WO2022267281A1 - 一种路基服役性能的健康诊断装置与方法 - Google Patents

一种路基服役性能的健康诊断装置与方法 Download PDF

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WO2022267281A1
WO2022267281A1 PCT/CN2021/126510 CN2021126510W WO2022267281A1 WO 2022267281 A1 WO2022267281 A1 WO 2022267281A1 CN 2021126510 W CN2021126510 W CN 2021126510W WO 2022267281 A1 WO2022267281 A1 WO 2022267281A1
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subgrade
roadbed
road surface
road
pavement layer
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PCT/CN2021/126510
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English (en)
French (fr)
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卢正
唐楚轩
姚海林
刘杰
詹永祥
骆行文
杨明亮
赵阳
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中国科学院武汉岩土力学研究所
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Publication of WO2022267281A1 publication Critical patent/WO2022267281A1/zh

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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00Computer-aided design [CAD]
    • G06F30/20Design optimisation, verification or simulation
    • G06F30/27Design optimisation, verification or simulation using machine learning, e.g. artificial intelligence, neural networks, support vector machines [SVM] or training a model
    • EFIXED CONSTRUCTIONS
    • E02HYDRAULIC ENGINEERING; FOUNDATIONS; SOIL SHIFTING
    • E02DFOUNDATIONS; EXCAVATIONS; EMBANKMENTS; UNDERGROUND OR UNDERWATER STRUCTURES
    • E02D1/00Investigation of foundation soil in situ
    • E02D1/08Investigation of foundation soil in situ after finishing the foundation structure
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10Complex mathematical operations
    • G06F17/11Complex mathematical operations for solving equations, e.g. nonlinear equations, general mathematical optimization problems
    • G06F17/12Simultaneous equations, e.g. systems of linear equations
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F2119/00Details relating to the type or aim of the analysis or the optimisation
    • G06F2119/14Force analysis or force optimisation, e.g. static or dynamic forces

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  • the invention relates to the technical field of roadbed service performance health diagnosis, in particular to a roadbed service performance health diagnosis device and method.
  • Subgrade is one of the most important components of road structure, which determines the long-term service performance of the road. Under the influence of natural factors such as rainfall, evaporation, and temperature fluctuations, as well as the increasing traffic load, the performance of the roadbed will gradually deteriorate, which will cause subsidence and cracking of the pavement structure, and eventually make the road structure invalid. In the past, repairs were often initiated only after structural damage to the pavement, such as cracking, had occurred. If the weak road section can be diagnosed in time at the early stage of subgrade deterioration, and then reinforced by grouting, the failure of the road structure and the damage of the pavement structure can be effectively avoided.
  • the Beckman beam method requires the use of a standard truck with two axles and four wheels on both sides of the rear axle, and a pavement deflection instrument composed of Beckman beams, dial gauges and gauge frames to test the rebound deflection of the subgrade and pavement.
  • This method requires the standard car to be driven at a slower speed while measuring the rebound deflection.
  • the rear axle load of the standard car is divided by the deflection value to obtain the road rebound modulus.
  • the static modulus of resilience of the road which cannot reflect the dynamic performance of the subgrade, and the manual reading of the deflection value through the dial gauge may cause large errors, requiring more personnel to test at the same time.
  • the value of the modulus of resilience measured by the Beckman beam method is the performance of the road as a whole, including the road surface and the subgrade, and cannot reflect the health of the subgrade alone.
  • the drop hammer deflection meter excites the road surface through the free fall of the hammer, and records the impact force of the hammer and the displacement of the hammer at the same time, so as to calculate the rebound modulus of the road and continuously collect the deflection data of the road.
  • This test method usually needs to be carried on a vehicle, and the cost is high.
  • the measured rebound modulus is also the modulus of the overall structure of the road, which cannot reflect the health status of the roadbed alone.
  • the Beckman beam method test obtains the rebound value of the road surface when the standard axle load vehicle load leaves, and the drop weight deflection meter test obtains the maximum deformation value of the road surface under the impact load.
  • These two methods are based on the theoretical solution of a uniform elastic half-space under a static load when inverting the dynamic elastic modulus of the road through the collected data.
  • the road is a typical layered structure, and the properties of the road surface and the roadbed are very different, and the roadbed is also layered and compacted during filling.
  • the subgrade soil is usually in an unsaturated state, which is a state where three phases of solid-liquid-gas exist simultaneously. The existence of liquid and gas has a great influence on the mechanical properties of the soil.
  • the elastic half-space model completely ignores the heterogeneity of the soil medium, which will produce inevitable errors when calculating the inversion.
  • the present disclosure proposes a roadbed service performance health diagnosis device and method, which realizes rapid non-destructive detection of roadbed health status.
