Vibration Analysis of Cracked Beam using Intelligent Technique

Structural systems in a wide range of Aeronautical, Mechanical and Civil Engineering fields are prone to damage and deterioration during their service life. So an effective and reliable damage assessment methodology will be a valuable tool in timely determination of damage and deterioration in structural members. Interest in various damage detection methods has considerably increased over the past two decades. During this time many detection methods founded on modal analysis techniques have been developed. Non-destructive inspection techniques are generally used to investigate the critical changes in the structural parameters so that an unexpected failure can be prevented. These methods concentrate on a part of the structure and in order to perform the inspection, the structure needs to be taken out of service. Since these damage identification techniques require a large amount of human intervention, they are passive and costly methods

Inspection and Monitoring of Structural Damage Using Vibration Signatures and Smart Techniques

The structural damage detection plays an important role in the evaluation of structural systems and to ensure their safety. Structures like large bridges should be continuously monitored for detection of damage. The cracks usually change the physical parameters like stiffness and flexibility which in turn changes the dynamic properties such as natural frequencies and mode shapes. Crack detection of a beam element comprises of two aspects: the first one is the forward problem which is achieved from the Eigen parameters and the second one is the process to locate and quantify the effect of damage and is termed as ‘inverse process of damage detection’. In the present investigation the analytical and numerical methods are known as the forward problem includes determination of natural frequencies from the knowledge of beam geometry and crack dimension. The vibration signals are derived from the forward problem is exploited in the inverse problem. The natural frequency changes occur due to the various reasons such as boundary condition changes, temperature variations etc. Among all the changes boundary condition changes are the most important factors in structural elements. Many major structures like bridges are made up of uniform beams of unknown boundary conditions. So in the present investigation two of the boundary conditions i.e. fixed -free and fixed- fixed are considered. Using the forward solution method, the natural frequencies are determined. In the inverse solution method various Artificial Intelligence (AI) techniques with their hybrid methods are proposed and implemented. Damage detection problems using Artificial Intelligence techniques require a number of training data sets that represent the uncracked and cracked scenarios of practical structural elements. In the second part of the work different AI techniques like Fuzzy Logic, Genetic Algorithm, Clonal Selection Algorithm, Differential Evolution Algorithm and their hybrid methods are designed and developed. In summary this investigation is a step towards to forecast the position of the damage using the Artificial Intelligence techniques and compare their results. Finally, the results from the Artificial Intelligence techniques and their hybridized algorithms are validated by doing experimental analysis

A study evaluating third trimester haemoglobin level as a predictor of feto-maternal outcome in pregnancy induced hypertension cases

Background: The aim of this study is to assess whether third trimester haemoglobin level can be used as a predictor of feto-maternal adverse outcomes in pregnancies complicated with PIH.Methods: This is an observational study in the Obstetrics and Gynaecology Department of IMS and SUM hospital, SOA university from July 2015 to December 2017. Institutional ethical committee permission obtained. All singleton pregnancies delivered during this period with PIH were included in the study. PIH and eclampsia was diagnosed as per ISSHP criteria. All chronic hypertension cases excluded. All were evaluated with haemoglobin level. They were divided into 3 groups depending upon haemoglobin level; low ( 13gm%) considering the WHO standard. Maternal complications observed were incidence of eclampsia, abruptio placentae, HELLP syndrome, PPH, neurological complications, ICU admissions and death. Fetal outcomes studied were NICU admission, stillbirth, incidence of prematurity and low birth weight. All these parameters were compared among 3 groups. Statistical analysis was done with SPSS 20 software using Yate’s corrected chi square test.Results: Incidence of eclampsia was significantly greater with both high (p13gm% in third trimester is associated with worst feto-maternal outcome whereas normal haemoglobin level (11-13gm%) is associated with least feto-maternal complications

Alternative approach to costing on Indian Railways: Linking outputs and expenses to activity centres

Costing of railway systems is complicated due to a large proportion of sunk and joint costs. Indian Railways (IR) currently estimates costs at the zonal level by first segregating the direct costs, i.e. costs which can be assigned to a service, and joint costs, i.e. costs which are incurred jointly for more than one service. While the direct costs are assigned to the service, the joint costs are assigned based on ratios worked out for assigning costs between various services. Compared to the method in vogue, the paper proposes and demonstrates a disaggregated approach for developing costs. Unlike the current approach, the proposed approach develops expenses and performance measures at the activity centre level, i.e. at division, shed, and workshop level. The disaggregated data is used to build statistical models relating expenditure to outputs. The paper also shows how the approach can help in i) separating variable and fixed costs ii) developing costs as per sectional characteristics, iii) comparing and benchmarking performance of entities and finally iv) how the process can be automated. The paper also shows how the work could be useful for the accounts reforms project of IR and to the Rail Development Authority in fulfilling some of its objectives

