss on the one hand.

In order to know the road surface condition in time so as to avoid influencing the normal operation of traffic and further increase the road surface damage degree, the road surface needs to be regularly detected. The current detection mode mainly takes manual patrol as a main mode, and the automation, informatization and intellectualization levels are relatively low. In addition, the manual patrol period and patrol assessment of the road surface condition are often determined depending on the experience of the patrol personnel. Therefore, the validity, accuracy and integrity of the manual patrol data are not easy to guarantee, and the follow-up process is difficult to make full use of.

SUMMERY OF THE UTILITY MODEL

To address at least one or more of the above technical problems, the present disclosure provides a road surface monitoring system. The road surface monitoring system includes: a first sensor unit arranged in a monitoring area of a road surface; a second sensor unit arranged in the same monitoring area as the first sensor unit; a data processing unit connected with the first sensor unit and the second sensor unit and configured to periodically analyze and process the weighing signal acquired by the first sensor unit and the sound signal acquired by the second sensor unit so as to generate a monitoring result.

In one embodiment, the first sensor unit comprises a load cell and the second sensor unit comprises a sound sensor.

In another embodiment, the load cell comprises any one of a bar sensor and a flexural plate sensor, and the acoustic sensor comprises any one of a resistive acoustic sensor, a capacitive acoustic sensor, and a magneto-acoustic sensor.

In yet another embodiment, the first sensor unit is arranged on the road surface of the monitoring area and the second sensor unit is arranged in the vicinity of the first sensor unit.

In yet another embodiment, the second sensor unit is arranged on a road portal in the monitoring area.

In yet another embodiment, the first sensor unit comprises a plurality of sets of bar sensors arranged in a direction perpendicular to the lane direction.

In a further embodiment, each of the plurality of sets of bar sensors comprises a plurality of bar sensors arranged perpendicular to the lane direction and parallel to each other.

In yet another embodiment, adjacent two of the plurality of sets of bar sensors are staggered.

In yet another embodiment, the sound sensor in the second sensor unit is provided with a pickup, and the pickup is directed toward the first sensor unit.

In yet another embodiment, the roadway monitoring system further comprises: an early warning unit connected with the data processing unit and configured to perform an early warning operation according to the monitoring result.

In yet another embodiment, the data processing unit is in communication connection with the first sensor unit and the second sensor unit in a wired or wireless manner.

According to the monitoring system disclosed by the invention, when a vehicle passes through two sensor units comprising different sensors, the two sensor units are utilized to respectively acquire a weighing signal and a sound signal of the vehicle, and the signals are analyzed and processed by the data processing unit so as to automatically determine the road surface condition, so that the accuracy of road surface monitoring is effectively improved, the monitoring efficiency is improved, and the monitoring data can be stored and used.

Drawings

The above and other objects, features and advantages of exemplary embodiments of the present disclosure will become readily apparent from the following detailed description read in conjunction with the accompanying drawings. In the drawings, several embodiments of the disclosure are illustrated by way of example and not by way of limitation, and like or corresponding reference numerals indicate like or corresponding parts and in which:

FIG. 1 is a schematic block diagram of a roadway monitoring system according to an embodiment of the present disclosure;

FIG. 2 is a schematic block diagram of a roadway monitoring system according to another embodiment of the present disclosure;

FIG. 3 is a schematic top view of a first sensor unit and a second sensor unit arranged in a roadway monitoring area in accordance with an embodiment of the present disclosure.

Detailed Description

The technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the drawings in the embodiments of the present disclosure, and it is obvious that the described embodiments are some, but not all embodiments of the present disclosure. All other embodiments, which can be derived by a person skilled in the art from the embodiments disclosed herein without making any creative effort, shall fall within the protection scope of the present disclosure.

The road surface according to the present disclosure is a layered structure that is laid on a road bed with various road building materials and directly receives a vehicle load. And the pavement of the present disclosure includes, but is not limited to, a highway pavement, a bridge pavement, a tunnel pavement, a pavement above a culvert, and the like.

