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If you keep the panels vacuumed, they should last for years. As a last resort, you can pull the panels and wash them. (See Martin Logan's Owner Site).So their limited lifespan is mainly related to dust accumulation? Or is it something related to repeated micro - arching (due to dust particles) identifiable by the typical low level buzz noises sometimes heard when putting your ear next to the charged panel when no music is playing? How often is it OK to vacuum them? (I\m doing it every 2 months or so; I wouldn't mind doing more often if this would prolong their life) |
I started out with ML Preface (non-electrostatic) for my fronts years ago. I quickly moved to a pair of used ReQuests which sounded great passively bi-amped. Currently I have the Summit Xs with their integrated pair of powered 10" woofers. The ReQuests are now my surround speakers. The ReQuests displayed a wider soundstage in my room. The Summit Xs are a bit brighter and more detailed. Their main difference is the bass is so much more natural and integrated. I have the Summits powered with a 100 WPC Rogue Atlas Magnum II tube amp. It sounds better than any SS amp I've used. I am still enjoying the ReQuests with their original panels, but have a spare pair of lightly used panels for backup if needed. If you keep the panels vacuumed, they should last for years. As a last resort, you can pull the panels and wash them. (See Martin Logan's Owner Site). |
Yes, it's essentially the same. With ML speakers, it's used only for optimizing the bass response. I suggest posting your question over at http://www.martinloganowners.com/forum/ if you'd like more responses. |
The woofer/bass integration with the stat panels has been markedly improved with their latest higher end models. Another big PLUS has been the addition of Anthem Room Correction, for optimizing overall bass response for your particular room and setup. That said, the ML Request was/is still an excellent speaker, with a slightly larger stat panel than many of the newer models. If the panels and woofers are still in good shape, you could add a separate ML BalancedForce sub (with the appropriate downloaded profile matching the Request), and be quite happy with the result. |