Dark output characteristic of γ-ray irradiated CMOS digital image sensors

The quality of dark output images from the CMOS (complementarymetal oxide semiconductor) black and white (B & W) digital imagesensors captured before and after γ-ray irradiation was studied. Thecharacteristic parameters of the dark output images captured atdifferent radiation dose, e.g. average brightness and itsnon-uniformity of dark out- put images, were analyzed by our testsoftware. The primary explanation for the change of the parameterswith the radi- ation dose was given.

320×240 Pixels CMOS Digital Image Sensor with Wide Dynamic Range

A 320×240 CMOS image sensor is demonstrated,which is implemented by a standard 0.6 μm 2P2M CMOS process.For reducing the chip area,each 2×2-pixel block shares a sample/hold circuit,analog-to-digital converter and 1-b memory.The 2×2 pixel pitch has an area of 40 μm×40 μm and the fill factor is about 16%.While operating at a low frame rate,the sensor dissipates a very low power by power-management circuit making pixel-level comparators in an idle state.A digital correlated double sampling,which eliminates fixed pattern noise,improves SNR of the sensor, and multiple sampling operations make the sensor have a wide dynamic range.

Fault Pattern Diagnosis and Classification in Sensor Nodes Using Fall Curve

The rapid expansion of Internet of Things(IoT)devices deploys various sensors in different applications like homes,cities and offices.IoT applications depend upon the accuracy of sensor data.So,it is necessary to predict faults in the sensor and isolate their cause.A novel primitive technique named fall curve is presented in this paper which characterizes sensor faults.This technique identifies the faulty sensor and determines the correct working of the sensor.Different sources of sensor faults are explained in detail whereas various faults that occurred in sensor nodes available in IoT devices are also presented in tabular form.Fault prediction in digital and analog sensors along with methods of sensor fault prediction are described.There are several advantages and disadvantages of sensor fault prediction methods and the fall curve technique.So,some solutions are provided to overcome the limitations of the fall curve technique.In this paper,a bibliometric analysis is carried out to visually analyze 63 papers fetched from the Scopus database for the past five years.Its novelty is to predict a fault before its occurrence by looking at the fall curve.The sensing of current flow in devices is important to prevent a major loss.So,the fall curves of ACS712 current sensors configured on different devices are drawn for predicting faulty or non-faulty devices.The analysis result proved that if any of the current sensors gets faulty,then the fall curve will differ and the value will immediately drop to zero.Various evaluation metrics for fault prediction are also described in this paper.At last,this paper also addresses some possible open research issues which are important to deal with false IoT sensor data.

Noise in a CMOS digital pixel sensor

Based on the study of noise performance in CMOS digital pixel sensor （DPS）, a mathematical model of noise is established with the pulse-width-modulation （PWM） principle. Compared with traditional CMOS image sensors, the integration time is different and A/D conversion is implemented in each PWM DPS pixel. Then, the quantitative calculating formula of system noise is derived. It is found that dark current shot noise is the dominant noise source in low light region while photodiode shot noise becomes significantly important in the bright region. In this model, photodiode shot noise does not vary with luminance, but dark current shot noise does. According to increasing photodiode capacitance and the comparator＇s reference voltage or optimizing the mismatch in the comparator, the total noise can be reduced. These results serve as a guideline for the design of PWM DPS.

Apple Grading System Based on Weight and Colour

This paper involves the systematic,integrated and unified design of an automatic apple grading system.Apples are placed on a constant-speed conveyor system and graded based on 2 parameters:weight and colour.For weight detection,a piezo-resistive load cell(ELAF-T1-M-10 L)is used.For colour detection,an RGB colour sensor(46 CLR-D5 LAC3-D5)is used.If the apples are equal to or above a pre-set weight threshold of 0.08 kg and if the colour of the apple is red,green or yellow,they are graded in to three bins(bin 1:red apples,bin 2:green apples,bin 3:yellow apples).If the weight is below the threshold and/or if the colour of the apple is not red,green or yellow,they are sent to a reject bin.Both weight and colour requirements have to be met to be successfully graded,otherwise the apple is rejected.Electric linear actuators(PA-15),actuated by combined signals from load cell,colour sensor and photoelectric sensors(OBR2000-R2)positioned very close to the actuators,are used to eject the apples to the correct bins.A digital magnetic speed sensor(DIGISPEC 0090/0091)is used to monitor the speed of the motor and maintain the required constant conveyor speed.Food grade conveyor belt(NS20 UFMT)is used to design the conveyor and direct drive DC motor(DMS07 G)is used to move the conveyor belt.In this paper,the functionality,operation,important parameters and justifications for choosing individual components have been provided as well as detailed explanations of the overall system operation,along with potential drawbacks of proposed system.Relevant calculations necessary for system design are also provided.

CMOS vision sensor with fully digital image process integrated into low power 1/8-inch chip

A digital still camera image processing system on a chip, different from the video camera system, is pre- sented for mobile phone to reduce the power consumption and size. A new color interpolation algorithm is proposed to enhance the image quality. The system can also process fixed patten noise （FPN） reduction, color correction, gamma correction, RGB/YUV space transfer, etc. The chip is controlled by sensor regis- ters by inter-integrated circuit （I2C） interface. The voltage for both the front-end analog and the pad cir- cuits is 2.8 V, and the volatge for the image signal processing is 1.8 V. The chip running under the external 13.5-MHz clock has a video data rate of 30 frames/s and the measured power dissipation is about 75 roW.

Problems Related to Excitation Winding Surface Temperature Measurement of a Salient Pole Synchronous Generator in Rotation

This paper addresses some of the problems related to direct surface temperature measurement of a salient pole synchronous generator excitation winding in rotation. Excitation winding temperature is used for determining the dynamic limit in a PQ diagram. The paper also addresses procedures of improving the accuracy of surface temperature measurement using the contact DS 18B20 digital temperature probes. The paper also provides experimental results of direct temperature measurement of the excitation winding surface conducted in the salient pole synchronous generator in the rotation.

Smart Image Sensor with Integrated Low Complexity Image Processing for Wireless Endoscope Capsules

A smart image sensor was developed which integrates a digital pixel image sensor array with an image processor, designed for wireless endoscope capsules. The camera-on-a-chip architecture and its on-chip functionality facilitate the design of the packaging and power consumption of the integrated capsule. The power reduction techniques were carried out at both the architectural and circuit level. Gray coding and power gating in the sensor array to eliminate almost 50% of the switch activity on the data bus and more than 99% of the power dissipation in each pixel at a transmitting rate of 2 frames per second. Filtering and compression in the processor reduces the data transmission by more than 2/3. A parallel fully pipelined architecture with a dedicated clock management scheme was implemented in the JPEG-LS engine to reduce the power consumption by 15.7%. The smart sensor has been implemented in 0.18 μm CMOS technology.