Feature leak-proof mechanical seals, easy service design, heavy-duty motors, rugged construction. 1 year limited warranty. Explore purchase options available for this product. Available in high head or medium head series (separate listing for Medium Head).

DHHG-53L STA-RITE D-Series High Head Centrifugal Pump with Noryl Impeller - 2-1/2 HP, 115/230 Volts, 60 Hz, Single Phase, 3450 RPM, Suction: PKG-72 (2-1/2"), Discharge: Top: 2". DISCHARGE SIZE: Depends Upon Specific Model. See Spec Sheet under "RESOURCES" Tab. Currently in stock.

Feature leak-proof mechanical seals, easy service design, heavy-duty motor.

DISCHARGE SIZE: Depends Upon Specific Model. See Spec Sheet under "RESOURCES" Tab. Best Price Guarantee! Request a Call. Currently in stock.

上海典昊化工科技有限公司现有厂房8800余平方米，并于2007年批获自行进出口权证，是通过 ISO9001及16949的企业。 自成立以来主要为客户提供金属零（部）件的钣金件、焊接加工、电泳加工、喷塑加工、喷漆加工。 现有主要设备：剪板机，折弯机、电焊机、悬挂式抛丸机，通过式抛丸机、手工喷砂机，悬挂式喷漆流水线，悬挂式喷塑流水线，悬挂式电泳流水线、大型喷塑烘箱。 以及相应的从业资质人员和质量检测设备。 涵盖的加工领域有纺织机械，工程机械，农业机 …

Sta-Rite D Series High Head Self-Priming Centrifugal Pump. Built with a rugged construction and heavy duty motor, this fast-priming pump has an easy service design and air volume control tapping. Note: suction flange PKG 53 (sold separately) is required to match pump for attachment with NPT pipe. Features. Applications.

Part #:DHHG Available in high head or medium head series (separate listing for Medium Head). Feature leak-proof mechanical seals, easy service design, heavy-duty motors, rugged construction.

Sta-Rite DHHG-53l Centrifugal Pump. Self Priming Centrifugal Pump and Motor assembly, High Head, c/w 2.5 Horsepower, Single Phase, Electric Motor. Key Features: 2 1/2 Horsepower; Phase - 1; Suct. Flanges - 53; Disch. - 2" Voltage - 115/230; Pounds - 120

Features mechanical seals, easy service design, heavy duty motors, rugged construction. Lawn Sprinkling operate from 1 to 30 or more heads. Can be safely operated by timer or other automatic device. Contractors for dewatering excavation, jetting, water …

To address this issue, this article introduces a dynamic heterogeneous hypergraph neural network (HGNN) model that utilizes a Transformer-based combined attention mechanism and designs a hypergraph representation imaging network to enhance model inference without increasing parameter count.