CN112924046B - Ring main unit cable terminal joint heating fault on-line monitoring system and method - Google Patents

Abstract

The invention provides an on-line monitoring system for heating faults of a cable terminal joint of a ring main unit, which structurally comprises a temperature sensor, a state monitoring front end, a cloud server and a client terminal; the temperature sensor is connected with the state monitoring front end, the state monitoring front end is in butt joint with the cloud server, and the cloud server is in butt joint with the client terminal. The method for on-line monitoring by using the on-line monitoring system comprises the following steps: monitoring a temperature signal at a joint of a three-phase cable terminal through a temperature sensor; secondly, the temperature sensor transmits the monitored temperature signal to the state monitoring front end; thirdly, the state monitoring front end sends monitoring data to the cloud server according to a set communication period; fourthly, the cloud server sends real-time monitoring data and abnormal fault identification results of the cable terminal connectors of each phase to the client terminal; fifthly, the user inquires historical data through the client terminal and the abnormal phase identification result of each phase of cable terminal connector of the ring main unit.

Description

An online monitoring system and method for heating fault of ring main unit cable terminal joint

Technical field

The invention relates to an online monitoring system and method for heating faults of ring network cabinet cable terminal joints, and belongs to the fields of single-chip microcomputer technology and power equipment online monitoring and fault diagnosis.

Background technique

With the continuous deepening of urban power grid construction and transformation projects, the use of ring main units in power grid transformation projects is also increasing. However, the ring main unit covers are closed when they are in operation. In addition, their large number and various installation locations make it difficult to inspect. Inspections have brought great difficulties to the corresponding operation and maintenance work; in recent years, due to untimely inspections and the lack of scientific and effective online monitoring methods, many power grid incidents have occurred in Jiangsu, Zhejiang, Anhui and other provinces and cities. Accidents such as phase-to-phase short circuit and single-phase grounding caused by the deterioration and ablation of the T-type cable terminal joint of the ring main unit have adverse effects on the safe and stable operation of the power system.

The space of the ring main unit is small, which is not conducive to heat dissipation. The construction process of the cable terminal joints is complicated and the quality is difficult to guarantee, which has caused the following objective problems: 1. After long-term operation in a strong electric field and weak convection environment, the internal thermal expansion and contraction of the joints, Surface scaling, oxidation or corrosion will lead to loose contacts, poor contact, and heating, aggravating the deterioration rate of the cable terminal insulation layer, posing a major safety hazard; 2. Due to production and installation problems, some ring main unit cable joints themselves have Certain defects lead to excessive contact resistance and bending stress. Under the effects of long-term thermal aging and mechanical aging, the root of the T-type cable terminal joint is seriously heated, loosened and cracked, posing a major safety hazard; 3. Currently, in the operation inspection work, the Partial discharge detection, infrared detection and other methods are very limited because there are a large number of ring main units and most of the lids are closed.

The operating status of power equipment can be effectively identified through online monitoring methods, and the occurrence and development of degradation faults can be predicted and prevented in a timely manner; research results show that the degradation and ablation of T-type cable terminal joints in ring main units is mostly caused by abnormal heating of the metal flange, so it can Deterioration is reflected by monitoring the temperature.

Contents of the invention

The present invention proposes an online monitoring system and method for heating faults of ring main unit cable terminal joints, which aims to solve the problem that the existing technology cannot perform online monitoring of heating faults of ring main unit cable terminal joints.

The technical solution of the present invention: an online monitoring system for heating faults of cable terminal joints of ring network cabinets. Its structure includes a temperature sensor, a status monitoring front end, a cloud server, and a client terminal; the temperature sensor is connected to the status monitoring front end, and the status monitoring front end Connect with the cloud server, and connect the cloud server with the client terminal.