Alternative approach to costing on Indian Railways: Linking outputs and expenses to activity centres

Costing of railway systems is complicated due to a large proportion of sunk and joint costs. Indian Railways (IR) currently estimates costs at the zonal level by first segregating the direct costs, i.e. costs which can be assigned to a service, and joint costs, i.e. costs which are incurred jointly for more than one service. While the direct costs are assigned to the service, the joint costs are assigned based on ratios worked out for assigning costs between various services. Compared to the method in vogue, the paper proposes and demonstrates a disaggregated approach for developing costs. Unlike the current approach, the proposed approach develops expenses and performance measures at the activity centre level, i.e. at division, shed, and workshop level. The disaggregated data is used to build statistical models relating expenditure to outputs. The paper also shows how the approach can help in i) separating variable and fixed costs ii) developing costs as per sectional characteristics, iii) comparing and benchmarking performance of entities and finally iv) how the process can be automated. The paper also shows how the work could be useful for the accounts reforms project of IR and to the Rail Development Authority in fulfilling some of its objectives

Characteristic Study on Sisal Fibre Hybrid Composites Filled With Nano SiO

The synthetic fibres are having high stiffness and strength still high manufacturing cost with environmental issues limited the use of synthetic fibres. This encourages towards thinking of intense research of natural fibres having similar property as synthetic fibres. To obtain the better mechanical and thermal property, hybridization of fibres is mostly preferred and that leads to minimize the use of synthetic fibres. As natural fibres are strong and having more ductile property, though moisture absorption is the primary limitation. So fibres is subjected to various treatments such as physical, thermal, chemical and laser treatments etc., to improve the surface characteristics with better interfacial bonding. Nano particle addition also helps in improving the performance of composites and develops cross linking in bonding of matrix and fibre. This research work mostly focuses on hybridization of short mercerized sisal and glass fibre filled with nano silica and marble dust particles, by injection moulding process with polypropylene matrix. It is noticed that among the addition of different fillers, marble dust added composite gave the better result than SiO2 added composite. Incorporation of SiO2 particles as filler material improves the flexural strength and thermal property of the composite

A hybridised CSAGA method for damage detection in structural elements

In recent years, significant developments have been noticed in nondestructive techniques for damage detection in cracked structures. Some of the proposed methods can be used to find out the existence of the crack; other methods locate and simultaneously find out the damage severity. In the current investigation, a novel hybridised method is proposed for damage detection in structural elements. The proposed method can be used to investigate both location and nature of damage in structures within a reasonable time limit. The problem in the current analysis requires a set of dynamic parameters that depend on the dynamics of the cracked structure due to the presence of the crack. In the present study, the first three natural frequencies of a structure are considered as the inputs to find out the damage location. A finite element method is used to generate the first three natural frequencies of a cracked cantilever beam with multiple cracks. A method hybridizing the nature-inspired artificial intelligence techniques has been implemented for crack detection. Here, clonal selection algorithm and genetic algorithm have been integrated to design the framework of the hybrid technique. The changes in the natural frequencies are given as inputs to the hybrid technique and the output from the technique is the locations of damage

Analysis of hybrid CSA-DEA method for fault detection of cracked structures

Formation of damage in a structural element often causes failures which is not desirable at all by a maintenance team. Identification of location and severity of damage can aid in taking necessary steps to reduce catastrophic failures of structures. As a result, non-destructive methods of damage detection have gained popularity over the last few years. In this paper, a method of damage detection is proposed to identify the location and severity of damage by hybridising a clonal selection algorithm with a differential evolution algorithm. The inputs to the hybrid system are the relative values of the first three natural frequencies of the damaged structure, and the outputs are relative crack locations and relative crack depths. For training the hybrid system, the natural frequencies are found out using finite element analysis and experimental analysis for different crack locations and crack depths. The test results from the proposed hybrid method are compared with finite element analysis and experimental analysis for validation, and satisfactory outcomes have been observed