Trains are an important means of transportation in China. With the popularity and speed increasement of trains, safety issues have received wide attention. The daily safety inspection of high-speed trains becomes crucial, the abnormal target detection for key component that is at the bottom of the train is an important part. Most of alarms which detected by machine vision based on global comparison method are false, thus, it cannot effectively monitor the key component. In this paper, the digital image processing technology is adopted to detect abnormal targets of the three key components, the steeve, the shaft cabinet and the core plate, and an algorithm is presented to detect these components of different types. The key component images are extracted from the train image by template matching. Traditional template matching method is often failed due to the strong reflection happened in the process of train bottom imaging. Therefore, the matching method based on structural similarity is proposed, which greatly improves matching accuracy. Finally, the abnormal target detection of three different key components of locomotive is realized by edge detection, shape detection and contour matching.
In order to achieve the in-service detection to high speed train wheel rims, this article analyzed the effects of the number of array elements to image focusing and image quality using water immersion ultrasonic phased array technology. Also, the effects of the depth of water to detecting technique had been researched. According to the results of the experiments, the number of optimal array elements, the corresponding thickness of immersion layer, and the optimal range of water’s depth had been obtained. Thus, appropriate references had been provided to water immersion ultrasonic phased array testing.
During the long-time working circle, the wheels will be damaged to a certain degree caused by the wearing, the impact, the loads, the climate and so on. In order to evaluate the health of the wheels and reduce the potential losses, many effective methods are used in railway health monitoring, such as laser method or ultrasonic method. But few of them can reach the demand of the real-time online detection, and integrate more comprehensive inspection function at the same time. A composite detection scheme for wheel-tread defects based on FBG sensing technique has been investigated in this paper. By collecting and analyzing the data from the sensors which are distributed on tracks and rails, we can precisely evaluate the Wheel-flats and also measure some other parameters used in rail health monitoring scheme such as speed, loads and axle counting measurement.
This paper describes a multi-FPGA imaging system dedicated for the real-time imaging using the Total Focusing Method (TFM) and Full Matrix Capture (FMC). The system was entirely described using Verilog HDL language and implemented on Altera Stratix IV GX FPGA development board. The whole algorithm process is to: establish a coordinate system of image and divide it into grids; calculate the complete acoustic distance of array element between transmitting array element and receiving array element, and transform it into index value; then index the sound pressure values from ROM and superimpose sound pressure values to get pixel value of one focus point; and calculate the pixel values of all focus points to get the final imaging. The imaging result shows that this algorithm has high SNR of defect imaging. And FPGA with parallel processing capability can provide high speed performance, so this system can provide the imaging interface, with complete function and good performance.
Train wheels should undergo heat treatment, thus producing circumferential compressive force on the tread to void crack propagation, and this way eventually increases the train wheel service life, excluding situations like wheel burst due to crack. Hem shoes braking will lead to calorification and cooling of wheel rim,in this case stress state of wheel rim will would change under the influence of caloric and mechanical load, and compressive stress will turn to circumferential tensile force. For wheels in service, small flaws appear in the shallow layer of wheel tread, and will expand into depth. Consequently, detecting of wheel rim stress state should be attached more importance. Ultrasonic testing technology is an extremely important method for convenient, fast and non-destructive detecting in routine application of wheel sets. Verification of ultrasonic detecting method in detecting stress of wheel rim is given in this paper. On experimentation platform established with wheel rim stress detecting equipment and tensile stress mechanism, ultrasonic wheel rim stress detecting method is verified to be reliable and stable in the light of contrast between theoretical and experimental results. Basing on wheel rim stress measurement method using transverse straight probe, results are obtained by measuring test block and wheel rim stress, and ultrasonic wheel rim stress detecting method is approved to be feasible in application.
In order to figure out the concentration of carbon monoxide, by measuring the second and third harmonics of the
absorption spectrum line, this paper obtained results which indicate that this method can be applied to industry field.
Tunable semiconductor laser of 1.58um can be used, and its wavelength is a nice window of communication in long
wavelength band of fiber. The measurement optical paths can well be integrated with fiber and passive component in
fiber system and it is already applied to industry field. Moreover, the 1.58um spectrum line is an absorption peak of
carbon monoxide and around the spectrum line, there is a good transmission window in the background gas of
atmosphere. It is very well to measure carbon monoxide concentration. Through measuring peaks of the first and second
harmonic or the second and fourth harmonic of absorption spectrum lines of carbon monoxide with tunable diode laser
absorption spectroscopy (TDLAS) technique, the carbon monoxide concentration can accurately be calculated by
composition algebra. This paper focuses on the study that the absorption coefficient changes with temperature. As the
absorption coefficient of different temperature changes, the parameters of concentration measurement will change. This
is a very complicated process.
KEYWORDS: Absorption, Carbon monoxide, Semiconductor lasers, Modulation, Gas lasers, Signal processing, Signal detection, Temperature metrology, Tunable lasers, Combustion
This paper presents the measurement of the carbon monoxide concentration in industry field by scanning absorption
spectrum. In the measurement, the frequency of DFB laser is stabilized in the central frequency point of absorption peak
in 1.57μm absorption band of carbon monoxide by a control system with a standard CO gas chamber, fiber loop, TEC
controlled by MCU and its temperature stability is 0.01°C at long time to stabilize the central frequency. In the process of
measurement, at first, the CO absorption spectrum will be determined by a standard gas camber to choose a maximum
CO absorption peak in its frequency band and its frequency point will be stabilized. The parameters of the operation
frequency and environment will be stored in the NV memory in MCU as next operation condition. The concentration can
be calculated in a composite algebra operation by first and second harmonic intensity passed through test gas chamber. It
has very high measurement precision and real time. The experiment result is consistent with actual gas concentration. It
shows that the measurement scheme is valuable for fast, real-time and efficiency measurement.
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