Specific embodiments of the present disclosure are described in detail below with reference to the accompanying drawings.

The present disclosure provides a pavement monitoring system. Fig. 1 is a schematic block diagram illustrating a roadway monitoring system 100 according to an embodiment of the present disclosure. As shown in fig. 1, the road surface monitoring system 100 includes a first sensor unit 110, a second sensor unit 120, and a data processing unit 130. The first sensor unit 110 may be arranged in a monitored area of the road surface. The second sensor unit 120 may be arranged in the same monitoring area as the first sensor unit 110. The data processing unit 130 may be connected to the first sensor unit 110 and the second sensor unit 120, and configured to periodically analyze the weighing signal acquired by the first sensor unit 110 and the sound signal acquired by the second sensor unit 120 to generate a monitoring result.

According to an embodiment of the present disclosure, the first sensor unit 110 may acquire a weighing signal when the vehicle passes through the first sensor unit 110, and the second sensor unit 120 may acquire a sound signal when the vehicle passes through the second sensor unit 110. The data processing unit 130 may perform analysis processing on all weighing signals and all sound signals acquired in a preset period to generate a monitoring result of the road surface condition.

According to an embodiment of the present disclosure, the first sensor unit 110 may include a load cell, and the second sensor unit 120 may include a sound sensor. Further, the load cell may include any one of a bar sensor and a bent plate sensor, and the sound sensor may include any one of a resistive sound sensor, a capacitive sound sensor, and a magnetoelectric sound sensor.

In this embodiment, the load signal may be acquired by a load cell such as a bar sensor, and the sound signal may be acquired by a sound sensor such as a resistive sound sensor. The above-mentioned sensors included in the first sensor unit 110 and the second sensor unit 120 are only exemplary and not restrictive, and other sensors may be used to acquire the weighing signal and the sound signal. For example, the load cell may include any sensor known for use in weighing apparatus, in addition to bar sensors and bent plate sensors.

According to an embodiment of the present disclosure, the first sensor unit 110 may be disposed on a road surface of the monitoring area, and the second sensor unit 120 may be disposed near the first sensor unit 110. In particular, the second sensor unit 120 may be arranged on a road portal in the monitored area. The monitoring area of the road surface refers to a road surface area to be monitored, and the size of the area can be matched with the first sensor unit and the second sensor unit. The number and positional arrangement of the sensors in the first sensor unit and the second sensor unit may be adjusted according to the size of the area. Of course, a plurality of first sensor units and second sensor units paired in pairs may also be provided. Therefore, the first sensor unit 110 and the second sensor unit 120 can acquire the weighing signal and the sound signal of the same target vehicle passing through the road surface monitoring area, respectively, and make the weighing signal and the sound signal acquired by each vehicle passing through the monitoring area have a corresponding relationship.

And the data processing unit 130 may be configured to periodically generate a monitoring result from the weighing signal and the sound signal in the following manner: determining corresponding vehicle information of all vehicles according to all weighing signals in a preset period; classifying the vehicles according to the vehicle information of all the vehicles to determine vehicle classification information; respectively determining a sound signal set corresponding to each type of vehicle according to the vehicle classification information; and determining a monitoring result according to the sound signal set.

In this embodiment, the vehicle information may include a vehicle type, a vehicle speed, and a weight. And the preset period can be considered to be set according to actual needs and road surface conditions, for example, one week or one month can be used. The data processing unit 130 may determine the model, the speed and the weight of all corresponding vehicles for all weighing signals within the preset period.

