Abstract: A method for processing accelerated degradation test data based on Wiener process includes obtaining accelerated degradation test data of a to-be-tested product, selecting a target time conversion model from a predefined set of time conversion models based on the accelerated degradation test data, constructing a nonlinear Wiener degradation process based on the target time conversion model, determining a product reliability function of the to-be-tested product, and testing the reliabilities of the to-be-tested product based on the product reliability function to obtain product reliability test results of the to-be-tested products.

Abstract: An industrial robot motion accuracy compensation method includes: establishing a motion parameter database, wherein the motion parameter database includes a plurality of different reference operating conditions and a motion parameter of the industrial robot corresponding to each reference operating condition, and each reference operating condition is formed by combining each element in each set in a total set of operation conditions; acquiring a current operating condition of the industrial robot; determining whether there is a reference operating condition matched with the current operating condition in the motion parameter database; if yes, taking a motion parameter corresponding to the matched reference operating condition as a motion parameter corresponding to the current operating condition; if no, performing an interpolation on a motion parameter corresponding to the current operating condition, and taking an interpolation result as the motion parameter corresponding to the current operating condition.

Abstract: An industrial robot motion accuracy compensation method includes: establishing a motion parameter database, wherein the motion parameter database includes a plurality of different reference operating conditions and a motion parameter of the industrial robot corresponding to each reference operating condition, and each reference operating condition is formed by combining each element in each set in a total set of operation conditions; acquiring a current operating condition of the industrial robot; determining whether there is a reference operating condition matched with the current operating condition in the motion parameter database; if yes, taking a motion parameter corresponding to the matched reference operating condition as a motion parameter corresponding to the current operating condition; if no, performing an interpolation on a motion parameter corresponding to the current operating condition, and taking an interpolation result as the motion parameter corresponding to the current operating condition.

Abstract: A predictive maintenance system and method for intelligent manufacturing equipment is provided. The predictive maintenance system includes a first-stage predictive maintenance module, a second-stage predictive maintenance module, and a maintenance decision module. The first-stage predictive maintenance module includes an acquisition module, a human-computer interaction module, a calculation module, and a storage module. The second-stage predictive maintenance module includes a communication module, a setting module, and a prediction module. The maintenance decision module is configured to receive a first-stage remaining service life calculated by the first-stage predictive maintenance module and a second-stage remaining service life predicted by the second-stage predictive maintenance module, and determine a predictive maintenance strategy of the intelligent manufacturing equipment according to the first-stage remaining service life and the second-stage remaining service life.