  • a health diagnosis device for subgrade service performance including:
  • loading device for applying load to the road
  • the data acquisition device is used to collect the stress and vertical displacement generated by the road surface when the load is applied to the road;
  • the data analysis device is used to perform frequency spectrum analysis on the vertical displacement signal, obtain the propagation velocity of the Rayleigh wave of the pavement layer and the thickness of the pavement layer, and obtain the elastic modulus of the pavement layer according to the propagation velocity; Input the modulus of subgrade soil and the thickness of the pavement layer into the trained subgrade soil modulus calculation model to obtain the subgrade soil elastic modulus; according to the pavement layer elastic modulus, subgrade soil elastic modulus and pavement layer thickness, obtain the subgrade under the standard load The dynamic deformation value of the subgrade is evaluated according to the dynamic deformation value of the subgrade under the standard load.
  • a health diagnosis method for subgrade service performance including:
  • Spectrum analysis is performed on the vertical displacement signal to obtain the propagation velocity of the Rayleigh wave of the pavement layer and the thickness of the pavement layer;
  • the elastic modulus of the pavement layer the elastic modulus of the subgrade soil and the thickness of the pavement layer, the dynamic deformation value of the subgrade under the standard load is obtained;
  • the health status of the subgrade is evaluated according to the dynamic deformation value of the subgrade under the standard load.
  • an electronic device including a memory, a processor, and computer instructions stored in the memory and run on the processor.
  • the computer instructions are run by the processor, a health diagnosis of roadbed service performance is completed. steps described in the method.
  • a computer-readable storage medium for storing computer instructions, and when the computer instructions are executed by a processor, the steps described in a method for health diagnosis of roadbed service performance are completed.
  • This disclosure applies loads to the road, collects the stress and vertical displacement generated by the road surface when the load is applied, and analyzes the stress and vertical displacement to obtain the dynamic deformation value of the subgrade under the standard load, and then according to the subgrade under the standard load.
  • the dynamic deformation value below can diagnose the health state of the subgrade, and realize the rapid non-destructive detection of the health state of the subgrade.
  • FIG. 1 is a schematic diagram of the overall structure of the device disclosed in Embodiment 1 of the present disclosure
  • Fig. 2 is a schematic diagram of the test process when the device disclosed in Embodiment 1 of the present disclosure performs a road test;
  • Fig. 3 is a schematic diagram of a double-layer unsaturated porous elastic medium model disclosed in Example 1 of the present disclosure.
  • Test vehicle 2. Road surface, 3. Subgrade, 4. Displacement sensor, 5. Synchronous wire, 6. Drop hammer guide rod, 7. Drop hammer, 8. Buffer steel plate, 9. Data analysis device.
  • orientation or positional relationship is based on the orientation or positional relationship shown in the drawings, and is only a relative term determined for the convenience of describing the structural relationship between the components or elements of the present disclosure. Public restrictions.
  • a health diagnosis device for roadbed service performance including:
  • loading device for applying load to the road
  • the data acquisition device is used to collect the stress and vertical displacement generated by the road surface when the load is applied to the road;
  • the data analysis device is used to perform frequency spectrum analysis on the vertical displacement signal, obtain the propagation velocity of the Rayleigh wave of the pavement layer and the thickness of the pavement layer, and obtain the elastic modulus of the pavement layer according to the propagation velocity; Input the modulus of subgrade soil and the thickness of the pavement layer into the trained subgrade soil modulus calculation model to obtain the subgrade soil elastic modulus; according to the pavement layer elastic modulus, subgrade soil elastic modulus and pavement layer thickness, obtain the subgrade under the standard load The dynamic deformation value of the subgrade is evaluated according to the dynamic deformation value of the subgrade under the standard load.
  • the loading device includes a test car and a free-falling drop weight and a buffer steel plate installed on the test car, and the drop weight falls on the buffer steel plate when it falls freely.
  • the buffer steel plate is connected to the test vehicle through a retractable drop weight guide rod, and the drop weight falls freely on the buffer steel plate along the drop weight guide rod.
  • the data acquisition device includes a position sensor that can be dropped and retracted installed on the test vehicle and a stress sensor installed on the buffer steel plate.
  • the dynamic deformation value of the subgrade under the standard load is compared with the allowable dynamic deformation value of the top surface of the subgrade to evaluate the health status of the subgrade.
  • the elastic modulus of the pavement layer the elastic modulus of the subgrade soil, the thickness of the pavement layer, the stress generated on the pavement and the vertical displacement of the pavement to form the training samples of the sample road
  • the calculation model of the subgrade soil modulus is trained to obtain the trained good Calculation model of subgrade soil modulus.
  • the vertical displacement of the pavement in the training samples is obtained by inputting the stress generated by the pavement into the double-layer unsaturated poroelastic medium model.
  • the calculation model of the subgrade soil modulus adopts the neural network model.
  • a health diagnosis device for roadbed service performance disclosed in this embodiment will be described in detail with reference to FIGS. 1-3 .