Specifically, the first sensor unit 110 may include a plurality of sensors. For vehicle speed, the speed of the vehicle may be calculated based on the relative positions of the sensors, the timing at which the sensors sense the weighing signals of the vehicle/axle (i.e., the time at which the vehicle/axle reaches each sensor in turn), and the like. The specific manner of calculating velocity is known in the art and will not be described in detail herein. For weight, the weight of the vehicle can be calculated accordingly based on the weighing signal sensed by each sensor. The way in which the weights are calculated in particular for the weighing signals obtained by the different weighing sensors is known in the art and will not be described in detail here. For the vehicle type, the vehicle type can be known according to the number of axles and the distance between the axles, and particularly the vehicle type can be distinguished according to the national standard of the automatic weighing apparatus of the dynamic road vehicle according to the axle information. The number of axles can be intuitively obtained according to the number of weighing signals of the same vehicle passing through the same sensor (for example, one axle corresponds to one weighing signal), and the distance between the axles can be obtained according to the time sequence and the vehicle speed of the weighing signals of two axles passing through the same sensor. The manner in which a vehicle model is specifically obtained is known in the art and will not be described in detail herein. The above manners of obtaining the vehicle type, the vehicle speed and the weight are all exemplary and can be easily obtained by those skilled in the art according to the existing manners.

According to the vehicle information of all the vehicles obtained by the above method, i.e., the model, the speed and the weight, the vehicles can be classified by dividing the vehicles into sections in the order of the model, the weight and the speed. Specifically, for each vehicle type, there may be a weight in a different weight section due to a difference in the weight of the loading object, and for each weight section, there may be a speed in a different speed section. It is possible to classify vehicles in each speed section for each weight section for each model type into one class. Thus, vehicle classification information, such as the number of vehicle classifications (into which classes) and the vehicles in each class of vehicles (with which vehicles) can be obtained. It should be noted that the vehicle types may be divided by the axles according to the above-described method, for example, and the weight section and the speed section may be set manually according to experience and need.

With the vehicle classification information obtained above, the corresponding sound signals can be determined for all the vehicles in each class of vehicles. Since in the first arrangement of the first and second sensor units 110 and 120, the weighing signal and the sound signal for the same vehicle are measured in pairs and the vehicle classification information is obtained from the weighing signal, the sound signal corresponding to the weighing signal of the vehicle is easily obtained. And finally, the sound signals corresponding to all the vehicles in each type of vehicle are formed into a sound signal set. Therefore, a plurality of sound signal sets can be obtained finally according to the number of classifications of the vehicle.

Finally, the monitoring result may be determined from the set of sound signals.

In particular, the data processing unit 130 may be configured to determine the monitoring result from the set of sound signals in the following manner: determining all respective valid sound information of each sound signal set aiming at all sound signals in each sound signal set; classifying all respective effective sound information of each sound signal set according to the frequency; determining a sound characteristic value according to the amplitude distribution of each type of effective sound information; and determining a monitoring result according to the sound characteristic value and the reference value.

Further, the data processing unit 130 may be configured to determine the respective total valid sound information of each sound signal set for all sound signals in each sound signal set in the following manner: determining all respective sound information of each sound signal set by carrying out time-frequency domain transformation on each sound signal in each sound signal set; and determining all valid sound information of each sound signal set according to all sound information of each sound signal set.

Therefore, in order to obtain effective sound information, each sound signal may be first subjected to time-frequency domain transformation to obtain a plurality of sound information at different frequencies. The time-frequency domain transform may include a fourier transform, a wavelet transform, and the like. Then, valid sound information is determined from the entire sound information.

And the data processing unit 130 may be configured to determine the respective total valid sound information for each set of sound signals from the respective total sound information for each set of sound signals in the following manner: and selecting sound information at a plurality of frequencies from 100Hz to 750Hz as effective sound information in all the sound information of each sound signal set.

In this embodiment, since the sound signal contains many pieces of interference information at different frequencies, it is necessary to select sound information closely related to the sound of the vehicle as a basis for analysis. Therefore, sound information that is closely related to the sound of the vehicle, i.e., effective sound information at different frequencies, among the plurality of sound information is determined.

