A series of Python scripts to access measurements from Fluke 28X meters. Fluke IR Remote Interface required.

Overview

Fluke289_data_access A series of Python scripts to access measurements from Fluke 28X meters. Fluke IR Remote Interface required. Created from information provided in Fluke Remote IR documentaton cited in eevblog threads. Buy a Remote Interface from Fluke to access meter data, some come with FlukeView--a form-completion application--that is well worth the money for paid work by skilled technicians.

Getting data from an instrument display for logging can be difficult, if not impossible, without a pathway into the device via GPIB, TCPIP, or other comm port. Messing with JTAG or sniffing the signal is far beyond the capabilities of most folks interested in using the data obtained, so "Hats off" to authors of software for reading and fetching data from an operating meter during measurement. Thanks as well to manufacturers who have provided logging capabilities in their instruments and made them accessible to users. That is the modern way . . .

Some meters are far more locked-down for reasons of security and protection of the customer's perception of the integrity of the data collected. Take Fluke, for example (see Dave's video on why Fluke meters are worth the money, etc.) and the 28X series of meters like my 289. The Fluke business model is that data collection is under the control of the firmware and is presented to the user via remote access thru form-completion software. After a technician logs voltage measurements from some industrial gear over several days, there is a printout with Fluke's name on it to support the log with timestamps for every sample and a whole lot more. Yes, the data is also available for export to CSV files and from there to any analysis, but only via the gateway FormView.

Other than the obvious, why is this a problem? Well, the Fluke 289 has the ability to capture data unattended for days at a time under battery power and preserve a detailed log for later retrieval. It can do this because it sleeps between samples using precious little power and does not rely on disks or tape for storage.

Other logging meters (Uni-T 61E, for example) will output readings to a PC and MooshiMeter logs via Bluetooth, also to another device. Not even in the same league as Fluke 28X series.

What would be better would be the ability to access the Fluke 289 recorded data directly, 'read-only' of course, much in the same way as getting data from a modern Keithley or Keysight bench meter. To that end, I'm contributing to a long-standing 289 eevblog forum thread:https://www.eevblog.com/forum/reviews/going-further-with-the-fluke-289

This is not an exercise in 'reverse-engineering' or alternative firmware creation, just a little probing with Python into features documented in the Remote Interface Specification using a Fluke IR USB interface.

Generate images from texts. In Russian. In PaddlePaddle

ruDALL-E PaddlePaddle ruDALL-E in PaddlePaddle. Install: pip install rudalle_paddle==0.0.1rc1 Run with free v100 on AI Studio. Original Pytorch versi

AgentMaker 20 Oct 18, 2022
TeST: Temporal-Stable Thresholding for Semi-supervised Learning

TeST: Temporal-Stable Thresholding for Semi-supervised Learning TeST Illustration Semi-supervised learning (SSL) offers an effective method for large-

Xiong Weiyu 1 Jul 14, 2022
[ICRA 2022] An opensource framework for cooperative detection. Official implementation for OPV2V.

OpenCOOD OpenCOOD is an Open COOperative Detection framework for autonomous driving. It is also the official implementation of the ICRA 2022 paper OPV

Runsheng Xu 322 Dec 23, 2022
Patch-Based Deep Autoencoder for Point Cloud Geometry Compression

Patch-Based Deep Autoencoder for Point Cloud Geometry Compression Overview The ever-increasing 3D application makes the point cloud compression unprec

17 Dec 05, 2022
Project for music generation system based on object tracking and CGAN

Project for music generation system based on object tracking and CGAN The project was inspired by MIDINet: A Convolutional Generative Adversarial Netw

1 Nov 21, 2021
An implementation of the AlphaZero algorithm for Gomoku (also called Gobang or Five in a Row)

AlphaZero-Gomoku This is an implementation of the AlphaZero algorithm for playing the simple board game Gomoku (also called Gobang or Five in a Row) f

