The humidity sensor and control algorithm of the nylon constant temperature and humidity machine are the core of achieving precise environmental control. The two work together to ensure that the humidity is stable within the set range, meeting the strict environmental requirements of nylon production, storage, and other scenarios.

Humidity Sensor: Accurately Sensing Environmental Humidity

Humidity sensors typically use capacitive or resistive principles. Capacitive sensors use polymer thin films as the dielectric layer, and water molecules enter to change the dielectric constant, thereby increasing the capacitance value with increasing humidity. They have the advantages of fast response, good linearity, and strong anti condensation ability, and are widely used in industrial environments. Resistance sensors measure humidity through the characteristic of the change in resistance value after the adsorption of water molecules by moisture sensitive materials. They have a simple structure and low cost, but require regular calibration to maintain long-term stability. The analog signals output by sensors (such as resistors and capacitors) are processed by circuits such as voltage regulation filtering, operational amplification, and nonlinear correction, and converted into current or voltage signals that are linearly related to humidity. Alternatively, they can be directly output through the main control chip via interfaces such as 485 and 232, providing a data foundation for control algorithms.

Control algorithm: dynamically adjust to achieve constant humidity

The control algorithm is based on PID (Proportional Integral Derivative), which calculates the error between the set humidity and the actual humidity, and adjusts the output by integrating the proportional, integral, and derivative variables. The proportional term responds quickly based on the magnitude of the error, the integral term eliminates persistent errors, and the differential term predicts the trend of error changes. The three work together to stabilize the humidity near the set value. For example, when the humidity deviates from the set value, the algorithm dynamically adjusts the operating status of the humidifier or dehumidifier to quickly reduce the error; If the humidity fluctuates frequently, the integral term can accumulate errors and gradually correct them to avoid excessive adjustment. Some models also introduce fuzzy logic control algorithms, which use fuzzy sets and rules to handle nonlinear and fuzzy environments, further improving control accuracy and adaptability.