Real-time monitoring system for hazardous chemicals based on DSP and wireless transmission technology

1 Introduction

With the development of industry, the types and application scope of flammable, explosive and toxic gases and liquids have increased. There are many harmful substances in the chemical, petroleum, dye and other industries, such as liquefied petroleum gas, ammonia, chlorine, hydrogen sulfide, sulfur dioxide and alcohol. If these dangerous substances leak out due to operational errors or other reasons during production or transportation, due to the diffusion of the gas itself, after the leakage, under the action of external wind and internal concentration gradient, the gas will diffuse along the surface, forming a combustion, explosion or poisoning danger zone at the accident site. In order to enhance transportation safety, the transportation vehicles of dangerous chemicals are supervised both inside and outside, mainly for the monitoring of vehicle driving status. There are also GIS platform-based risk assessment studies for the transportation of dangerous chemicals outside the circle, which is used as the basis for the selection of transportation routes. At present, the container monitoring system based on MEMS sensors used by CIMC Group in China can well monitor the gas concentration and temperature and humidity during transportation, the pressure and liquid level of dangerous chemicals in the tank, the spatial posture and acceleration of the tank, and the opening and closing status of the valve cavity. In order to further improve the reliability of gas concentration monitoring, the design uses dual sensors to monitor each other to prevent false alarms caused by single sensor failure, and the design focuses on data processing fusion accuracy to enhance alarm accuracy. Therefore, the design first determines the installation location, and then combines DSP and wireless transmission technology to enhance data processing capabilities and timeliness of transmission, and comprehensively and timely monitor leakage.

2. Distribution of experimental measurement points

According to the investigation of common defects in tanks of normal pressure railway tank cars for hazardous chemicals, the investigation of common leakage accidents, and the analysis of leakage and diffusion during the transportation of harmful gases, it can be learned that the main causes of frequent leakage of hazardous chemicals are tank weld tears, aging of the internal reinforcement ring inside the tank, tank leaks caused by acid and alkali corrosion, etc., and within the leakage monitoring range, the leakage diffusion is mainly heavy gas diffusion with a density greater than the ambient air density. It can be seen that the determination of the location of the installation point should not only achieve the purpose of all-round monitoring, but also focus on monitoring points prone to leakage such as tank welds and valves, and factors such as gas density and wind direction need to be taken into account. During the movement of the train, due to the effect of wind, the leaked gas will diffuse in the direction of the wind. And because the density of most hazardous gases is greater than that of air, that is, the so-called heavy gas, when it diffuses, there will be a direction.

The surface diffusion trend shows that the installation points in Figure 1 are all located downwind of the tank tail and below the leakage points (welds on both sides of the tank body and the safety valve on the tank top). The three installation points can fully monitor the leakage of the entire tank body.

Fig.1 Schematic diagram of experimental measurement point distribution

3. Overall system design

The DSP-based dangerous gas leakage monitoring and alarm system consists of a slave and a host, as shown in Figure 2. The slave uses TI's DSP chip TMS320F2812 as its core, and can complete the two-way gas concentration collection of one monitoring alarm point, one-way ambient temperature data collection, data processing after collection, control execution structure, communication with the host, etc. It constitutes a closed-loop measurement and control system to monitor the area where the installation point is located. The host is implemented by a secondary instrument consisting of a PIC microprocessor chip, liquid crystal display, sound and light alarm, and communication module. It is mainly responsible for data communication with the slave, sound and light alarm, and concentration display functions, so that operators can analyze the site and take effective measures based on the analysis results to prevent the leakage of flammable gas and eliminate potential accidents.

Figure 2 Overall structure diagram of the monitoring system

4 Hardware Block Diagram

In order to quickly and accurately detect the alcohol content in the surrounding gas and send out an audible and visual alarm when the dangerous concentration is reached, the system consists of 6 aspects:

(1) Combustible gas sensor, which can sense the concentration of combustible gas in the surrounding air and convert it into an electrical signal so that the circuit can identify it;

(2) Temperature sensor: The combustible gas sensor is greatly affected by the temperature in its working environment, so it is necessary to measure the temperature of the surrounding environment and then compensate the data measured by the gas sensor;

(3) Power supply guarantee system;

(4) Calculation and display unit;

(5) Sound and light alarm unit;

(6) Friendly human-computer interaction interface and communication interface.