It should be understood that each time the monitoring system analyzes the signal, the sound information at the same frequency as the last time is selected as the valid sound information, that is, each time the data processing unit in the road surface condition monitoring system performs signal analysis, the same frequency is used for selecting the valid sound information in the sound information at different frequencies, which makes the selected frequency standard the same, and thus the analysis reference the same.

After determining the respective total valid sound information for each sound signal set, the respective total valid sound information for each sound signal set may be classified according to frequency. The classification may take the form, for example, of: the valid sound information is classified according to the frequencies used when the valid sound information is selected, and the valid sound information of each frequency is classified into one type in all the valid sound information of each sound signal set. Or according to the frequency band formed by a plurality of frequencies used when the effective sound information is selected, namely the effective sound information in the frequency interval formed by a plurality of adjacent frequencies is classified into one type.

Then, the data processing unit 130 may be configured to determine the sound characteristic value from the amplitude distribution of each type of valid sound information in the following manner: determining a standard deviation according to the amplitude distribution of each type of effective sound information; and determining a sound characteristic value according to the standard deviation.

It should be understood that the amplitude distribution of each type of valid sound information is normally distributed, and thus the standard deviation can be calculated, and then, for example, three times the standard deviation can be taken as the sound characteristic value.

In summary, each type of vehicle corresponds to one sound signal set, and each sound signal set corresponds to a plurality of types of valid sound information divided according to frequency. Thus, the sound characteristic value of each type of vehicle at different frequencies or frequency intervals can be obtained.

Finally, the data processing unit 130 may be configured to determine the monitoring result from the sound feature value and the reference value in the following manner: obtaining a deviation by subtracting the sound feature value from the reference value; and determining the monitoring result according to the difference value of the deviation and a preset threshold value.

The reference value may be predetermined by: a plurality of weighing signals and a plurality of sound signals of a new road surface or a well-conditioned road surface within the above-mentioned preset period (for example, one week or one month) are acquired in advance using the monitoring system 100 through the first sensor unit 110 and the second sensor unit 120. The sound characteristic values at different frequencies or frequency intervals for each type of vehicle are then obtained by the data processing unit 130 according to the method described above. The sound characteristic values at different frequencies or frequency intervals for each type of vehicle are then used as reference values in the daily use of the monitoring system 100. And this reference value can be used at all times in later analysis operations of the monitoring system 100. Of course, the reference value may be recalculated according to the use condition of the road surface by using the above method or adjusted according to actual needs.

Therefore, the data processing unit 130 obtains respective deviations by subtracting the obtained sound characteristic values at different frequencies or frequency intervals for each type of vehicle from the respective corresponding reference values, then obtains respective differences by subtracting the respective deviations from the respective preset thresholds, and takes the respective differences as the monitoring results.

The respective preset threshold value may be set manually according to actual needs or experience. The obtained difference value indicates the magnitude relation between the deviation and the preset threshold value. And when the difference is less than or equal to 0, the monitoring result shows that the road surface condition is normal. When the difference is larger than 0, the monitoring result shows that the road surface condition is abnormal, and early warning information can be generated.

Since the monitoring result includes a plurality of difference values, the road surface condition can be determined according to each difference value, that is, if one difference value is greater than 0, it indicates that the road surface condition is abnormal, and the warning information can be generated.

And the early warning information can be divided into different early warning levels according to the difference value and the number of the difference values larger than 0, a person skilled in the art can set different conditions according to actual needs or experience, when the difference values larger than 0 and/or the difference values with different numbers fall into different numerical value ranges, the early warning information with different levels is generated, and the higher the difference value is and/or the more the number of the difference values larger than 0 is, the higher the early warning level is. For example: the first-stage early warning represents that the part possibly is damaged or the damage degree is low, and a maintainer needs to carry out investigation; the second-stage early warning, which represents that the damage degree is high, needs a maintainer to carry out investigation immediately; and a third-level early warning represents serious damage and requires immediate investigation and maintenance by a maintainer.

