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Building a Large Bridge Structural Monitoring System Based on CompactRIO and LabVIEW

Bing Zhou, CCCC Highway Consultants CO., Ltd.

"With this application, we introduced LabVIEW and CompactRIO to safety monitoring and structural analysis of bridges in China for the first time. By combining advanced data processing and signal analysis technology, we created a complete, systematic application for data acquisition, transmission, preprocessing, and control for the comprehensive monitoring system of a long-span, extra-large bridge."

- Bing Zhou, CCCC Highway Consultants CO., Ltd.,

The Challenge:

Verifying and analyzing the structural parameters of a distributed, nonlinear, strong-coupling, multivariable long-span bridge system with complicated time variation.

The Solution:

Using NI CompactRIO hardware and the NI LabVIEW FPGA Module to create a distributed signal acquisition system that can quickly and accurately perform online analysis and secondary processing of structure parameters from a system using NI LabVIEW software to provide a complete, systematic solution to acquire data from a long-span bridge monitoring system.

Author(s):

Bing Zhou - CCCC Highway Consultants CO., Ltd.,
Xiaofei Sun - CCCC Highway Consultants CO., Ltd.,

 

As bridge design and construction capabilities have improved, long-span bridges have emerged as one of the most important technology breakthroughs. Larger bridges are more aesthetically appealing and offer more complex functions, but they also present safety and durability concerns such as structural health monitoring, safety evaluation, and lifetime prediction. With the development of sensor testing technology, computer information processing techniques, structural analysis techniques, and bridge engineering techniques, we can now perform safety monitoring and deploy safety alarms earlier for extra-large bridges. We can take advantage of advanced intelligence materials and construction technologies originally used in military fields for more intelligent, systematic bridge structural health monitoring.

 

The Xiamen Jimei Bridge is an important part of the sea channel crossing between the rural area of Xiamen and the urban roads of Xiamen. Jimei Bridge withstands a huge traffic flow, which makes structural health monitoring extremely important. We chose NI hardware and software to create a rugged, reliable structural monitoring system for the Xiamen Jimei Bridge.

 

Details of the Monitoring System

The monitoring system includes load monitoring of the environment around the bridge site; wind load monitoring; temperature and humidity monitoring; temperature gradient monitoring of the control section; and traffic load (shared with a toll-by-weight system). It also features dynamic and static response structure monitoring including monitoring spatial-change of the main bridge, mainly on the deflection of the midspan for each span; monitoring static stress of the control section of the main bridge and approach bridge; monitoring external and internal prestressing of the main bridge and approach bridge; monitoring structural dynamics and vibration characteristics and how they change the main bridge and approach bridge.

 

 

Depending on the functional requirements, the safety early-alarming system includes the following subsystems:

 

1. An automated sensing test subsystem that includes a sensor submodule to convert various monitoring data into electrical (optical) signals; a data acquisition and transmission module for converting the monitoring signals into digital signals and completing the remote transmission; and a data processing and control module for preprocessing the monitoring signals and providing efficient monitoring data for other subsystems. The system also controls the acquisition of monitoring parameters as required.

2. An electronic manual patrol maintenance management subsystem

3. A comprehensive safety evalution subsystem

4. A central database subsystem

5. A user interface subsystem

 

Figure 1 illustrates the system structure.

 

Data acquisition, transmission, preprocessing and control subsystem of monitoring system are introduced mainly as follows:

 

 

Hardware Implementation

We used three CompactRIO acquisition systems located on the right and left sides of the bridge and on the bus rapid transit (BRT) lane on the bridge. The system acquires signals and serial signals from an acceleration synchronous acquisition pressure transmitter, a hemocytometer, an emoscope, a vibration string stress meter, and a magnetic-flux cable-force gauge. The sensors offer various output signals, which greatly increases the difficulty of system development. The system uses appropriate acquisition equipment and schemes for different sensors. Figure 2 shows the components of the system structure.

 

The CompactRIO programmable industrial I/O system features an embedded controller and chassis, a signal acquisition card with multiple functions, and an industrial-grade design. We used the following CompactRIO products:

 

  • NI cRIO-9014 embedded controller to design custom hardware
  • NI cRIO-9104 8-slot embedded chassis with operating temperature between -40 and 70°C and a 3 million gate reconfigurable I/O (RIO) field-programmable gate array (FPGA) core for its excellent processing to generate the user-defined control and signal processing circuit with LabVIEW
  • NI 9215 module to acquire the voltage signal of the unidirectional and three-directional accelerometer by using a 4-channel high-speed synchronous data acquisition card
  • NI 9401 8-channel high-speed digital I/O signal and 100 ns super-high-speed digital input and output to synchronize acceleration
  • NI 9871 standard RS485 communication card with magnetic flux sensor that uses magnetoelastic instrument for acquisition
  • NI 9871 standard RS485 communication card with ultrasonic three-directional anemoscope connected to the standard NI 9871 RS485 communication card
  • NI 9203 8-channel analog current acquisition module for the pressure transmitter output signal as well as temperature and humidity instrument at 4 to 20 mA respectively, sensor with standard current signal output connected to NI 9203
  • Fiber Bragg grating (FBG) temperature sensor and strain sensor using an FBG sensing network analyzer with Ethernet signal output for acquisition

