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Applications of sensors

Release Time:

2025-11-01

In the field of sensor applications for intelligent manufacturing, there are significant gaps across different industries. While process industries like petrochemicals tend to require fewer new, high-end industrial sensors, in the high-tech manufacturing sector, the localization rate of six-axis force sensors remains quite low. Moreover, for certain specialized components essential to intelligent manufacturing—such as sensors designed to withstand extreme temperatures and pressures—domestic products still fall somewhat short in terms of reliability and stability compared to their international counterparts.

For ordinary sensors, industrial environments place significantly higher demands—considering factors such as operational safety, accuracy, and stability. Compared to consumer electronics and other civilian applications, impact sensors used in smart manufacturing face even more stringent requirements in terms of precision, stability, vibration resistance, and shock tolerance. Industrial sensors are the lifeblood of a nation's industrial infrastructure. They come with far stricter performance criteria than other types of sensors, and their variety is exceptionally diverse. Functionally speaking, industrial sensors can be categorized into distinct types, including gas-sensitive, photoelectric, thermal, acoustic, humidity-sensitive, force-sensitive, and magnetic sensors, among others.

Industrial control requires ensuring zero error—sensors must not only enable real-time communication but also deliver exceptional precision. Sensors are applied across various industrial sectors, each with unique and personalized demands regarding their ability to withstand temperature, humidity, and pH levels. Additionally, power consumption and size are often subject to stringent limitations; for instance, operating in extreme environments as low as -60°C presents a significant challenge.

Latest News

How does the multi-dimensional force sensor enhance calibration efficiency?

Typically, a Design Of Experiment (DOE) is employed to generate a scientifically sound load table, while Regression Analysis (RA) is used to establish the functional relationships between dependent and independent variables. Ultimately, the calibration matrix obtained depends heavily on both the load table and the regression analysis method applied. Established force measurement laboratories usually have their own standardized procedures for acquiring and processing this data—though sometimes the individuals directly involved in calibration work may not even be fully aware of the underlying data calculation processes driving the calibration workflow.

2025-11-05

Three-Dimensional Force Sensor Calibration Data Processing Method

To simultaneously measure multi-component forces and torques, a multidimensional force sensor is required, which inevitably demands calibration before use—otherwise, the conversion from electrical signals to physical force values cannot be accurately achieved.

2025-11-05

Calibration Method for Six-Dimensional Force Sensors

Calibration of multi-component force sensors aims to establish the relationship between the signal and the applied force. The calibration process can be expressed as a quadratic polynomial. Interestingly, this representation differs slightly from what’s typically found in domestic textbooks—where we usually place the force F on the left side of the equation. From the perspective of the calibration procedure, however, this arrangement seems more logical, since it reflects applying a specific force and subsequently measuring the corresponding signal.

2025-11-05

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Nanjing Bio-inspired Intelligence Technology Co., Ltd.

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