CN-122015946-A - Composite triaxial vibration temperature sensor based on direct current carrier bus

CN122015946ACN 122015946 ACN122015946 ACN 122015946ACN-122015946-A

Abstract

The invention discloses a composite triaxial vibration temperature sensor based on a direct current carrier bus, and relates to the technical field of industrial equipment state monitoring; the sensor comprises a vibration temperature body, a data acquisition and processing board, a power supply and communication interface board and an external connector; the data acquisition and processing board and the power supply and communication interface board comprise a sensing unit, a signal conditioning unit, a central processing and storage unit and a direct current carrier bus interface unit; the invention adopts a two-wire system direct current carrier bus technology, realizes power supply and data communication simultaneously through the same pair of cables, and also adopts a single-chip microcontroller integrated with a large-capacity SRAM (static random Access memory), intelligent processing such as multichannel synchronous data acquisition, temperature compensation, time-frequency domain analysis, envelope analysis and the like is independently completed at the edge end, and refined characteristic data is uploaded through the direct current carrier bus; the invention realizes the equipment state monitoring with high precision, high reliability and low cost, and has excellent industrial applicability and environmental adaptability.

Inventors

HE WEITING
LI ZHIHAO
Yuan Jingyuan
TANG JINGYUAN

Assignees

浙江大学

Dates

Publication Date: 20260512
Application Date: 20260107

Claims (10)

