Multiprotocol Industrial Control Data Acquisition System

Published Date: 02 Nov 2017

ABSTRACT

DAQ (Data Acquisition) is simply the process of bringing the real-world data, such as voltage, pressure, temperature, humidity, etc., into the PC for processing, storing and analyzing of the manipulated data. Modern industrial controlling and data acquisition system utilizing embedded system modules have played an irreplaceable role in this field. Here, a data acquisition (DAQ) system has been developed, which will read out data such as humidity, air velocity and photovoltaic data and serves as a prototype system for the industrial and agricultural applications. This system is a modular, flexible and scalable DAQ in which the hardware and protocols used are standards-based, such as ARM Cortex and serial-RS-232 and wireless-ZigBee protocols.

Keywords: Data Acquisition concepts, ARM Cortex, wired and wireless protocols.

INTRODUCTION

DAQ is defined as the process of taking real-world signals such as voltage or current signal, into the PC for processing, storing and analyzing of the manipulated data. The real-world signal that we are trying to analyze can be represented by physical phenomena. Nowadays, computers with ESIA, ISA, PCI or PCMCIA bus is used for data acquisition in testing and measuring, laboratory applications, industrial automation environments and research by most of the scientists and engineers. Many applications use plug-in boards to acquire data and transfer it directly to computer memory. In some cases, DAQ hardware can be incorporated within the PC and communicated to the external world by means of parallel or serial port. Typically, DAQ plug-in boards are general-purpose data acquisition devices that are well suited for measuring voltage signals.

However, the output signals of many real-world sensors and transducers must be processed or conditioned before the continuous signal is fed to DAQ device for accurate and effective acquisition of the signal. In general, front end preprocessing is also termed as signal conditioning [1]. It incorporates the following functions; signal amplification, filtering, electrical isolation and multiplexing. The negative aspect of this board based DAQ systems are its enormous power consumption and bulky nature. (E.g. they may consume up to be 10W-15W from a 5V to l0 V power supply). The above drawbacks are the real-world challenges faced by modern electronic circuits and system design.

The existing DAQ system is categorized into three types. First category is the computer-based class, which utilizes a computer-processing power to perform the desired data manipulation, visualization, storage, and/or decision making [3], [4]. Embedded micro controller based systems [5] comes under the second category of DAQ system, which has the advantages such as high performance and portability, but they have fixed architecture. However, there exists a third category of DAQs, which involves a hardware reconfigurable Field-Programmable Gate Array (FPGA). The integration of multiple components on a single package is allowed in modern high-capacity FPGA, which includes processing, storage and input-output capabilities that is necessary for DAQ systems [6], [7]. Therefore, it is not scalable.

Here the proposed system introduces a scalable data-acquisition technique in which multiprotocol for the process of data-acquisition, built out of ARM Cortex processor is used.

HARDWARE DESIGN OF THE SYSTEM

The overall hardware design of the system is shown in fig 1. ARM Cortex-M0 processor board from NXP has been chosen as the main processing unit because of the advanced architecture, performance and low power requirements. This system is designed to support the usage of many kinds of protocols. Existing data- acquisition system using ARM processor supports either with wired protocol or with wireless protocols only. However, this newly designed system can be used with both wired and wireless protocols, and it can automatically detect the enabled protocol and accordingly transfer the data from the processor. Here this proposed system use humidity, air velocity and light sensor to acquire the data for industrial and agricultural applications.

Humidity

Air Velocity

Light

ARM

Cortex

USB

Wireless

Wired

PC

FIGURE 1. Overall Hardware Block Diagram

From these sensors, acquired data is sent to the ARM Cortex processor and through the USB device, it automatically transfers the data either wired or wireless to the PC. In the PC, we can monitor the real-time data.

HARDWARE REQUIREMENTS

The hardware requirements for this proposed system are: humidity, air velocity and light sensors, ARM Cortex-M0 processor board with RS-232 port and, which supports ZigBee transceiver chips and PC for data processing.

SENSORS

Humidity Sensor:

The humidity sensor shown in the following figure 2 will operate in the frequency range of 500 to 2 KHz, and its response time is less than 10s. The maximum power supply given to the sensor is 1.5V and its accuracy will be ±5%. It is small and light in weight.

FIGURE 2. Humidity Sensor

Light Sensor:

The resistance range of the photo resistor used here as in figure 3 is in the range of 5 to 10KΩ and operates in the temperature range of -30°C to 70°C. The maximum permissible power dissipation is 70mW. Its temperature coefficient is 0.6, and it has a dark resistance of 1.

FIGURE 3. Light Sensor

Air velocity sensor:

The Air Velocity Transducer 8455 shown in fig 4 is used for air velocity measurements, beneficial in research and development labs played an important role in this system design. The transducer probe located in the upstream is used for calculating the flow turbulence.

