A method of remotely configuring one or more building system components at a building site uses a cloud-based server remote from the building site. The cloud-based server receives information from an intelligent gateway at the building site that identifies each of one or more building system components at the building site. The cloud-based server is used to create a site configuration that is based at least in part on the identified information for each of the one or more building system components. The site configuration is then downloaded from the cloud-based server to the intelligent gateway such that the intelligent gateway is able to pass configuration information to one or more local controllers that control operation of the one or more building system components.

The present invention relates to a system (100) for monitoring process controls, said system (100) comprising: an engineering tool module (10) configured to provide process control for an engineering product and to accomplish initializing of the process control of the engineering product; and a monitoring tool module 20) configured to be co-executed with the initializing of the process control of the engineering product and to be coupled to the process control of the engineering product.

A shovel includes a hardware processor configured to collect diagnostic data from a condition detecting sensor and to detect an abnormality based on the collected diagnostic data. The hardware processor is configured to continue to collect the diagnostic data, after detection of the abnormality during collection of the diagnostic data.

A system for use with an electric machine is provided. The system includes a processor and a memory comprising a set of memory modules, which, when executed by the processor, cause the processor to perform certain operations. The operations include receiving operational data from the electric machine, and generating, based on the operational data, a first set of diagnostic data, by executing a first memory module from the set of memory modules. The operations further include generating, based on the operational data, a second set of diagnostic data, by executing a second memory module from the set of memory modules, the second memory module including a set of parameters associated with a diagnostics model of the electric machine. Furthermore, the operations include effecting, based on the operational data, the first set of diagnostic data, and the second set of diagnostic data, a change in at least one parameter.

A method for monitoring an industrial machine, the method may include selecting a selected reference component for each component out of one or more components of the industrial system; the selecting provides one more selected reference components; wherein each selected reference component is selected out of multiple reference components; wherein for each component the selecting is based on similarities between the component and reference components of the multiple reference components; determining one or more learnt mappings between (i) sensed information related to the one or more components and (ii) predicted failures of the one or more components ; wherein the learning is based, at least in part, on one or more reference mappings between (i) sensed information related to the one or more selected reference components and (ii) predicted failures of the one or more selected reference components; monitoring the one or more components to receive monitoring results; and evaluating the operation of the one or more components based on the monitoring results and the one or more reference mapping.

One embodiment of the present invention provides an apparatus, or the like, which detects an anomaly of a controller of a control system by learning relationship between input and output of the controller. An anomaly detection apparatus which is one embodiment of the present invention includes a first acquirer, a second acquirer, a history recorder, an estimator, and a first anomaly determiner. The first acquirer acquires an input signal to a control apparatus which executes control on a controlled apparatus. The second acquirer acquires an output signal from the control apparatus. The history recorder records information regarding the acquired input signal and the acquired output signal as history. The estimator estimates the output signal using the history and an estimation model. The first anomaly determiner determines an anomaly of the control apparatus by comparing the estimated output signal with the acquired output signal.

A monitoring apparatus according to the present invention includes: a predicting unit configured to, based on a correlation model that corresponds to processing executed in a monitored object in accordance with a preset operation plan and represents a mutual relation between one measured value and other measured value measured from the monitored object, predict the other measured value when the one measured value is changed; and a determining unit configured to determine whether or not the predicted other measured value exceeds an allowable value set for the other measured value during the processing executed in the monitored object in accordance with the operation plan.

A method and system for assigning slot addresses to modules in a fault tolerant industrial control system includes a pair of backplane switches on each base. Each backplane switch is configured to communicate between one backplane and the modules located on the base and to communicate between backplane switches located at adjacent bases. A backplane switch on a bank master base first assigns a base address and slot addresses to itself. The backplane switches on each additional base initiate transmission of a base address request. A base address response, including a base address and slot numbers for the adjacent base, is transmitted after a base has its own address assigned. Each base repeats the process in sequence along the bank, incrementing the base address by one and the slot address by the number of slots on the base and passing the new base and slot addresses along the bank.

A method detects and localizes a failure of a measurement acquisition channel in an acquisition system including two redundant acquisition channels for the measurement of a physical quantity in an environment. The method uses a processor with a memory storing a model including modeled values of the physical quantity based on measurements of other physical quantities in the environment. The method includes detecting a symptomatic error of a defective acquisition channel when a deviation between the measured values of the two channels reaches a detection threshold, waiting to let the acquisition system evolve for a certain period, and localizing the defective channel among the two channels, when the deviation of the values measured between the channels reaches a localization threshold different from the detection threshold. The localization is made from the comparison of the measured value of each of the channels with a modeled value of the physical quantity.

A monitoring apparatus according to the present invention includes: a detecting unit configured to detect that a monitored object is in a preset specific state based on a plurality of measured values measured from the monitored object; and a specifying unit configured to specify, among elements causing the measured values, the element related to detection of the specific state of the monitored object based on the measured values, and also specify the element based on preset properties of the elements of the measured values.