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Description
22226-E1-XL-C2 FAGTechnische Basisdaten Hersteller: FAG Synonym: 0190004990020 22226 E1 C2 Erweiterte technische Daten ueres Breitenmae: mm 230,00 Begrenzungsdrehzahl (n G) "3350. 0000" ueres Breitenmae: mm 64,00 ueres Breitenmae: mm 64,00 C2 Bearing Internal Clearance Smaller Than Normal E1 Increased Capacity Design ECLASS number 23 05 09 11 ECLASS2 number 23 05 09 11 Einzelgewicht in (kg): 10. 5 Innenmae: mm 130,00 Interne Radialluft C2 Innenluft (kleiner als Cn)
Technische Basisdaten
| Hersteller: FAG |
| Synonym: 0190004990020 22226-E1-C2 |
Erweiterte technische Daten
| Äußeres Breitenmaße: mm 230,00 |
| Begrenzungsdrehzahl (n G) "3350.0000" |
| Äußeres Breitenmaße: mm 64,00 |
| Äußeres Breitenmaße: mm 64,00 |
| C2 Bearing Internal Clearance Smaller Than Normal |
| E1 Increased Capacity Design |
| ECLASS number 23-05-09-11 |
| ECLASS2 number 23-05-09-11 |
| Einzelgewicht in (kg): 10.5 |
| Innenmaße: mm 130,00 |
| Interne Radialluft C2 Innenluft (kleiner als Cn) |
| Radial Dynamic Load Rating Cr (N) 760000 |
| Radial Static Load Rating C0r (N) 890000 |
| Referenzdrehzahl (n ϑr) "2500.0000" |
| Schwingsiebausführung Keine Schwingsiebausführung |
| XL X-Life |
| Artikelnummer 22226-E1-XL-C2 FAG |
| Auch bekannt als 019000499002022226-E1-C2 |
| B 64 mm Äußeres Breitenmaße: |
| Äußeres Breitenmaßmm 64,00 |
| C 0r 890.000 N Statische Tragzahl, radial |
| C r 760.000 N Dynamische Tragzahl, radial |
| C ur 81.000 N Ermüdungsgrenzbelastung, radial |
| Abdichtung Keine Abdichtung |
| Gewicht (kg) 10.5 |
| Innenmm 130,00 |
| Marke: FAG |
| T max 200 °C Betriebstemperatur max. |
| T min -30 °C Betriebstemperatur min. |
| Y 0 2,56 Statischer Axiallastfaktor |
| Y 1 2,62 Dynamischer Axiallastfaktor |
| Y 2 3,9 Dynamischer Axiallastfaktor |
| d =a min 144 mm Minimaler Anlagedurchmesser Wellenschulter |
| d =s 6,3 mm Durchmesser Schmierkanal |
| e 0,26 Grenzwert für Fa/Fr für die Anwendbarkeit der versch. Werte der Faktoren X und Y |
| n G 3.350 1/min Grenzdrehzahl |
| n s 12,2 mm SchmiernutÄußeres Breitenmaße: |
| n ϑr 2.500 1/min Bezugsdrehzahl |
| r a max 2,5 mm Maximaler Freistichradius |
| r min 3 mm Minimaler Kantenabstand |
| ≈m 10,988 kg Einzelgewicht |
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4.7 ★★★★★
Based on 29 reviews
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Product Reviews
★★★★★ 1
Nothing new
Format: Audiobook
There nothing new in this book you will defiantly find this content in any leadership book
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Reviewed in the United States on November 16, 2019
★★★★★ 5
Great book
Format: Paperback
Love the fact you put examples in python and javascript.
Great book.
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Reviewed in the United States on June 10, 2025
★★★★★ 5
proper documentation from langchain
Format: Paperback
Liked the book. But Still missing Human in the loop.
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Reviewed in the United States on April 19, 2025
★★★★★ 3
Already outdated
Format: Paperback
Concepts are sound but the code in this book is already obsolete
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Reviewed in the United States on August 5, 2025
★★★★★ 5
Unlocking Practical AI: A Developer’s Guide to Building with LLMs and LangChain
Format: Paperback
If you're a developer eager to move beyond LLM experimentation and build robust, context-aware AI applications, this book offers both inspiration and practical guidance. The authors open with a clear passion for the transformative potential of large language models (LLMs) and LangChain, framing these technologies as not just enhancements to the developer’s toolkit, but as gateways to new kinds of “thing-building” superpowers. This sense of possibility is grounded in step-by-step instruction, making the book approachable for those with Python or JavaScript backgrounds who may be new to the world of production-grade AI agents.
What stands out is the book’s careful scaffolding: starting with foundational concepts like prompt-based programming and progressing to advanced capabilities such as retrieval-augmented generation, agent planning, and tool integration. Each stage is contextualized with real-world use cases, like customizing chatbots to interact with your own documents, personalizing user experiences through memory, and deploying to production with reliability and security in mind. The focus on chain-of-thought reasoning and LangGraph’s agent architecture demonstrates the authors’ awareness of the current state of AI, where context and planning are just as important as raw language ability.
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Reviewed in the United States on July 17, 2025