NK Current Switches
Current Switches are a Current Sensor type that will "trip" a relay at a preset current alarm point. Current Switches combine a Current Transformer, signal conditioner and limit alarm relay. Current Switches measure the magnetic field around an AC or DC current carrying conductor/wire and instead of generating a proportional signal to other instruments, their output type is a relay.
Applying Non-Contact Current Sensors
Current sensors are frequently used to provide essential information to automated control systems, and as primary controllers in relay logic schemes. The most common types:
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Current Transducers
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Current Transformer
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Current Switches
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Power Transducers
Key considerations for selecting a current switch
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Current range
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Type (i.e. Normally Open or Normally Closed) and number of relays
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Non-adjustable, factory set trip point or field adjustable
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Split core or solid core enclosure
How do Current Sensors Work
Current Sensors measure the magnetic field around an AC or DC current carrying conductor/wire and generate a proportional signal for use by a wide variety of instruments. Current sensors measure this field using one of two technologies. For DC currents, we use "Hall Effect" while for AC currents, we use "Inductive" technology.
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)
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The Hall Effect sensor has a core, Hall Effect device and signal conditioning circuitry. The current conductor passes through a magnetically permeable core that concentrates the conductor's magnetic field. The Hall Effect device is mounted in the core at a right angle to the concentrated magnetic field. A constant current in one plane excites the Hall device. When the energized Hall device is exposed to a magnetic field from the core, it produces a potential difference (voltage) that can be measured and amplified into process level signals such as 4-20mA or a contact closure.
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The Inductive Sensor has a wire-wound core and a signal conditioner. The current conductor passes through the core that magnifies the conductor's magnetic field. AC current constantly changes potential from positive to negative and back again, generally at the rate of 50 or 60 Hz. The expanding and collapsing magnetic field induces current in the windings. This secondary current is converted to a voltage and conditioned to output process-level signals such as 4-20mA or contact closures.
Know Your Power
The current sensor is an economical and reliable tool that is indispensable for monitoring equipment status, detecting process variations, and ensuring personnel safety.
Methods of Current Sensing
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Resistive shunt
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Hall effect
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Induction.
Resistive Shunt
The resistive shunt is a calibrated resistor placed in a current path that produces a voltage drop proportional to the current flow according to:
V = I x R where: V = voltage drop, I = current flow, R = shunt resistance
The voltage drop measurement is typically in the millivolt AC range. This output must be conditioned by a separate transducer into a process signal such as 4–20 mA or a contact closure.
Unfortunately, the shunt presents serious operational problems and potential safety hazards. Both sides of the shunt resistor are at line voltage, which in practice means bringing 480 VAC into an otherwise low-voltage control panel. This lack of isolation can cause serious injury to unsuspecting service personnel.
Since it is essentially a resistor, the shunt is often perceived as the least expensive solution. Although it is in fact a low-cost device, the signal conditioner must be built to withstand 480 VAC and is very expensive. Installation and operating costs of the resistive shunt further restrict its use. Installing this device requires cutting and re-terminating the current carrying conductor--an expensive and time-consuming proposition. Furthermore, because the shunt is a fixed voltage drop (insertion impedance) in the monitored circuit, it generates heat and wastes energy. The shunt is suitable only for DC current measurement and low-frequency AC measurement (<100 Hz).
Hall Effect Sensor
Hall effect and induction are noncontact technologies based on the principle that for a given current flow, a proportional magnetic field is produced around the current-carrying conductor. Both technologies measure this magnetic field, but with different sensing methods (see Figure).
The Hall effect sensor consists of three basic components: the core, the Hall effect device, and signal conditioning circuitry. The current conductor passes through a magnetically permeable core that concentrates the conductor's magnetic field. The Hall effect device is carefully mounted in a small slit in the core, at a right angle to the concentrated magnetic field. A constant current in one plane excites it. When the energized Hall device is exposed to a magnetic field from the core, it produces a potential difference (voltage) that can be measured and amplified into process level signals such as 4–20 mA or a contact closure.
Because the Hall sensor is totally isolated from the monitored voltage, it is not a safety hazard and has almost no insertion impedance. It also provides accurate and repeatable measurement on both AC and DC power. Hall effect transducers require more energy than conventional loop-powered, two-wire systems. Subsequently, most Hall sensors are three-wire or four-wire devices.
