When producing bolts in a cold forging process, the pressure signals are recorded per cycle of forming a bolt. The dataset is collected from experiments of different failure modes of a forming machine. Two experiments were recorded in csv format for providing four failure modes, including core broken, cavity block, insufficient lubrication, and material out-of-specification, as well as one normal mode. The two experiments were performed in the same machine with different cavities and cores, and saved in Experimental Data for Modeling and Testing.

Instructions: 
  • Domain: cold bolt forging process
  • source: pressure sensor
  • Sampling rate: 1000 Hz
  • Target: failure classification
  • Failure modes:
    • 1. Normal: normal production.
    • 2. Cavity Block: a cavity was blocked with different heights of bumps.
    • 3. Core Broken: a core being broken into three levels
    • 4. Insufficient Lubrication: insufficient lubrication in two levels.
    • 5. Material out-of-specification: the materials being shorter or longer.
  • Total files: 2 
  • File format: csv
  • Description of fields in each file
    • TimeTag: experimental recording time of each producing cycle.
    • Label: faliure mode
    • Rawdata1-Rawdata386: pressure data collected by each bolt forming in a sampling rate 1000 Hz. 1-386 means it takes 0.386 sec to finish a bolt forming cycle, and their values stand for the raw data without standardization.
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The pressure sensors are represented by black circles, which are located in the three zones of each foot. For the left foot: S1 and S2 cover the forefoot area. S3, S4, and S5 the midfoot area. S6 and S7 the rearfoot or heel area. Similarly, for the right foot: S8 and S9 represent the forefoot area. S10, S11, S12 the midfoot area. S13 and S14 the heel area. The values of each sensor are read by the analog inputs of an Arduino mega 2560.

Instructions: 

Each label correspond to:

Label         Position                                             Pressure on sensors

1                normal footstep                                Left foot: S1, S2, S3, S4, S6, S7

                                                                           Right foot: S8, S9, S11, S12, S13, S14

 

 2                flat footstep                                     Left foot: S1, S2, S3, S4, S5, S6, S7

                                                                           Right foot: S8, S9, S10, S11, S12, S13, S14

 

 3                cavus footstep                                 Left foot: S1, S2, S3, S6, S7

                                                                           Right foot: S8, S9, S12, S13, S14

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Our research addresses time-dependent hysteresis effects in adhesive packaged MEMS pressure sensors.Typically calibrated inside a certain temperature and pressure range, they provide precise pressure measurements, giventhat certain setting times after temperature changes are maintained. Signal errors arise when temperature changesinduce time-dependent viscoelastic relaxation in the adhesive which cannot be compensated by calibration.

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