An online monitoring method for heating faults of ring main unit cable terminal joints, which method includes the following steps:

(1) Install the temperature sensor at the three-phase cable terminal joint in the cable room of the ring main unit, and monitor the temperature signal at the three-phase cable terminal joint through the temperature sensor;

(2) The temperature sensor is connected to the status monitoring front end, and the temperature sensor transmits the monitored temperature signal to the status monitoring front end;

(3) The status monitoring front-end amplifies and filters the temperature signal to form monitoring data, and sends the monitoring data to the cloud server according to the set communication cycle;

(4) The cloud server stores the monitoring data, and at the same time performs data preprocessing, algorithm analysis, and identification of abnormal fault phases; the cloud server sends real-time monitoring data to the client terminal, as well as the abnormal fault identification results of each phase cable terminal joint;

(5) Users can query historical data and abnormal phase identification results of each phase cable terminal joint of the ring main unit through the customer terminal to obtain the heating fault situation.

Beneficial effects of the present invention:

The present invention uses non-contact real-time monitoring of the temperature signal at the characteristic position of the ring main unit cable room, thereby accurately judging whether there is an obvious abnormal fault in the three-phase cable terminal joint, so as to obtain the operating status of the cable terminal joint in time and promptly troubleshoot the deterioration fault. Purpose: The present invention provides an online monitoring system and method for heating faults of ring main unit cable terminal joints, which can not only make up for the shortcomings of existing detection means, fill the gaps in the online monitoring technology of ring main unit cable terminal joints, and further ensure the power distribution within the jurisdiction. The safe and stable operation of the network.

Description of the drawings

Figure 1 is a working principle diagram of the present invention.

Figure 2 is a working principle diagram of the temperature sensor and status monitoring front-end.

Figure 3 is a workflow diagram of the cloud server.

Figure 4 is a flow chart of abnormal phase identification and weight calculation.

Detailed ways

An online monitoring system for ring main unit cable terminal connector heating faults. Its structure includes a temperature sensor, a status monitoring front end, a cloud server, and a client terminal; the temperature sensor is connected to the status monitoring front end, and the status monitoring front end is connected to the cloud server. The cloud server Connect with client terminal.

An online monitoring method for heating faults of ring main unit cable terminal joints, which method includes the following steps:

(1) Install the temperature sensor at the three-phase cable terminal joint in the cable room of the ring main unit, and monitor the temperature signal at the three-phase cable terminal joint through the temperature sensor;

(2) The temperature sensor is connected to the status monitoring front end, and the temperature sensor transmits the monitored temperature signal to the status monitoring front end;

(3) The status monitoring front-end amplifies and filters the temperature signal to form monitoring data, and sends the monitoring data to the cloud server according to the set communication cycle;

(4) The cloud server stores the monitoring data, and at the same time performs data preprocessing, algorithm analysis, and identification of abnormal fault phases; the cloud server sends real-time monitoring data to the client terminal, as well as the abnormal fault identification results of each phase cable terminal joint;

(5) Users can query historical data and abnormal phase identification results of each phase cable terminal joint of the ring main unit through the customer terminal to obtain the heating fault situation.

The temperature sensor is installed at the three-phase cable terminal joint flange in the cable room of the ring main unit.

As shown in Figure 2, the temperature sensors include three groups of temperature sensors A, B, and C. Group A temperature sensors, group B temperature sensors, and group C temperature sensors are respectively fixed on the A, B, and C three-phase cable terminal joints. On the blue surface, group A temperature sensors, group B temperature sensors, and group C temperature sensors are all connected to the status monitoring front end, and the temperature sensors work in a passive state.

Each set of temperature sensors includes a temperature measuring probe and is encapsulated by thermal conductive silicone grease; the temperature measuring probe is preferably a thermal resistance temperature sensor.

