KR-20260064802-A - DIAGNOSIS SYSTEM OF ABNORMALITY OF AIR COMPRESSOR

Abstract

The present invention relates to an air compressor fault diagnosis system, and provides an air compressor fault diagnosis system comprising an air compressor that produces compressed air, a measurement sensor unit that measures vibration of the air compressor, and a management server that performs a predictive diagnosis of the air compressor using the measurement value of the measurement sensor unit.

Inventors

• 김용호
• 이성훈

Assignees

• 경일대학교산학협력단
• 이성훈

Dates

Publication Date

20260508

Application Date

20241029

Claims (6)

1. An air compressor that produces compressed air; A measurement sensor unit for measuring the vibration of the above air compressor; and An air compressor fault diagnosis system including a management server that performs predictive diagnosis of an air compressor using the measurement values of a measurement sensor unit.
2. In paragraph 1, An air compressor fault diagnosis system characterized by the above air compressor comprising an air end section for compressing air, a suction section for transmitting external air to the air end section, a receiver tank section for storing compressed air, a pressure regulating section for regulating pressure within the tank section, and a driving section for operating each section including the air end section.
3. In paragraph 1, An air compressor fault diagnosis system characterized by the above-mentioned measurement sensor unit including a vibration measurement sensor unit installed in an air compressor to measure vibration, a sensor communication unit that transmits sensor measurement values, a control unit that controls the operation of each element, and a power supply unit that provides power to each element.
4. In paragraph 3, An air compressor fault diagnosis system characterized by the above-mentioned vibration measurement sensor unit measuring vibration based on an ADC (Analog-to-Digital Converter).
5. In paragraph 1, An air compressor fault diagnosis system characterized by the above-mentioned management server comprising: a sensing input unit that receives the sensing results of a measurement sensor unit; a vibration analysis unit that analyzes the frequency based on the input sensing results; a predictive diagnosis unit that stores the results of the vibration analysis unit in a database and performs predictive diagnosis based thereon; a control unit that controls the operation of each unit and provides the results to a manager; and a server communication unit that communicates with the measurement sensor unit.
6. In paragraph 5, The above vibration analysis unit performs analysis through FFT (Fast Fourier Transform), and An air compressor fault diagnosis system characterized by the above-mentioned predictive diagnosis unit storing the results of the vibration analysis unit in a database, analyzing patterns of the databased data, analyzing the normal operating state of the equipment and abnormal patterns at the time of failure precursor based on past data, and predicting the probability of failure occurrence by analyzing this through AI or machine learning algorithms.

Description

Air Compressor Abnormality Diagnosis System The present invention relates to an air compressor fault diagnosis system and provides an air compressor fault diagnosis system capable of predictive diagnosis to prevent failure by measuring real-time vibration data of the air compressor and analyzing signs of abnormality in real time. Compressed air is an essential power source used across various industries, including machinery, automobiles, electronics, construction, petrochemicals, and paper and pulp. If operation ceases due to mechanical failure of the air end of an air compressor, it can result in massive losses for the entire workplace, including the products manufactured using compressed air. Therefore, there is a growing need for a mechanical failure prediction and diagnosis (Progonstics and Health Management) function for screw-type air ends, which are critical mechanical elements for compressed air production in air compressors, and active research is being conducted on this matter. By avoiding sudden failures of air compressors through this failure prediction and diagnosis function, it will be possible to reduce massive maintenance costs, improve operational efficiency, and enhance the safety of the entire system. FIG. 1 is a drawing for explaining an air compressor fault diagnosis system according to one embodiment of the present invention. FIG. 2 is a drawing for explaining an air compressor according to one embodiment. FIG. 3 is a drawing for explaining a measurement sensor unit according to one embodiment. FIG. 4 is a diagram illustrating a management server according to one embodiment. Hereinafter, embodiments of the present invention will be described in more detail with reference to the attached drawings. However, the present invention is not limited to the embodiments disclosed below but may be implemented in various different forms; these embodiments are provided merely to ensure that the disclosure of the present invention is complete and to fully inform those skilled in the art of the scope of the invention. Identical reference numerals in the drawings refer to identical elements. It is intended to clarify that the classification of components in this specification is merely based on the primary function each component is responsible for. That is, two or more components described below may be combined into a single component, or a single component may be divided into two or more components based on more subdivided functions. Furthermore, each component described below may additionally perform some or all of the functions performed by other components in addition to its own primary function, and it is obvious that some of the primary functions performed by each component may be exclusively handled by other components. Therefore, the existence of each component described in this specification should be interpreted functionally. For this reason, it is clearly stated that the configuration of the components of the air compressor fault diagnosis system of the present invention may vary to the extent that the objectives of the present invention can be achieved. In this specification, relational terms such as first and second, upper and lower, etc., may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying an actual relationship or order between such entities or actions. The terms “comprises,” “comprising,” or other variations thereof are intended to cover non-exclusive inclusions so that a process, method, product, or device comprising a list of components may not include only the component but may include other components not explicitly enumerated or inherent in such process, method, product, or device. A component proceeding to “comprising” excludes, without further limitation, the presence of additional identical components within the process, method, product, or device comprising the component. FIG. 1 is a drawing for explaining an air compressor fault diagnosis system according to one embodiment of the present invention. FIG. 2 is a drawing for explaining an air compressor according to one embodiment. FIG. 3 is a drawing for explaining a measurement sensor unit according to one embodiment. FIG. 4 is a diagram illustrating a management server according to one embodiment. As illustrated in FIGS. 1 to 4, the air compressor fault diagnosis system according to the present embodiment includes an air compressor (100) that produces compressed air, a measurement sensor unit (200) that measures vibrations of the air compressor (100), and a management server (300) that performs a predictive diagnosis of the air compressor (100) using the measurement value of the measurement sensor unit (200). The air compressor (100) includes an air end section (110) for compressing air, an intake section (120) for transmitting external air to the air end section, a receiver tank section (130) for storing compressed air, a pressure control section (14