  • a health diagnosis device for subgrade service performance including a loading device, a data acquisition device and a data analysis device.
  • the loading device includes a test car, a drop weight 7 and a buffer steel plate 8 installed on the test car 1 .
  • the drop weight 7 can freely fall from the test vehicle 1, and the buffer steel plate 8 is connected with the test vehicle 1 through the drop weight guide rod 6.
  • the expansion and contraction of the hammer guide rod 6 drives the buffer steel plate 8 to stretch out or retract relative to the test vehicle.
  • the drop hammer 7 freely falls onto the buffer steel plate 8 along the drop hammer guide rod 6 .
  • the data acquisition device includes a displacement sensor 4 installed on the test vehicle 1 and a stress sensor installed on the buffer steel plate 8 .
  • the displacement sensor 4 can be stretched out and retracted from the test vehicle 1 .
  • the data analysis device 9 is installed on the test vehicle 1 and connected with the displacement sensor 4 and the stress sensor through the synchronization wire 5 .
  • test car 1 When the road is tested, the test car 1 is driven to a predetermined position on the road, and the displacement sensor 4, the drop weight guide rod 6 and the buffer steel plate 8 are released from the test car.
  • the displacement sensor 4 After the measurement at this place on the road is completed, as shown in Figure 2, the displacement sensor 4, the drop weight 7, the drop weight guide rod 6 and the buffer steel plate 8 are retracted into the test vehicle, and the vehicle is driven forward out of the effective measurement area of this section. And drive to the next measurement point for testing, realizing the evaluation of the health status of the entire road subgrade.
  • the data analysis device 9 analyzes the vertical displacement and stress, and the specific process of obtaining the evaluation result of the roadbed health state is as follows:
  • the formula for calculating the elastic modulus E1 of the pavement layer is:
  • is the density of the pavement medium
  • is the Poisson's ratio of the pavement medium
  • the calculation model of subgrade soil modulus adopts neural network model or machine learning algorithm, which is:
  • the elastic modulus of the pavement layer, the elastic modulus of the subgrade soil, the thickness of the pavement layer, the stress generated by the pavement and the vertical displacement of the pavement constitute the training sample of the sample road, and the calculation model of the subgrade soil modulus is trained to obtain the trained subgrade soil.
  • the vertical displacement of the pavement in the training sample is obtained by inputting the stress P generated by the pavement into the double-layer unsaturated poroelastic medium model, specifically:
  • the dynamic response problem of the subgrade can be simplified into a spatial axisymmetric model.
  • the overall stress-displacement relationship of the double-layer unsaturated porous elastic medium model can be obtained by using the exact stiffness matrix method and the integral transformation method:
  • the stress generated by the sample road pavement collected by the stress sensor on the buffer steel plate 8 is integrally transformed to obtain the stress Enter the double-layer unsaturated poroelastic medium model expressed by formula (3) to obtain the vertical displacement of the pavement.
  • - ⁇ 2 +2V ⁇ -V 2 ⁇ 2 ;
  • V and ⁇ are the driving speed and vibration frequency of the test vehicle respectively;
  • ⁇ and ⁇ are integral transformation parameters;
  • a 2 , B 2 , C 2 , and D 2 are integral constants.
  • the allowable dynamic deformation value u dr of the top surface of the subgrade is:
  • a c , A s , and A b are coefficients related to road grades, structural layer types and properties
  • a a is the ratio of the dynamic deformation of the top surface of the subgrade to the dynamic deformation amplitude of the road surface.
  • the disclosure applies loads to the road, collects the stress and vertical displacement generated by the road surface when the load is applied, and analyzes the stress and vertical displacement to obtain the dynamic deformation value of the subgrade under the standard load, and then according to the value of the subgrade under the standard load
  • the dynamic deformation value is used to diagnose the health state of the subgrade, and realize the rapid non-destructive detection of the health state of the subgrade.
  • the displacement sensor 4 in this embodiment can be replaced by a speed sensor or an acceleration sensor.
  • a speed sensor or an acceleration sensor the signal collected by the sensor needs to be time-integrated to obtain a displacement signal, and then the displacement signal is analyzed to obtain a subgrade. Dynamic deformation values under standard loads.
  • a method for health diagnosis of roadbed service performance including:
  • Spectrum analysis is performed on the vertical displacement signal to obtain the propagation velocity of the Rayleigh wave of the pavement layer and the thickness of the pavement layer;
  • the elastic modulus of the pavement layer the elastic modulus of the subgrade soil and the thickness of the pavement layer, the dynamic deformation value of the subgrade under the standard load is obtained;
  • the health status of the subgrade is evaluated according to the dynamic deformation value of the subgrade under the standard load.
  • an electronic device including a memory, a processor, and computer instructions stored in the memory and executed on the processor.
  • the computer instructions are executed by the processor, a method disclosed in Embodiment 2 is completed. The steps described in the health diagnosis method of subgrade service performance.