The status monitoring front end includes a temperature transmitter, a GPRS module, an MCU module, an inverter voltage stabilizing module, and an online power taking module; the signal input end of the temperature transmitter is connected to the temperature sensor, and the signal output end of the temperature transmitter is connected to the temperature sensor. The signal input terminal of the MCU module is connected, the signal output terminal of the MCU module is connected to the signal input terminal of the GPRS module; the electrical input terminal of the inverter voltage stabilizing module is connected to the online power taking module, and the electrical output terminal of the inverter voltage stabilizing module is connected to The electrical input terminals of the temperature transmitter, GPRS module, and MCU module are connected.

The working principle of the status monitoring front-end is: the temperature transmitter converts the weak signal output by the temperature probe into an analog signal and outputs it to the ADC port of the MCU module; the MCU module collects the ADC port temperature signal and uses software filtering to further eliminate external interference, and then transmits the signal to the GPRS module; the online power taking module converts the AC current in the cable into a voltage output of a certain power, and supplies power to the temperature transmitter, GPRS module, and MCU module through the inverter voltage stabilizing module.

The MCU module transmits monitoring data to the GPRS module in a period of time T _1. When GPRS receives the monitoring data, it also sends the monitoring data to the cloud server.

The T ₁ is preferably five minutes or ten minutes.

As shown in Figure 3, after the cloud server starts running, it first initializes the storage data and timer T, starts timing after receiving the first monitoring data, stores the received monitoring data, and transmits the monitoring data to Client terminal; stop storing when the time reaches T _2. At this time, the monitoring data stored inside the cloud server are respectively arrays W _A [n _a ], W _B [n _b ], and W _C [n _c ], where W represents the temperature. , the subscripts A, B, and C represent the three-phase data of A, B, and C in turn, and n _a , n _b , and n _c represent the number of temperature or electric field intensity data received by each phase in turn; after stopping the storage of monitoring data, the array Normalization processing, wavelet denoising interpolation transformation, Pearson similarity test, and abnormal phase identification are performed in sequence, and finally the abnormal fault phase identification results are obtained.

The T ₂ is preferably 12 hours or 24 hours.

Since there are three groups of temperature sensors, which are respectively installed on the surface of the A, B, and C phase cable joint flanges, it is impossible to ensure that their positions are completely consistent during actual installation, and that their initial values are consistent; therefore, in order to make the three sets of monitoring data comparable, It is necessary to eliminate the influence of data magnitude and dimension, that is, normalize the original data; the specific method of normalization is as follows:

In the formula, Wi _[ ] _min is the minimum value in the monitoring data array; _Wi [] _max is the maximum value in the monitoring data array, i represents A or B or C, and _Wi [t] is the internal storage of the cloud server. Data, t represents the sequence number.

The wavelet denoising interpolation transformation: In order to smooth the monitored data curve and filter out burrs caused by external environmental interference, the discrete wavelet (DWT) decomposition and reconstruction algorithm is used to decompose and reconstruct the array of monitoring data, filtering out High frequency components smooth the curve.

The specific methods of the wavelet denoising interpolation transformation include the following:

(1) Perform wavelet denoising on the normalized temperature monitoring data array of each phase to obtain the array after wavelet denoising;

(2) Perform interpolation transformation on the array obtained after wavelet denoising.

The wavelet denoising is performed on the normalized temperature monitoring data array of each phase. The specific method is as follows:

Taking the normalized phase A temperature monitoring data array as an example, use the DB wavelet basis as the wavelet function to decompose the array;

Decompose W' _A [t] (t=1,2,3...n _a ) on different scale metric spaces j through the DB wavelet basis, and obtain two coefficients A ₁ ( k) and D ₁ (k); let Φ _j,k (t) be the basis function, Φ _j-1,k (t) be the scale function after the first layer of decomposition, ω _j-1,k (t) be The first layer of decomposed wavelet function is:

where k is the position index, determined by the filter coefficient of the DB wavelet basis. After multi-layer decomposition of equation (2), the final scale function is obtained, and the wavelet component is removed, thereby retaining the main information of the monitoring data and filtering out the external Burrs caused by environmental interference;