1. A composite triaxial vibration temperature sensor based on a direct current carrier bus, comprising: the vibration temperature body (1) is made of metal materials, is arranged at the bottom of the sensor, and is provided with mounting threads at the lower part for fixing with equipment to be tested; The system comprises a sensor vibration temperature body (1), a data acquisition and processing board (2) and a power supply and communication interface board (3), wherein the sensor vibration temperature body is arranged in an upper cavity of the sensor vibration temperature body, the data acquisition and processing board (2) comprises a sensing unit, a signal conditioning unit and a central processing and storage unit, the power supply and communication interface board (3) is provided with a direct current carrier bus interface unit, the central processing and storage unit is a microcontroller and is used for controlling the sensing unit to acquire sensor signals and filter and amplify the sensor signals by the signal conditioning unit, and the direct current carrier bus interface unit is used for connecting a two-wire system direct current carrier bus, acquiring electric energy from the bus and carrying out bidirectional data communication; and the external connector (4) is arranged at the topmost end of the sensor, is connected with the direct current carrier bus interface unit and is used for connecting a two-wire system direct current carrier bus for realizing power supply and communication functions.
2. The sensor according to claim 1, wherein the sensing unit comprises: The Z-axis piezoelectric sensing element adopts a piezoelectric ceramic accelerometer and is used for collecting high-frequency impact vibration signals; the XY axis sensing element adopts a micro-electromechanical system accelerometer integrating an X axis and a Y axis and is used for collecting low-frequency vibration and static inclination angle signals; The temperature sensing element adopts a digital temperature sensor, is arranged near a metal base of the sensor and is used for collecting the surface temperature of equipment.
3. The sensor of claim 1, wherein the signal conditioning unit comprises an X/Y axis signal conditioning path and a Z axis signal conditioning path, the X/Y axis signal conditioning path receiving signals output by the MEMS sensing element and performing filtering and gain adjustment, the Z axis signal conditioning path being configured to condition signals output by the piezoelectric element.
4. The sensor of claim 1, wherein the microcontroller of the central processing and storage unit is integrated with a floating point arithmetic unit, a DSP instruction set, a high-precision analog-to-digital converter, a UART interface, a single bus interface and an on-chip SRAM, and the central processing unit opens up a data buffer area through the on-chip SRAM for buffering vibration original data synchronously acquired by multiple channels and finishing signal preprocessing, feature extraction and frequency domain analysis locally without a plug-in memory chip.
5. The sensor of claim 1, wherein the dc carrier bus interface unit comprises: the bus physical interface realizes nonpolar connection and is provided with a fuse and a TVS diode to respectively realize overcurrent protection and surge protection multistage power supply processing subunits; the communication modulation demodulation subunit is in signal coupling with the direct current bus through the two-wire system carrier communication chip; The multi-stage power supply processing subunit comprises a first-stage voltage reduction circuit and a second-stage voltage stabilizing circuit, wherein the first-stage voltage reduction circuit is used for converting direct current voltage input by a bus into intermediate voltage by adopting a DC-DC voltage reduction converter, and the second-stage voltage stabilizing circuit comprises at least two independent low-voltage difference linear voltage stabilizers for respectively generating a digital power supply and an analog power supply so as to realize the isolation of the analog power supply and the digital power supply.
6. A control method of the composite triaxial vibration temperature sensor based on the direct current carrier bus according to claim 1, including the steps of: The method comprises the steps of initializing a system, configuring an analog-to-digital converter, a hardware timer, a UART communication interface and a single bus interface after the system is powered on, and reading user configuration parameters from an internal memory; the second step, multichannel synchronous data acquisition, which is to synchronously acquire triaxial vibration analog signals based on signals output by a hardware timer, store the triaxial vibration analog signals in an SRAM buffer after analog-to-digital conversion, and simultaneously read temperature values through a single bus interface; step three, preprocessing and compensating in-situ data, performing temperature compensation on vibration original data by using a current temperature value, and windowing the compensated data; step four, edge intelligent calculation and feature extraction, carrying out layered feature extraction on the edge side, wherein the step four comprises the following steps: Aiming at X, Y, Z triaxial vibration data, respectively calculating time domain characteristics including mean value, effective value, peak-to-peak value and kurtosis, performing fast Fourier transform on Z-axis vibration data, extracting main frequency, main frequency amplitude and double frequency amplitude; And fifthly, packaging the extracted characteristic values into data frames according to a preset protocol, sending the data frames to the upper computer through a direct current carrier bus, and responding to remote configuration and query instructions of the upper computer.
7. The method according to claim 6, wherein the temperature compensation in the third step is used for performing in-situ numerical correction on the triaxial vibration data in the buffer area by using a preset calibration function according to the temperature values synchronously acquired by the temperature sensing elements after the data acquisition is completed, so as to eliminate temperature drift errors.
8. The method of claim 6, wherein the mean value calculation formula in the fourth step is: wherein N represents the total number of sampling points and N represents a discrete time index; the effective value calculation formula is as follows: wherein N represents the total number of sampling points and N represents a discrete time index; the peak-to-peak value calculation formula is as follows: the kurtosis calculation formula is as follows: wherein N represents the number of waveform points, and mu represents the average value; The fast Fourier transform calculation formula is as follows: wherein N represents the number of waveform points, Represents imaginary units; the main frequency and main frequency peak value calculation formula is as follows: wherein N represents the number of waveform points, Representing the sampling frequency of the sample, Representing the spectrum index corresponding to the main frequency peak; the double frequency amplitude calculation formula is as follows: wherein N represents the number of waveform points, Indicating the frequency of the reference of the device, Representing the sampling frequency; The calculation formulas of the envelope effective value and the envelope peak value are as follows: Wherein, the Representing the original time-domain signal, A variable of the time is represented and, The integral variable is represented by a value of the integral variable, Represents the complex number of the resolved signal, Representing the signal after hilbert transformation, The representation of the hilbert transform is given, Representing imaginary units Representing the envelope signal.
9. The method of claim 6, wherein the envelope analysis in the fourth step comprises performing digital bandpass filtering on the Z-axis vibration data to obtain a high-frequency signal, calculating an absolute value of the high-frequency signal, extracting an envelope signal through low-pass filtering, and calculating an effective value and a peak value of the envelope signal.
10. The method of claim 6, wherein the data frame in step five comprises a synchronization and addressing field, an instruction and function field, a data payload field, and a data integrity check field.