  • a computer-readable storage medium which is used to store computer instructions.
  • the computer instructions are executed by a processor, the method described in the method for health diagnosis of roadbed service performance disclosed in Embodiment 2 is completed. step.
  • the embodiments of the present application may be provided as methods, systems, or computer program products. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.
  • computer-usable storage media including but not limited to disk storage, CD-ROM, optical storage, etc.
  • These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing apparatus to operate in a specific manner, such that the instructions stored in the computer-readable memory produce an article of manufacture comprising instruction means, the instructions
  • the device realizes the function specified in one or more procedures of the flowchart and/or one or more blocks of the block diagram.

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Abstract

本公开公开的一种路基服役性能的健康诊断装置及方法,包括:加载装置,用于向道路施加荷载;数据采集装置,用于采集向道路施加荷载时路面产生的应力和竖向位移;数据分析装置,用于对竖向位移信号进行频谱分析,获得路面层瑞利波的传播速度和路面层厚度,根据传播速度获得路面层弹性模量;将应力、竖向位移、路面层弹性模量和路面层厚度输入训练好的路基土体模量计算模型中,获取路基土体弹性模量;根据路面层弹性模量、路基土体弹性模量和路面层厚度,获得路基在标准荷载下的动变形值,根据路基在标准荷载下的动变形值对路基的健康状态进行评估。实现了对路基健康状态的无损检测。

Description

一种路基服役性能的健康诊断装置与方法 技术领域
本发明涉及路基服役性能健康诊断技术领域,尤其涉及一种路基服役性能的健康诊断装置与方法。
背景技术
本部分的陈述仅仅是提供了与本公开相关的背景技术信息,不必然构成在先技术。
路基是道路结构最重要的组成部分之一,决定了道路的长期服役性能。在降雨、蒸发和温度波动等自然因素影响以及日益增长的交通荷载作用下,路基的性能会逐渐劣化,从而引起路面结构的沉陷、开裂,最终使道路结构失效。以往常常是在路面结构发生破坏,比如开裂之后才开始进行修复。若能在路基劣化的初期及时诊断出薄弱路段,再进行注浆等加固处理,就可以有效避免道路结构失效以及路面结构的破坏。
目前常使用钻孔取芯法、贝克曼梁法、落锤式弯沉仪等方法进行道路性能的评价,但现有的这些方法均存在一些不足之处。钻孔取芯虽然可以检测出不同层位道路结构的性能变化,但这是一种有损检测,会对道路产生破坏,且效率低成本高,取样过程中会不可避免对试样造成扰动。
贝克曼梁法需要使用双轴,后轴双侧4轮的标准载重车,用贝克曼梁、百分表及表架组成的路面弯沉仪测试路基路面的回弹弯沉。这 种方法需要标准车在较慢的速度下行驶的同时测量回弹弯沉,用标准车后轴的载重除以弯沉值得到道路的回弹模量。这实际上得到的是道路的静态回弹模量,不能反映路基的动态性能,且通过百分表人为读取弯沉值时可能产生较大的误差,需要较多的人员同时测试。在道路修建完成后,通过贝克曼梁法测得的回弹模量值是道路整体的性能,包括路面和路基,不能单独反映出路基的健康状况。
落锤式弯沉仪通过落锤自由落体激振路面,同时记录锤击冲击力以及锤击处的位移,由此计算出道路的回弹模量,可以连续采集道路的弯沉数据。这种测试方法通常需要车载,造价较高,测得的回弹模量同样是道路整体结构的模量,无法单独反映路基的健康状态。
