# Stating Diagnosis of Current State of Electric Furnace Transformer on the Basis of Analysis of Partial Discharges

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## Abstract

**:**

## 1. Introduction

## 2. Problem Statement

#### Characteristics of the Developed Monitoring System

- highest possible integration of all functions related to monitoring, control, and diagnosing the separate transformer subsystem into the single module;
- adding a module to or removing it from the system bears changes to functional capabilities of the system, but it does not have any impact on the capabilities of other modules;
- reconfiguring the operational algorithms of the entire monitoring system after changing the number of modules can be easily conducted through changing the configuration parameters;
- adding the new module to the system automatically connects it to the central monitoring module. Integration of data acquired from all the modules is conducted through the single digital and analog buses. Such a configuration allows for implementing the structure required for each object.

## 3. Materials and Methods

#### 3.1. Partial Discharges (PD) Occurrence in the Transformer Insulation

#### 3.2. Integral Properties of Partial Discharges

- Apparent Charge, Q
_{02}(nC), proportional to max pulse amplitude. The operating system was set so that the duration of a pulse would be no longer than 640 ns, while during the consequent 2560 ns, there should be no pulses with the amplitude higher than 30% of the initial pulse. In case these conditions are not met, the pulse is considered a distorting action and not registered. Pulses of partial discharges are considered to be regularly repeating if their frequency equals to 0.2 of the pulse value per power network period. When registering partial discharges using almost all known devices, the amplitude (pulse voltage, U_{02}(mV)) is measured. The apparent charge is found by the following formula: Q_{02}= 10∙U_{02}(in relative units), which simplifies system configuration. - Partial Discharge Power, in most cases presented in the form of PDI. This parameter characterizes the power and intensity of partial discharges, found by the following formula:$$\mathrm{P}\mathrm{D}\mathrm{I}=\frac{1}{\mathrm{T}}{\displaystyle \sum _{\mathrm{i}=1}^{\mathrm{m}}{\mathrm{Q}}_{\mathrm{i}}{\mathrm{U}}_{\mathrm{d}}}$$
_{d}—stands for the effective voltage.

_{02}and PDI definitely indicates insulation issues (destructive). 3–4-fold changes per observation year or 2-fold jump mean that the deficiency grows in the insulation [30].

- Worsened State: Q
_{02}> Q_{g1}= 2.5 nC, U_{02}> U_{g1}= 80 mV; PDI > PDI_{g1}= 60 mW; - Pre-Fault State: Q
_{02}> Q_{g2}= 5 nC, U_{02}> U_{g2}= 160 mV; PDI > PDI_{g2}= 80 mW.

_{02}and PDI for transformer phases. Such trends allow the rate of defect propagation to be obtained and, correspondingly, the extent of fault hazard. Continuous monitoring of the PD amplitude and capacity showed that their trends have a similar nature. The signal of amplitude of recurring pulses U

_{02}is read from a terminating resistor of PD sensors and due to this reduplicates the signal of the maximum measured charge Q

_{02}[29]. The presence of such discharges influences the PDI capacity.

## 4. Time-Series Data Processing Methods

#### 4.1. Elimination of Observation Errors

_{i}in the “problem” point from the average value of the total sample $\overline{\mathrm{x}}$ and the parameter τ

_{max}included in the Grubbs’ test [32]:

_{α,N-2}—table value of Student distribution.

- at ${\mathsf{\tau}}_{\mathrm{max}}<{\mathsf{\tau}}_{5\%},$—x
_{i}not eliminated; - at ${\mathsf{\tau}}_{\mathrm{max}}>{\mathsf{\tau}}_{0,1\%},\text{}$—x
_{i}eliminated; - at ${\mathsf{\tau}}_{5\%}\le {\mathsf{\tau}}_{\mathrm{max}}\le {\mathsf{\tau}}_{0,1\%},$—elimination x
_{i}by the user’s preference.

_{i}is eliminated otherwise the calculation is stopped.

#### 4.2. Distribution Law Checking

_{max}− x

_{min}[33]. To do this, one should obtain the ratio R/σ, and further it is compared with the critical upper RN and lower RL limits of this ratio at the set significance level. If R/σ < R

_{L}or R/σ > R

_{N}, the hypothesis on the normal distribution is rejected. Correspondingly, in case:

_{L}(N,α) and upper R

_{N}(N,α) limits are set as tabulated for all significance levels, 5% or 10%.

#### 4.3. Adjusting Time Series

_{t}.

_{t−p}, τ

_{t−p+1}, … τ

_{t+p}—time instants for the corresponding values in a row.

## 5. Practical Diagnosis of Furnace Transformer Technical State

#### 5.1. Detecting Transformer Insulation Issues with the Time Series of Partial Discharge Parameters

_{02}characterizes the partial discharge amplitude. However, as long as there exist the deficiencies that, while growing, lead to increase of the number of pulses with the same amplitude, PDI will be the parameter most sensitive to the deficiency growth.

