A method and an arrangement of controlling simulation of a coupled hybrid dynamic system comprising a component under test and a virtual model includes driving the physical component under test of the system on a test rig over a period of time to conduct a test by applying an initial test drive signal input to the test rig to generate a test rig response. At least a portion of the test rig response is inputted into the virtual model of the system to obtain a model response of the system. A condition of the physical component under test is assessed during at least a portion of the period of time to conduct the test based on comparing another portion of the test rig response with the model response where an output relating to the assessment is recorded or rendered.

An estimation unit calculates an estimated value of oxygen concentration in an exhaust passage on the basis of a target injection amount of a fuel injection valve and an air intake amount of an engine. A first determination unit determines the relationship of a detected value to the estimated value of the oxygen concentration, in both a fuel-injecting state and a non-fuel-injecting state. For each of a plurality of cylinders, a second determination unit acquires crankshaft angular acceleration during the expansion strokes of the cylinders in the fuel-injecting state, and determines the relationship of each angular acceleration to the average value of all of the angular accelerations. An abnormality determination unit determines whether or not there is an abnormality in an engine system on the basis of the determination results of the first and second determination units.

An apparatus is provided. The apparatus includes a detector configured to detect a state of the apparatus, and a processor configured to determine a current change degree of an apparatus state between a current point of time and a previous point of time based on a first change value of the apparatus state at the current point of time and a second change value of the apparatus state at the previous point of time earlier than the current point of time, and determine whether change in the apparatus state is normal or abnormal based on a result of comparison between the determined current change degree and an accumulated change degree of the apparatus state accumulated for a predetermined time section before the current point of time.

An apparatus is provided. The apparatus includes a detector configured to detect a state of the apparatus, and a processor configured to determine a current change degree of an apparatus state between a current point of time and a previous point of time based on a first change value of the apparatus state at the current point of time and a second change value of the apparatus state at the previous point of time earlier than the current point of time, and determine whether change in the apparatus state is normal or abnormal based on a result of comparison between the determined current change degree and an accumulated change degree of the apparatus state accumulated for a predetermined time section before the current point of time.

A malfunction detection device for a resolver detects malfunction in a resolver with accuracy and stability even if a value of a square sum is varied between inside and outside of a normal range. When the resolver is in malfunction, a sine signal and a cosine signal are read. It is determined whether a malfunction determination of the resolver is prohibited, or not, from read values of the sine signal and the cosine signal, or square values thereof. When it is determined that the malfunction determination of the resolver is prohibited, the count value is accumulated and incremented every time the test value falls outside a normal range. When the count value arrives at a given value or higher, it is determined that the resolver is in malfunction.

The present invention provides a system wherein an essential inspection of components of a machine or vehicle is performed and wherein the inspected components do no need to be brought into close proximity to the mechanism or device that activates the starting element of the machine. Moreover, the system of the present invention allows extending the essential safety inspection to those machine components that cannot be removed or are no practical to remove in order to be inspected. Still, the present invention provides a system that forces the safety essential inspection of machine components to be performed by not allowing the electrical feeding of the ignition mechanism that start the operation of the machine unless the essential inspection system is activated by completing a predetermined protocol or sequence of inspection steps.

Obtaining position data of an asset; obtaining one or more context sensor signals, each context sensor signal representing a real-time measured parameter related to the asset; in near-real-time, updating a function that determines a present usage rate of the asset based on the position data, weighted values of the context sensor signals, and an immediate past usage status; in near-real-time, estimating an asset time to failure based on the updated function and a future asset task allocation; and based on the estimate of asset time to failure, and in near-real-time, adjusting the future asset task allocation.

Obtaining position data of an asset; obtaining one or more context sensor signals, each context sensor signal representing a real-time measured parameter related to the asset; in near-real-time, updating a function that determines a present usage rate of the asset based on the position data, weighted values of the context sensor signals, and an immediate past usage status; in near-real-time, estimating an asset time to failure based on the updated function and a future asset task allocation; and based on the estimate of asset time to failure, and in near-real-time, adjusting the future asset task allocation.

Obtaining position data of an asset; obtaining one or more context sensor signals, each context sensor signal representing a real-time measured parameter related to the asset; in near-real-time, updating a function that determines a present usage rate of the asset based on the position data, weighted values of the context sensor signals, and an immediate past usage status; in near-real-time, estimating an asset time to failure based on the updated function and a future asset task allocation; and based on the estimate of asset time to failure, and in near-real-time, adjusting the future asset task allocation.

Obtaining position data of an asset; obtaining one or more context sensor signals, each context sensor signal representing a real-time measured parameter related to the asset; in near-real-time, updating a function that determines a present usage rate of the asset based on the position data, weighted values of the context sensor signals, and an immediate past usage status; in near-real-time, estimating an asset time to failure based on the updated function and a future asset task allocation; and based on the estimate of asset time to failure, and in near-real-time, adjusting the future asset task allocation.