贝克曼梁法测试得到的是标准轴载车辆荷载离开时路面的回弹值,落锤式弯沉仪测试得到的是冲击荷载作用下路面产生的最大变形值。这两种方法通过采集得到的数据反演道路的动回弹模量时,都是基于均匀弹性半空间在静止荷载作用下的理论解。但是实际上道路是典型的层状结构,路面和路基性质相差很大,路基在填筑时也是分层压实的。另一方面,路基土体通常处于非饱和的状态,是一个固-液-气三相同时存在的状态,液体和气体的存在对土体的力学特性有很大的影响。而弹性半空间模型完全忽略了土体介质的多相性,在计算反演时会产生不可避免的误差。
故发明人认为,现有的道路性能评价方法,均无法对道路路基进行无损、快速的健康检测。
发明内容
本公开为了解决上述问题,提出了一种路基服役性能的健康诊断装置与方法,实现了对道路路基健康状态的快速无损检测。
为实现上述目的,本公开采用如下技术方案:
第一方面,提出了一种路基服役性能的健康诊断装置,包括:
加载装置,用于向道路施加荷载;
数据采集装置,用于采集向道路施加荷载时路面产生的应力和竖向位移;
数据分析装置,用于对竖向位移信号进行频谱分析,获得路面层瑞利波的传播速度和路面层厚度,根据传播速度获得路面层弹性模量;将应力、竖向位移、路面层弹性模量和路面层厚度输入训练好的路基土体模量计算模型中,获取路基土体弹性模量;根据路面层弹性模量、路基土体弹性模量和路面层厚度,获得路基在标准荷载下的动变形值,根据路基在标准荷载下的动变形值对路基的健康状态进行评估。
第二方面,提出了一种路基服役性能的健康诊断方法,包括:
采集向道路施加荷载时路面产生的应力和竖向位移;
对竖向位移信号进行频谱分析,获得路面层瑞利波的传播速度和路面层厚度;
根据传播速度获得路面层弹性模量;
将应力、竖向位移、路面层弹性模量和路面层厚度输入训练好的路基土体模量计算模型中,获取路基土体弹性模量;
根据路面层弹性模量、路基土体弹性模量和路面层厚度,获得路基在标准荷载下的动变形值;
根据路基在标准荷载下的动变形值对路基的健康状态进行评估。
第三方面,提出了一种电子设备,包括存储器和处理器以及存储在存储器上并在处理器上运行的计算机指令,所述计算机指令被处理器运行时,完成一种路基服役性能的健康诊断方法所述的步骤。
第四方面,提出了一种计算机可读存储介质,用于存储计算机指令,所述计算机指令被处理器执行时,完成一种路基服役性能的健康诊断方法所述的步骤。
与现有技术相比,本公开的有益效果为:
1、本公开通过向道路施加荷载,并采集施加荷载时路面产生的应力和竖向位移,通过对应力和竖向位移分析,获得路基在标准荷载下的动变形值,进而根据路基在标准荷载下的动变形值对路基的健康状态进行了诊断,实现了对路基健康状态的快速无损检测。
本发明附加方面的优点将在下面的描述中部分给出,部分将从下面的描述中变得明显,或通过本发明的实践了解到。
附图说明
构成本申请的一部分的说明书附图用来提供对本申请的进一步理解,本申请的示意性实施例及其说明用于解释本申请,并不构成对本申请的不当限定。
图1为本公开实施例1公开装置的整体结构示意图;
图2为本公开实施例1公开装置进行道路测试时测试过程示意图;
图3为本公开实施例1公开的双层非饱和多孔弹性介质模型示意图。
其中:1、测试车,2、路面,3、路基,4、位移传感器,5、同步导线,6、落锤导杆,7、落锤,8、缓冲钢盘,9、数据分析装置。
具体实施方式:
下面结合附图与实施例对本公开作进一步说明。
应该指出,以下详细说明都是例示性的,旨在对本申请提供进一步的说明。除非另有指明,本文使用的所有技术和科学术语具有与本申请所属技术领域的普通技术人员通常理解的相同含义。
需要注意的是,这里所使用的术语仅是为了描述具体实施方式,而非意图限制根据本申请的示例性实施方式。如在这里所使用的,除非上下文另外明确指出,否则单数形式也意图包括复数形式,此外,还应当理解的是,当在本说明书中使用术语“包含”和/或“包括”时,其指明存在特征、步骤、操作、器件、组件和/或它们的组合。
在本公开中,术语如“上”、“下”、“左”、“右”、“前”、“后”、“竖直”、“水平”、“侧”、“底”等指示的方位或位置关系为基于附图所示的方位或位置关系,只是为了便于叙述本公开各部件或元件结构关系而确定的关系词,并非特指本公开中任一部件或元件,不能理解为对本公开的限制。
本公开中,术语如“固接”、“相连”、“连接”等应做广义理解,表示可以是固定连接,也可以是一体地连接或可拆卸连接;可以是直接相连,也可以通过中间媒介间接相连。对于本领域的相关科研或技术人员,可以根据具体情况确定上述术语在本公开中的具体含义,不能理解为对本公开的限制。
实施例1
为了实现对路基健康状态的快速无损检测,在该实施例中公开了一种路基服役性能的健康诊断装置,包括:
加载装置,用于向道路施加荷载;
数据采集装置,用于采集向道路施加荷载时路面产生的应力和竖向位移;