Of course, the multiple differences may be determined comprehensively, that is, the road surface condition may be determined to be abnormal only when the differences corresponding to all the types of vehicles or some types of vehicles in all the types of vehicles are greater than 0, or the road surface condition may be determined to be abnormal only when the differences corresponding to some frequencies or frequency ranges in one type of vehicles are greater than 0. The comprehensive judgment can be set arbitrarily according to experience, and the early warning information of different levels can be generated according to the difference value and the number of the difference values larger than 0 by combining the judgment of the early warning levels.

In the first arrangement for the first sensor unit 110 and the second sensor unit 120 as described above, it should be noted that the same criterion is adopted in the analysis processing of the signal in each preset period after the determination of the classification criterion of the vehicle and the classification criterion of the valid sound information. Of course, the above criteria may be redetermined as needed. Further, since the first sensor unit 110 and the second sensor unit 120 are arranged together, when the monitoring result indicates that the road surface condition is abnormal, it represents that the condition exists in the road surface monitoring area where the first sensor unit 110 and the second sensor unit 120 are located.

It should be noted that after the classification criteria of the vehicle and the classification criteria of the valid sound information are determined, the same criteria are used in the analysis processing of the signal in each preset period. Of course, the above criteria may be redetermined as needed.

FIG. 2 is a schematic block diagram illustrating a roadway monitoring system 200 according to one embodiment of the present disclosure. The pavement monitoring system 200 shown in fig. 2 includes a first sensor unit 210, a second sensor unit 220, a data processing unit 230, and an early warning unit 240.

Fig. 2 shows that the first sensor unit 210 includes a plurality of weighing sensors, and the second sensor unit 220 includes a plurality of sound sensors, wherein the first sensor unit 210 and the second sensor unit 220 are the same as the first sensor unit 110 and the second sensor unit 120 shown in fig. 1 in terms of configuration, function, principle, and mutual arrangement relationship, and the like, and are not described herein again.

The data processing unit 230 differs from the data processing unit 130 shown in fig. 1 in that the data processing unit 230 is configured to determine the monitoring result from the sound characteristic value and the reference value in the following manner: and obtaining a deviation by subtracting the sound characteristic value from the reference value, and taking the deviation as a monitoring result.

The early warning unit 240 is connected to the data processing unit 230, and may be configured to perform an early warning operation according to the monitoring result. Specifically, the early warning unit 240 is configured to perform an early warning operation according to the monitoring result in the following manner: and determining early warning information according to the difference value of the deviation and a preset threshold value. The preset threshold value can be set manually according to actual needs or experience. By the early warning unit, the road condition can be early warned in time

The description of the warning information may refer to the content described above with reference to fig. 1, and will not be repeated herein.

According to a not shown embodiment of the present disclosure, the road surface condition monitoring system may further include a first storage unit and a second storage unit.

The first storage unit is used for storing data of weighing signals acquired by the weighing sensors in the first sensor unit, and the second storage unit is used for storing data of sound signals acquired by the sound sensors in the second sensor unit. The data can be transmitted to the data processing unit in real time, and the signals can be stored in the first storage unit and the second storage unit so as to be analyzed and processed in a centralized manner at regular intervals. Of course, the data of the first sound signal and the data of the second sound signal may also be stored in one storage unit, which is not limited herein.

Since the signals acquired by the sound sensor and the weighing sensor are analog signals, the first sensor unit and the second sensor unit may include an analog-to-digital conversion module to perform analog-to-digital conversion on the signals. The analog-to-digital converted digital signal may then be stored in the first storage unit and the second storage unit.