Description

Composite triaxial vibration temperature sensor based on direct current carrier bus Technical Field The invention belongs to the technical field of industrial automation, equipment state monitoring and predictive maintenance, and particularly relates to a composite triaxial vibration temperature sensor based on a direct current carrier bus. Background In a modern industrial production system, rotary mechanical equipment such as a motor, a pump, a fan, a gear box and the like is a core for guaranteeing continuous and stable operation of a production line. Unplanned shutdowns of these critical equipment will result in significant economic losses and potential safety risks, which make predictive maintenance (PREDICTIVE MAINTENANCE, PDM) a key technique to ensure reliable operation of the equipment, gradually replacing traditional "regular maintenance" or "post-failure maintenance" modes. The technical core of predictive maintenance is to continuously collect physical parameters reflecting the health of the equipment in real time or periodically by a state monitoring system (Condition Monitoring System, CMS), and to perform trend analysis and fault diagnosis based on these parameters. The vibration and the temperature are recognized as two most direct and effective key indexes, namely different fault types usually show specific frequency characteristics in the frequency spectrum of vibration signals, and various mechanical faults of equipment such as rotor unbalance, shafting misalignment, bearing abrasion, gear tooth breakage, foundation looseness and the like can be revealed, so that accurate and broadband measurement and analysis of the vibration signals are the basis for early fault diagnosis, and temperature change is usually closely related to equipment load, lubrication state and friction state, and abnormal temperature rise is often a direct sign of equipment overload, lubrication failure or fault aggravation. Therefore, the development of the vibration temperature sensor with high precision, high reliability and easy deployment is important to the construction of an efficient and intelligent industrial equipment state monitoring system. Currently, a mainstream technical solution widely applied in industrial fields is a system architecture of "split sensor+multi-cable+centralized Data Acquisition (DAQ)". A typical implementation scheme is that a plurality of separation sensors are installed in parallel at key measuring points (such as a bearing seat of a high-speed rotating shaft) needing broadband monitoring to cover full-frequency band detection requirements, for example, a triaxial MEMS acceleration sensor is installed for measuring low-medium-frequency vibration and static inclination angles of the whole equipment, meanwhile, a single-axis high-frequency piezoelectric (IEPE/PZT) acceleration sensor is additionally installed for specially capturing high-frequency impact signals generated by early faults of parts such as a bearing, a gear and the like, and an independent temperature sensor such as a Pt100 thermal resistor or a K-type thermocouple is installed nearby the same position for monitoring the temperature of the equipment. Each sensor needs independent special cables to be led out from the measuring points of the equipment and connected into the field control cabinet or the relay box through the wire slots or the bridge frames. A multichannel data acquisition card (DAQ) is installed in a control cabinet, the acquisition card is required to be provided with input modules matched with different sensor types, such as a voltage input module for receiving MEMS signals, an IEPE input module with a built-in constant current source and a temperature acquisition module for a thermal resistor/thermocouple, and the acquisition card is used for digitally converting original and analog waveform signals transmitted by all sensors and then uploading massive original data packets to an upper computer, a PLC or a cloud server in a mode of an industrial Ethernet (such as Modbus-TCP, OPC UA) and the like. And finally, carrying out FFT spectrum analysis, eigenvalue extraction and fault diagnosis operation on the received mass data by special analysis software of the server side. Although the above prior art solutions enable to some extent the condition monitoring of the device, their inherent architectural and technical limitations have the following significant drawbacks: (1) The traditional industrial sensor is commonly connected by multiple wires, namely, each measuring point needs to be provided with a plurality of sensors, each sensor needs a plurality of independent multi-core cables, so that the on-site wiring is complicated, the workload is huge, the comprehensive cost of cables, bridges, manpower and the like is very high, the probability of system faults is greatly increased by a plurality of wiring points, and in addition, when monitoring points are needed to be increased in the later period, the syst