数据分析装置,用于对竖向位移信号进行频谱分析,获得路面层瑞利波的传播速度和路面层厚度,根据传播速度获得路面层弹性模量;将应力、竖向位移、路面层弹性模量和路面层厚度输入训练好的路基土体模量计算模型中,获取路基土体弹性模量;根据路面层弹性模量、路基土体弹性模量和路面层厚度,获得路基在标准荷载下的动变形值,根据路基在标准荷载下的动变形值对路基的健康状态进行评估。
进一步的,加载装置包括测试车和安装于测试车上的能够自由落体的落锤和缓冲钢盘,落锤自由落体时落于缓冲钢盘上。
进一步的,缓冲钢盘通过能够伸缩的落锤导杆与测试车连接,落锤沿落锤导杆自由落体落于缓冲钢盘上。
进一步的,数据采集装置包括安装于测试车上的能够落下与收回的位置传感器和安装于缓冲钢盘上的应力传感器。
进一步的,将路基在标准荷载下的动变形值与路基顶面允许动变形值进行比较,评估路基的健康状态。
进一步的,根据样本道路的路面层弹性模量、路基土体弹性模量、路面层厚度、路面产生应力和路面竖向位移构成训练样本,对路基土体 模量计算模型进行训练,获得训练好的路基土体模量计算模型。
进一步的,训练样本中的路面竖向位移,通过将路面产生应力输入双层非饱和多孔弹性介质模型中获得。
进一步的,路基土体模量计算模型采用神经网络模型。
结合图1-3对本实施例公开的一种路基服役性能的健康诊断装置进行详细说明。
一种路基服役性能的健康诊断装置,包括加载装置、数据采集装置和数据分析装置。
如图1所示,加载装置包括测试车及安装于测试车1上的落锤7和缓冲钢盘8。
其中,落锤7能够从测试车1上自由降落,缓冲钢盘8通过落锤导杆6与测试车1连接,落锤导杆6为伸缩杆,能够相对于测试车伸出与收回,落锤导杆6的伸缩带动缓冲钢盘8相对于测试车伸出或收回。
落锤7沿落锤导杆6自由降落至缓冲钢盘8上。
数据采集装置包括安装于测试车1上的位移传感器4和安装于缓冲钢盘8上的应力传感器。
位移传感器4能够从测试车1上伸出与收回。
数据分析装置9安装于测试车1上,通过同步导线5与位移传感器4和应力传感器连接。
当对道路进行测试时,将测试车1行驶至道路的预定位置处,将位移传感器4、落锤导杆6和缓冲钢盘8从测试车内放出。
将落锤7放出做自由落体,砸至缓冲钢盘8上,对道路进行激振。
当落锤7砸至缓冲钢盘8上时,通过位移传感器4采集道路产生的竖向位移,通过应力传感器采集道路产生的应力。
将道路产生的竖向位移和应力发送至数据分析装置9,通过数据分析装置9对竖向位移和应力进行分析,进而对路基的健康状态进行评估,当路基土体健康状态较差时,发出报警,提示该处路基土体的健康状况较差,需要及时采取措施补强。
当道路该处测量完成后,如图2所示,将位移传感器4、落锤7、落锤导杆6和缓冲钢盘8收回测试车内,将车辆向前行驶出该段有效测量区,并行驶至下一测量点进行测试,实现了对整条道路路基健康状态的评估。
数据分析装置9对竖向位移和应力进行分析,获取路基健康状态评估结果的具体过程为:
S1:对位移传感器4获得的竖向位移信号进行频谱分析,获得测试段的频散曲线,进而获得路面层瑞利波的传播速度V R和路面层厚度h 1,利用传播速度V R获得路面层弹性模量E 1
其中,路面层弹性模量E 1的计算公式为:
Figure PCTCN2021126510-appb-000001
其中ρ是路面介质的密度,ν是路面介质的泊松比。
S2:将应力P、竖向位移
Figure PCTCN2021126510-appb-000002
路面层弹性模量E 1和路面层厚度h 1输入训练好的路基土体模量计算模型中,获取路基土体弹性模量E 2
其中,路基土体模量计算模型采用神经网络模型或机器学习算法,为:
Figure PCTCN2021126510-appb-000003
通过样本道路的路面层弹性模量、路基土体弹性模量、路面层厚度、路面产生应力和路面竖向位移构成训练样本,对路基土体模量计算模型进行训练,获得训练好的路基土体模量计算模型。
训练样本中的路面竖向位移,通过将路面产生应力P输入双层非饱和多孔弹性介质模型中获得,具体为:
在落锤的轴对称竖向冲击荷载作用下,路基的动力响应问题可以简化成空间轴对称模型,为了便于说明,这里以如图3所示的双层模型为例,基于非饱和多孔弹性介质计算模型,使用精确刚度矩阵法和积分变换方法可以得到双层非饱和多孔弹性介质模型整体的应力与位移关系:
Figure PCTCN2021126510-appb-000004
其中
Figure PCTCN2021126510-appb-000005
是积分变换域内各层界面上的位移;
Figure PCTCN2021126510-appb-000006
是积分变换域内各层界面上的应力;[B]是双层模型的整体柔度矩阵,使用精确刚度矩阵法和积分变换方法可以从非饱和多孔介质的控制方程(4)推导得到。
Figure PCTCN2021126510-appb-000007