In addition, when the signals stored in the first storage unit and the second storage unit need to be analyzed, the signals may be transmitted to the data processing unit using, for example, a transmission unit (not shown). Specifically, the transmission unit may transmit the digital signal to the data processing unit in a wired or wireless manner, and the wired manner may be implemented by a network cable or an optical fiber; the wireless mode can be realized by a 4G or 5G module. In this embodiment, as for wireless transmission, a digital signal may be transmitted to the data processing unit by a wireless transmission technology such as ZigBee using 4G or 5G.

According to another not shown embodiment of the present disclosure, the road surface condition monitoring system may further include a monitoring center, such as a monitoring station, which may receive the warning information from the warning unit. As described with respect to fig. 2, the early warning information may be classified into different early warning levels. After receiving the early warning information, the monitoring center can inform maintenance personnel to correspondingly process the road surface condition according to the early warning level.

The early warning unit may send the early warning information to the monitoring center in a wired manner or a wireless manner as described above. In addition, the early warning unit can also carry out on-site early warning according to the generated early warning information.

Fig. 3 is a schematic top view of a first sensor unit and a second sensor unit arranged in a pavement monitoring area according to an embodiment of the disclosure. The arrangement of sensors in the first sensor unit shown in fig. 3 may be applied to the road surface condition monitoring system shown in fig. 1 to 2.

The load cells in the first sensor unit may be, for example, bar sensors. The first sensor unit may include a plurality of sets of bar sensors arranged in a direction perpendicular to the lane direction. Each of the plurality of sets of bar sensors may comprise a plurality of bar sensors arranged perpendicular to the lane direction and parallel to each other. Further, adjacent two of the plurality of sets of strip sensors may be staggered.

In fig. 3, the direction indicated by the arrow is a lane direction, i.e., a vehicle traveling direction. As shown in fig. 3, the first sensor unit includes two sets of bar sensors, i.e., a first set of bar sensors 311 and a second set of bar sensors 312, which are disposed in a direction perpendicular to the lane direction. Each set of strip sensors comprises 3 strip sensors 1 arranged perpendicular to the lane direction and parallel to each other. In this case, the first and second bar sensors 311 and 312 are arranged alternately, i.e., 3 bar sensors 1 in the first bar sensor 311 are arranged alternately with 3 bar sensors 1 in the second bar sensor 312. The distance d1 between two adjacent strip sensors 1 in each group of strip sensors 1 is the same, and preferably, the distance d1 is 1.4 m.

In the implementation scenario, a vehicle would normally push through 3 bar sensors (in one group) as it passes through the monitoring area. Thus 3 weighing signals are collected by 3 bar sensors for each axle of the vehicle.

Furthermore, the second sensor unit may be arranged on the road mast near the first sensor unit. The sound sensor in the second sensor unit is provided with a pickup, and the pickup faces the first sensor unit. The acoustic sensor in the second sensor unit may be positioned on the upper transversal frame of the portal (the superstructure of the crossing road).

In fig. 3, one portal 20 is arranged on each side of the first sensor unit in the direction of the roadway. Each portal 20 is disposed across a roadway or lane. Two acoustic sensors are mounted on each gantry 20, so that the second sensor unit comprises 4 acoustic sensors. In particular, on the upper transverse shelf of each portal 20 is mounted a sound sensor, under which the vehicle passes. Since each sound sensor is provided with a microphone 21, the sound sensor is not visible. And the opening direction of each pickup 21 is directed toward the first sensor unit so that the sound sensor can directionally acquire sound signals with as little interference sound signals as possible. Furthermore, the pickup of the at least one sound sensor is directed towards the set of first stripe sensors.

In the implementation scenario, a vehicle passing by would normally push through 3 bar sensors (one set). Thus 3 weighing signals are collected by 3 bar sensors for each axle of the vehicle. Simultaneously, 4 sound signals are collected by 4 sound sensors. And in this case, the weighing signal and the sound signal belonging to the same vehicle can be determined according to the timing of the signals.

The sensors and arrangements between the sensors used in fig. 1-3 above are merely exemplary, and other load cells (e.g., bent plate sensors, etc.) may also be employed, for example.

