How to realize the fault diagnosis of regulating valves

As a key executive component in industrial automation control systems, regulating valves are widely used in the oil, chemical, power, metallurgy, and other industries. Their operating status directly affects the safety, stability, and efficiency of the entire production process. Therefore, timely and accurate diagnosis of regulating valve faults is of great significance for ensuring system normal operation, reducing maintenance costs, and improving production efficiency.

One, Common Fault Types of Regulating Valves

The possible faults that regulating valves may occur during long-term operation mainly include the following categories:

1. Leakage failure: Including internal leakage (poor sealing between the valve core and the valve seat) and external leakage (failure of packing sealing).
2. Delayed action or sticking: Caused by impurities blocking, deformation of the valve rod, or actuator failure.
3. Inadequate response: Abnormal signal transmission or insufficient output force of the actuator.
4. Oscillation or fluctuation: Unstable control signal or valve core wear causing flow fluctuation.

Two, Diagnostic Methods for Regulating Valve Faults

The realization of fault diagnosis for regulating valves mainly depends on the collection, analysis, and judgment of operating data. Currently common diagnostic methods mainly include:

# 1. Methods Based on Signal Analysis

By real-time monitoring of control signals, valve position feedback signals, and actuator pressure, etc., the trend of their changes is analyzed. For example, when the control signal changes but the valve position has no response or a significant lag, it can be judged that there is a fault in the actuator or valve core.

# 2. Methods Based on Model Identification

Establish a mathematical model of the regulating valve and identify abnormal conditions by comparing the deviation between the actual input and output and the model prediction. This method is suitable for situations where the system modeling is relatively accurate.

# 3. Methods Based on Data-Driven

Using machine learning, neural networks, and other technologies, a large amount of historical operating data is trained and learned to build a fault identification model. For example, support vector machines (SVM) and convolutional neural networks (CNN) are used to classify and predict the operating status under different working conditions.

# 4. Methods Based on Physical Parameter Detection

For example, by measuring the stroke of the valve rod, the pressure of the actuator, and the change of temperature, etc., the existence of problems such as sticking and leakage can be judged in combination with empirical formulas.

Three, Development of Intelligent Diagnostic Systems

With the development of Industry 4.0, the fault diagnosis of regulating valves is gradually developing towards intelligence. Intelligent valve positioners integrating sensors, edge computing, and the Internet of Things have become a trend. These systems not only can monitor the operating status of regulating valves in real-time but also can provide fault warnings, diagnoses, and maintenance suggestions through remote platforms, greatly improving the efficiency and accuracy of equipment management.

Four, Conclusion

The fault diagnosis of regulating valves is a systematic project, which requires the integration of signal collection, data analysis, model algorithms, and practical operating experience. With the continuous advancement of intelligent sensors and artificial intelligence technology, the intelligent diagnostic system for regulating valves will become more efficient and accurate. In the future, the realization of 'predictive maintenance' for regulating valves will become a new direction for industrial development, providing a solid guarantee for the safe and stable operation of industrial automation systems.