Junxiao Song 2.8k Dec 26, 2022
DiscoBox: Weakly Supervised Instance Segmentation and Semantic Correspondence from Box Supervision

The Official PyTorch Implementation of DiscoBox: Weakly Supervised Instance Segmentation and Semantic Correspondence from Box Supervision

Shiyi Lan 3 Oct 15, 2021
Keras implementation of the GNM model in paper ’Graph-Based Semi-Supervised Learning with Nonignorable Nonresponses‘

Graph-based joint model with Nonignorable Missingness (GNM) This is a Keras implementation of the GNM model in paper ’Graph-Based Semi-Supervised Lear

Fan Zhou 2 Apr 17, 2022
Black box hyperparameter optimization made easy.

BBopt BBopt aims to provide the easiest hyperparameter optimization you'll ever do. Think of BBopt like Keras (back when Theano was still a thing) for

Evan Hubinger 70 Nov 03, 2022
PolyphonicFormer: Unified Query Learning for Depth-aware Video Panoptic Segmentation

PolyphonicFormer: Unified Query Learning for Depth-aware Video Panoptic Segmentation Winner method of the ICCV-2021 SemKITTI-DVPS Challenge. [arxiv] [

Yuan Haobo 38 Jan 03, 2023
EmoTag helps you train emotion detection model for Chinese audios

emoTag emoTag helps you train emotion detection model for Chinese audios. Environment pip install -r requirement.txt Data We used Emotional Speech Dat

_zza 4 Sep 07, 2022
Syntax-Aware Action Targeting for Video Captioning

Syntax-Aware Action Targeting for Video Captioning Code for SAAT from "Syntax-Aware Action Targeting for Video Captioning" (Accepted to CVPR 2020). Th

59 Oct 13, 2022
RoBERTa Marathi Language model trained from scratch during huggingface 🤗 x flax community week

RoBERTa base model for Marathi Language (मराठी भाषा) Pretrained model on Marathi language using a masked language modeling (MLM) objective. RoBERTa wa

Nipun Sadvilkar 23 Oct 19, 2022
One Million Scenes for Autonomous Driving

ONCE Benchmark This is a reproduced benchmark for 3D object detection on the ONCE (One Million Scenes) dataset. The code is mainly based on OpenPCDet.

148 Dec 28, 2022
Permeability Prediction Via Multi Scale 3D CNN

Permeability-Prediction-Via-Multi-Scale-3D-CNN Data: The raw CT rock cores are obtained from the Imperial Colloge portal. The CT rock cores are sub-sa

Mohamed Elmorsy 2 Jul 06, 2022
Official implementation of the paper Label-Efficient Semantic Segmentation with Diffusion Models

Label-Efficient Semantic Segmentation with Diffusion Models Official implementation of the paper Label-Efficient Semantic Segmentation with Diffusion

Yandex Research 355 Jan 06, 2023
Code for the paper “The Peril of Popular Deep Learning Uncertainty Estimation Methods”

Uncertainty Estimation Methods Code for the paper “The Peril of Popular Deep Learning Uncertainty Estimation Methods” Reference If you use this code,

EPFL Machine Learning and Optimization Laboratory 4 Apr 05, 2022
This is a classifier which basically predicts whether there is a gun law in a state or not, depending on various things like murder rates etc.

Gun-Laws-Classifier This is a classifier which basically predicts whether there is a gun law in a state or not, depending on various things like murde

Awais Saleem 1 Jan 20, 2022
This repository contains small projects related to Neural Networks and Deep Learning in general.

ILearnDeepLearning.py Description People say that nothing develops and teaches you like getting your hands dirty. This repository contains small proje

Piotr Skalski 1.2k Dec 22, 2022
This is a Tensorflow implementation of Learning to See in the Dark in CVPR 2018

Learning-to-See-in-the-Dark This is a Tensorflow implementation of Learning to See in the Dark in CVPR 2018, by Chen Chen, Qifeng Chen, Jia Xu, and Vl

5.3k Jan 01, 2023