The hardware structure diagram of the leakage monitoring system is shown in Figure 3.

Figure 3 Leakage monitoring system hardware structure diagram

5 System software and data processing methods

To facilitate programming and management, the software is written in C language and adopts modular design. The program works in a cyclic manner to complete initialization and subroutine calls. The software is divided into 3 subsystems:

(1) Data collection and storage of status of hazardous chemicals transportation equipment;

(2) Data processing;

(3) Wireless data transmission communication.

The three subsystems are interrelated and independent of each other, and work together to complete status data processing, status detection, data storage and uploading to the on-board terminal.

5.1 Data Collection

The state data collection and processing of hazardous chemicals transportation equipment is the core part of the system hardware and software design. It mainly completes the state data collection of each sensor, and filters, amplifies, and integrates the collected data as the data source for data fusion. Normal data is uploaded to the vehicle terminal every 10 minutes, and alarm data is uploaded to the vehicle terminal every 3 seconds and the sound and light alarm is activated.

5.2 Data Processing

The design uses two sensors. First, the cross-correlation value is calculated. When the correlation value is greater than 0.7, the two sensor data are considered to be significantly correlated. When it is less than 0.7, the sample is taken 10 times again. If it is continuously less than 0.7, a sensor fault alarm is issued. This can play a role of mutual supervision and prevent system failure due to a sensor failure. According to the calculation in Table 1, the data of the two sensors are in the temperature range of 15℃～19℃ when the alcohol concentration is 1×104g/m3. The data is processed by the sensor signal normalization method, and the measurement range is changed from 0～3.3V to the output between [0, 1]). The cross-correlation value of the data is 0.7058, which has been proved to be significantly correlated and can be used as the next data source.

Table 1 Measurement values ​​of two sensors of the same model under the same conditions

The environmental parameters that need to be monitored in the design are mainly temperature and the content of dangerous gases in the air. Since the gas sensor is significantly affected by temperature changes in the surrounding environment, temperature compensation is required, which is the key point of data processing.

When the mathematical relationship between the interference output and the sensor input is known, the interference can be compensated by digital calculation after measuring the amplitude of the interference variable. This design adopts this compensation method, that is, fitting the curve of the gas sensor and the temperature change, listing the corresponding equations, and calculating the value affected by temperature through equation calculation when the gas sensor and temperature sensor signals are obtained. The advantage of this design is that it has greater flexibility or a wide range of fitting functions. According to the obtained accurate temperature and humidity values, the characteristic curve of the sensor's influence on the ambient temperature is brought in, and the changed sensor data, that is, the voltage value, is obtained, and then the influence caused by the change in ambient temperature is compensated.

In this paper, the least square method is used for curve fitting. The least square method can be used to process a set of data. The dependence relationship between variables can be sought from a set of measured data. This functional relationship is called an empirical formula. In the experiment, n data (x1, y1), (x2, y2), ..., (xn, yn) between variables are measured. On the xoy plane, these data points P (xi, yi) (i = l, 2, ... n) form a "scatter plot". From the figure, it can be roughly seen that these points are roughly scattered near a certain straight line, and it is believed that x and Y are approximately a linear function. The least square method is used to calculate the functional relationship between the temperature and humidity curve and the sensor.

Table 2 Gas sensor voltage values ​​at continuous temperature

The curve obtained by fitting the data in Table 2 in Matlab is shown in FIG4 , and the curve relationship is y=0.020lx+0.2379.

The temperature-compensated data is then fused using the optimal weight allocation principle for multiple sensors in static state, i.e., the weight coefficient allocated to each sensor is:

Where Ri is the square of the accuracy of each sensor. Let Zi(k) represent the result of the kth sampling of the ith sensor, then the fusion value measured by each sensor at the kth sampling is:

The fusion results obtained by this principle are unbiased, effective and consistent.

6 Conclusion

The real-time monitoring system for the status of hazardous chemicals transportation equipment can realize comprehensive detection of hazardous chemicals leakage and detection of ambient temperature, etc., and realize real-time alarm through real-time data processing and transmission. It uses technical means to realize the maintenance of hazardous chemicals transportation umbrella detection, monitoring and tracking, thereby reducing and avoiding accidents, avoiding and reducing accident hazards, and improving the safety and reliability of hazardous chemicals transportation. The system has good applicability for land transportation of hazardous chemicals and provides a safe solution for industrial control modernization and modern logistics.