A method for simulating a peripheral circuit arrangement that can be connected to a control device is provided. A simulation device is electrically connected to the control device and has a first control element with which a first simulation current that can be passed from a first load terminal of the control device to a first control element output of the first control element can be influenced. The first control element includes a first multistage converter, and the simulation device also includes a first semiconductor switch control and a computing unit that executes model code. A first switch control signal is computed and provided for forwarding to the first semiconductor switch control, which has at least one first comparator. A pulse-width-modulated first gate-source voltage is generated and applied to a first control terminal and a first simulation current is influenced by the first gate-source voltage.

A handheld field maintenance tool with improved diagnostic functions is provided. The tool includes a process communication module configured to interact with a field device. A controller is coupled to the process communication module. The controller is configured to execute a number of improved diagnostic functions relative to the field device. The controller may obtain contextual information relative to a current field maintenance operation and preload at least one resource relative to a next field operation step. The controller may obtain process alarm information through a wireless communication module, and field device alert information through the process communication module and provide an indication on a display relative to both process alarm information and field device alert information. The controller may execute a sequence of field device maintenance operations on the field device in response to a signal from a user input device. The controller may obtain snapshot information in response to a signal from a user input device.

A handheld field maintenance tool is provided. The handheld field maintenance tool includes a process communication module configured to communicate with a field device. The handheld field maintenance tool also includes a display and a user input device. A controller is coupled to the process communication module, the user input device and the display and is configured to generate a listing of task-based field maintenance operations on the display and receive a user input selecting a task-based field maintenance operation. The controller is configured to automatically traverse a menu of the field device using a fast-key sequence relative to the selected task. A method of creating a task-based field maintenance operation is provided. A method of interacting with a field device menu is also provided.

A simulation apparatus for simulating a peripheral circuit arrangement connected to a regulating device and has a first current controller for influencing a first load current and a second current controller for influencing a first source current. The first current controller is controlled by a model code and used to set the first load current, and the first load current is routed to a first load connection of the regulating device. The second current controller is controlled by the model code and used to set the first source current, which is routed to a first supply connection of the regulating device. The model code influences the model code on the first current controller and the second current controller allows the first load current to be recovered at least proportionally from the first source current and/or the first source current to be recovered at least proportionally from the first load current.

A method for carrying out a setting mode of a container inspection apparatus including the following steps: a plurality of spatially resolved sensor data detected by the sensor device is stored on a non-volatile storage device, which is retrieved by a setting device in the setting mode; the setting device is provided with a set of test evaluation parameters, which are to be assessed in terms of a working mode of the container inspection device, in which the set of test evaluation parameters is set as a set of real-time evaluation parameters in the real-time evaluation device; for assessing the set of test evaluation parameters, the setting device determines at least one statistical assessment variable on the basis of the retrieved plurality of spatially resolved sensor data.

An intrinsically-safe handheld field maintenance tool includes a controller, a process communication module, and a display. The process communication module is configured to communicate with a field device using a process communication protocol. The display is coupled to the controller. A user interface module is also coupled to the controller and is configured to receive user input. The controller is configured to detect a user input help request and provide a video output on the display in response to the user input help request.

A testing system for testing an Electronic Control Module (ECM) of a machine is provided. The testing system comprises a host system and a hardware-in-loop (HIL) system. The HIL system includes a simulation model having one or more latency-sensitive test cases associated with the machine. The HIL system includes a processing unit. The processing unit is configured to simulate the one or more latency-sensitive test cases in response to a test initiation trigger signal from the host system. The testing system further includes an input/output (I/O) unit. The input/output unit is configured to communicate with the processor and an ECM under test.

Global optimization and verification of cyber-physical systems using graphical floating point math functionality on a heterogeneous hardware system (HHS). A program includes floating point implementations of a control program (CP), model of a physical system (MPS), objective function, requirements verification program (RVP), and/or global optimizer. A simulation simulates HHS implementation of the program using co-simulation with a trusted model, including simulating behavior and timing of distributed execution of the program on the HHS, and may verify the HHS implementation using the RVP. The HHS is configured to execute the CP and MPS concurrently in a distributed manner. After deploying the program to the HHS, the HHS is configured to globally optimize (improve) the CP and MPS executing concurrently on the HHS via the global optimizer. The optimized MPS may be usable to construct the physical system. The optimized CP may be executable on the HHS to control the physical system.

A decentralized peripheral having process input and process output modules which, in a process control mode of operation, interact with field devices connected to these modules, and having an interface module in which a process image is stored, wherein in the process control mode of operation the process input modules write process input values for processing via an automation device connected to the decentralized peripheral into the process image, and the automation device writes process output values for processing via the process output modules into the process image such that as real a behavior as possible of this decentralized peripheral can be simulated.

A system and method for conveyor configuration and testing. The system is configured to execute the method, which includes: receive input data relating to configuration of a conveyor system; prepare a simulation of the configured conveyor system; operate the simulation of the conveyor system; determine at least one operational parameter related to the conveyor system to be monitored; monitor the at least one operational parameter during operation of the simulation of the conveyor system; determine if the configuration of the conveyor system needs to be adjusted based on the monitored operational parameter; if the configuration needs to be adjusted, automatically make an adjustment and return to operate the simulation of the conveyor system; and continue the simulation until otherwise terminated. In some cases, the monitoring operational parameters uses a machine learning model based on actual data from operating conveyors.