Interactive Laboratory Experiment Data Preprocessing Pipeline

Create a comprehensive Python class using pandas and numpy that can automatically clean, normalize, and validate scientific experimental datasets. The class should include methods for handling missing data, detecting statistical outliers, performing automatic unit conversions, and generating detailed preprocessing reports. Implement robust error handling for various scientific measurement formats and include type checking for different experimental data types.