A high efficiency and high precision testing method for tightness detection method of aluminum foil seal is proposed.First of all, the thermal images of aluminum foil seal are obtained by a thermal imager.Then we use MATLAB software for getting the information of thermal image in batches,and then the image preprocessing. Then BP neural network was optimized by genetic algorithm to extract and classify image features.The experimental results show that this sealing test method has high recognition rate and short training time, which provides a guarantee for automatic screening and elimination of bad sealing products in the subsequent aluminum foil sealing production line.

A method for detecting the integrity of aluminum foil seals with high detection accuracy and high detection efficiency is proposed.First of all,in order to obtain the infrared image of the sealing part aluminum foil,the method has adopted the infrared imaging technology.Then，the infrared image is preprocessed and the feature is extracted by circular symmetric Gabor wavelet.Lastly,KNN is used to identify and classify the acquired imaging.Experiments show that the circular symmetric Gabor wavelet used by this sealing detection method has higher recognition rate and faster algorithm than the traditional Gabor transform algorithm, and provides technical assurance for the automatic screening and rejection of defective sealing products in the subsequent aluminum foil sealing production line.

        After the research on the distribution characteristic of temperature field for aluminum seal , a kind of inspection method for the sealing based on Gabor transformation and extreme learning machine (ELM) was proposed. The Gabor transformation was conducted on various thermal images ，and the textural features are extracted to train the ELM neural network. Then the training results are used to classify and identify the thermal images， and the sealing of aluminum seal could be judged through the classification features of the thermal images. Compared and analysed with BP neural network which extracts color features，it is found that the algorithm based on Gabor transformation and ELM has the advantages of strong generalization，fast response speed，high precision，etc.

The space more freedom position control system is studied for the simulation experiments which provide experimental device space more freedom need space of X、Y axis roll and pitch motion. The system selects the siemens S7300 PLC as lower computer, the WinCC as upper computer. The control system used the modular programming design thought, timer interrupt for a long timing, PID control of electrohydraulic proportional valve opening to make the simulating platform pitch and roll motion of the fast track come true, and the failure to make the solution in the process of debugging.