METHODS AND SYSTEMS FOR THE INDUSTRIAL INTERNET OF THINGS
The methods and systems for data collection, processing, and utilization of signals with a platform monitoring at least a first element in a first machine in an industrial environment generally include obtaining, automatically with a computing environment, at least a first sensor signal and a second sensor signal with a local data collection system that monitors at least the first machine and connecting a first input of a crosspoint switch of the local data collection system to a first sensor and a second input of the crosspoint switch to a second sensor in the local data collection system. The methods and systems also include switching between a condition in which a first output of the crosspoint switch alternates between delivery of at least the first sensor signal and the second sensor signal and a condition in which there is simultaneous delivery of the first sensor signal from the first output and the second sensor signal from a second output of the crosspoint switch and switching off unassigned outputs of the crosspoint switch into a high-impedance state. There is also continuously monitoring of at least a third input of the crosspoint switch with an alarm having a pre-determined trigger condition when the third input is unassigned to any of multiple outputs on the crosspoint switch and planning data acquisition routes based on hierarchical templates associated with at least the first element in the first machine in the industrial environment. The local data collection system also manages data collection bands.
1 . A method for data collection, processing, and utilization of signals with a platform monitoring at least a first element in a first machine in an industrial environment, the method comprising:
obtaining, automatically with a computing environment, at least a first sensor signal and a second sensor signal with a local data collection system that monitors at least the first machine;
connecting a first input of a crosspoint switch of the local data collection system to a first sensor and a second input of the crosspoint switch to a second sensor in the local data collection system;
switching between a condition in which a first output of the crosspoint switch alternates between delivery of at least the first sensor signal and the second sensor signal and a condition in which there is simultaneous delivery of the first sensor signal from the first output and the second sensor signal from a second output of the crosspoint switch;
switching off unassigned outputs of the crosspoint switch into a high-impedance state;
continuously monitoring at least a third input of the crosspoint switch with an alarm having a pre-determined trigger condition when the third input is unassigned to any of multiple outputs on the crosspoint switch; and
planning data acquisition routes based on hierarchical templates associated with at least the first element in the first machine in the industrial environment, and wherein the local data collection system manages data collection bands.
2 . The method of claim 1 wherein the data collection bands define a specific frequency band and at least one of a group of spectral peaks, a true-peak level, a crest factor derived from a time waveform, and an overall waveform derived from a vibration envelope.
3 . The method of claim 1 wherein the local data collection system includes a neural net expert system using intelligent management of the data collection bands.
4 . The method of claim 1 wherein the local data collection system creates data acquisition routes based on hierarchical templates that each include the data collection bands related to machines associated with the data acquisition routes.
5 . The method of claim 4 wherein at least one of the hierarchical templates is associated with multiple interconnected elements of the first machine.
6 . The method of claim 1 wherein at least one of the hierarchical templates is associated with similar elements associated with at least the first machine and a second machine.
7 . The method of claim 1 wherein at least one of the hierarchical templates is associated with at least the first machine being proximate in location to a second machine.
8 . The method of claim 1 further comprising controlling a graphical user interface system of the local data collection system to manage the data collection bands, wherein the graphical user interface system includes an expert system diagnostic tool.
9 . The method of claim 1 wherein the computing environment of the platform includes cloud-based, machine pattern analysis of state information from multiple sensors to provide anticipated state information for the industrial environment.
10 . The method of claim 1 wherein the computing environment of the platform provides self-organization of data pools based on at least one of utilization metrics and yield metrics.
11 . The method of claim 1 wherein the computing environment of the platform includes a self-organized swarm of industrial data collectors.
12 . The method of claim 1 wherein each of multiple inputs of the crosspoint switch is individually assignable to any of multiple outputs of the crosspoint switch.
13 . A method of monitoring of a machine having at least one shaft supported by a set of bearings, the method comprising:
monitoring a first data channel assigned to a single-axis sensor at an unchanging location associated with the machine;
monitoring second, third, and fourth data channels, each assigned to an axis of a three-axis sensor;
recording gap-free digital waveform data simultaneously from all of the data channels while the machine is in operation;
determining a change in relative phase based on the digital waveform data;
monitoring the first data channel assigned to the single-axis sensor at an unchanging location located on a second machine;
monitoring the second, the third, and the fourth data channels, each assigned to the axis of a three-axis sensor that is located at position associated with the second machine; and
recording gap-free digital waveform data simultaneously from all of the data channels from the second machine while both of the machines are in operation.
14 . The method of claim 13 wherein the tri-axial sensor is located at a plurality of positions associated with the machine while obtaining the digital waveform data.
15 . The method of claim 13 wherein the second, third, and fourth channels are assigned together to a sequence of tri-axial sensors each located at different positions associated with the machine.
16 . The method of claim 15 wherein the data is received from all of the sensors simultaneously.
17 . The method of claim 13 further comprising determining an operating deflection shape based on the change in relative phase information and the waveform data.
18 . The method of claim 13 wherein the unchanging location is a position associated with the shaft of the machine.
19 . The method of claim 15 wherein the tri-axial sensors in the sequence of the tri-axial sensors are each located at different positions and are each associated with different bearings in the machine.
20 . The method of claim 15 wherein the unchanging location is a position associated with the shaft of the machine and wherein the tri-axial sensors in the sequence of the tri-axial sensors are each located at different positions and are each associated with different bearings that support the shaft in the machine.
21 . The method of claim 13 further comprising characterizing a contribution from each of the machines in the gap-free digital waveform data simultaneously from the second machine.