FIGURE 4. Air Velocity Sensor

For this experimental setup, DC motor and a fan situated at the top of the DC motor is used. DC motor acts as a DC generator in which the fan rotates according to the electricity induced by the motor. This can cover a wide range of measurement applications (Range: 25–10,000 ft/min) and it has a fast response time.

ARM Cortex-M0 CONTROLLER

The ARM Cortex-M0 is a 32-bit general purpose microprocessor which consumes very low power and is of high performance. Operating frequency for the CPU ranges over up to 50 MHz. Peripheral components along with LPC1114 ARM micro controller are 64 KB of flash memory, 8 KB of data memory, one RS-232 UART, one I2C-bus interface, two SPI interfaces, which can support Serial SCSI protocol features, two pairs of general-purpose counter/timers, 42 general-purpose I/O pins and a 10-bit ADC.

WIRED PROTOCOL

An RS-232 port was a standard feature of a personal computer with this; we can interface the PC to modems, printers, mice, storage devices, power supplies without interrupt, and peripheral devices. Industrial machines or scientific instruments have exclusive usage.

Power to peripheral devices cannot be done via a RS-232 device. Driving the signals at a lesser voltage is the common deviation from the standard. Some of the manufacturers, therefore, built transmitters, which are operated with +5 V and -5 V and labeled as "RS-232 compatible." For USB based connections, corresponding device drivers are utilized, which allows application programs to access the USB-connected devices. USB to RS-232 convertors may not be supported by all software on all PCs, which may cause the reduction in bandwidth along with greater latency.

WIRELESS PROTOCOL

Monitoring [8] the weather parameters are critical in many agriculture/industrial applications. Furthermore, usage of wireless protocol plays a major role. To make it simple and cost effective ZigBee technology is used, and its parameters are displayed on the PC. This system contains two nodes: First is transmitter node and the second is receiver node, and both can be of any number.

The transmitter part consists of weather sensors, micro controller and ZigBee transmitter, while the receiver end contains a PC with the ZigBee receiver interface. This system design with wireless protocol helps an industry to monitor the remote parameters in real time. In addition to the above advantages, use of ZigBee favored an easy installation platform which is a low-cost solution for low bit rate transmission. The overall block diagram with wired and wireless protocols is shown in the following figure 5.

ARM-Cortex Processor

Amplifier

Amplifier

Amplifier

Humidity

Light

PC

RS-232

Air Velocity

ZigBee

ZigBee

FIGURE 5. Block diagram of the Data Acquisition System

SOFTWARE REQUIREMENTS

The software used in DAQ system is based on Embedded C language and developed using Keil IDE and Visual basic 6.0 for monitoring [8] the parameters in PC. The simulation result of the analog to digital conversion using Keil IDE is shown in fig 6.

FIGURE 6. Simulated output of the DAQ

EXPERIMENTAL RESULTS

Fig 7 & 8 shows the hardware experimental set-up of the transmitter section and receiver section.

FIGURE 7. Transmitter Section

FIGURE 8. Receiver Section

The monitoring parameter used in our DAQ system is shown in the following figures 9 and 10.

FIGURE 9. Monitoring Various Parameters

The data acquired from the sensors by the controller is transmitted through the ZigBee transmitter module. In the receiver side, the ZigBee receiver interfaced with the PC receives the transmitted data. The received parameters are then handled in the PC. Here the ZigBee can be transmitting up to 80m at a frequency range of 2GHz.

FIGURE 10. Monitoring Various Parameters

The data acquired by the Cortex processor can also be sent to the receiver section by the wired SPI (RS-232) and then monitored in the PC.

COMPARISON OF PROCESSORS

The following table shows the comparison of various specifications between ARM 7 and ARM Cortex processor.

TABLE 1. Comparison of Processors

Specifications

ARM7

ARM Cortex

Architecture

von Neumann

Harvard

Area (mm2)

0.62

0.37

Operating Frequency

55MHz

50MHz

Maximum Frequency

85MHz

100MHz

Maximum Latency

29 Cycles

12 Cycles

CONCLUSION

This paper proposed the development of data-acquisition system using ARM Cortex processor who includes high performance and accuracy. The main functions of the DAQ part have been designed and tested for a three-channel DAQ namely humidity, air velocity and light intensity. This particular implementation can be utilized in the field of agriculture/related industries for estimation/prediction of weather conditions based on previously acquired data. Better performance can be achieved by using stand-alone DAQ. It includes automatic recognition of protocol enabled during transmission of data. Here only two protocols are considered, If more protocols are used it will automatically detect the recognized protocol and transmits the data. Future work includes the data acquisition system using CAN network in ARM Cortex processor.