4results about How to "Reduce dynamic error" patented technology

The embodiment of the invention provides a high-low humidity step switcher and method for testing the performance of a humidity sensor. The device is applied to the technical field of sensor performance detection and comprises a sealing cylinder, a sealing cover, a sealing plug, a push-out device, a detected humidity sensor and a gas pipeline, the sealing barrel is of a barrel-shaped structure with two through ends, one end of the sealing barrel is buckled with a sealing cover, and the other end is fixedly connected with a sealing plug, so that the sealing barrel forms a closed space; one end of the push-out device is fixedly connected with the sealing cover, and the other end of the push-out device penetrates through the sealing plug and then is connected with a gas pipeline; a detected humidity sensor is mounted on the push-out device; and the gas pipeline is used for pumping out gas in the sealing cylinder or introducing external humidity gas. In this way, the humidity environment can be rapidly switched, the step starting point can be accurately indicated, and therefore the testing efficiency and precision of the tested humidity sensor are effectively improved.

This invention provides a real-time adaptive 3D measurement system and method for objects based on microstructured light. The system includes: multiple optical measurement units arranged in an equidistant circular array along the circumference on a ring mounting frame and moving synchronously with a lifting and adjusting mechanism; multiple measurement posture acquisition units, a reference posture monitoring unit, a posture compensation unit, a control unit, a data fusion module, and a quality analysis module. According to this invention, the multiple optical measurement units arranged in a circular array enable multi-view synchronous measurement of the workpiece, avoiding the time consumption and reference conversion errors of traditional indexing measurement methods. The real-time posture monitoring and dynamic compensation mechanism effectively suppresses measurement errors caused by factors such as mechanical vibration and temperature drift, reducing posture-related measurement errors. The system achieves automation, real-time measurement, and high precision in 3D measurement, improving measurement efficiency and accuracy.

The invention provides a parameter self-adaption device and method, a servo system and a computer readable storage medium. The parameter self-adaption device is used for being connected with the servo system. The servo system comprises a control module, a driving unit and a detection unit, the control module comprises a control unit and a feed-forward unit, the control unit is connected with the driving unit, the feed-forward unit is connected with the control unit, and the detection unit is connected between the driving unit and the control unit. The parameter self-adaption device comprises a parameter self-adaption module, and the parameter self-adaption module is connected with the control unit and the feed-forward unit. And the parameter adaptive module is used for adjusting the feed-forward control parameter of the feed-forward unit when the speed command signal received by the control unit changes suddenly. Thus, the feed-forward signal of the feed-forward unit changes along with the change of the feed-forward control parameter, the control unit is compensated through the change of the feed-forward signal, the error between the output signal of the driving unit and the instruction signal is reduced, and the adjustment time of the servo system is shortened.

The invention discloses a hydraulic machinery stall vortex online identification method based on nonlinear dynamic characteristics, and relates to the field of hydraulic machinery operation monitoring and fault diagnose.The hydraulic machinery stall vortex online identification method can distinguish loading and unloading processes by introducing an empirical formula and a model of a guide vane change rate, accurately identifies a vortex strip state on a hysteresis loop, and improves the accuracy of stall vortex identification. The dynamic error is reduced by more than 80%; secondly, through an empirical formula, the input of the neural network has a clear hydraulics meaning (such as a velocity triangle relation), and the unreliability of a pure black box model is avoided; wherein the complex fluid physical law is concentrated in an empirical formula, the neural network only needs to process residual mapping, the operation speed is extremely high, and the method can be deployed in an in-situ control unit.