This paper presents an improved monitoring system for the failure detection of engraving tool steel inserts during the injection molding cycle. This system uses acoustic emission PZT sensors mounted through acoustic waveguides on the engraving insert. We were thus able to clearly distinguish the defect through measured AE signals. Two engraving tool steel inserts were tested during the production of standard test specimens, each under the same processing conditions. By closely comparing the captured AE signals on both engraving inserts during the filling and packing stages, we were able to detect the presence of macro-cracks on one engraving insert. Gabor wavelet analysis was used for closer examination of the captured AE signals’ peak amplitudes during the filling and packing stages. The obtained results revealed that such a system could be used successfully as an improved tool for monitoring the integrity of an injection molding process.

The paper presents a modified adaptation algorithm for the super-twisted sliding mode controller structure, based on the barrier function method. The aim of the paper is to reduce the chattering phenomena of the controller, which limited the use of the controller in different applications. The chattering phenomena are mostly caused by the overestimated controller gain due to the assumed disturbance bound, which is mostly inaccurate. The chattering origins are also the unknown parasitic dynamic of the system and discrete implementation of the controller. The proposed method with the Barrier function is used to alleviate the chattering phenomena with the adaptation of the controller parameters. The novelty of the method is using an adaptation procedure only in prescribed regions of the sliding variable, otherwise, the adaptation is not used. The advantage of the method is the proper rejection of the chattering phenomena in the vicinity of the manifold of the sliding variable, regardless of the order of the system. With proper selection of the adaptation boundary, the effect of discrete implementation, especially for a longer sampling time of the algorithm, can be suppressed efficiently, as well as the effect of the overestimated controller parameters. The proposed method is verified and compared with a standard version of the algorithm in simulation and real-time environments.

Publisher: Vilnius University Institute of Data Science and Digital Technologies, Journal: Informatica, Title: GSM Speech Coder Indirect Identification Algorithm, Authors: Rajko Svečko, Bojan Kotnik, Amor Chowdhury, Zdenko Mezgec , This paper presents GSM speech coder indirect identification algorithm based on sending novel identification pilot signals through the GSM speech channel. Each GSM subsystem disturbs identification pilot, while speech coder uniquely changes the tempo-spectral characteristics of the proposed pilot signal. Speech coder identification algorithm identifies speech coder with the usage of robust linear frequency cepstral coefficient (LFCC) feature extraction procedure and fast artificial neural networks. First step of speech coder identification algorithm is the exact position detection of the identification pilot signal using normalized cross correlation approach. Next stage is time-domain windowing of the input signal to convolve each frame of the input speech signal and window spectrum. Consecutive step is a short-time Fast Fourier Transformation to produce the magnitude spectrum of each windowed frame. Further, a noise reduction with spectral subtraction based on spectral smoothing is carried out. In last steps we perform the frequency filtering and Discrete Cosine Transformation to receive 24 uncorrelated cepstral coefficients per frame as a result. Speech coder identification is completed with fast artificial neural network classification using the input feature vector of 24 LFCC coefficients, giving a result of identified speech coder. For GSM speech coder indirect identification evaluation, the standardized GSM ETSI bit-exact implementations were used. Furthermore, a set of custom tools was build. These tools were used to simulate and control various conditions in the GSM system. Final results show that proposed algorithm identifies the GSM-EFR speech coder with the accuracy of 98.85%, the GSM-FR speech coder with 98.71%, and the GSM-HR coder with 98.61%. These scores were achieved at various types of surrounding noises and even at very low SNR conditions.