 

We needed a real-time system with a high level of synchronization for the vibration acceleration of the bridge. We installed a global positioning system (GPS) clock receiver on each acquisition station using GPS-accurate time-service technology. With the NI 9401 100 ns super-high-speed digital synchronous card, we ensured synchronized acceleration-data acquisition by using LabVIEW and configuring an acquisition strategy.

 

 

Transmission and Control of Data Acquisition

The system acquires signal data and uses terminal hardware running the NI LabVIEW Real-Time Module on the acquisition station. The station provides a series of standard interfaces and commands that interact with the control terminal, the monitoring terminal, and the data storage terminal, which is where the users are located (see Figure 3).

 

The data processing and control system server sends network command messages to the CompactRIO acquisition station by controlling the start and stop of the sensor acquiring data; querying the operating state of the sensor, acquisition unit, conditioner, and other acquisition equipment; checking and modifying the parameter, label, and other acquisition unit and conditioner information; and configuring and changing acquisition and storage tasks by modifying the configuration file and loading it into the acquisition station

 

Data Processing and Control Module

The system must preprocess the acquired data before submission to a follow-up subsystem. The subsystem consists of a data acquisition control module, a data classification and extraction module, a monitoring database, and a user interface (see Figure 4).

 

The structural state characteristic parameter refers to physical quantities such as deflection, stress, and cable force that can reflect structural features; the sensor acquisition system obtains the sensor readings, which reflect electrical signals. It is critical to convert the electrical signal into structural characteristic parameters (see Figure 5).

 

The system filters static data with live load and wind-induced vibration. Static parameters after filtration only include the effect of temperature on the structure. The system uses lowpass filtering and amplitude domain analysis conducted at the time of acquisition. For dynamic parameters, we consider bandpass filtering within the frequency range tested.

 

The data storage engine stores the designated data based on timeframe. Each data package has the data content acquired during an interval (1 s) at one station (1 data acquisition channel). The data file names include the following information: sample data start time (hour, minute, second), data storage mode (data trigger description), sampling rate, data point number, maximum value, minimum value, mean value, and data variance. Document content includes sampled data of each point.

 

Depending on the data storage mode, the storage strategy for the data file is as follows. In intermittent storage, each section of continuous signal data of each channel is saved to a file. In triggered storage, each section of continuous signal data of each triggered channel is saved to a file. In manual continuous storage, if continuous data that should be stored is too large, signal data can automatically save to a new file every 10 min, depending on the data file size. The system can automatically delete previous data files (up to a week), depending on hard disk space available.

 

 

Software Implementation

There are two parts of the software system: the data acquisition software (running on the FPGA of CompactRIO), and the data processing and control software (running on the host computer).

 

The data acquisition software is a real-time system based on LabVIEW featuring an FPGA program that conducts acquisition, storage, and control tasks of mass data. It mainly includes sampling, de-sampling, and vibration characteristic value calculation of signals such as acceleration, wind, and temperature, as well as GPS time setting, timing storage, and acquisition channel setting. The program is written on the FPGA hardware module, compiled into bit stream file through a series of conversions, and downloaded to the FPGA module for operation. Multiple acquisition stations use the unified software architecture to achieve the modularity and normalization of acquisition tasks, accurate synchronous acquisition among multiple chassis, and local data storage.

 

We developed the data processing and control software using LabVIEW. The data processing and control workstation software platform receives the original data from the lower computer and operates a state of equipment workstation by TCP protocol in real time. It receives and interprets data and sends commands in the designated message format. It also extracts the characteristic parameter of the structural state by using LabVIEW subVIs such as signal analysis, digital filtering, and statistical analysis. First, the system packages data by the user-defined structure, then the data interchange among VIs occurs in the queue. The first-in, first-out mechanism of the queue effectively achieves data integrity and stability.

 

Our software platform uses LabVIEW and a standard data interface. Electric power monitoring software provides a visual monitoring interface to help users understand the operating state of the field sensor, uninterruptible power supply (UPS), magnetoelastic instrument, and the acquisition unit in a convenient, quick manner. Users can call out the historical operating state curve of electric equipment and complete the data management corresponding to the host computer by querying the historical database (see Figure 6).

 

 

Software Implementation

There are two parts of the software system: the data acquisition software (running on the FPGA of CompactRIO), and the data processing and control software (running on the host computer).

