Statistical evidence of central moment as fault indicators in ball bearing diagnostics

This paper deals with post processing of vibration data coming from a experimental tests. An AC motor running at constant speed is provided with a faulted ball bearing, tests are done changing the type of fault (outer race, inner race and balls) and the stage of the fault (three levels of severity: from early to late stage). A healthy bearing is also measured for the aim of comparison. The post processing simply consists in the computation of scalar quantities that are used in condition monitoring of mechanical systems: variance, skewness and kurtosis. These are the second, the third and the fourth central moment of a real-valued function respectively. The variance is the expectation of the squared deviation of a random variable from its mean, the skewness is the measure of the lopsidedness of the distribution, while the kurtosis is a measure of the heaviness of the tail of the distribution, compared to the normal distribution of the same variance. Most of the papers in the last decades use them with excellent results. This paper does not propose a new fault detection technique, but it focuses on the informative content of those three quantities in ball bearing diagnostics from a statistical point of view. In this paper, a discriminant function analysis is used, to determine which central moment has a high discrimination power in the diagnostics of ball bearing in stationary conditions

Extension of the predictive policy to a series of mechanical systems

In the literature, a great interest is reserved to complex systems (i.e. serial or parallel or mixed systems), constituted by the interconnection of single elements. The evolution of system reliability depends on its structure as well as on the evolution of the reliability of its individual elements. Maintenance activities on systems strongly affect element aging and system\u2019s operating life. Preventive maintenance, for example, is used to increase system availability reducing, as a consequence, the probability of failure. Generally, maintenance plans are performed with respect to some criteria depending on cost or on reliability/availability requirements. Therefore, the optimum maintenance scheduling of a system can be based on the minimization of the total cost or on the maximization of its availability. Many Authors emphasize the requirement on system reliability. In [1], for example, the concept of reliability equivalence from simple series and parallel systems to some complex systems is presented and reliability equivalence factors of complex systems are obtained. One of the most critical problems in preventive maintenance is the determination of the optimum frequency to perform maintenance actions on systems, in order to ensure a pre-defined level of availability. In this paper the predictive maintenance policy, for a single element, is extended to a system constituted by two series elements, named A and B. The transition from a single unit to a series system is not immediate and presents a great number of problems. Actually, when a maintenance action is scheduled for a system of this kind, the decision maker must decide if it is more convenient (with respect to some chosen criterion) to intervene on element A or B or on both. The proposed methodology deals with this practical problem in the context of the predictive maintenance policy. Research on this topic is in a running state and the methodology is only theoretically presented

System monitoring and maintenance policies: a review

In the industrial context, the main goal of the maintenance team is to avoid sudden failures that can cause the stoppage of the system with a consequent loss of production. This means that each maintenance action must be performed before the degradation level of a system exceeds a critical threshold beyond which the failure probability becomes high. The increasing importance given to maintenance is shown not only by the great deal of literature on the topic, but also by the interest in transforming this area from a managerial area to a branch of applied mathematics (Operational Research or Statistics). Maintenance is now considered as a subject and much research activity is concerned with its mathematical modeling rather than with the management processes relating to maintenance itself. In [1], Scarf evidences the great importance of the mathematical modeling of maintenance and the correlated strategic support given by the maintenance management information systems. Nevertheless, no model can be built without an exhaustive collection of data. By data, Author means not only specific figures regarding, for example, failure times, but all information related to the process under study. With the recent advent of condition monitoring and the development of appropriate decision models, critical components of a system can be tracked through appropriate variable(s) correlated to their degradation process, logistic support (for example, spares inventory) can be provided, maintenance history can be stored, predetermined maintenance activity can be alarmed and management reports can be produced. The use of condition monitoring techniques reduces the uncertainty operators feel about the current state of the plant. For example, knowledge about the vibration levels of a rotating bearing gives engineers confidence about its operation in the short term. Data acquired by monitoring systems, maintenance histories collected for specific components can be considered fundamental resources for the mathematical modeling of the maintenance activities. This paper is the first part of two [2], presenting the transition from preventive maintenance policy to the predictive one. In particular, the paper presents a brief review of the subject and some critical considerations about the two maintenance policies

Current Practices in the Management of Pulmonary Ground-Glass Opacities: A Survey of SICT Members

Several gray areas and controversies exist concerning the management of pulmonary ground-glass opacities (GGOs) and there is a lack of consensus among clinicians on this topic. One of the main aims of the Italian Society of Thoracic Surgery (SICT) is to promote education and research, so we decided to perform a survey on this topic to estimate current trends in practice in a large sample of thoracic surgeons

Current practices in the management of pulmonary Groun-Glass Opacities: a survey of SICT members

Background: Several gray areas and controversies exist concerning the management of pulmonary ground-glass opacities (GGOs), and there is a lack of consensus among clinicians on this topic. One of the main aims of the Italian Society of Thoracic Surgery is to promote education and research, so we decided to perform a survey on this topic to estimate current trends in practice in a large sample of thoracic surgeons. Methods: A total of 160 thoracic surgeons responded, namely, completed our questionnaire (response rate, 53%; 160 of 302). The survey was composed of 36 questions divided into six subsections: (1) demographic characteristics of the respondents; (2) terminology and taxonomy; (3) radiologic and radiometabolic evaluation; (4) diagnostic approach and indications for surgery; (5) surgical management; and (6) radiologic surveillance. Results: We observed some divergence of opinion regarding the definition of mixed GGOs, the role of 18F fluorodeoxyglucose positron emission tomography and computed tomography scans, indications for nonsurgical biopsy, intraoperative techniques for localizing GGOs, indications for surgery, extension of lung resection and lymph node dissection according to the radiologic scenario, use of intraoperative frozen section analysis, and radiologic surveillance of pure GGOs. Conclusions: This topic warrants more investigation in the future. An upcoming consensus conference of Italian Society of Thoracic Surgery experts (also open to experts in other specialties) could provide updated indications for GGO management based on the literature, expert opinions, and the results of the present survey