The meter automatically performs vibration analysis functions based on machine running speed to help diagnose faults such as unbalance, misalignment and looseness, as well as indicating the degree of bearing wear.
The Vib Meter 9085 unit is designed to enable a user to collect vibration and temperature measurements from assets (e.g. pumps, motors, fans and bearings). The unit displays vibration frequency plots and allows vibration severity and bearing condition to be monitored, analyzed and trended with the included C-Trend II PC analysis software.
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In brief, C-Trend II allows display of vibration data in a variety of different ways including vibration frequency spectra, bearing noise and ISO trend plots, waterfall diagrams (see figure below) and can generate reports either manually or automatically (e.g. by sending out email alerts).
Re the climb to 250m, it is caused by the EKF becoming confused because of high vibration levels. the Z-axis is about 40m/s/s which is in the grey zone (which stretches from 30m/s/s to 60m/s/s) which means that altitude control will sometimes work but sometimes it will have problems.
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We are discussing more ways to improve resistance to vibrations and I expect we will add a vibration failsafe to 3.7.0. The underlying cause though should still be fixed so please check this page re vibration isolation hardware.
The requirement for the MHD linear vibration sensors in aerospace technology to have amplitudes within millivolts and vibration frequencies within kilohertz, coupled with the complex external environment [1], makes signal acquisition and extraction separation difficult. Therefore, the extraction and separation of weak signals output from the MHD linear vibration sensors is one of the key techniques used to perform micro-vibration measurements [3].
In order to separate independent source signals from mixed signals with a low SNR, this paper proposes a method of MHD linear vibration signal separation based on SSA and FastICA. In this paper, SSA was first used to suppress the periodic narrowband interference and white noise in an acquired signal, and a noise-reduced mixed acceleration signal was obtained. Then, the noise-reduced signal was separated by a modified, fast, independent component analysis to obtain an unmixed signal. The unmixed signal was analyzed and identified to determine the useful and noisy components of the acquired magnetohydrodynamic sensor signal. Experimental analysis shows that this method can achieve the effective separation of independent line vibration signals with reasonable suppression of linear vibration signal admixture noise.
The collected linear vibration signal is a mixed signal containing multiple noise signals. The signal-to-noise ratio of such mixed signals is low, and the effect of using ICA directly is not good; thus, the mixed signals need to be denoised first. In this paper, a single-channel line vibration signal separation method based on SSA-FastICA is proposed. Firstly, the output signal of the MHD linear vibration sensor is collected, and the collected signal is a noise-laden mixed signal. Then, the SSA method is preliminarily used to denoise the acquired signal with noise. Finally, FastICA is used to separate the collected signal after denoising, and the unmixed signal was obtained. The separation process of mixed signals based on SSA and FastICA is shown in Figure 4.
(2) The collected MHD linear vibration signal is processed by SSA, the contribution rate of the eigenvalues of each order component is calculated, and according to the contribution rate of the eigenvalues, the useful signals and noise signals are determined from the components.
The experimental wiring diagram is shown in Figure 6. An MHD linear vibration sensor and quartz flexible accelerometer were placed on the vibration table, and the acquisition card was connected. Finally, the acquired line vibration signal is displayed through the upper computer. Before the experiment, the sensor was fixed with a fixture to prevent position deviation caused by the vibration of the shaking table and affecting the accuracy of the sensor output signal.
where si(t) represents the source signal, where denoised linear vibration signal is substituted, and Xi(t) indicates the collected signals. When the SNR after noise reduction is higher, the separation effect is greater. The SNR analysis of these four groups of useful linear vibration signals was carried out, as shown in Table 2.
The four groups of signals with the highest similarity coefficients among the decomposed signals are found, as shown in Table 4. These four groups of signals are the line vibration signals obtained by processing the four groups of collected signals by the SSA-FastICA algorithm. It is observed that the output signals of the quartz flexible accelerometer are essentially the same as the decomposed linear vibration signals waveform, as shown in Figure 8. In contrast, in the quartz flexible acceleration sensor and our experimental test sensor, the output voltage signals amplitudes are different. Therefore, it is more appropriate to measure the output signal of the MHD linear vibration sensor and quartz flexible accelerometer by signal similarity. The similarity of the output signals is more than 98%. It can be seen that the single-channel linear vibration signal blind source separation method based on SSA-FastICA can effectively extract standard linear vibration signals. In order to test the repeatability of the sensor, multiple sets of data of the MHD linear vibration sensors at different times on different dates are collected. The formula for the standard error (SE) [31] is shown below:
We offer over 800 pre-configured standard test programs in which all relevant parameters have already been set. This guarantees 100% standard-compliant testing and saves time. All you have to do is enter the specimen dimensions.
