A data mining approach for fault diagnosis: An application of anomaly detection algorithm

Purarjomandlangrudi, Afrooz; Ghapanchi, Amir Hossein; Esmalifalak, Mohammad

doi:10.1016/j.measurement.2014.05.029

Cited by 100 publications

(45 citation statements)

References 19 publications

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“…Due to this fact, the knowledgebased method is commonly referred to as data-driven method [10,13]. The empirical data, which records outside environmental factors, internal loads, and 30 mechanical system working conditions, is collected through sensor network and stored in the BMS [14,15]. Experts and researchers analyze the empirical data and feedback to building operators if any fault is found.…”

Section: Introductionmentioning

confidence: 99%

Fault detection and diagnosis for building cooling system with a tree-structured learning method

Zhou

et al. 2016

Energy and Buildings

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Section: Introductionmentioning

confidence: 99%

Fault detection and diagnosis for building cooling system with a tree-structured learning method

Zhou

et al. 2016

Energy and Buildings

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“…The commonly used data mining algorithm includes decision tree algorithm, Clustering algorithm, classification algorithm and neural network algorithm, and connection rule algorithm. In addition, for this condition, the commonly used algorithms can be generally summarized as follows Apriori algorithm.…”

Section: Association Data Mining Priormentioning

confidence: 99%

A novel systematic algorithm paradigm for the electric vehicle data anomaly detection based on association data mining

Wang

2018

Concurrency and Computation

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Summary The electric automobile electric regenerative braking control strategy request achieves two goals, namely, enhances the entire vehicle the energy returns‐ratio as well as optimizes the pilot to the feel. When the former request brake the electric regenerative braking first, it can satisfy the brake request under the premise first to then use the electric regenerative braking recycling brake energy, and before, the latter request rational distribution the trailing wheel braking force uses in tracking pilot's deceleration intention. Under this basis, this paper proposes the novel systematic algorithm paradigm for the electric car data anomaly detection based on association data mining. With the continuous improvement of the intelligent vehicle and the continuous improvement of the function of the system, the system can be used as a hybrid vehicle detection and vehicle maintenance standard equipment and has broad application prospects. The effectiveness of the proposed system is verified through the experiment.

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“…Unusual patterns in such data typically reflect disease conditions (Purarjomandlangrudi et al, 2014).…”

Section: Medical Diagnosismentioning

confidence: 99%

Detection of API(Anomaly Process Instance) Based on Distance for Process Mining

Jeon¹,

Bae²

2015

Journal of Korean Institute of Industrial Engineers

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There have been many attempts to find knowledge from data using conventional statistics, data mining, artificial intelligence, machine learning and pattern recognition. In those research areas, knowledge is approached in two ways. Firstly, researchers discover knowledge represented in general features for universal recognition, and secondly, they discover exceptional and distinctive features. In process mining, an instance is sequential information bounded by case ID, known as process instance. Here, an exceptional process instance can cause a problem in the analysis and discovery algorithm. Hence, in this paper we develop a method to detect the knowledge of exceptional and distinctive features when performing process mining. We propose a method for anomaly detection named Distance-based Anomaly Process Instance Detection (DAPID) which utilizes distance between process instances. DAPID contributes to a discovery of distinctive characteristic of process instance. For verifying the suggested methodology, we discovered characteristics of exceptional situations from log data. Additionally, we experiment on real data from a domestic port terminal to demonstrate our proposed methodology. †

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A data mining approach for fault diagnosis: An application of anomaly detection algorithm

Cited by 100 publications

References 19 publications

Fault detection and diagnosis for building cooling system with a tree-structured learning method

Fault detection and diagnosis for building cooling system with a tree-structured learning method

A novel systematic algorithm paradigm for the electric vehicle data anomaly detection based on association data mining

Detection of API(Anomaly Process Instance) Based on Distance for Process Mining

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