Depending on the design, Hall effect transducers can measure frequencies from DC to several kilohertz. Because they tend to be more expensive than shunts or inductive transducers, their use is generally limited to measuring DC power. Compared to the inductive transducer, their major disadvantage is limited rangeability.
Inductive Sensors
The inductive sensor consists of a wire-wound core and a signal conditioner. The current conductor passes through a magnetically permeable core that magnifies the conductor's magnetic field. AC current constantly changes potential from positive to negative and back again, generally at the rate of 50 Hz or 60 Hz. The expanding and collapsing magnetic field induces current in the windings. This is the principle that governs all transformers.
The current-carrying conductor is generally referred to as the primary and the core winding is called the secondary. The secondary current is converted to a voltage and conditioned to output process-level signals such as 4–20 mA or contact closures. Inductive sensing provides both high accuracy and wide turndown, and the output signal is inherently isolated from the monitored voltage. This isolation ensures personnel safety and creates an almost imperceptible insertion loss (voltage drop) on the monitored circuit.
Inductive sensors are designed to measure AC power and typically operate between 20 Hz and 100 Hz, although some units will work in the kilohertz range. A well-designed inductive sensor can be configured as a two-wire device to reduce installation cost.
Applying Non-Contact Current Sensors
Current sensors are frequently used to provide essential information to automated control systems, and as primary controllers in relay logic schemes. The two most common types are current transducers and current switches.
Current Transducers. Current transducers convert monitored current to a proportional AC or DC voltage or milliamp signal. These small devices have extremely low insertion impedance. Inductive transducers are easier to install because they are two-wire, self-powered (0–5 VDC or 0–10 VDC outputs), or loop-powered (4–20 mA output) instruments. Hall effect transducers are generally four-wire devices and require a separate power supply. Because both types can be connected directly to data systems and display devices, they are ideal for monitoring motors, pumps, conveyors, machine tools, and any electrical load that requires an analog representation over a wide range of currents.
Controlling pumps, compressors, heaters, conveyors, and other electrically powered loads requires accurate, real-time status feedback. The conventional approach to this monitoring problem has been to use pressure switches, optical sensors, and zero-speed switches. Within the past 10 years, however, a growing number of design and process engineers have found current sensing to be a more reliable and economical way to monitor and control electrically powered loads. Solid-state current sensors are easier to install and more reliable than electromechanical devices--and they deliver more information.
Simply stated, measuring the current input to equipment gives you more knowledge about actual equipment performance. Seeing load changes instantly can help you improve throughput, reduce waste, and prevent catastrophic equipment failure. Continuous real-time monitoring of current draw can also be used for trend analysis or status alarming.
Applications for Current Sensors
Controlling pumps, compressors, heaters, conveyors, and other electrically powered loads requires accurate, real-time status feedback. The conventional approach to this monitoring problem has been to use pressure switches, optical sensors, and zero-speed switches. Within the past 10 years, however, a growing number of design and process engineers have found current sensing to be a more reliable and economical way to monitor and control electrically powered loads. Solid-state current sensors are easier to install and more reliable than electromechanical devices--and they deliver more information.
Motors
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Fan Status: Independent Verification of Operation
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Conveyor Jam Protection
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Crusher/Grinder/Shredder Motor Interlocks
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Saw Load Monitoring
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DC Motor Installations
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Closed Loop Control
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Status Alarming
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Pumps
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Pump Jam & Suction Loss Protection
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Pump Load Monitoring
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Moisture Ingress on a Submersible Pump Motor
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Vacuum Pump Monitor
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Spin Pumps
Heaters
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Heater Life Prediction
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Heater Failure Detection
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Insulation Breakdown
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Ground Fault Monitoring on Heat Trace Systems
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Snow Melt Systems
Industrial Lighting
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Lamp Failure Detection
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Preventative Maintenance of a Critical Lighting System
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UV & IR Lamp Status Monitoring
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Power Equipment & Monitoring
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Current Transformer Monitoring
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Generator Installations
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Battery Charging System
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Equipment Ground Fault Monitoring
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Power Transfomer Monitoring
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Power Factor Correction Control
Miscellaneous
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Isolated Alarm System Interfacing
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Solar Panels
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Welder Tip Dressing
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Drill/Tool Status
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Safety Interlocks