其中σ ij表示总应力;ρ=(1-n)ρ s+nS rρ w+n(1-S ra为非饱和多孔介质总密度,n为土体孔隙度,S r表示饱和度,ρ s、ρ w和ρ a分别为各相介质的物质密度;(·)表示关于时间的求导;孔隙水与孔隙气体在i方向上相对土颗粒的位移分量为W i和V i;g代表重力加速度;k w和k a分别表示孔隙水和孔隙气体的渗透系数;δ ij为Kronecker符号;p表示作用在土颗粒周围的平均孔隙压力;λ和μ为Lame常数;第一Biot系数a=1-K b/K s,K b和K s分别为土骨架和土颗粒的体积压缩模量,且有K b=λ+2μ/3和K b<<K s
Figure PCTCN2021126510-appb-000008
为体应变,u表示土颗粒位移矢量;ε ij为应变张量;
Figure PCTCN2021126510-appb-000009
Figure PCTCN2021126510-appb-000010
A 14=1,
Figure PCTCN2021126510-appb-000011
A 24=1,
Figure PCTCN2021126510-appb-000012
α、m和d为土水特征曲线模型拟合参数;S e为有效饱和度。
将通过缓冲钢盘8上的应力传感器采集的样本道路路面产生应力进行积分变换后获得应力
Figure PCTCN2021126510-appb-000013
输入公式(3)表述的双层非饱和多 孔弹性介质模型中获得路面竖向位移。
由于双层非饱和多孔弹性介质模型中不同层位有不同的力学参数,根据实际的样本道路结构以及规范的要求,在可能的范围内对各个力学参数取大量的组合P E 1E 2h 1进行路面竖向位移的计算,得到在道路顶面与位移传感器4相同位置处的竖向位移,例如
Figure PCTCN2021126510-appb-000014
S3:通过路面层弹性模量E 1、路基土体弹性模量E 2和路面层厚度h 1,获得路基在标准荷载下的动变形值u z,路基在标准荷载下的动变形值u z的计算公式为:
Figure PCTCN2021126510-appb-000015
式中:
Figure PCTCN2021126510-appb-000016
Figure PCTCN2021126510-appb-000017
α=-ω 2+2Vωβ-V 2β 2
Figure PCTCN2021126510-appb-000018
V、ω分别为测试车的行驶速度和振动频率;β、γ为积分变换参数;A 2、B 2、C 2、D 2为积分常数。
S4:根据路基在标准荷载下的动变形值u z对路基的健康状态进行评估。
具体为:将路基在标准荷载下的动变形值u z与路基顶面允许动变形值u dr进行比较,评估道路的健康状态。
当u z>u dr时自动记录当前测试位置,发出警报,提示该处路基土体的健康状况较差,需要及时采取措施补强。
其中,路基顶面允许动变形值u dr为:
Figure PCTCN2021126510-appb-000019
其中A c、A s、A b为与公路等级、结构层类型和性质有关的系数,A a为路基顶面动变形与路表面动变形幅值之比。
本公开通过向道路施加荷载,并采集施加荷载时路面产生的应力和竖向位移,通过对应力和竖向位移分析,获得路基在标准荷载下的动变形值,进而根据路基在标准荷载下的动变形值对路基的健康状态进行了诊断,实现了对路基健康状态的快速无损检测。
另:本实施例中的位移传感器4可以采用速度传感器或加速度传感器代替,当采用速度传感器或加速度传感器时,需要对传感器采集的信号进行时间积分获得位移信号,之后对位移信号进行分析,获得路基在标准荷载下的动变形值。
实施例2
在该实施例中,公开了一种路基服役性能的健康诊断方法,包括:
采集向道路施加荷载时路面产生的应力和竖向位移;
对竖向位移信号进行频谱分析,获得路面层瑞利波的传播速度和路面层厚度;
根据传播速度获得路面层弹性模量;
将应力、竖向位移、路面层弹性模量和路面层厚度输入训练好的路基土体模量计算模型中,获取路基土体弹性模量;
根据路面层弹性模量、路基土体弹性模量和路面层厚度,获得路基在标准荷载下的动变形值;
根据路基在标准荷载下的动变形值对路基的健康状态进行评估。
实施例3
在该实施例中,公开了一种电子设备,包括存储器和处理器以及存储在存储器上并在处理器上运行的计算机指令,所述计算机指令被处理器运行时,完成实施例2公开的一种路基服役性能的健康诊断方法所述的步骤。
实施例4
在该实施例中,公开了一种计算机可读存储介质,用于存储计算机指令,所述计算机指令被处理器执行时,完成实施例2公开的一种路基服役性能的健康诊断方法所述的步骤。
以上仅为本申请的优选实施例而已,并不用于限制本申请,对于本领域的技术人员来说,本申请可以有各种更改和变化。凡在本申请的精神和原则之内,所作的任何修改、等同替换、改进等,均应包含在本申请的保护范围之内。
