Fault detection and analysis is a major aspect of several OMA (operations management automation systems). A fault is a problem that can result in other issues and observable symptoms. A root cause is linked with methods for its repair. It can either be the outcome of a complete equipment failure or involve specific hardware.
Let us discuss more on the diagnosis and detection of a fault.
Reasons for the occurrence of a fault
Fault in hardware equipment can be due to the following reasons such as poor selection of operating targets, inferior quality of feedstock, low-quality controller tuning, and partial reduction in catalyst activity, formation of coke, low steam system pressure, human mistake, and sensor calibration errors.
A fault is generally considered to be a binary variable or can be a number such as a leakage amount or as a degree of inefficiency. Visirule is a leading UK based company that provides fault diagnosis flow chart to capture and convey the steps needed to recognize, and repair faults.
What is Fault detection?
Fault identification is the way of recognizing the occurrence of a program whether you are aware or not aware of the root cause. Faults can be noticed by a series of qualitative and quantitative methods.
This includes multivariable approaches, model-based approaches, simple, and traditional methods for single variables that include alarms based on low, high, or deviation limits for the processing of variables.
What is Fault Diagnosis?
Fault diagnosis refers to an activity wherein you need to figure out one or multiple root causes behind any issue. Based on the findings, corrective measures are taken. Fault diagnosis is also called as “fault isolation”. In common terms, fault diagnosis includes fault detection, and due to which “fault isolation” stresses on the distinction.
There are a few more elements of OMA (Operations Management Automation) that are linked to fault diagnoses such as the associated user, and system interfaces, and procedural support for the entire process.
Workflow steps can either be automated or manual or include notifications, escalation processes, and online instructions if issues are ignored. Fault mitigation actions and direct corrective actions are needed to return to normal state after repairs are executed.
On what factors does fault diagnosis, and detection depends?
Automated recognition and diagnosis of fault are heavily dependent on input obtained from radars and derived measures of performance. In several applications, like the process industries, failures in radars are seen to be the commonest form of equipment failures.
The prime focus in such industries is to recognize sensor issues, and process troubles. Differentiating between sensor and process problems is seen to be a key issue in such applications.
The term “sensors” implies process supervising instrumentation for level, flow, temperature, pressure, and power. In fields like systems and network management, it can comprise of other measures that include the probability of error, length of the queue, processor usage, and dropped calls.
Fault detection and diagnose are performed using a wide range of methods in an organization. A better understanding of these methods is needed to perform the process in an efficient and precise manner.