The Class of a noise level meter describes its accuracy as defined by the relevant international standards. Sound level meters are defined by International Standards such as IEC 61672-1:2013 (or BS EN61672-1:2003). These standards define a wide range of complex accuracy, performance and calibration criteria that instruments must meet to be fit for purpose. Within the Standard, there are two allowable levels of tolerance and these are known as Class 1 and Class 2. Class 1 is more accurate than Class 2.
These Class 1 and Class 2 tolerances are necessary as a way of dealing with variations in the instruments. The variations are caused by the different electronic components used inside the sound level meters and because of the way different meters have been designed and verified. Even the test equipment used to check the sound level meters during manufacture will introduce some variation.
At lower and upper extremities of the sound frequency range* tolerances are wider, and at higher frequencies, the tolerances are narrower. At the outer extremes of the frequency range, you can expect Class 1 meters to have narrower tolerances and therefore a more accurate response.
Class 1 sound level meters need to measure sound over a wider frequency than Class 2 meters and meet narrower tolerances for all performance criteria. Class 1 is therefore seen as being more accurate than Class 2. So we can say a Class 2 meter has wider tolerances and is therefore slightly less accurate, but for most applications, the difference is not noticeable and as Class 2 sound level meters are a lower-cost compared to Class 1, for most users a Class 2 meter still meets the standard, is accurate enough and is fit for purpose.
Which meter you need will depend on what you want to use the meter for (i.e. what noise you want to measure), what measurement regulations you need to meet, and whether your measurements will be used as legal evidence (e.g. if you want your measurements submitted as legal evidence then you may prefer to use a Class 1 meter for increased accuracy). The Pulsar Nova range of noise level meters has both Class 1 and Class 2 and each offers a range of features depending on what you want to measure.
Klipper has built-in support for the ADXL345, MPU-9250 and LIS2DW compatibleaccelerometers which can be used to measure resonance frequencies of the printerfor different axes, and auto-tune input shapers tocompensate for resonances. Note that using accelerometers requires somesoldering and crimping. The ADXL345/LIS2DW can be connected to the SPI interfaceof a Raspberry Pi or MCU board (it needs to be reasonably fast). The MPU family canbe connected to the I2C interface of a Raspberry Pi directly, or to an I2Cinterface of an MCU board that supports 400kbit/s fast mode in Klipper.
When sourcing accelerometers, be aware that there are a variety of different PCBboard designs and different clones of them. If it is going to be connected to a5V printer MCU ensure it has a voltage regulator and level shifters.
You may connect the ADXL345 to your Raspberry Pi Pico and then connect thePico to your Raspberry Pi via USB. This makes it easy to reuse theaccelerometer on other Klipper devices, as you can connect via USB insteadof GPIO. The Pico does not have much processing power, so make sure it isonly running the accelerometer and not performing any other duties.
These accelerometers have been tested to work over I2C on the RPi, RP2040 (Pico)and AVR at 400kbit/s (fast mode). Some MPU accelerometer modules includepull-ups, but some are too large at 10K and must be changed or supplemented bysmaller parallel resistors.
The accelerometer must be attached to the toolhead. One needs to design a propermount that fits their own 3D printer. It is better to align the axes of theaccelerometer with the printer's axes (but if it makes it more convenient,axes can be swapped - i.e. no need to align X axis with X and so forth - itshould be fine even if Z axis of accelerometer is X axis of the printer, etc.).
Attention: make sure the accelerometer and any screws that hold it inplace do not touch any metal parts of the printer. Basically, the mount mustbe designed such as to ensure the electrical isolation of the accelerometerfrom the printer frame. Failing to ensure that can create a ground loop inthe system that may damage the electronics. be457b7860