Rolling bearing health assessment using only normal samples

To take maintenance measures timely and to prolong the lifetime of a bearing as a whole, bearing users need to know the current health state of the bearing. Those existing methods for health assessment are mostly based on fault samples and/or decline samples of bearings. However, the bearings are always not allowed to fail in the practical engineering application in consideration of the enormous harms and great damages might be caused by the bearing fault. So the fault samples or decline samples of bearing are often lacking. In this point of view, this paper presents a quantificational health assessment method for rolling bearing based solely on normal samples and SOM network. To demonstrate the capability of the proposed method, a series of vibration datasets of the bearings under various health states were employed to conduct case study. And this paper expresses the uncertainty of assessment results after training for many times by the probability density function (PDF)

Curve similarity recognition based rolling bearing degradation state estimation and lifetime prediction

The health state of a rolling bearing keeps changing from a normal state to a slight degradation state followed eventually by a severely degraded state. To make reasonable inspection and maintenance plans, it is necessary to estimate the degradation state and predict the lifetime of a running rolling bearing accurately and in a timely fashion. This paper presents a new method for rolling bearing degradation state estimation and lifetime prediction based on curve similarity recognition. Different from existing methods, this method employs a dynamic time warping algorithm to recognize the curve similarity of those extracted features of rolling bearings in different states of health, which can reflect the intrinsic state of the rolling bearing; it discretizes the bearing degradation state reasonably through curve similarity. Next, the curve similarity is used to train the degradation state estimation model and a support vector machine based lifetime prediction model. Finally, this paper conducts a case study for a rolling bearing with impact degradation and one with wear degradation, respectively. The experimental results indicate that the new proposed method is highly efficient in recognizing the bearing’s degradation state and predicting its lifetime

PENGEMBANGAN APLIKASI ANDROID ‘AYO CUCI TANGAN’ UNTUK MENGAJARKAN KEBERSIHAN ANGGOTA TUBUH PADA MUATAN PELAJARAN IPA DI SEKOLAH DASAR

This study aims to (1) produce an android application 'let's wash your hands' to teach body hygiene in science lesson content in elementary schools (2) determine the value of product feasibility. This type of research is research and development. This study uses a 4d model. This model consists of four steps; (1) define, (2) design, (3) development, and (4) disseminate. Product validation is calculated based on the results of expert assessments. The results of this research and development are (1) an android application with the topic of 'washing hands' (2) the media developed has a good feasibility value. Based on these findings, it shows that the 'let's wash your hands' android application is feasible to use in learning

PENGEMBANGAN INSTRUMEN PENILAIAN KEMAMPUAN KOMUNIKASI SAINS SEBAGAI BAGIAN DARI KETERAMPILAN ABAD 21

Research has been carried out on the development of instruments for science communication skills as part of 21st Century skills at the higher education level. The instrument was developed from indicators of communication skills, namely understanding the key ideas of other people's utterances and presenting or reading data in the form of tables or graphs. The development carried out with the Borg and Gall model produces valid and reliable instruments. The test subjects were 94 students who were selected by cluster sampling. The tests carried out included construct validation tests, empirical validation tests, and testing the use of instruments to measure science communication skills. The results of construct validation show that the instrument is considered very good and suitable for use. The results of empirical validation show that the instrument is valid and reliable so that it can be used. The trial results show that the instrument for the assessment of the results of this development can be used to measure science communication skills

Spatio-Temporal Variation of Some Physico-Chemical Parameters of Water in Lower Seybouse River (Northeastern Algeria)

Oued Seybouse is one of the most important rivers in Algeria. It runs for about 240 km, flows through sevenwilayas (Guelma, Annaba, Souk Ahras, El Tarf, Oum El Bouaghi, Constantine and Skikda) and 68 municipalities, 30 of which are fully included in its basin, and only partially for the others. OuedSeybouse’s water is exposed to multiple sources of pollution, as it directly receives industrial and urban discharges throughout its course. Also agriculture, which is intensively practiced in the lower valley of Seybouse, contributes to the pollution of this watercourse. In this context, we set out to assess the physical-chemical quality of a part of the Lower Seybouse, at three stations on a 28 km stretch; El Hadjar station in the wilaya of Annaba and those of Drean and Chihani in the wilaya of El Tarf. For this purpose, the parameters measured and analyzed are: potential of Hydrogen (pH), Temperature (T), Electrical Conductivity (EC), Suspended Matters (SM), Dissolved Oxygen (DO), Ammonium (NH₄⁺), Nitrates (NO3-), Nitrites (NO2-) and Orthophosphates (PO43-). The processing of analytical results showed that the three stations received urban or agricultural discharges which increased the concentrations of ammonium, nitrite and orthophosphate ions in the already highly mineralized water of OuedSeybouse. High concentrations of these ions can affect animal, plant and human life

Pengaruh Laju Aliran Udara terhadap Karakteristikpembakaran Biobriket dari Limbah Penggilingan Padi (Sekam)

This reseach is aimed to study about the effect of air current velocity to the combustioncharacteristics of biobricket from chaff.This research is an experimental research with air current velocity as a independent variable.Air current velocity includes varies of air current velocity, 0,6 m/s, 0,8 m/s, and 1 m/s. The effect ofthese variables to the combustion characteristics of biobricket from chaff is analyzed from theresult of combustion test.From this research, it can be concluded that air current velocity is in a non‐straightcomparison with combustion temperature, combustion temperature is in a straight comparisonwith mass decreasing, combustion temperature is in a straight comparison with combustionvelocity, and air current velocity is in a non‐straight comparison with the mass decreasing andcombustion velocity

Rolling bearing fault diagnosis based on health baseline method

In order to excavate the relationship between the different features of the vibration signal, and to provide more useful information for the fault diagnosis of rolling bearings, this paper developed a new method of fault diagnosis-health baseline method and introduced the technological process of this method in detail. Through the case study, a health baseline based on two kinds of linear models was constructed. After testing, this method can distinguish the normal state of the rolling bearing, the external ring fault and the rolling element fault, which indicates that the method was feasible and effective for the fault diagnosis of the rolling bearing

Performance assessment of hydraulic servo system based on bi-step neural network and autoregressive model

In recent years, condition monitoring and fault diagnosis of hydraulic servo systems has attracted increasing attention. However, few studies have focused on the performance assessment of these systems. This study proposes a performance assessment method based on a bi-step neural network and an autoregressive model for a hydraulic servo system; the performance is quantized by the performance confidence value (CV). First, a fault observer based on a radial basis function (RBF) neural network is designed to estimate the output of the system and calculate the residual error. Second, the corresponding adaptive threshold is generated by using another RBF neural network during system operation. Third, the difference value between the coefficients of the autoregressive model for the generated residual error and the adaptive threshold is obtained, and the Mahalanobis distance (MD) between the most recent difference (unknown conditions) and the constructed Mahalanobis space by using samples under normal conditions is calculated. Then, the condition of the system can be determined by normalizing the MD into a CV. The proposed method was further validated for three types of faults, and data were obtained using a simulation model. The experimental analysis results show that the performance of hydraulic servo systems can be assessed effectively by the proposed method