_{02}and PDI—contain information about partial discharges, being mutually dependent. This is why, in point of issue, it is reasonable to evaluate the power of their relation, which can be measured through determination coefficients r

^{2}or the absolute value of the correlation coefficient r.

_{02}and PDI for the present phase can be used. With that, the technical state of the phase where this relation becomes stronger, must be focused on. The experience shows that the progression of destructive processes in this phase is more intense.

#### 5.2. Comparing Data before and after Repair

_{02}decreased by 2.5 times. Intensity and amplitude of partial discharges stay in tolerable values in all phases.

_{02}was higher than 80 mV, while power almost reached the pre-fault level in phase C—PDI >80 mW.

## 6. Result Discussion

#### 6.1. Analysis of Research Results

#### 6.2. Research Prospects

## 7. Conclusions

## Author Contributions

## Conflicts of Interest

## References

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**Figure 1.**Functional diagram of the furnace transformer state-monitoring system: TT—current transformer; DV—vibration sensor; Dt—temperature sensor; DD—pressure sensor; TSM—partial discharge sensor; DK—climate sensor.

**Figure 2.**Partial discharges (PD) distribution in the phases before transformer taking out for repair (

**a**) and after repair (

**b**).

**Figure 4.**Smoothed trends of repetitive pulse voltages (

**a**) and partial discharge intensity (PDI) (

**b**) in phases of high-voltage inputs before repair: 1—Phase A; 2—Phase C; 3—Phase C.

**Figure 5.**Dependency of PDI on partial discharge amplitude and parameters of trend lines in phases A (

**a**), B (

**b**) and C (

**c**).

**Figure 6.**Trends similar to the dependences shown in Figure 5, after repair.

**Figure 7.**Input and smoothed trends of power and amplitude of partial discharges from 9 September to 22 December 2016: (

**a**)—Phase A; (

**b**)—Phase B; (

**c**)—Phase C.

Type | Rated Capacity, kVA | Rated Coil Voltage, V | Diagram and Group of Coil Connection | Number of OLTC Positions | Cooling System | Mass, Tons | Length × Width × Height, mm |
---|---|---|---|---|---|---|---|

ETCNKV -40000/110-UHL-4 | 20,282–26,000 | 110,000 HV 289.5–421 LV | Y/Δ-11 | 9 | Suspended | 80 | 4840 × 3540 × 6200 |

Measurement Conditions | Phase | Capacity, mW | Amplitude, V | Number of Pulses |
---|---|---|---|---|

Before repair (Figure 2a) | A | 18 | 0.045 | 1654 |

B | 10 | 0.128 | 1106 | |

C | 189 | 0.12 | 15,186 | |

After repair (Figure 2b) | A | 0 | 0 | 0 |

B | 33 | 0.054 | 5219 | |

C | 17 | 0.019 | 3130 |

Classification in Compliance with [31] | Classification of Technical State | Extent of Defect Propagation in Compliance with [31] | Values of Maximum PD Amplitudes, Ampere-Second | ||
---|---|---|---|---|---|

In Windings and between Coils | Main Insulation, Barriers, in Compliance with [31] | Inputs in Compliance with [31] | |||

Faulty state | PRE-FAULT | Limit state | more than 5 nC | more than 100 nC | more than 10 nC |

WORSENED | Critical defect | to 2.5 nC | 5–25 nC | 0.5–2.5 nC | |

NORM with significant deviations | Significant defect | to 500 pC | 1–5 nC | to 500 pC | |

Operating state | NORM with deviations | Minor defect | to 100 pC | to 1000 pC | to 100 pC |

NORM | Absence of obvious defects | – | to 100 pC | – |

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## Share and Cite

**MDPI and ACS Style**

Karandaeva, O.I.; Yakimov, I.A.; Filimonova, A.A.; Gartlib, E.A.; Yachikov, I.M. Stating Diagnosis of Current State of Electric Furnace Transformer on the Basis of Analysis of Partial Discharges. *Machines* **2019**, *7*, 77.
https://doi.org/10.3390/machines7040077

**AMA Style**

Karandaeva OI, Yakimov IA, Filimonova AA, Gartlib EA, Yachikov IM. Stating Diagnosis of Current State of Electric Furnace Transformer on the Basis of Analysis of Partial Discharges. *Machines*. 2019; 7(4):77.
https://doi.org/10.3390/machines7040077

**Chicago/Turabian Style**

Karandaeva, Olga I., Ivan A. Yakimov, Alexandra A. Filimonova, Ekaterina A. Gartlib, and Igor M. Yachikov. 2019. "Stating Diagnosis of Current State of Electric Furnace Transformer on the Basis of Analysis of Partial Discharges" *Machines* 7, no. 4: 77.
https://doi.org/10.3390/machines7040077