| Feb. 13, 2024, 4:20 p.m. |
Created
43
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[{"model": "core.projectfund", "pk": 67021, "fields": {"project": 15274, "organisation": 11085, "amount": 280453, "start_date": "2017-06-01", "end_date": "2018-03-31", "raw_data": 173396}}]
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| Jan. 30, 2024, 4:25 p.m. |
Created
43
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[{"model": "core.projectfund", "pk": 59842, "fields": {"project": 15274, "organisation": 11085, "amount": 280453, "start_date": "2017-06-01", "end_date": "2018-03-31", "raw_data": 147076}}]
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| Jan. 2, 2024, 4:16 p.m. |
Created
43
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[{"model": "core.projectfund", "pk": 52709, "fields": {"project": 15274, "organisation": 11085, "amount": 280453, "start_date": "2017-06-01", "end_date": "2018-03-31", "raw_data": 128774}}]
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| Dec. 5, 2023, 4:24 p.m. |
Created
43
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[{"model": "core.projectfund", "pk": 45456, "fields": {"project": 15274, "organisation": 11085, "amount": 280453, "start_date": "2017-05-31", "end_date": "2018-03-30", "raw_data": 90343}}]
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| Nov. 27, 2023, 2:16 p.m. |
Added
35
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{"external_links": []}
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| Nov. 21, 2023, 4:43 p.m. |
Created
43
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[{"model": "core.projectfund", "pk": 38180, "fields": {"project": 15274, "organisation": 11085, "amount": 280453, "start_date": "2017-05-31", "end_date": "2018-03-30", "raw_data": 78610}}]
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| Nov. 21, 2023, 4:43 p.m. |
Created
41
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[{"model": "core.projectorganisation", "pk": 114510, "fields": {"project": 15274, "organisation": 14755, "role": "PARTICIPANT_ORG"}}]
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| Nov. 21, 2023, 4:43 p.m. |
Created
41
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[{"model": "core.projectorganisation", "pk": 114509, "fields": {"project": 15274, "organisation": 14755, "role": "LEAD_ORG"}}]
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| Nov. 21, 2023, 4:43 p.m. |
Created
40
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[{"model": "core.projectperson", "pk": 72041, "fields": {"project": 15274, "person": 16746, "role": "PM_PER"}}]
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| Nov. 20, 2023, 2:06 p.m. |
Updated
35
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{"title": ["", "Event Detection using Pattern Analytics Platform (EDPAP)"], "description": ["", "\nTITLE: Event Detection using Pattern Analytics Platform (EDPAP) At a time when many organisations are monitoring \u2018things\u2019 and as a result collecting large amounts of time-based data, Cybula is using its\u2019 considerable skills in developing novel pattern matching methods which can be used to monitor the health of complex assets and systems. The company has developed a set of analytical tools which can be used to answer common questions such as is the asset working normally or has this event been experienced before across the fleet of assets. Multiple models can be set up and validated before routine use on the company\u2019s Event Visualisation Platform (EVP), a flexible, scalable data management platform that focuses the user on detected events. With the EVP, Cybula can offer a customised approach to monitoring as it can develop models quickly, customise the EVP according to client requirements and then integrate with other data systems to create the monitoring application. Typically, these event models can be adjusted so they accurately detect the events required unlike many traditional monitoring systems which generate many false alerts. This repeatable business model allows Cybula to assemble different monitoring applications in very productive way making Cybula\u2019s solutions affordable to many more organisations who want advanced monitoring systems but cannot justify the price of traditional condition monitoring solutions. There are many applications with Cybula having worked in aerospace (engine monitoring), rail transport (track and vehicle condition), water industry (pipeline leak detection) and medical (critical care monitoring). However, it is the energy industry where Cybula seeks to prove the usefulness of its\u2019 technologies using its\u2019 prior experience with a range of clients including monitoring on rotating machinery (EDF and SSE), critical steam generation (Doosan), energy balancing (SSE), short-term wind forecasting (SSE), and pipeline leak detection (Sim-Soft/Shell). In this FOAK project, we want to develop an EVP application to monitor a set of Gas Circulators operating at 2 nuclear power stations. Having already proved the value of Cybula\u2019s analytics to EDF UK\u2019s Rotating Machinery Group, we aim to show how various event models operating on performance data from these assets collected and managed by the EVP can provide a superior, advisory alerting system compared to the current plant installed vibration alarm system. In doing so, Cybula will gain valuable experience in implementing a working application of the EVP for the first time with the potential for wider application in the EDF group, the nuclear industry and the wider energy market.\n\n"], "extra_text": ["", "\n\n\n\n"], "status": ["", "Closed"]}
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| Nov. 20, 2023, 2:06 p.m. |
Added
35
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{"external_links": [60017]}
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| Nov. 20, 2023, 2:06 p.m. |
Created
35
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[{"model": "core.project", "pk": 15274, "fields": {"owner": null, "is_locked": false, "coped_id": "cced3847-a826-4a20-95d2-030352b39b03", "title": "", "description": "", "extra_text": "", "status": "", "start": null, "end": null, "raw_data": 78593, "created": "2023-11-20T13:57:35.251Z", "modified": "2023-11-20T13:57:35.251Z", "external_links": []}}]
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