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Small, Low-Cost Industrial Sensor for Real-Time Object Distance & Length (0.5-0.6m)

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    Jon Jon
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    EEWeb
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    Jon Jon
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    Aubrey Kagan
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    David Ashton
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    Jon Jon
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    David Ashton
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    Aubrey Kagan
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    ML Components
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Topic summary

The discussion focuses on identifying a small, low-cost industrial sensor capable of real-time detection and measurement of object distances and lengths within a sensing range of 0.5 to 0.6 meters. The application involves detecting multiple similar objects (comparable to cars) positioned parallel to a reference line, with the need to measure presence (yes/no) and length along one dimension in real time, tolerating delays up to 15 seconds. Various sensing approaches were considered, including arrays of light detectors for spatial resolution, beam break sensors, reflective photoelectric sensors, ultrasonic sensors, and inductive detection. Beam break sensors with a single-sided setup (transmitter and receiver integrated in one unit) were favored for simplicity and cost-effectiveness, especially in a sideways arrangement to avoid overhead lighting issues. Reflective photoelectric sensors were recommended for one-sided detection, requiring modulation (e.g., 40 kHz IR LED) to reduce ambient light interference. Inductive loops were discussed as an alternative for metallic objects but noted for limited range and resolution. Implementing multiple sensors in a string to cover the required length with approximately 5 cm resolution was proposed, necessitating additional electronics such as 24 V DC power supplies, open-collector outputs, and microcontrollers or PLCs for signal processing. Vendors like Red Lion Controls, Automation Direct, Omega, Banner, and Vishay were mentioned as sources for photoelectric and IR emitter/receiver components. The need for software to handle sensor input, filter false signals, and calculate object length and spacing was emphasized. The user was advised to communicate application specifics clearly to vendors and consider expert consultation for system integration and programming.
Summary generated by the language model.
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