The disclosure relates to an autonomous device for tracking the usage time of a generator set, capable of providing an operating time of the generator set. The module includes at least one first sensor (101) capable of measuring a first parameter representing a state of operation of said generator set (9), a data processor furnishing the characteristic information for an operating time, as a function of the first parameter, storage of the characteristic information for an operating time, and a transmitter capable of transmitting the characteristic information for an operating time to a terminal or an external server.

A grinder selection device includes: an input unit that inputs a grinding condition for a workpiece as a grinding target of grinding machining including at least the geometry of the workpiece and vibration data indicating vibration of a grinding machine, and grinder information about one or more grinders as grinder candidates to be used for the grinding machining; a learned model acquired through supervised learning using training data containing input data and label data, the input data containing an arbitrary grinding condition for a workpiece as a grinding target of grinding machining by an arbitrary grinding machine including at least the geometry of the workpiece and vibration data indicating vibration of the grinding machine, and grinder information about an arbitrary grinder, the label data being data indicating the adequacy or inadequacy of a combination between the grinding condition and the grinder information about the grinder; and a judgment unit.

A grinder selection device includes: an input unit that inputs a grinding condition for a workpiece as a grinding target of grinding machining including at least the geometry of the workpiece and vibration data indicating vibration of a grinding machine, and grinder information about one or more grinders as grinder candidates to be used for the grinding machining; a learned model acquired through supervised learning using training data containing input data and label data, the input data containing an arbitrary grinding condition for a workpiece as a grinding target of grinding machining by an arbitrary grinding machine including at least the geometry of the workpiece and vibration data indicating vibration of the grinding machine, and grinder information about an arbitrary grinder, the label data being data indicating the adequacy or inadequacy of a combination between the grinding condition and the grinder information about the grinder; and a judgment unit.

Performance mapping of equipment performance parameters by capturing, mapping, and/or structuralizing equipment performance data of a device for installation in a system. This includes generating performance maps which outline the expected feature performance parameter behavior of the equipment based on a set of operating parameters that capture the operating conditions. Each performance parameter on the map is representative of an operating point of specific operating conditions taken at a particular point in time. In one example, a performance parameter can be defined by an individualized set of parameter coefficients which in turn are dependent on instantaneous operating conditions. With the performance maps determined individually for devices as part of the system, and stored along with a time of testing, activities such as continuous commissioning, monitoring and verification, preventative maintenance, fault detection and diagnostics, as well as energy performance benchmarking and long term monitoring can be performed.

Performance mapping of equipment performance parameters by capturing, mapping, and/or structuralizing equipment performance data of a device for installation in a system. This includes generating performance maps which outline the expected feature performance parameter behavior of the equipment based on a set of operating parameters that capture the operating conditions. Each performance parameter on the map is representative of an operating point of specific operating conditions taken at a particular point in time. In one example, a performance parameter can be defined by an individualized set of parameter coefficients which in turn are dependent on instantaneous operating conditions. With the performance maps determined individually for devices as part of the system, and stored along with a time of testing, activities such as continuous commissioning, monitoring and verification, preventative maintenance, fault detection and diagnostics, as well as energy performance benchmarking and long term monitoring can be performed.

According to one embodiment, a monitoring system includes a processor. The processor accepts first data output from a first detector. The first detector detects a signal caused by equipment. The processor performs a first determination when a first value is in a first state. The first value indicates a state of the first detector or an environment where the equipment is provided. The first determination determines a condition of the equipment by using a first model and the first data. The processor performs a second determination when the first value is in a second state different from the first state. The second determination determines the condition of the equipment by using a second model and the first data. The second model is different from the first model.

A method for controlling a construction machine can include dividing a work area into a plurality of work lanes; selecting a first set of consecutive work lanes of the plurality of work lanes that can be worked without an obstruction; and completing one or more passes on the selected first set of consecutive work lanes before moving on to another set of the plurality of work lanes.

A method for controlling a construction machine can include dividing a work area into a plurality of work lanes; selecting a first set of consecutive work lanes of the plurality of work lanes that can be worked without an obstruction; and completing one or more passes on the selected first set of consecutive work lanes before moving on to another set of the plurality of work lanes.

A monitoring system for a machine is disclosed. The monitoring system may have a database, a memory storing first instructions, and a controller configured to execute the first instructions. The controller may be configured to receive a first input including selection of a sensor associated with a component of the machine, and a second input specifying a machine state, defining a first operating condition associated with the component. The controller may also be configured to receive a third input specifying generation of a component parameter based on a measurement from the sensor, and a fourth input specifying a fault condition associated with at least one of the measurement and the component parameter. The controller may generate a rule-set, including second instructions based on the first input, the second input, the third input, and the fourth input. The controller may also store the rule-set in the database.

A method of monitoring the health of a gas turbine engine of at least a pair of engines of an aircraft for example. The method comprising the steps of: a) obtaining steady state readings from predetermined sensors on the engines; b) calculate a percentage difference of the steady state readings from a unique engine linear synthesis model for each engine; c) compare the difference between the percentage differences for each engine and d) where this difference exceeds a predetermined value issue a warning as to an engine health problem. Maintenance of the engine can therefore be advantageously scheduled.