The present invention adopts four levels of decomposition, as follows:

Then solve for the coefficient A ₄ (k). According to the MRA equation of the scale function, we have:

In the formula, h ₀ [n] is the low-pass filter coefficient, which is obtained from the basis function of the DB wavelet basis, and then it can be obtained:

A ₄ (k) can be obtained through the iterative calculation of the above equation, and then brought into equation (3), so that the A phase temperature result W” _A [n _a ] can be obtained after wavelet denoising and burr elimination of data;

In the same way, the phase B temperature result W” _B [n _b ] and the phase C temperature result W” _C [n _c ] are obtained.

The arrays W” _A [n _a ], W” _B [n _b ], and W” _C [n _c ] obtained after wavelet denoising have different array lengths. In order to achieve unification of data lengths and thus make them comparable, The data are interpolated by cubic spline interpolation method (spline) and unified to T ₂ /T ₁ data points.

The above-mentioned interpolation transformation is performed on the array obtained after wavelet denoising. The specific method is as follows: For example, the denoised A-phase temperature monitoring data array W" _A [n _a ], the number of data is n _a , then 1 T ₂ /T ₁ is evenly divided into n _a points, recorded as x _i , i=1,2,... _na , where x ₁ =1, x _na =T ₂ /T ₁ , each x _i corresponds to A corresponding numerical value W” _A [i], and then the cubic spline interpolation method is used to solve x _i -W” _A [n _a ]. The boundary conditions are:

Bringing i=0, 1...n _a -1 into the solution sequentially can obtain the spline function _Si (x), corresponding to [1,x ₂ ], [x ₂ ,x ₃ ]..., [x respectively _na-1 ,T ₂ /T ₁ ] There are a total of n _a -1 independent variable intervals. Then, x=1,2...T ₂ /T ₁ is brought into the spline function to obtain T ₂ /T ₁ Numerical values form W” _A [n], n=1,2...T ₂ /T ₁ ; similarly, W” _B [n] and W” _C [n], n=1,2.. are obtained. .T ₂ /T ₁ .

The specific method of the Pearson correlation test is as follows:

After unifying the data length, the arrays W” _A [n], W” _B [n], and W” _C [n] are obtained. Each data is divided into K segments. K is preferably 60, recorded as W” _Aj , W” _Bj , W” _Cj , j=1,2,3...,K, each segment has T ₂ /(T ₁ ·K) data points, and then use the Pearson correlation coefficient to perform a correlation test to identify abnormal phases.

Taking W” _A [n] and W” _B [n] as an example, the correlation test formula is:

In the formula, is the average value of each array sequence;

In the same way, r _j (W” _Aj ,W” _Cj ) and r _j (W” _Bj ,W” _Cj ) are obtained.

According to the above method, a pairwise correlation comparison of the temperature monitoring data of phases A, B, and C can be performed to identify abnormal phases. If the temperature change trend of a certain phase is obviously different and has no correlation with the other two phases, It may have a heating failure.

As shown in Figure 4, the specific method for identifying abnormal phases is: initialize the temperature abnormality weights ΔW _A , ΔW _B , _ΔWC of each phase, and after performing the data processing in the previous steps, calculate the Pearson value according to Equation (5) The correlation coefficients are r _j (W” _Aj ,W” _Bj ), r _j (W” _Aj ,W” _Cj ), r _j (W” _Bj ,W” _Cj ), j=1,2,3..., K, respectively, are recorded as r _AB [K], r _AC [K], r _BC [K];

Taking temperature anomaly identification as an example, compare the values of r _AB [i], r _AC [i], r _BC [i], where i = 1, 2, 3..., K; if in a certain group, r _AB [ i] is greater than 0.6, and the other two values r _AC [i] and r _BC [i] are both less than 0.2, then it is determined that the temperature data of the two phases A and B are related at this time, and the temperature data of the C phase is abnormal, so it is judged that the C phase is Abnormal phase, then the temperature anomaly weight ΔW _C of phase C is recalculated; and by analogy, the final calculation results of ΔW _A , ΔW _B , and ΔW _C can be obtained.