本领域内的技术人员应明白,本申请的实施例可提供为方法、系统、或计算机程序产品。因此,本申请可采用完全硬件实施例、完全软件实施例、或结合软件和硬件方面的实施例的形式。而且,本申请可采用在一个或多个其中包含有计算机可用程序代码的计算机可用存储介质(包括但不限于磁盘存储器、CD-ROM、光学存储器等)上实施的计算机程序产品的形式。
本申请是参照根据本申请实施例的方法、设备(系统)、和计算机程序产品的流程图和/或方框图来描述的。应理解可由计算机程序指令实现流程图和/或方框图中的每一流程和/或方框、以及流程图 和/或方框图中的流程和/或方框的结合。可提供这些计算机程序指令到通用计算机、专用计算机、嵌入式处理机或其他可编程数据处理设备的处理器以产生一个机器,使得通过计算机或其他可编程数据处理设备的处理器执行的指令产生用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的装置。
这些计算机程序指令也可存储在能引导计算机或其他可编程数据处理设备以特定方式工作的计算机可读存储器中,使得存储在该计算机可读存储器中的指令产生包括指令装置的制造品,该指令装置实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能。
这些计算机程序指令也可装载到计算机或其他可编程数据处理设备上,使得在计算机或其他可编程设备上执行一系列操作步骤以产生计算机实现的处理,从而在计算机或其他可编程设备上执行的指令提供用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的步骤。
最后应当说明的是:以上实施例仅用以说明本发明的技术方案而非对其限制,尽管参照上述实施例对本发明进行了详细的说明,所属领域的普通技术人员应当理解:依然可以对本发明的具体实施方式进行修改或者等同替换,而未脱离本发明精神和范围的任何修改或者等同替换,其均应涵盖在本发明的权利要求保护范围之内。

Claims (10)

  1. 一种路基服役性能的健康诊断装置,其特征在于,包括:
    加载装置,用于向道路施加荷载;
    数据采集装置,用于采集向道路施加荷载时路面产生的应力和竖向位移;
    数据分析装置,用于对竖向位移信号进行频谱分析,获得路面层瑞利波的传播速度和路面层厚度,根据传播速度获得路面层弹性模量;将应力、竖向位移、路面层弹性模量和路面层厚度输入训练好的路基土体模量计算模型中,获取路基土体弹性模量;根据路面层弹性模量、路基土体弹性模量和路面层厚度,获得路基在标准荷载下的动变形值,根据路基在标准荷载下的动变形值对路基的健康状态进行评估。
  2. 如权利要求1所述的一种路基服役性能的健康诊断装置,其特征在于,加载装置包括测试车和安装于测试车上的能够自由落体的落锤和缓冲钢盘,落锤自由落体时落于缓冲钢盘上。
  3. 如权利要求2所述的一种路基服役性能的健康诊断装置,其特征在于,缓冲钢盘通过能够伸缩的落锤导杆与测试车连接,落锤沿落锤导杆自由落体落于缓冲钢盘上。
  4. 如权利要求2所述的一种路基服役性能的健康诊断装置,其特征在于,数据采集装置包括安装于测试车上的能够落下与收回的位置传感器和安装于缓冲钢盘上的应力传感器。
  5. 如权利要求1所述的一种路基服役性能的健康诊断装置,其特征在于,将路基在标准荷载下的动变形值与路基顶面允许动变形值进行比较,评估路基的健康状态。
  6. 如权利要求1所述的一种路基服役性能的健康诊断装置,其特征在于,根据样本道路的路面层弹性模量、路基土体弹性模量、路面层厚度、路面产生应力和路面竖向位移构成训练样本,对路基土体模量计算模型进行训练,获得训练好的路基土体模量计算模型。
  7. 如权利要求6所述的一种路基服役性能的健康诊断装置,其特征在于,训练样本中的路面竖向位移,通过将路面产生应力输入双层非饱和多孔弹性介质模型中获得。
  8. 一种路基服役性能的健康诊断方法,其特征在于,包括:
    采集向道路施加荷载时路面产生的应力和竖向位移;
    对竖向位移信号进行频谱分析,获得路面层瑞利波的传播速度和路面层厚度;
    根据传播速度获得路面层弹性模量;
    将应力、竖向位移、路面层弹性模量和路面层厚度输入训练好的路基土体模量计算模型中,获取路基土体弹性模量;
    根据路面层弹性模量、路基土体弹性模量和路面层厚度,获得路基在标准荷载下的动变形值;
    根据路基在标准荷载下的动变形值对路基的健康状态进行评估。
  9. 一种电子设备,其特征在于,包括存储器和处理器以及存储在存储器上并在处理器上运行的计算机指令,所述计算机指令被处理器运行时,完成权利要求8所述的一种路基服役性能的健康诊断方法的步骤。
  10. 一种计算机可读存储介质,其特征在于,用于存储计算机指 令,所述计算机指令被处理器执行时,完成权利要求8所述的一种路基服役性能的健康诊断方法的步骤。
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