8results about How to "Fully verified" patented technology

The invention discloses an MICP intensity prediction method and system based on machine learning and multi-feature fusion, and relates to the field of solidified data analysis. An accurate quality prediction mapping model and an abnormal compensation parameter mapping model are constructed based on historical data; the system has the capabilities of predicting curing quality from process parameters and intelligently recommending an optimal disposal scheme from an abnormal state; by setting a dual-threshold quality control mechanism and a real-time abnormity monitoring and early warning system, various abnormal conditions in the curing process can be actively identified and timely responded, and complete closed-loop processing from parameter deviation detection to automatic compensation measure execution to hardware standby switching can be realized. The stability of the solidification process and the consistency of the engineering quality are effectively guaranteed, the requirement for manual intervention and the misjudgment risk are greatly reduced, powerful technical support is provided for standardization, normalization and industrialization development of the sand solidification technology, and the engineering efficiency and economic benefits are remarkably improved.

The present application relates to a kind of virtual marshalling system station marshalling and test method of departure function, equipment and medium, the method respectively tests virtual marshalling system in station has waist branch's track and station marshalling function without waist branch's track, and in two kinds of scenes, respectively test train FS mode departure and ATO mode departure function;While in the testing process, respectively from the visual interface of vehicle-mounted DMI, dispatching centralized control system CTC, wireless block center RBC maintenance station and interlocking maintenance station observe each step test result in the process of station marshalling. Compared with prior art, the present application has the scene of station marshalling in virtual marshalling system, greatly improves test efficiency and the like advantages.

The utility model discloses an endurance test device for a storage vehicle. The endurance test device comprises a switch control part, a test bench and a console, the switch control part is connected with the upper end of a storage vehicle air handle, and an execution element used for pressing a button on the air handle is arranged in the switch control part. The test bed comprises a vehicle body fixing part, a driving wheel supporting part and a bumping simulation part; according to the storage vehicle testing device, the testing device is arranged, so that the whole or local parts of the storage vehicle can be tested, and the universal performance of the storage vehicle testing device is improved.

The application discloses a PCIE device state detection method and system, electronic equipment and medium, relates to the technical field of PCIE device, and comprises the following steps: scanning a PCIE device tree on a server mainboard, and obtaining a PCIE device identifier on the PCIE device tree; disabling and enabling the connection state of the PCIE device and a central processor according to the device identifier; after the connection state of the PCIE device is disabled and enabled each time, performing PCIE link training once within a preset time; and after each link training is completed, the register results associated with the PCIE device are read and traversed to analyze the PCIE device state. The application can perform pressure test on the PCIE device, effectively improves the detection and diagnosis efficiency of the PCIE device, and if the PCIE device fails, the register information can be inquired, and the failure cause can be analyzed and located.

The application provides a kind of support extended vehicle-mounted multi-channel camera simulation method and system.Method includes: obtaining specified picture or video data, generating the original picture data of each frame, and according to the format of PPI, it is packed into PPI data format, and the ECC and CRC data required for each line are calculated;According to the resolution size of each camera, the required simulation simulation platform memory space is generated;The generated PPI, ECC and CRC data are injected into the memory space;According to the output state of the platform, update the data in the memory space to the next frame data during frame blanking;Using the PPI format module of the platform, according to the configuration of each channel, the data is divided into different Lane according to PPI format, and is output to CSI2 HOST according to PPI format.The application can simulate different types of cameras and their parameters.

The invention provides an automatic regression test method and system for process step files of battery test software. The method comprises the following steps: establishing a golden sample library containing a process step file set passing historical verification and corresponding standard output time sequence data; starting to-be-tested software and loading a virtual battery simulation engine, wherein the virtual battery simulation engine is configured to simulate battery response characteristics and respond to a hardware control instruction of the to-be-tested software; obtaining a to-be-tested step file associated with the to-be-tested software, loading the to-be-tested step file in batches, driving the virtual battery simulation engine to execute a test, and collecting actual measurement output time sequence data; and comparing the actual measurement output time sequence data corresponding to the part, contained in the gold sample library, in the to-be-tested work step file with standard output time sequence data to judge a regression test result and output a report. According to the method, the automatic regression test of the battery test software working step file which runs at an ultra-real-time speed and automatically performs high-precision data comparison is realized.

The invention discloses a water pressure detection device for a solid rocket engine. The device consists of a combustion chamber shell, a spray pipe shell, a top cover, a rear blanking cap, a cushion block, a sealing ring, a bolt and a locking nut, the top cover is connected with the front connector through a bolt, and a first sealing ring is arranged on the front connector of the combustion chamber shell. The spray pipe shell is connected with a combustion chamber shell rear connector through a bolt, and a second sealing ring is arranged on the combustion chamber shell rear connector. A step is arranged on the largest outer cylindrical surface of the rear blanking cap and forms an end face sealing groove with the tail step of the spray pipe shell, and a third sealing ring is installed; the small end of the rear blanking cap is provided with an external thread, penetrates through the step at the tail part of the spray pipe shell and the cushion block, and is tensioned by the locking nut; the middle of the rear blanking cap is provided with a through hole as a water inlet channel, and the small end is provided with internal threads for connecting a water inlet pipe. The pressure bearing capacity of the combustion chamber shell, the spray pipe shell and the top cover is examined through one-time hydraulic test, the sealing performance of the sealing ring and the strength performance of the connecting structure are examined, and efficiency is improved.

Embodiments of the present application provide an influence link generation method, device and storage medium, comprising: in response to a link generation request of test code, obtaining a development branch submission record corresponding to the test code. According to the development branch submission record, a changed function in the test code is determined, and an API interface function corresponding to the changed function is determined, the API interface function being called by other function modules except the function module where the changed function is located. A target function module having a dependency relationship with the API interface function and an entry point function corresponding to the target function module are determined. According to the changed function, the API interface function and the entry point function, an influence link corresponding to the test code is generated. By identifying the API interface function exposed by the changed function, the target function module having the dependency relationship is found, so as to know all external calling points possibly affected by the change, and then the cross-cluster calling condition of the changed function is known, and the influence link can be generated more accurately.