Comparing the final calculation results of ΔW _A , ΔW _B , and ΔW _C , if the temperature abnormality weight of one phase is significantly greater than the weight of the other two phases, which indicates that there may be a heating failure in this phase, the cloud server will send a prompt message to the client terminal; the cloud In addition to the above prompt information, the abnormal phase identification results sent by the server to the client terminal also include the historical abnormal temperature weight data of each phase. Based on this information, the user can comprehensively judge the heating situation of the cable terminal joint of the ring main unit and take corresponding actions. Maintenance measures should be taken. For example, when a phase continues to receive abnormal signals and the abnormal weight continues to be too high, you should go to the site to investigate the situation in time to eliminate the heating fault.

The invention provides an online monitoring system and method for heating faults of ring main unit cable terminal joints. On the one hand, it can accurately monitor the operating status characteristic parameters of the cable terminal joints in real time in a non-contact manner. On the other hand, it can identify degradation through background algorithms. After identifying the obvious abnormal state, it will be sent to the customer terminal in time to remind the operation and inspection personnel to carry out timely operation and maintenance; through non-contact real-time monitoring of the temperature signal at the characteristic position of the ring main unit cable room, the three-phase cable terminal can be accurately judged Whether there is an obvious abnormal phase in the joint, in order to achieve the purpose of promptly knowing the operating status of the cable terminal joint and timely troubleshooting the heating fault. The present invention provides an online monitoring system and method for heating fault of the cable terminal joint of the ring main unit, which makes up for the existing detection means. It can effectively monitor the operating status of the ring main unit cable room in real time, detect potential faults and defects in a timely manner, fill the gap in online monitoring technology for ring main unit cable terminal joints, and further ensure the safe and stable operation of the power distribution network within the jurisdiction.

Claims (4)

1. The on-line monitoring system for the heating fault of the cable terminal joint of the ring main unit is characterized by comprising a temperature sensor, a state monitoring front end, a cloud server and a client terminal; the temperature sensor is connected with the state monitoring front end, the state monitoring front end is in butt joint with the cloud server, and the cloud server is in butt joint with the client terminal;

the method for carrying out on-line monitoring by utilizing the on-line monitoring system for the heating fault of the cable terminal joint of the ring main unit comprises the following steps:

firstly, installing a temperature sensor at a three-phase cable terminal joint of a ring main unit cable chamber, and monitoring a temperature signal at the three-phase cable terminal joint through the temperature sensor;

the temperature sensor is connected with the state monitoring front end, and the temperature sensor transmits the monitored temperature signal to the state monitoring front end;

thirdly, the state monitoring front end amplifies and filters the temperature signal to form monitoring data, and the monitoring data are sent to the cloud server according to a set communication period;

fourthly, the cloud server stores the monitoring data, and performs data preprocessing, algorithm analysis and abnormal fault phase identification; the cloud server sends real-time monitoring data and abnormal fault identification results of each phase of cable terminal connectors to the client terminal;

fifthly, inquiring historical data and identifying results of abnormal phases of each phase of cable terminal joint of the ring main unit by a user through the client terminal, so that a heating fault condition is obtained;

after the cloud server starts to operate, initializing storage data and a timer, starting timing after receiving first monitoring data, storing the received monitoring data, and transmitting the monitoring data to a client terminal; when the time reaches T ₂ And then stopping storing, wherein the monitoring data stored in the cloud server are respectively set as an array W _A [n _a ]、W _B [n _b ]、W _C [n _c ]Wherein W represents temperature, subscript A, B, C in turn represents A, B, C three-phase data, n _a 、n _b 、n _c Sequentially representing the number of the temperature or electric field intensity data received each time; after stopping storing the monitoring data, sequentially carrying out normalization processing, wavelet denoising interpolation conversion, pearson similarity detection and abnormal phase identification on the groups, and finally obtaining an abnormal fault phase identification result;

the wavelet denoising interpolation conversion method specifically comprises the following steps:

(1) Carrying out wavelet denoising on the normalized temperature monitoring data arrays of each phase to obtain arrays subjected to wavelet denoising;

(2) Performing interpolation transformation on the array obtained after wavelet denoising;

the method for carrying out interpolation transformation on the array obtained after wavelet denoising comprises the following steps: a phase temperature monitoring data array W' after denoising " _A [n _a ]The number of data is n _a Will be 1 to T ₂ /T ₁ Is equally divided into n _a Points, denoted as x _i ，i＝1,2,...n _a Wherein x is ₁ ＝1，x _na ＝T ₂ /T ₁ Each x is _i Corresponding to a corresponding value W' _A [i]Then to x _i -W” _A [n _a ]Solving by a cubic spline interpolation method, wherein the boundary conditions are as follows:

i=0 1..n _a -1 bringing into sequential solving to obtain spline function S _i (x) Respectively correspond to [1, x ₂ ]、[x ₂ ,x ₃ ]...、[x _na-1 ,T ₂ /T ₁ ]Altogether n _a -1 argument interval, followed by x=1, 2..t ₂ /T ₁ Is carried into a spline function to obtain T ₂ /T ₁ Numerical value, form W' _A [n]，n＝1,2...T ₂ /T ₁ The method comprises the steps of carrying out a first treatment on the surface of the Similarly, W is obtained " _B [n]And W' _C [n]，n＝1,2...T ₂ /T ₁ ；

The pearson correlation test comprises the following specific steps:

in W' _A [n]、W” _B [n]For example, the correlation test formula is:

in the method, in the process of the invention,an average value of each segment of array sequence;

similarly, get r _j (W” _Aj ,W” _Cj )、r _j (W” _Bj ,W” _Cj )；

According to the method, the temperature monitoring data of A, B, C three phases are subjected to pairwise correlation comparison, abnormal phases are identified, and if a certain phase temperature change trend has obvious difference and is uncorrelated with other two phases, a heating fault exists;

the specific method for identifying the abnormal phase comprises the following steps: initializing a temperature anomaly weight ΔW for each phase _A 、ΔW _B 、ΔW _C After the data processing of the previous steps, the pearson correlation coefficient is obtained according to the formula (5) to obtain r _j (W” _Aj ,W” _Bj )、r _j (W” _Aj ,W” _Cj )、r _j (W” _Bj ,W” _Cj ) J=1, 2, 3..k, respectively denoted r _AB [K]，r _AC [K]，r _BC [K]；

Comparison r _AB [i]，r _AC [i]，r _BC [i]Values, wherein i=1, 2, 3..k; if in a certain group r _AB [i]Greater than 0.6, and two other values r _AC [i]、r _BC [i]If the temperature of the C phase is less than 0.2, the A, B two-phase temperature data are determined to be related, and the C phase temperature data are determined to be abnormal, so that the C phase is determined to be abnormal, and the temperature abnormality weight delta W of the C phase is determined _C Recalculating; and so on, to obtain DeltaW _A 、ΔW _B 、ΔW _C Is a final calculation result of (a);

comparison DeltaW _A 、ΔW _B 、ΔW _C If the abnormal temperature weight of one phase is obviously larger than the weights of other two phases, which indicates that the phase possibly has heating faults, the cloud server sends prompt information to the client terminal; the cloud server sends abnormal phase identification results to the client terminal, besides the prompt information, the cloud server also comprises temperature abnormal weight historical data of each phase, and a user comprehensively judges the heating condition of the cable terminal connector of the ring main unit according to the information, so that corresponding operation and maintenance measures are taken.