In addition, another manner can also be taken with respect to the above arrangement of the second sensor unit with respect to the first sensor unit. For example, for a portal in which the second sensor unit is arranged, one portal may be arranged on the side of the first sensor unit in a direction perpendicular to the lane direction, one portal may be arranged on each side of the first sensor unit in a direction perpendicular to the lane direction, or one portal may be arranged on the side of the first sensor unit in a direction perpendicular to the lane direction. And any suitable number of sound sensors may be provided according to the sensing performance of the sound sensors and the sound pickup range of the sound pickup.

It should be noted that although in the above detailed description several units or modules of the monitoring system are mentioned, this division is only illustrative and not mandatory. Indeed, the features and functions of two or more units described above may be embodied in one unit, in accordance with embodiments of the present disclosure. Conversely, the features and functions of one unit described above may be further divided into embodiments by a plurality of units.

It should be understood that the terms "first," "second," "third," and "fourth," etc. in the claims, description, and drawings of the present disclosure are used to distinguish between different objects and are not used to describe a particular order. The terms "comprises" and "comprising," when used in the specification and claims of this disclosure, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.

It is also to be understood that the terminology used in the description of the disclosure herein is for the purpose of describing particular embodiments only, and is not intended to be limiting of the disclosure. As used in the specification and claims of this disclosure, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should be further understood that the term "and/or" as used in the specification and claims of this disclosure refers to any and all possible combinations of one or more of the associated listed items and includes such combinations.

While various embodiments of the present disclosure have been shown and described herein, it will be obvious to those skilled in the art that such embodiments are provided by way of example only. Numerous modifications, changes, and substitutions will occur to those skilled in the art without departing from the spirit and scope of the present disclosure. It should be understood that various alternatives to the embodiments of the disclosure described herein may be employed in practicing the disclosure. It is intended that the following claims define the scope of the disclosure and that equivalents or alternatives within the scope of these claims be covered thereby.

Claims (10)

1. A roadway monitoring system, the roadway monitoring system comprising:

a first sensor unit arranged in a monitoring area of a road surface;

a second sensor unit arranged in the same monitoring area as the first sensor unit;

a data processing unit connected with the first sensor unit and the second sensor unit and configured to periodically analyze and process the weighing signal acquired by the first sensor unit and the sound signal acquired by the second sensor unit so as to generate a monitoring result.

2. The pavement monitoring system of claim 1 wherein the first sensor unit includes a load cell and the second sensor unit includes an acoustic sensor.

3. The pavement monitoring system of claim 2 wherein the load cell includes any of a bar sensor and a flexural plate sensor, and the acoustic sensor includes any of a resistive acoustic sensor, a capacitive acoustic sensor, and a magneto-acoustic sensor.

4. The roadway monitoring system of claim 3, wherein the first sensor unit is disposed on the roadway of the monitoring area and the second sensor unit is disposed adjacent the first sensor unit.

5. A pavement monitoring system according to claim 4, characterised in that the second sensor unit is arranged on a road portal in the monitoring area.

6. A pavement monitoring system according to any one of claims 3 to 5, characterized in that the first sensor unit includes a plurality of sets of strip sensors arranged in a direction perpendicular to the lane direction.

7. The roadway monitoring system of claim 6, wherein each of the plurality of sets of strip sensors includes a plurality of strip sensors arranged perpendicular to the roadway direction and parallel to each other.

8. The roadway monitoring system of claim 7, wherein adjacent two of the plurality of sets of strip sensors are staggered.

9. A pavement monitoring system according to any one of claims 2-5, characterized in that the sound sensor in the second sensor unit is provided with a pickup, and that the pickup is directed towards the first sensor unit.

10. The roadway monitoring system of claim 1, further comprising:

an early warning unit connected with the data processing unit and configured to perform an early warning operation according to the monitoring result.

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