 

The data acquisition software is a real-time system based on LabVIEW featuring an FPGA program that conducts acquisition, storage, and control tasks of mass data. It mainly includes sampling, de-sampling, and vibration characteristic value calculation of signals such as acceleration, wind, and temperature, as well as GPS time setting, timing storage, and acquisition channel setting. The program is written on the FPGA hardware module, compiled into bit stream file through a series of conversions, and downloaded to the FPGA module for operation. Multiple acquisition stations use the unified software architecture to achieve the modularity and normalization of acquisition tasks, accurate synchronous acquisition among multiple chassis, and local data storage.

 

We developed the data processing and control software using LabVIEW. The data processing and control workstation software platform receives the original data from the lower computer and operates a state of equipment workstation by TCP protocol in real time. It receives and interprets data and sends commands in the designated message format. It also extracts the characteristic parameter of the structural state by using LabVIEW subVIs such as signal analysis, digital filtering, and statistical analysis. First, the system packages data by the user-defined structure, then the data interchange among VIs occurs in the queue. The first-in, first-out mechanism of the queue effectively achieves data integrity and stability.

 

Our software platform uses LabVIEW and a standard data interface. Electric power monitoring software provides a visual monitoring interface to help users understand the operating state of the field sensor, uninterruptible power supply (UPS), magnetoelastic instrument, and the acquisition unit in a convenient, quick manner. Users can call out the historical operating state curve of electric equipment and complete the data management corresponding to the host computer by querying the historical database (see Figure 6).

 

Data Real-Time Display and Early Warning Software Interface

Figure 8 shows the submodule interface of the real-time display and early warning software for the bearing platform seismic monitoring item. In addition to the operating button and display control shared by each submodule of the early-warning software, this module includes a 1 s data package oscillogram sent from the data processing and control server, installation section location diagram, early warning light and information, as well as the current 1 s acceleration time travel curve and automatic spectrum curve diagram.

 

The submodule interface of the real-time display and early warning software for deviation monitoring is pictured in Figure 9. In addition to the operating button and display control shared by each submodule of the early warning software, this module includes a 1 s data package oscillogram sent from the data processing and control server, installation section location diagram, early warning light and information, as well as real-time display of the current movement in the vertical and horizontal direction of the bridge.

 

 

Field Results

We created a system featuring three workstations that perform data acquisition, reduction, and transmission of the nearby sensor. First, the CompactRIO acquisition module performs necessary preconditioning for the signals of various sensors installed on the bridge. It then performs A/D conversion based on a certain sampling rate and simultaneously stores it on the data acquisition station computer. The system sends analog or digital signals from various sensors to a data processing and control computer located in the management and monitoring center of the field data acquisition station through industrial Ethernet after preprocessing and acquisition.

 

Conclusion

Seamless connection between CompactRIO and LabVIEW helped us easily customize lower level hardware, quickly develop our embedded system control and data acquisition application, and greatly reduce the technical risk of system development and production. The powerful data acquisition and signal processing ability of LabVIEW significantly reduced development time of the acquisition terminal software. With the help of the LabVIEW Real-Time and LabVIEW FPGA modules, our acquisition terminal can perform high-quality data acquisition, signal processing, data transmission, and data storage in real time, providing flexible and strong bottom data support for the safety monitoring system of the whole bridge structure.

 

We needed system hardware that could withstand a severe marine environment and harsh bridge deck conditions. The rugged CompactRIO system met the rigorous industrial-grade demands and met our requirements in the complicated and severe marine environment, and retained reliability.

 

With this application, we introduced LabVIEW and CompactRIO to safety monitoring and structural analysis of bridges in China for the first time. By combining advanced data processing and signal analysis technology, we created a complete, systematic application for data acquisition, transmission, preprocessing, and control for the comprehensive monitoring system of a long-span, extra-large bridge.

 

Our CompactRIO application in the structure safety monitoring system of the Xiamen Jimei Bridge is the first successful use case of the platform in the field of domestic structure safety monitoring. The CompactRIO platform runs in a normal and stable manner with favorable comments in the industry and is ideal for building an acquisition terminal.

 

Author Information:

Bing Zhou
CCCC Highway Consultants CO., Ltd.,
China

Figure 1: Bridge Structural Health Monitoring System (SHM)
Figure2: Automatic Sensing Subsystem
Figure: 3 Data Acquisition Station State and Control Interface
Figure 4: Data Acquisition, Processing, and Control Subsystem
Figure 5: Flow Diagram of Data Processing and Control Software
Figure. 6: Electric Power Monitoring Interface for Acquisition Station
Figure. 7: State and Control Module Interface for Acquisition Station
Figure 8: Seismic Motion Monitoring Module
Figure. 9: Deviation Submodule Interface