2. The on-line monitoring system for the heating fault of the cable terminal joint of the ring main unit according to claim 1, wherein the temperature sensor comprises A, B, C groups of temperature sensors, wherein the A group of temperature sensors, the B group of temperature sensors and the C group of temperature sensors are respectively and correspondingly fixed on the flange surface of the A, B, C three-phase cable terminal joint, and the A group of temperature sensors, the B group of temperature sensors and the C group of temperature sensors are all connected with the state monitoring front end; each group of temperature sensors comprises a temperature measuring probe and is packaged by heat conduction silicone grease;

the state monitoring front end comprises a temperature transmitter, a GPRS module, an MCU module, an inversion voltage stabilizing module and an online power taking module; the signal input end of the temperature transmitter is connected with the temperature sensor, the signal output end of the temperature transmitter is connected with the signal input end of the MCU module, and the signal output end of the MCU module is connected with the signal input end of the GPRS module; the electric input end of the inversion voltage stabilizing module is connected with the on-line power taking module, and the electric output end of the inversion voltage stabilizing module is respectively connected with the electric input ends of the temperature transmitter, the GPRS module and the MCU module;

the working principle of the state monitoring front end is as follows: the temperature transmitter converts the weak signal output by the temperature measuring probe into an analog signal and outputs the analog signal to an ADC port of the MCU module; the MCU module collects the temperature signals of the ADC port, eliminates external interference further by adopting a software filtering mode, and then transmits the signals to the GPRS module; the on-line power taking module converts alternating current in the cable into voltage output with certain power, and supplies power to the temperature transmitter, the GPRS module and the MCU module through the inversion voltage stabilizing module; the MCU module takes time T ₁ In order to periodically transmit the monitoring data to the GPRS module, the GPRS also transmits the monitoring data to the cloud server when receiving the monitoring data.

3. The on-line monitoring system for heating faults of the cable terminal connector of the ring main unit according to claim 1, wherein the normalization processing is carried out by the following specific method:

in which W is _i [] _min To monitor the minimum value in the data array; w (W) _i [] _max To monitor the maximum value in the data array, i represents A or B or C, W _i [t]And t represents a serial number for data stored in the cloud server.

4. The on-line monitoring system for heating faults of the cable terminal connector of the ring main unit according to claim 1, wherein the wavelet denoising is carried out on the normalized temperature monitoring data array of each phase, and the specific method is as follows:

taking the normalized A-phase temperature monitoring data array as an example, taking a DB wavelet base as a wavelet function, and decomposing the array;

will W' _A [t](t＝1,2,3...n _a ) Decomposing on different scale measurement spaces j through DB wavelet basis to obtain two coefficients A in the scale measurement space j-1 ₁ (k) And D ₁ (k) The method comprises the steps of carrying out a first treatment on the surface of the Setting phi _j,k (t) is a basis function, Φ _j-1,k (t) is the scale function after the first layer decomposition, ω _j-1,k (t) is a wavelet function after first layer decomposition, namely:

wherein k is a position index, determined by a filter coefficient of a DB wavelet base, performing multi-layer decomposition on the formula (2) to obtain a final scale function, removing wavelet components, thereby retaining main information of monitoring data and filtering burrs caused by external environment interference;

the invention adopts four layers of decomposition, and comprises the following steps:

then solve for the coefficient A ₄ (k) According to the MRA equation of the scale function, there are:

h in ₀ [n]Is a low-pass filter coefficient, which is derived from the basis function of the DB wavelet basis, which in turn yields:

obtaining A through the iterative calculation ₄ (k) Then is carried into the formula (3) to obtain the A phase temperature result W' of the data after the wavelet denoising and the burr elimination " _A [n _a ]；

And similarly, obtaining a B-phase temperature result W' _B [n _b ]And C-phase temperature results W' _C [n _c ]。